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Siamese network for Visual Tracking via Focal Loss

Siamese Network for Visual Tracking via Focal Loss

引用

IEEE International Symposium on parallel and distributed processing with Applications and IEEE International conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Shan Jiang Cheng Han Xiaoqiang Di Hua Li School of Computer Science and Technology ChangChun Unviersity of Science and Technology Changchun China

ISBN: (纸本)9781728152103

Visual tracking is a fundamental problem in computer vision. Lots efforts have been made in the past decades and researchers have obtained some achievements, but there are still problems exist. To get a more powerful feature representation, deep learning based methods appear layer upon layer, and most of them achieve good performance at the price of losing speed. In this paper, we propose a SiamFL network for visual tracking, which introduce the focal loss with the Siamese network. With the focal loss, the network is capable of filtering out the easy examples, leaving the hard samples to train a discriminative network. Moreover, the SiamFL network also can alleviate the class imbalance problem by properly sampling the positive and negative samples at a certain ratio. Experimental results demonstrate the SimaFL has quick convergence and also have a better performance over the baseline tracker.

关键词： computer vision image representation learning (artificial intelligence) visual tracking image representation images computer vision siamese Balance impairment network

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Financial Big Data Hot and Cold Separation Scheme based on HBase and Redis

Financial Big Data Hot and Cold Separation Scheme Based on H...

引用

IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Kunhui Li Kun Guo Hong Guo Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou University Fuzhou China Key Laboratory of Spatial Data Mining Information Sharing Ministry of Education Fuzhou China College of Mathematics and Computer Science Fuzhou University Fuzhou China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

In the era of big data, HBase has been widely used in scenarios of massive unstructured data. For the financial big data, due to the integrity and timing of it, unreasonable data storage and management usually lead to hot spots that decreases the query performance. In practice, the separation of hot and cold financial data will improve data query performance and utilization rate of cluster resources. In this paper, a hot and cold data separation scheme is designed, to store infrequently queried financial data to HBase, and frequently queried one to Redis. The cold data is reasonably planned and managed through pre-partitioning and row key design for HBase. A hot data cache based on Redis is realized to improve the query speed and reduces the pressure of HBase. In addition, due to the lack of Redis's inherent cache elimination strategy, we propose a caching strategy based on the frequencies of updating and querying operations. The experimental results show that the scheme can effectively avoid the hot storage problem, and improve the query performance, and improve the cache hit ratio of Redis. Therefore, the number of cold data access requests can be effectively reduced.

关键词： Big Data distributed databases Memory Time series analysis Stock markets

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Cost Efficient Offloading Strategy for DNN-based Applications in Edge-Cloud Environment

Cost Efficient Offloading Strategy for DNN-Based Application...

引用

IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Yinhao Huang Bing Lin Yongjie Zheng Junqin Hu Yuchang Mo Xing Chen College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China College of Physics and Energy Fujian Normal University Fuzhou China Fujian Province University Key Laboratory of Computational Science Huaqiao University Quanzhou China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Deep Neural networks (DNNs) are pervasively used in a large number of applications, such as Microsoft Cortana, Apple Siri, and Google Now. The traditional method is to offload them in the cloud, which causes serious data transmission delay and high network resource cost, as well as user privacy leakage. The emergence of Mobile Edge Computing(MEC) provides a new solution for the execution of DNN-based applications. With the increase of the computing power of mobile devices and the appearance of edge nodes, offloading partial layers of the DNN-based application to the edge will speed up system response, reduce the burden of cloud center and protect privacy of users. Most of existing researches focus on the optimization of response delay for DNN-based applications in edge computing system, but there is no mature solution to the cost optimization of edge computing system. To effectively reduce the cost of edge computing for offloading DNN-based applications, we propose a offloading strategy based on Discrete Particle Swarm Optimization with Genetic Operators(DPSO-GO). By introducing crossover operator and mutation operator of genetic algorithm, it overcomes the defect that the traditional PSO algorithm is easy to fall into local optimum. The results show that our algorithm can reduce the cost of edge computing system effectively while satisfying the delay requirements of all the DNN-based applications.

关键词： Mobile handsets Task analysis Cloud computing Edge computing Servers Optimization Bandwidth

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A Real-Time Traffic Flow Prediction System for National Freeways based on the Spark Streaming Technique 5

A Real-Time Traffic Flow Prediction System for National Free...

