检索结果-内蒙古大学图书馆

UPB Scientific Bulletin, Series C: Electrical engineering and Computer science 2022年第4期84卷 3-8页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

来源：评论

学校读者我要写书评

暂无评论

Exploring Concurrent Multi-materials and Multiscale Hybrid Topology Optimization for Lightweight Porous Gripping Mechanism 1

引用

International Conference on Steel and Composite for engineering Structures, ICSCES 2023

作者： Al Ali, Musaddiq Benaissa, Brahim Khatir, Samir Shimoda, Masatoshi Kobayashi, Masakazu Vignon, Paul Al-Shawk, Ameer Lay, Béatrice Department of Advanced Science and Technology Toyota Technological Institute 2-12-1 Hisakata Tenpaku-ku Aichi Nagoya468-8511 Japan Design Engineering Lab Department of Mechanical Systems Engineering Toyota Technological Institute 2-12-1 Hisakata Tenpaku-ku Aichi Nagoya468-8511 Japan Soete Laboratory Faculty of Engineering and Architecture Ghent University Wechnologiepark Zwijnaarde 903 Zwijnaarde9052 Belgium Mécanique et Ingénierie des Transports Institut Supérieur de l’Automobile et des Transports 49 Rue Mademoiselle Bourgeois Nevers58027 France Stellantis North America Headquarters Auburn HillsMI48326 United States

ISBN: (数字)9783031572241

ISBN: (纸本)9783031572234

Our research focuses on optimizing soft robotic gripper designs by employing an innovative hybrid topology approach with the aim of creating lightweight and porous grippers. Addressing the complex challenge of multiscale, multilateral topology optimization, we use a hybrid technique that combines SIMP (Solid Isotropic Material with Penalization) for macroscale optimization and MSB (Metaheuristic Structural Binary Distribution) for microscale optimization. At the microscale, our efforts are directed towards enhancing Young's modulus for weight reduction, considering orthotropic materials. Numerical examples in our study illustrate the adaptability of the microscale design to spatial configurations within both macro and microstructures. Various scenarios in macrostructure design demonstrate an advanced approach to strain energy distribution at the macroscale. Our innovative hybrid approach, integrating SIMP as for the macro-scale and MSB for micro-scale design, enables optimal designs while significantly reducing computational costs. This design methodology has the potential to yield novel, durable, lightweight, and porous soft robotic grippers with exceptional elastic flexibility. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Grippers

来源：评论

学校读者我要写书评

暂无评论

Awakened at CheckThat! 2022: Fake News Detection using BiLSTM and Sentence Transformer

Awakened at CheckThat! 2022: Fake News Detection using BiLST...

引用

2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Truică, Ciprian-Octavian Apostol, Elena-Simona Paschke, Adrian Department of Information Technology Uppsala University Lägerhyddsvägen 1 Uppsala75105 Sweden Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Splaiul Independentei 313 Bucharest060042 Romania Fraunhofer Institute for Open Communication Systems Berlin10589 Germany

In recent years, online social networks and online news venues have become some of the main news and event-related information spreading mediums. Although using these mediums has facilitated the speed of accessing information, it also created a new phenomenon used for propaganda and disinformation: fake news. As fake news has detrimental consequences to society, new technologies need to be developed in order to stop their harmful effects. In this paper, we propose two Bidirectional Long Short-Term Memory (BiLSTM) architectures with sentence transformers to solve two tasks: (1) a multi-class mono-lingual fake news detection task (i.e., mono-lingual task);and (2) a multi-class cross-lingual fake news detection task (i.e., cross-lingual task). For the mono-lingual task, we train and test a BiLSTM with BART sentence transformers model on an English dataset and obtain an accuracy of ∼ 0.53 and an F1-Score of ∼ 0.32. For the cross-lingual task, we train a BiLSTM with XLM sentence transformers model on an English dataset and test the model using transfer learning on a German dataset. For this task, we obtain an accuracy of ∼ 0.28 and an F1-Score of ∼ 0.19. © 2022 Copyright for this paper by its authors.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

Novel Gqds and Supra-Gqds Assemblies for High Strength, Flexible, and Conductive Cement Composites

