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Congress on Evolutionary Computation

作者： Jiajia Zhang Chaoli Sun Guochen Zhang Jing Li Hui Shi Zongchao Xie School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan China School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan China Faculty of Science University of Melbourne Melbourne Australia

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Several meta-heuristic algorithms have gained attention for addressing large-scale optimization problems (LSOPs). However, their effectiveness is limited when dealing with LSOPs that involve expensive objective functions because the significant number of objective evaluations required before identifying the optimal solution. In this paper, two sets of subproblems are op-timized, assisted by surrogate models, to collaboratively explore the optimal solution space for large-scale expensive optimization problems (LSEOPs). A variant of particle swarm optimization (PSO), engineered to accelerate convergence, is proposed to search for the optimal solution for each subproblem. Moreover, a novel infill criterion is introduced, where the solution with the maximum expected improvement in the first set of subproblems and the solution with the minimum objective value discovered so far in the second set of subproblems are selected. Then, their mean position will be evaluated using the real objective function. Experimental findings on 15 CEC2013 benchmark problems show that our proposed approach outperforms four state-of-the-art algorithms in solving expensive large-scale optimization problems with up to 1000 decision variables.

关键词： Sociology Metaheuristics Focusing Linear programming Search problems Resource management Object recognition

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Transformer-based Single-Cell Language Model: A Survey

arXiv

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arXiv 2024年

作者： Lan, Wei He, Guohang Liu, Mingyang Chen, Qingfeng Cao, Junyue Peng, Wei The Guangxi Key Laboratory of Multimedia Communications and Network Technology School of Computer Electronic and Information Guangxi University Nanning China The School of Computer and Electronic Information Guangxi University Nanning China The School of Computer Electronic and Information Guangxi University Nanning China The College of Life Science and Technology Guangxi University Nanning China The Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention mechanism. In addition, increasing studies based on transformers have been proposed to model single-cell data. In this review, we attempt to systematically summarize the single-cell language models and applications based on transformers. First, we provide a detailed introduction about the structure and principles of transformers. Then, we review the single-cell language models and large language models for single-cell data analysis. Moreover, we explore the datasets and applications of single-cell language models in downstream tasks such as batch correction, cell clustering, cell type annotation, gene regulatory network inference and perturbation response. Further, we discuss the challenges of single-cell language models and provide promising research directions. We hope this review will serve as an up-to-date reference for researchers interested in the direction of single-cell language models. Copyright © 2024, The Authors. All rights reserved.

关键词： Cytology

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Mako:A Graph-based Pattern Growth Approach to Detect Complex Structural Variants

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Genomics, Proteomics & Bioinformatics 2022年第1期20卷 205-218页

作者： Jiadong Lin Xiaofei Yang Walter Kosters Tun Xu Yanyan Jia Songbo Wang Qihui Zhu Mallory Ryan Li Guo Chengsheng Zhang The Human Genome Structural Variation Consortium Charles Lee Scott E.Devine Evan E.Eichler Kai Ye School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China Leiden Institute of Advanced Computer Science Faculty of ScienceLeiden UniversityLeiden 2311EZNetherland School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China The Jackson Laboratory for Genomic Medicine FarmingtonCT 06032USA Precision Medicine Center the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China Institute for Genome Sciences University of Maryland School of MedicineBaltimoreMD 21201USA Department of Genome Sciences University of Washington School of MedicineSeattleWA 98119USA Howard Hughes Medical Institute University of WashingtonSeattleWA 98195USA The School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China 不详

Complex structural variants(CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural ***,detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match *** a result,there has been limited progress for CSV discovery compared with simple structural ***,we systematically analyzed the multi-breakpoint connection feature of CSVs,and proposed Mako,utilizing a bottom-up guided model-free strategy,to detect CSVs from paired-end short-read ***,we implemented a graph-based pattern growth approach,where the graph depicts potential breakpoint connections,and pattern growth enables CSV detection without pre-defined *** evaluations on both simulated and real datasets revealed that Mako outperformed other ***,validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%,where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp,***,the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types,including two novel types of adjacent segment swap and tandem dispersed *** analysis of these CSVs also revealed the impact of sequence homology on the formation of *** is publicly available at https://***/xjtu-omics/Mako.

