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2025 ACM International Conference on Supporting Group Work, GROUP Companion 2025

作者： Berhane, Roda Akiode, Deo Adejoke Joshi, Swapna Elmimouni, Houda School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Field Robotics Lab Northeastern University BostonMA United States Department of Computer Science University of Manitoba WinnipegMB Canada Information Systems and New Media University of Siegen Siegen Germany

ISBN: (纸本)9798400711879

This study explores robotic telepresence in classrooms, from the perspectives of both the remote students (operators) and their in-person classmates. Analyzing a subset of field study data from 35 participants (22 operators, 13 classmates), we identified differing priorities: operators of the robot emphasize the need for improved functional aspects like camera control, while co-present classmates value social presence, interaction and identification, advocating for features like personalization and effective communication channels. These insights underline the need for telepresence robots that balance functional efficacy with social integration to provide a holistic educational experience. This work, though incomplete, enriches Group and CSCW literature on telepresence robots to facilitate collaborative interactions by highlighting the distinct needs of remote and in-person students, proposing design recommendations for telepresence robots that are technically proficient and socially responsive. © 2025 Copyright held by the owner/author(s).

关键词： Students

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Fisherman Location Store, Updating, and Alert System using Cloud AWS with Satellite

Fisherman Location Store, Updating, and Alert System using C...

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2024 IEEE International Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Kiruthiga Devi, M. Parthasarathy, R. Unnamalai, K. Perinba Athiban, S. Manikandan, K. Ramya, N. Dr. MGR Educational and Research Institute Chennai Department of Information Technology India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Adarsh College for Women Department of Computer Science Anna India VIT Artificial Intelligence and Robotics Chennai India Sona College of Technology Department of Biomedical Engineering Salem India Sri Sai Ram Engineering College Department of CSE Chennai India

ISBN: (纸本)9798331522988

he successful demonstration of their location tracking alert system for fishermen, Satellites will employ Amazon Web Services (AWS). Using cloud-based computing technology, the activities and whereabouts of fishermen are monitored in real time through this system. The ACS sat will send a vast amount of information in short always-shrinking cycle and store data very efficiently, only the location data for live updates on every moves by the fishermen. Here using this project we are stressing on the need to analyze data and push alerts according protocols, for timely raise alarm which definitely saves Fishermen life. The aim is to develop a Real Time Location Tracking and Monitoring GIS Application, which can trace the fishermen real-time location in marine activities. Analyze location information with the best edge of the sword such as cloud computing and AI /ML. The GIS App will have a simple user interface along with extensive monitoring abilities. Building a GIS App to aid marine safety by improving the tracking and monitoring of fishing operations using cloud technology. In the end, with these benchmarks in tow this could mark a step change and benchmark for maritime operations;as we finally get, safety and productivity combined. © 2024 IEEE.

关键词： Benchmarking

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A Research on Scattering Removal Technology Using Compact GPU Machine for Real-Time Visualization 23

A Research on Scattering Removal Technology Using Compact GP...

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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Ono, Seiya Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

In this paper, we propose a system that enables visualization under the situation of scattering media such as fog and smoke by Peplography which is scattering media removal system, on a small GPU machine. Compared to conventional haze removal techniques, peplography technology is capable of removing more dense scattering media and can handle cases where the density of fog varies in the image. On the other hand, the conventional peplography process is performed on a desktop PC, and no system has yet been developed to perform peplography in an outside environment. Thus, we have developed a peplography system using the Jetson AGX Xavier, a single-board computer equipped with a GPU, which is superior to conventional methods in terms of portability, execution speed, and power consumption. We also demonstrate the performance of this system by conducting experiments using this system under a simulated scattering media scene and evaluating the obtained results in terms of FPS and the image evaluation metric. © 2023 ICROS.

关键词： Graphics processing unit

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The Influence of Human Factors in Ensuring Cybersecurity in Organizations: Effectiveness of PDPA and GDPR Implementation 3

The Influence of Human Factors in Ensuring Cybersecurity in ...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Sharifi, Ahmad Zia Walid, Md. Abul Ala Momand, Mohammad Dawood Safi, Ihsan Ul Haq Safi, Hamidullah Khanzai Hossain, Sadia Nangarhar University Faculty of Computer Science Department of Networking and Communication Afghanistan Bangabandhu Sheikh Mujibur Rahman Digital University Department of Data Science and Engineering Gazipur Bangladesh Lautsprecher Teufel GMbH Berlin Germany Bangabandhu Sheikh Mujibur Rahman Digital University Department of Internet of Things and Robotics Engineering Gazipur Bangladesh

