Weidong Wang

China University of Mining and Technology

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Dian Li

Beijing University of Technology

Liqiang Wang

University of Central Florida

Dongyun Zhang

Shanghai Institute of Technology

Wei Lu

University of Chinese Academy of Sciences

Xuechao Yang

Affiliated Hospital of Nantong University

Weiwei Xing

Beijing Jiaotong University

Wangda Luo

Beijing University of Technology

Yinghai Zhang

Beijing University of Posts and Telecommunications

Y. James Kang

Sichuan University

Yange Li

Central South University

Cooperative Institutions

Beijing University of Technology

Chinese Academy of Sciences

Beijing University of Posts and Telecommunications

Huazhong University of Science and Technology

Zhejiang University

Tsinghua University

University of Science and Technology of China

Wuhan University

Sun Yat-sen University

Shanghai Jiao Tong University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

A Resilient Framework for Fault Handling in Web Service Oriented Systems

Weidong Wang Liqiang Wang Wei Lu

Resilience is an important factor in designing web service oriented systems due to frequent failures arising in runtime. These failures derive from the stochastic and uncertainty nature of a composite web service. Service providers need to rapidly address issue when a fault occurs in system running. But it is not easy to locate and fix the faults only using the log generated by the system. In this paper, we propose a resilient framework to automatically generate a fault handling strategy for each failed service to improve the efficiency of fault handling. In the framework, we design and implement three components including exception analyzer, decision maker, and strategy selector. First, The exception analyzer builds a record, derived from the system log generated by an application, for each failed service. Next, the decision maker adopts a k-means clustering approach to construct a decision including the fault handling to each failed service in a scope. Then, the strategy selector uses an integer program solver to generate the solution to strategy selection problem that is boiled down to the optimization problem. The experiment shows that the framework can improve resilience of Web service-oriented systems under acceptable overheads, and meanwhile the accuracy of fault handling strategy is over 95%.

Resilience

Scope (computer science)

Solver

10.1109/icws.2015.93

Cite

Citations (11)

A web service based gateway architecture for wireless sensor networks

International Conference on Advanced Communication Technology (2009)

Weidong Wang Yuexian Zou Guangyi Shi Yuesheng Zhu

This paper provides a novel method to access ZigBee based wireless sensor networks (WSN) from the Internet using web service approach. We designed a novel gateway between the WSN and the Internet mainly for the scenario of home and building automation. With the improvement of the traditional gateway, the users on the Internet can access the data of the sensor networks flexibly via web services. Each node in the WSN has a unique IP as its identifier, and it can be accessed by the IP directly.

H.248

Gateway (web page)

Residential gateway

Gateway address

Internetworking

Sensor web

Source

Cite

Citations (14)

ISAT: An intelligent Web service selection approach for improving reliability via two-phase decisions

Information Sciences (2017)

Weidong Wang Zhangqin Huang Liqiang Wang

Decision problem

10.1016/j.ins.2017.12.048

Cite

Citations (15)

Feasibility Analysis of Intelligent Instrument Application In Nuclear Power

Shuzhi Chen Meiliang Huang Qimeng Shen Jie Chen Xiaoqiang Liu

Abstract To achieve the in-depth combination of informatization and intelligence has become a development trend in the nuclear power industry, and the digitization/intelligence of instrumentation is a big part. Based on the technical status of nuclear power instruments and industrial integrated circuits, this paper analyzes the feasibility and suggestions of intelligent/digital instrument application for nuclear power plant by combing the environmental conditions of nuclear power, intelligence/digitization of typical meters, testing and verification etc. basic work.

Digitization

Informatization

Instrumentation

10.1115/icone29-93298

Cite

Citations (0)

Crowd counting using accumulated HOG

Tianchun Xu Xiaohong Chen Guo Wei Weidong Wang

People count is an important indicator in video surveillance. Due to the overlapping objects and cluttered background, counting people accurately in actual crowded scene remains a non-trivial problem. Existing regression-based methods either learn a single model mapping the global feature to people count, or estimate localized count by training a large number of regressors. In this paper, we present an intermediate approach using the accumulated HOG feature. Our approach is able to capture the spatial difference of crowd structure and does not need to train a large number of regressors. Contrast to the low-level features existing regression-based methods generally use, the accumulated HOG feature is more robust. Extensive evaluations have been done on five benchmark datasets in the field of crowd counting, which demonstrate the robustness and effectiveness of our approach. In particular, the processing speed is fast enough to be applied to practical applications.

