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research on Distribution Grid Line Defect Identification and Classification Methods in UAV Inspection

Research on Distribution Grid Line Defect Identification and...

引用

2025 international conference on Electrical Automation and Artificial intelligence, ICEAAI 2025

作者： Liao, Bin Guo, Zipei Liao, Maotian Shen, Xiaonan Zou, Yu Qinzhou Power Supply Bureau of Guangxi Power Grid Co. Ltd Guangxi Qinzhou535000 China

ISBN: (纸本)9798331506797

With the development of the power system, the application of UAVs in distribution network inspection is becoming more and more widespread, therefore, this paper carries out research on the algorithms for distribution network line defects, solves the problems of fewer samples for acceptance of line engineering defects, poorer training effect, and lower model recognition accuracy, and researches a method for the identification and categorization of line defects in distribution networks. Firstly, through the sample data enhancement technique, the generalization ability of the model is improved, overfitting is reduced, and the robustness of the model to the input data is enhanced;secondly, the Generative Adversarial Network (GAN) is introduced to generate the antagonistic samples, which significantly reduces the amount of computational effort;finally, in combination with the Transformer architecture, an algorithm applicable to the recognition of line defects of power distribution grids is proposed, which improves the algorithm's performance in the complex scenario. The experimental results show that the method in this paper has significant improvement in the accuracy of defect recognition, computational efficiency and anti-interference ability, which provides a new technical solution for distribution network line defect detection. © 2025 ieee.

关键词： defect recognition distribution network line generative adversarial network unmanned aircraft inspection

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research on Information System Optimization Based on Data Mining Technology using Hamming Distance based Fuzzy C Means Clustering 1

Research on Information System Optimization Based on Data Mi...

引用

1st international conference on Intelligent Systems and computational networks, ICISCN 2025

作者： Zhang, Chi Shanghai International Travel Healthcare Center Shanghai Customs Port Clinic Shanghai China

ISBN: (纸本)9798331529246

An advancement of informatization as well as intelligence is the unpredictable inclination of safety production is various applications. The advancement of data mining becomes a vital part in encouraging the advancement of education safety management. However, the greater education management system according to the data mining advancement needs to be optimized to attain the maximum efficiency. Hence, this research proposes the Hamming Distance based Fuzzy C Means (HD-FCM) clustering approach for an optimization of information system in educational management. HD measures guide variations in feature attributes, designing the clustering outcomes simple to interpret for high authorities and educators. The feature extraction method named FastText is utilized for the extraction of important data from the collected input. The FastText extracts meaningful features that enhances the model effectiveness through understanding word context. The experimental results demonstrates that the proposed HD-FCM approach attains the better parallel efficiency of 91.5%, load balancing efficiency of 99.7%, acceleration ratio of 3.8, parallel time of 398.2s and total time of 1198.3s correspondingly as compared to existing Machine Leaning (ML) approach. © 2025 ieee.

关键词： data mining fasttext fuzzy c means clustering hamming distance information system optimization

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Exploring the Potential of MANETs: A Study on Raspberry Pi and UAV Integration 3

Exploring the Potential of MANETs: A Study on Raspberry Pi a...

引用

3rd international conference on Intelligent Data communication Technologies and Internet of Things, IDCIoT 2025

作者： Archana, B. Mahalakshmi, A. Revathi, K. Ashok Kumar, K. Hema, A.B. Dept. of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore India Dept. of Information Technology SNS College of Engineering Coimbatore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

This research investigates the feasibility of utilizing Mobile Ad Hoc networks (MANETs) in conjunction with Raspberry Pi-equipped Unmanned Aerial Vehicles (UAV) swarms. The primary objective is to overcome the limitations of traditional communication infrastructures in dynamic and decentralized environments. Specifically, we address the challenge of establishing reliable and efficient communication links within a swarm of UAVs engaged in various applications, including disaster response, military reconnaissance, and environmental monitoring. By integrating Raspberry Pi devices with UAVs, we aim to create a self-organizing communication network that enables seamless data transmission, coordinated swarm operations, and enhanced mission effectiveness. The research explores different synchronization strategies, including master-slave and decentralized approaches, to optimize swarm coordination. Furthermore, we investigate the potential of incorporating advanced technologies such as machine learning, computer vision, and swarm intelligence to further enhance the autonomy, adaptability, and overall performance of the UAV swarm. © 2025 ieee.

关键词： Mobile ad hoc networks

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Analyzing Sentiments in Twitter Data on Russia-Ukraine Conflict Using Machine Learning Methods 2

Analyzing Sentiments in Twitter Data on Russia-Ukraine Confl...

