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A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce

IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 160-172页

作者： Lun Hu Shicheng Yang Xin Luo Huaqiang Yuan Khaled Sedraoui MengChu Zhou School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China School of Computer Science and Technology Wuhan University of TechnologyWuhan 430070China Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent ComputingChongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of SciencesUrumqi 830000China Center of Research Excellence in Renewable Energy and Power Systems and the Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA

Protein-protein interactions are of great significance for human to understand the functional mechanisms of *** the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them *** address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,CoFex,using *** do so,an in-depth analysis of its limitations is conducted from the perspectives of efficiency and memory consumption when applying it for large-scale PPI data analysis and *** solutions are then devised to overcome these *** particular,we adopt a novel tree-based data structure to reduce the heavy memory consumption caused by the huge sequence information of *** that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been conducted to evaluate the performance of our framework in terms of both efficiency and *** results well demonstrate that the proposed framework can considerably improve its computational efficiency by more than two orders of magnitude while retaining the same high accuracy.

关键词： Distributed computing large-scale prediction machine learning MapReduce protein-protein interaction(PPI)

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Aerodynamic Simulation of a Typical Multirotor e VTOL Aircraft Configuration

Aerodynamic Simulation of a Typical Multirotor e VTOL Aircra...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Ding, Menglong Zhang, Yanyan Zhu, Shiqiang Song, Wei Zhao, Pengyu Yan, Xufei Cai, Jiandong Gu, Jason Xie, Anhuan Research Institute of Interdisciplinary Innovation Zhejiang Lab Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H4R2 Canada

ISBN: (纸本)9781665481090

The aerodynamic interaction among rotors is a key phenomenon that influences the performance of the electric Vertical Takeoff and Landing (eVTOL) aircraft. This study applied Lattice-Boltzmann Method (LBM) to systematically investigate the aerodynamic interaction under typical flight conditions. Simulation of a single rotor was performed to validate the reliability of LBM on rotor aerodynamics and find the maximum acceptable grid size. A numerical study on the complex unsteady flowfield caused by the sixteen rotors was also performed when considering the eVTOL is in hovering, forward flight and hovering under sidewind. Moreover, the analysis of the flowfield provides a detailed insight into the flow physics involved in such regular flight conditions. © 2022 IEEE.

关键词： VTOL/STOL aircraft

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Design and Development of a Small UGV for Object Retrieval in Domestic Environments

Design and Development of a Small UGV for Object Retrieval i...

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IEEE Southeastcon

作者： Bhaavin Kishore Jogeshwar Joshua Bohannon Hakki Erhan Sevil Department of Intelligent Systems and Robotics University of West Florida (UWF) Pensacola FL USA Department of Electrical and Computer Engineering University of West Florida (UWF) Pensacola FL USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

The objective of this project is to develop an unmanned ground vehicle (UGV) prototype capable of retrieving small objects in domestic environments. As the robotics field continues to advance, the demand for autonomous systems that enhance daily life is rapidly increasing. Autonomous systems have the potential to improve efficiency by performing routine tasks, thereby reducing human effort and promoting convenience in household settings. This study explores the development of a small UGV designed to identify, navigate toward, and retrieve small objects while autonomously avoiding obstacles such as walls and furniture in domestic environments. The system utilizes neural networks for real-time object detection. The UGV design consists of an object retrieval mechanism suitable for handling items typically left scattered in domestic environments. The proof-of-concept results show the potential of designed UGV domestic, and could potentially enable further advancements in autonomous household assistance technologies.

关键词： Navigation Toy manufacturing industry Software algorithms Prototypes Object detection Grasping Land vehicles Real-time systems Planning Vehicle dynamics

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A Manta Ray-Inspired Biosyncretic Robot with Stable Controllability by Dynamic Electric Stimulation

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Cyborg and Bionic Systems 2022年第1期2022卷 314-326页

作者： Chuang Zhang Yiwei Zhang Wenxue Wang Ning Xi Lianqing Liu State Key Laboratory of Robotics Shenyang Inst itute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang 110159China Emerging Technologies Institute Department of Industrial Manufacturing Systems Engineering University of Hong KongPokfulamChina