Robustness

Benchmark (surveying)

Feature (linguistics)

10.1109/fskd.2016.7603465

Cite

Citations (11)

A novel method for periapical microsurgery with the aid of 3D technology: a case report

BMC Oral Health (2018)

Shangzhu Ye Shiyong Zhao Weidong Wang Qianzhou Jiang Xuechao Yang

Trephine

Radiodensity

3d printer

10.1186/s12903-018-0546-y

Cite

Citations (65)

A Two-phase Recommendation Framework for Consistent Java Method Names

arXiv (Cornell University) (2022)

Weidong Wang Dian Li Y. James Kang

In software engineering (SE) tasks, the naming approach is so important that it attracts many scholars from all over the world to study how to improve the quality of method names. To accurately recommend method names, we employ a novel framework to handle this problem. In our expeirments, nearly 8 million Java methods are collected from open source organizations as our evaluation dataset. In the first-phase recommendation, we introduce a fast and simple classifier based on the fast text neural network for reccomending potential method category. In the second-phase recomendation, we employ both two Long Short Term Memory Networks to reccomend consitent method names from each classification. Evaluation results prove that the proposed approach significantly outperforms state-of-the-art approach.

10.48550/arxiv.2201.09476

Cite

Citations (0)

OMP-Engineer: Bridging Syntax Analysis and In-Context Learning for Efficient Automated OpenMP Parallelization

arXiv (Cornell University) (2024)

Weidong Wang Haoran Zhu

In advancing parallel programming, particularly with OpenMP, the shift towards NLP-based methods marks a significant innovation beyond traditional S2S tools like Autopar and Cetus. These NLP approaches train on extensive datasets of examples to efficiently generate optimized parallel code, streamlining the development process. This method's strength lies in its ability to swiftly produce parallelized code that runs efficiently. However, this reliance on NLP models, without direct code analysis, can introduce inaccuracies, as these models might not fully grasp the nuanced semantics of the code they parallelize. We build OMP-Engineer, which balances the efficiency and scalability of NLP models with the accuracy and reliability of traditional methods, aiming to enhance the performance of automating parallelization while navigating its inherent challenges.

10.48550/arxiv.2405.03215

Cite

Citations (0)

SiC reinforced AlSi10Mg composites fabricated by selective laser melting

Journal of Alloys and Compounds (2021)

Dongyun Zhang Denghao Yi Xuping Wu Zhiyuan Liu Weidong Wang

Selective Laser Melting

Relative density

10.1016/j.jallcom.2021.162365

Cite

Citations (51)

A Novel Method of Seismic Signal Detection Using Waveform Features

Applied Sciences (2020)

Jian Li Mengmin He Gaofeng Cui Xiaoming Wang Weidong Wang

The detection of seismic signals is vital in seismic data processing and analysis. Many algorithms have been proposed to resolve this issue, such as the ratio of short-term and long-term power averages (STA/LTA), F detector, Generalize F, and etc. However, the detection performance will be affected by the noise signals severely. In this paper, we propose a novel seismic signal detection method based on the historical waveform features to improve the seismic signals detection performance and reduce the affection from the noise signals. We use the historical events location information in a specific area and waveform features information to build the joint probability model. For the new signal from this area, we can determine whether it is the seismic signal according to the value of the joint probability. The waveform features used to construct the model include the average spectral energy on a specific frequency band, the energy of the component obtained by decomposing the signal through empirical mode decomposition (EMD), and the peak and the ratio of STA/LTA trace. We use the Gaussian process (GP) to build each feature model and finally get a multi-features joint probability model. The historical events location information is used as the kernel of the GP, and the historical waveform features are used to train the hyperparameters of GP. The beamforming data of the seismic array KSRS of International Monitoring System are used to train and test the model. The testing results show the effectiveness of the proposed method.

SIGNAL (programming language)

10.3390/app10082919

Cite

Citations (11)