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Medium 9781601323248

Multiresolution Image Compression using Non Linear Transformations

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

407

Multiresolution image compression using non linear transformations

Ioannis Dologlou, and Stylianos Bakamidis

ATHENA–Research and Innovation Center in

Information, Communication and Knowledge Technology, Athens, Greece

Abstract - This paper presents a new non-linear algorithm for image compression operating at different resolution levels and exploiting the binary versions of the intermediate images. The decimation factor that applies between the resolution levels along with the efficient coding of the binary signals allow considerable compression rates while maintaining the image quality. Lossless compression algorithms based on arithmetic coding are used to compress the binary files that are created during the image decomposition. The method was compared experimentally against the existing standard JPEG using the well known reference image “lenna” and it was shown that for similar compression rates it is blocking artifact free, offering at the same time higher peak SNR.

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Medium 9781601322395

Flash reactivity : adaptative models in recommender systems

Robert Stahlbock; Gary M. Weiss; Mahmoud Abou-Nasr; and Hamid R. Arabnia (Editors) Mercury Learning and Information PDF

Int'l Conf. Data Mining | DMIN'13 |

111

Flash reactivity : adaptative models in recommender systems

J. Gaillard1 , M. El-Beze1 , E. Altman2 and E. Ethis3

1 SFR Agorantic, University of Avignon, France

2 Maestro, INRIA Sophia-Antipolis, France

3 Norbert Elias Center, University of Avignon, France

Abstract— Recommendation systems take advantage of products and users information in order to propose items to targeted consumers. Collaborative recommendation systems, content-based recommendation systems and a few hybrid systems have been developed. We propose a dynamic and adaptive framework to overcome the usual issues of nowadays systems. We present a method based on adaptation in time in order to provide recommendations in phase with the present instant. The system includes a dynamic adaptation to enhance the accuracy of rating predictions by applying a new similarity measure. We did several experiments on

films data from Vodkaster, showing that systems incorporating dynamic adaptation improve significantly the quality of recommendations compared to static ones.

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Medium 9781601323255

Meaningful Touch and Gestural Interactions with Simulations Interfacing via the Dart Programming Language

Hamid R. Arabnia, Leonidas Deligiannidis, Jane You, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Modeling, Sim. and Vis. Methods | MSV'14 |

139

Meaningful Touch and Gestural Interactions with Simulations

Interfacing via the Dart Programming Language

T. H. McMullen and K. A. Hawick

Department of Computer Science, University of Hull, Cottingham Road, Hull HU6 7RX, UK.

Email: t.h.mcmullen@hull.ac.nz; k.a.hawick@hull.ac.uk,

Tel: +44 01482 465181 Fax: +44 01482 466666

June 2014

ABSTRACT

Interactive technologies are improving the way in which we are able to communicate with devices. The rise in availability of products, such as the Leap Motion, Kinect and touch screen devices, means that we are able to program applications that significantly increase the potential input from human users. These devices are able to be programmed to work together allowing for situations where one device may improve the functionality of another. In this paper we discus use of the Leap Motion and touch screens in our research into interactive simulations. We use the Dart programming language as a suitable vehicle to integrate together interface components to these two different technologies. We show how combinations of these devices can lead to new and meaningful ways to communicate with applications over and beyond the capabilities of conventional input methods for simulations.

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Medium 9789351382669

4

Ajay Raj Parashar, Deepti Mittal Laxmi Publications PDF

Chapter

4

Authentication Applications

Kerberos

Kerberos is an authentication service developed as part of Project Athena at MIT. The problem that Kerberos addresses is this: Assume an open distributed environment in which users at workstations wish to access services on servers distributed throughout the network. We would like for servers to be able to restrict access to authorized users and to be able to authenticate requests for service. In this environment, a workstation cannot be trusted to identify its users correctly to network services.

Kerberos provides a centralized authentication server whose function is to authenticate users to servers and servers to users. Kerberos relies exclusively on symmetric encryption, making no use of public-key encryption. Two versions of Kerberos are in common use.

Version 4 implementations still exist. Version 5 corrects some of the security deficiencies of version 4 and has been issued as a proposed Internet Standard (RFC 1510).

