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Advances in Intelligent Systems and Computing 448
Shahram Latifi Editor
Information
Technology:
New
Generations
13th International Conference
on InformationTechnology
Advances in Intelligent Systems
and Computing
Volume 448
Series editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
e-mail: kacprzyk@ibspan.waw.pl
About this Series
The series “Advances in Intelligent Systems and Computing” contains publications on
theory, applications, and design methods of Intelligent Systems and Intelligent Computing.
Virtually all disciplines such as engineering, natural sciences, computer and information
science, ICT, economics, business, e-commerce, environment, healthcare, life science are
covered. The list of topics spans all the areas of modern intelligent systems and computing.
The publications within “Advances in Intelligent Systems and Computing” are primarily
textbooks and proceedings of important conferences, symposia and congresses. They cover
significant recent developments in the field, both of a foundational and applicable character.
An important characteristic feature of the series is the short publication time and world-wide
distribution. This permits a rapid and broad dissemination of research results.
Advisory Board
Chairman
Nikhil R. Pal, Indian Statistical Institute, Kolkata, India
e-mail: nikhil@isical.ac.in
Members
Rafael Bello, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Cuba
e-mail: rbellop@uclv.edu.cu
Emilio S. Corchado, University of Salamanca, Salamanca, Spain
e-mail: escorchado@usal.es
Hani Hagras, University of Essex, Colchester, UK
e-mail: hani@essex.ac.uk
László T. Kóczy, Széchenyi István University, Győr, Hungary
e-mail: koczy@sze.hu
Vladik Kreinovich, University of Texas at El Paso, El Paso, USA
e-mail: vladik@utep.edu
Chin-Teng Lin, National Chiao Tung University, Hsinchu, Taiwan
e-mail: ctlin@mail.nctu.edu.tw
Jie Lu, University of Technology, Sydney, Australia
e-mail: Jie.Lu@uts.edu.au
Patricia Melin, Tijuana Institute of Technology, Tijuana, Mexico
e-mail: epmelin@hafsamx.org
Nadia Nedjah, State University of Rio de Janeiro, Rio de Janeiro, Brazil
e-mail: nadia@eng.uerj.br
Ngoc Thanh Nguyen, Wroclaw University of Technology, Wroclaw, Poland
e-mail: Ngoc-Thanh.Nguyen@pwr.edu.pl
Jun Wang, The Chinese University of Hong Kong, Shatin, Hong Kong
e-mail: jwang@mae.cuhk.edu.hk
More information about this series at http://www.springer.com/series/11156
Shahram Latifi
Editor
Information Technology:
New
Generations
13th International Conference
on Information Technology
123
Editor
Shahram Latifi
PHASE
Las Vegas, NV
USA
ISSN 2194-5357 ISSN 2194-5365 (electronic)
Advances in Intelligent Systems and Computing
ISBN 978-3-319-32466-1 ISBN 978-3-319-32467-8 (eBook)
DOI 10.1007/978-3-319-32467-8
Library of Congress Control Number: 2016935571
© Springer International Publishing Switzerland 2016
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part
of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,
recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission
or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar
methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publication does not imply, even in the absence of a specific statement, that such names are exempt from
the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the
authors or the editors give a warranty, express or implied, with respect to the material contained herein or
for any errors or omissions that may have been made.
Printed on acid-free paper
This Springer imprint is published by Springer Nature
The registered company is Springer International Publishing AG Switzerland
Preface
Welcome to the 13th
International Conference on Information Technology- New
Generations- ITNG 2016. It is a pleasure to report that we have another successful
year for the ITNG 2016. Gaining popularity and recognition in the IT community
around the globe, the conference was able to attract many papers from authors
worldwide. The papers were reviewed for their technical soundness, originality,
clarity and relevance to the conference. The conference enjoyed expert opinion of
89 author and non-author scientists who participated in the review process. Each
paper was reviewed by at least two independent reviewers. A total of 96 articles
were accepted as regular papers and 14 were accepted as short papers (posters). The
overall acceptance rate was 35 %.
The articles in this proceeding address the most recent advances in such areas as
Wireless Communications and Networking, Software Engineering, Information
Security, Data Mining, Informatics, Wavelets, High Performance Computing
Architectures, Internet, and Computer Vision.
As customary, the conference features two keynote speakers on Monday and
Tuesday. The presentations for Monday and Tuesday are organized in 2 meeting
rooms simultaneously, covering a total of 16 technical sessions. Poster presenta-
tions are scheduled for the morning and afternoon of these days. The award cere-
mony, conference reception and dinner are scheduled for Tuesday evening. Two
parallel sessions have been organized for Wednesday.
Many people contributed to the success of this year’s conference by organizing
symposia or technical tracks for the ITNG. Dr. Yenumula Reddy deserves much
credit for spearheading the review process and running a symposium on Wireless
Communications and Networking. My sincere thanks go to other symposium and
major track organizers and associate editors namely- Drs. Kohei Arai, Alessio
Bucaioni, Glauco Carneiro, Narayan Debnath, Luiz Alberto Vieira Dias, Ray
Hashemi, Teruya Minamoto, Kashif Saleem, Basit Shahzad, Christoph Thuemmler,
and Fangyan Shen.
v
Others who were responsible for solicitation, review and handling the papers
submitted to their respective sessions include Drs Azita Bahrami, Doina Bein,
Wolfgang Bein, Federico Ciccozzi, Saad Mubeen, Armin Schneider and Mei Yang.
The help and support of the Springer in preparing the ITNG proceedings is
specially appreciated. Many thanks are due to Michael Luby, the Senior Editor and
Nicole Lowary, the Assistant Editor of the Springer supervisor of Publications for
the timely handling of our publication order. Finally, the great efforts of the con-
ference secretary, Ms. Mary Roberts who dealt with the day to day conference
affairs, including timely handling volumes of emails, are acknowledged.
The conference venue remains the same as last year- the Flamingo Hotel as the
conference. The hotel, conveniently located in the heart of Las Vegas Strip, pro-
vides an easy access to other major resorts and recreational centers.
I hope and trust that you have an academically and socially fulfilling stay in Las
Vegas.
April 2016 Shahram Latifi
The ITNG General Chair
vi Preface
ITNG 2016 Organization
Editor and General Chair
Shahram Latifi University of Nevada, Las Vegas, USA
Associate Editors
Kohei Arai Saga University, Japan
Glauco Carneiro University of Salvador, Brazil
Narayan Debnath Winona State University, USA
Luiz Alberto Vieira Dias Instituto Tecnológico de Aeronáutica, Brazil
Ray Hashemi Armstrong State University, USA
Yenumula Reddy Grambling State University, USA
Track Organizers
Kohei Arai Saga University, Japan
Alessio Bucaioni Mälardalen University, Sweden
Glauco Carneiro University of Salvador, Brazil
Narayan Debnath Winona State University, USA
Luiz Alberto Vieira Dias ITA, Brazil
Ray Hashemi Armstrong State University, USA
Teruya Minamoto Saga University, Japan
Kashif Saleem King Saud University, Saudi Arabia
Basit Shahzad King Saud University, Saudi Arabia
Yenumula Reddy Grambling State University, USA
Christoph Thuemmler Edinburgh Napier University, UK
Fangyan Shen New York City College of Technology, USA
Session Chairs
Azita Bahrami IT Consultation, USA
Doina Bein California State University, USA
Wolfgang Bein University of Nevada, USA
Federico Ciccozzi Mälardalen University, Sweden
Saad Mubeen Mälardalen University, Saudi Arabia
Armin Schneider Technical University Munich, Germany
Mei Yang University of Nevada, Las Vegas, USA
vii
Publicity Chair
Basit Shahzad King Saud University, Saudi Arabia
Conference Secretary
Mary Roberts PHASE Inc., USA
Reviewers
Abbas, Haider
Ahmed, Adel
Ahmed, Iqbal
Al-Muhtadi, Jalal
Arai, Kohei
Araujo, Marco Antonio
Ashino, Ryuichi
Autili, Marco
Awan, Fahim
Baguda, Yakubu
Barina, David
Behnam, Moris
Braga, Regina
Brito e Abreu, Fernando
Caetano, Paulo
Camargo, Valter
Campos, Fernanda
Carlson, Jan
Carneiro, Glauco
Carreiro, Bruno
Challah, Yacine
Chaudhry, Imran
Christos, Kalloniatis
Cicchetti, Antonio
Clincy, Victor
Colaco Jr., Methanias
Costa, Heitor
Crespo, Yania
Dai, Qing
David, Jose Maria
Delamaro, Marcio Eduardo
Derhab, Abdelouahid
Dias, Luiz
Eldefrawy, H.
Eramo, Romina
Fabbri, Sandra
Fernandes, Joao M.