关键词： Next-generation sequencing Complex structural variant Pattern growth Graph mining Formation mechanism

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Privacy-Preserved Incentive Mechanism for Split Learning in Edge Computing System

Privacy-Preserved Incentive Mechanism for Split Learning in ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Lu Yu Zheng Chang Timo Hämäläinen Geyong Min School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Department of Computer Science University of Exeter Exeter U.K.

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In the edge computing system, split learning (SL) is an emerging distributed learning approach that allows mobile users (MUs) and edge nodes (ENs) to train the model together without sharing the raw data of the MU. Although MU can preserve its privacy in SL, attacks on the intermediate data at the cut layer for model training can still lead to privacy leakage, which prevents privacy-sensitive MUs from participating in training. Therefore, it is important to implement an effective incentive mechanism to motivate MUs to join SL while preserving their privacy. In this work, from the perspective of maximizing the utility of edge service provider (ESP) while considering the privacy-sensitivity of different MUs, the incentive problem of ESP and MUs is transformed into the utility optimization problem, and an incentive mechanism based on the differential privacy (DP) and contract theory is established to model the interactions between the MUs and EN. The obtained convex optimization problem is obtained through the mathematical derivations, and the optimal contract is presented by solving this problem. The simulation results demonstrate the effectiveness of our proposed privacy preserved incentive mechanism.

关键词： Training Privacy Computational modeling Simulation Distributed databases Data models Convex functions Contracts Optimization Edge computing

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Convolutional Neural Networks with Feature Fusion Method for Automatic Modulation Classification 9

Convolutional Neural Networks with Feature Fusion Method for...

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9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Elshebani, Mohamed Salem Ali, Yahya Azroug, Nser Khalifa, Ramdan A. M. Khalifa, Othman O. Saeed, Rashid A. Faculty of Electronic Technology Department of Comm Eng Beni-Walid Libya University of Tripoli Department of Comm Eng Tripoli Libya Tripoli College for Sciences and Technology Department of Comm Eng Tripoli Libya High Institute of Science and Technology-Suk Algumaa Department of Comm Eng Tripoli Libya International Islamic University Malaysia Department of Electrical and Computer Engineering Malaysia Libyan Center for Engineering Research and Information Technology Bani Waleed Libya Taif University College of Computers and Information Technology Department of Computer Engineering P.O. Box 11099 Taif21944 Saudi Arabia

ISBN: (纸本)9798350325218

The analogy and application of Automatic modulation classification (AMC) detects the modulation type of received signals. Henceforth, the received signals can be correctly demodulated and, consequently, the transmitted message can be recovered. In Deep Learning (DL) based modulation classification, one major category, challenge is to pre-processing a received signal and representing it in a proper format-manner, before passing the desired-signal into the neural network. However, most existing modulation classification algorithms are neglecting the fact of mixing features between different representations, and the importance of features fusion method. This paper, however, attempted a Feature fusion scheme, for AMC, using convolutional neural networks (CNN). The approach was taken, in order to attempt fuse features extracted from In-phase & Quadrature (IQ) sequences, as well as, the Amplitude & Phase (AP) Sequences and Constellation Diagram images. Finally, simulation results show that fusing features from different representations can incorporate and leads to the best accuracy figures, achieved from each representation separately. Furthermore, our model achieved a classification accuracy of 84.68% at 0dB and 75.29% at -2dB and over 90% accuracy for high SNRs with a maximum accuracy of 94.65%, were available. © 2023 IEEE.

关键词： Cognitive radio

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American Sign Language Recognition Based on Machine Learning and Neural Network 2

American Sign Language Recognition Based on Machine Learning...