引用

IEEE International conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Tsai, Jichiang Chang, Tien-Yu Fang, Yu-Hsiang Chang, En-Shuo Natl Chung Hsing Univ Dept Elect Engn Taichung 402 Taiwan

ISBN: (纸本)9781538663011

In this paper, we discuss how to use the Hadoop parallel computing cluster architecture along with Spark's high-speed computing to analyze national road traffic databases for real-time estimation of future traffic information. Hadoop can process data in parallel and is inexpensive to build. It can also use its cloud data processing system to quickly upload collected data to the Hadoop distributed File System (HDFS). On the other hand, in addition to enjoying the most suitable platform architecture, Spark also provides Spark Streaming to receive files and information in real time. This allows immediate calculations to make the forecasting system quickly aware of the traffic flow minutes ago. Hence, more accurate forecasting information can be acquired. In conclusion, our real-time forecasting system for national road traffic flows will use the HDFS cooperated with the Spark Streaming and Spark MLlib Decision Tree operations. Furthermore, the parameters of machine learning will be adjusted by the difference between the original data and the estimated one to improve the efficiency and accuracy of the overall system.

关键词： Sparks Yarn Traffic control Decision trees Real-time systems Machine learning Training"

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An SDN-based QoS Guaranteed Mechanism for Geospatial Flows

An SDN-Based QoS Guaranteed Mechanism for Geospatial Flows

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Feilong Huang Jianzhong Zhang Jingdong Xu Yiran Shao Lingjun Pu Laboratory of Network and Information Security College of Cyber Science Nankai University Tianjin China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

As a significant portion of big data, geospatial big data is experiencing extremely rapid growth, which brings tremendous pressure and great challenges on geospatial data servers. To provide better services for users, it is an important approach to enable the transmission of geospatial data with QoS, which mainly focus on bandwidth. Therefore, based on the software-defined network(SDN), this paper puts forward a bandwidth guaranteed mechanism for geospatial flows for the first time. In our proposed mechanism, taking advantage of the fuzzy analytic hierarchy process(FAHP), a prioritization model for geospatial flows is proposed to calculate the comprehensive priority. With the comprehensive priority, geospatial flows are mapped into slices with different QoS levels. And then, a dynamic routing algorithm and a bandwidth adjustment mechanism are proposed to guarantee the transmission of geospatial flows with high-priority in sliced SDN. Experimental results show that the proposed QoS guaranteed mechanism has the ability to provide differentiated services for geospatial flows, and it can help to alleviate congestion in the geospatial cloud data center as well.

关键词： Geospatial analysis Quality of service Bandwidth Routing Heuristic algorithms Mathematical model Big Data

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Research on Gold ETF Forecasting based on LSTM

Research on Gold ETF Forecasting Based on LSTM

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Ziyan Xie Xiaoyu Lin Yiwen Zhong Qinglong Chen College of Computer and Information Science Fujian Agriculture and Forestry University Key Laboratory of Smart Agriculture and Forestry Fujian Province University Fuzhou PR China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

The gold Exchange Traded Funds (ETF) is a crucial financial product. In general, it is very difficult to make accurate price predictions because many factors can influence the price trend. The traditional approaches rarely consider other factors that affect the trend more besides historic data therefore the results obtained by the traditional methods are not reliable. In order to get a more reliable prediction, a novel model named Dilated Convolution Long Short-Term Memory (DCLSTM) considering more prediction factors based on Convolution Neural network (CNN) and Long Short-Term Memory (LSTM). The new model is a deep neural network with better feature extraction capabilities and a broader experience field than traditional deep networks. Data has been collected from the Data Base: https://***. Test data items contains several factors that have the greatest impact on prices. The experiments show that DCLSTM has better prediction accuracy than traditional methods such as the Autoregressive Integrated Moving Average (ARIMA), K-Nearest Neighbor (KNN) and Back Propagation Neural network (BPNN) models.

关键词： Gold Convolution Time series analysis Agriculture Forestry Predictive models Logic gates

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A Conflict Detection Method for IPv6 Time-based Firewall Policy

A Conflict Detection Method for IPv6 Time-Based Firewall Pol...

