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A detection method for logic functions suitable for dual-logic synthesis

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Progress in Natural Science:Materials International 2009年第10期19卷 1311-1315页

作者： Yinshui Xia,Fei Sun,Keyi Mao The Faculty of Information Science & Engineering,Ningbo University,Ningbo 315211,China The Faculty of Information Science & Engineering Ningbo University Ningbo 315211 China

Logic functions can be implemented in either AND/OR/NOT-based traditional Boolean(TB) logic or AND/XOR-based Reed-Muller(RM) logic.To the majority of logic functions,it will be beneficial to be partially implemented in both TB logic and RM logic,called dual-logic.In this paper,a detection condition favoring dual-logic synthesis is proposed.A corresponding detection algorithm is developed and implemented in C.The algorithm is applied to test a set of MCNC91 benchmarks for verifying the algorithm.The results show that the proposed algorithm is more efficient than published ones.

关键词： Logic synthesis Boolean logic Reed-Muller logic detection method

A method and device for online magnetic resonance multiphase flow detection

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Petroleum Exploration and Development 2020年第4期47卷 855-866页

作者： DENG Feng XIONG Chunming CHEN Shiwen CHEN Guanhong WANG Mengying LIU Huabing ZHANG Jianjun LEI Qun CAO Gang XU Dongping TAO Ye XIAO Lizhi PetroChina Research Institute of Petroleum Exploration&Development Beijing 100083China Beijing Limecho Technology Co. LtdBeijing 100089China China University of Petroleum Beijing 102249China Institute of Computing Technology China Academy of Railway Sciences Corporation LimitedBeijing 100081China

Most multiphase flow separation detection methods used commonly in oilfields are low in efficiency and accuracy,and have data delay.An online multiphase flow detection method is proposed based on magnetic resonance technology,and its supporting device has been made and tested in lab and field.The detection technology works in two parts:measure phase holdup in static state and measure flow rate in flowing state.Oil-water ratio is first measured and then gas holdup.The device is composed of a segmented magnet structure and a dual antenna structure for measuring flowing fluid.A highly compact magnetic resonance spectrometer system and intelligent software are developed.Lab experiments and field application show that the online detection system has the following merits:it can measure flow rate and phase holdup only based on magnetic resonance technology;it can detect in-place transient fluid production at high frequency and thus monitor transient fluid production in real time;it can detect oil,gas and water in a full range at high precision,the detection isn’t affected by salinity and emulsification.It is a green,safe and energy-saving system.

关键词： multiphase flow magnetic resonance(MR) flow rate phase holdup detection method detection device

Study of Clone Code detection method

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Study of Clone Code Detection Method

Asphalt pavement water film thickness detection and prediction model:A review

作者： Yafang Wang Dongsheng Liu Min Hou College of Computer Science and Technology Inner Mongolia Normal University

In the process of software development and maintenance,developers often use "copypaste" or use the development framework,so that a large number of clone codes appear in the software system.In order to eliminate clone code and reduce the negative effects of clone code,researchers have proposed many excellent methods for clone code detection.This paper first introduces the significance of the research on clone code detection,and sorts out the related concepts of clone code detection.Then,according to the clone code detection technology,the existing techniques can be categorized to Text-based,Token-based,Tree-based,Metric-based and Graph-based categories.The five categories,respectively introduce the corresponding existing methods or tools,and summarize their advantages and disadvantages.Finally summarize the key problems in the current clone code detection research.

关键词： clone code clone detection detection method

来源： cnki会议评论

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cnki会议

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Journal of Traffic and Transportation Engineering(English Edition) 2023年第3期10卷 349-367页

作者： Ke Xiao Bing Hui Xin Qu Hainian Wang Aboelkasim Diab Min Cao School of Highway Chang'an UniversityXi'an 710064China Key Laboratory of Intelligent Construction and Maintenance of CAAC Xi'an 710064China Department of Civil Engineering Aswan UniversityAswan 81542Egypt Wuhan Optics Valley ZOYON Science and Technology Co.Ltd. Wuhan 430000China

