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Indoor Navigation Using A* Algorithm 2nd

引用

2nd international conference on soft computing and data Mining (SCDM)

作者： Kasim, Shahreen Xia, Loh Yin Wahid, Norfaradilla Fudzee, Mohd Farhan Md Mahdin, Hairulnizam Ramli, Azizul Azhar Suparjoh, Suriawati Salamat, Mohamad Aizi Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol Parit Raja Malaysia

ISBN: (纸本)9783319512815;9783319512792

This paper introduced an indoor navigation application that helps junior students in Faculty of Computer science and Information Technology (FSKTM) to find their classroom location. This project implements the A* (pronounced A Star) path finding algorithm to calculate the shortest path for users. Users can choose to view the floor plan of the building or start navigation. Users can choose their starting point from the list and set their destination to start navigation. The application is then calculate the shortest path for users by implement the A* algorithm. The route path will show on the floor plan after calculation done. Thus, users will find this project is easy to use and time saving. © Springer international Publishing AG 2017.

关键词： Android Shortest path A* algorithm 2D map

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data and Decision Intelligence for Internet of Things: Putting Human in the Loop 3

Data and Decision Intelligence for Internet of Things: Putti...

引用

IEEE 3rd international conference on Big data Security on Cloud (BigdataSecurity) / 3rd IEEE international conference on High Performance and Smart computing (HPSC) / 2nd IEEE international conference on Intelligent data and Security (IDS)

作者： Ma, Meng Lin, Weilan Pan, Disheng Wang, Ping Zhou, Yuchen Liang, Xiaoxing Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China Peking Univ Sch Software & Microelect Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Software Beijing Peoples R China Peking Univ Natl Engn Res Ctr Software Engn Beijing Peoples R China IBM Res China Beijing Peoples R China

ISBN: (纸本)9781509062966

The requirement and expanding needs of bridging the physical and cyber world promote the emergence of a new global internet-based information architecture, the Internet of Things. The main challenge in Internet of Things is how to make fast and accurate decisions based on multi-modal sensing data. In this paper, we put human into the process and formulate a closed-loop computing paradigm for IoT data and decision intelligence. We first propose a human-in-the-loop reference model, which extends the traditional cyber-physical interaction extended into a closed-loop process based on cyber, physical and human three factors. We defined the three-factor decision paradigm in the model. On the basis of the reference model, we analyze the feature requirement in the data intelligent process and summarize it as three key aspects: semantic, interactive and iterative. Further, we analyze several major challenges facing IoT data and decision intelligence from the perspective of data characteristics. We select and review the recent progress in three typical application domains and analyzed whether the current research has solved the target issues. According to the results of the review and analysis, the paper finally summarizes and addresses some key research directions in the future.

关键词： Internet of Things data intelligence data mining decision-making human-in-the-loop

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Research on Big data-Driven High-Risk Students Prediction

Research on Big Data-Driven High-Risk Students Prediction

引用

2nd IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Yu Xiaogao Peng Ruiqing Hubei Univ Econ Sch Informat Management & Stat Wuhan Hubei Peoples R China

ISBN: (纸本)9781509044993

Big data technology is used to integrate, clean up and analyze the data of student management system, educational administration system, and campus card consumption system and so on in this paper. The characteristics of high risk students are extracted and selected, and the prediction model is constructed, which can be used to predict the high risk students scientifically, reasonably and effectively, we can take care of these students and take effective measures to help them improve. The massive data accumulated in Colleges and universities can be effectively utilized by this study, managers have a more detailed understanding of colleges and universities and students, the teaching effect is improved, the risk of student drop-out is reduced. Therefore, this study has strong theoretical value and important practical value.

关键词： big data prediction student model

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A Taxi Gap Prediction Method via Double Ensemble Gradient Boosting Decision Tree 3

A Taxi Gap Prediction Method via Double Ensemble Gradient Bo...

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作者： Zhang, Xiao Wang, Xiaorong Chen, Wei Tao, Jie Huang, Weijing Wang, Tengjiao Peking Univ Sch EECS Key Lab High Confidence Software Technol MOE Beijing 100871 Peoples R China China Elect Power Res Inst Technol & Strategy Res Ctr Beijing 100192 Peoples R China

ISBN: (纸本)9781509062966

Predicting the gap between taxi demand and supply in taxi booking apps is completely new and important but challenging. However, manually mining gap rule for different conditions may become impractical because of massive and sparse taxi data. Existing works unilaterally consider demand or supply, used only few simple features and verified by little data, but not predict the gap value. Meanwhile, none of them dealing with missing values. In this paper, we introduce a Double Ensemble Gradient Boosting Decision Tree Model (DEGBDT) to predict taxi gap. (1) Our approach specifically considers demand and supply to predict the gap between them. (2) Also, our method provides a greedy feature ranking and selecting method to exploit most reliable features. (3) To deal with missing value, our model takes the lead in proposing a double ensemble method, which secondarily integrates different Gradient Boosting Decision Tree (GBDT) model at the different data sparse situation. Experiments on real large-scale dataset demonstrate that our approach can effectively predict the taxi gap than state-of-the-art methods, and shows that double ensemble method is efficacious for sparse data.

关键词： taxi gap double ensemble GBDT data sparsity

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The Teaching Reform of Network Engineering under the Thinking of "Internet +"

The Teaching Reform of Network Engineering under the Thinkin...

