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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Liu, Zhizhong Huang, Guangyu Chu, Dianhui Sun, Yuhang Yantai University School of Computer and Control Engineering Yantai China Harbin Institute of Technology School of Computer Science and Technology Weihai China

ISBN: (纸本)9798350304855

In the past three years, global COVID-19 pandemic not only impacted people's physical health but also significantly affected their mental health, which resulting in rapid increase of psychological problems. Emotions are a common manifestation of psychological changes, and some services (such as music, video, or psychological counseling services) can help users to adjust their emotions in a timely manner, thus to avoid bringing extreme events (e.g., running away from home or committing suicide). Therefore, how to perceive users' real-time emotions and then recommend the most appropriate services to users has become a challenge. To address this issue, this work proposes an approach for proactive services recommendation driven-by multimodal emotion recognition (named as PSRMER). Specifically, PSRMER first actively identifies a user's emotion with a multimodal emotion recognition model based on BiGRU and Transformer;Then, considering the user's emotion and preferences, PSRMER selects the optimal services based on an index-graph linking different emotions and various services;Finally, PSRMER proactively recommends the selected optimal service to the user. Extensive experiments have been conducted and the effectiveness of our proposed method have been proved. Moreover, the proposed method can also be used in smart education, smart transportation, smart elderly care and other modern industry fields. © 2023 IEEE.

关键词： COVID-19

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A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

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Journal of Bionic Engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

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Design of the optimal motions of autonomous vehicles in intersections through neural networks

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IFAC-PapersOnLine 2018年第9期51卷 19-24页

作者： Németh, Balázs Gáspár, Péter Szcs, Dávid Mihály, András Systems and Control Laboratory Institute for Computer Science and Control Hungarian Academy of Sciences Budapest Hungary Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Budapest Hungary Hungarian Government European Social Fund Hungary

The handling of vehicle interactions is a challenge in the research into the traveling of autonomous vehicles. This paper focuses on collision-free motion design of autonomous vehicles to guarantee their minimum traveling time in intersections. First, a decision logic of the order of the vehicles in intersections is proposed. Based on the decision logic a constrained nonlinear optimization method is also proposed, with which the minimum traveling time of the vehicles without their collision is guaranteed. Since the on-line solution of the nonlinear optimization task can be numerically complex, a neural network based approximation of the optimal solution is developed. The efficiency of the method with various intersection scenarios is shown in the CarSim simulation environment. © 2018

关键词： Vehicles computer circuits Constrained optimization Intersections Neural networks Nonlinear programming Autonomous Vehicles Collision free Constrained non linear optimizations Non linear optimization Optimal motion Optimal solutions Simulation environment Vehicle interactions

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Estimating motor symptom presence and severity in Parkinson's disease from wrist accelerometer time series using ROCKET and InceptionTime

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Scientific reports 2025年第1期15卷 19140页

作者： Cedric Donié Neha Das Satoshi Endo Sandra Hirche TUM School of Computation Information and Technology Department of Computer Engineering Chair of Information-oriented Control Technical University of Munich Munich Germany. cedric.donie@tum.de. TUM School of Computation Information and Technology Department of Computer Engineering Chair of Information-oriented Control Technical University of Munich Munich Germany. Munich Institute of Robotics and Machine Intelligence (MIRMI) Munich Germany. Munich Data Science Institute (MDSI) Munich Germany.

Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classification and deep learning techniques have demonstrated limited efficacy in monitoring PD symptoms using wearable accelerometer data due to complex PD movement patterns and the small size of available datasets. We investigate InceptionTime and RandOm Convolutional KErnel Transform (ROCKET) as they are promising for PD symptom monitoring. InceptionTime's high learning capacity is well-suited to modeling complex movement patterns, while ROCKET is suited to small datasets. With random search methodology, we identify the highest-scoring InceptionTime architecture and compare its performance to ROCKET with a ridge classifier and a multi-layer perceptron on wrist motion data from PD patients. Our findings indicate that all approaches can learn to estimate tremor severity and bradykinesia presence with moderate performance but encounter challenges in detecting dyskinesia. Among the presented approaches, ROCKET demonstrates higher scores in identifying dyskinesia, whereas InceptionTime exhibits slightly better performance in tremor and bradykinesia estimation. Notably, both methods outperform the multi-layer perceptron. In conclusion, InceptionTime can classify complex wrist motion time series and holds potential for continuous symptom monitoring in PD with further development.

