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796 articles for “Model efficiency”
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Automatic Detection of Misplaced Tubes and Catheters Using EfficientNet B7
Abstract: Tube misplacement can lead to complications in patients together with serious medical malpractice cases. Intubation and the insertion of various medical tubes are employed to safeguard the airways of critically ill patients. Critically unwell patients undergo intubation, with the insertion of various medical tubes to safeguard their airways. The nasogastric tube serves the purpose of providing nutrition, while the central venous catheter finds application in a range of medical procedures. …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Lightweight Models for Per-PC Energy Consumption Forecasting: Comparative Study with ML and DL Approaches
Abstract: We have collected primary data from automated logging of parameters like CPU utilization, estimated power, active or idle state, user logging activity, and the type of day. Additionally, survey data showed user awareness, energy-saving behaviour, and PC usage patterns. The data is pre-processed and merged by applying processes such as data cleaning, normalization, and feature extraction, i.e., determining the peak active timings and downtime. Developed lightweight prediction models based on …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
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A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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A Comparison of Different Generative AI Models
Abstract: Generative models have significantly advanced the field of artificial intelligence by allowing machines to produce complex and realistic outputs such as images, text, and other forms of data. Among the leading frameworks in this domain are generative adversarial networks (GANs), variational autoencoders (VAEs), and architectures based on Transformers. Each model offers specific benefits and drawbacks concerning design structure, training demands, and range of applications. This paper provides a detailed comparison …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 16–22 Read article
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Improving Indoor Room Air Conditioning Using PID Control
Abstract: Energy use in building air conditioning contributes significantly to power demand; therefore, in this work, we propose an improved methodology to achieve comfort conditions through PID control assistance. The project develops a mathematical model based on analytical heat transfer equations for comfort conditions by fulfilling the Fanger equation, considering environmental parameters (ambient temperature), metabolic rate, and people’s physical activity (internal heat generation) to reduce power consumption and improve energy efficiency. …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 1–21 Read article
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Performance Analysis of Dual Junction Solar Cell Devices utilizing Subcells of In0.51Ga0.49P and GaAs to Study Key Solar Cell Parameters via TCAD based Simulation
Abstract: In the present work, a multi-junction solar cell was designed to obtain better performance over single-junction solar cells. The proposed structure is composed of different layers of diverse semiconductor materials stacked on each other. Here, an In0.51Ga0.49P/GaAs double-junction solar cell was outlined as having a distinctive composite material (GaAs) as the tunneling junction. To optimize the solar cell's effectiveness, In0.47Ga0.15Al0.37P was used in the window layer and the back-surface field …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 829–837 Read article
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Turbulence Exploitation in Offshore Wind Farms: Improvement in Generated Power
Abstract: The limited space available for wind energy projects highlights the importance of improving the efficiency of wind farms, like the exploitation of turbulent wakes. In this work, we analyze the available energy associated with the turbulent wakes generated by offshore wind turbines at various downstream distances using a computational fluid dynamics (CFD) program (Autodesk). Classical wind conditions for offshore wind farms are established for the probability distribution of wind speed, …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 2, 2025 · pp. 22–35 Read article
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Advancements in Electromechanical Modeling for Energy Harvesting and Actuators in Robotics and Design Engineering
Abstract: This article examines the expanding field of electromechanical modeling, highlighting the integration of energy harvesting, actuator behavior, and magnetic/electromagnetic analyses in the design and production of electromechanical systems. It discusses the application of the Galerkin method for modeling intricate vibrations and torque generation, with a particular focus on its use in actuators for robotics and induction motors. Significant advancements in energy harvesting methods, especially those utilizing mechanical vibrations, have led …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 21–25 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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Kick Tolerance Modeling in Well Design and Drilling: A Comprehensive Technical Review
Abstract: Kick and blowout events in drilling operations can lead to significant losses of equipment, and in some cases, human lives. Oil and gas companies, along with oilfield service providers involved in drilling operations, face severe penalties and sanctions following such incidents. Research has demonstrated that incorporating kick tolerance models during the well planning and drilling stages can mitigate the risk of blowouts during secondary well control operations. This study reviews …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 33–58 Read article
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Implementation of Energy-efficient Axial Fans for Air Handling Unit Using AI Model
Abstract: This research explores the integration of energy-efficient axial fans in Air Handling Units (AHUs) within a large automotive manufacturing facility to enhance HVAC (heating, ventilation, and air conditioning) performance and reduce energy consumption. Standard AHUs in the facility’s clean rooms and other spaces utilize traditional blower fans, which primarily rely on static pressure, limiting their efficiency. By replacing these with electronically commutated (EC) axial flow fans, which leverage both static …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 11, Issue 3, 2024 · pp. 28–34 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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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are …
Published in Recent Trends in Electronics Communication Systems 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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Leveraging Generative AI for Test Case Creation in Complex Systems
Abstract: Modern software systems exhibit increasing complexity, demanding sophisticated testing methodologies to ensure reliability and functionality. Traditional manual testing approaches often struggle to keep pace with this complexity, leading to inadequate test coverage and increased risk of unforeseen issues. This study explores the potential of Generative AI (GAI) in revolutionizing test case creation for complex systems. We delve into the practical application of GAI techniques, such as Variational Autoencoders (VAEs) and …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 16–22 Read article