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Design and development of mini electric bike

AIP Conference Proceedings 2022年第1期2527卷

作者： Dhiyaneswaran Jaganathan Rajender Gogu Balakumar Subramanian Harikumar Pallathadka Nithya Sabtharishi 1Department of Mechanical Engineering Sri Krishna College of Engineering and Technology Coimbatore - 641008 Tamil Nadu India 2Department of EEE Kakatiya Institute of Technology and Science Warangal Telangana India 3Electrical and Computer Engineering Arba Minch University Arba Minch Ethiopia 4Manipur International University Imphal Manipur India 5Department of Information Technology P.S.N.A College of Engineering and Technology Dindigul Tamilnadu India

The Concept and idea behind our E-bike is that due to the increase in usage of automobiles in the world, in turn it increases global warming and heat in our world. On behalf of this, the Indian government took a mission that by 2030, the nation will be transformed to a 100 percent e-mobility country. To achieve this humongous mission, first we need to achieve the factors like customers acceptability and desirability and the major factor cost-efficiency. In 2021, 15.2 million units of engine-based bikes were sold in India and the previous year 21 million units were sold. So, these bike owners tend to use these bikes around 10 years from the purchase, this shatters India’s 2030 mission. To overcome this, we come up with an idea that if we can convert the conventional engine bikes to electric bikes then we can displace the engines into e-bikes, which can make stupendous improvement in e-mobility usage in our country. Our bike is totally built and designed using old bikes, which makes it cost efficient as well as it retains every grain feature of bikes.

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Learning of long-horizon sparse-reward robotic manipulator tasks with base controllers

arXiv

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arXiv 2020年

作者： Wang, Guangming Xin, Minjian Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Engineering University of California San Diego La Jolla CA92093 United States Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Deep Reinforcement Learning (DRL) enables robots to perform some intelligent tasks end-to-end. However, there are still many challenges for long-horizon sparse-reward robotic manipulator tasks. On the one hand, a sparse-reward setting causes exploration inefficient. On the other hand, exploration using physical robots is of high cost and unsafe. In this paper, we propose a method of learning long-horizon sparse-reward tasks utilizing one or more existing traditional controllers named base controllers in this paper. Built upon Deep Deterministic Policy Gradients (DDPG), our algorithm incorporates the existing base controllers into stages of exploration, value learning, and policy update. Furthermore, we present a straightforward way of synthesizing different base controllers to integrate their strengths. Through experiments ranging from stacking blocks to cups, it is demonstrated that the learned state-based or image-based policies steadily outperform base controllers. Compared to previous works of learning from demonstrations, our method improves sample efficiency by orders of magnitude and improves the performance. Overall, our method bears the potential of leveraging existing industrial robot manipulation systems to build more flexible and intelligent controllers. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Introducing a mobility on demand system beyond COVID-19: Evidences from users’ perspective

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AIP Conference Proceedings 2021年第1期2343卷

作者： Vincenza Torrisi Giuseppe Inturri Matteo Ignaccolo 1Department of Civil Engineering and Architecture University of Catania Via S.Sofia 64 Catania 95125 Italy 2Department of Electric Electronic and Computer Engineering University of Catania Via S. Sofia 64 Catania 95125 Italy

The rapidly increasing transport in the last decades, characterized by high motorization rate especially in urban areas, constitutes a relevant contemporary issue addressed by scholars, planners and policy-makers, aiming to promote sustainable mobility. Nowadays, the COVID-19 crisis has influencing transport behaviour with a massive blow to public transport (PT) due to the social distancing. In this context, solutions represented by Demand Responsive Transport (DRT) can play a fundamental role not only in weak demand areas but also where the use of PT is relevant, as on-demand shuttles allow for more physical distancing and are cost-effective for more frequent *** essential point of the proposed study to be highlighted is the design of a structured multi-layered survey to identify the core attributes and the fundamental variables connected to the acceptance and potential use of a DRT service. The case study of a Mediterranean University has been analyzed, which is considering the opportunity to implement a public on-demand transport system, in order to enhance the efficiency of the current traditional public transport service and to discourage the use of the private *** results of an in-depth investigation are presented, which will serve to explore transport demand preferences towards flexible mobility and to identify the characteristics of the DRT service to be implemented. This work also lays the basis for further research with the aim of investigating the key aspects connected to innovative shared mobility solutions and thus supporting policy-makers and public and private transport companies to face new mobility issues.