SSRN

引用

SSRN 2023年

作者： Win, Thwe Thwe Prasittisopin, Lapyote Nganglumpoon, Rungkiat Pinthong, Piriya Watmanee, Suthasinee Tolek, Weerachon Panpranot, Joongjai Architectural Technology Research Unit Department of Architecture Faculty of Architecture Chulalongkorn University Bangkok10330 Thailand Advanced Railway Infrastructure Innovation and Systems Engineering Research Unit Department of Civil Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Centre of Excellence on Catalysis and Catalytic Reaction Engineering Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand CrystalLyte Co. Ltd. Research Unit 904 Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Graphene Electronics Research Unit Faculty of Science Chulalongkorn University Bangkok10330 Thailand

There has been significant interest in developing novel graphene quantum materials called graphene quantum dots (GQDs) in ultrafine scales. None has been explored in cement materials. This work presents the effects of these two synthesized graphene derivatives (Qds and BC) on the flow, bulk density, permeable void, water absorption, compressive strength, flexural strength, sulphate attack, electrical and thermal conductivity, and microstructures of cement composites, compared with commercial graphene oxide (GO) and plain mix. The findings show that the composites containing GQDs have excellent fresh, physical, mechanical, and sulphate attack properties. The 1.2% BC composites has the highest compressive and flexural strengths, with 50% and 108% higher than the control, respectively. Moreover, their electrical and thermal conductivity properties increased significantly that can be used as the conductive composites. The microstructural bridging mechanism regarding the seeding nucleation and crystal growth of C-S-H phase were seen and acted as nano-reinforcement. This study offers novel insights into the role of using GQDs in cement composites such that the materials can be implemented not only as strong and flexible concretes, but also as high conductive concretes, which can be future of functional resilient materials. © 2023, The Authors. All rights reserved.

关键词： Microstructure

来源：评论

学校读者我要写书评

暂无评论

Securing Smart Grids: Deep Reinforcement Learning Approach for Detecting Cyber-Attacks

Securing Smart Grids: Deep Reinforcement Learning Approach f...

引用

International Conference on Smart Communications and Networking (SmartNets)

作者： Ahmed T. El-Toukhy Islam Elgarhy Mahmoud M. Badr Mohamed Mahmoud Mostafa M. Fouda Mohamed I. Ibrahem Fathi Amsaad Department of Electrical and Computer Engineering Tennessee Tech. University Cookeville TN USA Department of Electrical Engineering Faculty of Engineering Al-Azhar University Cairo Egypt Department of Computer Systems Faculty of Computer and Information Sciences Ain Shams University Egypt Department of Network and Computer Security: Cybersecurity SUNY Polytechnic Institute Utica NY USA Department of Electrical Engineering Faculty of Engineering at Shoubra Benha University Cairo Egypt Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA School of Computer and Cyber Sciences Augusta University Augusta GA USA Department of Computer Science and Engineering Wright State University Dayton OH USA

ISBN: (数字)9798350385328

ISBN: (纸本)9798350385335

Smart meters (SMs) are deployed in smart power grids to monitor customer power consumption and facilitate energy management. However, fraudulent customers can compromise these SMs to manipulate power readings and engage in electricity theft cyber-attacks, resulting in reduced electricity bills. While various machine learning approaches have been employed for detecting such attacks, the potential of reinforcement learning (RL) remains unexplored. To bridge this gap, we propose a deep reinforcement learning (DRL) approach that leverages RL's adapt-ability to dynamic cyber-attacks and consumption patterns. This approach integrates exploration and exploitation mechanisms, enabling optimal decision-making. In this study, we present our approach in two scenarios. Firstly, we develop comprehensive detection models using deep Q networks (DQN) and double deep Q networks (DDQN) with various deep neural network architectures. Secondly, we address the challenges of defending against newly launched cyber-attacks. Extensive experimentation provides strong evidence of the effectiveness of our DRL approach in improving the detection of electricity theft cyber-attacks, as well as its capacity to efficiently adapt and defend against newly launched cyber-attacks.

