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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Orozco Villanueva, Kevin Alejandro Richter, Miguel Villa, Carlos Martinez-Villasenor, Lourdes Ponce, Hiram Barrera-Animas, Ari Yair Universidad Panamericana Faculty of Engineering Mexico City Mexico Massachusetts Institute of Technology Electrical Engineering and Computer Science Boston United States

ISBN: (纸本)9781665430654

Gait analysis is becoming increasingly central in various fields such as biomechanics, medicine, and sports. This complex study assesses how individuals walk, weighing in on aspects like bone alignment, joint range of motion, and neuro-muscular activity. Its profound importance emanates from its capability to identify potential walking anomalies at an early stage, which can offset the need for invasive medical interventions and offer valuable insights for clinicians to make well-informed decisions. Inspiration for this in-depth gait analysis research was sourced from previous attempts that employed tools like step mats and cameras to track and analyze movement. Several design imperatives were consolidated within this framework, including the vital need of user safety, assuring comfort throughout usage, preserving system stability, and the undoubtedly significant feature of keeping the insole lightweight. These priorities were not merely for user comfort but were essential for the fidelity of the data being captured. In this paper, it is described the design and optimization processes of an insole for gait analysis following an agile methodology which involves the following stages: requirements, design, implementation and testing. This study delves deeply into the challenges of designing, implementing, and optimizing instrumented insoles for gait analysis. The requirements were successfully achieved by creating a 3mm-thick, flexible insole using TPU 95 material through 3D printing. This insole effectively encapsulates electronic components, ensuring comfort, durability, and safety. © 2023 IEEE.

关键词： Gait analysis insole unobtrusive wearable

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Enhanced Neural SLAM with Semantic Segmentation in Dynamic Environments 8

Enhanced Neural SLAM with Semantic Segmentation in Dynamic E...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Shen, Zhengcheng Mao, Minzhe Kastner, Linh Lambrecht, Jens Chair Industry Grade Networks and Clouds Berlin Institute of Technology Faculty of Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350300178

Mobile robots face a significant challenge when navigating in dynamic environments such as human crowds. Existing research works typically employ separate data or simulators for dynamic object detection and navigation tasks. This paper combines the photo-realistic simulator Habitat with embedded dynamic objects to create a playground for optimizing vision-based navigation algorithms. To validate our system, we implement and train three approaches - zero masks, image memory inpainting, and semantic map filter - using semantically segmented information. We then implement and evaluate an adapted reinforcement-learning-based SLAM algorithm using the validation Gibson dataset. The results indicate that moderate localization bias occurs when the environment is small and the navigation process is short. However, the error will accumulate over time. Additionally, a dynamic environment leads to less accurate localization. All three approaches can reduce the localization error, while the semantic map filter approach shows the best overall performance. © 2023 IEEE.

关键词： Object detection

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Towards Real-Time Motion Planning for Industrial Robots in Collaborative Environments 49

Towards Real-Time Motion Planning for Industrial Robots in C...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Bhuiyan, Teham Kutschank, Benno Pruter, Karim Flach, Huy Kastner, Linh Lambrecht, Jens Berlin Institute of Technology Chair Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350331820

In collaborative environments, real-time motion planning is crucial for industrial robots to navigate safely and efficiently. Traditional planning algorithms, such as Rapidly-exploring Random Trees (RRT) or Probabilistic Roadmaps (PRM), often face challenges in coping with dynamic environments due to their inherent computational complexity. To address this issue, we propose an approach based on Deep Reinforcement Learning (DRL) for real-time motion planning of industrial robots. Our method leverages the power of machine learning and neural networks to enable robots to make intelligent decisions in real-time, ensuring prompt and adaptive navigation. However, applying DRL to industrial robots poses unique challenges, as vision-based training is difficult and distance sensors commonly used in mobile robots are unavailable. To overcome these challenges, we employ depth cameras to generate distance information and convert the obtained point cloud into voxels using the Open3D library. The obstacles are then loaded into the simulation environment in real-time, allowing the agent to perceive and react to the dynamic environment. To achieve a low simulation-to-real-gap, we propose a hardware-in-the-loop (HIL) approach, where the real robot mimics the movements of the simulated robot. We demonstrate the effectiveness of our system through real-world experiments. Our code is available on GitHub [1]. © 2023 IEEE.

