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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Kamkar, Spandana Anilkumar Sanjay, Srushti Vaishnavi, P.S. Karthik, S. Bnm Institute of Technology Affiliated to Vtu Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331515911

Oral health is vital to overall well-being but is often overlooked due to inefficient monitoring tools and delayed diagnosis. This project presents a smart handheld device featuring a miniaturized camera for detecting oral issues like plaque, cavities, teeth discoloration and gum diseases in real-time. Using image processing and deep learning algorithms, the device provides precise feedback and actionable insights. Paired with a mobile application offering detailed analysis and recommendations, it empowers users to adopt proactive oral hygiene practices to prevent teeth disorder. © 2025 IEEE.

关键词： Electronic health record

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Dynamic Charging on the Go: Optimizing Mobile Charging Stations for Electric Vehicle Infrastructure 11

Dynamic Charging on the Go: Optimizing Mobile Charging Stati...

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11th International Conference on Vehicle technology and Intelligent Transport Systems, VEHITS 2025

作者： Jain, Suhas Gupta, Arobinda Dept. of Computer Science & Engineering Indian Institute of Technology WB Kharagpur721302 India

ISBN: (纸本)9789897587450

With the growing adoption of electric vehicles (EVs) as an eco-friendly and sustainable means of transportation, availability of adequate EV charging infrastructure has become very important. While fixed charging stations are the primary means for public charging, they can be effectively augmented by mobile charging stations. In this paper, we address the problem of planning and operating a mobile charging station fleet by an operator. We propose an algorithm for the operator to use for route planning of the MCSs and for scheduling charging requests of EVs to them to try to maximize the number of charging requests served. Detailed simulation results are presented in different realistic scenarios to show that the proposed algorithm works well. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Electric vehicles

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Routing and Charge Planning Strategies for Ridesharing EV Fleets 11

Routing and Charge Planning Strategies for Ridesharing EV Fl...

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11th International Conference on Vehicle technology and Intelligent Transport Systems, VEHITS 2025

作者： Singh, Ashutosh Gupta, Arobinda Dept. of Computer Science & Engineering Indian Institute of Technology KharagpurWB-721302 India

ISBN: (纸本)9789897587450

Ridesharing systems have become an important part of urban transportation. At the same time, electric vehicle (EV) adoption is also growing at a fast pace as an eco-friendly and sustainable transportation option. To operate a ridesharing system with EV fleets, scheduling an EV fleet to serve passenger requests requires consideration of both the requests, and the available charge and potential future charge requirements of the EVs. In this paper, we address the problem of scheduling EVs by a ridesharing operator, and propose four algorithms that schedule passenger requests while taking into consideration charging requirements of the EVs. Detailed simulation results are presented on a real world data set to show that the algorithms perform well. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Urban transportation

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Smart ANPR: A Checkpoint-Based Toll and Parking Management System Using Hybrid OCR and Blockchain 3

Smart ANPR: A Checkpoint-Based Toll and Parking Management S...

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Samarth, M.N. Gopisetti, Sampriti Chaitra, M. Bnm Institute of Technology Affiliated to Vtu Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331515911

Automated Number Plate Recognition is one of the most important applications of computer vision, employed in the enforcement of traffic law, vehicular management, security, and even at toll collection. This paper proposed an advanced system for ANPR that can move away from the traditional booth and establish a checkpoint. The strategically located cameras with checkpointing will automatically capture the plates of passing vehicles, permitting road tax and parking fees to be deducted without making contact. A hybrid approach that combines the capabilities of OpenCV, Tesseract OCR, and deep-learningbased OCR models helps tackle such challenges as stable images from live video feeds and highly accurate text recognition. To this end, since the system integrates high-resolution frame stabilization using OpenCV to ensure crystal clear captures, it further employs the use of YOLOv8 to boost the precision of real-time detection. The blockchain technology is further implemented to ensure that transactions are tamper proof, therefore ensuring secure and transparent billing systems. This makes the ANPR solution deployable on edge devices, which opens real-time processing capabilities for high-speed and high-volume environments, thereby offering a scalable and efficient approach for intelligent transportation and smart city applications. © 2025 IEEE.

