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Multi-channel Parallel Computing in Capsule Network and Its Application in Mechanical Fault Diagnosis 1

TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Qiu, Haiwen Tao, Jie Xiao, Zhao Yang, Wenxian School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China School of Mechanical Engineering Hunan University of Science and Technology Xiangtan411201 China School of Computing and Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom

ISBN: (数字)9783031694837

ISBN: (纸本)9783031694820

Due to complex noise environments, it is difficult to extract bearing fault features from vibration signal and it affects the accuracy of fault diagnosis. To solve the problem, this paper proposes a multi-channel parallel computing capsule network (MPCN), which simultaneously uses various scales kernels to extract the features from original signals. In MPCN, the vibration signal is directly input into the model, then various specifications kernels explore multiple aspects characteristic of signals. Finally, MPCN takes advantage of vector neurons to fuse multiple aspects characteristic. In order to verify the effectiveness of MPCN, fault diagnosis experiments were conducted under different noise conditions. The experimental results show that the accuracy of MPCN exceeds 95%, which is significantly better than traditional diagnostic methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Parallel processing systems

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Intelligent IoT Based Temperature and Humidity Monitoring System for Tobacco Curing Barn 5

Intelligent IoT Based Temperature and Humidity Monitoring Sy...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Chundawat, Dipendra Pal Singh Mary, Gerardine Immaculate Julian, Anitha School of Electronics Engineering Vellore Institute of Technology Vellore632014 India Saveetha Engineering College Computer Science and Engineering Chennai602105 India

ISBN: (纸本)9798331518097

A Cloud-based real-time temperature and humidity monitoring device that monitors the tobacco curing process, automates the alarm, notifies in case of any deviation from prescribed levels of temperature and humidity, transmits temperature and humidity data to the cloud, and compares the data against the specified ranges. This system predicts the future values of temperature and humidity so one can calculate the efficiency of the system. The system tackles the issue of the Barn Monitoring System using a low-cost controller. The main idea behind the Intelligent IoT-based temperature and humidity monitoring system is to maintain the temperature and humidity inside the barn in each stage of curing. The device has a sensor for temperature and humidity. If the humidity crosses the threshold value, it can alert the barn driver and farmer via a Buzzer, SMS, or e-mail. © 2024 IEEE.

关键词： Tobacco

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DAO to HANOI via DeSci: AI Paradigm Shifts from AlphaGo to ChatGPT

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 877-897页

作者： Qinghai Miao Wenbo Zheng Yisheng Lv Min Huang Wenwen Ding Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430070China Institute of Automation Chinese Academy of SciencesBeijing 100190China Institute of System Engineering Macao University of Science and TechnologyMacaoChina

From AlphaGo to ChatGPT,the field of AI has launched a series of remarkable achievements in recent ***,comparing,and summarizing these achievements at the paradigm level is important for future AI innovation,but has not received sufficient *** this paper,we give an overview and perspective on machine learning ***,we propose a paradigm taxonomy with three levels and seven dimensions from a knowledge ***,we give an overview on three basic and twelve extended learning paradigms,such as Ensemble Learning,Transfer Learning,etc.,with figures in unified *** further analyze three advanced paradigms,i.e.,AlphaGo,AlphaFold and ***,to enable more efficient and effective scientific discovery,we propose to build a new ecosystem that drives AI paradigm shifts through the decentralized science(DeSci)movement based on decentralized autonomous organization(DAO).To this end,we design the Hanoi framework,which integrates human factors,parallel intelligence based on a combination of artificial systems and the natural world,and the DAO to inspire AI innovations.

关键词： ChatGPT decentralized science(DeSci) decentralized autonomous organization(DAO) machine learning paradigm shift

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Movable Superdirective Pairs: A Phase Shifter-Free Approach to mmWave Communications

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IEEE Wireless Communications Letters 2025年第6期14卷 1806-1810页

作者： Han, Liangcheng Yin, Haifan Gao, Mengying Zhang, Rui Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China The Chinese University of Hong Kong School of Science and Engineering Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

In this letter, we propose a novel Movable Superdirective Pairs (MSP) approach that combines movable antennas with superdirective pair arrays to enhance millimeter-wave (mmWave) communications. By controlling the rotation angles and positions of superdirective antenna pairs via low-power actuators on the user side, the proposed MSP approach maximizes the received signal-to-noise ratio (SNR) of multipath signals without the need for phase shifters, thereby reducing hardware costs and insertion losses. An efficient algorithm based on alternating optimization and gradient projection is developed to solve the non-convex rotation–position design problem. Moreover, MSP is shown to be robust in both line-of-sight (LOS) and non-line-ofsight (NLOS) channels. Simulation results demonstrate that MSP achieves significant performance gains over fixed-position arrays, while maintaining low system complexity. © 2012 IEEE.