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2nd International Conference on Machine Learning and Intelligent Systems engineering, MLISE 2022

作者： Li, Lanxi Liu, Da Shen, Chenlin Sun, Jing The Ohio State University Computer Science And Engineering Columbus43201 United States Sichuan University Department Of Computer Science Chengdu610207 China Jilin University Faculty Of Software Engineering Changchun130012 China Institute Of Information And Software Engineering University Of Electronic Science And Technology Of China Chengdu610066 China

ISBN: (数字)9781665492461

ISBN: (纸本)9781665492461

Numerous disabilities such as deaf and mute are suffered from not being capable of communicating with normal people, it is necessary to find a way to solve this problem. A feasible method is Sign Language Recognition (SLR) which is a sort of pattern recognition technique. In this paper, machine learning and deep learning methods are applied to recognize and classify American Sign Language (ASL), and only 24 English letters are classified because letter J and Z require fingers to move. First, Principal Component Analysis (PCA) and manifold algorithms are used to do dimension reduction to accelerate the training of machine learning and visualize it. Second, various machine learning methods such as Random Forest Classification (RFC), K-Nearest Neighbor (KNN), Gaussian Naïve Bayes (GNB), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD) are applied to classify the pattern. Since the SVM algorithm has several hyperparameters, this study uses the Grid Search method to find the best combination of hyperparameter which lead to predicting more accurately. It is found that different dimensionality reduction algorithms have unequal effects on the accuracy of each prediction model, and it can be concluded that the manifold algorithm is the best dimension reduction algorithm only for KNN but not for other prediction models, and PCA is much more feasible than KNN applied in such machine learning algorithms except KNN. Two deep learning algorithms such as Convolutional Neural Networks (CNN) and Deep Neural Networks (DNN) are also used in classification and their accuracy is highest among such algorithms mentioned above. © 2022 IEEE.

关键词： Principal component analysis

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Investigation on Sensorless PI-IFOC Speed Control Based Flux and Speed Estimator for High Power Induction Motor

Investigation on Sensorless PI-IFOC Speed Control Based Flux...

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IEEE Industrial electronics and Applications Conference (IEACon)

作者： Muhamad Syazmie Sepeeh Shamsul Aizam Zulkifli Sim Sy Yi Huang-Jen Chiu Department of Electrical Power Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Johor Malaysia Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipe Taiwan

This paper is to investigate the Proportional Integral (PI) controller that can be used with Indirect Filed Oriented Control (IFOC) mechanism. The PI controller used the parameters generated from the flux and speed estimator based on dq and park transformation of voltage and current inverter output. This estimator represents the sensorless technique that can be applied to the high-power AC motor rated at 20 Hp. The results are in good agreement where the estimator has less than 5% error between the speed estimator and reference speed controller which give faster response based on speed and flux controller with a superior performance on the IM speed.

关键词：

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Autonomous Power and Dynamic Load Management in Grid-Connected Microgrid with Supercapacitor and EV Integration

Autonomous Power and Dynamic Load Management in Grid-Connect...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Md. Badoruzzaman Jahidul Islam Shuvo Shaikh Tawhidul Islam Anik Md Salman Khan Mithil HM Farhan Unjum A.S. Nazmul Huda Shameem Ahmad Department of Electrical and Electronic Engineering Faculty of Engineering American International University–Bangladesh Dhaka Bangladesh Department of Electrical Engineering and Computer Science Electrical Engineering (MS) South Dakota School of Mines & Technology Rapid City United States Department of Electrical and Electronic Engineering BSRM School of Engineering BRAC University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The rising adoption of renewable energy sources (RESs) and electric vehicles (EVs) has made microgrids (MGs) essential for modern energy management. Integration with EV chargers with dynamic loads poses challenges such as fluctuating power supply, unstable grid operations, and limited load control, which conventional battery storage systems (BSSs) struggle to address effectively. An enhanced dynamic energy management strategy (DEMS) for photovoltaic (PV) integrated MG with supercapacitor (SC) storage, grid connectivity, and optimized power distribution for AC and EV charging demand is presented in this study. The SC storage provides instantaneous power stabilization, surpassing conventional systems in managing fluctuations and transient conditions. The proposed system utilizes a DEMS algorithm to optimize the balance among energy generation, storage, and consumption, which ensures reliable and efficient operation. The system’s performance was validated in MATLAB/Simulink under various scenarios. Results show that the PV system operates with 99.7% efficiency, fully meeting the load demand and charging the SC with the excess power. During PV insufficiency, the SC contributes 30.83% of the load, while the PV system provides 69.17%. When both PV and SC support are limited, the grid supplies 60% of the load demand, with the PV system covering the remaining 40%. The system enhances resilience by effectively managing dynamic loads, thereby promoting the shift to sustainable, adaptable, and robust energy solutions.

