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An equivalent electrical model for numerical analyses of ODEP manipulation

An equivalent electrical model for numerical analyses of ODE...

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IEEE international conference on Nano/Micro Engineered and Molecular systems (NEMS)

作者： Wenfeng Liang Shue Wang Yanli Qu Zaili Dong Gwo-Bin Lee Wen J. Li State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy and Sciences China Chinese Academy and Sciences China Chinese Academy of Sciences Beijing Beijing CN Center of Micro Nano Technology Research National Cheng Kung University Taiwan Centre of Micro and Nano Systems Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong China

Opticaldielectrophoresis(ODEP)has been explored experimentally with success in manipulating microscale objects in the last 5 years. However, not much theoretical analyses have been performed to understand its operating principles in depth and also determine its limitations as a tool to manipulate micro- and nano-scale objects. In this paper, we present our work on establishing an equivalent electrical model to analyze the important physical interactions when optically induced dielectrophoretic force is used to manipulate micron-sized polystyrene beads. Simulation results show that the ODEP manipulation of microbeads is frequency-dependent and that the electrothermal effect is negligible. Furthermore, the relationship between the frequency of the applied voltage and the maximum manipulation velocity of the microbeads obtained from simulation is consistent with our experimental measurements. In addition, simulation results also show that the minimum radius of a bead that can be manipulated exponentially decreases with respect to the size of the illuminated spot. For instance, when the illuminated spot size is 1 μm, ODEP can theoretically manipulate 100 nm beads - indicating that ODEP can be extended to manipulate nano-scale objects if the illuminated spot size can be significantly reduced.

关键词： Force Conductivity Electric fields Drag Simulation Nanobioscience

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Surrogate-Assisted Hybrid Metaheuristic for Mixed-Variable 3-D Deployment Optimization of Directional Sensor Networks

Surrogate-Assisted Hybrid Metaheuristic for Mixed-Variable 3...

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Data-driven Optimization of Complex systems (DOCS), international conference on

作者： Yuntian Zhang Chen Chen Tongyu Wu Changhao Miao Shuxin Ding School of Automation Beijing Institute of Technology Beijing China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing China Traffic Management Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing China

A major concern in designing sensor networks is the deployment problem. However, establishing an efficient algorithm for the real-world deployment problem is challenging due to three issues, which are 1) the realistic mixed-integer nonlinear programming problem (MINLP) with mixed-variable; 2) the combinatorial subset selection problem; and 3) the expensive computational cost for fitness evaluation in the 3-D coverage problem. therefore, this paper addresses these challenges and proposes a surrogate-assisted hybrid metaheuristic for mixed-variable 3-D deployment optimization of directional sensor networks (DSNs). First, an MINLP with flexible coordinate transformation technique and an efficient mixed-variable encoding scheme are introduced to model and represent the problem. We propose hybrid metaheuristic which applies two reproduction methods respectively for discrete and continuous variables. Second, we design sparse population-based incremental learning (s-PBIL) to handle inherent subset selection problem. s-PBIL could accurately learn the required information, and automatically learn a sparse distribution. third, a mixed-variable surrogate with unifying space under Bayesian model management is incorporated to reduce the expensive computational cost. Experiment results on real-world deployment scenarios scaling from small-size to large-size show the effectiveness of the proposed algorithm.

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An Intuitive Study: Intrusion Detection systems and Anomalies, How AI can be used as a tool to enable the majority, in 5G era

An Intuitive Study: Intrusion Detection Systems and Anomalie...

引用

international conference on Computing Communication Control and automation (ICCUBEA)

作者： Siddhant Shah Shailesh Pramod Bendale Dept. of Computer Engineering NBN Sinhgad School of Engineering Pune India

ISBN: (数字)9781728140421

ISBN: (纸本)9781728140438

the era of 5G is almost here, with tech companies distributing enabled micro-controllers and governments leasing the required spectrums. A heavily invested field with real-time response and attack systems is required. With data getting localised and handling ever rising cyber-security threats becoming a task, intranet warfare and data manoeuvring resulting in disasters, a new approach is required to redistribute power from the hands of a few to those of many. this paper provides for a novice's perspective to match its theme of power to the people and an approach of Open System Resources in Networking. It gives a well-informed literary survey to educate the reader of the recent developments and the way forward. the paper uses yesteryears coming of age techniques such as Software Defined Networking and Network Function Virtualisation as the basis for start and then deep dives into Artificial Neural Networks. It makes sure that the context of neural networks is not alarming and that data traffic is not analysed against any privacy constraints. this makes the algorithms involved safe to use and creates a viable career in the same sense of maintenance and updating the systems involved. We analyse the application of smart networks that empower a built-in common sense AI with a focus on aspects such as scalability, performance, dependability, security, and resiliency. All of this is with power capacity constraints in mind, and most of the implementations proposed can be created on a simple FPGA architecture.