关键词： Microwave antennas

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Fusion of Sparse Direct Method and Feature-based Approach in Stereo Point-Line SLAM Algorithm

Fusion of Sparse Direct Method and Feature-based Approach in...

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2024 International Conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Wang, Hao Xu, Zhen Leng, Kuang China Nanhu Academy of Electronics and Information Technology Zhejiang Jiaxing China School of Electronic Engineering and Computer Science University of Science and Technology of China Anhui Hefei China School of Management University of Science and Technology of China Anhui Hefei China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

The development of autonomous driving and augmented reality has led to increased demands for accuracy and speed in visual SLAM. Traditional feature-based visual SLAM performs real-time image analysis with high complexity and computation requirements, necessitating devices with exceptionally high arithmetic power. This poses challenges for deployment on low-power devices. Additionally, relying solely on photometric errors makes the system too sensitive to the environment. To tackle these issues, our algorithm integrates the feature-based method and the sparse direct method. We employ the sparse joint method for pose estimation in the tracking thread, considering both accuracy and speed. In case of tracking failure, we extract feature point lines for tracking. Furthermore,to enhance system robustness in low-texture environments and fuse point-line features, we employ adaptive weighted extraction of point-line features, considering computational resources. Our experimental results, based on public datasets, demonstrate that this algorithm achieves faster operation speeds in simple environments and higher accuracy compared to other SLAM algorithms in complex environments and fast camera movement scenes. © 2025 SPIE.

关键词： Stereo image processing

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Dynamics of synthetic yeast chromosome evolution shaped by hierarchical chromatin organization

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National science Review 2023年第5期10卷 240-250页

作者： Sijie Zhou Yi Wu Yu Zhao Zhen Zhang Limin Jiang Lin Liu Yan Zhang Jijun Tang Ying-Jin Yuan Frontiers Science Center for Synthetic Biology (Ministry of Education) Tianjin University Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemical Engineering and TechnologyTianjin University Institute for Systems Genetics NYU Langone Health School of Computer Science and Technology College of Intelligence and ComputingTianjin University Epigenetic Group Frasergen Bioinformatics Co.Ltd. Department of Computer Science University of South Carolina

Synthetic genome evolution provides a dynamic approach for systematically and straightforwardly exploring evolutionary *** Chromosome Rearrangement and Modification by LoxP-mediated Evolution(SCRaMbLE) is an evolutionary system intrinsic to the synthetic yeast genome that can rapidly drive structural ***,we detect over 260 000 rearrangement events after the SCRaMbLEing of a yeast strain harboring 5.5 synthetic yeast chromosomes(synⅡ,synⅢ,synⅤ,circular synⅥ,synⅨR and synⅩ).Remarkably,we find that the rearrangement events exhibit a specific landscape of *** further reveal that the landscape is shaped by the combined effects of chromatin accessibili and spatial contact *** rearrangements tend to occur in 3D spatially proximal and chromatin-accessible *** enormous numbers of rearrangements mediated by SCRaMbLE provide a driving force to potentiate directed genome evolution,and the investigation of the rearrangement landscape offers mechanistic insights into the dynamics of genome evolution.

关键词： synthetic biology genome rearrangement hierarchical chromatin organization synthetic yeast genome SCRaMbLE Saccharomyces cerevisiae

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Epidermal self-powered sweat sensors for glucose and lactate monitoring

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Bio-Design and Manufacturing 2022年第1期5卷 201-209页

作者： Xingcan Huang Jiyu Li Yiming Liu Tszhung Wong Jingyou Su Kuanming Yao Jingkun Zhou Ya Huang Hu Li Dengfeng Li Mengge Wu Enming Song Shijiao Han Xinge Yu Department of Biomedical Engineering City University of Hong KongHong Kong 999077China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 610054China

Sweat could be a carrier of informative biomarkers for health status identification;therefore,wearable sweat sensors have attracted significant attention for *** external power source is an important component of wearable sensors,however,the current power supplies,i.e.,batteries,limit further shrinking down the size of these devices and thus limit their application areas and ***,we report a stretchable self-powered biosensor with epidermal electronic format that enables the in situ detec-tion of lactate and glucose concentration in *** biofuel cells serve as self-powered sensing modules allowing the sweat sensor to exhibit a determination coefficient(R2)of 0.98 with a sensitivity of 2.48 mV/mM for lactate detection,and R2 of 0.96 with a sensitivity of 0.11 mV/μM for glucose *** microfluidic channels developed in an ultra-thin soft flexible polydimethylsiloxane layer not only enable the effective collection of sweat,but also provide excellent mechanical properties with stable performance output even under 30%*** presented soft sweat sensors can be integrated at nearly any location of the body for the continuous monitoring of lactate and glucose changes during normal daily activities such as *** results provide a promising approach to develop next-generation sweat sensors for real-time and in situ sweat analysis.

