ISSN 0253-2778

CN 34-1054/N

2018 Vol. 48, No. 9

Display Method:
Original Paper
Weak nuclear pulse signal extraction from intensive background noise
ZHANG Jiangmei, WANG Kunpeng, JI Haibo, FENG Xinghua
2018, 48(9): 691-695. doi: 10.3969/j.issn.0253-2778.2018.09.001
It is a very challenging problem to extract the amplitude and occurring time of weak nuclear pulse signals in the existence of intensive background noise. To solve this problem, this paper proposes a pulse signal estimation method based on Gabor transform and sparse representation. Firstly, it builds a pulse signal representation dictionary through the Gabor decomposition of mononuclear pulse signal samples. Then it eliminates the fluctuation of the Gabor bases, which is caused by the detector variation and the measurement noise, by using K-SVD algorithm, and learns a self-consistent over-complete dictionary which is used to represent the useful signal being overwhelmed in the background noise. Finally, it reconstructs the desired signal by an improved OMP algorithm, greatly attenuates the noise and achieves the goal of extracting the weak nuclear pulse signal. The effectiveness and efficiency of the proposed method are verified through simulations and experiments on a CsI(Tl) detector. Results confirm that the proposed method outperforms the traditional Salley-Keys smoothing and Kalman filtering methods with smaller estimation errors of the amplitude and peak occurring time of the concerned nuclear pulse signal.
A high-speed voltage-mode sense amplifier for SRAM
LIU Kangsheng, YU Zhiguo, WANG Tian, LIANG Sisi, QIAN Liming, GU Xiaofeng
2018, 48(9): 696-702. doi: 10.3969/j.issn.0253-2778.2018.09.002
This paper reports a novel sense amplifier (SA) suitable for voltage sensing in the read operation of static random access memory (SRAM). Contrary to the conventional cross-coupled SA, an NMOS cross coupling amplifier is added as the second stage amplifier and the pull-up and pull-down circuits are added as the output circuit. The proposed structure can quickly amplify the bit line voltage difference with high gain, improve the sensitivity, and ensure that the data output port of the SRAM encounters no interference when the utility model is not working. The simulation results show that this design reduces 95% of the voltage required for the bit lines to guarantee the full swing at output nodes and shortens 80% of the sensing delay for the same input voltage difference compared with the conventional SA.
Building software system of real-time controller communication by CANopen protocol based on ROS
JIA Pengfei, WANG Rongchuan, XYU Linsen, CHEN Danhui, LI Kaixia
2018, 48(9): 703-710. doi: 10.3969/j.issn.0253-2778.2018.09.003
The traditional robot software is facing problems of low developing efficiency and disunity of protocol of controller communication, aiming at these problems, the robot operating system (ROS) software framework was used to improve the efficiency of software development; the use of high performance industrial control protocol CANopen as the communication scheme of controller; and the help of modular manipulator hardware platform to further improve the speed of software development. Finally, the software system of controller communication by CANopen protocol based on ROS for modular manipulator was constructed. The experimental results show that the communication software system not only has the high developing efficiency and flexibility, but also meets the requirements for the real-time performance of the general robot.
A method of interference mitigation for GPS signal in cyclic spectral domain
HU Yi, YU Baoguo, DENG Zhixin, ZOU Guozhu
2018, 48(9): 711-717. doi: 10.3969/j.issn.0253-2778.2018.09.004
Aiming at the complicated strong interference overlapped on the weak GPS signal in time and frequency domains, and motivated by the idea of signal cancellation, a method for mitigating the strong interference in the cyclic spectral domain is proposed. First, the cyclic frequencies (CFs) of the interference are obtained by the cyclic spectral analysis; then with the obtained CFs and the adaptive FREquency SHift (FRESH) filter, a detailed process of mitigating the strong interference by the FRESH filtering is formed; finally by implementing the FRESH filtering with the adaptive least mean square (LMS) algorithm, the strong overlapped interference can be effectively mitigated. Simulations on the acquisition and tracking of performance of the separated GPS signal after the interference mitigation under different circumstances validate the proposed method.
