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567 articles for “model evaluation”
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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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AI-Driven Exam Evaluation Systems: Challenges, Innovations, and Future Directions
Abstract: A proposed AI system is used to grade exams automatically. It addresses inefficiencies in human assessment. A GPT model trained on graded replies is used for evaluation, and TrOCR is used for precise handwritten text recognition. Efficiency and less bias are provided by this method, although there are still issues. More work is needed to assess open-ended questions and make sure they are understandable. To automate many aspects of exam …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 7–13 Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 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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A Trust-Enhanced Security Architecture for Authenticating Customer Records in Banking Institutions
Abstract: The growing digital disruption of banking and financial services has completely altered the face of customer onboarding, money transactions, and financial service deliveries. Even as digital technologies provide unparalleled levels of efficiency and accessibility for consumers of financial services, they have also presented new challenges that are equally daunting. Among the growing number of financial threats that digital technology has spawned is the risk of synthetic identity fraud. Unlike identity …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 16–22 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Identification and Prioritization of Critical Erosion Prone and Water Potential Areas of Manandragarh Watershed Using HEC-HMS for Management
Abstract: This study was carried out at Indira Gandhi Krishi Vishwavidyalaya, Raipur (CG) on hydrological modelling and development of soil and water conservation plan for critical erosion prone and water potential sub-watersheds of Manendragarh watershed of upper Hasdeo subbasin in Chhattisgarh using Hydrological Engineering Centre-Hydrological Modelling System (HEC-HMS). The Hydrological Engineering Centre-Geo Hydrological Modelling System (HEC-Geo HMS) was utilized for developing the model setup, while the HEC-HMS model was employed to …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 1, 2025 · pp. 26–44 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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A Real-time Visualization Framework to Enhance Prompt Accuracy and Result Outcomes Based on the Number of Tokens
Abstract: In the rapidly evolving domain of artificial intelligence (AI), the efficacy of user-generated prompts has emerged as a critical factor influencing the quality of model-generated responses. Current methodologies for prompt evaluation predominantly rely on post-hoc analysis, which often leads to iterative prompting and increased computational overhead. Furthermore, the challenge of “prompt hallucinations,” where AI models produce irrelevant or nonsensical responses, persists as a significant impediment to effective AI utilization. The …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 45–53 Read article
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Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Cardiovascular Modeling with Computational and Mathematical Methods
Abstract: The cardiovascular system, a complex network responsible for delivering life-sustaining oxygen and nutrients throughout the body, is a prime target for advanced understanding and improved therapies. Due to the inherent difficulties in directly observing internal physiological processes and the complexities of interactions within the system, computational and mathematical modeling have emerged as powerful tools in cardiovascular research. This article explores the significance of these methods in unveiling the heart's secrets …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 11–21 Read article
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Assessing Air Quality, Climate Change, and Migration Dynamics in Delhi NCR: A System Dynamics Approach
Abstract: As climate change accelerates and environmental degradation worsens, urban centers like Delhi NCR are under increasing pressure from internal migration. Poor air quality—especially in rural and peri-urban regions—emerges both as a driver of out-migration and a deterrent for in-migration to already burdened cities. This study develops a system dynamics (SD) model that integrates climate variables, air pollution metrics, economic indicators, governance quality, and migration behavior to simulate population flows into …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 7–11 Read article
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A Sustainable EOQ Model for Declining Products Incorporating Cubic Demand, Variable Deterioration, Partial Backlogging, and Carbon Emission Optimization
Abstract: In this paper proposes a sustainable Economic Order Quantity (EOQ) model for inventory systems involving decaying items under cubic time-dependent demand, variable decaying rates, and partial backlogging while absolutely considering carbon emission costs. The model reflects practical market actions where demand initially increases and afterwards declines over time, and decay depends on the age of the item. To demonstrate the current model's applicability as well as evaluate the trade-off between …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Three Techniques for DC Thevenin Resistance Using Pspice Simulation
Abstract: A time-domain method for certain types of excitations is proposed to determine Thevenin equivalent circuit for a circuit with resistors and dependent/independent sources. SPICE/Pspice model descriptions for resistors at constant temperature and dependent source are used. Instead of making the energy sources zero (as in frequency domain) the sources in time domain are described using model description cards available for time-domain current/voltage sources at the same time evaluating circuit for …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Evaluation of Shear Walls and Bracings in Irregular Buildings Under Seismic Load
Abstract: The structural integrity and stability of irregular buildings under lateral forces such as wind and seismic loads pose significant challenges in modern construction practices. Irregularities in a building & geometry and mass distribution can lead to uneven force distribution, making the structure more vulnerable to lateral displacement and potential failure. To enhance the resilience of such structures, shear walls and bracing systems are commonly employed to improve lateral load resistance. …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 2, 2025 · pp. 22–28 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article