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Integrating Sustainability and Industry 4.0: A Framework for Sustainable Logistics 4.0

Circular Economy and Sustainability 2025年 1-39页

作者： Di Nardo, Mario Gallab, Maryam Murino, Teresa Wu, Jing Pandey, Shatrudhan Facoltàdi Ingegneria Università Telematica Pegaso Rome 00186 Italy MIS-LISTD Laboratory Computer Science Department Mines-Rabat School (ENSMR) Rabat 10000 Morocco Department of Chemical Materials and Industrial Production Engineering University of Naples “Federico II” Naples Italy Department of Electrical and Photonics Engineering Technical University of Denmark Kgs. Lyngby 2800 Denmark Marwadi University Research Center Faculty of Management Studies Marwadi University Gujarat Rajkot 360003 India

As society becomes more aware of environmental and social issues, supply chain stakeholders increasingly consider these factors alongside efficiency, cost, and time. The logistics industry must adapt by integrating Industry 4.0 technologies and sustainability practices. Sustainable Logistics 4.0, though nascent, is gaining traction for enhancing sustainability through digital interventions. This study conducted a comprehensive literature review and bibliometric network analysis using data extracted from the Scopus and Google Scholar databases, covering the period from 2013 to 2023, focusing on the integration of sustainability, Industry 4.0, and logistics. Noting a gap in conceptual frameworks, the paper performs a SWOT analysis to identify key factors and proposes a framework for digitalizing sustainable logistics and addressing emerging challenges. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Circular Economy Industry 4.0 Logistics Sustainability TBL

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Determination of Suitable Heats ink Layout for a High-Density Integrated Motor Drive Through an Effective Comparison Method

Determination of Suitable Heats ink Layout for a High-Densit...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Venkata Raghavendra I Yanda Lyu Fred Wang Debanjan Chatterjee Pietro Cairoli Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville Tennessee USA US Corporate Research Center ABB Inc Raleigh USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Integrated Motor Drives (IMDs), play a pivotal role in the ever-evolving landscape of technological advancements in fields such as electric transportation and industrial environments. IMDs face challenges managing heat dissipation from drive-switching devices, especially due to confined spaces and dynamic loads, intensified by elevated temperatures near motor heat sources. To overcome thermal challenges, Wideband gap devices are crucial for minimizing losses and enabling diverse heatsink layout configurations within natural cooling. This paper introduces a thermal design approach that employs an analytical thermal model to select extruded heatsinks. The heatsink lengths are then fine-tuned to limit device junction temperatures under dynamic load variations across various heatsink layout configurations. The validation of the analytical and CFD models is then demonstrated through experimental setup. Subsequently, for a 2-level VSI device placement, a comparative analysis is conducted on the heatsink designs selected across various layout configurations, with endeavours focused on identifying the layout configuration that gives out the highest power density.

关键词： Analytical models Motor drives Cooling Layout Transportation Thermal management Thermal analysis Space heating Wideband Load modeling

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Network Parameter Control in Cellular Networks through Graph-Based Multi-Agent Constrained Reinforcement Learning

Network Parameter Control in Cellular Networks through Graph...

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IEEE International Conference on Automation science and engineering (CASE)

作者： Albin Larsson Forsberg Alexandros Nikou Aneta Vulgarakis Feljan Jana Tumova Ericsson Research Research Area Artificial Intelligence (AI) Stockholm Sweden Department of Electrical Engineering and Computer Science Division of Robotics Perception and Learning KTH Stockholm Sweden

Cellular networks are growing in complexity at increasing speed and the geographical locations in which they are deployed in are getting denser. Traditional control methods fall short in providing a scalable and dynamic way of adapting the network to new conditions. Distributed multiagent reinforcement learning successfully addresses scalability problems seen in centralized approaches. The question of achieving learning with constraint satisfaction in distributed systems is still left unanswered in the state-of-the-art. In this work, we aim to perform distributed multi-agent constrained reinforcement learning in order to learn a policy online while satisfying imposed constraints. We use a coordination graph to model the interactions between agents and decompose the global value function. A conservative safety critic is trained in parallel to evaluate the safety of proposed actions. Our method allows for separate training of both the critic and the value network independently of each other, and hence offers flexibility in how and when to train the different models. The results are compared to a baseline using no safety critic. Simulations show that the agents succeed in learning a policy that can satisfy the constraints, while still maximizing the objective.

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Dual-Objective Mixed Integer Linear Program and Memetic Algorithm for an Industrial Group Scheduling Problem

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1199-1209页

作者： Ziyan Zhao Shixin Liu MengChu Zhou Abdullah Abusorrah State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering Northeastern UniversityShenyang 110819China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah 21481Saudi Arabia Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

Group scheduling problems have attracted much attention owing to their many practical *** work proposes a new bi-objective serial-batch group scheduling problem considering the constraints of sequence-dependent setup time,release time,and due *** is originated from an important industrial process,i.e.,wire rod and bar rolling process in steel production *** objective functions,i.e.,the number of late jobs and total setup time,are minimized.A mixed integer linear program is established to describe the *** obtain its Pareto solutions,we present a memetic algorithm that integrates a population-based nondominated sorting genetic algorithm II and two single-solution-based improvement methods,i.e.,an insertion-based local search and an iterated greedy *** computational results on extensive industrial data with the scale of a one-week schedule show that the proposed algorithm has great performance in solving the concerned problem and outperforms its *** high accuracy and efficiency imply its great potential to be applied to solve industrial-size group scheduling problems.