Figueiredo, Eduardo
Frederic, Jean
Fujinoki, Kensuke
Garcia, Rogerio
Garcia-Valls, Marisol
Gawanmeh, Amjad
Hashemi, Ray
Huang, Yingsong
Ji, Yanqing
Kimura, Takuma
Kinoshita, Takehiko
Liebel, Grischa
Maia, Marcelo
Malavolta, Ivano
Marques, Johnny
Meghanathan, Natarajan
Mesit, Jaruwan
Mialaret, Lineu
Minamoto, Teruya
Mirza, Abdulrahman
Monteiro, Miguel
Montini, Denis
Morimoto, Akira
Munson, Ethan V
Novais, Renato
viii ITNG 2016 Organization
Oliveira, Toacy
Orgun, Mehmet
Pathan, Al-Sakib
Paulin, Alois
Pontin, Renata
Reddy, Yenumula
Rehmani, Mubashir
Rodrigues, Joel
Rossi, Gustavo
Saito, Norikazu
Saleem, Kashif
Saleem, Kashif
Sampaio, Paulo
Sarijari, Adib
Satyanarayana, Ashwin
Schneider, Armin
Shahzad, Basit
Shen, Fangyang
Soares, Michel
Solari, Martin
Sreekumari, Prasanthi
Suzana, Rita
Takano, Shigeru
Thuemmler, Christoph
Tolle, Herman
Tsuchiya, Takuya
Watanabe, Yoshitaka
ITNG 2016 Organization ix
Contents
Networking and Wireless Communications
Understanding User’s Acceptance of Personal Cloud Computing:
Using the Technology Acceptance Model . . . . . . . . . . . . . . . . . . . . . . . 3
Mohamed Eltayeb and Maurice Dawson
Cognitive Spectrum Decision via Machine Learning in CRN. . . . . . . . . 13
A. M. Koushik, Fei Hu, Ji Qi and Sunil Kumar
Elastic Edge-Overlay Methods Using OpenFlow for Cloud Networks . . . 25
Amer Aljaedi, C. Edward Chow and Jia Rao
An Approach to Generate Automatic Variable Key to Assure Perfect
Security in Cryptosystem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Subhasish Banerjee, Manash P. Dutta and C. T. Bhunia
Airborne Networks with Multi-beam Smart Antennas:
Towards a QOS-Supported, Mobility-Predictive MAC . . . . . . . . . . . . . 47
Xin Li, Fei Hu, Lei Hu and Sunil Kumar
CR Based Video Communication Testbed with Robust Spectrum
Sensing / Handoff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Ji Qi, Fei Hu, Xin Li, A. M. Koushik, Lei Hu and Sunil Kumar
A Control-Message Quenching Algorithm in Openflow-Based Wireless
Mesh Networks with Dynamic Spectrum Access . . . . . . . . . . . . . . . . . . 71
Xin Li, Xiaoyan Hong, Yu Lu, Fei Hu, Ke Bao and Sunil Kumar
SINR Maximization in Relay-Assisted Multi-user Wireless Networks . . . 83
Umar Rashid, Faheem Gohar Awan and Muhammad Kamran
A Hybrid MAC for Long-Distance Mesh Network with Multi-beam
Antennas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Xin Li, Fei Hu, Ji Qi and Sunil Kumar
xi
Future Approach to Find Business Model Orientation for
Technological Businesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Sepehr Ghazinoory, Fatemeh Saghafi, Maryam Mirzaei,
Mohammadali Baradaran Ghahfarokhi and Parvin Baradaran Ghahfarokhi
Social Media Coverage of Public Health Issues in China:
A Content Analysis of Weibo News Posts . . . . . . . . . . . . . . . . . . . . . . . 111
Jiayin Pei, Guang Yu and Peng Shan
Advertisement Through the Most Popular Twitter Users Based
on Followers in Saudi Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
Abeer A. AlSanad and Abdulrahman A. Mirza
Sentiment Analysis for Arabic Reviews in Social Networks Using
Machine Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Mustafa Hammad and Mouhammd Al-awadi
Security and Privacy in Next Generation Networks
An Interactive Model for Creating Awareness and Consequences
of Cyber-crime in People with Limited Technology Skills . . . . . . . . . . . 143
Sheeraz Akram, Muhammad Ramzan, Muhammad Haneef
and Muhammad Ishtiaq
Power Analysis Attack and Its Countermeasure for a Lightweight
Block Cipher Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Masaya Yoshikawa and Yusuke Nozaki
Perpetuating Biometrics for Authentication: Introducing the Durable
True-Neighbor Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Fawaz E. Alsaadi and Terrance E. Boult
Certificate-Based IP Multimedia Subsystem Authentication and Key
Agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Wei-Kuo Chiang and Ping-Chun Lin
Software Optimizations of NTRUEncrypt for Modern Processor
Architectures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
Shay Gueron and Fabian Schlieker
Vulnerabilities and Mitigation Methods in the NextGen Air Traffic
Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
Sachiko Sueki and Yoohwan Kim
Pushing the Limits of Cyber Threat Intelligence: Extending STIX
to Support Complex Patterns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
Martin Ussath, David Jaeger, Feng Cheng and Christoph Meinel
xii Contents
Analyzing Packet Forwarding Schemes for Selfish Behavior
in MANETs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Asad Raza, Jamal Nazzal Al-Karaki and Haider Abbas
Speed Records for Multi-Prime RSA Using AVX2 Architectures . . . . . . 237
Shay Gueron and Vlad Krasnov
Privacy Preservation of Source Location Using Phantom Nodes . . . . . . 247
Shruti Gupta, Prabhat Kumar, J.P. Singh and M.P. Singh
Implementing a Bitcoin Exchange with Enhanced Security . . . . . . . . . . 257
Ebru Celikel Cankaya and Luke Daniel Carr
Information Systems and Internet Technology
REST-Based Semantic Annotation of Web Services . . . . . . . . . . . . . . . 269
Cleber Lira and Paulo Caetano
Synthetical QoE-Driven Anomalous Cell Pattern Detection with a
Hybrid Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
Dandan Miao, Weijian Sun, Xiaowei Qin and Weidong Wang
A Mobile Group Tour Tracking and Gathering System . . . . . . . . . . . . 293
Chyi-Ren Dow, Yu-Yun Chang, Chiao-Wen Chen and Po-Yu Lai
Model Based Evaluation of Cybersecurity Implementations. . . . . . . . . . 303
Aristides Dasso, Ana Funes, Germán Montejano, Daniel Riesco,
Roberto Uzal and Narayan Debnath
Accelerating the Critical Line Algorithm for Portfolio Optimization
Using GPUs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
Raja H. Singh, Lee Barford and Frederick Harris Jr.
Maximum Clique Solver Using Bitsets on GPUs . . . . . . . . . . . . . . . . . . 327
Matthew VanCompernolle, Lee Barford and Frederick Harris Jr.
CUDA Implementation of Computer Go Game Tree Search . . . . . . . . . 339
Christine Johnson, Lee Barford, Sergiu M. Dascalu
and Frederick C. Harris Jr.
Negotiation and Collaboration Protocol Based on EbXML Intended
to Optimize Port Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
Vinícius Eduardo Ferreira dos Santos Silva, Nunzio Marco Torrisi
and Rodrigo Palucci Pantoni
Reversible Data Hiding Scheme Using the Difference Between the
Maximum and Minimum Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365
Pyung-Han Kim, Kwang-Yeol Jung, In-Soo Lee and Kee-Young Yoo
Contents xiii
The Design, Data Flow Architecture, and Methodologies for a Newly
Researched Comprehensive Hybrid Model for the Detection of DDoS
Attacks on Cloud Computing Environment . . . . . . . . . . . . . . . . . . . . . 377
Anteneh Girma, Kobi Abayomi and Moses Garuba
Educational Gaming: Improved Integration Using Standard Gaming
Genres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
Ben Brown and Sergiu Dascalu
Designing a Web-Based Graphical Interface for Virtual Machine
Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401
Harinivesh Donepudi, Bindu Bhavineni and Michael Galloway
Towards Providing Resource Management in a Local IaaS Cloud
Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413
Travis Brummett and Michael Galloway
Integration of Assistive Technologies into 3D Simulations:
An Exploratory Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425
Angela T. Chan, Alexander Gamino, Frederick C. Harris Jr.
and Sergiu Dascalu
Data Profiling Technology of Data Governance Regarding Big Data:
Review and Rethinking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439
Wei Dai, Isaac Wardlaw, Yu Cui, Kashif Mehdi, Yanyan Li and Jun Long
Understanding the Service Model of Mobile Social Network in Live 4G
Network: A Case Study of WeChat Moments. . . . . . . . . . . . . . . . . . . . 451
Weijian Sun, Dandan Miao, Xiaowei Qin and Guo Wei
Applying Scrum in an Interdisciplinary Project for Fraud Detection in
Credit Card Transactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461
Mayara Valeria Morais dos Santos, Paulo Diego Barbosa da Silva,
Andre Gomes Lamas Otero, Ramiro Tadeu Wisnieski,
Gildarcio Sousa Goncalves, Rene Esteves Maria, Luiz Alberto Vieira Dias
and Adilson Marques da Cunha
The Visual Representation of Numerical Solution for a Non-stationary
Deformation in a Solid Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473
Zhanar Akhmetova, Seilkhan Boranbayev and Serik Zhuzbayev
Software Engineering
Developing Usability Heuristics for Grid Computing Applications:
Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485
Daniela Quiñones, Cristian Rusu, Silvana Roncagliolo, Virginica Rusu
and César A. Collazos
xiv Contents
Refining Timing Requirements in Extended Models of Legacy
Vehicular Embedded Systems Using Early End-to-end Timing
Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497
Saad Mubeen, Thomas Nolte, John Lundbäck, Mattias Gålnander
and Kurt-Lennart Lundbäck
Integrated Metrics Handling in Open Source Software Quality
Management Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509
Julio Escribano-Barreno, Javier García-Muñoz and Marisol García-Valls
Supporting the Development of User-Driven Service Composition
Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519
Alex Roberto Guido, Antonio Francisco do Prado,
Wanderley Lopes de Souza and Eduardo Gonçalves da Silva
Mining Source Code Clones in a Corporate Environment . . . . . . . . . . . 531
Jose J. Torres, Methanias C. Junior and Francisco R. Santos
Fuzzy Resource-Constrained Time Workflow Nets . . . . . . . . . . . . . . . . 543
Joslaine Cristina Jeske de Freitas and Stéphane Julia
Performance Indicators Analysis in Software Processes
Using Semi-supervised Learning with Information Visualization . . . . . . 555
Leandro Bodo, Hilda Carvalho de Oliveira, Fabricio Aparecido Breve
and Danilo Medeiros Eler
Techniques for the Identification of Crosscutting Concerns:
A Systematic Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569
Ingrid Marçal, Rogério Eduardo Garcia, Danilo Medeiros Eler,
Celso Olivete Junior and Ronaldo C.M. Correia
ValiPar Service: Structural Testing of Concurrent Programs as a Web
Service Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581
Rafael R. Prado, Paulo S.L. Souza, Simone R.S. Souza,
George G.M. Dourado and Raphael N. Batista
A Model-Driven Solution for Automatic Software Deployment
in the Cloud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591
Franklin Magalhães Ribeiro Jr., Tarcísio da Rocha, Joanna C.S. Santos
and Edward David Moreno
Software Process Improvement in Small and Medium Enterprises:
A Systematic Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603
Gledston Carneiro da Silva and Glauco de Figueiredo Carneiro
Investigating Reputation in Collaborative Software Maintenance:
A Study Based on Systematic Mapping . . . . . . . . . . . . . . . . . . . . . . . . 615
Cláudio Augusto S. Lélis, Marco Antônio P. Araújo, José Maria N. David
and Glauco de F. Carneiro
Contents xv
A 2-Layer Component-Based Architecture for Heterogeneous
CPU-GPU Embedded Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629
Gabriel Campeanu and Mehrdad Saadatmand
High-Performance Computing Architectures
Block-Based Approach to 2-D Wavelet Transform on GPUs . . . . . . . . . 643
Michal Kula, David Barina and Pavel Zemcik
Deriving CGM Based-Parallel Algorithms for the Optimal Binary
Search-Tree Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 655
Vianney Kengne Tchendji, Jean Frédéric Myoupo and Gilles Dequen
Experimental Evaluations of MapReduce in Biomedical
Text Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665
Yanqing Ji, Yun Tian, Fangyang Shen and John Tran
Algorithmic Approaches for a Dependable Smart Grid. . . . . . . . . . . . . 677
Wolfgang Bein, Bharat B. Madan, Doina Bein and Dara Nyknahad
Performance Evaluation of Data Migration Methods Between the Host
and the Device in CUDA-Based Programming . . . . . . . . . . . . . . . . . . . 689
Rafael Silva Santos, Danilo Medeiros Eler and Rogério Eduardo Garcia
Design of a Deadlock-Free XY-YX Router for Network-on-Chip . . . . . . 701
Sang Muk Lee, Eun Nu Ri Ko, Young Seob Jeong and Seung Eun Lee
An FPGA Based Compression Accelerator for Forex
Trading System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 711
Ji Hoon Jang, Seong Mo Lee, Oh Seong Gwon and Seung Eun Lee
Agile Software Testing and Development
An Academic Case Study Using Scrum . . . . . . . . . . . . . . . . . . . . . . . . 723
Luciana Rinaldi Fogaça, Luiz Alberto Vieira Dias
and Adilson Marques da Cunha
Distributed Systems Performance for Big Data. . . . . . . . . . . . . . . . . . . 733
Marcelo Paiva Ramos, Paulo Marcelo Tasinaffo,
Eugenio Sper de Almeida, Luis Marcelo Achite,
Adilson Marques da Cunha and Luiz Alberto Vieira Dias
Towards Earlier Fault Detection by Value-Driven Prioritization
of Test Cases Using Fuzzy TOPSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . 745
Sahar Tahvili, Wasif Afzal, Mehrdad Saadatmand, Markus Bohlin,
Daniel Sundmark and Stig Larsson
xvi Contents
Model-Driven Engineering for Cyber-Physical Systems
Experimenting with a Load-Aware Communication Middleware