关键词： Accelerometer Deep learning IMU InceptionTime Machine learning Parkinson’s disease ROCKET Time series classification

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Predicting CircRNA-Disease Associations Based on Improved Weighted Biased Meta-Structure

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Journal of computer Science & technology 2021年第2期36卷 288-298页

作者： Xiu-Juan Lei Chen Bian Yi Pan School of Computer Science Shaanxi Normal UniversityXi'an 710119China School of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Computer Science Georgia State UniversityAtlantaGA 30302U.S.A

Circular RNAs(circRNAs)are RNAs with a special closed loop structure,which play important roles in tumors and other *** to the time consumption of biological experiments,computational methods for predicting associations between circRNAs and diseases become a better *** the limited number of verified circRNA-disease associations into account,we propose a method named CDWBMS,which integrates a small number of verified circRNA-disease associations with a plenty of circRNA information to discover the novel circRNA-disease *** adopts an improved weighted biased meta-structure search algorithm on a heterogeneous network to predict associations between circRNAs and *** terms of leave-one-out-cross-validation(LOOCV),10-fold cross-validation and 5-fold cross-validation,CDWBMS yields the area under the receiver operating characteristic curve(AUC)values of 0.9216,0.9172 and 0.9005,***,case studies show that CDWBMS can predict unknow circRNA-disease *** conclusion,CDWBMS is an effective method for exploring disease-related circRNAs.

关键词： circular RNA(circRNA) circRNA-disease association meta-structure heterogeneous network

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Dual Variational Generation Framework for Enhanced Cross-Modal Face Recognition 15

Dual Variational Generation Framework for Enhanced Cross-Mod...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Evany Anne, M. Brindha, M. Sivakumaran, N. National Institute of Technology Computer Science and Engineering Tiruchirappalli India National Institute of Technology Instrumentation and Control Engineering Tiruchirappalli India

ISBN: (纸本)9798350370249

One of the major challenges in face recognition is accurately identifying faces under varying lighting conditions, leading to a problem known as Heterogeneous Face Recognition (HFR). The objective is to integrate the capabilities of the modified Dual Variational Generator (DVG-Face) framework with traditional recognition methods, such as Local Binary Pattern Histogram (LBPH) and the HaarCascade framework, to provide a robust solution to the challenges of heterogeneous face recognition. This involves developing and implementing a model that successfully handles the complexity of HFR tasks utilizing synthetic images generated from Near-Infrared (NIR) and Visible (VIS) modalities. To guarantee identity consistency in the produced paired heterogeneous images, pairwise identity preserving loss is also used. The integration of Haar Cascades, the LBPH algorithm, and the DVG approach, along with person reidentification using the SSRL model, establishes a reliable framework for facial recognition in real-world security applications. © 2024 IEEE.

关键词： Face recognition

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Subword pooling makes a difference 16

Subword pooling makes a difference

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16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021

作者： Ács, Judit Kádár, Ákos Kornai, András Budapest University of Technology and Economics Hungary Borealis AI Institute for Computer Science and Control

