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19th IEEE International Multi-Conference on systems, Signals and Devices, SSD 2022

作者： Mohammed, Faris E. Zghal, Nadia Smaoui Aissa, Dalinda Ben El-Gayar, M.M. Tunis University Microwave Electronics Research Laboratory Faculty of Science Tunisia Enis Control and Energy Management Research Laboratory Sfax Tunisia New Mansoura University Faculty of Computer Science and Engineering Department of Computer Science Egypt

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

Breast cancer is one of the most important diseases that lead to death, according to the reports of the World Health Organization. Reports also indicated that breast cancer affects women more than men. Late or wrong diagnosis leads to a deterioration in the patient's condition and may lead to death. Therefore, automated multiple classifications using machine learning of breast cancer from histopathological images plays a major role in the early diagnosis of the disease. Multiple classifications of breast cancer is the identification of tumors such as Carcinoma, Fibroadenoma, Cysts, etc. However, this type of classification faces many challenges such as extracting subtle differences between the binary classes of tumors and whether they are benign or malignant, strong coherence of tumor cells and widespread color heterogeneity. Therefore, we propose in this paper the use of a sophisticated model that works on semantic segmentation and extracting distinctive patterns and classifying them using a deep neural network. The structured deep learning model performed impressively (average accuracy of 98.7%) on a large-scale data set, demonstrating the power of our method in providing an effective tool for classifying multiple breast cancers in clinical settings. © 2022 IEEE.

关键词： Semantic Segmentation

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An Efficient Lightweight Authentication and Key Agreement Protocol for Patient Privacy

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computers, Materials & Continua 2021年第12期69卷 3495-3512页

作者： Seyed Amin Hosseini Seno Mahdi Nikooghadam Rahmat Budiarto Department of Computer Engineering Ferdowsi University of MashhadMashhad***Iran Department of Informatics Faculty of Science and TechnologyUniversitas Alazhar IndonesiaJakarta12110Indonesia

Tele-medical information system provides an efficient and convenient way to connect patients at home with medical personnel in clinical *** this system,service providers consider user authentication as a critical *** address this crucial requirement,various types of validation and key agreement protocols have been *** main problem with the two-way authentication of patients and medical servers is not built with thorough and comprehensive analysis that makes the protocol design yet has *** paper analyzes carefully all aspects of security requirements including the perfect forward secrecy in order to develop an efficient and robust lightweight authentication and key agreement *** secureness of the proposed protocol undergoes an informal analysis,whose findings show that different security features are provided,including perfect forward secrecy and a resistance to DoS ***,it is simulated and formally analyzed using Scyther *** results indicate the protocol’s robustness,both in perfect forward security and against various *** addition,the proposed protocol was compared with those of other related protocols in term of time complexity and communication *** time complexity of the proposed protocol only involves time of performing a hash function Th,i.e.,:O(12Th).Average time required for executing the authentication is 0.006 seconds;with number of bit exchange is 704,both values are the lowest among the other *** results of the comparison point to a superior performance by the proposed protocol.

关键词： Authentication key agreement protocol tele-medical Scyther perfect forward secrecy

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A Hybrid Blockchain Framework for Secure, Scalable, and Energy-Efficient Digital Identity Management with Token-based Selective Disclosure

A Hybrid Blockchain Framework for Secure, Scalable, and Ener...

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Electronics and Renewable systems (ICEARS), International Conference on

作者： Velmurugan M Shinzeer C K G. Maya R. Ramya R Kanimozhi Syed Ismail Abdul Lathif Department Of Computer Science & Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science And Technology Chennai Department of School of Computer Applications Lovely Professional University Phagwara Punjab Faculty of Management SRM Institute of Science and Technology Kattankulathur Department of Electronics and Communication Engineering K.Ramakrishnan College of Engineering Samayapuram Computer Science and Engineering Muthayammal Engineering College Rasipuram Department of Data Science and Business Systems SRM Institute of Science and Technology Chennai

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Data breaches, identity theft, and the lack of user control within traditional digital identity management systems, it begs a more secure and decentralized alternative. In this study we propose a blockchain based digital identity management framework that implements privacy, security and transparency by employing distributed ledger technology. To provide tamper proof identity storage and automated verification, the proposed model uses cryptographic hashing and smart contracts. The use of a novel token-based access mechanism enables users to safely share their identity data with third parties, while keeping sensitive information out of sight. Security metrics are enhanced by 30% for data integrity with 45% reduction in unauthorized access attempts all through simulations. The framework also achieves improved efficiency reducing identity verification time by 40 percent compared to traditional systems. It offers a promising approach to address important vulnerabilities in centralized identity management in line with the development of marketable and user-friendly digital identity solutions.