ISBN: (纸本)9798331518592

Modern organizations face rising levels of cyber risks, making cybersecurity a top priority for safeguarding sensitive data and maintaining operational continuity. Recent studies find human factors as the most critical contributors to cyber risks. These human-related risks include user misuse, user mistakes, and user malice. A large proportion of cyber risks arise when hackers use social engineering or phishing techniques to manipulate employees into disclosing confidential information. While some employees knowingly engage in these actions, some incidents occur accidentally due to a lack of awareness about cybersecurity protocols. As a result, governments around the world are enacting data protection legislation aimed at enhancing employees' cyber risk. This study explores the perception of US employees on the effectiveness of data protection legislation in countering cyber threats. It surveyed 30 randomly selected employees from various industries. The results showed that employees perceive data protection legislation as effective in mitigating employeerelated cyber risks. © 2024 IEEE.

关键词： Phishing

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Implementing SLAM for Robot Navigation with Lidar in ROS Platform 4

Implementing SLAM for Robot Navigation with Lidar in ROS Pla...

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4th IEEE International Conference on Emerging Frontiers in Electrical and Electronic Technologies, ICEFEET 2024

作者： Verma, Gaurav Kumar Ray, Ranjit Swar, Surya Narayan Meena, Gagan Deep Dept. of Electrical Engineering National Institute of Technology Patna India Underwater Robotics & Autonomous Group CSIR-Central Mechanical Engineering Research Institute Durgapur India Department of Computer Science & Engineering Gandhi Institute of Engineering and Technology University Gunupur India

ISBN: (纸本)9798331528614

This research covers the implementation of SLAM (Simultaneous Localization and Mapping) with Ouster OS0 LiDAR (Light Detection and Ranging) sensor in the Robot Operating System (ROS1) Noetic. Using the high-frequency capabilities of the ouster, this method works towards mapping and localization in structured and unstructured environments. The paper explains the Ouster sensor integration in the ROS1 Noetic environment, providing information on the sensor calibration, data acquisition, and pre-processing. The ROS ecosystem in Ubuntu 20.04 is set to process the data streams coming from the ouster LiDAR sensor which is further utilised to create map and localize the robot. The Ouster LiDAR sensor scans every object in its field of view (in 3D), the data is then used for the SLAM. SLAM is executed using the Direct Lidar Odometry (DLO) algorithm for mapping and simultaneously helping the robot with localization and enabling it to navigate through the environment smoothly and precisely. © 2024 IEEE.

关键词： SLAM robotics

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RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

arXiv

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arXiv 2024年

作者： Wang, Yufei Sun, Zhanyi Zhang, Jesse Xian, Zhou Bıyık, Erdem Held, David Erickson, Zackory Robotics Institute Carnegie Mellon University United States Department of Computer Science University of Southern California United States

Reward engineering has long been a challenge in Reinforcement Learning (RL) research, as it often requires extensive human effort and iterative processes of trial-and-error to design effective reward functions. In this paper, we propose RL-VLM-F, a method that automatically generates reward functions for agents to learn new tasks, using only a text description of the task goal and the agent’s visual observations, by leveraging feedbacks from vision language foundation models (VLMs). The key to our approach is to query these models to give preferences over pairs of the agent’s image observations based on the text description of the task goal, and then learn a reward function from the preference labels, rather than directly prompting these models to output a raw reward score, which can be noisy and inconsistent. We demonstrate that RL-VLM-F successfully produces effective rewards and policies across various domains — including classic control, as well as manipulation of rigid, articulated, and deformable objects — without the need for human supervision, outperforming prior methods that use large pretrained models for reward generation under the same assumptions. Videos can be found on our project website: https://***/. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems

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Evolutionary computation 2025年第1期33卷 115-140页

作者： Alvarez, Isidro M. Nguyen, Trung B. Browne, Will N. Zhang, Mengjie School of Engineering and Computer Science Victoria University of Wellington Kelburn 6140 Wellington New Zealand School of Engineering and Computer Science Victoria University of Wellington Kelburn 6140 Wellington New Zealand School of Electrical Engineering and Robotics Queensland University of Technology Brisbane 4001 Australia

