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1.th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Willis, Michael Zhang, L.I. Liu, H.A.N. Xie, Hailun Mistry, Kamlesh Northumbria University Faculty of Engineering and Environment Department of Computer and Information Sciences NewcastleNE1 8ST United Kingdom Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

ISBN: (纸本)9780738124261

The identification of the most discriminative features in an explainable AI decision-making process is a challenging problem. This research tackles such challenges by proposing Particle Swarm Optimization (PSO) variants embedded with novel mutation and sampling iteration operations for feature selection in object recognition. Specifically, five PSO variants integrating different mutation and sampling strategies have been proposed to select the most discriminative feature subsets for the classification of different objects. A mutation strategy is firstly proposed by randomly flipping the particle positions in some dimensions to generate new feature interactions. Moreover, instead of embarking the position updating evolution in PSO, the proposed PSO variants generate offspring solutions through a sampling mechanism during the initial search process. Two offspring generation sampling schemes are investigated, i.e. the employment of the personal and global best solutions obtained using the mutation mechanism, respectively, as the starting positions for the subsequent search process. Subsequently, several machine learning algorithms are used in conjunction with the proposed PSO variants to perform object classification. As evidenced by the empirical results, the proposed PSO variants outperform the original PSO algorithm, significantly, for feature optimization. © 2020 IEEE.

关键词： Object recognition

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Construction and cross-correlation analysis of the affective physiological response database

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science China(Information sciences) 2010年第9期53卷 1774-1784页

作者： WEN WanHui1.QIU YuHui2,LIU GuangYuan1.,CHENG NanPu3 & HUANG XiTing4 1.chool of Electronic and Information engineering,Southwest University,Chongqing 40071.,China 2{1. of computer and Information science,Southwest University,Chongqing 40071.,China 3School of Materials science and engineering,Southwest University,Chongqing 40071.,China 4School of Psychology,Southwest University,Chongqing 40071.,China 1. School of Electronic and Information Engineering Southwest University Chongqing 400715 China2. College of Computer and Information Science Southwest University Chongqing 400715 China3. School of Materials Science and Engineering Southwest University Chongqing 400715 China4. School of Psychology Southwest University Chongqing 400715 China

Six kinds of emotions,namely joy,surprise,disgust,grief,anger and fear,are elicited from 300 ordinary college students by means of high-rated movie *** signals of galvanic skin response(GSR),heart rate(HR),blood volume pulse(BVP),electrocardiogram(ECG),respiration(Rsp.),facial electromyography(EMG) and two channels of electroencephalography(EEG) from the frontal lobe were recorded while the subjects were watching the affective eliciting *** samples of each kind of signals are analyzed by using random matrix theory(RMT).From the distribution of the eigenvalues and eigenvectors of the correlation matrices of BVP,facial EMG and two EEGs,we find that the statistical properties of these four kinds of signals coincide with the RMT ***,the largest eigenvalue and the corresponding eigenvector component distribution of the correlation matrices of GSR,HR,ECG and *** deviated significantly from the RMT *** experiments also reveal that the correlations between two arbitrary samples of BVP,facial EMG or EEGs does not result from affective response but from random noises,whereas the amplitude variations of GSR,HR,ECG and *** the correlated affective physiological response *** to the data analysis results of RMT,1.0 features are firstly extracted from the GSR and HR signals,and then a subset of the initial features is selected by using the Backward Selection *** affective data samples each of which is a vector of the features are classified by using a Fisher classifier,and furthermore,the user-independent emotion recognition systems with good prediction performance are constructed during the model selection process.

