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Empowering STEM Students with Digital Skills: A Training Approach at UCN Industrial Playground 14th

Empowering STEM Students with Digital Skills: A Training App...

引用

14th International Conference on Learning Factories (CLF)

作者： Lindgren, Kurt Gron, Helge Glinvad Christiansen, Lasse Univ Coll Northern Denmark Dept Technol Aalborg Denmark Aalborg Univ Dept Mat & Prod Aalborg Denmark

ISBN: (纸本)9783031653995;9783031654008

The nine pillars of Industry 4.0 reveal the need for digital skills in the future workforce. This paper comprehensively explains the UCN Industrial Playground generic and modular learning platform. The primary objective of this paper is to provide knowledge on how the learning environment motivates and empowers science, technology, engineering, and mathematics students to acquire digital skills for the optimization and automation of business processes. This also includes being able to make decisions that are supported by objective data. Central for the UCN Industrial Playground is producing and assembling 3D-printed cars and using four mobile applications dedicated to tracking and visualizing information flow, handling preventive maintenance, ware-house management, and equipment management. Collaborative robots and automated guided vehicles are also vital parts of the learning and training activities. This paper explains the didactic and pedagogical model and how digital skills are acquired through reflective, practice-based learning, hands-on training, and supervision. It relies on a case study exploring participants' acquisition of digital skills based on formative and summative evaluations of participant reactions and learning objectives. The results can help educational practitioners unfold the potential of a learning factory outside of higher education.

关键词： learning factory Industry 4.0 education reflective practice-based learning UCN Industrial Playground

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A Multi-expert Agent for Efficient Learning from Demonstrations 1

引用

18th International Conference on Intelligent Autonomous systems (IAS)

作者： Chen, Yiwen Zhang, Zedong Liu, Haofeng Tan, Jiayi Chew, Chee-Meng Ang, Marcelo H. Natl Univ Singapore Singapore Singapore

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

In recent years, a myriad of seminal works on intelligent agents have been proposed, thanks to the advances in machine learning. Nonetheless, limited training efficiency and lack of transfer ability have been impeding the applications in broader domains, especially for human-robot collaboration when fast learning and flexibility are a must. To surmount this problem, we refer to a multi-expert architecture that contains pre-trained skills which can be transferred and reused easily. Meanwhile, a controller is employed to govern the learnt skills by unfolding them in a flexible sequence based on task specific preferences. This sequence is automatically interpreted from human demonstrations, minimizing the need for explicit procedural knowledge. To improve learning efficiency, we introduce reward augmented imitation learning and observation minimization techniques. Experimental results demonstrate that our algorithm is able to robustly pick up a multi-stage skill from only a few demonstrations, thus showcasing its capability for fast learning from human experts.

关键词： Reinforcement learning Multi-expert learning Imitation learning

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Study on the Use of Series Capacitors for Reducing Generation Constraints on the East Coast of Korea 9th

Study on the Use of Series Capacitors for Reducing Generatio...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Han, Sangwook Gachon Univ Gyeonggi Do 13120 Seongnam Si South Korea

ISBN: (纸本)9789819732982;9789819732999

In Korea's power system, a distinctive challenge arises due to the substantial distances between areas of power generation and consumption. This geographic separation demands extensive power transmission capabilities. However, the development of necessary transmission lines has been significantly delayed, sometimes exceeding a decade. In response to these challenges, a substantial number of FACTS units have been deployed to enhance system stability and transmission efficiency. Despite these efforts, in cases of failure in high-capacity 765 kV transmission lines, the resultant transient stability issues often necessitate the curtailment of generator output, leading to generation constraints. These constraints imply financial losses for the power system operator, making their reduction a critical objective. This paper specifically investigates the potential of series capacitors as a solution to mitigate these issues. By integrating series capacitors into the power grid, the study examines their effectiveness in overcoming transient stability challenges and thereby reducing the need for generation constraints. This approach represents a strategic effort to enhance the reliability and efficiency of Korea's power transmission system under complex operational scenarios.

关键词： Generation constraint Series capacitor South Korea Transient stability

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Constrained Pareto-Based Weighted-Sum ABC Algorithm for Efficient Sensor networks Deployment 7th

Constrained Pareto-Based Weighted-Sum ABC Algorithm for Effi...

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7th International Conference on Green Technology and Sustainable Development

作者： Son Tran Huy Nhat Minh Vu Thanh Tung Pham Duc Chinh Hoang Hanoi Univ Sci & Technol Sch Elect & Elect Engn Hanoi Vietnam Univ Fire Prevent & Fighting Hanoi Vietnam

ISBN: (纸本)9783031762314;9783031762321

Wireless Sensor Network performance relies heavily on the effectiveness of the deployment strategy, particularly in building applications. However, the inherent conflicting nature among the optimization objectives poses a significant challenge to achieving a balanced solution. This paper addresses this issue by introducing a constrained Pareto-based deployment algorithm, combining the Artificial Bee Colony and the linear weighted-sum approach. The method is validated through simulations, showcasing the efficacy of theoretical research. The main contribution is the utilization of the bee algorithm to deal with the intrinsic nature of the sensor network. Moreover, a comprehensive procedure integrating the algorithm and the weighting decision-maker is presented to showcase practical application. Nevertheless, the model scope is limited in terms of coverage and energy perspective.