关键词： Industrial robots

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Dark Forest Algorithm:A Novel Metaheuristic Algorithm for Global Optimization Problems

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computers, Materials & Continua 2023年第5期75卷 2775-2803页

作者： Dongyang Li Shiyu Du Yiming Zhang Meiting Zhao Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo315000China Engineering Laboratory of Advanced Energy Materials Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo315000China School of Material and Chemical Engineering Ningbo UniversityNingbo315000China

Metaheuristic algorithms,as effective methods for solving optimization problems,have recently attracted considerable attention in science and engineering *** are popular and have broad applications owing to their high efficiency and low *** algorithms are generally based on the behaviors observed in nature,physical sciences,or *** study proposes a novel metaheuristic algorithm called dark forest algorithm(DFA),which can yield improved optimization results for global optimization *** DFA,the population is divided into four groups:highest civilization,advanced civilization,normal civilization,and low *** civilization has a unique way of *** verify DFA’s capability,the performance of DFA on 35 well-known benchmark functions is compared with that of six other metaheuristic algorithms,including artificial bee colony algorithm,firefly algorithm,grey wolf optimizer,harmony search algorithm,grasshopper optimization algorithm,and whale optimization *** results show that DFA provides solutions with improved efficiency for problems with low dimensions and outperforms most other algorithms when solving high dimensional *** applied to five engineering projects to demonstrate its *** results show that the performance of DFA is competitive to that of current well-known metaheuristic ***,potential upgrading routes for DFA are proposed as possible future developments.

关键词： Metaheuristic algorithm global optimization

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Multi-Armed Bandits with Self-Information Rewards

Multi-Armed Bandits with Self-Information Rewards

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作者： Weinberger, Nir Yemini, Michal Technion-Israel Institute of Technology Faculty of Electrical and Computer Engineering Haifa3200003 Israel Bar-Ilan University Faculty of Engineering Ramat Gan5290002 Israel

This paper introduces the informational multi-armed bandit (IMAB) model, in which at each round, a player chooses an arm, observes a symbol, and receives an unobserved reward in the form of the symbol's self-information. Thus, the expected reward of an arm is the Shannon entropy of the probability mass function of the source that generates its symbols. The player aims to maximize the expected total reward associated with the entropy values of the arms played. Under the assumption that the alphabet size is known, two UCB-based algorithms are proposed for the IMAB model which consider the biases of the plug-in entropy estimator. The first algorithm optimistically corrects the bias term in the entropy estimation. The second algorithm relies on data-dependent confidence intervals that adapt to sources with small entropy values. Performance guarantees are provided by upper bounding the expected regret of each of the algorithms. Furthermore, in the Bernoulli case, the asymptotic behavior of these algorithms is compared to the Lai-Robbins lower bound for the pseudo regret. Additionally, under the assumption that the exact alphabet size is unknown, and instead the player only knows a loose upper bound on it, a UCB-based algorithm is proposed, in which the player aims to reduce the regret caused by the unknown alphabet size in a finite time regime. Numerical results illustrating the expected regret of the algorithms presented in the paper are provided. © 1963-2012 IEEE.

关键词： Biological systems

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Novel add-drop filter based on serial and parallel photonic crystal ring resonators (PCRR)

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Journal of Optical Communications 2024年第2期45卷 235-247页

作者： Fakhruldeen, Hassan Falah Al-Asady, Heba Abdul-Jaleel Mahinroosta, Tayebeh Sohrabi, Foozieh Hamidi, Seyedeh Mehri Computer Techniques Engineering Department Faculty of Information Technology Imam Ja’afar Al-sadiq University Baghdad Iraq Electrical Engineering Department College of Engineering University of Kufa Kufa Iraq Computer Technical Engineering Department College of Technical Engineering The Islamic University Najaf Iraq Magneto-Plasmonic Lab Laser and Plasma Research Institute Shahid Beheshti University Tehran*** Iran

