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693 articles for “machine learning method”
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An innovative antibiotic "Abaucin": Instigated by Artificial Intelligence
Abstract: Nosocomial Gram-negative pathogen, Acinetobacter baumannii repeatedly demonstrates multidrug resistance. Discovering novel antibiotics against A. baumannii has proven thought-provoking through conventional screening tactics. Providentially, machine learning approaches allow for the speedy exploration of chemical space, snowballing the probability of determining new antibacterial molecules. In the following research era, a neural network is accomplished with growth reserve dataset and accomplished in silico predictions for structurally unconventional molecules with commotion in divergence to …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 13, Issue 3, 2023 · pp. 29–33 Read article
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Express-U: Real-time Indian Sign Language Recognition
Abstract: This study describes a system that recognizes Indian Sign Language (ISL) hand poses and gestures in real time using the Hand Tracking Algorithm and the LSTM Deep Learning model. This approach aims to close the communication gap between those who are deaf or hard of hearing and the rest of society. Existing solutions either have a low level of accuracy or do not operate in real time. On both measures, …
Published in Journal of Open Source Developments · Vol. 9, Issue 1, 2022 · pp. 17–22 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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An Experimental Approach of Machine Learning Algorithms to Detect Botnet DDoS Attacks
Abstract: Botnets are one of the threats in a network to hamper the quality of the network by disrupting theresources of the network. These Botnets can be controlled remotely by Botmaster. The Machine Learning Algorithms play a major role to detect and control the Botnets that cause to DDoS attacks, malwares and phishing attacks that are vulnerable to network resources. The DDoS attacks are most dangerous malware events that disrupt whole …
Published in Journal Of Network security · Vol. 10, Issue 3, 2022 · pp. 7–14 Read article
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Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration
Abstract: The “Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration” project is a cutting-edge solution for intelligent traffic monitoring, with YOLO v8 (You Only Look Once) serving as the fundamental technology for real-time vehicle detection and traffic counting on roads. In addition to these features, the system interfaces effortlessly with data pipelines and machine learning projects by storing gathered traffic data in CSV (Comma-Separated Values) format. The major goal of …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 20–24 Read article
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Artificial Intelligence Based Education
Abstract: AbstractArtificial intelligence (AI) is a part of software engineering which includes building brilliant machines equipped for performing assignments that ordinarily require human knowledge. Computer-based intelligence is an interdisciplinary science with numerous methodologies, yet headways in AI and profound learning are making a change in perspective in for all intents and purposes each area of the tech business. Computer based intelligence has different applications, for example, mechanical technology, progressed counts which …
Published in Recent Trends in Parallel Computing · Vol. 7, Issue 3, 2020 · pp. 10–13 Read article
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Handwritten English Alphabet Recognition Using Convolutional Neural Network
Abstract: This research paper presents an approach for English alphabet recognition using machine learning. The proposed system utilizes a convolutional neural network (CNN) to identify individual characters within an input image. The dataset used in this research consists of a large collection of handwritten alphabet images, sourced from Kaggle's A-Z Handwritten Alphabets dataset in CSV (comma-separated values) format, which were preprocessed and augmented to improve the model's accuracy. We trained and …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 17–25 Read article
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Machine Learning Techniques for Early Detection of Heart Disease
Abstract: Cases of heart disease are increasing rapidly, thus it's important and concerning to be aware of any potential ailment beforehand. This diagnosis is a difficult task that must be completed fast and precisely. The primary goal of this study is to determine which patient, based on different medical features, has a higher chance of having heart disease. We created a heart disease prediction algorithm based on the patient's medical history …
Published in Journal of Microelectronics and Solid State Devices · Vol. 10, Issue 3, 2023 · pp. 16–21 Read article
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Channel Prediction and Estimation Based on Machine and Deep Learning Techniques: A Review