引用

2018 2nd international conference on Management, Education and Social science(ICMESS 2018)

作者： Haixia Sun Houdi Xu Department of Computer Science and Technology Anhui Sanlian University 38 Military Representative Offices in China

In order to solve the problem of ineffective supervision of MOOC online education and the lack of student enthusiasm,this paper proposed a MOOC-based SPOC College mixed learning mode,which can not only promote interna... 详细信息

关键词： Internet + MOOC SPOC Teaching reform

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Classification of resting-state fMRI datasets based on graph kernels 2

Classification of resting-state fMRI datasets based on graph...

引用

2nd international conference on Image, Vision and computing, ICIVC 2017

作者： Zhou, Yu Mei, Xue Li, Weiwei Jin, Huang College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China

ISBN: (纸本)9781509062379

Recently, functional network connectivity (FNC) is widely applied to detect the functional organization of brain network in the field of psychiatric illnesses analysis. Conventional FNC analyses assume that temporal stationarity and ignore the topology information among multiple brain regions. By the graph encoding of static FNC and dynamic FNC, in this paper we performed a graph approach combining machine learning techniques and graph kernels for automation classification of Schizophrenia (SZ) and Healthy Control (HC). In other words, we convert the FNC analysis into a graph classification problem. Furthermore, for optimal classification performance, we study the influence of parameters in the graph encoding and graph kernels computation. The experimental results show that the relevance of the proposed approach in the brain FNC analysis. In general, our methods complement the deficiency of the conventional stationary analysis, and provide novel insights into dynamic FNC analysis and have a potential application for other psychiatric disorders. © 2017 IEEE.

关键词： Classification (of information)

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A New Mobile Malware Classification for SMS Exploitation 2nd

引用

2nd international conference on soft computing and data Mining (SCDM)

作者： Zaizi, Nurzi Juana Mohd Saudi, Madihah Mohd Khailani, Adiebah USIM Fac Sci & Technol Nilai 71800 Negeri Sembilan Malaysia

ISBN: (纸本)9783319512815;9783319512792

Mobile malware is ubiquitous in many malicious activities such as money stealing. Consumers are charged without their consent. This paper explores how mobile malware exploit the system calls via SMS. As a solution, we proposed a system calls classification based on surveillance exploitation system calls for SMS. The proposed system calls classification is evaluated and tested using applications from Google Play Store. This research focuses on Android operating system. The experiment was conducted using Drebin dataset which contains 5560 malware applications. Dynamic analysis was used to extract the system calls from each application in a controlled lab environment. This research has developed a new mobile malware classification for Android smartphone using a covering algorithm. The classification has been evaluated in 500 applications and 126 applications have been identified to contain malware.

关键词： Mobile malware data classification Android Big data Covering algorithm

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2nd international Workshop on Algorithmic Aspects of Cloud computing, ALGOCLOUD 2016

2nd International Workshop on Algorithmic Aspects of Cloud C...

引用

2nd international Workshop on Algorithmic Aspects of Cloud computing, ALGOCLOUD 2016

ISBN: (纸本)9783319570440

The proceedings contain 11 papers. The special focus in this conference is on Algorithmic Aspects of Cloud computing. The topics include: Efficient indexing on top of NoSQL databases;an apache spark implementation for sentiment analysis on twitter data;a cloud-based time-dependent routing service;a big data architecture for traffic forecasting using multi-source information;mining uncertain graphs;recovering from cloud application deployment failures through re-execution;fair, fast and frugal large scale matchmaking for VM placement;survey of machine learning algorithms on spark over DHT-based structures;scaling out to become doctrinal;a survey on big data and collective intelligence.

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Application of Redundant Backup Technology in Network Security

Application of Redundant Backup Technology in Network Securi...

引用

2018 2nd international conference on Systems,computing,and Applications(SYSTCA 2018)

作者： Shuwen Deng Siping Hu Dianhua Wang Limin Liu Hubei University of Science and Technology Luxi Town Central Primary School of Jiayu County

This paper mainly introduces the implementation of bank network design and system construction. In the era of rapid network development, the network is becoming more and more important in daily life, especially in some large facilities and institutions, the network has become a necessary means to maintain its development. Because the bank is a large financial institution, its design needs are relatively high, not only to be safe, efficient, convenient, but also to consider fault tolerance and data integrity. In terms of bank demand, the performance planning and implementation of various aspects of the banking network are described point by point. This paper also introduces the overall structure of the bank design, implementation plan and test results.

关键词： redundant backup virtual local area network security authentication fault tolerance

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Research of Performance of Static and Dynamic Routing Protocol Based on NS2

Research of Performance of Static and Dynamic Routing Protoc...

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2018 2nd international conference on Systems,computing,and Applications(SYSTCA 2018)

作者： Hui Zheng Siping Hu Shejie Lu Wuxiong Xu Nanyang Institute of Technology Hubei University of Science and Technology

This paper mainly introduces the wireless mobile Ad Hoc network used for vehicle-to-vehicle communication. It also introduces the concepts of Ad Hoc network, vehicle-mounted Ad Hoc network and typical routing protocols. In this paper, 11 mobile nodes in the vehicle-based Ad Hoc network are studied, and the typical AODV and DSDV routing protocols are simulated in the LINUX environment using the famous simulation software NS2. Through the analysis of the simulation result data, the performance indexes of the two routing protocols are analyzed using performance indicators such as route throughput, jitter, packet loss rate, and end-to-end delay. The final result is that AODV performance is better than DSDV.

关键词： vehicle-mounted Ad Hoc network routing protocol packet loss rate throughput

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