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Autonomous Air and Ground Sensing systems for Agricultural Optimization and Phenotyping VIII 2023

作者： Sellers, Timothy Lei, Tingjun Carruth, Daniel Luo, Chaomin Department of Electrical and Computer Engineering Mississippi State University Mississippi StateMS39762 United States Center for Advanced Vehicular Systems Mississippi State University StarkvilleMS39759 United States

ISBN: (数字)9781510661950

ISBN: (纸本)9781510661943

In order to face the everyday growing population in today's world, the deployment of autonomous vehicles is a promising direction for precision agriculture. Autonomous vehicles (AVs) have been developed and deployed for various agricultural needs such as field planting, harvesting, soil collection, and crop data collection. One method of achieving those task is complete coverage path planning (CCPP), which constructs a continuous path that covers a wide area of interest. However, in a large farm with multiple fields, those tasks have been extremely complicated and computationally expensive on a navigation system when utilizing a single AV. A heterogeneous system is proposed to sense the fields and solve the navigation and routing problem within multi-field path planning. We developed a deep learning-based routing scheme for Unmanned Aerial Vehicles (UAVs) to sense mature crops for harvest. The deep learning routing scheme utilizes a goal embedding feature and coordinate position feature to generate an optimal path for the Unmanned Aerial Vehicles, which allows them to find several candidate solutions. A deep learning-based complete coverage path planning (DL-CCPP) navigation scheme is also proposed for our Unmanned Ground Vehicle (UGVs) to navigate through the fields and collect the mature crops within them. The DL-CCPP uses UAV's images in its deep learning network to construct the CCPP path from the AV coordinates. © 2023 SPIE.

关键词： Crops

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Sensor-Based Multi-Waypoint Autonomous Robot Navigation with Graph-Based Models

Sensor-Based Multi-Waypoint Autonomous Robot Navigation with...

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Autonomous systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2023

作者： Rogers III, James H. Sellers, Timothy Lei, Tingjun Carruth, Daniel W. Luo, Chaomin Department of Electrical and Computer Engineering Mississippi State University Mississippi StateMS39762 United States Center for Advanced Vehicular Systems Mississippi State University StarkvilleMS39759 United States

ISBN: (数字)9781510661974

ISBN: (纸本)9781510661967

Multi-waypoint navigation for autonomous robot is in high demand in real-world robotics applications including search and rescue, disaster response, and environment exploration. In this paper, a sensor-based methodology is proposed for validation of autonomous robot multi-waypoint navigation utilizing graph-based models with adjacent node selection. In addition to time and distance efficiency, the proposed graph-based models incorporate safety in relation to the robot's environment as a driving feature. These models provide path planning for autonomous robot experiments. This methodology is implemented in a real-world environment with simulated dynamic obstacles utilizing a Clearpath Jackal unmanned ground vehicle (UGV) featuring four-wheel drive, GPS, odometry, and a Velodyne VLP-16 LiDAR as the experimental robot configuration. The LiDAR unit utilized has a one hundred meter range with a thirty degree vertical field of view, as the primary navigation sensor. It is utilized to map the environment prior to performing autonomous navigation experiments. This robot configuration is also presented in a simulated environment for more thorough evaluation. The environments to be examined are controlled with obstacles and environment features within the expected view of the LiDAR. The proposed graphbased model is evaluated in terms of planning efficiency from simulated to real-world environments including dynamic obstacle avoidance. © 2023 SPIE. All rights reserved.

关键词： Navigation

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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

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Science China(Information Sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG Shenzhen Research Institute of Big Data Future Network of Intelligence Institute (FNii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

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Robust Control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China Automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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Dynamic Thermal Line Rating Considering Cooling Impact on Conductor's Heating of Transmission Power Loss

Dynamic Thermal Line Rating Considering Cooling Impact on Co...

