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Burst Transmission and Frame Aggregation for Inter-Vehicle Communications 18

Burst Transmission and Frame Aggregation for Inter-Vehicle C...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Lai, Wei Kuang Lin, Mei-Tso Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung Taiwan

ISBN: (纸本)9781509055043

In vehicular ad hoc networks (VANETs), due to highly mobile and frequently changing topology, available resources and transmission opportunities are restricted. Transmitting frames efficiently within transmission opportunities is very important for system performance. Generally, there are many transmissions between many senders and receivers in a congested environment, which leads to network congestion and reduces transmission efficiency. To address this, we propose a burst transmission and frame aggregation (FAB) scheme to enhance transmission opportunity (TXOP) efficiency of IEEE 802.11p. the proposed scheme considers aggregation and TXOP techniques. Such techniques are useful for improving transmission performance. FAB aggregates frames in the relay node and utilizes the TXOP to transmit these frames to the next hop with a burst transmission. FAB also select multiple relay nodes to improve the efficiency of data forwarding if data is large and can not be forwarded by the node with the largest weight value. this FAB scheme increases transmission efficiency within one TXOP while decreasing transmission overheads. FAB can also support traffics with multiple classes. the proposed strategy is evaluated using various metrics such as end-to-end delays, collision rates, and transmission overheads. Simulation results show that the proposed FAB scheme can significantly improve the performance of inter-vehicle communications.

关键词： vehicular ad hoc networks transmission opportunity bursting routing collision aggregation

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Developing Personalized Security Information Service Using Open Data 18

Developing Personalized Security Information Service Using O...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Kagawa, Takuhiro Saiki, Sachio Nakamura, Masahide Kobe Univ Grad Sch Syst Informat Nada Ku 1-1 Rokkodai Kobe Hyogo 6578501 Japan

ISBN: (纸本)9781509055043

Local governments in Japan recently provide security information services for residents, which deliver regional incident information using Email or Web. However, since the conventional services usually provide "one-for-all" information. users tend to miss important incidents within the flood of information. In this paper, we propose a new security information service, called PRISM (Personalized Real-time Information with Security Map). For given incident information and user's living area, PRISM first computes severity of the incident, based on distance, time, and type of the incident. It then visualizes the incidents with the severity on a heat map. thus, PRISM provides real-time personalized information adapted to individual situation of users. To illustlate the feasibility, we implement PRISM as a Web application using Hyogo Bouhan Net, and Kobe city facility open data.

关键词： open data security information service smart city visualization street crime Web application

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Performance Comparisons and Data Compression of Time-bound Live Migration and Pre-copy Live Migration of Virtual Machines 18

Performance Comparisons and Data Compression of Time-bound L...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Chanchio, Kasidit thaenkaew, Phithak Thammasat Univ Fac Sci & Technol Dept Comp Sci Pathum Thani 12121 Thailand Natl Elect & Comp Technol Ctr NECTEC Pathum Thani 12120 Thailand

ISBN: (纸本)9781509055043

Pre-copy live migration is a popular virtual machine (VM) live migration mechanism that has been used in most hypervisors. In this mechanism, a key parameter, namely the maximum tolerable downtime, is required for each migration. However, defining an appropriate value for this parameter is nontrivial, especially for the migration of a virtual machine running CPU-intensive and memoryintensive applications. If an inappropriate value is used, the migration may suffer poor performance. Time-bound Live Migration (TLM) is another live migration mechanism that was proposed to solve this problem. the TLM can operate automatically without the need for the maximum tolerable downtime. thus, the operational burden and performance penalty due to the configuration of the maximum tolerable downtime are eliminated. the contributions of this study are two folds. First, a novel compression framework for TLM, namely TLMZ, is proposed. Second, the live migration performances of TLM and TLMZ are evaluated against those of the pre-copy mechanism. In our comparisons, the pre-copy mechanism was configured to operate using a range of maximum tolerable downtime values and a number of compression options. An extensive number of experiments have been conducted. In our experiments, the TLM, TLMZ, and pre-copy mechanisms are used to migrate VMs running four OpenMP NAS parallel benchmarks. Experimental results show that TLM and TLMZ are practical solutions for the migrations of VMs running CPU-intensive and memoryintensive applications.

关键词： live migration virtualization compression

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A parallelized GPU- based Simulating Annealing Algorithm for Intensity Modulated Radiation therapy Optimization 18

A Parallelized GPU- based Simulating Annealing Algorithm for...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Galanakou, Panagiota Leventouri, theodora Georgakilas, Alexandros Kalantzis, Georgios Florida Atlantic Univ Dept Phys Boca Raton FL 33431 USA Natl Tech Univ Athens Dept Phys Athens 15780 Greece