for CPS Domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 763
Luis Cappa-Banda and Marisol García-Valls
Adaptive Message Restructuring Using Model-Driven Engineering . . . . 773
Hang Yin, Federico Giaimo, Hugo Andrade, Christian Berger
and Ivica Crnkovic
Towards Modular Language Design Using Language Fragments:
The Hybrid Systems Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 785
Sadaf Mustafiz, Bruno Barroca, Claudio Gomes and Hans Vangheluwe
Data Mining
Data Clustering Using Improved Fire Fly Algorithm . . . . . . . . . . . . . . 801
Mehdi Sadeghzadeh
Intelligent Mobile App for You-Tube Video Selection . . . . . . . . . . . . . . 811
Mark Smith
An Application of GEP Algorithm for Prime Time Detection in Online
Social Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 821
Hsiao-Wei Hu, Wen-Shiu Lin and I-Hsun Chen
Transport Logistic Application: Train’s Adherence Evolution
and Prediction Based on Decision Tree and Markov Models . . . . . . . . . 833
Steve Ataky T. Mpinda, Marilde T.P. Santos and Marcela X. Ribeiro
A Method for Match Key Blocking in Probabilistic Matching:
(Research-in-Progress). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847
Pei Wang, Daniel Pullen, John R. Talburt and Cheng Chen
Accuracy Assessment on Prediction Models for Fetal Weight Based
on Maternal Fundal Height: Applications in Indonesia . . . . . . . . . . . . . 859
Dewi Anggraini, Mali Abdollahian and Kaye Marion
Ensemble Noise Filtering for Streaming Data Using Poisson Bootstrap
Model Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 869
Ashwin Satyanarayana and Rosemary Chinchilla
Mining Persistent and Dynamic Spatio-Temporal Change in Global
Climate Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 881
Jie Lian and Michael P. McGuire
Open Source Data Quality Tools: Revisited . . . . . . . . . . . . . . . . . . . . . 893
Venkata Sai Venkatesh Pulla, Cihan Varol and Murat Al
Contents xvii
New Trends in Wavelet and Numerical Analysis
Some Outflow Boundary Conditions for the Navier-Stokes
Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905
Yoshiki Sugitani, Guanyu Zhou and Norikazu Saito
Successive Projection with B-spline . . . . . . . . . . . . . . . . . . . . . . . . . . . 917
Yuki Ueda and Norikazu Saito
Computer-Aided Diagnosis Method for Detecting Early Esophageal
Cancer from Endoscopic Image by Using Dyadic Wavelet Transform
and Fractal Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 929
Ryuji Ohura, Hajime Omura, Yasuhisa Sakata and Teruya Minamoto
Daubechies Wavelet-Based Method for Early Esophageal Cancer
Detection from Flexible Spectral Imaging Color Enhancement Image . . . 939
Hiroki Matsunaga, Hajime Omura, Ryuji Ohura and Teruya Minamoto
A Refined Method for Estimating the Global Hölder Exponent . . . . . . . 949
S. Nicolay and D. Kreit
A New Wavelet-Based Mode Decomposition for Oscillating Signals
and Comparison with the Empirical Mode Decomposition . . . . . . . . . . 959
Adrien Deliège and Samuel Nicolay
Computer Vision, HCI and Image Processing/Analysis
Short Boundary Detection Using Spatial-Temporal Features . . . . . . . . . 971
Muhammad Ali and Awais Adnan
A Set of Usability Heuristics and Design Recommendations
for u-Learning Applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 983
Fabiola Sanz, Raúl Galvez, Cristian Rusu, Silvana Roncagliolo,
Virginica Rusu, César A. Collazos, Juan Pablo Cofré, Aníbal Campos
and Daniela Quiñones
Computer Input just by Sight and Its Applications in Particular
for Disable Persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995
Kohei Arai
User Impressions About Distinct Approaches to Layout Design
of Personalized Content. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1009
Anelise Schunk, Francine Bergmann, Ricardo Piccoli, Angelina Ziesemer,
Isabel Manssour, João Oliveira and Milene Silveira
Video Compression Using Variable Block Size Motion Compensation
with Selective Subpixel Accuracy in Redundant Wavelet Transform . . . 1021
Ahmed Suliman and Robert Li
xviii Contents
PPMark: An Architecture to Generate Privacy Labels Using TF-IDF
Techniques and the Rabin Karp Algorithm . . . . . . . . . . . . . . . . . . . . . 1029
Diego Roberto Gonçalves de Pontes and Sergio Donizetti Zorzo
RGB and Hue Color in Pornography Detection . . . . . . . . . . . . . . . . . . 1041
Awais Adnan and Muhammad Nawaz
Potpourri
Sociology Study Using Email Data and Social Network Analysis . . . . . . 1053
Wajid Rafiq, Shoab Ahmed Khan and Muhammad Sohail
Evaluation of Usability Heuristics for Transactional Web Sites:
A Comparative Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1063
Freddy Paz, Freddy A. Paz and José Antonio Pow-Sang
Algorithm for Gaussian Integer Exponentiation . . . . . . . . . . . . . . . . . . 1075
Aleksey Koval
Dynamic Simulation of the Flight Behavior of a Rotary-Wing
Aircraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1087
Sebastião Simões Cunha Jr., Marcelo Santiago de Sousa,
Danilo Pereira Roque, Alexandre Carlos Brandão Ramos
and Pedro Fernandes Jr.
Origami Guru: An Augmented Reality Application to Assist
Paper Folding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1101
Nuwee Wiwatwattana, Chayangkul Laphom, Sarocha Aggaitchaya
and Sudarat Chattanon
Augmented Reality Approach for Knowledge Visualization and
Production (ARAKVP) in Educational and Academic Management
System for Courses Based on Active Learning Methodologies
(EAMS–CBALM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1113
Helen de Freitas Santos, Wanderley Lopes de Souza,
Antonio Francisco do Prado and Sissi Marilia dos Santos Forghieri Pereira
Designing Schedulers for Hard Real-Time Tasks . . . . . . . . . . . . . . . . . 1125
Vasudevan Janarthanan
An Autonomous Stair Climbing Algorithm with EZ-Robots . . . . . . . . . 1135
Jason Moix, Sheikh Faal, M. K. Shamburger, Chris Carney,
Alex Williams, Zixin Ye and Yu Sun
Toward Indoor Autonomous Flight Using a Multi-rotor Vehicle . . . . . . 1145
Connor Brooks, Christopher Goulet and Michael Galloway
Contents xix
Using Tweets for Rainfall Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . 1157
Luiz Eduardo Guarino de Vasconcelos, Eder C.M. dos Santos,
Mário L.F. Neto, Nelson Jesuz Ferreira
and Leandro Guarino de Vasconcelos
Algorithms Performance Evaluation in Hybrid Systems . . . . . . . . . . . . 1169
Rafael Manochio, David Buzatto, Paulo Muniz de Ávila
and Rodrigo Palucci Pantoni
An Efficient Method for the Open-Shop Scheduling Problem
Using Simulated Annealing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183
Haidar M. Harmanani and Steve Bou Ghosn
Schematizing Heidegger. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1195
Sabah Al-Fedaghi
Constrained Triangulation of 2D Shapes . . . . . . . . . . . . . . . . . . . . . . . 1209
Laxmi P Gewali and Roshan Gyawali
Software Project and Analysis of a Training Screen Based System
for Healthcare Professionals Working in the NICU in Brazil. . . . . . . . . 1219
Daniel Rocha Gualberto, Renata Aparecida Ribeiro Custódio,
Alessandro Rodrigo Pereira Dias, Gabriel Bueno da Silva,
Clarissa Gonçalves Eboli and Alexandre Carlos Brandão Ramos
Short Papers
A Self-Configuration Web-API for the Internet of Things . . . . . . . . . . . 1233
Eric Bernardes C. Barros, Admilson de Ribamar L. Ribeiro,
Edward David Moreno and Luiz Eduardo C. Neri
Automated Behavioral Malware Analysis System . . . . . . . . . . . . . . . . . 1243
Saja Alqurashi and Omar Batarfi
A Message Efficient Group Membership Protocol in Synchronous
Distributed Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1249
SungHoon Park, SuChang Yoo, YeongMok Kim, SangGwon Lee
and DoWon Kim
Ontology-Driven Metamodel Validation in Cyber-Physical Systems . . . . 1255
Kevin Lynch, Randall Ramsey, George Ball, Matt Schmit and Kyle Collins
Developing Software in the Academic Environment: A Framework
for Software Development at the University . . . . . . . . . . . . . . . . . . . . . 1259
William Phillips, Shruthi Subramani, Anusha Gorantla
and Victoria Phillips
Automatic Reverse Engineering of Classes’ Relationships . . . . . . . . . . . 1267
Maen Hammad, Rajaa Abu-Wandi and Haneen Aydeh
xx Contents
Developing Predictable Vehicular Distributed Embedded Systems
on Multi-core . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1273
Saad Mubeen, Thomas Nolte and Kurt-Lennart Lundbäck
Formalizing the Process of Usability Heuristics Development . . . . . . . . 1279
Daniela Quiñones, Cristian Rusu, Silvana Roncagliolo, Virginica Rusu
and César A. Collazos
Analysis of a Training Platform for the Digital Battlefield, Based
on Semiotics and Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1283
Cristian Barría, Cristian Rusu, Claudio Cubillos, César Collazos
and Miguel Palma
Usability Heuristics and Design Recommendations for Driving
Simulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1287
Aníbal Campos, Cristian Rusu, Silvana Roncagliolo, Fabiola Sanz,
Raúl Gálvez and Daniela Quiñones
Model for Describing Bioprinting Projects in STL . . . . . . . . . . . . . . . . 1291
Luiz Angelo Valota Francisco and Luis Carlos Trevelin
The Fractal Nature of Mars Topography Analyzed via the Wavelet
Leaders Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1295
Adrien Deliège, Thomas Kleyntssens and Samuel Nicolay
Privacy Enhancement in E-Mail Clients . . . . . . . . . . . . . . . . . . . . . . . . 1299
Prabhat Kumar, Jyoti Prakash Singh, Rajni Kant Raman and Rohit Raj
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1303
Contents xxi
Part I
Networking and Wireless Communications
© Springer International Publishing Switzerland 2016 3
S. Latifi (ed.), Information Technology New Generations,
Advances in Intelligent Systems and Computing 448,
DOI: 10.1007/978-3-319-32467-8_1
Understanding User’s Acceptance of Personal
Cloud Computing: Using the Technology
Acceptance Model
Mohamed Eltayeb and Maurice Dawson
Abstract Personal Cloud Computing (PCC) is a rapidly growing technology,
addressing the market demand of individual users for access to available and reli-
able resources. But like other new technologies, concerns and issues have surfaced
with the adoption of PCC. Users deciding whether to adopt PCC may be con-
cerned about the ease of use, usefulness, or security risks in the cloud. Negative
attitudes toward using a technology have been found to negatively impact the
success of that technology. The purpose of this study was to understand users’
acceptance of PCC. The population sample consisted of individual users within
the United States between 18 and 80 years of age. The theoretical framework uti-
lized in this study was based on the technology acceptance model (TAM). A web
survey was conducted to assess the measurement and understanding of patterns
demonstrated by participants. Our results shows that in spite of the potential bene-
fits of PCC, security and privacy risks are deterring many users from moving
towards PCC.*
Keywords Personal Cloud Computing · Cloud computing · Technology
Acceptance Model
1 Introduction
Recently, cloud computing has been injected with new life from companies such
as Google, Microsoft, IBM, Amazon, and others who now offer cloud computing
M. Eltayeb
Colorado Technical University, 4435 N. Chestnut St., Colorado Springs, CO 80907, USA
e-mail: Mohamed.Eltayeb@coloradotech.edu
M. Dawson()
University of Missouri-St. Louis, 1 University Drive, St. Louis, MO 63121, USA
e-mail: Maurice.Dawson@umsl.edu
http://www.umsl.edu/
4 M. Eltayeb and M. Dawson
services for personal use. In this paper, we refer to PCC as the private and hybrid
cloud computing for the individual user’s usage. PCC has emerged as a new para-
digm model for individual users. It has transformed the user’s computer device
from being device-centric to information-centric [1-7]. PCC enables individuals to
share music, photos, videos, documents, and applications using any computer
devices connected to the network. It provides portable access from anywhere in
the world to information held centrally.
Though PCC demonstrated great potential in terms of scalability and agility,
and is therefore enjoying great popularity and attention, storing data and applica-
tions in the cloud is becoming very risky [8]. Many cloud users have become con-
cerned about security and protection of privacy [9], perhaps not surprisingly as the
cloud functions to store and share private data [10]. The main challenge and dis-
advantage users see in the adoption of cloud computing is that they lack full con-
trol over the hardware [11]. There are, therefore, several issues related to privacy
and security that must be addressed before PCC can be considered reliable.
Very often, data stored in the cloud is seen as valuable to those with malicious
intent [12]. Storing data and applications in the cloud is becoming very risky. It is
very important for users to take personal precautions in order to secure personal,
sensitive information—information they would have stored in their local computer
device (laptop, desktop, phone, tablet, etc.), and now store in the cloud. It is criti-
cal for users to understand the security measures that the cloud provider has in
place [13].