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2022 International Conference on Informatics electrical and Electronics, ICIEE 2022

作者： Afandi, A.N. Wibawa, Aji Prasetya Rahmawati, Yuni Sunaryono Kobayashi, Makiko Smart Power and Advanced Energy Systems Center Center of Advanced Material for Renewable Energy Universitas Negeri Malang Electrical Engineering Department Malang Indonesia Universitas Negeri Malang Electrical Engineering Department Malang Indonesia Universitas Negeri Malang Department of Physics Malang Indonesia Computer Science and Electrical Engineering Kumamoto University Kumamoto Japan

ISBN: (纸本)9781665486224

The power system is made up of electricity generating facilities, transmission networks, and distribution networks. Utility companies are also final energy users in these systems. Transmission lines are used in the construction of the trans-mission system to link all networks and transport generated power to load requirements. Electricity loss on transmission lines during power supply is transformed into line heating. In this study, the Thunderstorm Algorithm (TA) is used to optimize transmission conductor heating caused by power losses. By taking into consideration dynamic power losses, conductors, measured external temperature, solar radiation, and wind speed, Transmission Conductor Heating (TCH) is used to determine the temperature of bare overhead lines. Technical parameters are used to apply TA to the TCH as well. The transmission conductor heating is approached using a thermal model for the end temperature, and the results demonstrate that power losses result in thermal performances. Additionally, due to the current dynamic losses, the temperature deviation changes with each operating hour. At the temperature threshold, which represents the ambient operating temperature, the optimization produces various outcomes. © 2022 IEEE.

关键词： Electric power transmission networks

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Scattering exceptional point in the visible

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Light(Science & Applications) 2023年第10期12卷 2228-2235页

作者： Tao He Zhanyi Zhang Jingyuan Zhu Yuzhi Shi Zhipeng Li Heng Wei Zeyong Wei Yong Li Zhanshan Wang Cheng-Wei Qiu Xinbin Cheng MOE Key Laboratory of Advanced Micro-Structured Materials Shanghai 200092China Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China Shanghai Frontiers Science Center of Digital Optics Shanghai 200092China Shanghai Professional Technical Service Platform for Full-Spectrum and High-Performance Optical Thin Film Devices and Applications Shanghai 200092China Department of Electronic Science and Technology Tongji UniversityShanghai 201804China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China

Exceptional point (EP) is a special degeneracy of non-Hermitian systems. One-dimensional transmission systems operating at EPs are widely studied and applied to chiral conversion and sensing. Lately, two-dimensional systems at EPs have been exploited for their exotic scattering features, yet so far been limited to only the non-visible waveband. Here, we report a universal paradigm for achieving a high-efficiency EP in the visible by leveraging interlayer loss to accurately control the interplay between the lossy structure and scattering lightwaves. A bilayer framework is demonstrated to reflect back the incident light from the left side ( | r_(−1) | >0.999) and absorb the incident light from the right side ( | r_(+1) | < 10^(–4)). As a proof of concept, a bilayer metasurface is demonstrated to reflect and absorb the incident light with experimental efficiencies of 88% and 85%, respectively, at 532 nm. Our results open the way for a new class of nanoscale devices and power up new opportunities for EP physics.

关键词： visible exceptional incident

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Hybrid Signal Integrity Modeling and Analysis of Heterogeneous Integrated System With Neuromorphic Darwin Chip

IEEE Transactions on Signal and Power Integrity

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IEEE Transactions on Signal and Power Integrity 2024年 3卷 37-46页

作者： Chen, Quankun Ma, Hanzhi Li, Da Tao, Tuomin Tan, Shurun Liu, En-Xiao Schutt-Aine, Jose Li, Er-Ping Zhejiang University Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems and Applications College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang University University of Illinois at Urbana-Champaign Institute Haining314400 China A∗star Institute of High Performance Computing Singapore138632 Singapore University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61820 United States

This article introduces a comprehensive approach for designing and analyzing signal integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips. The proposed integrated system architecture includes a neuromorphic Darwin chip, digital signal processing unit, microcontroller unit, field programmable gate arrays, and coding and decoding modules to encode and reconstruct analog spiking signals. The study evaluates the encoding module and the heterogeneous integration structure and conducts signal integrity analysis. To achieve optimal signal integrity performance, the article proposes a novel binocular eye diagram analysis technique. This innovative approach guides the encoding algorithm modification and improves the overall system performance. This research is the first to combine joint field-circuit simulation, heterogeneous integration modeling, and signal integrity analysis of the Darwin neuromorphic chip, and it is expected to serve as a valuable reference for future studies on similar systems. © 2022 IEEE.

关键词： Neural networks

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Real-time Lightning 3D Imaging and Forecasting Project in Malaysia for Sustainable and Reliable Supply of Energy and Storm Disaster Early Warning 12

Real-time Lightning 3D Imaging and Forecasting Project in Ma...