关键词： Renewable energy sources Fluctuations Microgrids Supercapacitors Load management Electric vehicle charging Stability analysis Vehicle dynamics Transient analysis MATLAB

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An integrated microfluidic platform for nucleic acid testing

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Microsystems & Nanoengineering 2024年第3期10卷 181-194页

作者： Antao Sun Petra Vopařilová Xiaocheng Liu Bingqian Kou TomášŘezníček TomášLednický Sheng Ni JiříKudr Ondřej Zítka Zdenka Fohlerová Petr Pajer Haoqing Zhang Pavel Neužil Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical EngineeringNorthwestern Polytechnical University127 West Youyi RoadXi’anShaanxi 710072P.R.China Department of Chemistry and Biochemistry Mendel University in BrnoZemědělská161300 BrnoCzech Republic ITD Tech s.r.o Osvoboditelů100573581 BohumínCzech Republic Central European Institute of Technology Brno University of TechnologyPurkyňova 123Brno 61200Czech Republic Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong Kong SARChina Department of Microelectronics Faculty of Electrical Engineering and CommunicationBrno University of TechnologyTechnická3058/10Brno 61600Czech Republic Military Health Institute U Vojenskénemocnice 120016200 Praha 6Czech Republic The Key Laboratory of Biomedical Information Engineering of Ministry of Education School of Life Science and TechnologyXi’an Jiaotong UniversityXi’anShaanxi 710049P.R.China Bioinspired Engineering and Biomechanics Center(BEBC) Xi’an Jiaotong UniversityXi’an 710049P.R.China

This study presents a rapid and versatile low-cost sample-to-answer system for SARS-CoV-2 *** system integrates the extraction and purification of nucleic acids,followed by amplification via either reverse transcriptionquantitative polymerase chain reaction(RT–qPCR)or reverse transcription loop-mediated isothermal amplification(RT–LAMP).By meeting diverse diagnostic and reagent needs,the platform yields testing results that closely align with those of commercial RT-LAMP and RT‒qPCR *** advantages of our system include its speed and *** assay is completed within 28 min,including sample loading(5 min),ribonucleic acid(RNA)extraction(3 min),and RT-LAMP(20 min).The cost of each assay is≈$9.5,and this pricing is competitive against that of Food and Drug Administration(FDA)-approved commercial *** some RNA loss during on-chip extraction is observed,the platform maintains a potential limit of detection lower than 297 *** makes the system particularly useful in environments where centralized laboratories are either unavailable or inconveniently *** key feature is the platform’s versatility,allowing users to choose between RT‒qPCR or RT‒LAMP tests based on specific requirements.

关键词： testing maintain versatile

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A QoS provisioning architecture of fiber wireless network based on XGPON and IEEE 802.11ac

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Journal of Optical Communications 2023年第s1期44卷 S1017-S1022页

作者： Mohammadani, Khalid H. Butt, Rizwan A. Memon, Kamran A. Pirzado, Azhar A. Faheem, Muhammad Abro, Adeel Ali, Babar Ain, Noor-Ul Beijing China Department of Electronic Engineering NED University of Engineering Karachi Pakistan Faculty of Engineering and Technology University of Sindh Jamshoro Pakistan Department of Computer Engineering Abdullah Gul University Kayseri Turkey Beijing China

The integration of the XGPON network with the 5G WLAN network is a suitable solution for next-generation high-speed access Internet service. We demonstrated the integration of two different standards via the QoS concept. Further, this work also presents a proper mapping scheme of QoS traffic between XG-PON and fifth-generation Wi-Fi standards known as IEEE 802.11ac. The analysis assessment compares the behavior of different IEEE 802.11ac standards with XGPON with-respect-to multimedia traffic in the FiWi network. To assess the performance of the FiWi network, the OMNET++ and INET framework are used to carrying out a comparative analysis in terms of upstream (US) delay and fairness index. The study concludes that the EDCA Wi-Fi module has better performance than the DCF Wi-Fi module with the integrated XGPON system for the FiWi access network. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Quality of service

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