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On periodic groups with prescribed orders of elements

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science China Mathematics 2009年第2期52卷 311-317页

作者： MAZUROV victor Danilovich sobolev Institute of Mathematics Siberian Branch of Russian Academy of Sciences

This is a survey of results and open problems concerning the structure of periodic group with prescribed orders of their elements. In particular, an outline of a proof of the following recent result is given: every pe... 详细信息

关键词： spectrum periodic group local finiteness 20F50

An Improved BPNN Prediction Method Based on Multi-strategy sparrow search Algorithm

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Computers, Materials & Continua 2023年第2期74卷 2789-2802页

作者： Xiangyan Tang Dengfang Feng KeQiu Li Jingxin Liu Jinyang song victor s.sheng College of Intelligence and Computing Tianjin UniversityTianjin300350China school of Computer science and Technology Hainan UniversityHaikou570228China school of Cyberspace security(school of Cryptology) Hainan UniversityHaikou570228China Department of Computer science Texas Tech University TX 79409USA

Data prediction can improve the science of decision-making by making predictions about what happens in daily life based on natural law *** propagation(BP)neural network is a widely used prediction *** reduce its probability of falling into local optimum and improve the prediction accuracy,we propose an improved BP neural network prediction method based on a multi-strategy sparrow search algorithm(MssA).The weights and thresholds of the BP neural network are optimized using the sparrow search algorithm(ssA).Three strategies are designed to improve the ssA to enhance its optimization-seeking ability,leading to the MssA-BP prediction *** MssA algorithm was tested with nine different types of benchmark functions to verify the optimization performance of the *** different datasets were selected for comparison experiments on three groups of *** the same conditions,the mean absolute error(MAE),root mean square error(RMsE),andmean absolute percentage error(MAPE)of the prediction results of MssA-BPwere significantly reduced,and the convergence speed was significantly ***-BP can effectively improve the prediction accuracy and has certain application value.

关键词： Prediction parrow search algorithm back propagation neural network

Fast rectangular matrix multiplication and some applications

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science China Mathematics 2008年第3期51卷 389-406页

作者： victor Y PAN Department of Mathematics and Computer science.Lehman College City University of New York BronxNew York 10468 USA

We study asymptotically fast multiplication algorithms for matrix pairs of arbitrary dimensions, and optimize the exponents of their arithmetic complexity bounds. For a large class of input matrix pairs, we improve the known exponents. We also show some applications of our results: (i) we decrease from O(n 2 + n 1+o(1)logq) to O(n 1.9998 + n 1+o(1)logq) the known arithmetic complexity bound for the univariate polynomial factorization of degree n over a finite field with q elements; (ii) we decrease from 2.837 to 2.7945 the known exponent of the work and arithmetic processor bounds for fast deterministic (NC) parallel evaluation of the determinant, the characteristic polynomial, and the inverse of an n × n matrix, as well as for the solution to a nonsingular linear system of n equations; (iii) we decrease from O(m 1.575 n) to O(m 1.5356 n) the known bound for computing basic solutions to a linear programming problem with m constraints and n variables.

关键词： rectangular matrix multiplication asymptotic arithmetic complexity bilinear algorithm polynomial factorization over finite fields 68Q25 11Y16

Air Pollution Prediction Via Graph Attention Network and Gated Recurrent Unit

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Computers, Materials & Continua 2022年第10期73卷 673-687页

作者： shun Wang Lin Qiao Wei Fang Guodong Jing victor s.sheng Yong Zhang Beijing Key Laboratory of Multimedia and Intelligent software Technology Beijing Artificial Intelligence Institutethe Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Beijing Meteorological Observatory Beijing100089China Nanjing University of Information science&Technology Nanjing210044China China Meteorological Administration Training Centre Beijing100081China Texas Tech University LubbockTX79409United States

PM2.5 concentration prediction is of great significance to environmental protection and human *** accurate prediction of PM2.5 concentration has become an important research ***,PM2.5 pollutants can spread in the earth’s atmosphere,causing mutual influence between different *** effectively capture the air pollution relationship between cities,this paper proposes a novel spatiotemporal model combining graph attention neural network(GAT)and gated recurrent unit(GRU),named GAT-GRU for PM2.5 concentration ***,GAT is used to learn the spatial dependence of PM2.5 concentration data in different cities,and GRU is to extract the temporal dependence of the long-term data *** proposed model integrates the learned spatio-temporal dependencies to capture long-term complex spatio-temporal *** that air pollution is related to the meteorological conditions of the city,the knowledge acquired from meteorological data is used in the model to enhance PM2.5 prediction *** input of the GAT-GRU model consists of PM2.5 concentration data and meteorological *** order to verify the effectiveness of the proposed GAT-GRU prediction model,this paper designs experiments on real-world datasets compared with other *** results prove that our model achieves excellent performance in PM2.5 concentration prediction.