ISBN: (纸本)9781509055043

Intensity modulated radiation therapy (IMRT) exhibits the ability to deliver the prescribed dose to the planning target volume (PTV), while minimizing the delivered dose to the organs at risk (OARs). Metaheuristic algorithms, among them the simulating annealing algorithm (SAA), have been proposed in the past for optimization of IMRT. Despite the advantage of the SAA to be a global optimizer, IMRT optimization is an extensive computational task due to the large scale of the optimization variables. therefore stochastic algorithms, such as the SAA, require significant computational resources. In an effort to elucidate the performance improvement of the SAA in highly dimensional optimization tasks, such as the IMRT optimization, we introduce for the first time to our best knowledge a parallel graphic processing unit (GPU)-based SAA developed in MATLAB platform and compliant with the computational environment for radiotherapy research (CERR) for IMRT treatment planning. Our strategy was firstly to identify the major "bottlenecks" of our code and secondly to parallelize those on the GPU accordingly. Performance tests were conducted on four different GPU cards in comparison to a serial version of the algorithm executed on a CPU. Our studies have shown a gradual increase of the speedup factor as a function of the number of beamlets for all four GPUs. Particularly, a maximum speedup factor of similar to 33 was achieved when the K40m card was utilized.

关键词： intensity modulated radiation therapy simulating annealing algorithm optimization GPU execution time

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An Analysis of Random Forest Algorithm Based Network Intrusion Detection System 18

An Analysis of Random Forest Algorithm Based Network Intrusi...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Aung, Yi Yi Min, Myat Myat Univ Comp Studies Mandalay Myanmar

ISBN: (纸本)9781509055043

In the world today, the security of the computer system is of great importance, And in the last few years, there have seen an affected growth in the amount of intrusions that intrusion detection has become the dominant of current information security. Firewalls cannot provide complete protection. Applying on a firewall system alone is not enough to prevent a corporate network from all types of network attacks. therefore more system should be complemented by intrusion detection system. Data mining skills can be used as an effective approach to detect intrusions in intrusion detection system. Data Mining and Knowledge Discovery is the computerized process of trenching and analysis of huge amounts of data, and then extract the meaning of the data. Data mining tools can assist to predict future behaviors and trends, so that organizations proactively, can make decisions based on knowledge. Data mining can answer organization questions that were too traditional time, to solve. Data mining takes its name from the valuable information in a large database. Recent studies display that cascading based approaches of several algorithms are much better performance than an individual algorithm. In this research, we use K-means and Random Forest algorithm to classify instances. this model was verified using KDD'99 data set. Experimental results show that hybrid methods can support suitable detection rates and lower model training time than using single algorithm.

关键词： Intrusion Detection System KDD'99 data set K-means Random Forest

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A three-ratio SACRO-based Particle Swarm Optimization with Local Search Scheme for the Multidimensional Knapsack Problem 18

A Three-ratio SACRO-based Particle Swarm Optimization with L...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Chih, Mingchang Natl Chung Hsing Univ Dept Business Adm Taichung Taiwan

ISBN: (纸本)9781509055043

this study proposes a novel particle swarm optimization (PSO) to solve the multidimensional knapsack problem (MKP). this novel PSO is composed of a new three-ratio self-adaptive check and repair operator (SACRO) idea and a hill-climbing local search scheme. the SACRO idea was first proposed in 2015 and originally utilized only two dynamic ratios (namely, profit/weight utility and profit density) in repairing infeasible solutions. the third unique pseudo-utility ratio (that is, the surrogate relaxation ratio) was further introduced into SACRO, and three ratios (namely, surrogate relaxation ratio, profit/weight utility, and profit density) were used instead of two ratios. A local search idea (that is, the hill-climbing scheme) was also employed to avoid being trapped in the local optimal solutions. the proposed algorithm was tested using the benchmark problems from the OR-library to validate and demonstrate the efficiency of the proposed idea. Results were compared with those of two-ratio SACRO-based algorithms. the simulation and evaluation results showed that the three-ratio SACRO-based PSO with local search scheme is more competitive and robust than the two-ratio SACRO-based algorithm. Moreover, the SACRO idea could be combined with other population-based optimization algorithms to solve MKPs.

关键词： self-adaptive check and repair multidimensional knapsack problem particle swarm optimization pseudo-utility ratio hill-climbing component

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Developing Game AI Agent Behaving Like Human by Mixing Reinforcement Learning and Supervised Learning 18

Developing Game AI Agent Behaving Like Human by Mixing Reinf...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Miyashita, Shohei Lian, Xinyu Zeng, Xiao Matsubara, Takashi Uehara, Kuniaki Kobe Univ Dept Comp Sci & Syst Engn Kobe Hyogo Japan Kobe Univ Grad Sch Syst Informat Kobe Hyogo Japan

ISBN: (纸本)9781509055043

Artificial intelligence (AI) agent created with Deep Q-Networks (DQN) can defeat human agents in video games. Despite its high performance, DQN often exhibits odd behaviors, which could be immersion-breaking against the purpose of creating game AI. Moreover, DQN is capable of reacting to the game environment much faster than humans, making itself invincible (thus not fun to play with) in certain types of games. On the other hand, supervised learning framework trains an AI agent using historical play data of human agents as training data. Supervised learning agent exhibits a more human-like behavior than reinforcement learning agents because of imitating training data. However, its performance is often no better than human agents. the ultimate purpose of AI agents is to entertain human players. A good performance and a human-like behavior are important factors of the AI agents, and both of them should be achieved simultaneously. this study proposes frameworks combining reinforcement learning and supervised learning and we call then separated network model and shared network model. We evaluated their performances by the game scores and behaviors by Turing test. the experimental results demonstrate that the proposed frameworks develop an AI agent of better performance than human agent and natural behavior than reinforcement learning agents.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Recognizing ADLs of One Person Household based on Non-intrusive Environmental Sensing 18

