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2023 IEEE International Conference on Image Processing Challenges and Workshops, ICIPCW 2023

作者： Vrigkas, Michalis Nikou, Christophoros University of Western Macedonia Dept. Communication and Digital Media Kastoria52100 Greece University of Ioannina Dept. Computer Science and Engineering Ioannina45110 Greece

ISBN: (纸本)9798350302585

The work aims to design and implement a 3D interactive and addictive object avoidance game using the Unity platform. The implementation of the immersive virtual reality application uses any smart mobile device as an input and output device, utilizing its accelerometer and compass to record the orientation and rotation data of the device in 3D space and capture the digital environment stereoscopically on the device screen. A comparative study between a virtual reality and a desktop real-time 3D game is performed to analyze the various attributes of the game and determine which medium is most effective. © 2023 IEEE.

关键词： Virtual reality

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Platform-independent SCADA and IoT Architecture Based on Metadata

Platform-independent SCADA and IoT Architecture Based on Met...

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2022 IEEE International Multi-Conference on Engineering, computer and Information sciences, SIBIRCON 2022

作者： Romanov, Eugene L. Gervas, Nikolai A. Menzhulin, Sergey A. Novosibirsk State Technical University Dept. of Computer Science Novosibirsk Russia

ISBN: (纸本)9781665464802

The architecture of SCADA and IoT systems based on the use of Modbus equipment (things) interfaces description metadata, markup of a graphical user interface and mapping of GUI elements to equipment registers were considered in the article. Solutions have been proposed for describing the interfaces of multicomponent such as containers, arrays of descriptors of arbitrary nesting, templates, as well as their regular display on the GUI elements of their rendering. The article defined common solutions and services for SCADA and IoT such as virtualization of equipment interfaces, tools for collection, compression, storage and transmission of streaming data. A scripting language for technological programming was proposed for server and client components. The article also described an example of developing a two-level SCADA for an electric energy storage system. A variant of using the UDP/CoAP/DTLS/IoT-Gateway/Modbus protocol stack was proposed to extend the basic Modbus protocol with the means of identifying and authorizing devices/things, transmitting asynchronous equipment events and ensuring connection security. © 2022 IEEE.

关键词： Metadata

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Application of Virtual Reality (VR) to Advance Social Ability in Children with ASD 2

Application of Virtual Reality (VR) to Advance Social Abilit...

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Krishna, Athul P.V. Satheesh, Abhinav Abhishek, N.M. Menon, Hema P. Devasia, Davidson Dept. of Computer Science and Engineering Sreepathy Institute of Management and Technology Vavannor Kerala Palakkad India Dept. of Neurology Aster Medcity Kerala Kochi India

ISBN: (纸本)9798350340235

Virtual Reality (VR) technology provides a novel approach for therapy, offering controlled exposure to sensory stimuli, personalized learning experiences, and social skills practice in a safe and engaging virtual environment. The use of VR has the potential to improve social and cognitive skills, reduce anxiety, and increase engagement, ultimately enhancing the quality of life for children with Autism Spectrum Disorder (ASD) and their families, while also reducing the stigma associated with autism and fostering ongoing research and innovation in the field. © 2023 IEEE.

关键词： Autism Spectrum Disorder (ASD) Social Ability Training Virtual Environment Virtual Reality (VR) VR Training Kit

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Empirical evaluation of LLMs in predicting fixes of Configuration bugs in Smart Home System

arXiv

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arXiv 2025年

作者： Monisha, Sheikh Moonwara Anjum Bharadwaj, Atul Dept. Of Computer Science BlacksburgVA United States

