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23rd international conference on control Systems and Computer Science Technologies, CSCS 2021

作者： Oprea, Marin Mocanu, Mariana University Politehnica of Bucharest Calarasi Romania Faculty of Automatic Control and Computer Science Computer Department University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665439398

In a world in a continuous and rapid change, it is absolutely necessary for our students to keep up with the rapid progress of new technologies: Internet of Things (IoT), robotics, Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR) etc. The rapid evolution and diversification of these emerging technologies has recently led to their introduction into the educational offer of the school curriculum for the gymnasium. The discipline of Information and Communication Technology (ICT) has already been implemented, a discipline that involves both the formation of skills to use new technologies and the formation of computational thinking necessary for the efficient and intelligent use of these technologies. In order to teach and learn Physics from a STEM (Science, Technology, Engineering and Mathematics) educational perspective, we initiated optional school courses of IoT, robotics and AI (approached through Machine Learning). These courses stimulate, at the level of students, computational thinking, creativity and innovation and lead, from an interdisciplinary perspective, to the development of emerging specializations such as Mathematics-Physics-automation, Mathematics-Physics-Electronics, Mathematics-Physics-informatics-robotics etc. In this paper we presented a method of approaching, in the school educational space, the study of wireless communication technologies between smart devices, through an Educational robotics project. The project consisted of creating a wireless controlled mobile robotic platform (robot car) via a Bluetooth module connected to an Arduino Uno board. © 2021 IEEE.

关键词： Students

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Design of Digital Image Encryption Scheme with Cryptographic Analysis 3

Design of Digital Image Encryption Scheme with Cryptographic...

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3rd international conference on control Systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2021

作者： Kordov, Krasimir Zhelezov, Stanimir Nachev, Atanas Gueorguiev, Nikolay Pavlova, Daniela Konstantin Preslavsky University of Shumen Dept. of Computer Informatics Shumen Bulgaria University of Library Studies and Information Technologies Sofia Bulgaria Institute of Metal Science Equipment and Technology with Hydroaerodynamic Center Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (纸本)9781665439817

In this paper a new cryptographic algorithm, de-signed for digital image encryption is proposed. The encryption scheme is based on two chaotic maps, combined for constructing a pseudorandom generator. Using the chaotic behavior of the pseudorandom generator, permutation and substitution operations are performed for completing the encryption process. For proving the security of the cryptographic scheme, an extensive cryptographic analysis is performed including statistical tests for randomness, key-space analysis, key sensitivity, visual analysis, histogram analysis, correlation analysis, entropy analysis, number of pixels change rate and encryption/decryption key sensitivity analysis. The results from empirical experiments are presented in this paper. © 2021 IEEE.

关键词： Cryptography

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Advanced Government Chatbot Featuring Multi-Source Strategy for Effective Goal-Driven Dialogues

Advanced Government Chatbot Featuring Multi-Source Strategy ...

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automation, robotics and Computer Engineering (ICARCE), international conference on

作者： Zhixuan Lian Fang Wang Meiyin Huang Xiaoyu Wang Hangzhou International Innovation Institute Beihang University HangZhou China Institute of Reliability Engineering Beihang University Beijing China Department of Information Resources Management Business School Nankai University Tianjin China Department of Information Management Dongbei University of Finance & Economics Dalian Liaoning China

ISBN: (数字)9798331529505

ISBN: (纸本)9798331529512

Government chatbots (G-chatbots) aim to provide proactive, comprehensive information services, focusing on high-quality consultation rather than just answering queries. Due to the complexity of user questions, multiple dialogue turns are often needed for accurate responses. However, optimal answers in single turns may not align with the user's ultimate goal. To address this, we propose a Multi-Source-Aware algorithm designed for conversation-level objectives in G-chatbots. This algorithm features two key components: the Multi-Source-Aware (MSA) adapter module, which fine-tunes the chatbot's understanding based on user intent, conversation context, and preset knowledge, and the Virtual Edge module, which guides the conversation toward the final goal. Experiments show that this approach improves QA efficiency and answer quality, with fine-tuning using just 0. 01-13% of the parameters, resulting in a 2% increase in question comprehension and a 6% boost in answer quality compared to baseline models.

关键词： automation Accuracy Computational modeling Government Information services Focusing Oral communication Chatbots Complexity theory Robots

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Experimental and numerical study of rigid polyurethane foams for mechanical characteristics using finite element analysis 3

Experimental and numerical study of rigid polyurethane foams...