Dynamic task scheduling algorithm of parallel computing for FCD big data
CHEN Feng, ZHANG Zhi, LI Qinjian, CHEN Yuqiang, CHEN Guoliang
2018, 48(9): 718-722. doi: 10.3969/j.issn.0253-2778.2018.09.005
FCD (floating car data) technique is new way of collecting real-time traffic flow from large-scale urban networks. It is necessary to implement rapid processing of FCD big data for the dynamic guidance and control of urban traffic. A dynamic task scheduling algorithm is proposed for parallel computation of FCD. To address the uncertainty and dynamics of FCD package processing, FCD packages are partitioned dynamically. The load balance among computing nodes can be achieved using the dynamic task allocation strategy. The algorithm is developed on LoongSon big data integrated machine platform and evaluated using field FCD. The experimental results indicate that the proposed algorithm has significantly higher parallel processing performances compared to the polling scheduling algorithm and Min-Min scheduling algorithm.
Application of the pruning technique in dominant query
SUN Zhi, SUN Xuejiao
2018, 48(9): 723-729. doi: 10.3969/j.issn.0253-2778.2018.09.006
User preferences can influence the user choices in many cases, and the question of preference query becomes an increasingly important issue in relational databases. In many applications, qualitative preferences can be applied more widely than quantitative preferences. In the existing studies of multi-attribute preferences, preference attributes do not have a dependency relationship, but CP-nets(conditional preference networks) is a graph model that represents multi-attribute qualitative preferences with dependencies. At present, the processing of preference queries mainly uses dominance queries and compares the two outcomes one by one to obtain the outcome that satisfies the user preferences. It can be found that comparing the outcomes in pairs causes great waste of resources. Reduce the number of comparisons of its outcomes is examined. The pruning technique is proposed to be applied to dominance queries, and the path of the flipping sequence is pruned so as to effectively reduce the space for database search.
Network public opinion propagation model based on interest matching in multiple relationship social network
SUN Gengxin, BIN Sheng
2018, 48(9): 730-738. doi: 10.3969/j.issn.0253-2778.2018.09.007
The relationship between user profiles and the data of microblog content in Sina microblog was obtained by programming and web crawler, and a variety of explicit or implicit relationships between microblog users were discovered by using data mining. On the basis of this, a semi-supervised user interest matching prediction algorithm was proposed. According to the individual state division method of compartment model, a network public opinion propagation model is constructed based on user interest matching through state transition analysis and inference of state transition probability. The results show that the model can well describe the laws of public opinion propagation in social networks, and reproduce the real propagation process of network public opinion in the social network from the perspective of complex networks.
Dialogue matching prediction model applied in campus psychological counseling
TAN Jiali, HE Yu, WU Yanjing, SUN Guangzhong
2018, 48(9): 739-747. doi: 10.3969/j.issn.0253-2778.2018.09.008
Chat-bots have received wide attention in both academia and industry.In academia,there have been many promising research results in the end-to-end dialogue response area.Among them,data-driven dialogue response methods predominate,which learn and understand natural language through deep neural networks.Existing dialogue response models are mainly designed for open domains.The current mature chat-bot applications are mostly used for entertainment.Methods used on professional chat-bots (like psychological counseling chat-bots) are mainly based on rule and template.To enhance the intelligence of the psychological counseling chat-bot, a new method of modeling dialogue matching pattern in the context of campus counseling is proposed.This method is based on the psychological counseling website and Tieba corpus,from which relevant characteristics of words and sentences in the category of psychological counseling types are extracted,and are applied to machine learning and deep learning networks to model the dialogue matching pattern.Compared with traditional dialogue matching models in open domain,the proposed model achieved better matching results with the use of analyzed psychological counseling information.
