Orthogonal time frequency space(OTFS)modulation is a recently proposed modulation scheme that exhibits robust performance in high-Doppler environments.It is a two-dimensional modulation scheme where information symbol...Orthogonal time frequency space(OTFS)modulation is a recently proposed modulation scheme that exhibits robust performance in high-Doppler environments.It is a two-dimensional modulation scheme where information symbols are multiplexed in the de⁃lay-Doppler(DD)domain.Also,the channel is viewed in the DD domain where the chan⁃nel response is sparse and time-invariant for a long time.This simplifies channel estima⁃tion in the DD domain.This paper presents an overview of the state-of-the-art approaches in OTFS signal detection and DD channel estimation.We classify the signal detection ap⁃proaches into three categories,namely,low-complexity linear detection,approximate max⁃imum a posteriori(MAP)detection,and deep neural network(DNN)based detection.Simi⁃larly,we classify the DD channel estimation approaches into three categories,namely,separate pilot approach,embedded pilot approach,and superimposed pilot approach.We compile and present an overview of some of the key algorithms under these categories and illustrate their performance and complexity attributes.展开更多
目的:探究防护型急救车底盘抵御爆炸性武器手雷、地雷的毁伤效果。方法:在满足防护型急救车防护要求的前提下,采用12 mm厚聚乙烯(polyethylene,PE)防护板和复合陶瓷PE防护板(1 mm铝板+6 mm B4C陶瓷+12 mm高分子量聚乙烯纤维)对急救车底...目的:探究防护型急救车底盘抵御爆炸性武器手雷、地雷的毁伤效果。方法:在满足防护型急救车防护要求的前提下,采用12 mm厚聚乙烯(polyethylene,PE)防护板和复合陶瓷PE防护板(1 mm铝板+6 mm B4C陶瓷+12 mm高分子量聚乙烯纤维)对急救车底盘进行防护。通过理论计算和仿真模拟,分别分析某62 g TNT手雷对PE防护板和某6000 g TNT当量地雷对复合陶瓷PE防护板的爆炸毁伤效果。结果:PE防护板和复合陶瓷PE防护板能够分别抵御某手雷和某地雷在1.1 m炸距下的爆炸毁伤作用,且均未出现明显破坏。结论:PE防护板和复合陶瓷PE防护板均能满足抵御爆炸性武器手雷、地雷毁伤作用及机动性、轻量化要求,该研究可为防护型急救车底盘防护设计提供参考。展开更多
A large number of community discovery algorithms have been proposed in the last decade. Recently, the sharp increase of network scale has become a great challenge for traditional community discovery algorithms. Label ...A large number of community discovery algorithms have been proposed in the last decade. Recently, the sharp increase of network scale has become a great challenge for traditional community discovery algorithms. Label propagation algorithm is a semi-supervised machine learning method, which has linear time complexity when coping with large scale networks. However, the output result has less stability and the quality of the output communities still remains to be improved. Therefore, we propose a novel coreleader based label propagation algorithm for community detection called CLBLPA. Firstly, we find core leaders of potential community by using a greedy method. Then we utilize the label influence potential to guide the process of label propagation. Thus we can accelerate the convergence of algorithm and improve the stability of the output. Experimental results on synthetic datasets and real networks show that CLBLPA can significantly improve the quality of the output communities.展开更多
Internet of Vehicles(henceforth called IoV) is a public network system and high-value target for intrusions that may cause efficiency issues, privacy leakages or even physical damage. Conventional intrusion detection ...Internet of Vehicles(henceforth called IoV) is a public network system and high-value target for intrusions that may cause efficiency issues, privacy leakages or even physical damage. Conventional intrusion detection methods are normally designed for the Internet infrastructures which cannot directly apply in the context of IoV. This work proposes an FPGA based intrusion detection method that can not only achieve real-time scanning performance but also be applied in vehicular environment. We evaluate our scheme on a Xilinx FPGA based platform. Experiments show that the proposed system can achieve a throughput of more than 39 Gbps on existing FPGA platform which is about 15% higher than state-of-the-art techniques,and the total power consumption for the prototype is about 7.5 w. Moreover, the processing latency of the prototype is about 4 us and is about one sixtieth part of the popular software IDS systems.展开更多
