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563 articles for “decision analysis”
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Face and Iris based Multimodal Person Identification using Likelihood Ratio Score Fusion Approach.
Abstract: AbstractThe aim of this paper is to propose a multimodal biometric system where likelihood ratio score fusion technique has been used to combine face and iris uni-modal biometric system outputs. Active Shape Model (ASM) has been used to extract the facial features and standard methods have been applied to effectively extract the human iris features. To evaluate the output of each individual modality of face and iris, Discrete Hidden Markov …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 3, 2015 · pp. 60–67 Read article
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Male Involvement in Family Planning in Harari Regional State, Ethiopia, 2019
Abstract: Introduction: Family planning (FP) programmes should always be a concern for both men and women. FP should be the business for both male and female. However, most of the FP programmes focus on only females as if it is only the business of female, with little or not at all attention given to the role of male that play the overall decision regarding FP. Objective: To assess male involvement in …
Published in Research and Reviews: A Journal of Medicine · Vol. 10, Issue 1, 2020 · pp. 5–10 Read article
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House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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ExploroBot: A Versatile Robotic Explorer
Abstract: ExploroBot: A versatile robotic explorer is a cutting-edge robotic platform designed for exploration and surveillance applications. Equipped with six battery-operated motors for mobility and an Arduino UNO microcontroller as its brain, the rover integrates ultrasonic sensors and two ESP32 CAM modules for obstacle avoidance and live footage streaming. With precise control mechanisms and advanced sensor technologies, ExploroBot: A versatile robotic explorer offers a versatile solution for navigating complex environments while …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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An Evaluation of Versatile CNC Machines for Tabletop Applications
Abstract: The tabletop CNC provides a comprehensive analysis of computer numerical control (CNC) machines tailored for tabletop use. In today's rapidly evolving manufacturing landscape, compact and adaptable CNC systems have gained prominence due to their potential to revolutionize small-scale production and prototyping. This research examines a range of versatile CNC machines, assessing their capabilities, precision, ease of use, and suitability for various tabletop applications. By exploring key factors such as size, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 88–104 Read article
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Ranking of Epoxy/Kota Stone Dust/Fly Ash Composite Using Integrated AHP-TOPSIS Approach
Abstract: The generation of industrial waste is a significant contributor to environmental pollution. The stone industry is no exception to this, and it is known to produce a significant amount of waste. The Kota Stone Industry in India is one such industry that generates waste. This research article focuses on composite material selection for mechanical and structural applications by fabricating epoxy composites reinforced with Kota stone dust and fly ash using …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 36–42 Read article
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Use of Multi Criteria Decision Making Methods in Assessment of Occupational Safety and Health
Abstract: Assessment of Occupational Safety and Health (OSH) of process plants is an important aspect in safety management. Quantitative assessment is necessary to compare the OSH status of different plants. For this purpose, usually, an evaluation team is constituted which evaluates the OSH performance based on the available OSH related information. The evaluation team arrives at a decision through discussions and mutual agreement. However, while working in a group, there always …
Published in Journal of Industrial Safety Engineering · Vol. 6, Issue 3, 2019 · pp. 25–34 Read article
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Accelerate Drug Development with Pharmacokinetic Softwares
Abstract: During continuously evolving technologies and mechanized equipments, there has been a tremendous growth in the pharmaceutical sector over the past few decades. New technologies, software, devices, and techniques are being developed or researched upon with each passing day. By leveraging pharmacokinetic software, researchers can efficiently analyze vast datasets from preclinical and clinical studies, extracting actionable insights that inform decision-making early in the development cycle. This predictive capability not only accelerates …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Analyzing Potential Leads Data to Improve Marketing Strategies
Abstract: To develop a lead scoring model using multiple machine learning models and create a user-friendly web application, the first step is to clearly define the problem and collect relevant data from various sources such as CRM, website, social media, email campaigns, etc. After cleaning and pre-processing the data, identify the essential features that can affect the lead score and split the data into training and testing sets. Next, select a …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 18–25 Read article
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The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big data analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support highly informed decision-making and truly superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of BDA within the airline industry. …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 · pp. 13–18 Read article
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Call Admission Control in ATM Networks using Interval Arithmetic CEN
Abstract: Call admission control (CAC) is one of the most fundamental preventive congestion control mechanisms in asynchronous transfer mode (ATM) networks. Call admission control is further complicated by the diverse mix of traffic types and service requirements and by the increasing speed of transmission. In this project, the focus is on a call admission control with interval arithmetic coulomb energy network, a generalization of coulomb energy network (CEN), which can handle …
Published in Journal Of Network security · Vol. 2, Issue 3, 2014 · pp. 12–21 Read article
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Portable and User-friendly Air Watch System Based on IoT
Abstract: The internet of things (IoT) based air monitoring system is a novel approach to monitoring air quality in real time. With the increasing concerns over pollution and its impact on human health, our IoT-based air monitoring system offers a solution to gather and analyze air quality data efficiently. The system utilizes IoT devices like Node MCU and sensors like MQ135 and DTH11 to collect data such as temperature, air quality, …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 3, 2024 · pp. 19–27 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article