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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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Revolutionizing Traditional Supermarkets: A Comprehensive Solution for Enhancing Efficiency, Security and Customer Satisfaction 2024

Revolutionizing Traditional Supermarkets: A Comprehensive So...

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16th International Conference on Contemporary Computing, IC3 2024

作者： Tanna, Om H. Vasani, Ankur M. Thakkar, Krishna H. Gotecha, Malav J. Dept. of Information Technology MPSTME NMIMS University India Dept. of Information Technology Shri Bhagubhai Mafatlal Polytechnic India Dept. of Computer Engineering DJ Sanghvi College of Engineering India

ISBN: (纸本)9798400709722

This research proposes an Artificially Intelligent enabled Smart Supermarket System for enhanced efficiency, security and reduces man power as compared to traditional Supermarkets. In order to ensure a perfect omnichannel shopping experience the system uniquely includes an Artificially Intelligent model. Customers can scan items on the go with the app in their smartphones, select product variants as required, add the product to their virtual cart and pay online for the total cart value. With the help of YOLOv5 computer vision algorithm, eliminating long checkout queues and manpower the system proves to be revolutionizing the traditional supermarket procedures. Moreover, the system also incorporates the indoor navigation assistance on customer's app to facilitate easy access and navigation to preferred items. This futuristic solution not only provides valuable insights for business development but also is proven to be more efficient and helpful for customers saving their time and companies resources. © 2024 Copyright held by the owner/author(s).

关键词： Sales

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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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A Survey on Blockchain-Based Certificate Authentication System: From Traditional to Digital 4

A Survey on Blockchain-Based Certificate Authentication Syst...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Saraswathi, R Vijaya Vasavi Swathi, Meda Venkata Punwatkar, Sakshi Manoj Konduru, Shreya Sami, Mohammed Abdul Vnr Vignana Jyothi Institute of Engineering and Technology Dept. Of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331529635

This research study pertains to the essential problems of certificate authentication within academic organizations. It concentrates on the major issues of forgery and inefficiencies as well as administrative bottlenecks that arise in conventional systems. The usual ways, which are based on one authority organization, are likely to be compromised, move slowly on verification, and have increased overhead costs. Blockchain technology is a distributed way of doing things without a middleman, and thus it is able to improve security, transparency, and the immutability of educational records. The article identifies the shortcomings of the present blockchain-based implementations with the focus on scalability, interoperability with legacy infrastructure, and high transaction costs. In the paper, an experiment on Ethereum-based smart contracts as well as the Secure Hash Algorithm (SHA-256) and InterPlanetary File System (IPFS) technologies shows the potential of these technologies to a certificate validation system by providing cryptographic integrity and, therefore, data storage that cannot be altered. The proposed work introduces a decentralized architecture that uses smart contracts for certificate issuing and verification to some extent. By integrating cryptographic hashing mechanisms, the system provides real-time, verifiable, and immutable credential records, addressing both fraud prevention and operational inefficiencies. © 2024 IEEE.

关键词： Ethereum

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Transformer-Based Embeddings for Greek Language Categorization 24

Transformer-Based Embeddings for Greek Language Categorizati...

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24th IEEE/ACIS International Conference on computer and Information Science, ICIS 2024

作者： Liapis, Charalampos M. Kyritsis, Konstantinos Perikos, Isidoros Paraskevas, Michael University of Patras Computer Technology Institute & Press 'Diophantus' Mathematics Dept. Patras26504 Greece University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece University of Patras Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press 'Diophantus' Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350376647

The Greek School Network (GSN) provides support to students, teachers, and school units in secondary education across Greece. Handling numerous user queries manually can be challenging, necessitating the development of an automated system for accurate categorization of these queries. This paper presents a comparative study of various transformer-based models for multi-class text categorization of Greek language queries submitted to the GSN helpdesk. We introduce a new experimental balanced dataset and extract vector representations from eleven transformer-based models. These representations are evaluated using ten classic machine learning classifiers. Our findings highlight the superior performance of the Multilingual E5 Text Embeddings model, particularly when paired with the extreme gradient-boosting classifier. This combination demonstrates a clear advantage in accurately categorizing user queries, paving the way for more efficient automated helpdesk systems. © 2024 IEEE.

