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Multiple mobile data offloading through disruption tolerant networks

IEEE Transactions on Mobile Computing 2014年第7期13卷 1579-1596页

作者： Li, Yong Qian, Mengjiong Jin, Depeng Hui, Pan Wang, Zhaocheng Chen, Sheng Tsinghua National Laboratory for Information Science and Technology Department of Electronic Engineering Tsinghua University Beijing 100084 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Telekom Innovation Laboratories Berlin Hong Kong Aalto University Helsinki Finland Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom Faculty of Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia

To cope with explosive traffic demands on current cellular networks of limited capacity, Disruption Tolerant Networking (DTN) is used to offload traffic from cellular networks to high capacity and free device-to-device networks. Current DTN-based mobile data offloading models are based on simple and unrealistic network assumptions which do not take into account the heterogeneity of mobile data and mobile users. We establish a mathematical framework to study the problem of multiple-type mobile data offloading under realistic assumptions, where (i) mobile data are heterogeneous in terms of size and lifetime;(ii) mobile users have different data subscribing interests;and (iii) the storages of offloading helpers are limited. We formulate the objective of achieving maximum mobile data offloading as a submodular function maximization problem with multiple linear constraints of limited storage, and propose three algorithms, suitable for the generic and more specific offloading scenarios, respectively, to solve this challenging optimization problem. We show that the designed algorithms effectively offload data to the DTN by using both the theoretical analysis and simulation investigations which employ both real human and vehicular mobility traces. © 2002-2012 IEEE.

关键词： Digital storage

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A New Expert System Shell in Turkish Language for Training

A New Expert System Shell in Turkish Language for Training

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International Conference on challenges in IT, engineering and technology (ICCIET’2014, Phuket)

作者： Kemal Tutuncu Murat Koklu Electric-Electronic Engineering Department Technology Faculty of Selcuk University Computer Engineering Department Technology Faculty of Selcuk University

The aim of this study is to design an Expert System(ES) Shell in Turkish language for training license students about building ES. All the current ES shells and tools are required to know English and/or other foreign language. Since most of Turkish university present education in Turkish language and students are not good at any other foreign language, It is vital them to use education materials in Turkish language. The software developed for this study will help lecturer to teach ES, ES application and ES construction in a specific field. The developed ES shell has rule based knowledgebase, forward-chain inference mechanism and certainty factor for including fuzzy logic. The developed ES shell has user-friendly Graphical User Interface where all the menu items and tools are presented in Turkish language. In order to build a new ES in any area It facilitate easy entrance of domain specific variables, range and values that variables can have and rules that uses these variables. Apart from building new ESs in different areas the students will learn structural parts of ES(knowledge-base, working memory, inference mechanism, and etc.) by looking at the source code of the prepared ES shell.

关键词： ES Shell ES application Fuzzy Logic Knowledgebase Inference Mechanism

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Qualitative Bankruptcy Prediction Rules Using Artificial Intelligence Techniques

Qualitative Bankruptcy Prediction Rules Using Artificial Int...

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International Conference on challenges in IT, engineering and technology (ICCIET’2014, Phuket)

作者： Murat Koklu Kemal Tutuncu Computer Engineering Department Technology Faculty of Selcuk University Electric-Electronic Engineering Department Technology Faculty of Selcuk University

Qualitative bankruptcy prediction rules represent experts' problem-solving knowledge to predict qualitative bankruptcy. The objective of this research is predicting qualitative bankruptcy using 4 different Artificial Intelligence(AI) techniques Qualitative Bankruptcy namely;Naive Bayes Classifier(NBC), Multilayer Perceptron(MLP), J48 and Classification via Regression(CR). Correctly Classified Instances were found as 96.5714 %, 94.8571 %, 95.4286 % and 96% for NBC, MLP, J48 and CR, respectively. These results have shown that NBC has the most successful prediction ratio among the four techniques regarding to classification. By using NBCs we can generate better rules with more qualitative factors and redundancy and overlapping of the rules can also be avoided.

关键词： Qualitative Bankruptcy Prediction Naive Bayes Classifier(NBC) Multi-Layer Perceptron(MLP) J48 and Classification via Regression(CR)

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Determination of direction and speed of a uniformly moving obstacle from intersections with virtual window

Determination of direction and speed of a uniformly moving o...

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2014 IEEE Symposium on Industrial electronics and Applications, ISIEA 2014

作者： Mansor, Asri Hj. Rashid, Zarina Abdul Abdullah, Erma Rahayu Mohd Faizal Faculty of Electrical Engineering MARA University of Technology Shah Alam Malaysia Faculty of Electrical and Electronic Engineering University Tun Hussein Onn Malaysia Parit Raja Batu Pahat86400 Malaysia Dept. of AI Faculty of Computer Science and IT Malaya University Kuala Lumpur50603 Malaysia

ISBN: (纸本)9781479955909

A virtual window is used to determine the path and speed of a uniformly moving obstacle. Two intersections with the virtual window at different location are used to calculate the relative path and speed of the obstacle. Two simulations were performed using Excel 2010. The first simulation simulates a practical running of a uniformly moving obstacle, while the second has the obstacle moving at a very high speed. © 2014 IEEE.