Predicting technology usage and adoption has become a topic of mainstream
study [14]. The rapidly growing importance of technologies has led researchers to
study user technology acceptance intensively. Negative attitudes toward a tech-
nology, its ease of use, and its usefulness may negatively impact the success of
that technology. Indeed, several IT scholars considered the user’s acceptance of a
technology to be the key success factor for the adoption of that technology [15].
The remaining of the paper is organized as follows: in the next section, we pre-
sent the objectives of the study. Section 2 discusses and articulates our theoretical
framework. Section 3 presents the research questions and hypothesis. The popula-
tion sample information are discussed in section 4. A detailed discussion of
the study’s data collection and validation are provided in section 5. Section 6
discusses the data analysis of the study.
Section 5 presents methods used for data collections. Section 6 discusses the
data analysis. Section 7 discusses our findings; and additional findings are dis-
cussed in section 8. Our recommendation and discussion are presented in section 9.
Finally, section 10 concludes the paper.
2 Theoretical Framework
This research was deductive in nature. Therefore, a quantitative method was
selected to understand user’s acceptance of PCC. In particular, a non-experimental
quantitative approach was used. The theoretical framework utilized in this study
Understanding User’s Acceptance of Personal Cloud Computing 5
was based on TAM—a widely recognized model in the field of IT, introduced by
Davis in 1986 [16]. Davis [16, 17] recommended TAM as the best model for in-
vestigating end user attitudes towards and acceptance or rejection of a technology.
According to Gao [18], “TAM can serve the purpose of predicting user acceptance
of a technology before the users get heavily involved in the technology and thus is
a cost-effective tool in screening potential candidate systems or programs” (p. 3).
This theoretical framework was used in this study to examine factors influencing
PCC adoption.
TAM proposes two independent variables—perceived ease of use, and perceived
usefulness (PU) of a technology—to predict the user’s attitude toward adopting a
technology [18]. Davis [16, 17] defined PU as the degree to which a user believes
that the adoption of a particular technology will improve the performance of his or
her job. The perceived ease of use, on the other hand, is the degree to which a user
believes that using a particular technology would be effortless [17].
Since the purpose of this study was to understand users’ thoughts, experiences,
expectations, and security concerns with respect to the adoption of PCC, TAM was
found to be the most suitable theoretical approach due to its validity and reliability in
exploring and explaining users’ attitudes toward using technologies [16]. Cloud
computing is a new approach to computing [19], and as new technologies are intro-
duced and are adopted, concerns and challenges emerge [20]. Therefore, this study
on PCC technology has a legitimate place in research on user technology
acceptance.
This research study extended TAM to include attitude towards using (ATU) as
an additional independent variable. This study adapted a survey instrument tested
by Davis [16], and validated by Venkatesh [21]. Overall, this study included three
independent variables and one dependent variable. The independent variables are
perceived ease of use (PEOU), attitude toward using PCC (ATU) and perceived
usefulness of PCC (PU). One dependent variable—Intention to Use PCC (ITC)—
was used broadly in this study.
3 Research Questions and Hypothesis
3.1 Research Question 1: How Does Perceived Ease of Use
Influence the Acceptance of PCC?
H1A: Perceived ease of use positively influences attitude toward the acceptance of
PCC.
H10: Perceived ease of use has no correlation to attitude toward the acceptance of
PCC.
6 M. Eltayeb and M. Dawson
The independent variable PEOU determines the degree to which a user believes
that using PCC would be effortless. PEOU is measured on a typical scale of seven
ordered continuum of response categories: Strongly disagree, Disagree, Slightly
disagree, Neutral, Slightly agree, Agree, Strongly agree.
3.2 Research Question 2: How Does Perceived Usefulness of
PCC Influence the Acceptance of PCC?
H2A: Perceived usefulness positively influences attitude toward the acceptance of
PCC.
H20: Perceived usefulness has no correlation to attitude toward the acceptance of
PCC.
The independent variable PU determines the degree to which a user believes that
the adoption of PCC would improve the performance of his or her job. PU is
measured on a typical scale of seven ordered continuum of response categories:
Strongly disagree, Disagree, Slightly disagree, Neutral, Slightly agree, Agree,
Strongly agree.
Research Question 3: How does attitude toward using PCC influence
acceptance of PCC?
H3A: There will be a correlation between attitude toward using PCC and the
user’s acceptance of PCC.
H30: There will be no correlation between attitude toward using PCC and the
user’s acceptance of PCC.
The independent variable (ATU) determines the degree to which a user’s
acceptance of PCC relates to that user’s attitude toward using PCC. ATU is meas-
ured across a typical scale of seven ordered continuum of response categories:
Strongly disagree, Disagree, Slightly disagree, Neutral, Slightly agree, Agree,
Strongly agree.
4 Population Sample
This study used a simple random sample from Survey Monkey engineering and IT
professionals panels. The minimum representative sampling size (n) was estimated
to be 384 participants for this study, based on a confidence interval of 5% and
a confidence level of 95%. As many participants as possible were included to
increase the accuracy of statistical sampling data.
Understanding User’s Acceptance of Personal Cloud Computing 7
A total of 464 participants were randomly chosen to participate in the study.
However, only 399 of the chosen participants fully completed the survey; 20 par-
ticipants opted out and 45 were disqualified either with unanswered questions or
with providing partial data. Only fully completed responses were admitted. There
was a 95.69% completion rate of surveys. Thus, the number of completed responses
exceeded the estimated, representative minimal sample size of 384. Several items in
the survey—gender, age range, education, state, and census region—were included
to further describe demographic characteristics of the sample.
5 Data Collection and Validation
This study used a web survey to collect data from participants. The survey was
hosted by SurveyMonkey.com, which is considered one of the leading providers
of online survey solutions. The identity of participants was kept confidential and
anonymous. Participant had the right to withdraw from participation at any time.
Participants were required to complete a consent form as soon as they login to the
SurveyMonkey.com. The consent form store collected information confidentially.
Information collected by the survey included: gender, age range, state of residence,
and level of education.
The survey questions in this study were designed to express a clearly negative
or positive opinion and avoided neutral opinions to solicit more definitive
responses. The researcher transcribed the data collected through Survey Monkey
into digital documents. Data was downloaded by the researcher after the comple-
tion of data collection. Only fully completed surveys were employed in this study.
Some participants were disqualified either with unanswered questions or with
providing partial data. Incomplete responses and partial data were completely
discarded. Additionally, Survey data was assessed for multicollinearity, homosce-
dasticity, linearity, and normality [22].
6 Data Analysis
The multiple regression test was performed as follows: (1) predictors were se-
lected using their semi-partial correlation with the outcome; (2) predictors were
entered into the model based on a mathematical method using Statistical Package
for the Social Sciences (SPSS) Version 19.0; (3) the selection of predictors was
performed in steps [23].
Descriptive statistics, ANOVA, Chi-square, and Multiple regressions were per-
formed to explore the relationship between the continuous dependent variable
(ITU) and independent variables (PEOU, PU, and ATU). Several descriptive sta-
tistics techniques were used to depict the sample population characteristics.
ANOVA was used to analyze both dependent and independent variables. In addi-
tion, the multiple regression test was performed to assess the impact of each
independent variable (PU, PEOU, and ATU) on the dependent variable (ITU).
8 M. Eltayeb and M. Dawson
7 Findings
TMultiple regressions were performed to explore the relationship between the
continuous dependent variable (ITU) and independent variables (PEOU, PU, and
ATU). This research study tested the relationship between perceived ease of use,
usefulness, attitude toward using PCC, and the acceptance of PCC. The model’s
adequacy was tested in terms of normality, linearity, and collinearity [24].
7.1 First Regression Model
The first regression was performed to determine the relationship between the in-
dependent variable PEOU and the dependent variable ITU. Six predictors of the
independent variable PEOU were tested to address the first research question. The
relationship between the predictors and the outcome were measured using a step-
wise method, so that the unique contribution of each predictor could be assessed to
explain variance of the outcome [24]. The following research question and
hypothesis were tested at this stage:
How does perceived ease of use influence the acceptance of PCC?
H10: Perceived ease of use has no correlation to the acceptance of PCC.
The results of the regression analysis demonstrated a positive correlation between
PEOU and the acceptance of PCC. It was found that approximately 23.5% of the
variance in the acceptance of PCC can be accounted for by PEOU. Therefore, the
null hypothesis was rejected and the alternative was supported.
This result is consistent with other studies showing that there is a positive cor-
relation between PEOU and the user’s acceptance of a technology. Davis [16]
argued that perceived ease of use positively influence attitude toward using a
technology. Perceived ease of use plays an important role in determining and pre-
dicting the user’s intention to use a technology [25]. Ramgovind [26] stated “The
success of modern day technologies highly depends on its effectiveness of the
world’s norms, its ease of use by end users and most importantly its degree of
information security and control” (p. 1).
7.2 Second Regression Model
The second regression was performed to determine the relationship between the
independent variable PU and the dependent variable ITU. Five predictors of the
independent variable PU were tested to address the first research question.
A stepwise regression was performed to build the model. The unique contribution
of each predictor was measured to explain the variance of the outcome [24]. The
following research question and hypothesis were tested at this stage:
Understanding User’s Acceptance of Personal Cloud Computing 9
How does perceived usefulness of PCC influence the acceptance of PCC?
H20: Perceived usefulness has no correlation to attitude toward the acceptance of
PCC.
The results of the regression analysis demonstrated a positive correlation between
PU and the acceptance of PCC. It was found that approximately 78.2% of the
variance in the acceptance of PCC can be accounted for by PU. Therefore, the null
hypothesis was rejected and the alternative was supported. This result is consistent
with other studies showing that there is a positive correlation between PU and the
user’s acceptance of a technology.
7.3 Third Regressions Model
The third regression was performed to determine the relationship between the
independent variable ATU and the dependent variable ITU. Four predictors of
the independent variable ATU were tested to address the first research question.
The relationship between the predictors and the outcome were measured using
stepwise regression. The unique contribution of each predictor was measured to
explain the variance of the [24]. The unique contribution of each predictor is
measured to explain the variance of the outcome. The following research question
and hypothesis were tested at this stage:
How does attitude toward using PCC influence user’s acceptance of PCC?
H30: There will be no correlation between attitude toward using PCC and user’s
acceptance of PCC.
The independent variable ATU was used for determining the degree in which
there is a correlation between attitude toward using PCC and users’ intention to
use. The results of the regression analysis demonstrated a significant correlation
between ATU and the acceptance of PCC. It was found that approximately 38.2%
of the variance in the acceptance of PCC can be accounted for by ATU. Therefore,
the null hypothesis was rejected and the alternative was supported.
8 Additional Findings
Statistically significant differences were found between age group means, as indi-
cated by results of the one-way ANOVA (F (5, 2.801)=2.801, p=.017). The output
result of the one-way ANOVA showed that the age group significantly contributed
to the variation in the respondent’s acceptance of the PCC technology. Because
the output result of the one-way ANOVA test demonstrated significant differences
between the age groups, a Post Hoc test was conducted to further investigate
which means were significantly different from each other. The Post Hoc test result
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Transcriber’s Note:
Obvious printer errors corrected silently.
Inconsistent spelling and hyphenation are as in the original.
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Information Technology New Generations 13th International Conference on Information Technology 1st Edition Shahram Latifi (Eds.)

  • 1.
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  • 4.
    Advances in IntelligentSystems and Computing 448 Shahram Latifi Editor Information Technology: New Generations 13th International Conference on InformationTechnology
  • 5.
    Advances in IntelligentSystems and Computing Volume 448 Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]
  • 6.