This empirical study evaluates the effectiveness of Large Language Models (LLMs) in predicting fixes for configuration bugs in smart home systems. The research analyzes three prominent LLMs - GPT-4, GPT-4o (GPT-4 Turbo), and Claude 3.5 Sonnet - using four distinct prompt designs to assess their ability to identify appropriate fix strategies and generate correct solutions. The study utilized a dataset of 129 debugging issues from the Home Assistant Community, focusing on 21 randomly selected cases for in-dept. analysis. Results demonstrate that GPT-4 and Claude 3.5 Sonnet achieved 80% accuracy in strategy prediction when provided with both bug descriptions and original scripts. GPT-4 exhibited consistent performance across different prompt types, while GPT-4o showed advantages in speed and cost-effectiveness despite slightly lower accuracy. The findings reveal that prompt design significantly impacts model performance, with comprehensive prompts containing both description and original script yielding the best results. This research provides valuable insights for improving automated bug fixing in smart home system configurations and demonstrates the potential of LLMs in addressing configuration-related challenges. © 2025, CC0.

关键词： Smart homes

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An empirical study of PMU data based power system event detection techniques 5

An empirical study of PMU data based power system event dete...

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5th International Conference on Power, Control and Embedded Systems, ICPCES 2023

作者： Shaikh, Saba Kausar M Manjunath, K. Iitram Ahmedabad Dept. of Ecse India Aissms Ioit Dept. of Ee Pune India Iitram Ahmedabad Electrical and Computer Science Engineering Ahmedabad India

ISBN: (纸本)9798350310252

The interconnected power system as well as small-scale power system such as microgrids are exposed to numerous unexpected events, such as tripping, capacitor switching, and faults. Hence the detection of power system events obtains the significant role in system restoration, power control, and reliable operation. The study reported in this submission provides the brief description of the event detection techniques which are implemented using phasor measurement unit (PMU) data. The overview of the reported literature within the sight of the authors is lucidly presented with some key insights. The details of data utilized, performance metrics, simulation tool, and the methodology employed are provided so as to give the outline and possible features of the reported work. © 2023 IEEE.

关键词： Phasor measurement units

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Demonstration of Effectiveness of Nativeness in Stepwise Learning by Performing Sentiment Analysis

Demonstration of Effectiveness of Nativeness in Stepwise Lea...

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2023 International Conference on Next-Generation Computing, IoT and Machine Learning, NCIM 2023

作者： Al-Mahmud Shimada, Kazutaka Kyushu Institute of Technology Dept. of Computer Science and Systems Engineering 680-4 Kawazu Iizuka 850-8502 Japan

ISBN: (纸本)9798350316001

Nowadays, more people and entities express opinions on online platforms. With this increasing trend of online opinion mass information, it is impossible to analyze them manually. For this reason, an automatic approach to opinion and sentiment analysis is essential and useful in the real world. Several approaches based on machine learning techniques in sentiment analysis have been proposed. However, machine learning essentially needs massive data to generate a robust model. On the other hand, collecting the training data is costly, especially in low-resource language. To solve this problem, we introduce stepwise learning. Stepwise learning is a technique that improves the model capacity for a target task (i.e., main task) by exploiting auxiliary information from source tasks. It is effective when the data in the target tasks are inadequate. The target task of this paper is sentiment analysis for reviews in the Bangla language. Our proposed method consists of two stages: source and target tasks. For the source task, we train a transformers-based model, such as BanglaBERT, by a large dataset translated into the Bangla language;the original dataset is written in English. For the target task, we retrain and evaluate the model with a relatively small target dataset. We further investigate the effect of opinion expression style of writers between source and target data in stepwise learning. We call it 'nativeness.' The experimental result shows that nativeness has an important role in improving performance. © 2023 IEEE.

关键词： Sentiment analysis

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Household Energy Consumption Prediction: A Deep Neuroevolution Approach 23

Household Energy Consumption Prediction: A Deep Neuroevoluti...

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3rd International Conference on Artificial Intelligence, Automation and Algorithms, AI2A 2023

作者： Soudaei, Alexander Zhang, Jianhua Elmi, Mohamed Tsechoev, Mikael Khan, Zishan Osman, Ahmed Dept. of Computer Science Oslo Metropolitan University Oslo Norway Dept. of Mechanical Electronic and Chemical Eng. Oslo Metropolitan University Oslo Norway

ISBN: (纸本)9798400707605

Accurate energy consumption prediction can provide insights to make better informed decisions on energy purchase and generation. It also can prevent overloading and make it possible to store energy more efficiently. In this work, we propose a new deep learning model to predict the household energy consumption. In the new model, we employ differential evolution (DE) algorithm to automatically determine the optimal architecture of the deep neural network. The energy prediction results are presented and analyzed to show the effectiveness of the deep neuroevolution model constructed. © 2023 Owner/Author.