ISBN: (纸本)9781954085022

Contextual word-representations became a standard in modern natural language processing systems. These models use subword tokenization to handle large vocabularies and unknown words. Word-level usage of such systems requires a way of pooling multiple subwords that correspond to a single word. In this paper we investigate how the choice of subword pooling affects the downstream performance on three tasks: morphological probing, POS tagging and NER, in 9 typologically diverse languages. We compare these in two massively multilingual models, mBERT and XLM-RoBERTa. For morphological tasks, the widely used 'choose the first subword' is the worst strategy and the best results are obtained by using attention over the subwords. For POS tagging both of these strategies perform poorly and the best choice is to use a small LSTM over the subwords. The same strategy works best for NER and we show that mBERT is better than XLM-RoBERTa in all 9 languages. We publicly release all code, data and the full result tables at https://***/juditacs/subword-choice. © 2021 Association for Computational Linguistics

关键词： Natural language processing systems

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High Precision Soft-Switching Converter with Low Voltage Stress and Fast Response Characteristic Based on SiC Power Devices

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IEEE Transactions on Power Electronics 2025年

作者： Wei, Jian Qiu, Guangjuan Kou, Baoquan Yang, Xiaobao Zhao, Xiaokun Wang, Weinan Zhang, Jiawei Northeast Forestry University college of computer and control engineering Harbin150040 China Harbin Institute of Technology School of Electrical Engineering and Automation Harbin150001 China School of Sichuan University Sichuan 610065 China

Due to the characteristic of no blanking time, dual buck topology is attractive in high precision applications and the bias current is injected to eliminate zero crossing distortion. However, with the extending of bus voltage, it is difficult to ensure the current response speed and accuracy due to the limitation of bias current operation and the impact of parasitic parameters of switching devices. Thus, this paper proposes a low voltage stress resonant dual buck soft-switching topology combined with SiC power device for achieving fast response and high precision. At first, the principle of the bias current and soft-switching topology is introduced. Then combined with the bias current decoupling and the realization of zero current switching (ZCS) and zero voltage switching (ZVS), the control strategy is analyzed. Moreover, based on the resonant circuit considering parasitic parameters, the factors that affect the voltage and current stress are presented. Finally, a prototype of 500 V bus voltage with 100 kHz switching frequency is built to verify the theory analysis © 1986-2012 IEEE.

关键词： Silicon carbide

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computer vision based object grasping 6DoF robotic arm using picamera 4

Computer vision based object grasping 6DoF robotic arm using...

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4th International Conference on control, Automation and Robotics, ICCAR 2018

作者： Kumar, Vishal Wang, Qiang Minghua, Wang Rizwan, Syed Shaikh, S.M. Liu, Xuan Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9781538663387

This article presents a project to design a robust robotic arm which can perform multifunctional tasks. The controller of the manipulator is based on Arduino mega 2560 Microcontroller. The aim of the project is to focus all axes of manipulator to lift, carry and unload the objects at a desired location. This requires a precise drive motion control that incorporate electric motors as a drive system. Further experiments are done to implement a camera based 3D vision system integrated with a computer vision algorithm to recognize object deformation and spatial coordination to control the deviation from the original training. The 3D visualization systems are able to detect the objects as well as their distance from the End-effecter and transmit the signals to the drive system. The vision system requires a separate computing hardware capable of processing complex vision algorithms. We utilize Raspberry pi microcontroller for processing the vision data, separately making the vision system capable of recognizing the specified object as per program commands. © 2018 IEEE.

关键词： Robotic arms

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Construction of the electromagnetic mill with the grinding system, classification of crushed minerals and the control system

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IFAC-PapersOnLine 2016年第20期49卷 67-71页

作者： Wolosiewicz-Glb, Marta Ogonowski, Szymon Foszcz, Dariusz AGH University of Science and Technology in Cracow Faculty of Mining and Geoengineering Department of Environmental Engineering and Mineral Processing United States Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Institute of Automatic Control Poland

The article presents the construction of an innovative electromagnetic mill, which in comparison to traditional solutions provide a significant reduction of energy consumption and higher technological performance. The device is equipped with a control system, measuring grinding quality or analyzing the operating status of the mill. Direct control of the grinding process is implemented in industrial controllers (PLC) and is supported by the optimization algorithms that run in the supervisory control system (SCADA). © 2016

关键词： Quality control

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