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International High Speed Intelligent Communication Forum (HSIC)

作者： Sheng Zhao Zhiqun Li Engineering Research Center of RF-ICs & RF-Systems Southeast University Jiangsu Provincial Key Laboratory of sensor network technology Wuxi

A 1.8 GHz LC VCO in 1.8-V supply is presented. The VCO achieves low power consumption by optimum selection of inductance in the L-C tank. To increase the tuning range, a three-bit switching capacitor array is used for digital switched tuning. Designed in 0.18μm RF CMOS technology, the proposed VCO achieves a phase noise of -126.2dBc/Hz at 1MHz offset and consumes 1.38mA core current at 1.8-V voltage supply.

关键词： Voltage-controlled oscillators Tuning Phase noise Power demand Wireless sensor networks Switches Inductors

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Joint DBF and SAO parallel filtering based on multithread load balancing

Joint DBF and SAO parallel filtering based on multithread lo...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Ma, Hao Hu, Dong Li, Yi Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

This paper presents a joint parallel loop filtering algorithm based on multi-thread load balancing in HEVC decoding, which implements the parallel processing of deblocking filtering (DBF) and sample adaptive compensation (SAO). Because of the diversity of video, the texture of different regions in an image is also different, which leads to various CTU partition methods. Therefore, the number of the boundary to be filtered is greatly different, resulting the computation load among multiple threads unbalanced in parallel processing. To solve this problem, an area division scheme is proposed, which divides the image into multiple areas, and the number of boundaries to be filtered in each area is similar. Then, the mapping relationship table is used to allocate these areas to multiple threads for parallel processing, so as to achieve the load balancing among the filtering threads. Finally, the cache technology is used to combine DBF and SAO to reduce the delay between them and improve the overall parallelism of the loop filter. Experimental results show that the performance of the proposed load balancing joint filtering algorithm is 8.15% higher than the previous scheme. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Textures

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Scale adaptive block target tracking based on multi-layer convolution features and Kernel correlation filter

Scale adaptive block target tracking based on multi-layer co...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Zhang, Ting Hu, Dong Zhang, Jing Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

Target tracking is currently a hot research topic in Computer Vision and has a wide range of use in many research fields. However, due to factors such as occlusion, fast motion, blur and scale variation, tracking method still needs to be deeply studied. In this paper, we propose a block target tracking method based on multi-convolutional layer features and Kernel correlation filter. Our method divides the tracking process into two parts: target position estimation and target scale estimation. First, we block the target frame based on the condition number. Second, we extract the features by the convolutional layer and apply it to the kernel correlation filter to get the center position of different block targets. With the reliability of different blocks measured by the Barker coefficient, the overall target position center is obtained. Then, the affine transformation is adopted to achieve the scale adaptation. The algorithm in this paper is evaluated by the public video sequences in OTB-2013. Numerous experimental results demonstrate that the proposed tracking method can achieve target scale adaptation and effectively improve the tracking accuracy. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Target tracking

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Di-defects synergy boost electrocatalysis hydrogen evolution over two-dimensional heterojunctions

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Nano Research 2022年第1期15卷 677-684页

作者： Yan Cui Xiaoyu Guo Jian Zhang Xing’ao Li Xinbao Zhu Wei Huang Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China New Energy Technology Engineering Lab of Jiangsu Province School of ScienceNanjing University of Posts&Telecommunications(NUPT)Nanjing 210023China Key Laboratory for Organic Electronics and Information Displays&Institute of Advanced Materials(LAM) Jiangsu National Synergetic Innovation Center for Advanced Materials(SICAM)Nanjing University of Posts&Telecommunications(NUPT)Nanjing 210023China College of Chemical Engineering Nanjing Forestry UniversityNanjing 210037China Shaanxi Institute of Flexible Electronics(SIFE) Northwestern Polytechnical University(NPU)}127 West Youyi RoadXian 710072China