Recognizing ADLs of One Person Household based on Non-intrus...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Niu, Long Saiki, Sachio Nakamura, Masahide Kobe Univ Grad Sch Syst Informat Nada Ku 1-1 Rokkodai Kobe Hyogo 6578501 Japan

ISBN: (纸本)9781509055043

Pervasive sensing technologies are promising for increasing one-person households (OPH), where the sensors monitor and assist the resident to maintain healthy life rhythm. Towards the practical use, the recognition of activities of daily living (ADL) is an important step. Many studies of the ADL recognition have been conducted so far, for real-life and human-centric applications such as eldercare and healthcare. However, most existing methods have limitations in deployment cost, privacy exposure, and inconvenience for residents. To cope with the limitations, this paper presents a new indoor ADL recognition system especially for OPH. To minimize the deployment cost as well as the intrusions to user and house, we exploit an IoT-based environment-sensing device, called Autonomous Sensor Box (SensorBox) which can autonomously measure 7 kinds of environment attributes. We apply machine-learning techniques to the collected data, and predicts 7 kinds of ADLs. We conduct an experiment within an actual apartment of a single user. the result shows that the proposed system achieves the average accuracy of ADL recognition with more than 88%, by carefully developing the features of environment attributes.

关键词： Non-intrusive environment sensing Activities of Daily Living ADLs recognition Feature Engineering Machine Learning

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Clustering Search Engine Suggests by Integrating a Topic Model and Word Embeddings 18

Clustering Search Engine Suggests by Integrating a Topic Mod...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Nie, Tian Ding, Yi Zhao, Chen Lin, Youchao Utsuro, Takchito Kawada, Yasuhide Univ Tsukuba Grad Sch Syst & Informat Engn 1-1-1 Tennodai Tsukuba Ibaraki 3058573 Japan Univ Tsukuba Fac Engn Informat & Syst 1-1-1 Tennodai Tsukuba Ibaraki 3058573 Japan Logworks Co Ltd Shibuya Ku 1-3-15 Yoyogi Tokyo 1510053 Japan

ISBN: (纸本)9781509055043

the background of this paper is the issue of how to overview the knowledge of a given query keyword. Especially, we focus on concerns of those who search for Web pages with a given query keyword. the Web search information needs of a given query keyword is collected through search engine suggests. Given a query keyword, we collect up to around 1,000 suggests, while many of them are redundant. We cluster redundant search engine suggests based on a topic model. However, one limitation of the topic model based clustering of search engine suggests is that the granularity of the topics, i.e., the clusters of search engine suggests, is too coarse. In order to overcome the problem of the coarse-grained clusters of search engine suggests, this paper further applies the word embedding technique to the Web pages used during the training of the topic model, in addition to the text data of the whole Japanese version of Wikipedia. then, we examine the word embedding based similarity between search engines suggests and further classify search engine suggests within a single topic into ner-grained subtopics based on the similarity of word embeddings. Evaluation results prove that the proposed approach performs well in the task of subtopic clustering of search engine suggests.

关键词： Search Engine Suggest Overview Clustering Topic Model Word Embeddings

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A Study of Factors Influencing Intention to Purchase Local Community Product on E-Commerce Website: the Case of One Tambon One Product (OTOP) in thailand 18

A Study of Factors Influencing Intention to Purchase Local C...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Akasarakul, Krittika Cooharojananone, Nagul Lipikorn, Rajalida Chulalongkorn Univ Fac Sci MIMIT Lab Dept Math & Comp Sci Bangkok Thailand

ISBN: (纸本)9781509055043

According to thailand policy framework which has a policy to expand the market and create opportunities in business by using ICT and E-Commerce for supporting rural community people. However, these communities mostly do not have their own website to sell their products. they have to rely on web portal to sell their local community products. therefore, having the rural community official website and electronic commerce (E Commerce) would expect to gain more attention and would be more advantages to the community. therefore, in this paper, we would like to study factors influencing customer's purchasing intention through internet shopping of One Tambon One Product (OTOP), derived from the concept of One Village One Product (OVOP) in Japan, between on web portal and official web. Several factors such as perceived ease of use, reliability of website, reliability of product and social influences that effect customer's purchasing intention were discussed and analyzed. the data was collected using a simply sampling method with survey participants who are people from each rural area in north eastern of thailand. Understanding well the factors influencing online purchasing would allow rural people the possibility of making their official OTOP website to finally attract most of their potential consumers and profit most from the opportunities offered by E-Commerce.

关键词： E-Commerce One Tambon One Product (OTOP) One Village One Product (OVOP) Purchasing Intention Technology Acceptance Model (TAM) Reliability Social Influence Perceived ease of use

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