关键词： affective computing emotion recognition affective physiological response database correlation analysis random matrix theory

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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework

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International Journal of Electrical Power & Energy Systems 2025年 169卷

作者： Mengji Yang Haiqing Zhang Xi Yu Aicha Sekhari Seklouli Abdelaziz Bouras Yacine Ouzrout Univ Lyon Univ Lyon 2 INSA Lyon Université Claude Bernard Lyon 1 DISP-UR4570 Bron France Stirling College Chengdu University Chengdu 610106 China School of Software Engineering Chengdu University of Information Technology Chengdu 610225 China Department of Computer Science Qatar University Doha Qatar

Key factors influencing photovoltaic (PV) power generation predictions encompass solar radiation, aerosols, sunshine duration, temperature, humidity, wind direction, wind speed, cloud cover, and so on. The various influencing factors exhibit nonlinear correlation correlations, causing high volatility and discreteness in PV power time series. Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. Key sequences from nonlinear correlation analysis are used in the next time series prediction model. Afterward, a novel d ual- b ranch architecture that has synthesized the S tructured G lobal C onvolution (SGC) and iTrans former branches has been proposed which is called DBSGCformer . This framework enhances the ability to capture long-term dependencies through the combined effects of efficient convolution parameter optimization and variable-oriented multivariate modeling. We perform comprehensive experiments to investigate DBSGCformer’s potential in tackling complex multivariate time series forecasting challenges. Experiments conducted on two PV power datasets and five additional real-world datasets demonstrate that DBSGCformer significantly improves the accuracy of PV power forecasting and exhibits strong generalizability.

关键词： Photovoltaic power prediction Nonlinear correlation search algorithm Structured global convolution Hybrid prediction model iTransformer

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Integrate chinese semantic knowledge into word sense disambiguation

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International Journal of Hybrid Information Technology 2015年第4期8卷 105-116页

作者： Chun-Xiang, Zhang Lu-Rong, Sun Xue-Yao, Gao Zhi-Mao, Lu Yong, Yue School of Software Harbin University of Science and Technology Harbin150080 China College of Information and Communication Engineering Harbin Engineering University Harbin150001 China School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China School of Computer Science and Technology Dalian University of Technology Dalian116024 China Department of Computer Science and Technology University of Bedfordshire Park Square LutonLU1 3JU United Kingdom

Word sense disambiguation is important for many applications in natural language processing fields including machine translation, information retrieval and automatic summarization. In this paper, left word unit and right word unit are extracted for improving the quality of word sense disambiguation (WSD) starting from the target polysemous word. Their semantic knowledge is mined from Tongyici Cilin which is a Chinese semantic lexicon. A new method of word sense disambiguation is proposed with semantic information of left word unit and right word unit. The classifier of word sense disambiguation is built based on bayesian model. SemEval-2007: Task#5 is used as training corpus and test corpus. Experimental results show that the disambiguation classifier’s precision is improved and demonstrate the effectiveness of the method. © 201. SERSC

关键词： Bayesian networks

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A note on object-oriented software architecting 3rd

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3rd Workshop on Object-Oriented Technology, ECOOP 1.98

作者： Galal, Galal Hassan Software Systems Engineering Group Department of Computer Science University College London Gower Street LondonWC1E 6BT United Kingdom

ISBN: (纸本)3540654607

There is currently an enormous interest in the concept of software architecture, largely induced by the concept of architectural patterns first introduced by the architect Christopher Alexander (Alexander, 1.79;Alexander et. al, 1.77). We feel that some of the earlier work on software and system architectures has not benefited sufficiently from a deeper understanding of the complexity of the act of architecting in its home discipline: the built environment. This has lead to a confusion between fine-grain constructional mechanisms and techniques, and the overall, coarse-grain, software architectures that should in some way reflect original problem domains. © Springer-Verlag Berlin Heidelberg 1.98.