    About this Series Theseries “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing. The publications within “Advances in Intelligent Systems and Computing” are primarily textbooks and proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results. Advisory Board Chairman Nikhil R. Pal, Indian Statistical Institute, Kolkata, India e-mail: [email protected] Members Rafael Bello, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Cuba e-mail: [email protected] Emilio S. Corchado, University of Salamanca, Salamanca, Spain e-mail: [email protected] Hani Hagras, University of Essex, Colchester, UK e-mail: [email protected] László T. Kóczy, Széchenyi István University, Győr, Hungary e-mail: [email protected] Vladik Kreinovich, University of Texas at El Paso, El Paso, USA e-mail: [email protected] Chin-Teng Lin, National Chiao Tung University, Hsinchu, Taiwan e-mail: [email protected] Jie Lu, University of Technology, Sydney, Australia e-mail: [email protected] Patricia Melin, Tijuana Institute of Technology, Tijuana, Mexico e-mail: [email protected] Nadia Nedjah, State University of Rio de Janeiro, Rio de Janeiro, Brazil e-mail: [email protected] Ngoc Thanh Nguyen, Wroclaw University of Technology, Wroclaw, Poland e-mail: [email protected] Jun Wang, The Chinese University of Hong Kong, Shatin, Hong Kong e-mail: [email protected] More information about this series at http://www.springer.com/series/11156
  • 7.
    Shahram Latifi Editor Information Technology: New Generations 13thInternational Conference on Information Technology 123
  • 8.
    Editor Shahram Latifi PHASE Las Vegas,NV USA ISSN 2194-5357 ISSN 2194-5365 (electronic) Advances in Intelligent Systems and Computing ISBN 978-3-319-32466-1 ISBN 978-3-319-32467-8 (eBook) DOI 10.1007/978-3-319-32467-8 Library of Congress Control Number: 2016935571 © Springer International Publishing Switzerland 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
  • 9.
    Preface Welcome to the13th International Conference on Information Technology- New Generations- ITNG 2016. It is a pleasure to report that we have another successful year for the ITNG 2016. Gaining popularity and recognition in the IT community around the globe, the conference was able to attract many papers from authors worldwide. The papers were reviewed for their technical soundness, originality, clarity and relevance to the conference. The conference enjoyed expert opinion of 89 author and non-author scientists who participated in the review process. Each paper was reviewed by at least two independent reviewers. A total of 96 articles were accepted as regular papers and 14 were accepted as short papers (posters). The overall acceptance rate was 35 %. The articles in this proceeding address the most recent advances in such areas as Wireless Communications and Networking, Software Engineering, Information Security, Data Mining, Informatics, Wavelets, High Performance Computing Architectures, Internet, and Computer Vision. As customary, the conference features two keynote speakers on Monday and Tuesday. The presentations for Monday and Tuesday are organized in 2 meeting rooms simultaneously, covering a total of 16 technical sessions. Poster presenta- tions are scheduled for the morning and afternoon of these days. The award cere- mony, conference reception and dinner are scheduled for Tuesday evening. Two parallel sessions have been organized for Wednesday. Many people contributed to the success of this year’s conference by organizing symposia or technical tracks for the ITNG. Dr. Yenumula Reddy deserves much credit for spearheading the review process and running a symposium on Wireless Communications and Networking. My sincere thanks go to other symposium and major track organizers and associate editors namely- Drs. Kohei Arai, Alessio Bucaioni, Glauco Carneiro, Narayan Debnath, Luiz Alberto Vieira Dias, Ray Hashemi, Teruya Minamoto, Kashif Saleem, Basit Shahzad, Christoph Thuemmler, and Fangyan Shen. v
  • 10.
    Others who wereresponsible for solicitation, review and handling the papers submitted to their respective sessions include Drs Azita Bahrami, Doina Bein, Wolfgang Bein, Federico Ciccozzi, Saad Mubeen, Armin Schneider and Mei Yang. The help and support of the Springer in preparing the ITNG proceedings is specially appreciated. Many thanks are due to Michael Luby, the Senior Editor and Nicole Lowary, the Assistant Editor of the Springer supervisor of Publications for the timely handling of our publication order. Finally, the great efforts of the con- ference secretary, Ms. Mary Roberts who dealt with the day to day conference affairs, including timely handling volumes of emails, are acknowledged. The conference venue remains the same as last year- the Flamingo Hotel as the conference. The hotel, conveniently located in the heart of Las Vegas Strip, pro- vides an easy access to other major resorts and recreational centers. I hope and trust that you have an academically and socially fulfilling stay in Las Vegas. April 2016 Shahram Latifi The ITNG General Chair vi Preface
  • 11.
    ITNG 2016 Organization Editorand General Chair Shahram Latifi University of Nevada, Las Vegas, USA Associate Editors Kohei Arai Saga University, Japan Glauco Carneiro University of Salvador, Brazil Narayan Debnath Winona State University, USA Luiz Alberto Vieira Dias Instituto Tecnológico de Aeronáutica, Brazil Ray Hashemi Armstrong State University, USA Yenumula Reddy Grambling State University, USA Track Organizers Kohei Arai Saga University, Japan Alessio Bucaioni Mälardalen University, Sweden Glauco Carneiro University of Salvador, Brazil Narayan Debnath Winona State University, USA Luiz Alberto Vieira Dias ITA, Brazil Ray Hashemi Armstrong State University, USA Teruya Minamoto Saga University, Japan Kashif Saleem King Saud University, Saudi Arabia Basit Shahzad King Saud University, Saudi Arabia Yenumula Reddy Grambling State University, USA Christoph Thuemmler Edinburgh Napier University, UK Fangyan Shen New York City College of Technology, USA Session Chairs Azita Bahrami IT Consultation, USA Doina Bein California State University, USA Wolfgang Bein University of Nevada, USA Federico Ciccozzi Mälardalen University, Sweden Saad Mubeen Mälardalen University, Saudi Arabia Armin Schneider Technical University Munich, Germany Mei Yang University of Nevada, Las Vegas, USA vii
  • 12.
    Publicity Chair Basit ShahzadKing Saud University, Saudi Arabia Conference Secretary Mary Roberts PHASE Inc., USA Reviewers Abbas, Haider Ahmed, Adel Ahmed, Iqbal Al-Muhtadi, Jalal Arai, Kohei Araujo, Marco Antonio Ashino, Ryuichi Autili, Marco Awan, Fahim Baguda, Yakubu Barina, David Behnam, Moris Braga, Regina Brito e Abreu, Fernando Caetano, Paulo Camargo, Valter Campos, Fernanda Carlson, Jan Carneiro, Glauco Carreiro, Bruno Challah, Yacine Chaudhry, Imran Christos, Kalloniatis Cicchetti, Antonio Clincy, Victor Colaco Jr., Methanias Costa, Heitor Crespo, Yania Dai, Qing David, Jose Maria Delamaro, Marcio Eduardo Derhab, Abdelouahid Dias, Luiz Eldefrawy, H. Eramo, Romina Fabbri, Sandra Fernandes, Joao M. Figueiredo, Eduardo Frederic, Jean Fujinoki, Kensuke Garcia, Rogerio Garcia-Valls, Marisol Gawanmeh, Amjad Hashemi, Ray Huang, Yingsong Ji, Yanqing Kimura, Takuma Kinoshita, Takehiko Liebel, Grischa Maia, Marcelo Malavolta, Ivano Marques, Johnny Meghanathan, Natarajan Mesit, Jaruwan Mialaret, Lineu Minamoto, Teruya Mirza, Abdulrahman Monteiro, Miguel Montini, Denis Morimoto, Akira Munson, Ethan V Novais, Renato viii ITNG 2016 Organization
  • 13.
    Oliveira, Toacy Orgun, Mehmet Pathan,Al-Sakib Paulin, Alois Pontin, Renata Reddy, Yenumula Rehmani, Mubashir Rodrigues, Joel Rossi, Gustavo Saito, Norikazu Saleem, Kashif Saleem, Kashif Sampaio, Paulo Sarijari, Adib Satyanarayana, Ashwin Schneider, Armin Shahzad, Basit Shen, Fangyang Soares, Michel Solari, Martin Sreekumari, Prasanthi Suzana, Rita Takano, Shigeru Thuemmler, Christoph Tolle, Herman Tsuchiya, Takuya Watanabe, Yoshitaka ITNG 2016 Organization ix
  • 14.
    Contents Networking and WirelessCommunications Understanding User’s Acceptance of Personal Cloud Computing: Using the Technology Acceptance Model . . . . . . . . . . . . . . . . . . . . . . . 3 Mohamed Eltayeb and Maurice Dawson Cognitive Spectrum Decision via Machine Learning in CRN. . . . . . . . . 13 A. M. Koushik, Fei Hu, Ji Qi and Sunil Kumar Elastic Edge-Overlay Methods Using OpenFlow for Cloud Networks . . . 25 Amer Aljaedi, C. Edward Chow and Jia Rao An Approach to Generate Automatic Variable Key to Assure Perfect Security in Cryptosystem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Subhasish Banerjee, Manash P. Dutta and C. T. Bhunia Airborne Networks with Multi-beam Smart Antennas: Towards a QOS-Supported, Mobility-Predictive MAC . . . . . . . . . . . . . 47 Xin Li, Fei Hu, Lei Hu and Sunil Kumar CR Based Video Communication Testbed with Robust Spectrum Sensing / Handoff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Ji Qi, Fei Hu, Xin Li, A. M. Koushik, Lei Hu and Sunil Kumar A Control-Message Quenching Algorithm in Openflow-Based Wireless Mesh Networks with Dynamic Spectrum Access . . . . . . . . . . . . . . . . . . 71 Xin Li, Xiaoyan Hong, Yu Lu, Fei Hu, Ke Bao and Sunil Kumar SINR Maximization in Relay-Assisted Multi-user Wireless Networks . . . 83 Umar Rashid, Faheem Gohar Awan and Muhammad Kamran A Hybrid MAC for Long-Distance Mesh Network with Multi-beam Antennas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Xin Li, Fei Hu, Ji Qi and Sunil Kumar xi
  • 15.
    Future Approach toFind Business Model Orientation for Technological Businesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Sepehr Ghazinoory, Fatemeh Saghafi, Maryam Mirzaei, Mohammadali Baradaran Ghahfarokhi and Parvin Baradaran Ghahfarokhi Social Media Coverage of Public Health Issues in China: A Content Analysis of Weibo News Posts . . . . . . . . . . . . . . . . . . . . . . . 111 Jiayin Pei, Guang Yu and Peng Shan Advertisement Through the Most Popular Twitter Users Based on Followers in Saudi Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Abeer A. AlSanad and Abdulrahman A. Mirza Sentiment Analysis for Arabic Reviews in Social Networks Using Machine Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Mustafa Hammad and Mouhammd Al-awadi Security and Privacy in Next Generation Networks An Interactive Model for Creating Awareness and Consequences of Cyber-crime in People with Limited Technology Skills . . . . . . . . . . . 143 Sheeraz Akram, Muhammad Ramzan, Muhammad Haneef and Muhammad Ishtiaq Power Analysis Attack and Its Countermeasure for a Lightweight Block Cipher Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Masaya Yoshikawa and Yusuke Nozaki Perpetuating Biometrics for Authentication: Introducing the Durable True-Neighbor Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Fawaz E. Alsaadi and Terrance E. Boult Certificate-Based IP Multimedia Subsystem Authentication and Key Agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Wei-Kuo Chiang and Ping-Chun Lin Software Optimizations of NTRUEncrypt for Modern Processor Architectures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Shay Gueron and Fabian Schlieker Vulnerabilities and Mitigation Methods in the NextGen Air Traffic Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Sachiko Sueki and Yoohwan Kim Pushing the Limits of Cyber Threat Intelligence: Extending STIX to Support Complex Patterns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Martin Ussath, David Jaeger, Feng Cheng and Christoph Meinel xii Contents
  • 16.