Migration algorithm for Ceph block device cross clusters
SHAO Xiyu, LI Jing, ZHOU Zhiqiang
2018, 48(9): 748-754. doi: 10.3969/j.issn.0253-2778.2018.09.009
The migration time of huge image files is vital to the efficiency of the whole-system on-line migration of a virtual machine. Therefore, optimizing the migration time has become a hot research area in virtual-machine migration technology. For virtual machines based on a distributed storage system, in which the more common one is Ceph block device, image data must go from the source storage nodes to the source client nodes, then to the destination client nodes, and finally to the destination storage nodes. This way ignores the benefit from the storage system to the migration. Given the above problems, a migration algorithm for Ceph block device cross clusters is effective. Image data go from the source storage nodes to the destination storage nodes in parallel, which uses the network of storage nodes.The result of the experiment shows that this algorithm shortens the migration time,and a few more storage nodes can improve efficiency of this algorithm.
A method of knowledge item recommendation based on Skill-LFM
FANG Jiansheng, XU Yanwu, CAI Ruichu, QIN Yan
2018, 48(9): 755-761. doi: 10.3969/j.issn.0253-2778.2018.09.010
At present, the users of knowledge base mainly get the required knowledge items through search, which relies on the search engine to solve the information overload problem. It is inefficient for real-time online services, and has no integrity and continuity of offline knowledge learning. Therefore, it is proposed that knowledge items should be actively recommended to users by the knowledge base system according to their level of skills, to improve the efficiency of decision making, and also to help users establish a complete knowledge learning system. A collaborative filtering recommendation method is proposed to predict every user's preference on knowledge items, based on the historical behavior of a user on the knowledge items, and the knowledge learning ability of this user. This method combines latent factor model with skill, named Skill-LFM, where the difficulties of knowledge items are taken as potential factors, and users' ability level is considered to give personalized recommendations. Tested on the data from a call center knowledge base, the proposed Skill-LFM outperforms the baseline latent factor model in terms of lower RMSE. Considering the characteristics of the application domain and the historical behavior data of the knowledge base, this paper demonstrates the possibility of further improving knowledge item recommendation through integrating user and knowledge item context information.
Heart physiological and pathological age estimation based on wrapper deviation regression
LI Yongming, XIAO Jie, WANG Pin, YAN Fang
2018, 48(9): 762-769. doi: 10.3969/j.issn.0253-2778.2018.09.011
Researches show that a person age is highly related to his heart. Heart age is very important for examining and monitoring of the heart’s state. Two algorithms for estimating the physiological and pathological age of the heart were proposed based on data mining technique. The first algorithm is based on a regression model for healthy people by using the mean absolute error (MAE), while the latter is based on a regression model for all types of people by considering the age deviation. The optimal age deviation is searched within the range of deviation candidates and is obtained by maximizing the classification accuracy. Based on the optimal age deviation and real age, the heart pathological age is obtained. The public heart dataset is used for verification of the proposed algorithm. Experimental results show that two estimated heart ages are better than the real age, with the apparent significance level the lower than 0.01. Compared with the current heart age estimation algorithm, the heart pathological age estimation algorithm can lead to the better classification capability and is more helpful with improving the classification accuracy of heart disease as a marker or feature. Besides, a new concept——heart pathological age is proposed for the first time, and which may help provide an effective marker for monitoring and supervising heart health.
Origin of Qingbai porcelain technology of Fanchang kiln from the aspect of body and glaze crafts
CUI Mingfang, ZHU Jianhua, XU Fan
2018, 48(9): 770-776. doi: 10.3969/j.issn.0253-2778.2018.09.012
Wavelength dispersive X-ray fluorescence (WDXRF) was used to determine the elemental abundance patterns of the Qingbai porcelain bodies and glazes from Fanchang kiln. In-depth explorations were conducted on the origin of the Qingbai porcelain technology in Fanchang kiln by combining the analysis of polarized light microscope and previous research, systemically contrasting Fanchang Qingbai porcelain with the Xing, Ding, Gongyi white porcelain and Yue blue porcelain in terms of their chemical compositions of porcelain bodies and glazes,