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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Md. Shohel Rana Nitun Kumar Podder Humayan Kabir Rana Md. Imam Hasan Md. Shafiul Azam Md Abdur Rahim S. M. Hasan Sazzad Iqbal Subir Saha Dept. of Computer Science and Engineering Pabna University of Science and Technology Pabna Bangladesh Dept. of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh

Neurodegenerative diseases (NDGs) can slowly damage the brain as well as the central and peripheral nervous systems. Parkinson's disease (PD) is a sensitive sensory disease that causes a malfunction of dynamic equilibrium. PD causes certain brain neuronal cells to gradually split or die. There are certain significant characteristics of PD that may increase the risk of acquiring deferent NDGs including Alzheimer's disease (AD), Amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and Multiple sclerosis disease (MSL). We conducted a transcriptomic analysis to find connections between PD and NDGs. To explore how PD may affect the advancement of NDGs, we employed a quantitative framework to analyze the gene expression microarray dataset. To obtain genomic associations between PD and NDGs, we performed gene expression profiling by identifying dysregulated pathways, gene ontologies, PPIs, and phylogenetic analysis. We found 15, 11, 28, and 24 significant genes are shared between PD and AD, ALS, HD, and MSL respectively. We also identified a significant number of functional and ontological pathways, hub proteins and phylogenetic associations that indicate PD may have a link to develop NDGs (AD, ALS, HD, and MSL). We validate our findings through gold benchmark databases. This systematic approach is highly beneficial in understanding the causes and progression of NDGs owing to the effect of PD.

关键词： Proteins Peripheral nervous system Multiple sclerosis systematics Parkinson's disease Genomics Phylogeny

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Visual Traits-Based Recommendation system for Proactive Retailing in Physical Store Environment

Visual Traits-Based Recommendation System for Proactive Reta...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Kh'ng, Xin Yi Ooi, Boon Yaik Teoh, Sheng Kang Ooi, Boon Sheng Chen, Yen-Lin Universiti Tunku Abdul Rahman Department of Computer Science Kampar Malaysia Xilnex Web Bytes Sdn. Bhd. Penang Malaysia National Taipei University of Technology Dept. of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350324174

A comprehensive visual traits-based recommendation system is designed for proactive retailing in a physical store environment. The proposed system utilizes computer vision algorithms to analyze various visual traits of customers, including facial features, clothing and accessories, to provide targeted product recommendations. The system does not require customers to provide any personal information, making it a less intrusive and more hassle-free approach compared to the conventional membership approach. By providing tailored product suggestions, the system offers retailers the opportunity to enhance their customers' shopping experience and increase sales. This paper provides a detailed description of the system's design and setup. © 2023 IEEE.

关键词： Recommender systems

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Facial Expression Recognition Using Reversible Neural Network

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SSRN 2023年

作者： Barman, Asit Dutta, Paramartha Dept. of Computer Science & Engineering and Information Technology Siliguri Institute of Technology Darjeeling734009 India Dept. of Computer & System Sciences Visva-Bharati University Santiniketan731235 India

When identifying facial expressions using a set of salient features, reversible neural network plays a crucial role. In order to create a prominent feature set, these salient features are extracted from a face image utilizing distance and shape signatures, corresponding stability indices, and statistical measurements. The collected feature set is fed into the Reversible Neural Network (RNN), which maps it to various emotions. To carry out our experiment and verify the efficacy of facial expression recognition, the suggested network was applied to the MMI, CK+, and JAFFE data sets. © 2023, The Authors. All rights reserved.

关键词： Face recognition

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BLOCK-SECURE: AI-Based Blockchain Enabled Secure Framework for IoMT Applications

BLOCK-SECURE: AI-Based Blockchain Enabled Secure Framework f...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Panchal, Barkha Bhatia, Jitendra Kumhar, Malaram Tanwar, Sudeep Dutta, Ashit Kumar Rodrigues, Joel J.P.C. Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad India Dept. of Comp. Science and Information Systems College of Applied Sciences AlMaarefa University Saudi Arabia Amazonas State University AM Manaus Brazil

ISBN: (纸本)9798350350548

The Internet of Medical Things (IoMT) revolutionizes healthcare by integrating medical devices and systems with the internet. However, the vast amounts of sensitive medical data in IoMT networks pose significant security and privacy concerns. Traditional security measures often fall short in identifying the malicious data attacks within the IoMT ecosystems. This paper introduces an AI-based non-malicious data classification scheme based on blockchain. We applied and evaluated the machine learning (ML) classifiers, such as support vector machine (SVM), random forest (RF), and K-Nearest neighbor (KNN). We evaluated the proposed framework based on various performance metrics that includes accuracy, precision, recall, and F1 score. The accuracy using SVM obtained 75.3%, RF is 75.9%, and KNN is 84.3%. The results shows that KNN performs better than other models by the factor of 9%. © 2024 IEEE.