Abstract: Channel prediction estimation in the high- speed mobile environment is a hot issue for 3D massive multiple input multiple output (MIMO) millimeter-wave (mmWave) system. In this environment, the channel has fast time-varying and non-stationary characteristics. And its time-domain correlation coefficient is a time- varying parameter, which makes it difficult for traditional channel estimation methods to capture the channel variations over time and achieve ideal channel estimation performance. A known signal, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 10, Issue 3, 2023 · pp. 13–17 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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Fake Cryptocurrency Detection Using Python
Abstract: This study investigates the use of Python-based techniques for detecting fraudulent cryptocurrencies, addressing a growing concern in the digital financial ecosystem. The research methodology integrates various data science approaches, including web scraping, API integration, and advanced data analysis using Pandas and NLTK. Machine learning models, particularly classification algorithms such as Random Forest, are employed to analyze key features extracted from cryptocurrency whitepapers, social media discussions, and transactional data. By training …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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The Adoption of Artificial Intelligence in Different Network Security Concepts
Abstract: The obstacles of each security system combined with the increase of cyber-attacks, negatively affect the effectiveness of network security management and rise the activities to be taken by the security staff and network administrators. So, there is a growing need for automated auditing and intelligent reporting strategies for reliable network security with as less model complexity as possible. Newly, artificial intelligence has been effectively applied to various network security issues, …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 30–43 Read article
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Preprocessing of Product Reviews
Abstract: In this era, when we go for online shopping we go on checking online reviews of a product posted by users who already bought and used the product or when we want to download a movie, we go on checking movie reviews posted by users who watched that movie or it can be food reviews etc. So, product reviews are important. But the reviews posted by users are not clean …
Published in Recent Trends in Programming languages · Vol. 5, Issue 2, 2018 · pp. 31–35 Read article
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Digital Twin-Driven Structural Health Monitoring and Energy Management of IoT-Enabled Energy-Storing Polymer Composites Using Explainable Machine Learning
Abstract: Energy storing polymer composites are widely utilized in intelligent structural systems, because of their mechanical and electrochemical properties. But, under varying thermo-mechanical and environmental conditions, it is important to have accurate degradation monitoring for real-time industrial process is challenging. In this work, an explainable machine-learning framework for structural health monitoring and adaptive energy management of polymer composites with energy storage capacity is proposed in an IoT environment with the help …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Advance in Spatial Statistics for Environmental Data Analysis
Abstract: Recent advancements in spatial statistics have significantly enhanced the analysis of environmental data, addressing complex spatial dependencies and offering robust methodologies for environmental monitoring, modeling, and decision-making. This abstract highlights key developments in the field, emphasizing their applications and impact. Geostatistical Methods, Improved geostatistical techniques, such as kriging and co-kriging, provide more accurate predictions of environmental variables by incorporating spatial correlation structures. Advanced kriging variants, including Bayesian kriging and machine …
Published in Research & Reviews : Journal of Statistics · Vol. 12, Issue 3, 2023 · pp. 35–39 Read article
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Machine Learning-Based Structure–Property Quantification of Advanced Polymer Composites
Abstract: Advanced polymer composites are widely used in high-performance engineering due to their superior mechanical and multifunctional properties. Accurate structure–property quantification is essential for efficient material design and reducing experimental costs. Existing Machine Learning (ML) approaches often exhibit limited predictive generalization due to inadequate feature discrimination and suboptimal hyperparameter tuning. To address these limitations, the proposed method enhances the ability to capture the complex nonlinear interactions among composite structural descriptors. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization
Abstract: This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 114–129 Read article
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A Random Forest Approach to Navigating Cryptocurrency Market Fluctuations
Abstract: This study looks at the main elements influencing daily price variations to improve our analysis and prediction of Bitcoin values. Our forecasting algorithm is based on comprehensive data that we have collected and analyzed over the last few years. Because the Random Forest algorithm provides more accurate forecasts than previous techniques, that is why we chose it. Predicting the price swings of cryptocurrencies, like Bitcoin, can be challenging due to …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 7–11 Read article