关键词： Speed

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Integrating Active Learning with Supervision for Crowdsourcing Generalization

Integrating Active Learning with Supervision for Crowdsourci...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Zhenyu Shu Victor S. Sheng Yang Zhang Dianhong Wang Jing Zhang Heng Chen Institute of Geophysics & Geomatics South-Central University for Nationalities Wuhan China Department of Computer Science University of Central Arkansas Conway AR USA State Key laboratory of Networking an d Switching Technology Beijing University of Posts & Telecommunications Beijing China Faculty of Mechanical & Electronic Information China University of Geosciences Wuhan China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Shanghai Information Center for Life Sciences The Chinese Academy of Sciences Shanghai China

With various online crowdsourcing platforms, it is easy to collect multiple labels for the same examples from the crowd. Consensus integration algorithms can infer the estimated ground truths from the multiple label sets of these crowdsourcing datasets. However, it couldn't be avoided that these integrated (estimated) labels still contain noises. In order to further improve the performance of a model learned from data with these integrated labels, we propose an active learning framework to further improve the data quality, such that to improve the model quality, through acquiring limited true labels from experts (the oracle). We further investigate two active learning strategies in terms of two uncertainty measures (i.e., CLUE and MUE) within the active learning framework. From our experimental results on eight simulation crowdsourcing datasets and four real-world crowdsourcing datasets with three popular consensus integration algorithms, we draw several conclusions as follows. (i) Our active learning framework with the input from the oracle significantly improves the generalization ability of the model learned from crowdsourcing data. (ii) Our two active learning strategies outperform a random active learning strategy.

关键词： Crowdsourcing Uncertainty Data models Noise measurement Estimation Training Labeling

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Driver behavior detection based on multi GNSS technology 35th

Driver behavior detection based on multi GNSS technology

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35th FISITA World Automotive Congress, 2014

作者： Chatranuwathana, Sunhapos Thitipatanapong, Raksit Noomwongs, Nuksit Phondeenana, Peerapat Klongnaivai, Sanya Smart Mobility Research Center Department of Mechanical Engineering Faculty of Engineering Chulalongkron University Bangkok Thailand Space Technologies Group Information Communication & Computing Research Unit National Electronic & Computer Technology Center Pathumtani Thailand

The driver behavior is the key to safe mobility. In general, vehicle maneuvers can be determined from acceleration of the vehicle. Physically, the acceleration and brake can be detected with longitudinal acceleration while turning and lane change can be detected with lateral acceleration. Normally, IMU (inertia measurement unit) has been designated to get those data. However, the I MU is not convenience to install in the vehicles especially as aftermarket additional parts. Nowadays, navigation system technologies have been much improved both on availability and accuracy with combination of multiple navigation satellite systems. Normally, it’s called Multi-GNSS (multiple global navigation satellite system). With decimeter precision and the update rate scale up to 10-Hz, the GNSS would be an alternative solution for driver behavior detection. This paper applied the behavior detection algorithm from previous study [3], and enhanced with advance Multi-GNSS;precise point position (PPP) technique. The advantage of PPP over conventional navigation is decimeter accuracy without direct connection to reference base station. The experimental Multi-GNSS receiver was JAVAD Delta G3T that installed on a utility vehicle. The navigation data was post-processed with the open source RTKLIB 2.4.2 software. On the other hand, the reference vehicle dynamic measurement system was VBOX 3LSi with integrated IMU. As results, the PPP improved the chance of detection of the algorithm from nothing in lane-changing to half of total incidents and significant improved on fault detected. Furthermore, the turning of vehicle which can be detected with conventional GPS was slightly improved with PPP by 15%. The limitations of current study are satellite availability that new block of navigation satellite still in commissioning phase and limited. Moreover, all experiments were carried out in Pathumthani, Thailand. Different city, location and satellite systems may obtain different results. In this pap

关键词： Global positioning system

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Traffic Sign Recognition using Multi-class morphological detection 7

Traffic Sign Recognition using Multi-class morphological det...