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Balanced truncation of k-positive systems

arXiv

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arXiv 2020年

作者： Grussler, Christian Damm, Tobias Sepulchre, Rodolphe The Department of Electrical Engineering and Computer Sciences UC Berkeley BerkeleyCA94720 United States The Department of Mathematics at TU Kaiserslautern Fraunhofer ITWM Gottlieb-Daimler-Straße 48 Kaiserslautern67663 Germany The Control Group The Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom

This paper considers balanced truncation of discrete-time Hankel k-positive systems, characterized by Hankel matrices whose minors up to order k are nonnegative. Our main result shows that if the truncated system has order k or less, then it is Hankel totally positive (∞-positive), meaning that it is a sum of first order lags. This result can be understood as a bridge between two known results: the property that the first-order truncation of a positive system is positive (k = 1), and the property that balanced truncation preserves state-space symmetry. It provides a broad class of systems where balanced truncation is guaranteed to result in a minimal internally positive *** Codes 47A58, 93A15, 93A30 Copyright © 2020, The Authors. All rights reserved.

关键词： Matrix algebra

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Front Cover: Micrometer-Sized Liposome-Based Systems: A Hierarchical Breakdown (ChemSystemsChem 3/2025)

ChemSystemsChem

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ChemSystemsChem 2025年第3期7卷

作者： Prof. Dr. Shogo Hamada Dr. Hironori Sugiyama Prof. Dr. Yiting Zhang Prof. Dr. Shoji Iwabuchi Soichiro Hiroi Toshiki Maruyama Yuktesh Balaji Sota Kumagai Prof. Dr. Satoshi Murata Prof. Dr. Taro Toyota Department of Computer Science School of Computing & Department of Systems and Control Engineering School of Engineering Institute of Science Tokyo 4259 Nagatsuta-cho Midori-ku Yokohama-city Kanagawa 226-8501 Japan These authors contributed equally. Department of Applied Chemistry Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Department of Chemistry College of Science Rikkyo University 3-34-1 Nishi-Ikebukuro Toshima-ku Tokyo 171-8501 Japan Department of Biotechnology and Life Science Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei-shi Tokyo 185-8588 Japan Department of Basic Science Graduate School of Arts and Sciences The University of Tokyo 3-8-1 Komaba Meguro-ku Tokyo 153-8902 Japan Department of Robotics Graduate School of Engineering Tohoku University 6-6-01 Aramaki-Aza Aoba Aoba-ku Sendai Miyagi 980-8579 Japan Universal Biology Institute The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan

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Deep learning enabled smart charging technology for electric vehicles

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AIP Conference Proceedings 2022年第1期2527卷

作者： T. Blesslin Sheeba C. Sharanya C. Nayanatara S. K. Indumathi K. Kalins G. Ignisha Rajathi 1Department of ECE R.M.K. Engineering College Chennai India 2Department of ECE Vels Institute of Science Technology and Advanced Studies Chennai India 3Department of EEE Sri Sairam Engineering College Chennai India 4Centre for Automation and Robotics Hindustan Institute of Technology and Science Chennai India 5Department of Science and Humanities Sri Krishna College of Engineering and Technology Coimbatore India 6Department of Computer Science and Business Systems Sri Krishna College of Engineering and Technology Coimbatore India

Reliability, efficiency, and cost-effectiveness of smart grids are enhanced with power demand softening by means of efficient load management in electric vehicles. In such initiatives, the involvement of EV users may reduce due to the lack of adaptable user-centric approaches. During the connection sessions, the EV charging time is determined using a deep learning algorithm-based smart charging strategy proposed in this paper. Here, the total energy cost of the vehicle is minimized by making charging decisions considering demand time series, pricing, environment, driving, and other auxiliary data. The memorization technique is used for the estimation of the optimal solution of the existing connection sessions in the initial stage. The deep learning models are trained with this existing data and optimal decisions to make suitable decisions in real-time scenarios where car usage or future energy price values are undetermined. A significant reduction in the charging cost is observed by training the neural network with the proposed model. The results obtained are compared to the optimal charging costs computed and are found to be closely similar.

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Flight control design for a highly flexible flutter demonstrator

Flight control design for a highly flexible flutter demonstr...