Photonic crystal ring resonators (PCRR) as momentous candidates for future photonic crystal integrated circuits (PCICs) draw worldwide attention. In this paper, different configurations are proposed based on single, parallel, and serial PCRRs. To be precise, the different coupling lengths and alignments have been discussed in double and triple PCRRs in parallel and serial configurations to achieve the highest efficiency concerning the desired applications such as an add-drop filter (ADF) and a power splitter. Moreover, in the achieved optimum double and triple PCRRs, the effect of coupling radius change has been discussed. © 2024 Walter de Gruyter GmbH. All rights reserved.

关键词： Photonic crystals

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An Efficiency-Enhanced LCC-S Based Inductive Power Transfer Converter Throughout Battery Constant Current Charging Process 32

An Efficiency-Enhanced LCC-S Based Inductive Power Transfer ...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Luo, Yuying Iam, Io-Wa Ding, Zhaoyi Chan, Pak-Ian Lam, Chi-Seng University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350399714

Constant current (CC) charging is a dominant charging process before the battery can be fully charged and the battery is considered as an equivalent resistance with a wide range variation during the process. However, a wide load range variation causes the transfer efficiency of inductive power transfer (IPT) converter to deviate from the optimum point. Therefore, transfer efficiency optimization measures are required during battery CC charging process with IPT converter. Herein, this paper proposed a suitable bivariate control method for a single-stage IPT converter based on inductor-capacitor-capacitor-series (LCC-S) compensation topology, which keeps the converter output current constant and improves transfer efficiency. The newly adopted bivariate control method includes two control variables, the conduction angle of the voltage-controlled semi-active rectifier (VCSAR) and the operating frequency of the inverter. The equivalent load of the VCSAR is adjusted by controlling the conduction angle, and at the same time, the operating frequency of the inverter is controlled to ensure constant current output. Finally, simulation results are presented to verify the effectiveness of the bivariate control method for the LCC-S compensated IPT converter. In addition, zero-voltage switching (ZVS) can be realized in both sides of the converter. © 2023 IEEE.

关键词： Zero voltage switching

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A Framework for Vehicle and License Plate Detection in Pakistani Traffic Environments Using Algorithms Pool

A Framework for Vehicle and License Plate Detection in Pakis...

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2024 International Conference on IT and Industrial Technologies, ICIT 2024

作者： Shahid, Zara Khan, Fatima Khan, Khurram Syed, Muhammad Ibrahim Tareen, Nauman Khan Mahmood, Zahid Faculty of Electrical Engineering GIK Institute of Engineering Sciences and Technology KPK Topi Pakistan Electrical and Computer Engineesring COMSATS University Abbottabad Islamabad Pakistan GIK Institute of Engineering Sciences and Technology KPK Topi Pakistan Department of Product Design Ziel Global Limited Islamabad Pakistan

ISBN: (纸本)9798331504465

Automation of vehicle and license plate detection plays a vital role in several applications, such as security, traffic management, vehicle monitoring, tool collection, and parking-lot entry/exit control. This paper presents a framework to detect vehicles and license plates for Pakistani traffic environments. To detect vehicles and license plates, the proposed framework uses two pools to locate vehicles and license plates. Each of the pools uses two algorithms to locate vehicles and license plates. The pool of vehicle detection uses the Gaussian Mixture Model (GMM) along with the Faster-RCNN. While the license plate detection pool uses an image processing-based technique along with the HSV segmentation method. Detailed simulations have been performed on our own collected 1142 diverse Pakistani traffic images. Our system achieves a mean accuracy of 90.26% and consumes less than 2 seconds on average to locate vehicles and license plates. © 2024 IEEE.