Electronic modulation on the inert basal plane of transition-metal dichalcogenides(TMDs)through vacancy defect excitation,although extremely challenging,is urgent for understanding the factors that impact the hydrogen evolution reaction(HER)catalytic ***,ultrathin WS2 nanosheets with precise quantitative single atomic S-vacancy on the inert basal plane were flexible prepared through hydrogen peroxide etching *** as-synthesized single atomic S-vacancy defect WS2(SVD-WS2)nanoflake with the activated basal plane exhibited an impressive overpotential of 137 mV at a current density of 10 mA·cm^(-2) and a Tafel slope of 53.9 mV dec^(-1).Furthermore,anchoring on the defect graphene matrix,the assembled two-dimensional(2D)stacking heterojunction exhibits further enhanced HER catalytic activity(an overpotential of 108 mV vs.10 mA·cm^(-2) and a Tafel slope of 48.3 mV·dec^(-1))and stability(〜10%decline after 9,000 cycles),which attributed to the electronic structure modulation from the synergetic interactions between SVD-WS_(2) and defect *** finding provides a smart defects introduce strategy to trigger high-efficiency hydrogen evolution over WS_(2) nanosheets and a general 2D heterojunctions fabricated inspiration based on strong interaction interface.

关键词： S-vacancies defect graphene hydrogen evolution reaction heterojunctions

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Channel state division of land satellite mobile and its multi-states Markov model based on fuzzy clustering

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Journal of Computational Information Systems 2014年第4期10卷 1349-1356页

作者： Guo, Yecai Yuan, Tao Zhang, Xiuzai College of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing 210044 China Jiangsu Key Laboratory of Meteorol Observa and Information Processing Nanjing 210044 China Jiangsu Technology and Engineering Center of Meteorology Sensor Network Nanjing 210044 China

Channel modeling of land mobile satellite (LMS) is the foundation of communication system design and its related circuit design. Furthermore, the research on the channel modeling is the key of satellite communications. Firstly, the propagation characteristics of the land mobile satellite channel (LMSC) are analyzed and their second-order statistical characteristics are derived in this paper. Secondly, the LMSC state division method based on fuzzy clustering analysis is proposed according to the real satellite communication environments. Finally, the multi-states Markov chain model with the real LMS propagation characteristics is established and simulated. Simulation results show that the proposed model can effectively reflect the real propagation characteristics of the LMSC. © 2014 Binary Information Press.

关键词： Fuzzy clustering

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A New BDI Forecasting Model based on Support Vector Machine

A New BDI Forecasting Model based on Support Vector Machine

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2016 IEEE Information technology,networking,Electronic and Automation Control Conference(ITNEC 2016)

作者： Jianmin Bao Lin Pan Yuanfa Xie Key Lab of Broadband Wireless Communication and Sensor Network Technology (Jiangsu Provincial Engineering Research Center of Telecommunications and Network Technology) Ministry of Education Baer Institute of Excellence Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467391955

BDI(Dry Baltic Index) is a barometer of the shipping market, which is very important and difficult to predict precisely. The traditional forecasting method is not enough to predict precisely for it with higher complexity. The support vector machine has strong nonlinear function approximation and strong generalization ability. In this paper, a new BDI forecasting model based on support vector machine combined with CFS(Correlation-based Feature Selection) is presented and we first introduce the macroeconomic fundamental indicators of BDI. Firstly, we studied and researched the main macroeconomic fundamental indicators of BDI, investigate the inherent law and external influence of freight index fluctuation, and then put forward the BDI forecasting model based on support vector machine and demonstrate the construction principle of the forecasting model. Finally, in order to evaluate the predictive power of support vector machines, we compare their performance with the neural network model. The results show that the SVM model has a better performance in both the trend and the forecast precision, which can provide a powerful tool for the shipping market operators and investors to grasp the market trend and avoid the price risk.