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AIAA Scitech Forum, 2019

作者： Luspay, Tamás Baár, Tamás Teubl, Dániel Vanek, Bálint Ossmann, Daniel Wüstenhagen, Matthias Pusch, Manuel Kier, Thiemo Waitman, Sérgio Iannelli, Andrea Marcos, Andres Lowenberg, Mark Systems and Control Lab Institute for Computer Science and Control Kende u 13-17 Budapest Hungary DLR German Aerospace Center Institute of Robotics and Mechatronics Wessling82234 Germany Aerospace Engineering Department University of Bristol University Walk BristolBS8 1TR United Kingdom

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

The paper presents the control design approaches for the European research project FLEXOP. The ultimate goal is to develop and apply active flutter suppression and load alleviation techniques on an unmanned flying aircraft demonstrator. Due to the flexible wing of the aircraft new challenges rise for the control design: the traditional rigid body (baseline) control loops have to be augmented with flutter control laws. In our approach, the controllers are designed based on a dynamical model, which is briefly discussed first. Details of the baseline control design, as well as the two different flutter suppression algorithms are discussed in the paper. Hardware-in-the-Loop testing of the controllers are reported before the first test flights of the aircraft. © 2019, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： controllers

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Mathematical models of control processes and stability in problems of mechanics

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AIP Conference Proceedings 2022年第1期2425卷

作者： S. Kadry G. Alferov V. Korolev D. Shymanchuk 1Department of mathematics and computer science faculty of science Beirut Arab University P.O. Box 11-5020 Riad El Solh Beirut 1107 2809 Lebanon 2Faculty of Applied Mathematics and Control Processes Saint-Petersburg State University 199034 Saint-Petersburg Russia 198504 St. Petersburg Peterhof University Avenue 35

The development of scientific directions of mechanics as a result of research in analytical mechanics, space dynamics and applied mathematics is considered. The basic theorems of analytical dynamics were extended to mechanical systems of variable composition. The abstract concept of a point of variable mass is introduced in the form of a small area of space, endowed with mass, associated with the main body. The subject of consideration is a system of particles with constant masses, the composition of which varies. This allows one to take into account the change in mass and the internal movement of particles, leading to the creation of reactive forces.

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Konjac glucomannan (KGM) aerogel immobilized microalgae: A new way for marine oil spills remediation

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Marine Pollution Bulletin 2025年 218卷 118158页

作者： Wang, Xudong Du, Zhuorong Song, Zhao Liu, Mei He, Pengfei Feng, Lijuan Chen, Zhi Chen, Qingguo Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry Zhejiang Ocean University Zhoushan316022 China National & local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology Zhejiang Ocean University Zhoushan316022 China School of Marine Science & Technology Zhejiang Ocean University Zhoushan316022 China Zhejiang Marine Fisheries Research Institute Zhoushan316021 China Department of Building Civil and Environmental Engineering Faculty of Engineering & Computer Sciences Concordia University MontrealQCH3G1M8 Canada

This study investigated the oil pollution remediation ability of konjac glucomannan (KGM) aerogel immobilized Chlorella vulgaris LH-1 (C. vulgaris). The KGM aerogel exhibited a high porosity of 86.83 %, and with the change of crude oil concentration (1–10 g/L), the crude oil adsorption efficiency of KGM aerogel was up to 18.75 %. The KGM aerogel carrier enhanced the crude oil biodegradation efficiency of C. vulgaris by 13.86 %. The concentration of residual n-alkanes of the immobilized C. vulgaris group was only 36.83 % of that of the free C. vulgaris group after 14 days of cultivation. In the crude oil metabolites of immobilized C. vulgaris, the concentrations of benzoic acid, phthalic acid, and benzophenone were 1.35, 21.18 and 3.43 times higher than those of the free C. vulgaris, respectively. Compared with free C. vulgaris group, 9 monooxygenase genes, 11 dioxygenase genes and 2 cytochrome P450 genes of immobilized C. vulgaris group were up-regulation and the "hydrocarbon metabolism process" was significantly enriched (enrichment factor is 0.85) in the gene ontology (GO) analysis of the transcriptome of C. vulgaris. These results showed that the ability of C. vulgaris to degrade crude oil was improved due to the existence of the KGM aerogel immobilized carrier. © 2025 Elsevier Ltd

关键词： Marine pollution

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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

arXiv

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arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

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