关键词： Adversarial machine learning

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Bounded Simultaneous Messages 43

Bounded Simultaneous Messages

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43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical computer science, FSTTCS 2023

作者： Bogdanov, Andrej Dinesh, Krishnamoorthy Filmus, Yuval Ishai, Yuval Kaplan, Avi Sekar, Sruthi School of EECS University of Ottawa Canada Dept. of Computer Science and Engineering Indian Institute of Technology Palakkad India The Henry and Marylin Taub Faculty of Computer Science Technion Haifa Israel University of California BerkeleyCA United States

ISBN: (纸本)9783959773041

We consider the following question of bounded simultaneous messages (BSM) protocols: Can computationally unbounded Alice and Bob evaluate a function f(x, y) of their inputs by sending polynomial-size messages to a computationally bounded Carol? The special case where f is the mod-2 inner-product function and Carol is bounded to AC0 has been studied in previous works. The general question can be broadly motivated by applications in which distributed computation is more costly than local computation. In this work, we initiate a more systematic study of the BSM model, with different functions f and computational bounds on Carol. In particular, we give evidence against the existence of BSM protocols with polynomial-size Carol for naturally distributed variants of NP-complete languages. © 2023 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Automata theory

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Did COVID-19 Pandemic Influence the Ether Cryptocurrency Market? Perception and Analysis

Did COVID-19 Pandemic Influence the Ether Cryptocurrency Mar...

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2022 International Conference on Breakthrough in Heuristics and Reciprocation of Advanced Technologies, BHARAT 2022

作者： Mithillesh Kumar, P. Jeyanthi, R. Deepa, K. Amrita Vishwa Vidyapeetham Amrita School of Engineering Dept. of Computer Science and Engg. Bengaluru India

ISBN: (数字)9781665436250

ISBN: (纸本)9781665436250

In recent days, DeFi tokens have gained popularity as an investment option in the pandemic period and has gained a significant amount of investment. Cryptocurrency trading is a type of DeFi that has gained a lot of attention in the global market. The value of such currencies is increasing on a daily basis and peaked during the pandemic. One of these significant cryptocurrencies is the ether cryptocurrency, which ranks second only to the bitcoin cryptocurrency in terms of the value of a single coin. The ARIMA model will be used to forecast the price of ether. In this paper, an hourly forecast and a short term period forecast are performed. The forecast clearly shows that the ARIMA model performed better on log transformed data than on the original data. It's also evident that COVID-19 pandemic has also aided the growth of ethereum when compared to previous year. © 2022 IEEE.

关键词： Ethers

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Exploring the Impact of Univariate Feature Selection Method on Machine Learning Algorithms for Heart Disease Prediction

Exploring the Impact of Univariate Feature Selection Method ...

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

作者： Mainul Islam Rafiqul Islam Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Computer Science and Engineering Dhaka University of Engineering & Technology Gazipur Bangladesh

This study compares various machine learning techniques such as logistic regression, support vector machine (SVM), random forest, Naïve Bayes, and decision tree. Later, a feature selection approach that considers the Univariate Feature Selection (UFS) method was applied to select the best features based on statistical testing. In this research, we employed the ANOVA F-test to pick the most significant features, and we used a cutting-edge dataset for experimental analysis. The ANOVA F-test was used to exploit the target variable's dependency on the continuous variables. The results show that employing the UFS approach for picking features improves the performance of the algorithms. According to the experimental results, using UFS with the logistic regression technique yields 93.3% accuracy, whereas the standalone Naïve Bayes algorithm achieved the best accuracy.

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Enhancing Hyperledger Fabric Security with Lightweight Post-Quantum Cryptography and National Cryptographic Algorithms

Enhancing Hyperledger Fabric Security with Lightweight Post-...

