An Improved LDV-Hop Localization Algorithm in Wireless Sensor Networks

Xiaoan Bao,Zhongtao Ren,Na Zhang,Xing Hu,Tongshu Wu,Yangqiu Liu 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.10

Localization of sensor nodes is a fundamental and a key technology in wireless sensor networks, it has been widely studied by many universities and research institutions in recent years and many localization algorithms have been put forward by scholars from diverse aspects. A new localization algorithm, which is based on the LDV-Hop algorithm, is proposed in this paper. Firstly, to reduce the localization error we modify the average one-hop distance between anchor nodes, and the average one-hop distance used for each unknown node's location is also modified through weighting the received average one-hop distance from anchor nodes. Then, to solve the problem of low localization coverage which is the main disadvantage of LDV-Hop localization algorithm, we regard regular node with newly estimated location as anchor node and utilize believable factor threshold to restrain the error accumulation brought by this method.

Research of The Web Service Automatic Composition based on Generalized Stochastic Petri Nets

Xiaoan Bao,Jun Gao,Xiaoming Xie,Hui Lin,Na Zhang 보안공학연구지원센터 2013 International Journal of Multimedia and Ubiquitous Vol.8 No.4

Large-Scale Text Similarity Computing with Spark

Xiaoan Bao,Shichao Dai,Na Zhang,Chenghai Yu 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.4

Text understanding is a hot research in Natural Language Processing and Information Retrieval. In recent years, it has received wide attention and research. In the era of big data, Understanding text in large-scale datasets is a challenge. Although the earliest systems designed for these workloads, such as MapReduce, gave users a powerful, but low-level, procedural programming interface. So, MapReduce doesn’t compose well for lager text applications. Recently, Spark, an in-memory cluster-computing platform, has been proposed. It has emerged as a popular framework for large-scale data processing and analytics. It provides a general-purpose efficient cluster computing engine and simpler for the end users. In this work, we consider using Vector Space Model (VSM) and TF-IDF weighting schema and feature hashing feature extraction techniques in order to solve the problem of large-scale text data similarity computing by Spark. As a result, Experimental results that using Spark in order to solve document similarity computation problems as soon as quickly by 20Newsgroups. In additions, It is more benefit from document classification and clustering of machine learning tasks.

Combinatorial Test Generation Using Improved Harmony Search Algorithm

Xiaoan Bao,Shuhan Liu,Na Zhang,Meng Dong 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.9

Combinatorial testing can effectively detect the faults triggered by interactions among the various factors in software system. Harmony Search Algorithm (HS), which is a new optimization algorithm and has been widely applied in the fields of portfolio design, repeatedly adjusts the solution variables in harmony memory to reach the optimum. In order to improve the convergence speed of HS, we propose an improved HS algorithm (IHS) and uses one-test-at-a-time strategy to generate a set of optimum initial solutions in IHS. To avoid the algorithm falling into local optima, we dynamically adjust the values of HMCR and PAR in the new algorithm. Compared to some existing algorithms and tools, the improved harmony search algorithm performs more stably and efficiently in generating optimum combinatorial test cases.

Automatic Generation of Test Cases Based On Multi-population Genetic Algorithm

Na Zhang,Biao Wu,Xiaoan Bao 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6

Improving Test Efficiency through Prioritization Based On Testing Dependency

Na Zhang,Yangqiu Liu,Xiaoan Bao,Xiaoming Xie,Zhongtao Ren,Hui Lin 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.6

During the various iterations of software development, test case prioritization generally schedules test cases in order to increase test efficiency as soon as possible without reducing the scale of the test. It is noted that currently, many prioritization techniques are usually based on the assumption that the test cases are independent so as to reduce testing effort. However in the actual test, the dependencies and relations exist between the test cases. In this paper, we propose a new type of prioritization technique based on the relationship of dependencies between test cases. We gather the dependency information of a test suite and then put forward a weighted depth-first search algorithm to determine the most effective order. To assess our approach, an academic feasibility study and three industrial experiments are conducted. Evaluation results indicate that our proposed method can be used to improve the fault detection effectiveness when compared with random ordering and some existed prioritization techniques which are based on function coverage.

Weighted sparsity-based denoising for extracting incipient fault in rolling bearing

Wan Zhang,Minping Jia,Xiaoan Yan,Lin Zhu 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.10

Given that the incipient fault is too weak for extraction, a novel approach that is based on sparse optimization is proposed for incipient fault diagnosis. The proposed optimization method consists of three steps: First, autocorrelation analysis is utilized to filter broadband random noise. Then, the weighted sparsity-based denoising method is proposed to extract periodic impulses. The prior knowledge that periodic impulses are sparse is used to constitute a penalty term; thus a novel weighted sparse optimization model is established. The majorization-minimization method is used to solve the optimization model. The high-pass filter in quadratic fidelity term is constructed by a Butterworth filter based on banded matrices, thus effectively improving computational efficiency. Lastly, the interval of periodic impulses, which corresponds to the fault frequency of rolling bearing, is obtained. Moreover, simulation and experimental results show that the proposed approach can successfully extract fault features from the signals of low signal to noise ratio.

