3044 Slices
Medium 9781601323255

A Simulation Approach for Traffic Management

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

92

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

A Simulation Approach for Traffic Management

Karmel Manaa

Engineering and Environment Faculty, Northumbria University, Newcastle, England

1

Abstract- The traffic congestion problems have been aggravated lately; becoming an annoying daily phenomenon accompanied negative impacts on human health, environment and economy.

Conventional traffic management methodologies failed to accommodate the ever-increasing of mobility needs. Hence, the necessity of modern approaches was raised to handle the problem; technology has the power of solving our road congestions dilemmas, it’s challengeable but worthwhile. This paper presents a notion of traffic management methodology based on a smart control system that varies the street flow by alterable luminous road lanes and signs, according to circumstances in that time to redistribute the road usage priority. Three main scenarios were considered and simulated on Witness Software to find the efficiency of the notion, a noticeable enhancement in the traffic flow was found. Finally, a value and risk assessment performed to find the possibilities and challenges of the projects realistic implementation.

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Medium 9781601322586

MCM Based Cluster Algorism for Ocean Sensor Networks

Hamid R. Arabnia, Hiroshi Ishii, Minoru Ito, Hiroaki Nishikawa, Fernando G. Tinetti, George A. Gravvanis, George Jandieri, and Ashu M. G. Solo CSREA Press PDF

404

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

MCM Based Cluster Algorism for Ocean Sensor Networks

G

Hwanghyuk Lee*, Sang-Eon Park**, Young-Jun Chung*

* Computer Science Department, Kangwon National University, Chunchon, Korea

** Department of Mathematics and Computer Science, Salisbury University, MD, USA

{yhhyuk, ychung}@kangwon.ac.kr, sxpark@salisbury.edu

Abstract

OSN runs at the worst operating environments.

OSN requires more reliable and more stable operating conditions to extend the network lifetime compared to other WSN. In this paper, we propose a

MCM based clustering algorithm for OSN. As properly managing the number of cluster member nodes, our proposed algorithm increases the lifetime of network nodes, enhances the network efficiency, and predicts the network performance and reliability. In addition, NS-2 simulation results show that our algorithm has the better performance compared to LEACH and extends the network

lifetime.

Keywords: OSN, WSN, algorithm, network reliability

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Medium 9781601323118

Relevance of Information in Cell Signaling Pathways Using Default Logic

Hamid R. Arabnia, Quoc-Nam Tran, Mary Q. Yang, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

16

Int'l Conf. Bioinformatics and Computational Biology | BIOCOMP'14 |

Relevance of Information in Cell Signaling Pathways using Default

Logic

A. Doncescu1 , P. Siegel2 , and T. Le1

1 LAAS-CNRS, University of Toulouse, Toulouse, France

2 Aix Marseille Université, CNRS, LIF UMR 7279, 13288, Marseille, France

Abstract— Cell Signaling Pathway Simulation is a very useful tool in the drug discovery process. These simulation programs can be divided into dynamic simulation and

Knowledge-Based Discovery. In the first case the simulation is based on differential equations and could be considered in "real-time", meanwhile in the case of Knowledge Based

Discovery Programs KBDP the consistency of the model is checked. The most efficient KBDP approach is based on

first order logic (FOL). In this paper, algorithms based on Default Logic are proposed to check-out the consistency of the simplest representation of DNA double strand breaks. DNA double-strand breaks are among the most severe genomic lesions. This representation is concise and adequat for keeping the flow of information represented by gene expression, receptor and protein structure through the apoptosis and cell cycle.

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Medium 9781601323187

Research and Implementation of a New Cloud Server

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

Int'l Conf. Grid & Cloud Computing and Applications | GCA'14 |

79

Research and Implementation of a New Cloud Server

1, 3, 5

Hua Nie1, Xiaojun Yang2, Chaoqun Sha3, Yanping Gao4, and Keping Long5

School of Computer and Communication Engineering, University of Science and Technology Beijing.

Beijing, China

2

Dawning Information Industry Co., Ltd. Beijing, China

4

Institute of Computing Technology, Chinese Academy of Sciences. Beijing, China

4

Loongson Technology Co., Ltd. Beijing, China

Abstract - Instead of all using TOR schemes, an approach building a cloud server on top of a high-performance fabric is presented in this paper. The advantage is to provide both high performance/cost and performance/Watt compared with the existing method. A FPGA-based system controller integrated with shared networking, shared storage, and interconnect fabric controller is designed and implemented to interconnect a set of lightweight server processors for building a highdensity server. All the processors can share the networking and storage resources through an inter-system interconnect fabric. For the 64-processor prototyping system, the evaluating results show the cloud server not only keeps some traditional cluster advantages such as OS compatibility, but also achieves the better scalability, high performance/cost and high performance/Watt for workloads.

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Medium 9781601323118

Dynamic Protein-protein Interaction Networks and the Detection of Protein Complexes: An Overview

Hamid R. Arabnia, Quoc-Nam Tran, Mary Q. Yang, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

138

Int'l Conf. Bioinformatics and Computational Biology | BIOCOMP'14 |

Dynamic protein-protein interaction networks and the detection of protein complexes: an overview

Eileen Marie Hanna and Nazar Zaki

College of Information Technology, United Arab Emirates University, Al Ain, Abu Dhabi, UAE

Abstract - Developing computational approaches for the

detection of protein complexes in protein-protein interaction networks continues to be an evolving area of research. These approaches seek to complement the experimental methods which are usually expensive in terms of time and cost. A protein-protein interaction dataset is typically modeled as a static network whose vertices and edges respectively represent all the proteins and their interconnections. Despite the agreeable accuracies attained by various computational methods when applied on such networks, their additional improvements seem to face some limitations. It is believed that the more enrichment with biological information is added to the interaction networks and complex-detection algorithms, the better will be the overall quality of the results. In this paper, we stress on the importance of reflecting the dynamic nature of protein interaction networks as a primary enhancement phase and we highlight possible aspects by which it could be acquired.

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