MOTIVATION

If a set of users is provided with dedicated personal computers that have no network connections, then a user’s resources and files can be protected by physically securing each personal computer. When these users instead are served by a centralized time-sharing system, the time-sharing operating system must provide the security. The operating system can enforce access control policies based on user identity and use the logon procedure to identify users.

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Medium 9781601323699

SESSION Security Applications

Kevin Daimi, Hamid Arabnia, CSREA Press PDF

Int'l Conf. Security and Management | SAM'16 |

75

SESSION

SECURITY APPLICATIONS

Chair(s)

Dr. Greg Vert

ISBN: 1-60132-445-6, CSREA Press ©

76

Int'l Conf. Security and Management | SAM'16 |

ISBN: 1-60132-445-6, CSREA Press ©

Int'l Conf. Security and Management | SAM'16 |

77

Strategic Risk Management in Counter-Terrorism for the Railbound Public Transport

Merging Qualitative and Quantitative Operations Research Techniques

Martin Zsifkovits*, Stefan Pickl

Universität der Bundeswehr München

Institute for Informatics, Mathematics, and Operations Research

Neubiberg, Germany

*martin.zsifkovits@unibw.de, stefan.pickl@unibw.de

*Corresponding author

Abstract—Every modern state is strongly dependent on a functioning infrastructure. This makes it even more vulnerable and furthermore attractive for terroristic attacks. The situation gets even more severe when people are directly involved, such as in public transport, as they are – at least for some groups of terrorists – the main aim of attacks. In the paper at hand we propose the standardized ISO31000 risk management framework coupled with various qualitative and quantitative Operations

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Medium 9781601322470

Session - International Workshop on Intelligent Linguistic Technologies - Ilintec'13

Hamid R. Arabnia; David de la Fuente; Elena B. Kozerenko; Peter M. LaMonica; Raymond A. Liuzzi; Todd Waskiewicz; George Jandieri; Ashu M. G. Solo; Ivan Nunes da Silva; Fernando G. Tinetti; and Fadi Thabtah (Editors) Mercury Learning and Information PDF
Medium 9781601322395

Using Data Mining to Analyze Donation Data for a Local Food Bank

Robert Stahlbock; Gary M. Weiss; Mahmoud Abou-Nasr; and Hamid R. Arabnia (Editors) Mercury Learning and Information PDF

Int'l Conf. Data Mining | DMIN'13 |

105

Using Data Mining to Analyze Donation Data for a Local

Food Bank

S. Jiang, L. Davis, H. Tavares De Mleo, and J. Terry

Department of Industrial and Systems Engineering, North Carolina A&T State University, Greensboro, NC,

USA

Abstract - Food insecurity is one of the difficult situations a lot of American communities face today. Hunger, particularly experienced by children has serious impacts on the society.

Fighting hunger cannot solely depend on the government assistance programs. Non-profit organizations such as

Feeding America play a very important role in this effort.

These organizations heavily rely on food donations. However, it is not easy to understand donation and hence presents challenges for those organizations to plan and manage their resources. In this research, data mining techniques were applied to analyze donation data from a local food bank and useful information was generated to help the food bank manage their resources.

Keywords: Data Mining, Donation, Food Bank

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Medium 9781601322401

Effective Implementation of e-Learning in Initial Learning Program: A Case Study

Hamid R. Arabnia; Azita Bahrami; Fernando G. Tinetti; Leonidas Deligiannidis; George Jandieri; and Ashu M. G. Solo (Editors) Mercury Learning and Information PDF

10

Int'l Conf. e-Learning, e-Bus., EIS, and e-Gov. | EEE'13 |

Effective Implementation of e-Learning in Initial

Learning Program: A Case Study

Soumya Hari

Corporate ILP Team, Tata Consultancy Services Limited, Trivandrum, Kerala, India

Abstract - Case studies are effective in dealing with factors like creativity, innovation and context. This case study attempts to highlight the outcomes of introducing the concept of e-learning into teaching technical topics like Dotnet, Java,

Mainframe and C++ of the Initial Learning Program at Tata

Consultancy Services Limited in 2012-2013. These findings will be of interest to any organization that plans to implement e-learning methodologies to help its employees learn and remember the initial lessons of software development and the various programming languages with limited faculty support.