Dynamics modeling and modal experimental study of high speed motorized spindle

Yunsong Li,Xiaoan Chen,Peng Zhang,Jinming Zhou 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.3

This paper presents a dynamical model of high speed motorized spindles in free state and work state. In the free state, the housing is modeled as a rotor with equivalent masses including bearing pedestals, motor stator and rear end cover. As a consequence, a double rotor dynamics can be modeled for high speed motorized spindles by a bearing element which connects the housing and bearing pedestals. In the work state, the housing is fixed and the system becomes a bearing-rotor dynamical model. An excitation-measurement test in the free state is designed to analyze the cross spectral density and auto spectral density of input and output signals. Then the frequency response function of system and coherence function of input and output signals which are used to analyze the inherent characteristics of the double-rotor model can be obtained. The other vibration test in the work state is designed to research the dynamical supporting characteristics of bearings and the effects from bearings on the inherent characteristics of the system. The good agreement between the experimental data and theoretical results indicates that the dynamical model in two states is capable of accurately predicting the dynamic behavior of high speed motorized spindles.

Efficacy and safety of neoadjuvant chemotherapy versus primary debulking surgery in patients with ovarian cancer: a meta-analysis

Xiaofeng Lv,Shihong Cui,Xiaoan Zhang,Chenchen Ren 대한부인종양학회 2020 Journal of Gynecologic Oncology Vol.31 No.2

Objective: Neoadjuvant chemotherapy (NACT) for the treatment of epithelial ovarian cancer (EOC) has remained controversial. This meta-analysis was performed to systematically assess the efficacy and safety of NACT versus primary debulking surgery (PDS) in patients with EOC. Methods: PubMed, Embase, ClinicalTrials.gov, and Cochrane Library were queried to assess the therapeutic value of NACT versus PDS in EOC. Electronic databases were queried by using the keywords “ovarian cancer/neoplasms”, “primary debulking surgery”, and “neoadjuvant chemotherapy”. Results: The available trials were pooled, and hazard ratios (HRs), relative risk ratios (RRs) and associated 95% confidence intervals (95% CIs) were determined. Sixteen trials involving 57,450 participants with EOC (NACT, 9,475; PDS, 47,975) were evaluated. We found that NACT resulted in markedly decreased overall survival than PDS in patients with EOC (HR=1.30; 95% CI=1.13–1.49; heterogeneity: p<0.001, I2=82.7%). Furthermore, our results demonstrated that the NACT group displayed increased completeness of debulking removal (RR=1.69, 95% CI=1.32–2.17; heterogeneity: p<0.001, I2=81.9%), and reduced risk of postsurgical death (RR=0.18, 95% CI=0.06–0.51; heterogeneity: p=0.698, I2=0%) and major infection (RR=0.29, 95% CI=0.17–0.51; heterogeneity: p=0.777, I2=0%) compared with patients administered PDS. Conclusions: This meta-analysis indicated that NACT results in increased completeness of debulking removal, and reduced risk of postsurgical death and major infection compared with PDS, while PDS is associated with improved survival in comparison with NACT in EOC patients. Trial Registration: PROSPERO Identifier: CRD42019120625

Indoor feeding combined with restricted grazing time improves body health, slaughter performance, and meat quality in Huang-huai sheep

Huang Yafeng,Zhao Mengyu,Zhang Xiaoan,Wei Huiqing,Liu Lumeng,Zhang Zi Jun,Cheng Xiao,Wang Guanjun,Ren Chunhuan 아세아·태평양축산학회 2023 Animal Bioscience Vol.36 No.11

Objective: The aim of this study was to evaluate the effects of three feeding systems, i.e., indoor feeding (CON), indoor feeding with 4-h daily access to grazing artificial pasture (ITGP), and indoor feeding with 8-h daily access to grazing artificial pasture (IEGP), on the plasma antioxidant and immunological capacity, slaughter characteristics, meat quality and economic efficiency of Huang-huai lambs. Methods: Thirty-three healthy Huang-huai rams with similar body weight (approximately 5 mo of age, 28.96±1.01 kg) were assigned equally to three experimental groups. When finished fattening, six lambs from each group were collect blood samples for plasma analyses and then slaughtered to determine slaughter characteristics and obtain biceps brachii muscle for further analysis of meat quality and fatty acid profile. Results: Compared to CON group, animals submitted to ITGP and IEGP groups resulted in greater contents of serum glutathione peroxidase, immunoglobulins (IgA, IgG, and IgM), polyunsaturated fatty acids (PUFA), n-6 PUFA, and PUFA/saturated fatty acid (FA) ratio and lower palmitic /oleic acid ratio (p<0.05). Moreover, animals in ITGP group exhibited a higher (p<0.05) loin eye area, content of meat crude protein (CP), and eicosetrienoic acid compared to CON group, while slaughter performance was superior (p<0.05) to that of the IEGP group. The economic efficiency of ITGP group was 70.12% higher than that of CON group, while the IEGP group exhibited a decrease of 92.54% in economic efficiency compared to the CON group. Conclusion: Restricted grazing time combined with indoor feeding was more effective in conferring superior body health, carcass traits and economic efficiency in Huang-huai lambs, as well as higher CP content and healthier FA composition in the resulting meat.