关键词： Insertion-based local search iterated greedy algorithm machine learning memetic algorithm nondominated sorting genetic algorithm II(NSGA-II) production scheduling

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Random suppression of ECG artifacts using a NLSRLMMN-based cascaded noise canceller

Random suppression of ECG artifacts using a NLSRLMMN-based c...

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Asilomar Conference on Signals, Systems & computers

作者： Mohammed Mujahid Ulla Faiz Azzedine Zerguine Izzet Kale Department of Electrical and Computer Engineering Presidency University Bengaluru Karnataka India Electrical Engineering Department Interdisciplinary Research Center for Communication Systems and Sensing KFUPM Dhahran Saudi Arabia Department of Computer Science and Engineering Applied DSP and VLSI Research Group (ADVRG) University of Westminster London United Kingdom

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Normally, the electrocardiogram (ECG) signal artifacts are removed in a particular sequence starting with baseline wander removal at the beginning. In this work, a methodology has been proposed using a novel algorithm called the Normalized Leaky Sign Regressor Least Mean Mixed Norm (NLSRLMMN) algorithm to remove multiple ECG artifacts such as baseline wander, motion artifacts, muscle artifacts, and power line interference randomly without following a particular sequence. Through rigorous simulations we have shown that if we remove multiple ECG artifacts randomly using our proposed approach then an improvement in signal to noise ratio and mean square error is observed as opposed to a conventional method that employs the Least Mean Square (LMS) algorithm in all the cascaded adaptive noise canceller stages.

关键词： computers Adaptation models Adaptive systems Mean square error methods Interference Electrocardiography Muscles Noise cancellation Signal to noise ratio Motion artifacts

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Analysis of Gait Data Based on Deep Learning to Predict Multiple Balance Scale Scores

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IEEE Sensors Journal 2024年第1期24卷 920-930页

作者： Lin, Chueh-Ho Peng, Chih-Wei Lee, I-Jung Wu, Chi-Ming Lin, Bor-Shing Taipei Medical University International Ph.D. Program in Gerontology and Long-Term Care Taipei City110 Taiwan Taipei Medical University Research Center in Nursing Clinical Practice Wan Fang Hospital Taipei City110 Taiwan Taipei Medical University School of Biomedical Engineering College of Biomedical Engineering Taipei City110 Taiwan Taipei Medical University School of Gerontology and Long-Term Care College of Nursing Taipei City110 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City237 Taiwan National Taipei University College of Electrical Engineering and Computer Science New Taipei City237 Taiwan

Unbalanced walking is increasingly common among older adults;therefore, routinely assessing the balance of older adults is crucial. The traditional method of assessing balance uses scales, requires the supervision of a physical therapist (PT), and is time-consuming. The present study, therefore, proposes a deep learning (DL) model architecture that combines a convolutional neural network (CNN) and a long short-term memory (LSTM) network model to predict the scores of three scales, namely the Berg balance scale (BBS), timed up and go (TUG), and single-leg stance (SLS). The gait data of 15 m of walking were collected from seven inertial measurement units (IMUs) and input into the CNN-LSTM model for evaluation. The BBS and TUG only require the participants to wear two IMUs on the left and right thighs, respectively, for accurate predictions. The mean absolute errors (MAEs) of predicting the scores of the BBS and TUG are 1.2562 and 1.4016 s, respectively;however, the MAE of score predictions of SLS is higher than that of the BBS and TUG, indicating that gait data cannot be used for assessing SLS;moreover, participants only wear one IMU on the right calf for BBS and TUG evaluations, which yield MAEs of 1.4334 and 1.5229 s, respectively. The proposed system can quickly and accurately predict the scores of the BBS and TUG. The proposed model can assist PTs with making clinical decisions. © 2001-2012 IEEE.

关键词： Long short-term memory

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Temperature Dependent Implantation of As-Isoelectronic Impurity in GaN Micro and Nanostructures

Temperature Dependent Implantation of As-Isoelectronic Impur...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Aadil Waseem Clarence Chan Xihang Wu Yujie Liu Yifan Shen Manos Kapritsos Theodore B Norris Xiuling Li Chandara Family Department of Electrical and Computer Engineering Microelectronic Research Center The University of Texas at Austin Austin Tx USA Department of Electrical and Computer Engineering Holonyak Micro and Nanotechnology Laboratory University of Illinois Urbana-Champaign Urbana Illinois USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan USA

To enhance solar photo absorption of III-N semiconductors, we demonstrate Arsenic implantation at elevated temperatures, improving doping activation and reducing crystal damage.