关键词： Contrastive Learning

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An Interpretable Framework for Predicting Type 2 Diabetes using ML and Explainable AI 26

An Interpretable Framework for Predicting Type 2 Diabetes us...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Ahmed, Kazi Fardeen Uz Zaman, Md Shahid Peyal, Hasibul Islam Hossain, Anika Rahman Ratul, Md. Toyaha Abdal, Md. Nazmul Islam, Md. Injamul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Bangladesh Uttara University Dept. of Computer Science & Engineering Bangladesh Khulna University Dept. of Computer Science & Engineering Discipline Bangladesh

ISBN: (纸本)9798350359015

Diabetes Mellitus is an incurable disease and stands as a major universe cause of destruction. With the universal prevalence of diabetes increasing rapidly, accurate detection and identification of the disease have become crucial. In this paper, we present an explainable AI-based diabetes indicative methodology that is carefully constructed, effective, and, most importantly, interpretable. Using two real-world diabetes datasets, the three most well-known machine learning classifiers in the literature - Random Forest (RF), Decision Tree (DT), and XGBoost - were subjected with quantitative assessments. After training and assessment of all classification models, the suggested method achieved the best results in the XGBoost classifier for the Sylhet dataset with 99.4% accuracy and the Pima Indian dataset with 92.59% accuracy. The datasets were normalized across observations to provide standardized values for improved analytical applicability and comparability. Explainable AI has been implemented for the XGBoost machine learning model by generating both global and local explanations using Shapley additive explanations (SHAP) and Local interpretable model-agnostic explanations (LIME). The elements that contribute to diabetes are explained and shown in graphs to help medical professionals make decisions about clinical diagnosis and treatment options. © 2023 IEEE.

关键词： Decision Tree (DT) Diabetes diabetes diagnosis explainable AI interpretable LIME Pima Indian dataset Random Forest (RF) SHAP Sylhet dataset XGBoost

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A Futuristic Optical and Wireless Convergence Network Towards 6G and Beyond 4

A Futuristic Optical and Wireless Convergence Network Toward...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Molefe, Mlungisi Sibiya, Khulekani Nleya, Bakhe Durban University of Technology Dept. of Electronic and Computer Engineering Durban South Africa

ISBN: (纸本)9798350395914

Emerging use cases and stringent requirements for 6G and beyond networks require new quantum leaps in mobile communication due to the demands of higher throughput, extensive bandwidth requirements, ultra-low latency and massive number of connected devices. The advancement in wireless communications and the advancement in optical networks will be essential in addressing the demands for future mobile networks by providing an innovative infrastructure for 6G and beyond networks. To support stringent requirements for 6G networks and beyond, new innovative technologies and systems are required that will combine optical and wireless networks. An innovative approach of converging optical and wireless networks promises to improve the network into new heights by creating a smart world with beyond-human cognitive communication capacity and speed, improved network scalability and enhanced energy efficiency. Research has shown that a promising architecture to achieve this goal, and cater for extremely high bandwidth and extremely low latency requirements is based on an All-Photonics Network. Therefore, in this paper, we propose an All-Photonics Network for the future to address bandwidth limitations, latency issues and massive connectivity. Furthermore, we propose an evolved infrastructure or architecture converging optical and wireless networks. Potential benefits for the evolved infrastructure are also discussed. © 2024 IEEE.