Over the course of storm or rainfall event,water thickness builds up on road surface resulting in a loss of contact between vehicle tires and road surface and puts drivers into immediate danger especially at high speeds.Therefore this is a considerably dangerous condition of the road and the realistic measurements and prediction model of water film thickness(WFT)on pavement surface is crucial for determining the road friction coefficient and evaluating the impact of rainfall on traffic safety.A review of the principle as well as critical evaluation of current detection methods of pavement WFT were compared for consistency and accuracy in this paper.The method selection guidelines are given for different road surface water film thickness detection requirements.This paper also introduces the latest development of WFT detection and prediction models for asphalt pavement,and gives the calculation elements and conditions of different WFT prediction models from different modeling ideas,which provides a basis for the selection and optimization of WFT models for future researchers.This article also suggests a few insights as further research directions on this topic.(1)The research can consider the influencing factors of WFT to conduct research on the delineation standard of pavement WFT.(2)In order to meet the future traffic safety dynamic early warning needs,road factors of different material types,disease conditions and linear conditions should be studied,as well as a comprehensive and accurate real-time water film thickness detection and evaluation method considering meteorological factors of rainfall timing,scale and intensity.(3)The prediction model of WFT should be further studied by the analytical method to clarify the influence of the pavement WFT on the driving safety.

关键词： Asphalt pavement Water film thickness detection method Prediction model

Sources, distribution, behavior, and detection techniques of microplastics in soil: A review

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China Geology 2023年第4期6卷 695-715页

作者： Yu-chen Yan Zhong-fang Yang School of Earth Sciences and Resources China University of GeosciencesBeijing 100083China

In recent years, the problem of environmental pollution caused by microplastics has attracted widespread attention. This paper reviews the latest research progress in terms of the source, content and distribution characteristics, harm, and detection technology of soil microplastics by referring to the relevant literature on soil microplastics worldwide. It concludes that:(1) Existing studies worldwide have detected the presence of microplastics in soil, water, and atmosphere, and the use of agricultural films, sewage sludge,and other man-made activities are the main sources of microplastics in soil;(2) microplastics can adsorb heavy metals, persistent organic pollutants and antibiotics in soil, change the physical and chemical properties of soil. This will result in composite pollution and harm to the ecosystem;(3) microplastics in soil not only can destroy the activity of key soil microorganisms, but also enter the body of crops and soil animals, affecting normal growth of crops and soil animals, and further threaten human health;(4) at present, there is no unified operating standard for the sampling, processing, and detection process of microplastics. Analysis methods such as visual inspection, spectroscopy, and thermal analysis have both advantages and disadvantages, and emerging detection technologies require urgent development.Microplastics have become a new pollutant in soil and their distribution characteristics are closely related to human activities. They pollute the environment and threaten human health through the food chain.Although related research on soil microplastics has just begun, it will become the focus of research in the future.

关键词： soil microplastic heavy metal organic pollutant antibiotic microorganism ecological risk composite pollution detection method

method for detecting 2D grapevine winter pruning location based on thinning algorithm and Lightweight Convolutional Neural Network

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International Journal of Agricultural and Biological Engineering 2022年第3期15卷 177-183页

作者： Qinghua Yang Yuhao Yuan Yiqin Chen Yi Xun Key Laboratory of E&M(Zhejiang University of Technology) Ministry of Education&Zhejiang ProvinceHangzhou 310023China

In viticulture,there is an increasing demand for automatic winter grapevine pruning devices,for which detection of pruning location in vineyard images is a necessary task,susceptible to being automated through the use of computer vision methods.In this study,a novel 2D grapevine winter pruning location detection method was proposed for automatic winter pruning with a Y-shaped cultivation system.The method can be divided into the following four steps.First,the vineyard image was segmented by the threshold two times Red minus Green minus Blue(2R−G−B)channel and S channel;Second,extract the grapevine skeleton by Improved Enhanced Parallel Thinning Algorithm(IEPTA);Third,find the structure of each grapevine by judging the angle and distance relationship between branches;Fourth,obtain the bounding boxes from these grapevines,then pre-trained MobileNetV3_small×0.75 was utilized to classify each bounding box and finally find the pruning location.According to the detection experiment result,the method of this study achieved a precision of 98.8%and a recall of 92.3%for bud detection,an accuracy of 83.4%for pruning location detection,and a total time of 0.423 s.Therefore,the results indicated that the proposed 2D pruning location detection method had decent robustness as well as high precision that could guide automatic devices to winter prune efficiently.