ISBN: (纸本)9798350369311

To enhance solar photo absorption of III-N semiconductors, we demonstrate Arsenic implantation at elevated temperatures, improving doping activation and reducing crystal damage.

关键词： Temperature dependence Photonic band gap Impurities Arsenic Metals Lattices Crystals Electro-optic effects Doping profiles Nanostructures

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Hyperbolic metamaterials: fusing artificial structures to natural 2D materials

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eLight 2022年第1期2卷 1-23页

作者： Dasol Lee Sunae So Guangwei Hu Minkyung Kim Trevon Badloe Hanlyun Cho Jaekyung Kim Hongyoon Kim Cheng‑Wei Qiu Junsuk Rho Department of Mechanical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Department of Biomedical Engineering Yonsei UniversityWonju 26493Republic of Korea Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Department of Chemical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics Pohang 37673Republic of Korea.

Optical metamaterials have presented an innovative method of manipulating *** metamaterials have an extremely high anisotropy with a hyperbolic dispersion *** are able to support high-k modes and exhibit a high density of states which produce distinctive properties that have been exploited in various applications,such as super-resolution imaging,negative refraction,and enhanced emission ***,state-of-the-art hyperbolic metamaterials are reviewed,starting from the fundamental principles to applications of artificially structured hyperbolic media to suggest ways to fuse natural two-dimensional hyperbolic *** review concludes by indicating the current challenges and our vision for future applications of hyperbolic metamaterials.

关键词： Hyperbolic metamaterials High resolution optical imaging Nanoscale lithography Light propagation and manipulation Spontaneous emission engineering Natural 2D materials

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InGaN-based Micro-LEDs: Enhancing Efficiency and Speed for Next-Generation Visible Light Communication Applications 19

InGaN-based Micro-LEDs: Enhancing Efficiency and Speed for N...

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Gallium Nitride Materials and Devices XIX 2024

作者： Huang, Wei-Ta Lee, Tzu-Yi Hsiao, Fu-He Miao, Wen-Chien Iida, Daisuke Hong, Kuo-Bin Lin, Chien-Chung Chen, Fang-Chung Chang, Shu-Wei Horng, Ray-Hua Hong, Yu-Heng Huang, Yao-Wei Ohkawa, Kazuhiro Kuo, Hao-Chung Department of Photonics Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan Department of Electrophysics College of Science National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Thuwal23955 6900 Saudi Arabia Department of Electrical Engineering National Taiwan University Taipei10639 Taiwan Research Center for Applied Sciences Academia Sinica Taipei11529 Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu30010 Taiwan

ISBN: (纸本)9781510670327

Visible light communication (VLC), which utilizes LEDs, promises superior privacy and security and reduced impact on surrounding electronics compared to traditional Wi-Fi. This paper explores the potential of InGaN-based micro-light-emitting diodes (micro-LEDs) in high-speed VLC applications, focusing on yellow-green micro-LEDs with nanoporous distributed Bragg reflector (NP-DBR) and red InGaN micro-LEDs. Yellow-green micro-LEDs achieved a maximum external quantum efficiency (EQE) of 8.7%, bandwidth of 442 MHz, and data rate of 800 Mbit/s, while red micro-LEDs demonstrated an EQE of 5.95%, maximum bandwidth of 424 MHz, and data rate of 800 Mbit/s. The application of four core technologies, including circular devices and electrodes, reduced contact electrode area, atomic layer deposition (ALD) for passivation protection, and multi-chip parallel arrays, enhanced optoelectronic characteristics. This paper also highlights the superior performance of InGaN-based red micro-LEDs with a single quantum well (SQW) structure over double quantum wells (DQWs) for VLC applications. The SQW structure yielded higher maximum EQE, modulation bandwidth, and faster transmission rates, paving the way for the potential of full-color micro-display and high-speed VLC applications. © 2024 SPIE.

关键词： Semiconductor quantum wells

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An Optimized Ensemble Model for Prediction the Bandwidth of Metamaterial Antenna

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computers, Materials & Continua 2022年第4期71卷 199-213页

作者： Abdelhameed Ibrahim Hattan F.Abutarboush Ali Wagdy Mohamed Mohamad Fouad El-Sayed M.El-kenawy Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyEgypt

Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their *** size affects the quality factor and the radiation loss of the *** antennas can overcome the limitation of bandwidth for small *** learning(ML)model is recently applied to predict antenna *** can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated *** accuracy of the prediction depends mainly on the selected *** models combine two or more base models to produce a better-enhanced *** this paper,a weighted average ensemble model is proposed to predict the bandwidth of the Metamaterial *** base models are used namely:Multilayer Perceptron(MLP)and Support Vector Machines(SVM).To calculate the weights for each model,an optimization algorithm is used to find the optimal weights of the *** Group-Based Cooperative Optimizer(DGCO)is employed to search for optimal weight for the base *** proposed model is compared with three based models and the average ensemble *** results show that the proposed model is better than other models and can predict antenna bandwidth efficiently.

关键词： Metamaterial antenna machine learning ensemble model multilayer perceptron support vector machines

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