关键词： Bandwidth

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Analysis of Physical Layer Impairments Resources Allocation Aware Algorithm/Framework in Transparent OTNs 4

Analysis of Physical Layer Impairments Resources Allocation ...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Nleya, Bakhe Molefe, M. Khulekani, Sibiya Durban University of Technology Dept. of Electronic and Computer Engineering Durban South Africa

ISBN: (纸本)9798350395914

Present-day, limitedly fixed wavelength routed based all Transparent Optical Transport Networks (OTNs) are quite energy efficient in comparison to translucent and opaque equivalents. As a result they are also regarded as a practical solution transport network provisioning ultrahigh bandwidth capabilities to support the various applications and services. The resulting heterogeneous nature of present-day global traffic makes such wavelength-routed networks spectrally inefficient. However, advancements in DSP techniques, modulation approaches, and transmission impairment mitigation techniques have vastly improved such net-works' spectral efficiencies and optical reach. The paper thus reviews the efficiency in the operation of an orthogonal frequency division multiplexing (OFDM) based Transparent OTN that is characterized by flexibility in the provisioning of available spectral resources. We address the challenges of optimal routing level allocation of wavelengths subject to maximizing spectral efficiencies. In so doing, we also consider the impact of various physical impairments. We introduce a quality factor-based tool (Q-factor) that aids in choosing op-timal routes. Ultimately, The tool is later incorporated into a proposed resource allocation framework's algorithms, which focus on ensuring spectral efficiency and overall network energy-efficient operation. Overall, we conclude that the pro-posed transport network architecture is relatively efficient regarding energy and spectral efficiencies. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Active Control for Resonance Mitigation in Electric Drive Applications 15

Active Control for Resonance Mitigation in Electric Drive Ap...

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15th International Symposium on Industrial Electronics and Applications, INDEL 2024

作者： Berglund, Emelie Borg, Johan Johansson, Jonny Luleå University of Technology Dept. of Computer Science Electrical and Space Engineering Sweden

ISBN: (纸本)9798350352320

The use of inverter-based motor controllers that can generate fast voltage level transitions is increasing in the field of electric drive systems because of their ability to achieve higher efficiency. However, the fast voltage transitions, dv/dt's, are prone to generate bearing currents and cause overvoltages that may harm the electric motor. An LC filter applied between the inverter and the motor terminals can reduce the dv/dt's. However, the LC filter will cause overvoltage due to resonance but this can be overcome by introducing an extra pulse at each pulse-width modulation (PWM) transition. The timing of this extra pulse is crucial for suppressing the resonance, but due to nonlinearities in a real system, the time instants may vary over time and are thus in need of control. In this study, an analytical expression for the optimal pulse location and duration is derived and we propose a control algorithm that continuously calculates the optimal pulse switch time instants based on the measured output voltage. The control algorithm can handle sudden system disturbances and a Monte Carlo simulation is performed to evaluate the performance of the algorithm. This hybrid filter successfully reduces dv/dt's at the motor terminals while simultaneously eliminating overvoltages due to the filter resonance. © 2024 IEEE.

关键词： Control nonlinearities

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Enhancing Brain Tumor Classification Using Data-Efficient Image Transformer

Enhancing Brain Tumor Classification Using Data-Efficient Im...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Yang, Jiafeng Rusak, Alena Belozubov, Alexander ITMO University Software Engineering and Computer Technology Dept. Saint-Petersburg Russia

ISBN: (纸本)9798350395044

Medical image analysis is essential in the diagnosis and treatment of many diseases, including brain tumors. This work investigates the effectiveness of transformer models in the multiclass classification of brain tumor MRI images. We use a combination of three publicly available brain tumor datasets classified into four categories and appropriately modify existing transformer variants, including adjustments to patch size, number of categories, dropout, etc. The results indicate that, due to the condition of insufficient data volume, most transformer variants are still inferior to the benchmark model VGG-16. The DeiT model with knowledge distillation has significantly improved various indices on the test set, verifying its effectiveness in the classification of brain tumor MRI images under limited data. The article supports the application of transformer-based models to medical image analysis. Follow-up work will verify the generalization performance of the model on other datasets and explore methods to reduce the dependence of the transformer on the data, making it more applicable to tasks such as medical images classification. © 2024 IEEE.

关键词： Distillation

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