Distributed Virtual Environment systems simulate the behaviour and activities of a great number of users interacting in a virtual world over a wide area network. The sizes of the virtual worlds and the tremendous numb...
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ISBN:
(纸本)9789639799455
Distributed Virtual Environment systems simulate the behaviour and activities of a great number of users interacting in a virtual world over a wide area network. The sizes of the virtual worlds and the tremendous number of users that DVEs are called to support require additional bandwidth and computational resources. For handling these growing requirements a lot of work has been done both to the direction of alternative architectural solutions as well as to techniques and algorithms for handling the limitations of these environments. For supporting large-scale DVEs, extended infrastructure is needed in terms of both hardware and software. However, both researchers and application designers do not always have access to such extended infrastructure and the assessment and evaluation of developed techniques becomes extremely difficult. To this direction, this paper presents a simulation modelling tool for networked servers DVEs that could be used by designers for simulating the performance of their approaches under different scenarios.
In this paper we show a platform which allows for education and training of a number of essential embedded skills. The Java optimized processor (JOP) is open source and has been used in several educational and trainin...
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The growing use of case-based reasoning (CBR) systems on the Web has brought with it increased awareness of the Web-scale case base maintenance (CBM). While most existing CBM policies and approaches, which were design...
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The computerized modeling of cognitive visual information has been a research field of great interest in the past several decades. The research field is interesting not only from a biological perspective, but also fro...
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ISBN:
(纸本)9781617825583
The computerized modeling of cognitive visual information has been a research field of great interest in the past several decades. The research field is interesting not only from a biological perspective, but also from an engineering point of view when systems are developed that aim to achieve similar goals as biological cognitive systems. This paper briefly describes a general framework for the extraction and systematic storage of low-level visual features, and demonstrates its applicability in image categorization using a linear categorization algorithm originally developed for the characterization of text documents. The performance of the algorithm together with the newly developed feature array was evaluated using the Caltech 101 database. Extremely high (95% and higher) success rates were achieved when distinguishing between pairs of categories using independent test images. Efforts were made to scale up the number of categories using a hierarchical, branch-and-bound decision tree, with limited success.
Flexible Manufacturing Systems (FMSs) cope with multi-product, usually small sized production. In this research work we investigate the use of evolutionary methods to solve the linear or single-row layout problem, whi...
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Network biology methods have been promising in linking diseases, genes, and drugs. In this study, we propose a novel computational method to construct drug-drug correlation networks, which consist of drug compounds as...
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ISBN:
(纸本)9781605581668
Network biology methods have been promising in linking diseases, genes, and drugs. In this study, we propose a novel computational method to construct drug-drug correlation networks, which consist of drug compounds as network graph nodes and correlated protein-drug profiles above a pre-determined threshold as network graph edges. This computational method is based on extensions of related work on identifying disease-specific proteins within protein-protein sub-networks, and mining protein-drug association profiles from biomedical literature. Our method provides a quantitative framework to compare how each drug compound from one therapeutic area is correlated with other drug compounds in other therapeutic areas, using a drug's protein-drug association profile mined from biomedical literature. We applied this method to the study of drug re-purposing and found that two breast cancer drugs "Mitomycin" and "Bleomycin" may be top drug candidates for treating pancreatic cancers. Copyright 2009 ACM.
In recent years, computer-generated interactive virtual characters, called Embodied Conversational Agents (ECAs), are subjects of considerable ongoing research. Nevertheless, their conversational abilities are mediocr...
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Cooperative communications have been demonstrated to be effective in combating the multiple fading effects in wireless networks, and improving the network performance in terms of adaptivity, reliability, data throughp...
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ISBN:
(纸本)9781424428472
Cooperative communications have been demonstrated to be effective in combating the multiple fading effects in wireless networks, and improving the network performance in terms of adaptivity, reliability, data throughput and network life time. In this paper, we investigate the use of cooperative communications for quality of service (QoS) provisioning in resource-constrained wireless sensor networks, and propose MRL-CC, a Multi-agent Reinforcement Learning based multi-hop mesh Cooperative Communication mechanism for wireless sensor networks. In order to disseminate data reliably in MRL-CC, a multi-hop mesh cooperative structure is first constructed. Then a cooperative mechanism with cooperative partner assignments, and coding and transmission schemes is implemented using a multi-agent reinforcement learning algorithm. We compare the network performance of MRL-CC with MMCC [1], a Multi-hop Mesh structure based Cooperative Communication scheme, and investigate the impacts of network traffic load, interference and sensor node's mobility on the network performance. Simulation results show that MRL-CC performs well in terms of a number of QoS metrics, and fits well in large-scale networks and highly dynamic environments.
In this paper, we investigate the use of cooperative communications for reliable data dissemination in wireless sensor networks. We first identify the disadvantages of some existing cooperative schemes. While the prev...
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ISBN:
(纸本)9788955191387
In this paper, we investigate the use of cooperative communications for reliable data dissemination in wireless sensor networks. We first identify the disadvantages of some existing cooperative schemes. While the previously proposed "multihop mesh cooperative transmission structure" addresses these disadvantages, it suffers from large end-to-end delays during data disseminations due to its random value-based forwarding node selection scheme. This paper proposes a novel distance-based forwarding node selection scheme that yields smaller end-to-end delays. We present extensive simulation results that verify the effectiveness of the proposed data dissemination scheme.
Abstract The computerized modeling of cognitive visual information has been a research field of great interest in the past several decades. The research field is interesting not only from a biological perspective, but...
详细信息
Abstract The computerized modeling of cognitive visual information has been a research field of great interest in the past several decades. The research field is interesting not only from a biological perspective, but also from an engineering point of view when systems are developed that aim to achieve similar goals as biological cognitive systems. This paper briefly describes a general framework for the extraction and systematic storage of low-level visual features, and demonstrates its applicability in image categorization using a linear categorization algorithm originally developed for the characterization of text documents. The performance of the algorithm together with the newly developed feature array was evaluated using the Caltech 101 database. Extremely high (95% and higher) success rates were achieved when distinguishing between pairs of categories using independent test images. Efforts were made to scale up the number of categories using a hierarchical, branch-and-bound decision tree, with limited success.
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