Evolutionary Computation (EC) often throws away learned knowledge as it is reset for each new problem addressed. Conversely, humans can learn from small-scale problems, retain this knowledge (plus functionality), and then successfully reuse them in larger-scale and/or related problems. Linking solutions to problems has been achieved through layered learning, where an experimenter sets a series of simpler related problems to solve a more complex task. Recent works on Learning Classifier Systems (LCSs) has shown that knowledge reuse through the adoption of Code Fragments, GP-like tree-based programs, is plausible. However, random reuse is inefficient. Thus, the research question is how LCS can adopt a layered-learning framework, such that increasingly complex problems can be solved efficiently. An LCS (named XCSCF*) has been developed to include the required base axioms necessary for learning, refined methods for transfer learning and learning recast as a decomposition into a series of subordinate problems. These subordinate problems can be set as a curriculum by a teacher, but this does not mean that an agent can learn from it;especially if it only extracts over-fitted knowledge of each problem rather than the underlying scalable patterns and functions. Results show that from a conventional tabula rasa, with only a vague notion of which subordinate problems might be relevant, XCSCF* captures the general logic behind the tested domains and therefore can solve any n-bit Multiplexer, n-bit Carry-one, n-bit Majority-on, and n-bit Even-parity problems. This work demonstrates a step towards continual learning as learned knowledge is effectively reused in subsequent problems. © 2024 Massachusetts Institute of Technology.

关键词： code fragments layered learning. Learning classifier systems

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Global Solar Radiation Prediction using Empirical based Models 1

Global Solar Radiation Prediction using Empirical based Mode...

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1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

作者： Sivakumar, Mahima Priya, S. Jeba Subathra, M.S.P Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Karunya Institute of Technology and Sciences Department of Robotics Engineering Coimbatore India

ISBN: (纸本)9781665497107

Solar Radiation (SR) is crucial for the energy balance at the Earth's surface, evaporation, snow melting, plant water needs, and catchment hydrological regulation. In this regard, the major goal of this research is constructing a mathematical model or in other words empirical model to estimate the amount of SR upon a horizontal region in terms of latitude for four Indian cities. The cities considered for this work are NewDelhi, Chennai, Hyderabad and Coimbatore. Based on the input parameters, two categories of empirical models are developed namely, category 1 is sunshine duration (SD) based models and category 2 is air temperature (AT) based models. For performance evaluation, the metrics mean percentage error (MPE), mean bias error (MBE), mean absolute bias error (MABE), root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). The results signify that both the category of empirical models have a promising capability in this field of research and can hence be an efficient option for solar forecasting. © 2022 IEEE.

关键词： Solar energy

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A deep convolutional neural network for diabetic retinopathy detection via mining local and long-range dependence

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 153-166页

作者： Xiaoling Luo Wei Wang Yong Xu Zhihui Lai Xiaopeng Jin Bob Zhang David Zhang Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of TechnologyShenzhenChina Peng Cheng Laboratory ShenzhenChina Shenzhen Institute of Artificial Intelligence and Robotics for Society ShenzhenChina College of Big Data and Internet Shenzhen Technology UniversityShenzhenChina The Department of Computer and Information Science University of MacaoMacaoMacaoChina The Chinese University of Hong Kong(Shenzhen) ShenzhenChina

Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of *** present,deep convolutional neural networks have achieved promising performance in automatic DR detection *** convolution operation of methods is a local cross-correlation operation,whose receptive field de-termines the size of the local neighbourhood for ***,for retinal fundus photographs,there is not only the local information but also long-distance dependence between the lesion features(*** and exudates)scattered throughout the whole *** proposed method incorporates correlations between long-range patches into the deep learning framework to improve DR ***-wise re-lationships are used to enhance the local patch features since lesions of DR usually appear as *** Long-Range unit in the proposed network with a residual structure can be flexibly embedded into other trained *** experimental results demon-strate that the proposed approach can achieve higher accuracy than existing state-of-the-art models on Messidor and EyePACS datasets.

关键词： image classification medical image processing pattern recognition

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Analysis of Accurate Focal Points and Automatic Method of Digital Holographic Microscopy (DHM) for Obtaining an Accurate 3D Profile 23

Analysis of Accurate Focal Points and Automatic Method of Di...

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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Ono, Taishi Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

Currently, Digital Holographic Microscopy(DHM) is used for researching disease diagnosis or microbes. It cannot obtain the correct three-dimensional (3D) profile for a little noise because biological cells are microscopic. Then we need images of the focal point of DHM for reducing noise. However, in DHM, the depth of field becomes smaller influenced by the objective lens. In addition, focusing to obtain hologram images of biological cells in conventional DHM systems is entirely manual, because the decision of the focal point is made by the photographer's senses, which makes it even more difficult to focus on the object. These factors make it difficult for the conventional DHM system to acquire images of the focal points. Therefore, in this paper, we propose the analysis of accurate focusing points using a noise map. This eliminates the illusion or misperception that is a drawback of the manual. We improved an accurate 3D profile. 3D profiles were created at the focal point by the proposed method and at the positions before and after the focal points, and evaluated for SNR. From this, the proposed method can be used to analyze biological cells and microstructures. © 2023 ICROS.

关键词： Holograms

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