关键词： Blockchain

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Securing of Cloud Storage Data Using Hybrid AES-ECC Cryptographic Approach

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Journal of Mobile Multimedia 2023年第2期19卷 363-388页

作者： Kumar, Sunil Kumar, Dilip Dept. of Computer Science and Engineering National Institute of Technology Jamshedpur India

Internet has revolutionized the world in a way no one could have ever imagined. It paved the way for various different technologies, that have transformed the world exceptionally. Internet enabled cloud technology which provides cost-effective, scalable, on-demand computing resources with little to no downtime. Cloud storage allows its users to store and access private data from anywhere in the world without needing any high-end computing system. Cloud storage isn’t always secure, but that doesn’t imply it isn’t. The security of a data depends on the security policies followed by the provider along with the security of the communication channel via which the data is being sent. Encryption is used to obfuscate the data so that it can only be viewed when correct credentials, known as encryption keys, are provided. Following study proposes an encryption technique using ECC (Elliptic Curve Cryptography) along with AES (Advance Encryption Standard) to provide data confidentiality in an efficient way for securing data on cloud and hence, protect the personal information of user from any adversary. This new method is more effective, and the results are superior as a consequence. © 2022 River Publishers.

关键词： AES asymmetric encryption authentication blowfish cloud storage security ECC Symmetric encryption

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Improving Fake News Detection with a Mixture of Experts: Leveraging Sentiment Analysis and Sarcasm Detection as Core Expert Models 6

Improving Fake News Detection with a Mixture of Experts: Lev...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Gunasekara, Tharindu Thihan, Disira Kodithuwakku, Sansika Dissanayake, Dinuka Fernando, Harinda Vidhanaarachchi, Samitha Sindhujan, Archchana Sri Lanka Institute of Information Technology Malabe Dept. of Software Engineering Sri Lanka Sri Lanka Institute of Information Technology Malabe Dept. of Computer Computer Systems Engineering Sri Lanka University of Surrey Dept. of Computer Science and Electronic Engineering United Kingdom

ISBN: (纸本)9798331517878

Fake news continues to proliferate, posing an increasing threat to public discourse. The paper proposes a framework of a Mixture of Experts, Sentiment Analysis, and Sarcasm Detection experts for improved fake news detection. This approach captures the emotional cues in the text through a Sentiment Analysis expert, which is based on bidirectional encoder representations from Transformers (BERT) models with sentiment vectors generated using SentiWordNet and Integrated Gradients. It combines a sarcasm detection expert based on BERT, recognizing sarcasm and its type to help classify fake news. By fusing these experts through a Mixture of Experts gateway, subtle linguistic cues often found in fake news are more effectively analyzed, leading to improved accuracy in detecting misinformation. Experimental results are presented as 96% for the Sarcasm expert with the BERT base model and 83% for the Sentiment Analysis expert with the distilled version of the BERT (DistilBERT) base model, proving the effectiveness of the proposed approach in beating traditional methods. © 2024 IEEE.

关键词： fake news detection gateway mixture of experts sarcasm detection sentiment analysis

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A review on 3D image reconstruction on specific and generic objects

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Materials Today: Proceedings 2023年 80卷 2400-2405页

作者： Shalma, H. Selvaraj, P. Dept. of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Dept. of Information Technology SRM Institute of Science and Technology Kattankulathur Chennai India

With the emergence of various techniques involved in deep learning the researchers of computer vision tends to focus on the strategies such as object recognition and segmentation of image. This has inclined to accomplish the deep learning techniques in 3D reconstruction of both specific and generic objects. As the space for reconstruction of 3D images either in single or multi view has envisioned the researchers to concentrate on the available technologies used for reconstruction. With the available built in methods and technologies in deep learning, the performance of the proposed methods were reviewed and analyzed using several parameters. As the remaking of 2D images is still in the beginning stage, it is important to study the 3D shape representations, various network architecture, methodologies and approaches behind 3D reconstruction. In this work a review of deep learning methods for single or multiple RGB images of specific and generic object 3D reconstruction was done. Several methods and their importance were also discussed along with the challenges encountered and with further research directions. This paper critically analyzes the various 3D Shaped Representations, 3D Data Network Architectures, depth Estimation methods, Multi View Representations and the Data Representation Techniques. © 2021

关键词： Object recognition

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Cybersecurity Threat Detection Using Deep Learning and Anomaly Detection Techniques

Cybersecurity Threat Detection Using Deep Learning and Anoma...

