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449 articles for “machine learning applications”
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Revolution of Artificial Intelligence and Machine Learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are profoundly transforming various industries by introducing groundbreaking technologies such as deep learning, federated learning, reinforcement learning, and natural language processing. These innovations are not only reshaping the way organizations operate but are also opening new avenues for solving complex problems across diverse sectors, including healthcare, finance, transportation, and more. This study provides a comprehensive exploration of these emerging technologies, emphasizing their practical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 38–44 Read article
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Polymer Nanocomposites and Functional Materials for Lithium-Ion Battery Supercapacitor Hybrid Energy Storage Systems: Materials, Interfaces, and Performance Perspectives
Abstract: The growing need for high-performance energy storage solutions in electric vehicles, renewable energy applications, portable electronics, and other sectors has accelerated research and development efforts in Lithium-Ion Battery–Supercapacitor Hybrid Energy Storage Systems (HESS). By combining the high energy density of lithium-ion batteries with the high power density and fast charge/discharge characteristics of supercapacitors, HESS offers a promising approach to meeting diverse energy storage requirements. Nevertheless, several critical challenges remain that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 96–113 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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The Emergence of Personal Desktop Voice Assistants for Effortless Task Management
Abstract: In an era defined by rapid technological advancement, desktop voice assistants have emerged as crucial tools, not only for enhancing productivity but also for fundamentally reshaping digital interactions. This study delves into the transformative potential of voice-enabled artificial intelligence in task automation, emphasizing its profound impact on efficiency, accessibility, and overall user experience. By harnessing the power of natural language processing and machine learning, these desktop assistants facilitate hands-free operation, …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 11–16 Read article
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Myco-Engineering Systems: Harnessing Fungal Networks for Carbon Sequestration and Sustainable Ecosystem Restoration
Abstract: Fungal organisms play a foundational role in global ecosystem stability, particularly through their contributions to nutrient cycling, soil regeneration, and carbon sequestration. Recent scientific advances have highlighted the potential of fungal mycelial networks as natural bioengineered systems capable of supporting sustainable environmental restoration. This paper introduces the concept of Myco-Engineering Systems, an interdisciplinary framework that integrates fungal biology, environmental science, and artificial intelligence (AI) to enhance carbon capture and ecosystem …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites
Abstract: Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability. This study developed an artificial intelligence-assisted framework for balanced composite formulation. Experimental data of agricultural biomass reinforced polymer composites were gathered, harmonized and validated using leakage controlled validation. The mechanical and physical properties were predicted by artificial neural networks and conventional regression models. Explainable analysis …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Advanced Fiber-Reinforced Polymer Composites: Processing, Nano-Modified Adhesive Technologies, Interfacial Engineering, Durability, and Structural Applications—A Comprehensive Review
Abstract: Fiber reinforced polymer (FRP) composites are considered to be one of the most universal categories of advanced engineering materials owing to their unique properties such as outstanding strength-to-weight ratio, corrosion resistance, fatigue durability, and wide opportunities for design. Innovations in the fields of fiber reinforcement, polymer matrix system, composite manufacturing technologies, and nano-modified adhesives technology have greatly extended the range of applications of this type of materials in aerospace, automotive, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 980–990 Read article
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Time Series Sales Forecasting Using ARIMA Model
Abstract: Sales forecasting is a critical application in various industries and presents one of the most challenging problems worldwide. One method of prediction involves identifying patterns in historical data, where the outcome is known in advance and can be validated using more recent data. If a pattern consistently leads to the same outcome, it can be considered a genuine relationship. This method is highly flexible and can be utilized with diverse …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 17–27 Read article
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Self-Healing Structural Polymer Composites Incorporating Bio-Inspired Nanofillers
Abstract: Self-healing polymer composites become an attractive family of intelligent materials that are capable of autonomously repairing damage, which will enhance their durability, reliability and service life in extreme engineering applications. The materials are based on the principles of nature, using the nanofillers that are derived from biological systems to improve mechanical properties and self-healing capabilities by utilizing hierarchical structures and multifunctional interface interactions. The recent developments on the formulation of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Calorie Measurement and Food Recognition Using Machine Learning
Abstract: Nowadays, all over the world most people are suffering from different types of diseases or obesity. This is because of bad food habits or eating food without knowing the calorie and other sources from the foods. Precise techniques for gauging food and energy consumption play a vital role in addressing obesity. Offering users or patients accessible and smart solutions to assess their food intake and gather dietary information constitute valuable …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 1–9 Read article
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Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Design And Implementation Of A Multi-Modal Mobile Application Safety Analytics Utilizing Nlp
Abstract: This study suggests a multi-modal mobile app safety analytics platform that uses natural language processing (NLP) to handle voice, text, and SOS messages. For effective intent recognition and decision-making, the platform processes all messages in a standard text or SOS flag format. Tokenization and normalization are used to process text communications, whereas noise reduction and text conversion are used to handle voice messages. For a quicker response, the SOS messages …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Human Following Robot Using Arduino Uno
Abstract: A human-following robot is a mobile autonomous system designed to detect, track, and follow a specific individual in real-time while navigating through dynamic environments. This feature is essential for various applications, including delivery services, healthcare assistance, personal support, and collaborative industrial operations. It enhances efficiency, safety, and user experience by enabling intelligent and responsive interactions, making it an asset in both commercial and personal environments. The robot integrates cameras, LiDAR, …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 26–31 Read article
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Intelligent Decision Support System for Production Planning and Control in an Automotive Assembly Line
Abstract: The automobile industry has realized the importance of Intelligent Decision Support Systems (IDSS) to improve production planning and control on assembly lines. In the context of automobile manufacturing, this review paper examines the most recent developments, methodology, and applications of IDSS. Key trends, obstacles, and possibilities are discovered through an in-depth examination of the literature. Examining real-world case studies and success stories, the integration of artificial intelligence (AI) and machine …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 16–21 Read article
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Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article