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579 articles for “Learning Techniques”
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Advances in Analytical Chemistry Research Methodology: Trends and Applications
Abstract: Analytical chemistry is critical to scientific study because it allows for the accurate identification, measurement, and characterization of chemical compounds. Recent advances in methodology have improved accuracy, sensitivity, and efficiency, with techniques such as High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) spectroscopy transforming analytical procedures. The combination of Artificial Intelligence (AI) and Machine Learning (ML) has enhanced data processing, pattern recognition, and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 10–18 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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Survey Paper on Multilingual Live Call Translation Using Deep Learning
Abstract: This research work surveys cutting-edge language translation technologies, including multi-lingual, real-time translation, voice recognition, speech-to-text conversion, and transcription in the hearing process. The study explores the complex mechanisms behind voice call language translation, focusing on sophisticated machine learning models integrated with cloud-based or local applications to facilitate seamless communication across language barriers. Furthermore, conducting research in live communication analyzes the complexity of text and voice techniques to deliver translated content …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 13–21 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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A Novel Approach to Fingerprint Authentication Using Histogram Oriented Gradients for Feature Extraction and Machine Learning Convolution Neural Network for Classification
Abstract: With applied biometrics, it is possible to identify a person by examining a feature vector of attributes derived from their physical and behaviour characteristics. In biometrics, fingerprints have become one of the most famous and well known techniques of identification and authentication. In light of technological advancements and safety, fingerprint recognition has been successfully used in a variety of Civil, Defence, and Commercial applications for more than a decade. The …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 1–12 Read article
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Demand Forecasting for Perishable Food Commodities Using Data Analytics
Abstract: This paper introduces a comprehensive study aimed at enhancing the forecasting of perishable food item demand. Focusing on solving the critical issue of waste management within the supply chain of food products, the research undertakes a comparative analysis of various machine learning models. The development of an optimized model that is capable of accurately forecasting the demand for perishable food items is the focus of this research. The research includes …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 3, 2024 · pp. 27–37 Read article
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Optimizing Sentiment Analysis with Naïve Bayes and Random Forest Techniques: A Result-based Approach
Abstract: In the increased digitalization, the sentiment analysis and classification have evolved as an eminent area to determine the polarity of positive, negative, and neutral reviews of the customers and users on products. It is an integral application field that employs supervised learning, Machine Learning, and Natural Language Processing concepts. The proposed Semantic Analysis and Classification using Naive Bayes and Random Forest system accomplishes the sentiment polarity by classifying the user …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 46–57 Read article
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Mindwell: A Psychological Guide for Well-being
Abstract: Mental health is a crucial aspect of overall well-being, yet access to professional therapy remains a significant challenge for many individuals due to various barriers, including cost, availability, and stigma. This research aims to develop an accessible and effective mental health therapy chatbot, named Mindwell Psychology, leveraging the power of large language models (LLMs) and state-of-the-art natural language processing techniques. The primary objective of this study is to create a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 63–77 Read article
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Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
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DRIVE-DEFENDER: A Driver Safety-oriented Alcohol and Drowsiness Detection System
Abstract: DRIVE-DEFENDER presents a pioneering approach in driver safety through the development of a real-time machine learning system for alcohol detection. The detrimental impact of alcohol-impaired driving on road safety necessitates efficient detection mechanisms. Current methodologies are often hindered by their cost, invasiveness, and reliance on specialized sensors. DRIVE-DEFENDER utilizes a camera for recording the face of the driver in real time, employing image processing techniques to identify facial landmarks. These …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 15–26 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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NLP Revolution in Education Feedback Analysis: Trends and Challenges
Abstract: Artificial Intelligence (AI) is a rapidly growing area of study in many domains like research and business. Various subsets of AI, such as Machine Learning, Deep Learning, and Natural Language Processing (NLP), are employed to address diverse aspects of data processing and modeling. This review is about the impact of AI on the education system and students feedback for the analysis is required for the enhancement of the technology used …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 21–25 Read article
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Sky Scanners: Using satellite remote sensing to figure out what Earth is like
Abstract: Satellite remote sensing has changed the way we look at, study, and learn about the Earth changing systems. Orbiting sensors take data from many different spectral bands, giving us constant, large-scale information about land, oceans, and the atmosphere. This study discusses the fundamental concepts of satellite remote sensing, including the various types of sensors, methods for data acquisition, and techniques for interpreting images. It talks about important uses like monitoring …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 22–33 Read article
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Phisherman: A Phishing Email Detection Browser Extension
Abstract: Phishing attacks continue to pose significant security risks, exploiting email as a primary vector to deceive users and compromise sensitive information. To counter these threats, Phisherman presents a sophisticated, real-time phishing detection system that integrates both rule-based methods and deep learning for heightened accuracy. Built as a cross-browser extension, compatible with Chrome, Firefox, and Edge through the WebExtension API, Phisherman combines traditional verification checks, such as DNS blacklisting, SPF, DKIM, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 99–105 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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Advances in Trauma Surgery: Innovations, Historical Perspectives, and Future Directions in Patient Care
Abstract: Trauma care has evolved significantly over the past few decades, with innovations in surgical techniques, medical devices, and procedural protocols enhancing the outcomes for patients experiencing life-threatening injuries. This article explores recent surgical innovations in trauma care, focusing on advancements in hemorrhage control, rapid trauma intervention, and the use of novel technologies to improve surgical precision and recovery. Key developments such as hemostatic agents, minimally invasive techniques, and the integration …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 Read article