引用

2nd international conference on computational intelligence, communication Technology and Networking, CICTN 2025

作者： Chaudhry, Meeta Kumar, Rakesh Patel, Harvendra Kumar Prakash, Navin Ashish Mishra, D.K. Department of CSIT KIET Group of Institutions Ghaziabad India GNIOT Greater Noida India Noida International University India Department of CSE IIMT College of Engineering Greater Noida India Department of CSE RIMT Bareilly India Department of CSE ABES Ghaziabad India

ISBN: (纸本)9798331530389

As the conflict between Russia and Ukraine has deepened and more international countries have been engaged, it has become critical to ascertain if the universal message is one of support for or opposition to military activities. This goal is supported by research on how public opinion and foreign affairs are critically connected. As a result, researchers looked at how the global community felt about Russia's invasion of Ukraine. In total, 27,894 tweets with the hashtag #UkraineRussia that were published on the first day were examined. The findings indicate that some of the most often recurring words in the tweets were "war," "people," "world," and "people." Sadness was the most prominent emotion, and negative sentiments were higher than positive sentiments. It was discovered that nearly 89% of conflicts involved the word "world" when a term was supervised in context concordance analysis. This finding underlines the rising worry that the situation between Russia and Ukraine may worsen. © 2025 ieee.

关键词： Tweets

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Enhancing 6G-Satellite Network Integration with Artificial intelligence: A Future communication Paradigm 22

Enhancing 6G-Satellite Network Integration with Artificial I...

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22nd international Learning and Technology conference, L and T 2025

作者： Salah, Ibrahim Hussein, Aziza I. Wageh Lotfy, Mostafa Mabrook, Mohamed Mourad Almaaqal University College of Engineering Control and Computer Department Basrah61001 Iraq Effat University College of Engineering Energy and Technology Research Center Saudi Arabia Faculty of Technology and Education Beni-Suef University Dept. of Process Control Technology Beni-Suef Egypt Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt

ISBN: (纸本)9798331532215

The integration of 6G networks and satellite communications is set to revolutionize global connectivity, offering seamless coverage across terrestrial and non-terrestrial environments. Artificial intelligence (AI) is essential for improving this integration, addressing challenges such as dynamic resource management, latency reduction, and network optimization. AI techniques like machine learning, deep learning, and reinforcement learning offer innovative solutions to handle the complexities of 6G-satellite networks. These advancements promise to significantly improve network efficiency, enhance data transmission reliability, and ensure seamless connectivity across different areas. Potential use cases include smart cities, autonomous vehicles, and Internet of Things (IoT) applications, where AI-driven 6G-satellite integration will be crucial. The proposed AI-enhanced 6G-satellite framework not only addresses current challenges but also lays the groundwork for a resilient, scalable, and globally interconnected communication infrastructure, offering a promising future. © 2025 ieee.

关键词： Satellite communication systems

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Application of Visual communication in the Three-Dimensional Image Design of Interior Architecture 1

Application of Visual Communication in the Three-Dimensional...

引用

1st international conference on Intelligent Systems and computational networks, ICISCN 2025

作者： Liu, Danqiong Zhou, Shengke Sun, Qian Yuncheng Vocational and Technical University Yuncheng China

ISBN: (纸本)9798331529246

This study explores the application of visual communication design in interior architectural three-dimensional image design, aiming to solve the problems of unclear definition of indoor LoD, low modeling efficiency and insufficient integration of indoor space information in smart city construction. The research method is based on visual communication design, which enhances the expressiveness and user experience of interior design through the integration of visual elements such as graphics, color and typography. First, this study introduces the application of visual communication design in automated modeling, using visual recognition technology to automatically generate three-dimensional models from floor plans, which significantly improves modeling efficiency. Secondly, the application of visual communication design in indoor navigation and positioning services is studied to provide more intuitive navigation instructions through augmented reality technology, thereby improving the accuracy and user experience of indoor navigation. Experimental results show that the visual communication method performs well in LoD evaluation under different view conditions, with significant advantages over traditional methods in terms of geometric accuracy, texture quality, element integrity, and indoor LoD similarity. In addition, the application of visual communication improves the efficiency of indoor 3D image design and improves the integration of indoor space information. The evaluation of the rationality of element layout reaches 94.15%, providing a more effective indoor architectural 3D image design solution for smart city construction. plan. © 2025 ieee.

关键词： Visual communication

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Multi-Channel Sales Forecasting in a Kenyan Retail Environment 2

Multi-Channel Sales Forecasting in a Kenyan Retail Environme...

引用

2nd international conference on computational intelligence, communication Technology and Networking, CICTN 2025

作者： Avasthi, Sandhya Tripathi, Suman Lata Sanwal, Tanushree Dwivedi, Vimal Department of CSE ABES Engineering College Ghaziabad India School of EEE Lovely Professional University Jalandhar India Department of Management KIEt Group of Institutions Delhi-NCR Ghaziabad India Intelligent System Research Centre Ulster University Londonderry United Kingdom

ISBN: (纸本)9798331530389

The fast and continuous progress in technology is significantly impacting not only the dynamics of retail and e-commerce but also the innovations in sales forecasting. Identifying what could potentially be the most effective method available for predicting sales across online and offline sales channels in this rapidly growing market is becoming more and more crucial to business owners. This study on multi-channel retailing examines the performances of conventional time series forecasting models ARIMA/SARIMA and the more recent approaches like Facebook Prophet and RNN. For this purpose, Kenyan retail time series data of three years was utilized. Our findings highlight that among these methods, LSTM emerges as the top performer, demonstrating superior accuracy in capturing the complex characteristics of the sales data. It is also important to note that based on the results of the experiments, SARIMA still has potential especially in short-term predictions of time series with strong seasonality. © 2025 ieee.