关键词： First Keyword Second Keyword Third Keyword

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Image Classification Method Considering Overlapping and Correlation Between Probability Density Functions of Features

Image Classification Method Considering Overlapping and Corr...

引用

Intelligent systems Conference

作者： Arai, Kohei Saga Univ Saga 8408502 Japan

ISBN: (纸本)9783031663284;9783031663291

Image classification method considering overlapping and correlation between Probability Density Function: PDFs of features in the feature space in concern is proposed. As an example of the proposed method, sea ice type classification is demonstrated. A sea ice classification method based on eigen value decomposition with polarimetric SAR image data is proposed. Polarimetric SAR allows using surface and volume scattering characteristics of the targets such as odd/even/diffuse scattering, sphere/di-plane/helix scattering and so on. Based on such these eigen value decomposition, sea ice classification can be done with a variety of types of thin, rough and smooth surface sea ice. A comparative study among the proposed Maximum Likelihood based method with three components data of HH, VV and HV as well as odd/even/diffuse and sphere/di-plane/helix scattering components is conducted with PI-SAR of fully polarimetric SAR data of the Sea of Okhotsk area acquired on 23 Feb. 1999. It is found that the proposed method shows 1.3% improvement on percent correct classification compared to that of the existingmethod with three components and odd/even/diffuse scattering components.

关键词： Polarimetric SAR Scattering mechanism Image classification Odd/Even/Diffuse scattering Sphere/Di-plane/Helix scattering Sea ice classification

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Human Factors in Space Exploration: Opportunities for International and Interdisciplinary Collaboration 20th

Human Factors in Space Exploration: Opportunities for Intern...

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20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Kopec, Wieslaw Pochwatko, Grzegorz Kornacka, Monika Stawski, Wiktor Grzeszczuk, Maciej Skorupska, Kinga Karpowicz, Barbara Maslyk, Rafal Zinevych, Pavlo Knapinski, Stanislaw Barnes, Steven Biele, Cezary Polish Japanese Acad Informat Technol XR Ctr Warsaw Poland Polish Acad Sci Inst Psychol Warsaw Poland SWPS Univ Social Sci & Humanities Warsaw Poland Kobo Assoc Warsaw Poland Natl Informat Proc Inst Warsaw Poland

ISBN: (纸本)9783031665936;9783031665943

As humanity pushes the boundaries of space exploration, human factors research becomes more important. Human factors encompass a broad spectrum of psychological, physiological, and ergonomic factors that affect human performance, well-being, and safety in the unique and challenging space environment. This panel explores the multifaceted field of human factors in space exploration and highlights the opportunities that lie in fostering international and interdisciplinary cooperation. This exploration delves into the current state of research on human factors in space missions, addressing the physiological and psychological challenges astronauts face during long space flights. It emphasizes the importance of interdisciplinary collaboration, combining knowledge from fields such as psychology, medicine, engineering, and design to address the complex interaction of factors affecting human performance and adaptation to the space environment.

关键词： Space Exploration Human Factors Virtual Reality

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Integration of Distributed Intrusion Detection systems in IoT Infrastructure 9th

Integration of Distributed Intrusion Detection Systems in Io...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Bimenyimana, Christian Ildegard Nsabimana, Thierry Vlavonou, Ghislain Hounsou, Joel T. Niyonsaba, Gerard Univ Grands Lacs St Michel Bujumbura Burundi Univ Burundi Inst Stat Appl Nyamugerera Bujumbura Burundi Univ Abomey Calavi Inst Math & Sci Phys Dangbo Porto Novo Benin Ctr Porta Sion Ctr Rech Independant & Informatisat Syst Informat Bujumbura Burundi

ISBN: (纸本)9789819732883;9789819732890

Internet of Things (IoT) is an attractive innovation technology which utilized to interrelate all IoT devices worldwide with the help of the best high speed Internet. Nowadays, industries' data are being transferred over heterogeneous IoT devices (e.g., smart house, smart watch, sensors, and so forth) connected with each other via power Internet. Nevertheless, this emerging innovation technology is under risks due to the lack of safe security. IoT network requires strong security to detect malicious behavior accurately. Intrusion Detection System (IDS) is a smart tool/software used to monitor input/output network traffic and generate an alarm message whenever malicious activities occurred. In this study, we build a smart IDS based on machine learning (ML) approaches using data mining tool known as Knime and Anaconda-Python to classify intrusions in IoT network. The evaluation of the model is conducted based on two tools for efficiently predicting and classifying real-world network intrusions from Coburg Intrusion Detection Dataset (CIDDS-001) for better decision making.