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Xue Zhang Yi Yin Wei Liu Zhizhen Peng Guoqiang Zhang Yun Wang Yuichiro Tateiwa Naohisa Takahashi School of Computer Science and Technology Nanjing Normal University Nanjing China School of Computer Science and Engineering Southeast University Nanjing China Department of Computer Science and Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Firewalls have been a very important secure tool to protect networks against attacks, which usually filter the unauthorized traffic entering the secured network. The packet filtering based on a predefined collection of ordered rules. Along with the IPv6 protocol is widely used, and the security issues comes with it. Firewall for IPv6 network, as an important element to protect network security, it will be not able to filter packets correctly if there are conflicts that caused by the same packet matching two or more rules. In addition, a new kind of firewall with time constraint is used more and more widely by different firewall company, such as, ACLs of Cisco, Iptalbes of Linux, and the like. It is a hard work to manage the rules in IPv4 firewall policy, not to mention the rules in IPv6 time-based firewall policy. Many methods have been proposed to analyze and detect the conflicts of individual or distributed firewall policies. However, very few of them can deal with the time constraint of rules. Therefore, it is an urgent problem to detect the conflicts of the IPv6 time-based firewall policy. In order to solve this problem, we describe a method, which can analyze the IPv6 time-based firewall policy. We use a formal method to analyze the meaning of IPv6 time-based firewall policy. Next, we take the formal validation tool (SMT solver Z3) to detect all the possible conflicts between every two rules. Lastly, we developed an experimental system to evaluate the performance of our method.

关键词： Firewalls (computing) Time factors Computer science Protocols Communication networks Internet

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Agricultural Product Traceability System based on Blockchain Technology

Agricultural Product Traceability System Based on Blockchain...

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Weipeng Xie Xianghan Zheng Xiaoliang Lu Xiaowei Lin Xionghui Fan Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China MingByte Technology (Qingdao) Co. Ltd Qingdao China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

The quantity of agricultural products produced in China is huge. How to ensure the quality of agricultural products from farmland to table is a problem that has been studied all the time. From the perspective of decentralization, this paper uses the blockchain technology to combine the characteristics of agricultural products traceability, and the alliance chain hyperledge recology. As the underlying technology of the blockchain, the Fabric1.4.2 project under the application, the factory, quality inspection, logistics, distribution and supervision as the alliance nodes in the alliance chain, combined with the Internet of Things technology to automatically collect data to achieve agricultural products from planting, processing, quality Traceability of inspection, logistics, distribution and other processes. Through the scanning of the two-dimensional code, the matching of the traceable data and the data uplink are realized, and the products produced are guaranteed to be one yard and one code. Finally, the trace data of the production and circulation process of the product is realized through the scanning of the code of the e-commerce platform of the WeChat mini program.

关键词： Blockchain Organizations Peer-to-peer computing Agricultural products Inspection Production facilities

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A New Feature Selection Method for Intrusion Detection

A New Feature Selection Method for Intrusion Detection

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IEEE International Symposium on parallel and distributed processing with Applications and IEEE International conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Zhen Wang Mingwei Tang Jiayu Deng Yanting Wang Jiang Qian Xiaoliang Chen School of Computer Science and Software Engineering Xihua University Chengdu China

ISBN: (纸本)9781728152103

Intrusion detection is an effective measure to prevent host and network attacks. The use of an intrusion detection system makes up for the shortcomings of traditional firewall technology, signature authentication technology, and access control technology in security protection. However, due to the imbalance of the distribution of intrusion detection data samples, the mutual redundancy between sample features seriously affects the accuracy and efficiency of specific attack detection. In this paper, a proposal was forward, the appropriate feature subsets are selected respectively based on mutual information and the firefly algorithm, and then proposed a feature selection strategy combining two feature subsets. Experiment outcomes show that the accuracy and efficiency of detection are improved by using the best feature set, compared to the use of all features.

关键词： authorisation computer network security feature extraction Feature extraction network security Data Security Authorization INTRUSION DETECTION SYSTEMS selection methods

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A Percolation based Approach for Critical Density in Non-Orientation Directional Sensor network

A Percolation Based Approach for Critical Density in Non-Ori...

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IEEE International Symposium on parallel and distributed processing with Applications and IEEE International conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Lin Kang Yanjie Qi Wenhua Gao Anhong Wang Zenshou Dong School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan China

ISBN: (纸本)9781728152103

Both coverage and connectivity are important problems in wireless sensor network, as more and more non-orientation sensors are continuously added in to the region of interest, the size of covered component and connected component are increased, at some point, the network can achieve an entire coverage and a full connectivity, then the network percolates. In this paper, we calculate the critical density in non-orientation directional sensor network in which the orientations of the sensors are random and the sensors are deployed according to Poisson point process. We propose an approach to compute the critical density in such network, a collaborating path is proposed with the sum of field-of-view angles of two collaborating sensors being π. Then a correlated model of non-orientation directional sensing sectors for percolation is proposed to solve the coverage and connectivity problems together. The numerical simulations confirm that percolation occurs on the estimated critical densities.

关键词： percolation sensor placement stochastic processes telecommunication network planning wireless sensor networks Critical density telecommunication network planning Percolation sensor placement Wireless sensor networks Markov chain Sensors Sensor networks Coverage DIRECTIONAL Stochastic Processes connected component

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