    Analyzing Packet ForwardingSchemes for Selfish Behavior in MANETs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Asad Raza, Jamal Nazzal Al-Karaki and Haider Abbas Speed Records for Multi-Prime RSA Using AVX2 Architectures . . . . . . 237 Shay Gueron and Vlad Krasnov Privacy Preservation of Source Location Using Phantom Nodes . . . . . . 247 Shruti Gupta, Prabhat Kumar, J.P. Singh and M.P. Singh Implementing a Bitcoin Exchange with Enhanced Security . . . . . . . . . . 257 Ebru Celikel Cankaya and Luke Daniel Carr Information Systems and Internet Technology REST-Based Semantic Annotation of Web Services . . . . . . . . . . . . . . . 269 Cleber Lira and Paulo Caetano Synthetical QoE-Driven Anomalous Cell Pattern Detection with a Hybrid Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 Dandan Miao, Weijian Sun, Xiaowei Qin and Weidong Wang A Mobile Group Tour Tracking and Gathering System . . . . . . . . . . . . 293 Chyi-Ren Dow, Yu-Yun Chang, Chiao-Wen Chen and Po-Yu Lai Model Based Evaluation of Cybersecurity Implementations. . . . . . . . . . 303 Aristides Dasso, Ana Funes, Germán Montejano, Daniel Riesco, Roberto Uzal and Narayan Debnath Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Raja H. Singh, Lee Barford and Frederick Harris Jr. Maximum Clique Solver Using Bitsets on GPUs . . . . . . . . . . . . . . . . . . 327 Matthew VanCompernolle, Lee Barford and Frederick Harris Jr. CUDA Implementation of Computer Go Game Tree Search . . . . . . . . . 339 Christine Johnson, Lee Barford, Sergiu M. Dascalu and Frederick C. Harris Jr. Negotiation and Collaboration Protocol Based on EbXML Intended to Optimize Port Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351 Vinícius Eduardo Ferreira dos Santos Silva, Nunzio Marco Torrisi and Rodrigo Palucci Pantoni Reversible Data Hiding Scheme Using the Difference Between the Maximum and Minimum Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 Pyung-Han Kim, Kwang-Yeol Jung, In-Soo Lee and Kee-Young Yoo Contents xiii
  • 17.
    The Design, DataFlow Architecture, and Methodologies for a Newly Researched Comprehensive Hybrid Model for the Detection of DDoS Attacks on Cloud Computing Environment . . . . . . . . . . . . . . . . . . . . . 377 Anteneh Girma, Kobi Abayomi and Moses Garuba Educational Gaming: Improved Integration Using Standard Gaming Genres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 Ben Brown and Sergiu Dascalu Designing a Web-Based Graphical Interface for Virtual Machine Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 Harinivesh Donepudi, Bindu Bhavineni and Michael Galloway Towards Providing Resource Management in a Local IaaS Cloud Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 Travis Brummett and Michael Galloway Integration of Assistive Technologies into 3D Simulations: An Exploratory Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425 Angela T. Chan, Alexander Gamino, Frederick C. Harris Jr. and Sergiu Dascalu Data Profiling Technology of Data Governance Regarding Big Data: Review and Rethinking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439 Wei Dai, Isaac Wardlaw, Yu Cui, Kashif Mehdi, Yanyan Li and Jun Long Understanding the Service Model of Mobile Social Network in Live 4G Network: A Case Study of WeChat Moments. . . . . . . . . . . . . . . . . . . . 451 Weijian Sun, Dandan Miao, Xiaowei Qin and Guo Wei Applying Scrum in an Interdisciplinary Project for Fraud Detection in Credit Card Transactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461 Mayara Valeria Morais dos Santos, Paulo Diego Barbosa da Silva, Andre Gomes Lamas Otero, Ramiro Tadeu Wisnieski, Gildarcio Sousa Goncalves, Rene Esteves Maria, Luiz Alberto Vieira Dias and Adilson Marques da Cunha The Visual Representation of Numerical Solution for a Non-stationary Deformation in a Solid Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473 Zhanar Akhmetova, Seilkhan Boranbayev and Serik Zhuzbayev Software Engineering Developing Usability Heuristics for Grid Computing Applications: Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 Daniela Quiñones, Cristian Rusu, Silvana Roncagliolo, Virginica Rusu and César A. Collazos xiv Contents
  • 18.
    Refining Timing Requirementsin Extended Models of Legacy Vehicular Embedded Systems Using Early End-to-end Timing Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 Saad Mubeen, Thomas Nolte, John Lundbäck, Mattias Gålnander and Kurt-Lennart Lundbäck Integrated Metrics Handling in Open Source Software Quality Management Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509 Julio Escribano-Barreno, Javier García-Muñoz and Marisol García-Valls Supporting the Development of User-Driven Service Composition Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519 Alex Roberto Guido, Antonio Francisco do Prado, Wanderley Lopes de Souza and Eduardo Gonçalves da Silva Mining Source Code Clones in a Corporate Environment . . . . . . . . . . . 531 Jose J. Torres, Methanias C. Junior and Francisco R. Santos Fuzzy Resource-Constrained Time Workflow Nets . . . . . . . . . . . . . . . . 543 Joslaine Cristina Jeske de Freitas and Stéphane Julia Performance Indicators Analysis in Software Processes Using Semi-supervised Learning with Information Visualization . . . . . . 555 Leandro Bodo, Hilda Carvalho de Oliveira, Fabricio Aparecido Breve and Danilo Medeiros Eler Techniques for the Identification of Crosscutting Concerns: A Systematic Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569 Ingrid Marçal, Rogério Eduardo Garcia, Danilo Medeiros Eler, Celso Olivete Junior and Ronaldo C.M. Correia ValiPar Service: Structural Testing of Concurrent Programs as a Web Service Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581 Rafael R. Prado, Paulo S.L. Souza, Simone R.S. Souza, George G.M. Dourado and Raphael N. Batista A Model-Driven Solution for Automatic Software Deployment in the Cloud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591 Franklin Magalhães Ribeiro Jr., Tarcísio da Rocha, Joanna C.S. Santos and Edward David Moreno Software Process Improvement in Small and Medium Enterprises: A Systematic Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603 Gledston Carneiro da Silva and Glauco de Figueiredo Carneiro Investigating Reputation in Collaborative Software Maintenance: A Study Based on Systematic Mapping . . . . . . . . . . . . . . . . . . . . . . . . 615 Cláudio Augusto S. Lélis, Marco Antônio P. Araújo, José Maria N. David and Glauco de F. Carneiro Contents xv
  • 19.
    A 2-Layer Component-BasedArchitecture for Heterogeneous CPU-GPU Embedded Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629 Gabriel Campeanu and Mehrdad Saadatmand High-Performance Computing Architectures Block-Based Approach to 2-D Wavelet Transform on GPUs . . . . . . . . . 643 Michal Kula, David Barina and Pavel Zemcik Deriving CGM Based-Parallel Algorithms for the Optimal Binary Search-Tree Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 655 Vianney Kengne Tchendji, Jean Frédéric Myoupo and Gilles Dequen Experimental Evaluations of MapReduce in Biomedical Text Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665 Yanqing Ji, Yun Tian, Fangyang Shen and John Tran Algorithmic Approaches for a Dependable Smart Grid. . . . . . . . . . . . . 677 Wolfgang Bein, Bharat B. Madan, Doina Bein and Dara Nyknahad Performance Evaluation of Data Migration Methods Between the Host and the Device in CUDA-Based Programming . . . . . . . . . . . . . . . . . . . 689 Rafael Silva Santos, Danilo Medeiros Eler and Rogério Eduardo Garcia Design of a Deadlock-Free XY-YX Router for Network-on-Chip . . . . . . 701 Sang Muk Lee, Eun Nu Ri Ko, Young Seob Jeong and Seung Eun Lee An FPGA Based Compression Accelerator for Forex Trading System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 711 Ji Hoon Jang, Seong Mo Lee, Oh Seong Gwon and Seung Eun Lee Agile Software Testing and Development An Academic Case Study Using Scrum . . . . . . . . . . . . . . . . . . . . . . . . 723 Luciana Rinaldi Fogaça, Luiz Alberto Vieira Dias and Adilson Marques da Cunha Distributed Systems Performance for Big Data. . . . . . . . . . . . . . . . . . . 733 Marcelo Paiva Ramos, Paulo Marcelo Tasinaffo, Eugenio Sper de Almeida, Luis Marcelo Achite, Adilson Marques da Cunha and Luiz Alberto Vieira Dias Towards Earlier Fault Detection by Value-Driven Prioritization of Test Cases Using Fuzzy TOPSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . 745 Sahar Tahvili, Wasif Afzal, Mehrdad Saadatmand, Markus Bohlin, Daniel Sundmark and Stig Larsson xvi Contents
  • 20.
    Model-Driven Engineering forCyber-Physical Systems Experimenting with a Load-Aware Communication Middleware for CPS Domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 763 Luis Cappa-Banda and Marisol García-Valls Adaptive Message Restructuring Using Model-Driven Engineering . . . . 773 Hang Yin, Federico Giaimo, Hugo Andrade, Christian Berger and Ivica Crnkovic Towards Modular Language Design Using Language Fragments: The Hybrid Systems Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 785 Sadaf Mustafiz, Bruno Barroca, Claudio Gomes and Hans Vangheluwe Data Mining Data Clustering Using Improved Fire Fly Algorithm . . . . . . . . . . . . . . 801 Mehdi Sadeghzadeh Intelligent Mobile App for You-Tube Video Selection . . . . . . . . . . . . . . 811 Mark Smith An Application of GEP Algorithm for Prime Time Detection in Online Social Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 821 Hsiao-Wei Hu, Wen-Shiu Lin and I-Hsun Chen Transport Logistic Application: Train’s Adherence Evolution and Prediction Based on Decision Tree and Markov Models . . . . . . . . . 833 Steve Ataky T. Mpinda, Marilde T.P. Santos and Marcela X. Ribeiro A Method for Match Key Blocking in Probabilistic Matching: (Research-in-Progress). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847 Pei Wang, Daniel Pullen, John R. Talburt and Cheng Chen Accuracy Assessment on Prediction Models for Fetal Weight Based on Maternal Fundal Height: Applications in Indonesia . . . . . . . . . . . . . 859 Dewi Anggraini, Mali Abdollahian and Kaye Marion Ensemble Noise Filtering for Streaming Data Using Poisson Bootstrap Model Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 869 Ashwin Satyanarayana and Rosemary Chinchilla Mining Persistent and Dynamic Spatio-Temporal Change in Global Climate Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 881 Jie Lian and Michael P. McGuire Open Source Data Quality Tools: Revisited . . . . . . . . . . . . . . . . . . . . . 893 Venkata Sai Venkatesh Pulla, Cihan Varol and Murat Al Contents xvii
  • 21.
    New Trends inWavelet and Numerical Analysis Some Outflow Boundary Conditions for the Navier-Stokes Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905 Yoshiki Sugitani, Guanyu Zhou and Norikazu Saito Successive Projection with B-spline . . . . . . . . . . . . . . . . . . . . . . . . . . . 917 Yuki Ueda and Norikazu Saito Computer-Aided Diagnosis Method for Detecting Early Esophageal Cancer from Endoscopic Image by Using Dyadic Wavelet Transform and Fractal Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 929 Ryuji Ohura, Hajime Omura, Yasuhisa Sakata and Teruya Minamoto Daubechies Wavelet-Based Method for Early Esophageal Cancer Detection from Flexible Spectral Imaging Color Enhancement Image . . . 939 Hiroki Matsunaga, Hajime Omura, Ryuji Ohura and Teruya Minamoto A Refined Method for Estimating the Global Hölder Exponent . . . . . . . 949 S. Nicolay and D. Kreit A New Wavelet-Based Mode Decomposition for Oscillating Signals and Comparison with the Empirical Mode Decomposition . . . . . . . . . . 959 Adrien Deliège and Samuel Nicolay Computer Vision, HCI and Image Processing/Analysis Short Boundary Detection Using Spatial-Temporal Features . . . . . . . . . 971 Muhammad Ali and Awais Adnan A Set of Usability Heuristics and Design Recommendations for u-Learning Applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 983 Fabiola Sanz, Raúl Galvez, Cristian Rusu, Silvana Roncagliolo, Virginica Rusu, César A. Collazos, Juan Pablo Cofré, Aníbal Campos and Daniela Quiñones Computer Input just by Sight and Its Applications in Particular for Disable Persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995 Kohei Arai User Impressions About Distinct Approaches to Layout Design of Personalized Content. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1009 Anelise Schunk, Francine Bergmann, Ricardo Piccoli, Angelina Ziesemer, Isabel Manssour, João Oliveira and Milene Silveira Video Compression Using Variable Block Size Motion Compensation with Selective Subpixel Accuracy in Redundant Wavelet Transform . . . 1021 Ahmed Suliman and Robert Li xviii Contents
  • 22.