关键词： CIDDS-001 Machine learning IoT IDS Knime

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Reduced-Order H∞ Loop-Shaping Controller Design for Nonlinear Continuous-Time HDD systems Using Hankel-Norm Approximation 13th

Reduced-Order H∞ Loop-Shaping Controller Design for Nonline...

引用

13th Computer Science Online Conference

作者： Shaikh, Ibrahim Zerdazi, El Wardi Wendimu, Abebe Alemu Matusu, Radek Zarghoon, Sohaibullah Emebu, Samuel Tomas Bata Univ Zlin Fac Appl Informat Dept Automat & Control Engn Nam TG Masaryka 5555 Zlin 76001 Czech Republic Slovak Univ Technol Bratislava Inst Automat Measurement & Appl Informat Fac Mech Engn Namestie Slobody 17 Bratislava 81231 1 Slovakia Lappeenranta Lahti Univ Technol LUT Dept Separat Sci Yliopistonkatu 34 Lappeenranta 53850 Finland

ISBN: (纸本)9783031702990;9783031703003

This paper presents the design and analysis of a reduced-order H-infinity loop-shaping controller for nonlinear continuous-time Hard Disk Drive (HDD) systems. Utilizing the Hankel-norm approximation, we systematically reduce the controller order, aiming to preserve system performance while enhancing computational efficiency. MATLAB simulations are employed to model the HDD system dynamics and to evaluate the controller's efficacy. Performance is quantitatively assessed using the Integral of Time multiplied by Absolute Error (ITAE) criterion. Results indicate that a 10th-order controller achieves a balanced tradeoff between robust control, disturbance and noise attenuation, without significant performance loss. This approach demonstrates the potential for reduced-order controllers in complex HDD systems, offering a pathway towards practical implementation in high-precision industrial applications.

关键词： Reduced-Order Controller H-infinity Loop-Shaping Hankel-Norm Approximation Nonlinear systems HDD Control MATLAB Simulation Disturbance Rejection Noise Attenuation ITAE Criterion

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Image Forgery Detection Using Machine Learning 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Janokar, Sagar Kulkarni, Tejas Kulkarni, Yash Kulkarni, Varad Kullarkar, Harshal Kumare, Rahul Kumawat, Jay Vishwakarma Inst Technol Pune 411037 Maharashtra India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

With the widespread availability of various powerful image editing softwares, the integrity of digital content has become increasingly vulnerable to manipulation and forgery. Image forgery is a concept where images are edited/modified and often mislead people to make assumptions. This is a pervasive issue in today's digital age, with the advancements in image editing tools making it increasingly difficult to detect manipulated images. To tackle this problem, a model has been developed to analyze and classify images as either authentic or forged by leveraging the power of deep learning algorithms. The model achieves an impressive accuracy of 93.39%, making it highly reliable for practical applications. The model has been developed by using algorithms such as Error Level Analysis (ELA) and Convolutional Neural networks (CNNs). The user has to enter the path of an image as the input and then the model employs its learnt features and patterns to evaluate the authenticity of the image provided. The research paper describes the methodology adopted for training the model, including the dataset used and the deep learning architecture employed.

关键词： CNN ELA Image forgery detection Machine learning

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ChatGPT: A Powerful Assistant, When Using Double-Loop Co-design

ChatGPT: A Powerful Assistant, When Using Double-Loop Co-des...

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Intelligent systems Conference

作者： Alm, Klas Hakan Forsgren, Olov Roos, John Magnus Univ Boras Boras Sweden Stockholm Univ Stockholm Sweden

ISBN: (纸本)9783031663284;9783031663291

Computers can now carry out tasks, by first learning from being given examples, rather than just doing exactly what they are told, this is often referred to as Machine Learning or AI. This has given almost endless possibilities what these machines can ultimately do. At the same time, it also gives us many threats and things to worry about from a safety, security and ethical point of view and voices are raised that we should control what AI is allowed to do by laws and regulations. By applying a Double loop Co-design approach to science this paper focusses on ChatGPT and researchers experience with effectiveness and ethics related to use o this tool. 3 workshops were conducted with totally 14 participants from 5 continents. Most of the respondents are positive and excited about what Chat GPT and AI can do for us, but they are also worried. The main concerns are that AI will do the creative and fun parts of our work and that it produces false facts. In conclusion, if applying a perspective conscious view of knowledge, AI can inspire human controlled creativity and informed decision making with multi-perspective views of reality.

关键词： ChatGPT OpenAI AI Machine learning Natural language Co-design Research ethics

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