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Self Operating Paint Bot

Self Operating Paint Bot

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international conference on Devices, Circuits and systems (ICDCS)

作者： Ram Kumar S. S Kaviarasu Kingson Kumar M. K. Saran J. Karthikeyan Satheesh Kumar S. Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore India

ISBN: (数字)9781728163680

ISBN: (纸本)9781728163697

Painting the wall plays a vital role to fix one's gaze at the building. But we have identified a problem behind every painter is their torment due to exposure to paint. Our project overcomes this issue through automation via IoT. In addition to that, our solution finds a way to calculate the exact amount of paint requirement with the image processing technique. the image of the wall is captured by the camera from which the dimensions of the wall can be found by image processing. Using the area of the wall, paint estimation is done. A 2-dimensional axes arms are used to paint the wall. the live status of the painting can be viewed from anywhere by using IoT.

关键词： Paints Painting automation Estimation Buildings Robots DC motors

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Research on the regulation technology of the PV-storage based on the real-time interaction of source and load

Research on the regulation technology of the PV-storage base...

引用

IEEE international conference on automation, Electronics and Electrical Engineering (AUTEEE)

作者： Liu Yi Li Yafei Qian Kejun Zheng Zhong Jiangsu Electric Power Company Suzhou Power Supply Company Suzhou Jiangsu China

ISBN: (数字)9781665471978

ISBN: (纸本)9781665471985

With the novel power system environment including distributed power sources, electric vehicles, energy storage and other emerging elements continuing to access, new requirements for grid operation and control have been put forward. However, each system operates more independently, resulting in low utilization of the existing capacity of the grid. In order to improve the source-load synergy, this paper analyzes the source-load characteristics of typical users, establishes the optimization objectives of minimum carbon emission, minimum multi-entity energy cost and maximum new energy utilization, designs a multi-objective optimization decision method based on adaptive weighting, analyzes multiple constraints such as power, voltage, load and consumption rate, and constructs an integrated regulation and control strategy for PV and storage. the paper validates the research for the actual grid demonstration application scenario, and proves the effect of integrated regulation for improving power quality, enhancing new energy consumption rate and reducing carbon emission.

关键词： Costs Microgrids Carbon dioxide Regulation Real-time systems Power systems Time factors

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Evolutionary Multi-Objective Neural Architecture Search for Generalized Cognitive Diagnosis Models

Evolutionary Multi-Objective Neural Architecture Search for ...

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Data-driven Optimization of Complex systems (DOCS), international conference on

作者： Shangshang Yang Cheng Zhen Ye Tian Haiping Ma Yuanchao Liu Panpan Zhang Xingyi Zhang Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

Cognitive diagnosis models (CDMs) with high generalization are essential for intelligent education systems to reveal students' knowledge states in multiple datasets. However, existing CDMs' architectures are designed dependent on researcher expertise and experience from observing and summarizing partial students' learning behaviors, which makes handcrafted models not cover all learning behaviors well and thus limits their generalization. To develop generalized CDMs, this paper proposes an evolutionary neural architecture search to design CDMs' architectures effective on multiple datasets automatically. Specifically, we first formulate the search task as a multi-objective optimization problem (MOP), which maximizes model performance on multiple datasets containing learning behaviors as many as possible to ensure model generalization. then, an expressive search space is devised to contain as many potential architectures as possible, where each architecture is denoted by a unified form, taking three given inputs and integrating them in a linear or no-linear manner for prediction. Finally, an evolutionary algorithm with a tailored deduplication strategy is employed to solve the MOP, where each architecture is further represented by a single-root computation tree for easy optimization. Experiments on multiple datasets demonstrate the generalization and effectiveness of the best architecture searched by the proposed approach, and the searched architecture also holds as good interpretability as handcrafted architectures.

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Double-layer planning configuration with distributed PV power and energy storage system

Double-layer planning configuration with distributed PV powe...

引用

IEEE international conference on automation, Electronics and Electrical Engineering (AUTEEE)

作者： Han Yu Hu Rong Xu Yong Li Cheng Fujian Provincial Key Laboratory of Big Data Mining and Application Fujian University of Technology Fuzhou China

ISBN: (数字)9781665471978

ISBN: (纸本)9781665471985

For distributed photovoltaic power sources are intermittent and random, which makes it difficult to meet the needs of distribution networks, this article proposes an economic planning and configuration method for distributed energy storage systems from the perspective of energy storage investors. this paper is based on the investor's perspective with the lowest cost of distributed energy storage as the goal, considering the tide, voltage, storage power, capacity and other constraints, establishing a distributed energy storage configuration optimization model with distributed energy storage investment and construction cost, maintenance costs, store low and sell high for profit and network loss cost as the goal. Convert a single -layer optimization into dual -layer optimization, and conduct simulation experiments in the IEEE 33-node arithmetic system through improved genetic algorithms. According to the experimental results, the model proposed in this paper can enhance the voltage quality and economic efficiency of the grid and reduce the network losses.