    PPMark: An Architectureto Generate Privacy Labels Using TF-IDF Techniques and the Rabin Karp Algorithm . . . . . . . . . . . . . . . . . . . . . 1029 Diego Roberto Gonçalves de Pontes and Sergio Donizetti Zorzo RGB and Hue Color in Pornography Detection . . . . . . . . . . . . . . . . . . 1041 Awais Adnan and Muhammad Nawaz Potpourri Sociology Study Using Email Data and Social Network Analysis . . . . . . 1053 Wajid Rafiq, Shoab Ahmed Khan and Muhammad Sohail Evaluation of Usability Heuristics for Transactional Web Sites: A Comparative Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1063 Freddy Paz, Freddy A. Paz and José Antonio Pow-Sang Algorithm for Gaussian Integer Exponentiation . . . . . . . . . . . . . . . . . . 1075 Aleksey Koval Dynamic Simulation of the Flight Behavior of a Rotary-Wing Aircraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1087 Sebastião Simões Cunha Jr., Marcelo Santiago de Sousa, Danilo Pereira Roque, Alexandre Carlos Brandão Ramos and Pedro Fernandes Jr. Origami Guru: An Augmented Reality Application to Assist Paper Folding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1101 Nuwee Wiwatwattana, Chayangkul Laphom, Sarocha Aggaitchaya and Sudarat Chattanon Augmented Reality Approach for Knowledge Visualization and Production (ARAKVP) in Educational and Academic Management System for Courses Based on Active Learning Methodologies (EAMS–CBALM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1113 Helen de Freitas Santos, Wanderley Lopes de Souza, Antonio Francisco do Prado and Sissi Marilia dos Santos Forghieri Pereira Designing Schedulers for Hard Real-Time Tasks . . . . . . . . . . . . . . . . . 1125 Vasudevan Janarthanan An Autonomous Stair Climbing Algorithm with EZ-Robots . . . . . . . . . 1135 Jason Moix, Sheikh Faal, M. K. Shamburger, Chris Carney, Alex Williams, Zixin Ye and Yu Sun Toward Indoor Autonomous Flight Using a Multi-rotor Vehicle . . . . . . 1145 Connor Brooks, Christopher Goulet and Michael Galloway Contents xix
  • 23.
    Using Tweets forRainfall Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . 1157 Luiz Eduardo Guarino de Vasconcelos, Eder C.M. dos Santos, Mário L.F. Neto, Nelson Jesuz Ferreira and Leandro Guarino de Vasconcelos Algorithms Performance Evaluation in Hybrid Systems . . . . . . . . . . . . 1169 Rafael Manochio, David Buzatto, Paulo Muniz de Ávila and Rodrigo Palucci Pantoni An Efficient Method for the Open-Shop Scheduling Problem Using Simulated Annealing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183 Haidar M. Harmanani and Steve Bou Ghosn Schematizing Heidegger. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1195 Sabah Al-Fedaghi Constrained Triangulation of 2D Shapes . . . . . . . . . . . . . . . . . . . . . . . 1209 Laxmi P Gewali and Roshan Gyawali Software Project and Analysis of a Training Screen Based System for Healthcare Professionals Working in the NICU in Brazil. . . . . . . . . 1219 Daniel Rocha Gualberto, Renata Aparecida Ribeiro Custódio, Alessandro Rodrigo Pereira Dias, Gabriel Bueno da Silva, Clarissa Gonçalves Eboli and Alexandre Carlos Brandão Ramos Short Papers A Self-Configuration Web-API for the Internet of Things . . . . . . . . . . . 1233 Eric Bernardes C. Barros, Admilson de Ribamar L. Ribeiro, Edward David Moreno and Luiz Eduardo C. Neri Automated Behavioral Malware Analysis System . . . . . . . . . . . . . . . . . 1243 Saja Alqurashi and Omar Batarfi A Message Efficient Group Membership Protocol in Synchronous Distributed Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1249 SungHoon Park, SuChang Yoo, YeongMok Kim, SangGwon Lee and DoWon Kim Ontology-Driven Metamodel Validation in Cyber-Physical Systems . . . . 1255 Kevin Lynch, Randall Ramsey, George Ball, Matt Schmit and Kyle Collins Developing Software in the Academic Environment: A Framework for Software Development at the University . . . . . . . . . . . . . . . . . . . . . 1259 William Phillips, Shruthi Subramani, Anusha Gorantla and Victoria Phillips Automatic Reverse Engineering of Classes’ Relationships . . . . . . . . . . . 1267 Maen Hammad, Rajaa Abu-Wandi and Haneen Aydeh xx Contents
  • 24.
    Developing Predictable VehicularDistributed Embedded Systems on Multi-core . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1273 Saad Mubeen, Thomas Nolte and Kurt-Lennart Lundbäck Formalizing the Process of Usability Heuristics Development . . . . . . . . 1279 Daniela Quiñones, Cristian Rusu, Silvana Roncagliolo, Virginica Rusu and César A. Collazos Analysis of a Training Platform for the Digital Battlefield, Based on Semiotics and Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1283 Cristian Barría, Cristian Rusu, Claudio Cubillos, César Collazos and Miguel Palma Usability Heuristics and Design Recommendations for Driving Simulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1287 Aníbal Campos, Cristian Rusu, Silvana Roncagliolo, Fabiola Sanz, Raúl Gálvez and Daniela Quiñones Model for Describing Bioprinting Projects in STL . . . . . . . . . . . . . . . . 1291 Luiz Angelo Valota Francisco and Luis Carlos Trevelin The Fractal Nature of Mars Topography Analyzed via the Wavelet Leaders Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1295 Adrien Deliège, Thomas Kleyntssens and Samuel Nicolay Privacy Enhancement in E-Mail Clients . . . . . . . . . . . . . . . . . . . . . . . . 1299 Prabhat Kumar, Jyoti Prakash Singh, Rajni Kant Raman and Rohit Raj Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1303 Contents xxi
  • 25.
    Part I Networking andWireless Communications
  • 26.
    © Springer InternationalPublishing Switzerland 2016 3 S. Latifi (ed.), Information Technology New Generations, Advances in Intelligent Systems and Computing 448, DOI: 10.1007/978-3-319-32467-8_1 Understanding User’s Acceptance of Personal Cloud Computing: Using the Technology Acceptance Model Mohamed Eltayeb and Maurice Dawson Abstract Personal Cloud Computing (PCC) is a rapidly growing technology, addressing the market demand of individual users for access to available and reli- able resources. But like other new technologies, concerns and issues have surfaced with the adoption of PCC. Users deciding whether to adopt PCC may be con- cerned about the ease of use, usefulness, or security risks in the cloud. Negative attitudes toward using a technology have been found to negatively impact the success of that technology. The purpose of this study was to understand users’ acceptance of PCC. The population sample consisted of individual users within the United States between 18 and 80 years of age. The theoretical framework uti- lized in this study was based on the technology acceptance model (TAM). A web survey was conducted to assess the measurement and understanding of patterns demonstrated by participants. Our results shows that in spite of the potential bene- fits of PCC, security and privacy risks are deterring many users from moving towards PCC.* Keywords Personal Cloud Computing · Cloud computing · Technology Acceptance Model 1 Introduction Recently, cloud computing has been injected with new life from companies such as Google, Microsoft, IBM, Amazon, and others who now offer cloud computing M. Eltayeb Colorado Technical University, 4435 N. Chestnut St., Colorado Springs, CO 80907, USA e-mail: [email protected] M. Dawson() University of Missouri-St. Louis, 1 University Drive, St. Louis, MO 63121, USA e-mail: [email protected] http://www.umsl.edu/
  • 27.
    4 M. Eltayeband M. Dawson services for personal use. In this paper, we refer to PCC as the private and hybrid cloud computing for the individual user’s usage. PCC has emerged as a new para- digm model for individual users. It has transformed the user’s computer device from being device-centric to information-centric [1-7]. PCC enables individuals to share music, photos, videos, documents, and applications using any computer devices connected to the network. It provides portable access from anywhere in the world to information held centrally. Though PCC demonstrated great potential in terms of scalability and agility, and is therefore enjoying great popularity and attention, storing data and applica- tions in the cloud is becoming very risky [8]. Many cloud users have become con- cerned about security and protection of privacy [9], perhaps not surprisingly as the cloud functions to store and share private data [10]. The main challenge and dis- advantage users see in the adoption of cloud computing is that they lack full con- trol over the hardware [11]. There are, therefore, several issues related to privacy and security that must be addressed before PCC can be considered reliable. Very often, data stored in the cloud is seen as valuable to those with malicious intent [12]. Storing data and applications in the cloud is becoming very risky. It is very important for users to take personal precautions in order to secure personal, sensitive information—information they would have stored in their local computer device (laptop, desktop, phone, tablet, etc.), and now store in the cloud. It is criti- cal for users to understand the security measures that the cloud provider has in place [13]. Predicting technology usage and adoption has become a topic of mainstream study [14]. The rapidly growing importance of technologies has led researchers to study user technology acceptance intensively. Negative attitudes toward a tech- nology, its ease of use, and its usefulness may negatively impact the success of that technology. Indeed, several IT scholars considered the user’s acceptance of a technology to be the key success factor for the adoption of that technology [15]. The remaining of the paper is organized as follows: in the next section, we pre- sent the objectives of the study. Section 2 discusses and articulates our theoretical framework. Section 3 presents the research questions and hypothesis. The popula- tion sample information are discussed in section 4. A detailed discussion of the study’s data collection and validation are provided in section 5. Section 6 discusses the data analysis of the study. Section 5 presents methods used for data collections. Section 6 discusses the data analysis. Section 7 discusses our findings; and additional findings are dis- cussed in section 8. Our recommendation and discussion are presented in section 9. Finally, section 10 concludes the paper. 2 Theoretical Framework This research was deductive in nature. Therefore, a quantitative method was selected to understand user’s acceptance of PCC. In particular, a non-experimental quantitative approach was used. The theoretical framework utilized in this study
  • 28.
    Understanding User’s Acceptanceof Personal Cloud Computing 5 was based on TAM—a widely recognized model in the field of IT, introduced by Davis in 1986 [16]. Davis [16, 17] recommended TAM as the best model for in- vestigating end user attitudes towards and acceptance or rejection of a technology. According to Gao [18], “TAM can serve the purpose of predicting user acceptance of a technology before the users get heavily involved in the technology and thus is a cost-effective tool in screening potential candidate systems or programs” (p. 3). This theoretical framework was used in this study to examine factors influencing PCC adoption. TAM proposes two independent variables—perceived ease of use, and perceived usefulness (PU) of a technology—to predict the user’s attitude toward adopting a technology [18]. Davis [16, 17] defined PU as the degree to which a user believes that the adoption of a particular technology will improve the performance of his or her job. The perceived ease of use, on the other hand, is the degree to which a user believes that using a particular technology would be effortless [17]. Since the purpose of this study was to understand users’ thoughts, experiences, expectations, and security concerns with respect to the adoption of PCC, TAM was found to be the most suitable theoretical approach due to its validity and reliability in exploring and explaining users’ attitudes toward using technologies [16]. Cloud computing is a new approach to computing [19], and as new technologies are intro- duced and are adopted, concerns and challenges emerge [20]. Therefore, this study on PCC technology has a legitimate place in research on user technology acceptance. This research study extended TAM to include attitude towards using (ATU) as an additional independent variable. This study adapted a survey instrument tested by Davis [16], and validated by Venkatesh [21]. Overall, this study included three independent variables and one dependent variable. The independent variables are perceived ease of use (PEOU), attitude toward using PCC (ATU) and perceived usefulness of PCC (PU). One dependent variable—Intention to Use PCC (ITC)— was used broadly in this study. 3 Research Questions and Hypothesis 3.1 Research Question 1: How Does Perceived Ease of Use Influence the Acceptance of PCC? H1A: Perceived ease of use positively influences attitude toward the acceptance of PCC. H10: Perceived ease of use has no correlation to attitude toward the acceptance of PCC.