关键词： Air pollution prediction deep learning spatiotemporal data modeling graph attention network

Gate-Attention and Dual-End Enhancement Mechanism for Multi-Label Text Classification

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Computers, Materials & Continua 2023年第11期77卷 1779-1793页

作者： Jieren Cheng Xiaolong Chen Wenghang Xu shuai Hua Zhu Tang victor s.sheng school of Computer science and Technology Hainan UniversityHaikou570228China Hainan Blockchain Technology Engineering Research Center Hainan UniversityHaikou570228China school of Cyberspace security Hainan UniversityHaikou570228China Department of Computer science Texas Tech UniversityLubbock79409USA

In the realm of Multi-Label Text Classification(MLTC),the dual challenges of extracting rich semantic features from text and discerning inter-label relationships have spurred innovative *** studies in semantic feature extraction have turned to external knowledge to augment the model’s grasp of textual content,often overlooking intrinsic textual cues such as label statistical *** contrast,these endogenous insights naturally align with the classification *** our paper,to complement this focus on intrinsic knowledge,we introduce a novel Gate-Attention *** mechanism adeptly integrates statistical features from the text itself into the semantic fabric,enhancing the model’s capacity to understand and represent the ***,to address the intricate task of mining label correlations,we propose a Dual-end enhancement *** mechanism effectively mitigates the challenges of information loss and erroneous transmission inherent in traditional long short term memory *** conducted an extensive battery of experiments on the AAPD and RCV1-2 *** experiments serve the dual purpose of confirming the efficacy of both the Gate-Attention mechanism and the Dual-end enhancement *** final model unequivocally outperforms the baseline model,attesting to its *** findings emphatically underscore the imperativeness of taking into account not just external knowledge but also the inherent intricacies of textual data when crafting potent MLTC models.

关键词： Multi-label text classification feature extraction label distribution information sequence generation

Tunable electrochemistry of gold-silver alloy nanoshells

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Nano Research 2018年第12期11卷 6336-6345页

作者： Lorenzo Russo victor Puntes Arben Merkoci Catalan Institute of Nanoscience and Nanotechnology (ICN2) CSIC and BISTCampus UABBellaterra08193BarcelonaSpain Universitat Autonoma de Barcelona (UAB) Campus UABBellaterra08193BarcelonaSpain Vail d'Hebron Institut de Recerca (VHIR) 08035BarcelonaSpain Institucio Catalana de Recerca i Estudis Avancats (ICREA) P Llub Companys 2308010BarcelonaSpain

The widespread and increasing interest in enhancing biosensing technologies by increasing their sensitivities and lowering their costs has led to the exploration and application of complex nanomaterials as signal transducers and enhancers. In this work, the electrochemical properties of monodispersed AuAg alloy nanoshells (Nss) with finely tunable morphology, composition, and size are studied to assess their potential as electroactive labels. The controlled corrosion of their silver content, caused by the oxidizing character of dissolved oxygen and chlorides of the electrolyte, allows the generation of a reproducible electrochemical signal that is easily measurable through voltammetric techniques. Remarkably, the underpotential deposition of dissolved Ag+ catalyzed on AuAg Ns surfaces is observed and its dependence on the nanoparticle morphology, size, and elemental composition is studied, revealing a strong correlation between the relative amounts of the two metals. The highest catalytic activity is found at Au/Ag ratios higher than ≈ 10, showing how the synergy between both metals is necessary to trigger the enhancement of Ag+ reduction. The ability of AuAg Nss to generate an electrocatalytic current without the need for any strong acid makes them an extremely promising material for biosensing applications.

