1-15hit |
Xinyun ZHANG Xue ZHOU Xinglei CUI Rui LI Guofu ZHAI
To study the molten bridge phenomenon of contacts at the initial breaking process, an experimental device of molten bridge between slowly opening contacts was developed. The system consists of the contact moving control module, the circuit load and the observation module. The molten bridge of copper contact under two load conditions 9,V/19,A and 9,V/7.3,A were studied. The voltage and current characteristics curves of Cu molten bridge were extracted and the resistance and the instantaneous power of the molten bridge were analyzed. The image of the Cu molten bridge diameter was captured by CCD under 9,V/19,A and the influences of the contact force and the separation speed on the molten bridge length and the crater diameter of the anode were studied. The root profile of the Cu contacts after separation was analyzed by digital microscope. Research results show that the Cu molten bridge length has the same changing trend as the diameter of the anode crater. They both decrease with the increment of the separation speed and the decrement of the contact force.
Jiarui LI Ying HONG Chengpeng HAO
Wheeze is a general sign for obstructive airway diseases whose clinical diagnosis mainly depends on auscultating or X-ray imaging with subjectivity or harm. Therefore, this paper introduces an automatic, noninvasive method to detect wheeze which consists of STFT decomposition, preprocessing of the spectrogram, correlation-coefficients calculating and duration determining. In particular, duration determining takes the Haas effect into account, which facilitates us to achieve a better determination. Simulation result shows that the sensibility (SE), the specificity (SP) and the accuracy (AC) are 88.57%, 97.78% and 93.75%, respectively, which indicates that this method could be an efficient way to detect wheeze.
Xiaozhou CHENG Rui LI Yanjing SUN Yu ZHOU Kaiwen DONG
Visible-Infrared Person Re-identification (VI-ReID) is a challenging pedestrian retrieval task due to the huge modality discrepancy and appearance discrepancy. To address this tough task, this letter proposes a novel gray augmentation exploration (GAE) method to increase the diversity of training data and seek the best ratio of gray augmentation for learning a more focused model. Additionally, we also propose a strong all-modality center-triplet (AMCT) loss to push the features extracted from the same pedestrian more compact but those from different persons more separate. Experiments conducted on the public dataset SYSU-MM01 demonstrate the superiority of the proposed method in the VI-ReID task.
Gang WANG Yaping LIN Rui LI Jinguo LI Xin YAO Peng LIU
High-speed IP address lookup with fast prefix update is essential for designing wire-speed packet forwarding routers. The developments of optical fiber and 100 Gbps interface technologies have placed IP address lookup as the major bottleneck of high performance networks. In this paper, we propose a novel structure named Compressed Multi-way Prefix Tree (CMPT) based on B+ tree to perform dynamic and scalable high-speed IP address lookup. Our contributions are to design a practical structure for high-speed IP address lookup suitable for both IPv4 and IPv6 addresses, and to develop efficient algorithms for dynamic prefix insertion and deletion. By investigating the relationships among routing prefixes, we arrange independent prefixes as the search indexes on internal nodes of CMPT, and by leveraging a nested prefix compression technique, we encode all the routing prefixes on the leaf nodes. For any IP address, the longest prefix matching can be made at leaf nodes without backtracking. For a forwarding table with u independent prefixes, CMPT requires O(logmu) search time and O(mlogmu) dynamic insert and delete time. Performance evaluations using real life IPv4 forwarding tables show promising gains in lookup and dynamic update speeds compared with the existing B-tree structures.
Tao LIU Tianrui LI Yihong CHEN
In this letter, a distributed TDMA-based data gathering scheme for wireless sensor networks, called DTDGS, is proposed in order to avoid transmission collisions, achieve high levels of power conservation and improve network lifetime. Our study is based on corona-based network division and a distributed TDMA-based scheduling mechanism. Different from a centralized algorithm, DTDGS does not need a centralized gateway to assign the transmission time slots and compute the route for each node. In DTDGS, each node selects its transmission slots and next-hop forwarding node according to the information gathered from neighbor nodes. It aims at avoiding transmission collisions and balancing energy consumption among nodes in the same corona. Compared with previous data gathering schemes, DTDGS is highly scalable and energy efficient. Simulation results show high the energy efficiency of DTDGS.
In this paper, we investigate two improved turbo receivers for the Long Term Evolution (LTE) uplink in the presence of transmitter (Tx) in-phase and quadrature-phase imbalance (IQI) with parameters known at eNodeB. For multiuser multiple-input multiple-output (MU-MIMO) single-carrier frequency division multiple access (SC-FDMA) systems, we derive a optimal joint linear minimum mean square error (MMSE) turbo multiuser detector (MUD) based on the mirror symmetry clusters. For the single use SC-FDMA system with Tx IQI, we derive an optimal widely linear MMSE (WLMMSE) turbo equalizer. Both receivers are implemented in the discrete frequency domain and only slightly increase the computational complexity compared to the conventional turbo receivers. Monte Carlo simulations show that the proposed receivers significantly outperform the conventional turbo receivers. The simulation results are then confirmed by the extrinsic information transfer (EXIT) chart analysis.
Jan and Tseng, in 1999, proposed two efficient digital signature schemes with subliminal channels. However, we show that a malicious subliminal receiver can forge subliminal messages that will be accepted by other subliminal receivers in Jan and Tseng's two schemes. Moreover, we also present a modification of Jan and Tseng's schemes to repair the security flaw.