关键词： Adaptation models Power demand Electricity Power system dynamics Detectors Deep reinforcement learning Smart meters

来源：评论

学校读者我要写书评

暂无评论

Chemo-Physical Mechanisms of High-Strength Cement Composites with Suprastructure of Graphene Quantum Dots

SSRN

引用

SSRN 2023年

Utilizing various forms of graphene derivatives for producing high-strength concrete is being assessed recently. Among these derivatives are superstructure of graphene quantum dots (GQDs), particularly in their assemblies of carbon dots, which is innovative in cement. This research investigates the impact of graphene derivatives known as supra-GQDs on the Chemo-physical mechanisms of cement composites, compared with the control mixture and GQDs solution. The results found that supra-GQDs exhibit enhanced mechanical characteristics. The supra-GQDs had higher 40 % compressive and 108 % flexural strengths than the control. Additionally, a microstructural bridging mechanism involving the seeding and crystal growth of the C-S-H phase, leading to refined pore structure and less nano-, meso-, and micro-pores in cement matrix. The measured total pore volume was 30% than the control. This investigation provides novel insight into the potential of utilizing supra-GQDs in cement, opening promising possibilities for high-performance concrete in the construction industry. © 2023, The Authors. All rights reserved.

关键词： Nanocrystals

来源：评论

学校读者我要写书评

暂无评论

Magnetic Bead Conjugated Lung Tumor Cell Binding Efficiency Assessment Based on Deep-Learning Approach

Magnetic Bead Conjugated Lung Tumor Cell Binding Efficiency ...

引用

Health science and Technology (ICHST), International Conference on

作者： Hoang Anh Phan Anh Nguyen Thi Nguyen Pham Dang Hien Vu-Dinh Bao Lam Dang Tung Thanh Bui Chun-Ping Jen Loc Do Quang Hai Hoang Nguyen Trinh Chu Duc Department of Micro-Electro-Mechanical Systems and Micro Systems VNU University of Engineering and Technology Vietnam Hanoi Vietnam Department of Mechanical Engineering and Advanced Institute of Manufacturing for High-Tech Innovations National Chung Cheng University Chia-Yi Taiwan Faculty of Mechatronics School of Mechanical Engineering Hanoi University of Science and Technology Vietnam Hanoi Vietnam Faculty of Physics VNU University of Science Hanoi Vietnam Vietnam National University Hanoi Hanoi Vietnam

ISBN: (数字)9798350315714

ISBN: (纸本)9798350315721

Accurate quantification and isolation of circulating tumor cells (CTCs) are critical for early cancer detection and treatment. Magnetic beads (MBs) have emerged as a promising non-invasive and effective method for capturing CTCs. The success of CTC capture primarily relies on the binding efficiency of MBs to these rare cells through antibody-antigen or aptamer-receptor interaction. This study proposed a deep learning-based approach to automatically evaluate the binding efficiency of the magnetic beads immobilization on lung cancer cells (A549 cell line). This investigation studied two different sizes of magnetic beads (4.5 µm and 3.0 µm) to understand their effect on the binding process between cells and beads. The methodology leverages a combination of object detection and semantic segmentation deep learning models to precisely detect the A549 cells in the acquired microscopic image data and calculate the area of MBs binding to each cell. The object detection model accurately classifies unbound cells, MBs-bound cells, and unbound MBs. Each MBs-bound cell image is then cropped and subjected to further analysis by the semantic segmentation model to delineate cell and binding MBs regions. Integrating these two deep learning models streamlines the evaluation process, reducing manual intervention and offering an automated and efficient solution for quantifying magnetic bead (MB) binding. This approach can potentially serve as a reliable signal readout mechanism in a biochip designed for CTC detection and analysis.

关键词： Deep learning Analytical models Magnetic resonance imaging Semantic segmentation Microscopy Biological system modeling Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Bayesian Optimization Framework for Efficient Fleet Design in Autonomous Multi-Robot Exploration

arXiv

引用

arXiv 2024年

作者： Concha, David Molina Li, Jiping Yin, Haoran Park, Kyeonghyeon Lee, Hyun-Rok Lee, Taesik Sirohi, Dhruv Lee, Chi-Guhn The Dynamic Optimization and Reinforcement Learning Laboratory The Department of Mechanical & Industrial Engineering University of Toronto TorontoONM5S3G8 Canada The Department of Electrical & Computer Engineering University of Toronto TorontoONM5S3G8 Canada The Division of Engineering Science The Faculty of Applied Science and Engineering University of Toronto TorontoONM5S3G8 Canada The Complex System Design Laboratory The Department of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of The Department of Industrial Engineering Inha University Incheon22212 Korea Republic of