Biosyncretic robots,which are new nature-based robots in addition to bionic robots,that utilize biological materials to realize their core function,have been supposed to further promote the progress in *** as the main operation mechanism relates to the robotic overall ***,biosyncretic robots actuated by living biological actuators have attracted increasing ***,innovative propelling modes and control methods are still necessary for the further development of controllable motion performance of biosyncretic *** this work,a muscle tissue-based biosyncretic swimmer with a manta *** propelling mode has been *** is more,to improve the stable controllability of the biosyncretic swimmer,a dynamic control method based on circularly distributed multiple electrodes(CDME)has been *** this method,the direction of the electric field generated by the CDME could be real-time controlled to be parallel with the adtuation tissue of the dynamic ***,the instability of the tissue actuation induced by the dynamic included angle between the tissue axis and electric field direction could be ***,the biosyncretic robot has demonstrated stable,controllable,and efective swimming,by adjusting the electric stimulation pulse direction,amplitude,and *** work may be beneficial for not only the development of biosyncretic robots but also other related studies including bionic design of soft robots and muscle tissue engineering.

关键词： Robot robot Dynamic

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Modeling and Parameter Identification for Human-robot Coupled Systems in Powered Lower Limb Prostheses.

Modeling and Parameter Identification for Human-robot Couple...

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WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Yongshan Huang Xin Wang Dingkun Liang Jiaming Xiong Anhuan Xie Jason Gu Research Center for Intelligent Robotics Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

Good trajectory tracking results are the basis for the implementation of other upper-level algorithms in powered lower limb prostheses, which rely on dynamics modeling and good parameter identification. However, powered lower limb prosthesis are human-robot coupled systems with human-inthe-loop, and it has been a challenge to model them as well as to perform parameter identification. This paper proposes a modeling method that can realize the decoupling of human-machine, and by constructing the linearized models of human-machine coupled system and prosthetic subsystem about the physical parameter sets respectively, and finally obtaining the relationship of their corresponding physical parameter sets, thus the method of indirectly identifying the parameters of human-machine coupled system through the prosthetic subsystem can be realized. The experimental results verify the feasibility and effectiveness of the method proposed in this paper. And the experimental results also shows that prosthetic controller should take advantage of dynamic of hip motion in order to make the wearer more comfortable and fluid when swinging the leg, and will also make the prosthesis more energy efficient.

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Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

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computers, Materials & Continua 2022年第3期70卷 5133-5142页

作者： Ibrahim M.Mehedi Rachid Mansouri Ubaid M.Al-Saggaf Ahmed I.M.Iskanderani Maamar Bettayeb Abdulah Jeza Aljohani Thangam Palaniswamy Shaikh Abdul Latif Abdul Latif Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia L2CSP Laboratory Mouloud Mammeri UniversityTizi OuzouAlgeria Electrical&Computer Engineering Department University of SharjahUnited Arab Emirates Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics King Abdulaziz UniversityJeddah21589Saudi Arabia

A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this *** this control scheme,the performance against disturbances,uncertainties,and attenuation is *** active disturbance rejection control(LADRC)is mainly based on an extended state observer(ESO)technology.A fractional integral(FOI)action is combined with the LADRC technique which proposes a hybrid control scheme like *** this FOI action improves the robustness of the standard *** set-point tracking of the proposed FO-LADRC scheme is designed by Bode’s ideal transfer function(BITF)based robust closed-loop concept,an appropriate pole placement *** effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system(LFJS).The results show the enhancement of the robustness with disturbance ***,a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.

关键词： Active disturbance rejection fractional calculus ADRC pole placement linear flexible joint system robust control

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Power Dispatch Estimation from Electric Vehicles in a Distribution System

Power Dispatch Estimation from Electric Vehicles in a Distri...

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International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Ganesh K. Venayagamoorthy Imanthi Kalanika Subasinghe Raj Naidoo Holcombe Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University Clemson SC USA Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

The integration of electric vehicles (EVs) into the electric power distribution system poses numerous challenges and opportunities for optimizing energy management and system operations. Electric vehicle grid interfaces (EVGIs), essentially bidirectional power converters, allow for charging/grid-to-vehicle (G2V) and discharging/vehicle-to-grid (V2G) power transfers. A power dispatch estimation (PDE) model for V2G, based on availability of EVs in a distribution system and capabilities of the distribution system, is needed to assist in grid operations. This paper presents the development of a PDE model based on nodal power flows to capture the complex spatiotemporal dependencies inherent in G2V and V2G patterns. The hierarchical structure of a distribution system, feeder to EVGI node, is taken into consideration for PDE. Typical PDE estimation results are presented for the IEEE 34 test node feeder distribution system allocated with EVGIs.