关键词： BDI support vector machine feature selection CFS modeling

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Short text classification algorithm based on semi-supervised learning and SVM

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2015年第12期10卷 195-206页

作者： Yin, Chunyong Xiang, Jun Zhang, Hui Yin, Zhichao Wang, Jin Jiangsu Key Laboratory of Meteorological Observation and Information Processing School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China Nanjing No.1 Middle School NanjingJiangsu China

Short text is a popular text form, which is widely used in real-time network news, short commentary, micro-blog and many other fields. With the development of the application such as QQ, mobile phone text messages and movie websites, the size of data is also becoming larger and larger. Most data is useless for us while other data is significant for us. Therefore, it is necessary for us to extract the useful short text from the big data. However, there are many problems with the short text classification, such as fewer features, irregularity and so on. To solve these problems, we should pretreat the short text set first, and then choose the significant features. This paper use semi-supervised learning method and SVM classifier to improve the traditional methods and it can classify a large number of short texts to mining the useful massage from the short text. The experimental results in this paper also show a good promotion. © 2015 SERSC.

关键词： Supervised learning

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A siamese network tracking algorithm based on hierarchical attention mechanism

A siamese network tracking algorithm based on hierarchical a...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Zhang, Hu Hu, Dong Qiu, Yingcan Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing210003 China Nanjing University of Posts and Telecommunications Nanjing210003 China

A siamese network tracking algorithm based on hierarchical attention mechanism is proposed in this paper. In order to obtain more robust target tracking results, different layer features are fused effectively. In the process of extracting features, attention mechanism is used to recalibrate the feature map, and AdaBoost algorithm is used to weight the target feature map, which improves the reliability of the response map. Besides, the Inception module is also introduced which not only increases the width of the network and the adaptability of the siamese network to the scale, but also reduces the parameters and improves the speed of network training. Experimental results show that this method can effectively solve the impact of background clutter and improve the accuracy of tracking. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Target tracking

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A feature selection algorithm towards efficient intrusion detection

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2015年第11期10卷 253-264页

作者： Yin, Chunyong Ma, Luyu Feng, Lu Yin, Zhichao Wang, Jin School of Computer and Software Jiangsu Key Laboratory of Meteorological Observation and Information Processing Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China Nanjing No.1 Middle School Nanjing China

Feature selection algorithm plays a crucial role in intrusion detection, data mining and pattern recognition. According to some evaluation criteria, it gets optimal feature subset by deleting unrelated and redundant features of the original data set. Aiming at solving the problems about the low accuracy, the high false positive rate and the long detection time of the existing feature selection algorithm. In this paper, we come up with a feature selection algorithm towards efficient intrusion detection, this algorithm combines the correlation algorithm and redundancy algorithm to chooses the optimal feature subset. Experimental results show that the algorithm shows almost and even better than the traditional feature selection algorithm on the different classifiers. © 2015 SERSC.

关键词： Redundancy

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An Appointment Based MAC Protocol for Wireless sensor networks

An Appointment Based MAC Protocol for Wireless Sensor Networ...

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International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC

作者： Hao Liu Fulong Jiang Guoliang Yao Jiangsu Provincial Key Laboratory of Sensor Network Technology Southeast University Nanjing China National ASIC System Engineering Research Center Southeast University Nanjing China

Several asynchronous duty cycle MAC protocols have been proposed for low power in the wireless sensor networks. However, these proposed MACs pay little attention on the performance degradation in many-to-one communications which is the most common traffic pattern in wireless sensor networks. In this paper, we propose AB-MAC, an appointment based MAC protocol to overcome the effect of channel contention of multiple senders. In AB-MAC, a fusion appointment scheme is proposed to enable scheduled batch transmission for multiple senders with low overhead. This scheme improves the transmission efficiency of the current asynchronous MACs in many-to-one traffic pattern. The experimental results show that, comparing to X-MAC which is a leading asynchronous MAC, AB-MAC can achieve better performance in terms of throughput, latency and energy efficiency.

关键词： Receivers Wireless sensor networks Media Access Protocol Throughput Energy consumption Wireless communication

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