关键词： software architecture

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HORSE: Harmonize regional and global stratigraphic records through horizon sequencing

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Palaeogeography, Palaeoclimatology, Palaeoecology 2025年 670卷

作者： Chu, Tianyi Huang, Hanhui Fan, Junxuan Deng, Yiying Xu, Tao Qian, Chao Xue, Ke Sheets, H. David Stephenson, Michael H. Shi, Yukun Hou, Xudong School of Earth Sciences and Engineering and Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing 210023 China State Key Laboratory of Critical Earth Material Cycling and Mineral Deposits Nanjing University Nanjing 210023 China Department of Earth Sciences University of Oxford South Parks Road Oxford OX1 3AN United Kingdom School of Resources and Environmental Engineering Hefei University of Technology Hefei 230009 China HIC-ZJU Sunny Innovation Institute ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311200 China National Key Laboratory for Novel Software Technology Nanjing University Nanjing 210023 China School of Artificial Intelligence Nanjing University Nanjing 210023 China Data Science Program Department of Computer and Data Science Merrimack College North Andover 01845 MA United States Stephenson Geoscience Consulting Ltd. Keyworth Nottingham NG125HU United Kingdom

A uniform, high-resolution geological timescale is essential for studying Earth's history, including the dynamics of biodiversity and environmental change. Quantitative stratigraphy combines stratigraphic data with statistical and computational approaches into a global timescale that allows them to be correlated simultaneously. For example, Constrained Optimization (CONOP), built upon Graphic Correlation, sequences geological events to generate a composite sequence by resolving inconsistencies among stratigraphic records. However, CONOP determines only the global order of events (e.g., first or last appearances of species) and cannot assign ages to local records, e.g., a locally observed fossil occurrence. Horizon Annealing (HA) addresses this by using a simulated annealing algorithm to sequence sampling “horizons” while preserving local stratigraphic details. Here, we report HORizon SEquencing (HORSE), a generalized and optimized method for HA, with an implementation including parallel computing and genetic algorithms to enable fast, automatic stratigraphic correlation on large datasets. We evaluate HORSE, HA, and CONOP on three datasets—two empirical and one simulated—and assess their performance in terms of accuracy, efficiency, and robustness. HORSE greatly outperforms HA in computational efficiency and performs comparably to CONOP in event sequencing with greater robustness. Beyond constructing high-resolution geological timescales or life histories in deep time, HORSE uniquely preserves local stratigraphic information, enabling applications in palaeogeographical or palaeoecological studies, as well as evaluations of preservation and sampling biases—capabilities not possible with CONOP. © 2025 Elsevier B.V.

关键词： Constrained Optimization Geological timescale Horizon Annealing Parallelization Quantitative stratigraphy

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Flexible Capacitive Pressure Sensors and Their Applications in Human-Machine Interactions 2

Flexible Capacitive Pressure Sensors and Their Applications ...

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2nd International Symposium on Sensor Technology and Control, ISSTC 2023

作者： Fang, Chenyu Fu, Tianli Shi, Yao Changzhou No.1 High School Changzhou China Wuhan University of Technology School of Mechanical and Electronic Engineering Wuhan China Southwest University College of Computer and Information Science College of Software Chongqing China

ISBN: (纸本)9798350314465

Flexible capacitive pressure sensors have shown excellent application potential in human-machine interactions, wearable electronic devices, biological and medical, and electronic skin. Compared with piezoresistive and piezoelectric pressure sensors, capacitive pressure sensors with advantages such as high flexibility, high stability, low consumption, and simple construction. Because of these advantages, flexible capacitive pressure sensors have become the key research direction of pressure sensors in recent years. This paper introduces the working principle of flexible capacitive pressure sensors and discusses numerous research on improving the performance of flexible capacitive pressure sensors. Then two methods of improving the dielectric layer structures to improve the sensitivity of the sensor and some related works are reviewed. Finally, the flexible capacitive pressure sensors' huge potential for advances in human-machine interactions areas such as health care and motion monitoring is also discussed. The paper concludes with an overview of future research directions of improving the performance of flexible capacitive pressure sensors. © 2023 IEEE.

关键词： Pressure sensors

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SolarCAST: Using widely accessible environmental variables to forecast solar power 46

SolarCAST: Using widely accessible environmental variables t...