  • 29.
    6 M. Eltayeband M. Dawson The independent variable PEOU determines the degree to which a user believes that using PCC would be effortless. PEOU is measured on a typical scale of seven ordered continuum of response categories: Strongly disagree, Disagree, Slightly disagree, Neutral, Slightly agree, Agree, Strongly agree. 3.2 Research Question 2: How Does Perceived Usefulness of PCC Influence the Acceptance of PCC? H2A: Perceived usefulness positively influences attitude toward the acceptance of PCC. H20: Perceived usefulness has no correlation to attitude toward the acceptance of PCC. The independent variable PU determines the degree to which a user believes that the adoption of PCC would improve the performance of his or her job. PU is measured on a typical scale of seven ordered continuum of response categories: Strongly disagree, Disagree, Slightly disagree, Neutral, Slightly agree, Agree, Strongly agree. Research Question 3: How does attitude toward using PCC influence acceptance of PCC? H3A: There will be a correlation between attitude toward using PCC and the user’s acceptance of PCC. H30: There will be no correlation between attitude toward using PCC and the user’s acceptance of PCC. The independent variable (ATU) determines the degree to which a user’s acceptance of PCC relates to that user’s attitude toward using PCC. ATU is meas- ured across a typical scale of seven ordered continuum of response categories: Strongly disagree, Disagree, Slightly disagree, Neutral, Slightly agree, Agree, Strongly agree. 4 Population Sample This study used a simple random sample from Survey Monkey engineering and IT professionals panels. The minimum representative sampling size (n) was estimated to be 384 participants for this study, based on a confidence interval of 5% and a confidence level of 95%. As many participants as possible were included to increase the accuracy of statistical sampling data.
  • 30.
    Understanding User’s Acceptanceof Personal Cloud Computing 7 A total of 464 participants were randomly chosen to participate in the study. However, only 399 of the chosen participants fully completed the survey; 20 par- ticipants opted out and 45 were disqualified either with unanswered questions or with providing partial data. Only fully completed responses were admitted. There was a 95.69% completion rate of surveys. Thus, the number of completed responses exceeded the estimated, representative minimal sample size of 384. Several items in the survey—gender, age range, education, state, and census region—were included to further describe demographic characteristics of the sample. 5 Data Collection and Validation This study used a web survey to collect data from participants. The survey was hosted by SurveyMonkey.com, which is considered one of the leading providers of online survey solutions. The identity of participants was kept confidential and anonymous. Participant had the right to withdraw from participation at any time. Participants were required to complete a consent form as soon as they login to the SurveyMonkey.com. The consent form store collected information confidentially. Information collected by the survey included: gender, age range, state of residence, and level of education. The survey questions in this study were designed to express a clearly negative or positive opinion and avoided neutral opinions to solicit more definitive responses. The researcher transcribed the data collected through Survey Monkey into digital documents. Data was downloaded by the researcher after the comple- tion of data collection. Only fully completed surveys were employed in this study. Some participants were disqualified either with unanswered questions or with providing partial data. Incomplete responses and partial data were completely discarded. Additionally, Survey data was assessed for multicollinearity, homosce- dasticity, linearity, and normality [22]. 6 Data Analysis The multiple regression test was performed as follows: (1) predictors were se- lected using their semi-partial correlation with the outcome; (2) predictors were entered into the model based on a mathematical method using Statistical Package for the Social Sciences (SPSS) Version 19.0; (3) the selection of predictors was performed in steps [23]. Descriptive statistics, ANOVA, Chi-square, and Multiple regressions were per- formed to explore the relationship between the continuous dependent variable (ITU) and independent variables (PEOU, PU, and ATU). Several descriptive sta- tistics techniques were used to depict the sample population characteristics. ANOVA was used to analyze both dependent and independent variables. In addi- tion, the multiple regression test was performed to assess the impact of each independent variable (PU, PEOU, and ATU) on the dependent variable (ITU).
  • 31.
    8 M. Eltayeband M. Dawson 7 Findings TMultiple regressions were performed to explore the relationship between the continuous dependent variable (ITU) and independent variables (PEOU, PU, and ATU). This research study tested the relationship between perceived ease of use, usefulness, attitude toward using PCC, and the acceptance of PCC. The model’s adequacy was tested in terms of normality, linearity, and collinearity [24]. 7.1 First Regression Model The first regression was performed to determine the relationship between the in- dependent variable PEOU and the dependent variable ITU. Six predictors of the independent variable PEOU were tested to address the first research question. The relationship between the predictors and the outcome were measured using a step- wise method, so that the unique contribution of each predictor could be assessed to explain variance of the outcome [24]. The following research question and hypothesis were tested at this stage: How does perceived ease of use influence the acceptance of PCC? H10: Perceived ease of use has no correlation to the acceptance of PCC. The results of the regression analysis demonstrated a positive correlation between PEOU and the acceptance of PCC. It was found that approximately 23.5% of the variance in the acceptance of PCC can be accounted for by PEOU. Therefore, the null hypothesis was rejected and the alternative was supported. This result is consistent with other studies showing that there is a positive cor- relation between PEOU and the user’s acceptance of a technology. Davis [16] argued that perceived ease of use positively influence attitude toward using a technology. Perceived ease of use plays an important role in determining and pre- dicting the user’s intention to use a technology [25]. Ramgovind [26] stated “The success of modern day technologies highly depends on its effectiveness of the world’s norms, its ease of use by end users and most importantly its degree of information security and control” (p. 1). 7.2 Second Regression Model The second regression was performed to determine the relationship between the independent variable PU and the dependent variable ITU. Five predictors of the independent variable PU were tested to address the first research question. A stepwise regression was performed to build the model. The unique contribution of each predictor was measured to explain the variance of the outcome [24]. The following research question and hypothesis were tested at this stage:
  • 32.
    Understanding User’s Acceptanceof Personal Cloud Computing 9 How does perceived usefulness of PCC influence the acceptance of PCC? H20: Perceived usefulness has no correlation to attitude toward the acceptance of PCC. The results of the regression analysis demonstrated a positive correlation between PU and the acceptance of PCC. It was found that approximately 78.2% of the variance in the acceptance of PCC can be accounted for by PU. Therefore, the null hypothesis was rejected and the alternative was supported. This result is consistent with other studies showing that there is a positive correlation between PU and the user’s acceptance of a technology. 7.3 Third Regressions Model The third regression was performed to determine the relationship between the independent variable ATU and the dependent variable ITU. Four predictors of the independent variable ATU were tested to address the first research question. The relationship between the predictors and the outcome were measured using stepwise regression. The unique contribution of each predictor was measured to explain the variance of the [24]. The unique contribution of each predictor is measured to explain the variance of the outcome. The following research question and hypothesis were tested at this stage: How does attitude toward using PCC influence user’s acceptance of PCC? H30: There will be no correlation between attitude toward using PCC and user’s acceptance of PCC. The independent variable ATU was used for determining the degree in which there is a correlation between attitude toward using PCC and users’ intention to use. The results of the regression analysis demonstrated a significant correlation between ATU and the acceptance of PCC. It was found that approximately 38.2% of the variance in the acceptance of PCC can be accounted for by ATU. Therefore, the null hypothesis was rejected and the alternative was supported. 8 Additional Findings Statistically significant differences were found between age group means, as indi- cated by results of the one-way ANOVA (F (5, 2.801)=2.801, p=.017). The output result of the one-way ANOVA showed that the age group significantly contributed to the variation in the respondent’s acceptance of the PCC technology. Because the output result of the one-way ANOVA test demonstrated significant differences between the age groups, a Post Hoc test was conducted to further investigate which means were significantly different from each other. The Post Hoc test result
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    PORTRAITS OF THEGREAT TROTTERS Size, 25×23. Price, $3. Goldsmith Maid, to sulky, 2.14. Lula, to sulky, 2.15. Smuggler, to sulky, 2.15¼. American Girl, to sulky, 2.16½. Occident, to sulky, 2.16¾. Hopeful, to sulky, driven by Mace, 2.17¼. Judge Fullerton, to sulky, 2.19. Red Cloud, to sulky, 2.18. Lucy, to sulky, 2.18¼. Lady Thorn, to wagon, 2.24; to sulky, 2.18¼. Music, to sulky, 2.21¼. Thos. Jefferson, to sulky, 2.23. George Wilkes, to sulky, 2.22. Joe Elliott, to sulky, 2.15½. Tom Moore, to sulky, 2.31. Dan Rice, better known as Rhode Isl’d, to wagon, 2.81½; s’ky, 2.23½. Trustee, to sulky, twenty miles in 59min. 35½sec. Rarus, to sulky. Rarus to sulky, and Great Eastern to saddle. Size, 22×28. Price, $1.50. Com. Vanderbilt, to wagon. Jack Rossiter, to sulky. RUNNING HORSES.
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    The King ofthe Road, Dexter and Bonner. American Girl, and Lady Thorn. Goldsmith Maid, and American Girl. Billy Boyce—Pacer, To Saddle, 2:14¼. Dexter—To Sulky, 2:17¼. Monk. $ 5.50 King Lear Wig and Beard. 12.00 Clown Wigs By sending the size of Hat worn, a good fit can be obtained. Beards, Moustaches, Etc. Full Beard. $3.00 Extra long. 4.00 Side Whiskers and Moustache, on wire. Side Whiskers and Moustache, on gauze. 3.00 Moustaches, all colors, each. 50 Imperials. 50 Banjos. Stage Banjo, 14 Screws. $15.00 Solo Banjo, 15 Screws. 18.00 Rosewood Banjo, 16 Screws. 25.00 Solid Rosewood Banjo, 16 Screws. 35.00 Silver Plated, 16 Screws. 45.00
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    Sundries. Tambourines, Violins, from10.00 Accordeons, Concertinas, Mouth Harmonicons, 32 Holes. Best Ebony or Rosewood Bones, Triangles, each. 1.50 Burnt Cork, the Receipt for making it. 25 Magic Lanterns, from 2.00 Albums, for 50 Cartes. 2.00 Albums, with 50 Cartes of Celebrities. 4.00 Ivory Sleeve Buttons—Horse, Dog, Stag, Frog, Turtle, Owl, and Egyptian Heads, with glass eyes, per pair 75c. Faro and Keno Goods Etc. Ivory Faro Checks. FIRST QUALITY. 1½ in., plain, per hundred. $35.00 19 /16 “ “ “ “ 7.50 1⅝ “ “ “ “ 40.00 1½ “ fancy, “ “ 37.50 19 /16 “ “ “ “ 40.00 1⅝ “ “ “ “ 42.50 SECOND QUALITY. 17 /16 in., plain, per hundred 27.50
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    Card Punches, steel4.00 Card Punches, silver, with hinge 10.00 Trimming Shears, double edged Cutter 35.00 Trimming Shears, Knife small 20.00 Trimming Shears, Knife large 50.00 Stripper Plates, to use with Knife, per set 5.00 Card Press, without cover 6.00 Card Press, with slide cover, compartment for dealing Box, lock and key 10.00 The same, to hold a dozen packs, Double 14.00 Case Keepers, Cards, Wooden markers 12.00 Case Keepers, Cards, Composition markers 15.00 Square Props, per set, 4 in a set 3.00 Case Keepers, finest painted Ivory markers 25.00 Transcriber’s Note: Obvious printer errors corrected silently. Inconsistent spelling and hyphenation are as in the original.
  • 48.
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