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Open Innovations Association (FRUCT), Conference of

作者： Vinay Kumar Kasula Sarath Babu Rakki Rajkumar Banoth Dept. Information Technology University of the Cumberlands Williamsburg KY USA Dept. of Computer Science and Engineering JNTUH University College of Engineering Hyderabad TG India Dept. of Computer Science University of Texas at San Antonio San Antonio TX USA

ISBN: (数字)9789526524634

ISBN: (纸本)9798331595425

Hyperledger Fabric is a scalable and modular consortium blockchain platform designed for enterprise applications, where cryptographic algorithms play a fundamental role in ensuring data security and integrity. However, the native Fabric framework lacks support for national cryptographic standards, necessitating the integration of secure cryptographic mechanisms. This study proposes an enhanced approach to embedding national cryptographic algorithms into the Fabric platform. First, Graph-based Dependency Analysis is employed to investigate the interaction logic among Fabric components and the invocation of cryptographic functions, facilitating an efficient integration strategy. Next, the Lightweight Post-Quantum Cryptography (L-PQC) framework, which enhances resistance to quantum threats while maintaining computational efficiency, is utilized to integrate SM2, SM3, and SM4 cryptographic algorithms into Fabric’s Blockchain Cryptographic Service Provider (BCCSP) module. Subsequently, a Microservices-Based Cryptography Integration mechanism is designed to establish seamless mapping between Fabric’s cryptographic function calls and the national cryptographic algorithm interfaces, ensuring compatibility and interoperability. Finally, the implementation is evaluated using Blockchain Simulation Environments, where a fabric-gm consortium blockchain instance is deployed to validate the correctness and efficiency of the embedded cryptographic modules. Comparative analysis with the original Fabric platform reveals that the enhanced system introduces a 2.5% increase in network startup time, a 1.8× rise in transaction latency, and a 7.5% increase in dynamic certificate generation time, while maintaining operational performance within acceptable limits. The proposed integration strategy ensures secure and efficient cryptographic support within Hyperledger Fabric, making it resilient to emerging cryptographic threats.

关键词： Resistance Technological innovation Quantum computing Distributed ledger Heuristic algorithms system performance Fabrics Blockchains Cryptography Standards

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Improved Dual Haptic Controller with Extra Virtual Damper for Z-Width Enhancement 3

Improved Dual Haptic Controller with Extra Virtual Damper fo...

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3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Tiwari, Arpan R. Saha, S.K. Kumar, Subodh Indian Institute of Technology Delhi Dept. of Mechanical Engineering New Delhi India Indian Institute of Technology Delhi Dept. of Computer Science Engineering New Delhi India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Haptic simulation systems use the sensation of touch to allow users to experience virtual surroundings. In interfaces that are based on impedance, haptics controllers are sampled data that use angular position and velocity to provide torque feedback. The sample and hold data collecting strategy, which connects the continuous and discrete worlds, hinders the haptic model's stability. Increasing the sampling rate enlarges the Z-width of the system but increases sampling frequencies, deteriorates the velocity information, reducing the stable range of damping. In this work, implementation of a concept similar to virtual coupling has been used by introducing an extra layer of the damper in between the virtual system and the Haptic device. Sampling the velocity at lower frequencies and position at higher one help in maximizing the stiffness range. This dual control of the improved architecture of the dual-rate controller is discussed in this paper. The suggested scheme's effectiveness was validated by theoretical stability analyses utilizing linear control methods and compared with passivity theory. © 2022 IEEE.

关键词： Controllers

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Self-Adaptive Smart Lighting system using Yolov8 and ESP32

Self-Adaptive Smart Lighting System using Yolov8 and ESP32

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International Conference on Electrical Energy systems (ICEES)

作者： Virum Ranka Dwisha Shah Devam Shah Pradnya Saval Dept. of Computer Science and Engineering (Data Science) Dwarkadas J. Sanghvi College of Engineering Mumbai India

ISBN: (数字)9798350353778

ISBN: (纸本)9798350353785

In the pursuit of sustainable living and enhanced user comfort, the integration of smart technologies into everyday devices has become paramount. This paper highlights the importance of dynamic lighting control in improving energy efficiency and the overall quality of life. Traditional lighting systems often fail to account for the dynamic nature of human activities, resulting in unnecessary energy wastage and suboptimal lighting conditions. The proposed system seeks to bridge the gap between existing lighting systems and the evolving needs of modern indoor spaces, with its focus on adaptability, efficiency, and user-centricity, promoting a more comfortable and nurturing environment. Although earlier studies have explored various aspects of smart lighting technologies, there remains a paucity of comprehensive solutions that integrate machine learning with sensor technologies to create truly adaptive environments. Novel algorithms have been utilized to optimize both visual comfort and energy efficiency. This system achieves up to 45-70% energy savings compared to existing lighting systems, making it a promising solution for both environmental and economic concerns.

关键词： Visualization Machine learning algorithms Energy conservation Smart homes Activity recognition Energy efficiency Real-time systems Trajectory Sensors Smart lighting

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