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46th Annual Southeast Regional Conference on XX, ACM-SE 46

作者： Hatfield, Chris Umphress, David Asbury College 1 Macklem Drive Wilmore KY 40390 United States Department of Computer Science and Software Engineering Auburn University Auburn AL 36849-5347 United States

ISBN: (纸本)9781605581057

The study in renewable energy is one of great discussion, since we, as energy users, are being faced with the dilemma of running out of non-renewable energy sources. A popular alternative to non-renewable energy, especially for residential areas, is solar energy. This paper demonstrates that it is possible to derive a function using linear regression and least squares approximation techniques with information from an online weather source, such as ***, which can predict, with little error, the voltage and photovoltaic (PV) energy that can be expected for the day. We provide empirical results using a solar system. Copyright 2008 ACM.

关键词： Solar energy

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Time-Division Online Speculative Inference for Cost-Effective Intelligent Internet of Things 10

Time-Division Online Speculative Inference for Cost-Effectiv...

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1.th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Du, Yao Wang, Zehua Leung, Cyril Leung, Victor C.M. The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

ISBN: (纸本)9798350373011

Intelligent Internet of Things (IIoT), a network paradigm, is an interconnection of intelligent edge devices, empowered by machine learning models. The recent emergence of large language models (LLMs) opens a new path towards IIoT. Although device models are generally lightweight and suitable for edge devices with limited processing power, their performance is less impressive compared to LLMs running on large servers. Server models offer superior performance with the cost of significant computational resources for model inference. To realize cost-effective IIoT, we introduce a novel collaborative inference framework: the online speculative inference enabled by device collaboration and time divisions. We aim to find the minimum number of servers required for the immediate processing of arrived inference requests. To solve the problem, we propose an evolving directed acyclic graph along with a Proof-of-Deletion mechanism for cost reduction and privacy protection. Based on computer simulations using heterogeneous LLMs, it is found that time-division online speculative inference is a promising approach towards cost-effective IIoT. © 2024 IEEE.

关键词： Adversarial machine learning

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Restoration method of characters on Jiagu rubbings based on Poisson distribution and fractal geometry

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science China(Information sciences) 2010年第7期53卷 1296-1304页

作者： GU ShaoTong1.2,3, FENG GeFei1.2,3, MA XiaoHu1.2,4 & YANG YiMing1.2,3 1.nstitute of Linguistics, Xuzhou Normal University, Xuzhou 221.09, China 2Jiangsu college Key Lab of Linguistic {1.s and Neuro-cognition engineering, Xuzhou Normal University, Xuzhou 221.09, China 3Linguistic {1. college, Xuzhou Normal University, Xuzhou 221.09, China 4School of computer {1. and Technology, Soochow University, Suzhou 21.006, China 1. Institute of Linguistics Xuzhou Normal University Xuzhou 221009 China2. Jiangsu College Key Lab of Linguistic Sciences and Neuro-cognition Engineering Xuzhou Normal University Xuzhou 221009 China3. Linguistic Science College Xuzhou Normal University Xuzhou 221009 China4. School of Computer Science and Technology Soochow University Suzhou 215006 China

A scheme for character restoration of Jiagu rubbings based on Poisson distribution and fractal geometry is proposed in this paper. The distribution characteristics of the connected regions on Jiagu rubbings is analyzed, and all the connected regions are recognized according to differences between these and their mathematical expectations. Regions are recognized as noise regions and filled if the differences are negative, while stroke regions are reserved. The attributes of the character image edges on Jiagu rubbings are also analyzed. The fractal dimensions of the character edge of Jiagu rubbings are calculated by means of statistics. The feature points are obtained using the cosine of the angle between the two vectors of the point and the consecutive two points. Different compression transformations with weighted coordinates are performed on different strokes and segments of the characters so as to smoothen the character edge of Jiagu rubbings images. Experimental results show that our scheme could successfully clear noise regions and polish the character edge of Jiagu rubbings.

关键词： Jiagu rubbings Poisson distribution fractal geometry fractal dimension compression transformation character restoration

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