31 Slices
Medium 9781601323231

Operational and Organizational Dimensions of the Bid Process Information System (B.P.I.S.)

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

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

133

Operational and Organizational Dimensions of the

Bid Process Information System (B.P.I.S.)

Sahbi Zahaf

Higher Institute of Computer and Multimedia

MIRACL Laboratory, Sfax University, Tunisia sahbi@zahaf.net

Abstract— Bid process translates the techno-economic expertise, which partners build in a cooperative way. It is a key business process which evaluates the results of different trade tasks: hence, it influences the company’s survival and strategic orientations. Therefore, the Information System that supports this process must be characterized by integrity, flexibility and interoperability. Nevertheless, the urbanization approach, on which we rely to implement this system, has to deal with “three fit” problems. To overcome these problems, we suggest addressing these exigencies following an operational dimension which remains responsive to other dimensions: the organizational and decision-making ones. However, the cooperative dimension covers the remaining dimensions. In fact, it ensures the consistency and the interaction between the different dimensions.

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Medium 9781601323231

Keyword Searches with Customized Preferences

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

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

69

Keyword Searches with Customized Preferences

Yu-Chin Liu, Yi-Hsuan Chiang and Yu-Lien Hsieh

Abstract—In accordance with the great business opportunities emerging through SNSs, entrepreneurs strive to explore the potential benefits by analyzing data collected from

SNSs. For example, Google+ attempts to integrate keyword searches with the individual’s social network. In this paper, we propose a new method for considering the common preferences of friends on social networks while ranking the order of related web pages returned from search engines. The simulation shows the proposed method performing well comparing to general search engines.

I. INTRODUCTION

I

NFORMATION searching has become as one of the most important tasks for on-line information retrieval. At present, there are three main methods of information searching on the

Internet: searching by web pages, by directories, and by keywords. For users, tools supporting timely searching are in great demands.

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Medium 9781601323231

Multi-Projects Scheduling Via Non-cooperative Agents Through Heterogeneous Multiprocessor Systems For Energy Efficiency

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

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

73

Multi-Projects Scheduling Via Non-cooperative Agents Through Heterogeneous Multiprocessor Systems For

Energy Efficiency

Marjan Abdeyazdan1, Mohammad Reza Moini2

1

Department of Computer Engineering, College of Electricity and Computer, Mahshahr branch, Islamic Azad

University, Mahshahr, Iran. e-mail: abdeyazdan87@yahoo.com , m.abdeyazdan@mahshahriau.ac.ir

2

Department of Computer Engineering, College of Electricity and Computer, Mahshahr branch, Islamic Azad

University, Mahshahr, Iran.

e-mail: rezamoini_it@yahoo.com

Abstract. Multiprocessor systems started a revolution in high performance computing that brought about fundamental changes in computation.

This article examines scheduling of multiprojects, in which each project is assumed as an agent.

Scheduling is done by assignment of agents to homogeneous and heterogeneous processors in parallel where every agent is comprised of some tasks and the related tasks in each agent constitute task graphs. Every agent has one initial point and a final point. To go from the initial point to the final point, there are some strategies, namely, various scenarios, which are selected based on the two objectives of minimizing energy consumption

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Medium 9781601323231

A Knowledge Based Selection Framework for Cloud Services

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

26

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

A Knowledge Based Selection Framework for

Cloud Services

Gülfem Isiklar Alptekin1 and S. Emre Alptekin2

Computer Engineering, Galatasaray University, İstanbul, Turkey

2

Industrial Engineering, Galatasaray University, İstanbul, Turkey

1

Abstract - Cloud computing is a scalable services consumption and delivery platform where resources

(computational processing power, storage, etc.) are retrieved from the network from anywhere in the world. The inherent complexity and elasticity of the cloud platform products makes their selection a difficult decision for their prospective customers. This paper proposes a multi-criteria based decision support tool which incorporates customer expectations and product attributes and their interrelationships into the decision process. Based on this knowledge the customers are able to rank various alternatives.

The proposed knowledge based decision framework is based on quality function deployment and analytic network process.

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Medium 9781601323231

Efficient Image Segmentation Algorithm for Mobile Devices

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

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

41

Efficient Image Segmentation Algorithm for Mobile Devices

Mark Smith

University of Central Arkansas

Conway, Arkansas 72035

Abstract

An efficient image segmentation algorithm utilized for mobile applications running on the iPhone’s iOS platform is presented. Mobile devices such as the iPhone have limited CPU and memory resources, thus presenting a more challenging task when implementing complex algorithms such as image segmentation. The image segmentation utilized in this work splits the image into real-world objects that are numbered for the user to either select for further processing. First, a color quantization algorithm is applied to the entire image thus simplifying the image to only 16 available colors. Next, a fast texture measurement utilizing the co-occurrence matrix is applied to entire image using a pre-selected neighborhood of interest. Multiple regions are then automatically merged based on a color comparison measurement extracted at each object’s boundary. The resulting regions are then displayed to the user for further analysis or selection.

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