关键词： Image segmentation

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Data-Filtered Prediction with Decomposition and Amplitude-Aware Permutation Entropy for Workload and Resource Utilization in Cloud Data Centers

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IEEE Internet of Things Journal 2025年第12期12卷 19189-19201页

作者： Yuan, Haitao Hu, Qinglong Wang, Meijia Wang, Shen Bi, Jing Buyya, Rajkumar Shi, Shuyuan Yang, Jinhong Zhang, Jia Zhou, MengChu Beihang University School of Automation Science and Electrical Engineering Beijing100191 China City University of Hong Kong Department of Computer Science Hong Kong999077 Hong Kong Beijing University of Technology School of Software Engineering The Faculty of Information Technology Beijing100124 China Lab School of Computing and Information Systems MelbourneVIC3010 Australia Beihang University School of Integrated Circuit Science and Engineering Beijing China CSSC Systems Engineering Research Institute Beijing China Southern Methodist University Department of Computer Science The Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

In recent years, cloud computing has witnessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to substantial improvements in quality of service and cost efficiency. However, these data often exhibit non-linearity, high volatility, and interdependencies across different categories, presenting challenges for accurate forecasting. Consequently, there is a critical need to develop a method that thoroughly and comprehensively analyzes all available data to forecast future trends effectively. This work proposes a novel integrated data-enhanced prediction model named SVAPI for achieving high-accuracy workload prediction in cloud computing systems. SVAPI employs the Savitzky-Golay filter, Variational mode decomposition, and the mode selection based on Amplitude-aware Permutation entropy for feature processing, whose features are subsequently utilized by Informer for multivariate joint analysis of the enhanced data, achieving high-precision prediction. Ablation and comparative experiments with advanced prediction models are conducted on the Google cluster trace and other typical datasets. Realistic data-driven results indicate that SVAPI improves the prediction accuracy by 37.7% compared to the original Informer, with each module contributing to the performance enhancement. Furthermore, compared with Autoformer, SVAPI enhances the prediction accuracy of workload, CPU, and memory by 65.6%, 66.9%, and 70.8%, respectively, demonstrating that SVAPI owns strong abilities in noise filtering, feature processing, and multivariate joint analysis for achieving higher prediction accuracy. © 2014 IEEE.

关键词： Quality of service

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Highly efficient ternary organic solar cells with excellent open-circuit voltage and fill factor via precisely tuning molecular stacking and morphology

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Science China Chemistry 2024年第3期67卷 963-972页

作者： Dinghong Sun Zhenyu Chen Jianfeng Zhang Wei Song Jingyu Shi Jintao Zhu Yuanyuan Meng Fei Jin Shuncheng Yang Ziyi Ge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Faculty of Material Science and Chemical Engineering Ningbo UniversityNingbo 315211China Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology&EngineeringChinese Academy of SciencesNingbo 315201China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049China Department of Chemical and Environmental Engineering University of Nottingham NingboNingbo 315100China

The micro-morphology and molecular stacking play a key role in determining the charge transport process and nonradiative energy loss, thus impacting the performances of organic solar cells(OSCs). To address this issue, a non-fullerene acceptor PhC6-IC-F with alkylbenzene side-chain, possessing optimized molecular stacking, complementary absorption spectra and forming a cascade energy level alignment in the PM6:BTP-eC9 blend, is introduced as guest acceptor to improve efficiency of ternary OSCs. The bulky phenyl in the side-chain can regulate crystallinity and optimizing phase separation between receptors in ternary blend films, resulting in the optimal phase separations in the ternary films. As a result, high efficiencies of 18.33% as photovoltaic layer are obtained for PhC6-IC-F-based ternary devices with excellent fill factor(FF) of 78.92%. Impressively, the ternary system produces a significantly improved open circuit voltage(V_(oc)) of 0.857 V compared with the binary device,contributing to the reduced density of trap states and suppressed non-radiative recombination result in lower energy loss. This work demonstrates an effective approach for adjusting the aggregation, molecular packing and fine phase separation morphology to increase V_(oc) and FF, paving the way toward high-efficiency OSCs.

关键词： alkylbenzene side-chain morphology regulation ternary blends organic solar cells

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