Shujiao LIAO Qingxin ZHU Rui LIANG
Rough set theory is an important branch of data mining and granular computing, among which neighborhood rough set is presented to deal with numerical data and hybrid data. In this paper, we propose a new concept called inconsistent neighborhood, which extracts inconsistent objects from a traditional neighborhood. Firstly, a series of interesting properties are obtained for inconsistent neighborhoods. Specially, some properties generate new solutions to compute the quantities in neighborhood rough set. Then, a fast forward attribute reduction algorithm is proposed by applying the obtained properties. Experiments undertaken on twelve UCI datasets show that the proposed algorithm can get the same attribute reduction results as the existing algorithms in neighborhood rough set domain, and it runs much faster than the existing ones. This validates that employing inconsistent neighborhoods is advantageous in the applications of neighborhood rough set. The study would provide a new insight into neighborhood rough set theory.
Yun ZHANG Bingrui LI Shujuan YU Meisheng ZHAO
In this paper, we propose a new scheme which uses blind detection algorithm for recovering the conventional user signal in a system which the sporadic machine-to-machine (M2M) communication share the same spectrum with the conventional user. Compressive sensing techniques are used to estimate the M2M devices signals. Based on the Hopfield neural network (HNN), the blind detection algorithm is used to recover the conventional user signal. The simulation results show that the conventional user signal can be effectively restored under an unknown channel. Compared with the existing methods, such as using the training sequence to estimate the channel in advance, the blind detection algorithm used in this paper with no need for identifying the channel, and can directly detect the transmitted signal blindly.
Jia-Rui LIU Shi-Ze GUO Zhe-Ming LU Fa-Xin YU Hui LI
In complex network analysis, there are various measures to characterize the centrality of each node within a graph, which determines the relative importance of each node. The more centrality a node has in a network, the more significance it has in the spread of infection. As one of the important extensions to shortest-path based betweenness centrality, the flow betweenness centrality is defined as the degree to which each node contributes to the sum of maximum flows between all pairs of nodes. One of the drawbacks of the flow betweenness centrality is that its time complexity is somewhat high. This Letter proposes an approximate method to calculate the flow betweenness centrality and provides experimental results as evidence.
Based on the completeness of the real-valued discrete Gabor transform, a new biorthogonal relationship between analysis window and synthesis window is derived and a fast algorithm for computing the analysis window is presented for any given synthesis window. The new biorthogonal relationship can be expressed as a linear equation set, which can be separated into a certain number of independent sub-equation sets, where each of them can be fast and independently solved by using convolution operations and FFT to obtain the analysis window for any given synthesis window. Computational complexity analysis and comparison indicate that the proposed algorithm can save a considerable amount of computation and is more efficient than the existing algorithms.
Rui LI Ruqi XIAO Hong GU Weimin SU
A novel direction of arrival (DOA) estimation method for the coherent signal is presented in this paper. The proposed method applies the eigenvector associated with max eigenvalue, which contains the DOAs of all signals, to form a Toeplitz matrix, yielding an unconstrained optimization problem. Then, the DOA is obtained by peak searching of the pseudo power spectrum without the knowledge of signal number. It is illustrated that the method has a great performance and low computation complexity for the coherent signal. Simulation results verify the usefulness of the method.
Dong Il KIM Chang-Mook CHOI Rui LI Dae Hee LEE
In this paper, we use Permalloy and CPE (Permalloy: CPE=70:30 wt.%) to fabricate the electromagnetic (EM) wave absorber for W-band radars. The EM wave absorption abilities at different thicknesses were simulated using material properties of the EM wave absotber, and an EM wave absorber was manufactured based on the simulated design. The comparisons of simulated and measured results show good agreement. Measurements show that a 1.15 mm thick EM wave absorber has absorption ability higher than 18 dB at 94 GHz for missile guidance radars, and a 1.4 mm EM wave absorber has absorption ability higher than 20 dB at 76 GHz for collision-avoidance radars.
Hao WANG Sirui LIU Jianyong DUAN Li HE Xin LI
Sememes are the smallest semantic units of human languages, the composition of which can represent the meaning of words. Sememes have been successfully applied to many downstream applications in natural language processing (NLP) field. Annotation of a word's sememes depends on language experts, which is both time-consuming and labor-consuming, limiting the large-scale application of sememe. Researchers have proposed some sememe prediction methods to automatically predict sememes for words. However, existing sememe prediction methods focus on information of the word itself, ignoring the expert-annotated knowledge bases which indicate the relations between words and should value in sememe predication. Therefore, we aim at incorporating the expert-annotated knowledge bases into sememe prediction process. To achieve that, we propose a CilinE-guided sememe prediction model which employs an existing word knowledge base CilinE to remodel the sememe prediction from relational perspective. Experiments on HowNet, a widely used Chinese sememe knowledge base, have shown that CilinE has an obvious positive effect on sememe prediction. Furthermore, our proposed method can be integrated into existing methods and significantly improves the prediction performance. We will release the data and code to the public.
Diancheng WU Jiarui LI Leiou WANG Donghui WANG Chengpeng HAO
This paper presents a novel data compression method for testing integrated circuits within the selective dictionary coding framework. Due to the inverse value of dictionary indices made use of for the compatibility analysis with the heuristic algorithm utilized to solve the maximum clique problem, the method can obtain a higher compression ratio than existing ones.