文摘Orthogonal time frequency space(OTFS)modulation is a recently proposed modulation scheme that exhibits robust performance in high-Doppler environments.It is a two-dimensional modulation scheme where information symbols are multiplexed in the de⁃lay-Doppler(DD)domain.Also,the channel is viewed in the DD domain where the chan⁃nel response is sparse and time-invariant for a long time.This simplifies channel estima⁃tion in the DD domain.This paper presents an overview of the state-of-the-art approaches in OTFS signal detection and DD channel estimation.We classify the signal detection ap⁃proaches into three categories,namely,low-complexity linear detection,approximate max⁃imum a posteriori(MAP)detection,and deep neural network(DNN)based detection.Simi⁃larly,we classify the DD channel estimation approaches into three categories,namely,separate pilot approach,embedded pilot approach,and superimposed pilot approach.We compile and present an overview of some of the key algorithms under these categories and illustrate their performance and complexity attributes.
文摘目的:探究防护型急救车底盘抵御爆炸性武器手雷、地雷的毁伤效果。方法:在满足防护型急救车防护要求的前提下,采用12 mm厚聚乙烯(polyethylene,PE)防护板和复合陶瓷PE防护板(1 mm铝板+6 mm B4C陶瓷+12 mm高分子量聚乙烯纤维)对急救车底盘进行防护。通过理论计算和仿真模拟,分别分析某62 g TNT手雷对PE防护板和某6000 g TNT当量地雷对复合陶瓷PE防护板的爆炸毁伤效果。结果:PE防护板和复合陶瓷PE防护板能够分别抵御某手雷和某地雷在1.1 m炸距下的爆炸毁伤作用,且均未出现明显破坏。结论:PE防护板和复合陶瓷PE防护板均能满足抵御爆炸性武器手雷、地雷毁伤作用及机动性、轻量化要求,该研究可为防护型急救车底盘防护设计提供参考。
基金supported by the National Natural Science Foundation of China under Grant No. 61272277, 41301409, 41571390the Fundamental Research Funds for the Central Universities under Grant No. 274742
文摘A large number of community discovery algorithms have been proposed in the last decade. Recently, the sharp increase of network scale has become a great challenge for traditional community discovery algorithms. Label propagation algorithm is a semi-supervised machine learning method, which has linear time complexity when coping with large scale networks. However, the output result has less stability and the quality of the output communities still remains to be improved. Therefore, we propose a novel coreleader based label propagation algorithm for community detection called CLBLPA. Firstly, we find core leaders of potential community by using a greedy method. Then we utilize the label influence potential to guide the process of label propagation. Thus we can accelerate the convergence of algorithm and improve the stability of the output. Experimental results on synthetic datasets and real networks show that CLBLPA can significantly improve the quality of the output communities.
基金supported by the National Science Foundation of China under Grant No. 61402474by the Excellent Young Scholar Research Fund of Beijing Institute of Technology
文摘Internet of Vehicles(henceforth called IoV) is a public network system and high-value target for intrusions that may cause efficiency issues, privacy leakages or even physical damage. Conventional intrusion detection methods are normally designed for the Internet infrastructures which cannot directly apply in the context of IoV. This work proposes an FPGA based intrusion detection method that can not only achieve real-time scanning performance but also be applied in vehicular environment. We evaluate our scheme on a Xilinx FPGA based platform. Experiments show that the proposed system can achieve a throughput of more than 39 Gbps on existing FPGA platform which is about 15% higher than state-of-the-art techniques,and the total power consumption for the prototype is about 7.5 w. Moreover, the processing latency of the prototype is about 4 us and is about one sixtieth part of the popular software IDS systems.