关键词： Resistance Privacy Fault tolerance Smart contracts Fault tolerant systems Throughput Energy efficiency Blockchains Identity management systems Interoperability

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Implementation Of M-A-C Convention For Wireless AD HOC

Implementation Of M-A-C Convention For Wireless AD HOC

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Yogesh Kumaran S Sunanda Das Department of Computer Science and Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore India

In this post, we discuss how to boost quality when faced with high loads and rapid diminishing. In order to improve bandwidth utilization and delay efficiency, a methodology was presented in the Transactions of the IEEE Conference on Connectivity (ICC), that employed either a sensible path or a relayed path depending on rate comparability. Unfortunately, since direct route or intermediary path dependability are less reliable amid dimming circumstances, speed decreases. was demonstrated to outperform due to higher communication stability offered by the secondary relay line in terms of typical capacity and latency metrics. Despite being superior to the direct way, only utilises the broadcast path as a supplementary alternative path, thus it is unable to benefit significantly from the relay method's 4 percentage. The collaborating Proposed method we progress in this editorial, called extremely rapid relay-based conscientious, researchers estimate the transceiver ratio of the starting point, reroute, and citation links and seems to be using broadcaster remains a central to consistently select between the relay path and the successful and prosperous for feedback and control and delay achievements.

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Transcription for Thai Traditional Medicine Texts with Wav2Vec2

Transcription for Thai Traditional Medicine Texts with Wav2V...

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International Electrical engineering Congress (iEECON)

作者： Jettasic Popun Wilaiporn Lee Akara Prayote Kanabadee Srisomboon Luepol Pipanmekaporn Department of Computer and Information Science Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

Recently, Automatic Speech Recognition (ASR) technology is widely used for communication convenience in converting speech to text. Initial surveys reveal that existing studies on ASR, both in Thai and foreign languages, focus on contemporary language communication, lacking support for specialized vocabulary. Thai Traditional Medicine (TTM) contain ancient medical terminology recorded in various media such as palm leaves, parchment, notebooks, and inscriptions. Centuries of textual preservation have led to text degradation. Given the suitability of ASR study to accommodate medical terminology and ancient languages, it is proposed to apply it to convert original Thai Traditional Medicine texts into contemporary language, aiding experts in reading and interpreting them. ASR involves converting speech signals into text. In this paper, we propose an end-to-end speech recognition approach for Thai Traditional Medical texts leveraging self-supervised learning (SSL) to overcome the limitations of limited labeled data. We utilize a transformer-based model pre-trained (XLSR-Wav2Vec) on unlabeled TTM texts speech data using SSL techniques and fine-tune it with a small dataset of labeled TTM texts audio-text pairs. Due to the absence of a Thai Traditional Medicine vocabulary repository, a dataset comprising text and speech is developed, consisting of 1,800 training sentences and 200 test sentences randomly selected from recordings of 10 Thai Traditional Medicine experts. Offline evaluation methods are employed, resulting in improved accuracy rates. Future efforts will focus on expanding the speech dataset to enhance recognition accuracy further. This study lays the groundwork for efficiently extracting knowledge from Thai Traditional Medicine prescriptions, ensuring the preservation of this valuable heritage for future generations.

关键词： Training Surveys Vocabulary Accuracy Terminology Self-supervised learning Speech enhancement Transformers Automatic speech recognition Speech to text

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Indoor Air Quality Monitoring system for Healthcare Facilities 7th

Indoor Air Quality Monitoring System for Healthcare Faciliti...

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7th International Conference on Advancements of Medicine and Health Care through Technology, MEDITECH 2020

作者： Puscasiu, Adela Fanca, Alexandra Valean, Honoriu Gota, Dan-Ioan Stan, Ovidiu Roman, Nicolae M. Clitan, Iulia Muresan, Vlad Faculty of Automation and Computer Science Department of Automation Technical University of Cluj Napoca Cluj Napoca Romania Faculty of Electrical Engineering Electrical Engineering and Measurements Department Technical University of Cluj Napoca Cluj Napoca Romania

ISBN: (纸本)9783030935634

The human body is not able to detect whether the air is polluted or not, which is why it is important to have a device that can measure the air quality, both in the closed environment and in nature. Thus, air pollution is defined as a harmful phenomenon to the ecological system and to the normal conditions of human existence and development when certain substances in the atmosphere exceed a certain concentration. The paper proposes an indoor air monitoring system for healthcare facilities, using an Arduino Mega2560 board, temperature sensor, humidity sensor, eCO2 (equivalent CO2 which designates global warming potential), TVOC (Total Volatile Organic Compounds) and atmospheric pressure sensor. The technologies used for the software implementation are Arduino IDE for the acquisition of data from sensors and Visual Studio for the graphical interface implementation. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Air quality

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Challenges in Mobile Network Capacity Monitoring & Solutions to Improve Capacity Problems Using Various Parameters

Challenges in Mobile Network Capacity Monitoring & Solutions...