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12th Asia-Pacific International Conference on Lightning, APL 2023

作者： Morimoto, Takeshi Ahmad, Mohd Riduan Baharuddin, Mohd Zafri Wang, Daohong Yamamoto, Kazuo Kudo, Takeshi Kahtani, Ammar Nasser Al Aziz, Mohamad Zoinol Abidin Abd Akita, Manabu Takayanagi, Yuji Kawasaki, Zen-Ichiro Torii, Tatsuo Kindai University Depertment of Electrical Electronic and Communication Engineering Osaka Japan Melaka Malaysia Universiti Tenaga Nasional Department of Electrical and Electronic Engineering Kajang Malaysia Gifu University Department of Electrical Electronic and Computer Engineering Gifu Japan Chubu University Deptment. of Electrical and Electronic Engineering Aichi Japan Fundamental and Advanced Research Group Otowa Electric Co. Ltd Hyogo Japan Universiti Tenaga Nasional Department of Electrical and Electronics Engineering Kajang Malaysia The University of Electro-Communications Department of Mechanical and Intelligent Systems Engineering Tokyo Japan Osaka University Osaka Japan Research Institute of Nuclear Engineering University of Fukui Fukui Japan

ISBN: (纸本)9781665456852

A joint research project 'real-time lightning 3D imaging and forecasting project for sustainable and reliable supply of energy and storm disaster early warning' has been selected for Science and Technology Research Partnership for Sustainable Development (SATREPS) program. Held in the coastal area of the Straits of Malacca in Malaysia, which suffers from serious lightning disasters with more than 200 lightning days per year, this research aims to contribute to disaster prevention by forecasting lightning strikes by constructing the world's highest lightning observation network. This research project is to conduct the field campaigns associated with artificial rocket-triggered lightning in the coastal area of the Straits of Malacca, where the thunderstorm activity is very high and there are many positive cloud-to-ground flashes that may damage electric, communication and other equipments. Measurements of radio waves in various frequency bands and high-energy radiations, and several Rogowski coils are set up surrounding the strike points. It is planned to realize an electromagnetic field observation network in VHF and LF bands to observe the entire progression of each lightning in detail in a wide area. 3D charge distribution in the thundercloud and the amounts of neutralized charges estimated from the information where the lightning discharge begins, how it progresses, and where it terminates. Then, it is examined by the lightning current waveform measured directly with the high structure and rocket-triggered lightning. By comprehensively grasping the charge behavior in the air related to lightning discharge, it is possible to estimate the charge distribution in the cloud and to predict lightning strike. In addition, promoting the control of electric power equipment using IoT, and the early warning system of severe weather disasters to be implemented in the society. This project further researches on active and adaptive lightning resistance and protection as well as

关键词： Imaging systems

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Black-hole-inspired thermal trapping with graded heat-conduction metadevices

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National Science Review 2023年第2期10卷 131-138页

作者： Liujun Xu Jinrong Liu Peng Jin Guoqiang Xu Jiaxin Li Xiaoping Ouyang Ying Li Cheng-Wei Qiu Jiping Huang Department of Physics State Key Laboratory of Surface Physics and Key Laboratory of Micro and Nano Photonic Structures (MOE) Fudan University Department of Electrical and Computer Engineering National University of Singapore Graduate School of China Academy of Engineering Physics School of Materials Science and Engineering Xiangtan University Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang University International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University

The curved space-time produced by black holes leads to the intriguing trapping *** far,metadevices have enabled analogous black holes to trap light or sound in laboratory ***,trapping heat in a conductive environment is still challenging because diffusive behaviors are *** by black holes,we construct graded heat-conduction metadevices to achieve thermal trapping,resorting to the imitated advection produced by graded thermal conductivities rather than the trivial solution of using insulation materials to confine thermal *** experimentally demonstrate thermal trapping for guiding hot spots to diffuse towards the *** heat-conduction metadevices have advantages in energy-efficient thermal regulation because the imitated advection has a similar temperature field effect to the realistic advection that is usually driven by external energy *** results also provide an insight into correlating transformation thermotics with other disciplines,such as cosmology,for emerging heat control schemes.

关键词： thermal trapping graded metadevices imitated advection

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