31 Slices
Medium 9781601323231

Session - Knowledge and Information Visualization + Imaging Science and Applications

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

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

Session - Information and Knowledge Engineering and Management + Feature Extraction and AI

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF
Medium 9781601323231

Collaborative Shared Awareness: Human-AI Collaboration

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

10

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

Collaborative Shared Awareness: Human-AI Collaboration

James A. Crowder, John N. Carbone

Raytheon Intelligence, Information, and Services

16800 E. Centretech Parkway, Aurora, Colorado 80011

Abstract - The ability to reason within an autonomous information processing system denotes the ability to infer about information, knowledge, observations and experiences, and affect changes within the system to perform new tasks previously unknown, or to perform tasks already learned more efficiently and effectively [Crowder

1996]. The act of reasoning and inferring allows an autonomous system to construct or modify representations of concepts or knowledge that the system is experiencing and learning. Reasoning allows an Artificially Intelligent

System (AIS) to fill in skeletal or incomplete information or specifications about one or more of its domains (selfassessment).

The research described here details architectures and algorithms for a cognitive system of

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