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1193 articles for “agriculture chat bot.csv dataset”
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 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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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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IoT Meets Cloud: A Smart Integration
Abstract: Digital transformation and industry change are fueled by a combination of cloud computing and the Internet of Things (IoT). While cloud computing gives scalable resources for processing, storage, and advanced analytics, IoT allows devices to gather, distribute, and analyze data in real time. This connection supports big data and machine learning-driven applications and enhances data management and operational efficiency across industries, such as smart cities, industrial automation, healthcare, and agriculture. …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 26–34 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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A Comprehensive Survey on Detection of Video Transitions
Abstract: Video shot boundary detection (SBD) is a fundamental task in the field of video processing and analysis. It plays a critical role in various video applications such as content-based video retrieval, video indexing, editing, summarization, and browsing. Identifying shot boundaries helps segment a continuous video stream into distinct shots, each representing a meaningful visual unit. This segmentation is essential for organizing and interpreting video data efficiently. This study provides an …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 17–26 Read article
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Role of Artificial Intelligence in Transforming Personalized Learning in Education
Abstract: Artificial Intelligence (AI) is revolutionizing personalized education by tailoring learning experiences to meet each student's unique needs. Through advanced algorithms, AI can adapt educational content to align with individual learning speeds, preferences, and styles. Technologies such as adaptive learning systems, smart tutoring tools, and AI-powered assessments offer instant feedback and assist teachers in quickly identifying areas where students may be struggling. Additionally, predictive analytics help anticipate student outcomes, enabling early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Hybrid DL-ML Approach for Android Malware Detection
Abstract: The widespread growth of Android malware has become a significant mobile security threat during the past few years thus requiring the development of strong detection solutions. The primary tool applied in this research for Android malware detection consists of app permissions. The main indicator in the dataset for identifying malicious and benign applications functions through displaying application permission information. The evaluation of particular permission relationships with malware behavior leads to …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 18–25 Read article
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Artificial Intelligence and Personalized Learning
Abstract: Artificial Intelligence is transforming education by delivering customized learning pathways that align with each learner’s unique abilities and areas for improvement. Traditional teaching often struggles to meet individual needs; however, AI-powered systems analyse learning patterns in real time, ensuring customized lessons. Virtual tutors and AI chatbots provide instant feedback and 24/7 support, improving comprehension. Gamified learning, combined with augmented and virtual reality, transforms education into a more engaging and enjoyable …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 11–18 Read article
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Remote Sensing and GIS-Based Approaches for Groundwater Contamination Assessment: A Comprehensive Review of Methods, Sources, and Emerging Trends
Abstract: Groundwater contamination poses a serious threat to sustainable water resources, especially in developing regions with limited monitoring infrastructure. This review provides an in-depth analysis of remote sensing (RS) and geographic information system (GIS) techniques applied to identify, monitor, and assess groundwater contamination. The study categorizes major sources of pollution, including industrial effluents, agricultural runoff, and geogenic inputs and examines how multispectral and hyperspectral satellite data contribute to indirect mapping of …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 39–49 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
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IoT-Based Real-Time Weather Monitoring System
Abstract: In the evolving landscape of the Internet of Things (IoT), real-time environmental monitoring has become increasingly vital across various domains, including agriculture, smart cities, and climate research. This study presents the design and implementation of an IoT-based real-time weather monitoring system that utilizes the ESP32 microcontroller in conjunction with AWS cloud services. Temperature and humidity data are captured using onboard sensors and transmitted using the MQTT protocol to AWS IoT …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 19–25 Read article
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IoT Based Weather Monitoring System
Abstract: The Internet of Things (IoT)-Based Weather Monitoring System is developed to provide accurate, real- time monitoring of essential environmental parameters, including temperature, humidity, and atmospheric pressure. The system integrates high-precision sensors with a microcontroller, enabling continuous data acquisition from the surrounding environment. Collected data is transmitted wirelessly to a dedicated IoT platform via an internet connection, allowing remote users to access and visualize the information through web or mobile interfaces. …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 26–34 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Chewable Healthcare: The Rising Impact of Gummy Supplements in Modern Medicine
Abstract: Gummy supplements, a chewable dosage form historically associated with pediatric vitamin products, are increasingly recognized as a versatile platform for delivering a wide range of nutraceutical and pharmaceutical agents. Their consumer appeal lies in their palatability, convenience, and the ability to overcome swallowing difficulties—a significant barrier to adherence in multiple patient populations. Recent advances in formulation science have expanded the potential of gummy supplements beyond basic vitamin delivery to include …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 52–68 Read article