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Rajendran, T. Mohamed Imtiaz, N. Jagadeesh, K. Sampathkumar, Balaji Rajalakshmi Institute of Technology Department of Computer Science and Engineering Chennai India Nagarjuna College of Engineering and Technology Dept. of Information Science and Engineering Bangalore India Sri Venkateswaraa College of Technology Dept. of Computer Science and Engineering Chennai India Akshaya College of Engineering and Technology Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350359688

Through the use of combined deep learning and anomaly detection approaches, this research investigates the area of cybersecurity threat detection. The study proves the framework's extraordinary success in recognizing as well as mitigating diverse cyber dangers, including insider threats and zero-day attacks, through practical testing and case studies. The framework establishes itself as a proactive cybersecurity solution adaptive to the changing threat landscape due to its high accuracy of 95%, low amount of false positives 5%, and quick reaction times. The recommendations cover user training, scalability, regulatory compliance, including cross-disciplinary collaboration. Behavioral analysis, AI explainability, IoT security, and countering quantum computing concerns should be the main areas of future research. These revelations help the cybersecurity industry become more resilient and well-prepared. In this research investigation, experiments on threat detection were conducted using deep learning algorithms, with a specific focus on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). The findings of the study reveal that a detection accuracy of 93% was achieved by CNN, while a higher accuracy of 96% in threat detection was exhibited by RNN. © 2024 IEEE.

关键词： Zero-day attack

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Increasing the RES Hosting Capacity of the Cyprus Distribution System

Increasing the RES Hosting Capacity of the Cyprus Distributi...

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CIRED 2024 Vienna Workshop

作者： Therapontos, Phivos Konstantinou, Rafail Charalambous, Charalambos A. Aristidou, Petros Electricity Authority of Cyprus Nicosia Cyprus University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Dept. of Electrical & Computer Engineering & Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9781837242672

The Renewable Energy Sources (RES) penetration in the power system of Cyprus has dramatically increased over the last years. As a result, the system is already facing significant challenges limiting the RES hosting capacity of the Distribution Network (DN). The major limitation factors are network congestion and voltage security. In this paper, alternative solutions for increasing the RES hosting capacity in DNs are reviewed, and a methodology is introduced to evaluate their effectiveness. More specifically, different inverter settings and an advanced centralised voltage control from power transformers are used to mitigate voltage-related issues, while network reinforcements and upgrading the operating voltage are considered for further increase in hosting capacity. The solutions and evaluation methodology are tested using a real MV network of the Cyprus distribution system and the strategic plan of the Cyprus Distribution System Operator (DSO) for maximizing RES hosting capacity is outlined. © The Institution of engineering & technology 2024.

关键词： Distribution transformers

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Unforgettable Password Generation Using LoRA Fine-Tuned Large Language Model

Unforgettable Password Generation Using LoRA Fine-Tuned Larg...

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Sameer, Mohammed Sudharsan, K. Benazir Begum, A. Hindustan Institute Of Technology And Science Dept.of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

In response to the challenges posed by complex and hard-to-remember passwords in traditional authentication systems, this research introduces an innovative approach leveraging Low Rank Adaption (LoRA) fine-tuned Large Language Models (LLMs) to generate natural language-like strong passwords. Focused on striking a balance between usability and security, proposed system methodology employs smaller-sized pre-trained LLMs, adapted using LoRA fine-tuning, to produce passwords that are both strong and memorable. By addressing the limitations of current password generation practices, proposed system framework aims to encourage user adoption of secure practices, contributing to a positive societal impact through improved cybersecurity hygiene. The proposed solution involves deploying a fine-tuned LLM and serving them through an frontend web UI which emphasizes resource efficiency scalability of deployment of such model, and ease of using the generated passwords in real life authentication purposes fostering good cybersecurity practices among non-technical users. © 2024 IEEE.

关键词： Authentication

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