The outcome of this case study indicates a stable and prominent increase in the use of e-learning strategies in consort with the traditional methods of training.

Keywords: e-learning, strategy

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Medium 9781601322401

A Comparative Study of Multiple Social Network Sites Based on Google Analytics Data

Hamid R. Arabnia; Azita Bahrami; Fernando G. Tinetti; Leonidas Deligiannidis; George Jandieri; and Ashu M. G. Solo (Editors) Mercury Learning and Information PDF

264

Int'l Conf. e-Learning, e-Bus., EIS, and e-Gov. | EEE'13 |

A Comparative Study of Multiple Social Network Sites

Based on Google Analytics Data

S. M. Horng

Department of Business Administration

National Chengchi University, Taiwan (ROC)

Abstract

This study collects the data from four social network sites to study user behavior. Data are retrieved from their Google Analytics measures, including visits, percentage of new visits, bounce rate, average time on page, and average time on site. Through statistical analyses and in-depth interviews with the founders of the web services, several patterns from analyzing the measures are identified and categorized into two groups, visiting behavior and user behavior. Managerial implications are proposed and discussed based on the analyzed results and discussions with practitioners.

Keywords: Google Analytics, user behavior, social network sites

Introduction

The term “web 2.0” was first documented by O’Reilly (2005) and its impact on the internet has been studied widely. An important development of web 2.0 services is the increasing user-generated content on the Web, and the ability to combine parts of it to form new content. Three web 2.0 collaborative tools, Blogs, Mashups, and Wikis

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Medium 9781601323132

Generating Well-Behaved Learning Curves: An Empirical Study

Robert Stahlbock, Gary M. Weiss, Mahmoud Abou-Nasr, Hamid R. Arabnia CSREA Press PDF

210

Int'l Conf. Data Mining | DMIN'14 |

Generating Well-Behaved Learning Curves: An Empirical Study

Gary M. Weiss and Alexander Battistin

Department of Computer & Information Science, Fordham University, Bronx NY, USA

Abstract—Data mining is an important discipline that helps extract useful knowledge from data in business, science, health, and engineering domains. Classification is one of the most common and important data mining tasks. Achieving good classification performance is critical and performance is known to be linked to the amount of available training data. Learning curves, which describe the relationship between training set size and classifier performance, can be used to help determine the optimal amount of training data to use when there are costs associated with procuring labeled data. For learning curves to be helpful, they should be good predictors of future performance, which means that they should be “well-behaved” (i.e., smooth and monotonically nondecreasing). This paper describes how various factors, such as the classification algorithm and experiment methodology (e.g., random sampling vs. cross validation), affect the behavior of learning curves.

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Medium 9781601323248

Effect of AWGN Parameters Estimation on Accurate Denoising Process

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF

234

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

Effect of AWGN Parameters Estimation on Accurate

Denoising Process

Huda Al-Ghaib

Reza Adhami

Electrical and Computer Engineering

Electrical and Computer Engineering

The University of Alabama in Huntsville

The University of Alabama in Huntsville

Huntsville, AL 35899

Huntsville, AL 35899

hag0002@eng.uah.edu

adhamir@uah.edu

ABSTRACT

The image denoising process attempts to restore a noiseless image from its noisy observation. When the noise is of an unknown source and distribution, it is assumed to have an additive white Gaussian noise

(AWGN) distribution. AWGN is characterized by its mean and variance. Denoising digital images of

AWGN is a challenging process. An investigation of the relationship between accurate estimation of noise parameters and denoising process is presented in this research. Ant colony optimization (ACO) and region merging algorithms are utilized to estimate noise variance. The denoising process is implemented using wavelet shrinkage operation and the estimated variance. A commonly used metric for measuring the efficiency of denoising algorithms is the peak signal to noise ratio (PSNR). Experimental results based on

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Medium 9781601322586

A Fault-Tolerant Approach to Distributed Applications

Hamid R. Arabnia; Hiroshi Ishii; Minoru Ito; Hiroaki Nishikawa; Fernando G. Tinetti; George A. Gravvanis; George Jandieri; and Ashu M. G. Solo (Editors) Mercury Learning and Information PDF