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2014 7th International Conference on Advanced Technologies for Communications, ATC 2014

作者： Huynh-The, Thien Nguyen Thanh, Hai Tran Cong, Hung Department of Computer Engineering Kyung Hee University Gyeonggi-do446-701 Korea Republic of Faculty of Electrical and Electronic Engineering University of Technical Education Hochiminh Viet Nam Training and Science Technology Department Posts and Telecoms Institute of Technology Hochiminh Viet Nam

ISBN: (纸本)9781479969555

In this paper, a novel method is proposed for the Traffic Sign Recognition (TSR) using the Principle Component Analysis (PCA) and the Multi-Layer Perceptrons (MLPs) network. In particular, the candidate signs are individually detected from two chroma components in the YCbCr space and then classified into three shape classes: circle, square, and triangle based on computing the rotated version correlations. The PCA-based features of these objects will be used for the MLPs as the training system corresponding to previously determined class. This approach not only reduces the time but also increases the performance of the recognition process. In simulation, the proposed method is estimated with over 500 statistic images for the accuracy rate up to 96%. © 2014 IEEE.

关键词： Principal component analysis

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An alternative method on quadratic programming problems

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AIP Conference Proceedings 2015年第1期1660卷

作者： Y. Dasril I. B. Mohd I. Mustaffa MMM. Aminuddin 1Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia 2Hang Tuah Jaya 76100 Durian Tunggal Melaka Faculty of Science and Technology University Malaysia Terengganu 21030 Kuala Terengganu Malaysia 3Faculty of Technology Engineering Universiti Teknikal Malaysia Melaka Malaysia 4Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia

In this paper we proposed an alternative approach to find the optimum solution of quadratic programming problems (QPP) in its original form without additional information such as slack variable, surplus variable or artificial variable as done in other favourite methods. This approached is based on the violated constraints by the unconstrained optimum. The optimal solution of QPP obtained by searching from initial point to another point alongside of feasible region.

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Comparison of Brain Network Models using Cross-Frequency Coupling and Attack Strategies

Comparison of Brain Network Models using Cross-Frequency Cou...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Marios Antonakakis Stavros I. Dimitriadis Michalis Zervakis Roozbeh Rezaie Abbas Babajani-Feremi Sifis Micheloyannis George Zouridakis Andrew C. Papanicolaou the Technical University of Crete Department of Electronic and Computer Engineering Akrotiri Campus Chania 73100 Greece the AIIA Laboratory Department of Informatics Aristotle University Thessaloniki 54124 Greece and the NeuroInformatics Group Aristotle University of Thessaloniki Greece Department of Pediatrics Division of Clinical Neurosciences University of Tennessee Health Science Center Memphis TN USA and the Neuroscience Institute Le Bonheur Children's Hospital Memphis TN USA. University of Crete Faculty of Medicine Greece Departments of Engineering Technology Computer Science and Electrical and Computer Engineering University of Houston Houston TX USA the Department of Neurobiology and Anatomy University of Tennessee Health Science Center Memphis TN USA

ISBN: (纸本)9781424492695

Several neuroimaging studies have suggested that functional brain connectivity networks exhibit "small-world" characteristics, whereas recent studies based on structural data have proposed a "rich-club" organization of brain networks, whereby hubs of high connection density tend to connect among themselves compared to nodes of lower density. In this study, we adopted an "attack strategy" to compare the rich-club and small-world organizations and identify the model that describes best the topology of brain connectivity. We hypothesized that the highest reduction in global efficiency caused by a targeted attack on each model's hubs would reveal the organization that better describes the topology of the underlying brain networks. We applied this approach to magnetoencephalographic data obtained at rest from neurologically intact controls and mild traumatic brain injury patients. Functional connectivity networks were computed using phase-to-amplitude cross-frequency coupling between the δ and β frequency bands. Our results suggest that resting state MEG connectivity networks follow a rich-club organization.

关键词： Comparison Attack Strategies lower density

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Dual band monopole antenna for wireless communication system

Dual band monopole antenna for wireless communication system

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International Symposium on technology Management and Emerging Technologies (ISTMET)

作者： M. H. Ramli M. Z. A Abd Aziz M. A. Othman A. H. Dahalan Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Faculty of Engineering Technology Universiti Teknikal Malaysia Melaka Malaysia

A dual band monopole antenna for Wireless local area network (WLAN) communication system is presented. The antenna has been designed with two meander branch monopole elements and the rectangular ground structure with simple configuration. The first branch is optimized by using a quarter wavelength of desired resonance frequency at 2.45 GHz. Meanwhile, additional branch of second branch brings resonance frequency of 5.8 GHz. This can easily suited by using 50 ohm probe feed with SMA connector. The proposed antenna is simulated by using computer Simulation technology (CST) software in order to simulate the return loss, bandwidth, gain, directivity, surface current and radiation pattern. The impedance bandwidth for return loss less than - 10 dB is 284 MHz and 267 MHz for first and second resonance frequency. In fact, second resonance can be adjusted by modifying the second branch length, L B1 with little effect on the first resonance.

关键词： Antennas Wireless LAN Resonant frequency Dual band Bandwidth Gain

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