关键词： Sweat sensor Self-powered Epidermal electronics Enzymatic biofuel cells Microfluidics

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AKGIN: An API Knowledge Graph and Intent Network based Mashup-Oriented API Recommendation Method 26

AKGIN: An API Knowledge Graph and Intent Network based Mashu...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Yu, Changyong Hu, Rong Wang, Bangjun Hunan University of Science and Technology Computing and Novel Software Technology Hnust School of Computer Science and Engineering Xiangtan China

ISBN: (纸本)9798350331684

With the continuous development of the Web API ecosystem, mashup-oriented API recommendation gets a lot of attention. Collaborative filtering, deep learning and their combination based methods are recently proposed for API recommendation. However, the recommendation results often perform poorly when data is sparse. Therefore, we propose an API knowledge graph (AKG) and intent network based mashup-oriented API recommendation method, whose main target is to recruit the semantic representation ability to improve the precision of API recommendation. Firstly, Latent Dirichlet Allocation (LDA) is used to extract API topics, which are important entities in the AKG. Then, the mashup intention is modeled based on the mashup-API interactions. The high-order relationship paths are recursively aggregated into the representation vector of Mashup and API. Finally, the inner product of their representations present the probability of the API recommendation for the mashup. The experimental results on real-world datasets show that our proposed method outperforms several baseline methods in mashup-oriented API recommendations. © 2023 IEEE.

关键词： Knowledge graph

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Reliability and Incentive of Performance Assessment for Decentralized Clouds

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Journal of computer science & technology 2022年第5期37卷 1176-1199页

作者： Jiu-Chen Shi Xiao-Qing Cai Wen-Li Zheng Quan Chen De-Ze Zeng Tatsuhiro Tsuchiya Min-Yi Guo Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Computer Science China University of GeosciencesWuhan 430074China Graduate School of Information Science and Technology Osaka UniversityOsaka 565-0871Japan

Decentralized cloud platforms have emerged as a promising paradigm to exploit the idle computing resources across the Internet to catch up with the ever-increasing cloud computing *** any user or enterprise can be the cloud provider in the decentralized cloud,the performance assessment of the heterogeneous computing resources is of vital ***,with the consideration of the untrustworthiness of the participants and the lack of unified performance assessment metric,the performance monitoring reliability and the incentive for cloud providers to offer real and stable performance together constitute the computational performance assessment problem in the decentralized *** this paper,we present a robust performance assessment solution RODE to solve this *** mainly consists of a performance monitoring mechanism and an assessment of the claimed performance(AoCP)*** performance monitoring mechanism first generates reliable and verifiable performance monitoring results for the workloads executed by untrusted cloud *** on the performance monitoring results,the AoCP mechanism forms a unified performance assessment metric to incentivize cloud providers to offer performance as *** extensive experiments,we show RODE can accurately monitor the performance of cloud providers on the premise of reliability,and incentivize cloud providers to honestly present the performance information and maintain the performance stability.

关键词： decentralized cloud computing robust performance assessment trusted execution environment(TEE)

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Privacy-Preserving Federated Deep Learning Diagnostic Method for Multi-Stage Diseases

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computer Modeling in engineering & sciences 2024年第6期139卷 3085-3099页

作者： Jinbo Yang Hai Huang Lailai Yin Jiaxing Qu Wanjuan Xie School of Computer Science and Technology Harbin University of Science and TechnologyHarbin150080China Shanghai Futures Information Technology Co. Ltd.Shanghai201201China Heilongjiang Province Cyberspace Research Center Harbin150001China Information Network Engineering and Research Center South China University of TechnologyGuangzhou510641China

Diagnosing multi-stage diseases typically requires doctors to consider multiple data sources,including clinical symptoms,physical signs,biochemical test results,imaging findings,pathological examination data,and even genetic *** applying machine learning modeling to predict and diagnose multi-stage diseases,several challenges need to be ***,the model needs to handle multimodal data,as the data used by doctors for diagnosis includes image data,natural language data,and structured ***,privacy of patients’data needs to be protected,as these data contain the most sensitive and private ***,considering the practicality of the model,the computational requirements should not be too *** address these challenges,this paper proposes a privacy-preserving federated deep learning diagnostic method for multi-stage *** method improves the forward and backward propagation processes of deep neural network modeling algorithms and introduces a homomorphic encryption step to design a federated modeling algorithm without the need for an *** also utilizes dedicated integrated circuits to implement the hardware Paillier algorithm,providing accelerated support for homomorphic encryption in ***,this paper designs and conducts experiments to evaluate the proposed *** experimental results show that in privacy-preserving federated deep learning diagnostic modeling,the method in this paper achieves the same modeling performance as ordinary modeling without privacy protection,and has higher modeling speed compared to similar algorithms.

关键词： Vertical federation homomorphic encryption deep neural network intelligent diagnosis machine learning and big data

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