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3rd international conference on Intelligent robotics, Mechatronics and automation Systems, IRMAS 2023

作者： Jeyanthi, S. Nivedhitha, D.M. Jeyamani, Elammaran Lazar, Prince Jeya Lal Krishnaswamy, Prabhu School of Mechanical Engineering Vellore Institute of Technology Chennai Campus Tamil Nadu 600127 India Department of Mechanical Engineering Swinburne University of Technology Sarawak Malaysia Department of Mechanical Engineering Rajalakshmi Institute of Technology Tamil Nadu Chennai600124 India Department of Automotive Engineering Vellore Institute of Technology Tamil Nadu Vellore India

Over the past three decades, the global market has attracted polyurethane (PU) foams. It has been estimated that three-quarters of global consumption of polyurethane products are mainly foams. Based on hardness and density, foams can be classified into flexible and rigid. Features like flexibility, durability, stiffness, lightweight, less cost, and low density make foams more suitable for a wide range of automotive, industrial and agricultural industries. In this aspect, rigid foams are largely used as base materials for insulating purposes, seals, gaskets, tires, bedding, and seating of trucks. Generally, these PU foams are synthesized by mixing two chemicals: polyol and isocyanates. But unfortunately, the utilisation of Petro-based polyols makes PU foam restricted due to the rapid depletion of fossil fuels. Hence, this study attempts to replace Petro-based polyols with castor oil-based polyols. Other mechanical properties, such as compression strength, were tested to evaluate its ductile and flow behaviour. Finally, the developed Kelvin foam models were used for Finite Elemental Analysis (FEM) using ANSYS software to validate experimental results. Based on the results shows that both experimental and numerical analysis of castor oil PU foams resulted in greater compressive strength when compared to Petro-based PU foams. © Published under licence by IOP Publishing Ltd.

关键词： international trade

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From 2D to 3D Mixed Reality Human-Robot Interface in Hazardous Robotic Interventions with the Use of Redundant Mobile Manipulator 18

From 2D to 3D Mixed Reality Human-Robot Interface in Hazardo...

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18th international conference on informatics in control, automation and robotics (ICINCO)

作者： Szczurek, Krzysztof Adam Prades, Raul Marin Matheson, Eloise Perier, Hugo Buonocore, Luca Rosario Di Castro, Mario European Org Nucl Res Meyrin Switzerland Jaume I Univ Castellon Castellon De La Plana Spain

ISBN: (纸本)9789897585227

3D Mixed Reality (MR) Human-Robot Interfaces (HRI) show promise for robotic operators to complete tasks more quickly, safely and with less training. The objective of this study is to assess the use of 3D MR HRI environment in comparison with a standard 2D Graphical User Interface (GUI) in order to control a redundant mobile manipulator. The experimental data was taken during operation with a 9 DOF manipulator mounted in a robotized train, CERN Train Inspection Monorail (TIM), used for the Beam Loss Monitor robotic measurement task in a complex hazardous intervention scenario at CERN. The efficiency and workload of an operator were compared with the use of both types of interfaces with NASA TLX method. The usage of heart rate and Galvanic Skin Response parameters for operator condition and stress monitoring was tested. The results show that teleoperation with 3D MR HRI mitigates cognitive fatigue and stress by improving the operators understanding of both the robot's pose and the surrounding environment or scene.

关键词： Human-Robot Interface robotics Teleoperation Virtual Reality Mixed Reality Operator Workload Galvanic Skin Response

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Preface: The 3^rd international conference on automation, Mechatronics, and robotics (ICAMEROB 2021)

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AIP conference Proceedings 2022年第1期2502卷

作者： Nastaran, Reza Nazar Zadeh

Preface: The 3rd international conference on automation, Mechatronics, and robotics (ICAMEROB 2021), AIP conference Proceedings, Volume 2502, Issue 1, 26 Octobe

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Performance Analysis of Load Frequency control for Power Plants Using Different Optimization Techniques

Performance Analysis of Load Frequency Control for Power Pla...

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international conference on robotics,Electrical and Signal Processing Techniques (ICREST)

作者： Niloy Goswami Abu Hena Md. Shatil Electrical and Electronics Engineering Department American International University-Bangladesh(AIUB) Dhaka Bangladesh

In this paper, several optimization techniques including the Particle Swarm Optimization (PSO) technique, the Genetic Algorithm (GA), and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are applied to determine the most efficient output for load frequency control. These optimization techniques analyze the optimal level of system performance. The goal of this paper is to identify the most effective optimization technique for this sophisticated LFC system. In this research, three strategies (PSO, GA, ANFIS) are used in the LFC system to analyze frequency fluctuation and compare the load change rate. The model consists of the transfer function of the governor, turbine, rotating mass, and load. In this analysis, the ideal performance is examined across three separate case scenarios. The MATLAB/SIMULINK software simulates the performance analysis, which offers more realistic data and is generally preferred in this sort of optimization strategy work.

关键词： Fluctuations System performance Simulation Transfer functions Software Performance analysis Optimization

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A Deep Reinforcement Learning Approach for Navigation and control of Autonomous Underwater Vehicles in Complex Environments

A Deep Reinforcement Learning Approach for Navigation and Co...