关键词： Au nanoshells nanoparticles surface chemistry underpotential deposition

An interpretable model for large-scale smart contract vulnerability detection

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Blockchain(Research and Applications) 2024年第3期5卷 130-139页

作者： Xia Feng Haiyang Liu Liangmin Wang Huijuan Zhu victor s.sheng City University of Macao Macao 999078China Jiangsu University Zhenjiang 212013China southeast University Nanjing 211189China Texas Tech University Lubbock 79409USA

smart contracts hold billions of dollars in digital currency,and their security vulnerabilities have drawn a lot of attention in recent *** methods for detecting smart contract vulnerabilities rely primarily on symbol execution,which makes them time-consuming with high false positive ***,deep learning approaches have alleviated these issues but still face several major limitations,such as lack of interpretability and susceptibility to evasion *** this paper,we propose a feature selection method for uplifting *** fundamental concept of this method is a feature selection algorithm,utilizing interpretation outcomes to select critical features,thereby reducing the scales of *** learning process could be accelerated significantly because of the reduction of the feature *** experiment shows that our proposed model performs well in six types of vulnerability *** accuracy of each type is higher than 93%and the average detection time of each smart contract is less than 1 ***,through our proposed feature selection algorithm,the training time of each type of vulnerability is reduced by nearly 80%compared with that of its original.

关键词： Blockchain Vulnerability detection smart contract

Determining short chain fatty acids in sewage sludge hydrolysate: A comparison of three analytical methods and investigation of sample storage effects

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Journal of Environmental sciences 2014年第4期26卷 926-933页

作者： victor Ibrahim Tobias Hey Karin Jonsson VA sYD SE-201 21 Malmo Sweden Water and Environmental Engineering Department of Chemical Engineering Lund University SE-21100 Lund Sweden

In anaerobic digestion, the production of short-chain fatty acids （sCFAs） can be beneficial or harmful to the overall process, depending on the concentration of accumulated acids. Therefore, the accurate determination of the sCFA concentration in both fresh and stored sludge hydrolysates is important. To select a suitable method for monitoring sCFAs during the anaerobic digestion of sewage sludge, the accuracy of three available analytical methods, including 5 pH point acid titration （TITRA5）, gas chromatography （GC）, and spectrophotometry, were compared in the present study. The results revealed that TITRA5 and GC displayed better agreement in the achieved measurements and higher precision and accuracy than the spectrophotometric assay, as supported by the application of different statistical models. TITRA5 excelled in titrating unfiltered hydrolysate while simultaneously measuring the alkalinity, whereas the GC method provided detailed information on the contribution of different fatty acids to the total acidity. In contrast, the spectrophotometric assay suffered from many forms of interference, depending on the sample＇s matrix. sCFA production followed the pattern of enzymatic reactions and fitted the Michaelis-Menten model. In addition to promoting TITRA5 as an accurate and robust analytical tool for routine sCFA analyses, this comparative study also demonstrated the possibility of storing hydrolysate samples at different temperatures and durations without altering the sCFA measurements.

关键词： five pH point titration gas chromatography spectrophotometry short-chain fatty acids sludge hydrolysis sample storage

Load Optimization scheduling of Chip Mounter Based on Hybrid Adaptive Optimization

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Complex system Modeling and simulation 2023年第1期3卷 1-11页

作者： Xuesong Yan Hao Zuo Chengyu Hu Wenyin Gong victor s.sheng school of Computer science China University of GeosciencesWuhan 430074China Department of Computer science Texas Tech UniversityLubbockTX 79409−3104USA

A chip mounter is the core equipment in the production line of the surface-mount technology,which is responsible for finishing the mount *** is the most complex and time-consuming stage in the production ***,it is of great significance to optimize the load balance and mounting efficiency of the chip mounter and improve the mounting efficiency of the production *** this study,according to the specific type of chip mounter in the actual production line of a company,a maximum and minimum model is established to minimize the maximum cycle time of the chip mounter in the production *** production efficiency of the production line can be improved by optimizing the workload scheduling of each chip *** this basis,a hybrid adaptive optimization algorithm is proposed to solve the load scheduling problem of the *** hybrid algorithm is a hybrid of an adaptive genetic algorithm and the improved ant colony *** combines the advantages of the two algorithms and improves their global search ability and convergence *** experimental results show that the proposed hybrid optimization algorithm has a good optimization effect and convergence in the load scheduling problem of chip mounters.

关键词： surface Mount Technology(sMT) chip mounter load optimization scheduling adaptive genetic algorithm ant colony algorithm