This study addresses the challenge of fleet design optimization in the context of heterogeneous multi-robot fleets, aiming to obtain feasible designs that balance performance and costs. In the domain of autonomous multi-robot exploration, reinforcement learning agents play a central role, offering adaptability to complex terrains and facilitating collaboration among robots. However, modifying the fleet composition results in changes in the learned behavior, and training multi-robot systems using multi-agent reinforcement learning is expensive. Therefore, an exhaustive evaluation of each potential fleet design is infeasible. To tackle these hurdles, we introduce Bayesian Optimization for Fleet Design (BOFD), a framework leveraging multiobjective Bayesian Optimization to explore fleets on the Pareto front of performance and cost while accounting for uncertainty in the design space. Moreover, we establish a sub-linear bound for cumulative regret, supporting BOFD’s robustness and efficacy. Extensive benchmark experiments in synthetic and simulated environments demonstrate the superiority of our framework over state-of-the-art methods, achieving efficient fleet designs with minimal fleet evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Effectiveness of Clean Energy Technologies (Renewables and Nuclear) and External Support for Climate Change Mitigation in Ghana

Evaluating the Effectiveness of Clean Energy Technologies (R...

引用

IEEE International Conference on Smart Energy Grid engineering (SEGE)

作者： Mark Amoah Nyasapoh Samuel Gyamfi Seth Kofi Debrah Hossam A. Gaber Nana Sarfo Agyemang Derkyi Department of Energy and Petroleum Engineering School of Energy University of Energy and Natural Resources (UENR) Sunyani Ghana Nuclear Power Institute Ghana Atomic Energy Commission Accra Department of Nuclear Engineering School of Nuclear and Allied Sciences University of Ghana – Legon Accra Ghana Smart Energy Systems Lab (SESL) and Advanced Plasma Engineering Lab (APEL) Faculty of Energy Systems and Nuclear Science and Faculty of Engineering and Applied Science Ontario Tech University Ontario Canada School of Engineering University of Energy and Natural Resources (UENR) Sunyani Ghana

The selection of appropriate electricity generation strategies is crucial in reducing greenhouse gas emissions and promoting a low-carbon economy. Assessing the effectiveness of clean energy technologies and external support in Ghana’s climate change mitigation is crucial for sustainable development. This study focuses on Ghana’s commitment to emission reduction goals outlined in the country’s Energy Transition Framework, Nationally Determined Contributions (NDC) and the Fourth National Communication (NC4) under the United Nations Framework Convention on Climate Change (UNFCCC). These goals recognize the significance of external assistance in achieving a conditional 30% reduction target, along with an unconditional 15% reduction strategy. By utilizing the IAEA MESSAGE model, a comprehensive quantitative analysis is conducted to assess the effectiveness of additional installed capacity of clean energy technologies, mainly renewables and nuclear energy, in mitigating climate change, considering the role of external support. The results highlight the need for a transition from fossil fuel-based sources to low-carbon alternatives such as renewables and nuclear energy to meet emission reduction targets and promote sustainable development. Also, despite the higher investment cost associated with the additional installed capacity, the mitigation measures deployed in the electricity system reduced CO2 emissions by 15% (4,142.2 kilotons). Furthermore, the study emphasizes the importance of additional clean energy capacity to meet the growing electricity demand, facilitated by external aid. The findings provide valuable insights into best practices and strategies for achieving sustainable development goals in Ghana and can inform policy decisions and support sustainable energy development in other developing countries.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Adaptive Future Frame Prediction with Ensemble Network 25th

Adaptive Future Frame Prediction with Ensemble Network

引用

25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Kim, Wonjik Tanaka, Masayuki Okutomi, Masatoshi Sasaki, Yoko Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Meguto-ku Tokyo152-8550 Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology Koto-ku Tokyo135-0064 Japan

ISBN: (纸本)9783030687861

Future frame prediction in videos is a challenging problem because videos include complicated movements and large appearance changes. Learning-based future frame prediction approaches have been proposed in kinds of literature. A common limitation of the existing learning-based approaches is a mismatch of training data and test data. In the future frame prediction task, we can obtain the ground truth data by just waiting for a few frames. It means we can update the prediction model online in the test phase. Then, we propose an adaptive update framework for the future frame prediction task. The proposed adaptive updating framework consists of a pre-trained prediction network, a continuous-updating prediction network, and a weight estimation network. We also show that our pre-trained prediction model achieves comparable performance to the existing state-of-the-art approaches. We demonstrate that our approach outperforms existing methods especially for dynamically changing scenes. © 2021, Springer Nature Switzerland AG.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：