关键词： Evolutionary algorithms

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Location Independent Gesture Recognition Using Channel State Information 19

Location Independent Gesture Recognition Using Channel State...

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19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Elujide, Israel Feng, Chunhai Shiran, Aref Li, Jian Liu, Yonghe University of Texas at Arlington Dept. of Computer Science and Engineering United States

ISBN: (纸本)9781665431620

Gesture recognition has been the subject of intensive research in recent years owing to its wide applications. Unlike traditional systems, which usually require wearable sensors, many recent works have achieved the desirable gesture recognition performance using wireless channel state information from commercially available WiFi devices. However, existing works generally require training new models for different locations due to the location-dependent nature of channel state information. This paper proposes a location-independent system that can recognize gestures performed in a new location without training a new model. Our approach uses disentanglement that extricates location and other extraneous information from those needed for gesture recognition. The implementation is based on an unsupervised invariance induction framework consisting of feature extraction, a multi-output latent space, gesture recognition, and decoder modules. The key idea in designing this system is to separate gesture-dependent features from location-dependent features. Specifically, the feature extraction module consisting of a long short-term memory network is employed to select representative features;it essentially serves as an encoder to generate the latent space. During the training process, the network learns to cluster features representation for the gesture recognition and decoder by minimizing the total loss of the gesture recognition and decoder modules. We test our system with a dataset collected from various subjects performing four different gestures in multiple locations in seven rooms with different layouts. The results show that our location-independent gesture recognition system can achieve 88.69% accuracy for new locations. © 2022 IEEE.

关键词： Location

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Multiplicative Partially Homomorphic CRT Secret Sharing : (Preliminary Version) 21

Multiplicative Partially Homomorphic CRT Secret Sharing : (P...

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21st IEEE International Symposium on Network Computing and Applications, NCA 2022

作者： Dolev, Shlomi Kleinman, Yaniv Ben-Gurion University of the Negev Dept. of Computer Science Beersheba Israel

ISBN: (纸本)9798350397307

A new CRT-based positive (non-zero) secret-sharing scheme with perfect information-theoretic (PIT) security and multiplicative homomorphism is presented. The scheme is designed to support the evaluation of multiplications of non-zero secrets of multiplicative groups. Our CRT-based scheme is partially homomorphic, supporting homomorphic multiplications. Nevertheless, it has the potential to be regarded as fully homomorphic for practical scenarios, such as bounded-sized multi-cloud databases. © 2022 IEEE.

关键词： Information theory

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A Review on GAN based Image Dehazing 6

A Review on GAN based Image Dehazing

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6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Singh, Kavinder Khare, Vishruth Agarwal, Vishwas Sourabh, Sourabh Delhi Technological University Dept. of Computer Science New Delhi India

ISBN: (纸本)9781665410359

The improvement of deep learning facilitated the evolution of computer vision methods. Image dehazing is one of the challenging tasks in computer vision. Haze is a very common phenomenon arising due to bad weather, poor lighting, pollution, etc. Haze poses the problem of poor visibility in images under extreme circumstances. Several deep learning-based methods have been used to overcome haze-oriented problems. Generative networks (GANs) focus on the distribution of the normal images to remove the haze from a hazy image. The methods enhance the performance of computer vision under hazy conditions. This paper focuses on discussing a few important techniques, specially GANs, to solve the problem of dehazing. Various techniques have been qualitatively analyzed and the merits and demerits of the respective models have been discussed. Finally, some light is thrown upon the real-world applications and significance of dehazing. © 2022 IEEE.

关键词： Generative adversarial networks

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