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international conference on control, automation, robotics and Vision (ICARCV)

作者： Artemis Stefanidou Elena Politi Christos Chronis George Dimitrakopoulos Iraklis Varlamis Department of Informatics and Telematics Harokopio University Athens Greece

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

The comprehension of the underwater environment is recently being accelerated by technological advances in sensors, robotics and Artificial Intelligence (AI). At the forefront of this evolution, lies the Autonomous Underwater Vehicle (AUV), a sophisticated ocean exploration tool that is capable of performing underwater mapping, leveraging data obtained by onboard sensors. AUVs can navigate autonomously in unknown environments without any human interaction, while their level of autonomy is tightly linked to their path planning strategy. In this study, we perform a comparative analysis of a Deep Reinforcement Learning (DRL) method utilising two neural network models, a Linear Model (LM) that consists only of linear layers, and a Convolutional Model (CM) that consists of convolution layers for feature extraction that are merged with linear layers. Our evaluation focuses on assessing the performance of the proposed models for generating optimal paths in 3D underwater environments based on path length and obstacle avoidance. Through comprehensive simulations, we showcase the efficiency of our solution and present a comprehensive framework tailored for solving path planning problems in 3D complex underwater settings.

关键词： Analytical models Solid modeling Autonomous underwater vehicles Three-dimensional displays Navigation Deep reinforcement learning Robot sensing systems Path planning Artificial intelligence Intelligent sensors

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Automated Biofloc Technology for Fish Farming with GSM based Monitoring System

Automated Biofloc Technology for Fish Farming with GSM based...

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robotics, automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE international conference on

作者： Md Mehedi Hassain Muhammad Osman Gani Abdur Rahman S. M. Rahbar Abdullah Hasnat Dept. of Electrical & Electronics Engineering International Islamic University Chittagong Chittagong Bangladesh Dept. of Electrical & Electronics Engineering East Delta University Chittagong Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

Biofloc technology mitigates aquaculture’s environmental impact by using microbial flocs to convert organic waste into nutrient rich feed. To enhance water quality management, our research focuses on a GSM based monitoring system for real time data collection and analysis. The system integrates pH, temperature, and ultrasonic sensors with an Arduino Uno microcontroller, GSM module, servo, and pump motors to monitor and regulate water quality. The system measures timely and crucial data on water quality, including parameters such as temperature, pH levels, and the state of the feeding box. The pH and temperature sensors provide analog readings, while the ultrasonic sensor monitors feeding box levels. Food management is controlled by a servo motor that operates the feeding box, and a pump motor maintains water quality. The system uses temperature and pH sensors for rapid hazard detection, minimizing ammonia and nitrite buildup risks. The GSM module enables real time data connectivity, allowing users to track and control system operations remotely. This study empowers fish farmers and hobbyists with real-time water quality data, promoting informed decision-making to enhance aquatic health and productivity. It offers valuable insights to the broader aquaculture community.

关键词： Temperature sensors GSM Temperature measurement Water quality Fish Real-time systems Acoustics Sensors Servomotors Aquaculture

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Sea Scene Classification from Synthetic Aperture Radar Images Using A modified MobileNetV1 3

Sea Scene Classification from Synthetic Aperture Radar Image...

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3rd international conference on Signal Image Processing and Communication, ICSIPC 2023

作者： Wang, Zhongbo He, Miao Ding, Qinghai Luo, Haibo Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Space Star Technology Co Ltd. Beijing100086 China

ISBN: (纸本)9781510670945

Synthetic aperture radar (SAR) has a special ability to work in any type of inclement weather, and is a very suitable tool for Ocean surveillance. Scene classification is an essential pre-task of other computer vision tasks for ocean monitoring. It is of great importance to develop scene classification technology of SAR sea images. Due to the excellent feature representation abilities of neural networks, the deep learning-based methods are far superior to the traditional methods based on manual features in scene classification task performance. Many lightweight classification networks have been proposed to improve the inference speed of the networks. But in comparison with ordinary CNNs, the lightweight networks have slightly lower accuracy for scene classification tasks. So in this article, we proposed an improved lightweight Convolutional Neural Network for scene classification of SAR sea images. First, in order to meet the real-time performance, we choose MobileNetv1 as the original classification network in this paper. Then, to compensate for the lack of accuracy, we use 1D asymmetric convolution kernels to strengthen each layer of the depthwise convolutions in the network. Finally, after training time, we merge the linear calculations of each layer of the network to convert it into the original structure. The experimental results show that the modified model has obtained an accuracy improvement than the original one on the scene classification of sea SAR images without extra computation. © 2023 SPIE.

关键词： Synthetic aperture radar

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