Int'l Conf. Par. and Dist. Proc. Tech. and Appl. | PDPTA'13 |

23

A Fault-Tolerant Approach to Distributed Applications

T. Nguyen1, J-A. Desideri2, and L. Trifan1

INRIA, Grenoble Rhône-Alpes, Montbonnot, Saint-Ismier, France

2

INRIA, Sophia-Antipolis Méditerranée, Sophia-Antipolis, France

1

Abstract - Distributed computing infrastructures support system and network fault-tolerance, e.g., grids and clouds.

They transparently repair and prevent communication and system software errors. They also allow duplication and migration of jobs and data to prevent hardware failures.

However, only limited work has been done so far on application resilience, i.e., the ability to resume normal execution after errors and abnormal executions in distributed environments. This paper addresses issues in application resilience, i.e., fault-tolerance to algorithmic errors and to resource allocation failures. It addresses solutions for error detection and management. It also overviews a platform used to deploy, execute, monitor, restart and resume distributed applications on grids and cloud infrastructures in case of unexpected behavior.

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Medium 9781601323217

Big Data Anonymization Method for Demand Response Services

Hamid R. Arabnia, Leonidas Deligiannidis, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

76

Int'l Conf. Internet Computing and Big Data | ICOMP'14 |

Big Data Anonymization Method for Demand

Response Services

Kengo Okada, Hiroaki Nishi

Graduate School of Science and Technology, Keio University, Japan okada@west.sd.keio.ac.jp, west@sd.keio.ac.jp

Abstract—A demand response services as smart grid application produces and requires large amount of information about electric power consumption. This data can be regarded as big data and is needed to be anonymized for preserving privacy and reducing the amount. Electric power consumption data must be used carefully because it contains private information. The proposed method can convert data to existence probabilities by considering anonymity. In addition, the proposed method can anonymize data according to a required degree of anonymity. An evaluation of demand response services using data anonymized by the proposed method was performed, and the results show that the error rate of the demand and supply balance was smaller than the required level.

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Medium 9781601324085

Security Management II

Kevin Daimi, Hamid R. Arabnia, George Markowsky, Ashu M. G. Solo (Editors) CSREA Press PDF

Int'l Conf. Security and Management | SAM'15 |

231

Device-based Secure Data Management Scheme in a Smart

Home

Ho-Seok Ryu1, and Jin Kwak2

1

2

ISAA Lab., Department of Computer Engineering, Ajou University, Suwon, Korea

Department of Information and Computer Engineering, Ajou University, Suwon, Korea

Abstract - Due to the developments in IT, smart home services

using network-based smart devices are becoming more diverse. A smart home provides users with numerous services, regardless of time and place, through interactions among users, objects, and services. However, there are security concerns such as data leakage, data forgery, and unidentified access. In case of smart home data is exposure at threats, smart home exist very danger into characteristic of smart home. This paper will examine smart home communication and analyze the security problems and security requirements.

Based on this information, we will propose a device-based secure data management scheme for a smart home.

Keywords: Smart home, Smart devices, Data management,

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Medium 9781601323125

Parallel Scaling Performance and Higher-Order Methods

Hamid R. Arabnia, George A. Gravvanis, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Scientific Computing | CSC'14 |

155

Parallel Scaling Performance and Higher-Order Methods

A. Jared Buckley1 and B. Gaurav Khanna1

1 Physics Department, University of Massachusetts Dartmouth, Dartmouth, MA, USA

Abstract— There is considerable current interest in higherorder methods and also large-scale parallel computing in nearly all areas of science and engineering. In this work, we take a number of basic finite-difference stencils that compute a numerical derivative to different orders of accuracy and carefully study the scaling performance of each, on a parallel computer cluster. We conclude that if one has a code that exhibits a high order of convergence, then there is likely to be no significant gain through cluster parallelism in the context of total execution or “wall clock” time. Conversely, for a low order code that exhibits good parallel scaling, there is insignificant gain through the implementation of a higher-order convergent algorithm.

Keywords: higher-order, finite-difference, parallel, scaling

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