关键词： grapevine winter pruning Lightweight Convolutional Neural Network thinning algorithm detection method

Optimization of Solid-Phase Extraction Conditions for Perfluorooctanoic Acid in Leachate

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Wuhan University Journal of Natural Sciences 2022年第4期27卷 341-348页

作者： WANG Ying ZENG Xiaolan YU Zhipeng JIN Jiyuan MI Ruidong SUN Yuan Power China Chengdu Engineering Corporation Limited Chengdu 610072SichuanChina College of Environment and Ecology Chongqing UniversityChongqing 400045China

In order to optimize the solid phase extraction(SPE)conditions of perfluorooctanoic acid(PFOA)in the raw leachate and treated leachate,the effects of activator properties,SPE cartridge,p H value,ionic strength,and eluent properties were studied through single factor experiments.The optimal results of each single factor were obtained.Considering that the concentration of PFOA in the treated leachate is lower than that of the raw leachate,the SPE conditions of the treated leachate have been further optimized.Based on the above single-factor experiment,the main influencing factors were screened out as the volume of activator,ionic strength,and volume of eluent,and the three-factor threelevel response surface methodology(RSM)was optimized.The optimum SPE conditions of PFOA from treated landfill leachate were as follows:Activation of weak anion exchange(WAX)cartridge with 10 mL methanol,dosage of 600 mg KCl,6 m L 1%ammonia methanol eluted PFOA,the theory recovery rate is over95.67%.It has been verified that the error between the predicted value and the actual extraction recovery is small and has good repeatability.

关键词： response surface methodology(RSM) box-behnken design perfluorooctanoic acid solid phase extraction detection method

Research Progress of MicroRNA in Early detection of Ovarian Cancer

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Chinese Medical Journal 2015年第24期128卷 3363-3370页

作者： Ze-Hua Wang Obstetrics and Gynecology Hospital of Fudan University Shanghai 200011 China Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases Shanghai 200011 China

Objective： This review aimed to update the progress of microRNA （miRNA） in early detection of ovarian cancer. We discussed the current clinical diagnosis methods and biomarkers of ovarian cancer, especially the methods of miRNA in early detection of ovarian cancer. Data Sources： We collected all relevant studies about miRNA and ovarian cancer in PubMed and CNKI from 1995 to 2015. Study Selection： We included all relevant studies concerning miRNA in early detection of ovarian cancer, and excluded the duplicated articles. Results： miRNAs play a key role in various biological processes of ovarian cancer, such as development, proliferation, differentiation, apoptosis and metastasis, and these phenomena appear in the early-stage. Therefore, miRNA can be used as a new biomarker for early diagnosis of ovarian cancer, intervention on miRNA expression of known target genes, and potential target genes can achieve the effect of early prevention. With the development ofnanoscience and technology, analysis methods ofmiRNA are also quickly developed, which may provide better characterization of early detection of ovarian cancer. Conclusions： In the near future, miRNA therapy could be a powerful tool for ovarian cancer prevention and treatment, and combining with the new analysis technology and new nanomaterials, point-of-care tests for miRNA with high throughput, high sensitivity, and strong specificity are developed to achieve the application of diagnostic kits in screening of early ovarian cancer.

关键词： detection method MicroRNA Ovarian Cancer

GPS Spoofing Attack detection in Smart Grids Based on Improved CapsNet

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China Communications 2021年第3期18卷 174-186页

作者： Yuancheng Li Shanshan Yang School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China

This paper analyzes the influence of the global positionong system(GPS)spoofing attack(GSA)on phasor measurement units(PMU)measurements.We propose a detection method based on improved Capsule Neural Network(CapsNet)to handle this attack.In the improved CapsNet,the gated recurrent unit(GRU)is added to the front of the full connection layer of the CapsNet.The improved CapsNet trains and updates the network parameters according to the historical measurements of the smart grid.The detection method uses different structures to extract the temporal and spatial features of the measurements simultaneously,which can accurately distinguish the attacked data from the normal data,to improve the detection accuracy.Finally,simulation experiments are carried out on IEEE 14-,IEEE 118-bus systems.The experimental results show that compared with other detection methods,our method is proved to be more efficient.

关键词： smart grid detection method improved capsule neural network phasor measurement units global positioning system spoofing attack