关键词： Sales

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Bi-Linear Alternative Least Squares and Maximum Likelihood based MIMO communication System 1

Bi-Linear Alternative Least Squares and Maximum Likelihood b...

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1st international conference on Intelligent Systems and computational networks, ICISCN 2025

作者： Jasim, Laith Hussein Manjunatha, B.N. Godavarthi, Sahithi Thamizhkani, B. Sushama, C. The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Doddaballapur India Hyderabad India New Prince Shri Bhavani College of Engineering and Technology Department of Electrical and Electronics Engineering Chennai India Mohan Babu University Department of Computer Science and Engineering Tirupati India

ISBN: (纸本)9798331529246

In the recent years, the field of wireless communication networks have changed dramatically due to Multiple-Input Multiple-Output (MIMO) radar and communication system. MIMO system uses multiple antennas at both ends, transmitter and receiver. The deployment of huge MIMO technology shows enormous progresses in communication systems with extraordinary improvements in energy and spectral efficiencies. Even though, signal processing and channel estimation become challenging tasks in massive MIMO system. To overcome these challenges in this research proposed Orthogonal Matching Pursuit (OMP) with Bi-Linear Alternative Least Squares (BALS) method for channel estimation and Maximum Likelihood (ML) for signal detection. Initially, Channel State Information (CSI) is considered as input data. Then, channel estimation is performed through OMP with BALS and signal detection is performed using ML. From the results, the proposed BALS model attained better outcomes compared to existing OMP-based Linear Minimum Mean Square Error (LMMSE) in terms of Signal-to-Noise Ratio (SNR) by achieving -10 decibels (dB) correspondingly. © 2025 ieee.

关键词： Mean square error

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Lung and Colon Cancer Classification Using Convolutional Neural networks

Lung and Colon Cancer Classification Using Convolutional Neu...

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2025 ieee international conference on computational, communication and Information Technology, ICCCIT 2025

作者： Prasad, Ch. Rajendra Kumar, A. Sai Ananyaa, D. Gayathri Thanush, K. Anusha, S. Moola, Ramu SR University Dept. of ECE Warangal India Sumathi Reddy Institute of Technology for Women Dept. of ECE Warangal India

ISBN: (纸本)9798331512965

Lung cancer is a dangerous illness affecting humans. The kind and location of the cancer will mostly determine the course of medical therapy. Detecting cancer cells at the earliest possible stage has the potential to save a great number of irreplaceable human lives. Developing an automated method is crucial for early cancer detection. Despite various methods offered by scholars, prediction accuracy has always been a difficulty. To address this challenge, Convolutional Neural Network (CNN) - based Lung and Colon Cancer classification is presented in this paper. The dataset was gathered from Kaggle to train and test the network. The data is pre-processed to be suitable for the CNN model. The performance of the customized CNN model is evaluated in terms of accuracy, precision, recall, and f1-score, The proposed model is suitable for assisting doctors in classifying Lung and Colon Cancer. © 2025 ieee.

关键词： Lung cancer

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Deep Learning Techniques For Dental Caries Detection And Prosthodontics: A Systematic Review 2

Deep Learning Techniques For Dental Caries Detection And Pro...

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2nd international conference on computational intelligence, communication Technology and Networking, CICTN 2025

作者： Singh, Vinay Singh, Kuldeep Sehrawat, Ruchi Singh, Amit Prakash Augustine, Jeyaseelan Verma, Mahesh University School of Information Communication & Technology Guru Gobind Singh Indraprastha University Dwarka New Delhi India Oral Pathology and Forensic Odontology Maulana Azad Institute of Dental Sciences New Delhi India University School of Information Communication and Technology Guru Gobind Singh Indraprastha University Sector 16C Dwarka New Delhi India Guru Gobind Singh Indraprastha University Sector 16C Dwarka New Delhi India

ISBN: (纸本)9798331530389

Deep learning applications are increasing in dental caries detection and prosthodontics. However, the current growth and execution of deep learning in dental applications have not been evaluated and presented thoroughly. One of the major challenges to make the dental application more intelligent is to acquire knowledge and information from complex, multi dimensional and diverse structures. Current research has recorded a positive result in handling complex, heterogeneous, badly documented and mostly unstructured dental records. The classification still holds certain limitations even after the integration of many new novel deep learning modern applications to classify more robust and novel insight from the data for analysis. This structured review explores the burgeoning role of Deep Learning in dental caries classification and prosthodontics, focusing on its application in various aspects such as tooth shade selection, restoration design, and classifying facial changes in patients with removable prostheses. © 2025 ieee.

关键词： Dental prostheses

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