关键词： Partial discharges Vehicle-to-grid Systems operation Estimation Spatiotemporal phenomena Resource management Energy management Voltage control Vehicle dynamics Sustainable development

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Remote Aerial Vehicle Solutions for Weed Detection in Precision Agriculture

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IEEE Access 2025年 13卷 101440-101454页

作者： Shekhar S. Borah Aryan Anand Prabha Sundaravadivel Reginald Fletcher Krishna N. Reddy Department of Electrical and Computer Engineering Center for Robotics and Intelligent Systems The University of Texas at Tyler Tyler TX USA Crop Production Systems Research Unit USDA-Agricultural Research Service (ARS) Stoneville MS USA

This study presents a novel Remote Aerial Vehicle-based approach for detecting pigweeds in soybean (Glycine max) fields using a combination of deep learning and advanced image processing techniques. A custom, high-resolution dataset comprising RGB (red, green, and blue) and multispectral images was collected from USDA operated fields and manually annotated for target pigweed detection. Beyond incorporating YOLOv8 variants for real-time weed classification, this study integrates a comprehensive image processing pipeline, incorporating global thresholding, k-means clustering, 3D surface mapping, and spectral signature analysis to enhance interpretability and detection accuracy. A comparative evaluation of YOLOv8 nano, small, medium, and large models, along with Faster R-CNN, confirmed YOLOv8’s balance between detection accuracy and real-time performance for deployment in precision agriculture. The YOLOv8 nano model emerged as the most balanced in terms of precision (75.6%), recall (81.7%), and mAP@0.5 (81.5%), demonstrating effective weed detection performance under real field conditions. In addition, quadrant-level weed coverage and spatial heatmaps were generated to support targeted interventions. This study advances the current state of RAV based weed detection by providing a field-ready, explainable, and resource-efficient solution, contributing to sustainable farming and data-driven weed management practices.

关键词： Crops Deep learning Accuracy Autonomous aerial vehicles Agriculture Real-time systems Feature extraction Soil Precision agriculture Drones

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FRAME: A Modular Framework for Autonomous Map Merging: Advancements in the Field

IEEE Transactions on Field Robotics

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IEEE Transactions on Field robotics 2024年 1卷 1-26页

作者： Nikolaos Stathoulopoulos Björn Lindqvist Anton Koval Ali-Akbar Agha-Mohammadi George Nikolakopoulos Department of Computer Electrical and Space Engineering Robotics and AI Group Luleå University of Technology Luleå Sweden Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

In this article, a novel approach for merging 3-D point cloud maps in the context of egocentric multirobot exploration is presented. Unlike traditional methods, the proposed approach leverages state-of-the-art place recognition and learned descriptors to efficiently detect overlap between maps, eliminating the need for the time-consuming global feature extraction and feature matching process. The estimated overlapping regions are used to calculate a homogeneous rigid transform, which serves as an initial condition for the general iterative closest point (GICP) point cloud registration algorithm to refine the alignment between the maps. The advantages of this approach include faster processing time, improved accuracy, and increased robustness in challenging environments. Furthermore, the effectiveness of the proposed framework is successfully demonstrated through multiple field missions of robot exploration in a variety of different underground environments.

关键词： Robots Point cloud compression Feature extraction Three-dimensional displays Robot sensing systems Robot kinematics Accuracy

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Research on hybrid flow-shop scheduling based on improved genetic algorithm 18

Research on hybrid flow-shop scheduling based on improved ge...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Chen, Haopeng Fang, Zaojun Zhong, Caiming Ningbo University Ningbo Institute of Materials & Technology Engineering Chinese & Academy of Sciences Faculty of Electrical Engineering and Computer Science Ningbo China Chinese & Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials & Technology Engineering Ningbo China Ningbo University College of Science & Technology Ningbo China

ISBN: (纸本)9798350312201

Aiming at the scheduling problem in the production process of hybrid flow-shop, a hybrid flow-shop scheduling model with the objective of minimizing the makespan is established, and a neighborhood search adaptive genetic algorithm (NSAGA) based on heuristic decoding strategy is proposed. An encoding strategy based on the first stage processing sequence and a decoding strategy based on a heuristic rule are used to guide the algorithm to find the optimal solution quickly. In order to speed up the convergence of the algorithm, the elitism strategy is introduced into the genetic operation, and adaptive crossover and mutation strategy based on sigmoid function is designed. In order to enhance the local search capability of the algorithm, a neighborhood search strategy is designed. Finally, the effectiveness and superiority of NSAGA for solving the hybrid flow-shop scheduling problem (HFSP) with different scales are verified by simulation experiments. © 2023 IEEE.

关键词： Genetic algorithms

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