关键词： Photovoltaic systems Adaptation models Costs Voltage Distribution networks Planning Tides

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Adaptive Robotic Grasping with Replay Tail Memory Enhancement

Adaptive Robotic Grasping with Replay Tail Memory Enhancemen...

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Artificial Intelligence, robotics and Control (AIRC), international conference on

作者： Hytham A. Tag Abdullah T. Elgammal Ahmed M. Elassal Mechanical Engineering Department Benha Faculty of Engineering Benha University Benha Egypt The British University in Egypt Electrical Engineering Department Benha Faculty of Engineering Benha University Benha Egypt

ISBN: (数字)9798350385076

ISBN: (纸本)9798350385083

Robotic grasping faces catastrophic forgetting as knowledge of manipulated objects fades when handling new items. this paper introduces “replay tail,” a memory technique using an RGBD camera to capture tabletop scenes, convert observations to 3D point clouds, and generate vertically projected heightmaps. Building on deep Q-learning combining deep neural networks and reinforcement learning, replay tail replays recent heightmap experiences to maintain adaptation. By emphasizing recent interactions during memory replay, grasping policies continuously recalibrate, preventing performance degradation despite emerging novelty. Experiments with 2000 simulated automated grasping attempts show 89% average success rates using replay tail versus 86% otherwise. these highlights replay tail's potential to enable real-world deployment by mitigating catastrophic forgetting through consolidated recent memories.

关键词： Point cloud compression Degradation three-dimensional displays Q-learning Robot vision systems Tail Grasping

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automation of Shopping Carts using Technology

Automation of Shopping Carts using Technology

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international conference for Convergence of Technology (I2CT)

作者： B Aiswarya Padma Arun Aravindakshan Amal Prakash College of Engineering Trivandrum Kerala Technical University (KTU) Thiruvananthapuram India Rajiv Gandhi Institute of Technology Kottayam M G University (KTU) Thiruvananthapuram India Sree Buddha College of Engineering Pattor Kerala University (KU) Thiruvananthapuram India

ISBN: (数字)9781538680759

ISBN: (纸本)9781538680766

the advancements and developments in the field of innovative and creative thinking have played a pivotal role in kick-starting a whole new phase of technology - Internet of things (IoT). A lot of research is being done in the line of robotics and artificial intelligence, all of which has helped us think of a very effective and economical means of reducing manual labor in our day to day activities. We found our inspiration in a supermarket. Moving shopping carts manually can sometimes become too tedious to control, especially for the elderly and physically disabled. the objective of our work was to solve a major problem of existing shopping carts, which is that they rely on manual labor to move. Our cart uses the principles of image processing to map itself to one particular user using a pattern tag and follows the user based on single object tracking and the distance sensed by ultrasonic sensors interfaced with a Raspberry Pi.

关键词： Sensors Acoustics Tracking Shape Image color analysis Webcams

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Frequency characteristics analysis of large-scale gridconnected photovoltaic power system considering frequency response of under-frequency load shedding

Frequency characteristics analysis of large-scale gridconnec...

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Artificial Intelligence and Electromechanical automation (AIEA), international conference on

作者： Hongjun Fu Xingwei Du Feng Yao Wei Han Wenyan Duan State Grid Henan Electric Power Company Zhengzhou China State Grid Henan Electric Power Research Institute Zhengzhou China

ISBN: (数字)9798350366174

ISBN: (纸本)9798350366181

Under-frequency load shedding (UFLS) control strategy can solve the frequency drop problems when the source and load sides of the power system are disturbed by a large range of active power. Based on the traditional system frequency response model (SFR), the new energy system’s improved SFR model is established. the combined frequency modulation control strategy of thermal power and photovoltaic units is considered, and the frequency control of UFLS is introduced. the new power system parameters are analyzed by mathematical analysis method, and the system frequency characteristic expression is established. Finally, the process of the simulation shows that this strategy can effectively improve the frequency stability, which guides the frequency control of large-scale photovoltaic grid-connected power systems.

关键词： Photovoltaic systems Analytical models Time-frequency analysis Frequency modulation Load shedding Power system stability Frequency response Stability analysis thermal stability Load modeling

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