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Technological Advancements in Computational sciences (ICTACS), International Conference on

作者： Vikas Gupta Ashish Kumar Chakraverti Manoj Kumar Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida Uttar Pradesh India Faculty of Engineering and Information Science University of Wollongong Dubai UAE

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

This paper has an overview on study of traffic capacity of Mobile network parameter that affect the network utilization and network experience in Mobile network era., This capacity study & analytics provide a conception of how the various networks function, capacity parameters & constraints of different domain of Mobile Network like RAN (Radio access Network),CN (Core Network), IP & TX (Internet Protocol & Transport Network) & their associated capacity parameter have correlations in network utilization. It also has the access of Mobile Network KPIs detail, for readers to easily retrieve a variety of capacity parameters for effective capacity management. In order to manage end to end capacity requirement in telecom domain & can help for solving capacity problem with the help of various network parameters. These various capacity parameters can be used to generate systematic, rule-based decision which are standardized, more flexible, and faster to take decision on capacity expansion well in advance through the parametric behaviour. furthermore, the review concludes the published work their gaps and future work in the direction of improving Mobile network capacity management.

关键词： systematics Protocols Correlation Reviews Internet Resource management IP networks Monitoring Radio access networks

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ML Techniques for Employee Performance Prediction

ML Techniques for Employee Performance Prediction

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Kumar, Brajesh Agrawal, Prateek Uike, Dipesh Lourens, Melanie Bhati, Indira Peter, M. Chandrakumar Dr. Apj Abdul Kalam Women's Institute of Technology Department of Computer Science & Engineering Bihar Darbhanga India India Dr. Ambedkar Institute of management studies and research Maharashtra Nagpur India Durban University of Technology Faculty of Management Sciences South Africa Department of Management India PeriyarManiammai Institute of Science and Technology Department of Software Engineering Tamilnadu Thanjavur India

ISBN: (纸本)9798331543617

When it comes to maximizing the effectiveness of a business and promoting professional growth, employee performance prediction is an extremely important factor. This research article investigates the use of machine learning (ML) approaches to forecast employee performance, with a particular emphasis on the incorporation of different algorithms from different sources to improve accuracy and dependability. Methods that have been used for a long time, such as linear regression and decision trees, are evaluated alongside more recent approaches, such as ensemble methods and deep learning. To refine the prediction models, our research makes use of approaches such as feature selection and dimensionality reduction. These techniques are utilized by utilizing previous performance data, demographic information, and behavioral indicators. It has been demonstrated through the analysis that sophisticated machine learning techniques, in particular ensemble and deep learning models, are superior to traditional methods when it comes to anticipating employee performance. Our findings offer HR departments concrete insights that can be used to adopt data-driven methods for performance management, which will eventually contribute to improved organizational outcomes and increased employee satisfaction. This paper offers opportunities for future development in predictive analytics within the field of human resources and emphasizes the potential of machine learning to alter performance evaluation systems. © 2024 IEEE.

关键词： Predictive analytics

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Study of Photonic Platforms for On-Chip Refractive Index Sensing

Study of Photonic Platforms for On-Chip Refractive Index Sen...

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Photonics North

作者： Raghi El Shamy Mohamed A. Swillam Xun Li Department of Electrical and Computer Engineering Faculty of Engineering McMaster University Hamilton Canada Department of Physics School of Science and Engineering The American University in Cairo New Cairo Egypt

ISBN: (数字)9798350366365

ISBN: (纸本)9798350366372

Here we present a rigorous study for the different integrated photonic platforms that can be used for on-chip refractive index (RI) sensing. The study includes the widespread silicon photonics platform, the silicon nitride platform and the silica platform. We compare these three platforms according to five parameters that determine the performance and reliability of the RI sensor. Finally, we conclude with the optimum platform for on-chip RI sensing according to the available technology and the aimed application.

关键词： Refractive index Silicon nitride Silicon photonics system-on-chip Sensors Reliability

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Semantic Search Engine, Thai Traditional Medicine Knowledge Graph Application

Semantic Search Engine, Thai Traditional Medicine Knowledge ...

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International Electrical engineering Congress (iEECON)

作者： Natthinan Sakulpakdee Nattavee Narischat Kanabadee Srisomboon Wilaiporn Lee Luepol Pipanmekaporn Akara Prayote Department of Computer and Information Science Faculty of Apply Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

In this paper, a semantic information retrieval framework is presented to improve the precision of search results by concentrating on the context of concepts is presented. Instead of the keyword matching technique, the graph theory is used for leveraging the relationships and meanings of search terms. Information is represented as a knowledge graph for semantic searching performed by the inference engine and results are passed to the NLP technique for interpreting entity, relationship and property to their relevancy query. In the current system, we focused on healthcare system to helping the foundation recommendations of Thai Traditional Medicine. Once Thai Traditional Medicine contains a numerous of words which have the same meaning, the traditional keyword based cannot retrieve all relevant document. In our proposed semantic architecture, the query is performed an context-based understanding for retrieving all relevant document, therefore, it can retrieve the same number of documents for the queries which have the same meaning.

关键词： Knowledge engineering Electrical engineering Accuracy Semantic search Keyword search Knowledge graphs Medical services Information retrieval Graph theory Engines

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