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796 articles for “Model efficiency”
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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Extraction Properties of Mangifera indica Seed Kernels: A Comprehensive Analysis of Their Industrial Potential
Abstract: Mango (Mangifera indica) is widely regarded as one of the world's finest fruits, with a rich nutritional profile, including fiber, riboflavin, carotene, and ascorbic acid. Among its lesser-known components, the mango seed kernel offers significant nutritional and industrial value. Mango kernels are composed of protein, fat, carbohydrates, crude fiber, and ash, and contain bioactive compounds such as polyphenols, phytosterols, and tocopherols. The fat extracted from mango seed kernels has shown …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 22–28 Read article
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Design and Estimation of Biogas Plant For Canteen Waste: A Case Study of RD’s Rajgad Technical Campus, Dhangwadi, Bhor, Pune
Abstract: Today's economy and society rely on energy. In the end, conventional fossil fuels like oil will run out, and an alternate primary energy source will be required to close the widening gap between rising demand and declining supply. Biogas is a great energy source in light of rising petroleum prices, declining foreign exchange reserves, and the rupee-dollar exchange rate. Organic matter breaks down to produce biogas, a fuel. The primary …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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Dynamic Cost Projection: Enhancing BIM-Integrated Estimation and Budgeting in Construction Projects
Abstract: In the realm of construction project management, the integration of Building Information Modeling (BIM) with dynamic cost projection tools represents a pivotal advancement. This paper explores the synergy between BIM and cost estimation, emphasizing their collective potential to revolutionize project budgeting. By harnessing real-time data and predictive analytics, BIM facilitates accurate and proactive cost projections throughout the project lifecycle. This integration not only enhances cost estimation precision but also fosters …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 2, 2024 · pp. 1–10 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
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AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations
Abstract: Dynamic and unpredictable characteristics of environmental processes create challenges in their management and regulation. Artificial intelligence (AI) offers a powerful solution for addressing these complexities.AI tools have become more and more popular across a range of fields and research domains due to their efficient development and rapid growth. We analyse key trends in AI applications, including predictive analytics for climate modelling, automated monitoring of biodiversity, and smart resource management. The …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Statistical Modeling of Heat Transfer and Fluid Dynamics: Application in Mechanical Engineering Design
Abstract: Understanding and optimizing the intricate processes involved in heat transfer and fluid dynamics—two concepts essential to mechanical engineering design—require statistical modeling. Engineers can forecast, regulate, and enhance the performance of systems including heat exchangers, turbines, cooling mechanisms, and different fluid machinery by using statistical approaches. In order to address uncertainties, variability in material properties, boundary conditions, and operational parameters, this work investigates the integration of statistical modeling tools in the …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 2, 2024 · pp. 18–22 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Digital Frontiers in Life Sciences: The Transformative Role of Computing in Modern Biology
Abstract: The integration of computers in the biological sciences has revolutionized research and experimentation, facilitating advancements in areas such as genomics, bioinformatics, systems biology, and ecological modeling. The ability to process vast amounts of biological data efficiently has transformed how scientists study complex biological systems and phenomena. Computational tools enable the analysis of DNA sequences, protein structures, metabolic pathways, and ecological dynamics, which were previously beyond the reach of traditional laboratory …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Experimental Investigation of Aerodynamic Characteristics of Dimpled 3D Aircraft Wing
Abstract: There is a strong demand for innovative designs, optimization of the aircraft components for their parts with respect to design, etc. One such innovation is by introduction of dimples in the wing of the aircraft. To study the effect of geometry modification of the wing, the present work compares the aerodynamic efficiency, ratio of lift to drag coefficients, along with different aerodynamic characteristics of an Inward and outward circular dimpled …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 1, 2023 · pp. 11–22 Read article
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Study of Perovskite (CH3NH3PbI3) Solar Cell using CuI (Copper Iodide) as Hole Transport Layer (HTL) at different thickness of HTL layer
Abstract: While solar energy is a viable option, future clean energy solutions may require other energy sources. Renewable electricity sources are known for being affordable, easy to access, and not producing greenhouse gases. Photovoltaic cells, which turn sunlight into electrical power, are a good choice. Over the last twenty years, advancements in photovoltaic technology have lowered costs and improved the efficiency of solar cells. Perovskite materials, recognized for their unique crystal …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 2, 2024 · pp. 1–11 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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Energy-Efficient Design Strategies for Sustainable Machine Tool Development
Abstract: The design of energy-efficient machine tools is essential for promoting sustainable manufacturing, as it addresses the significant energy consumption and carbon emissions generated by these tools in industrial settings. This study investigates innovative design approaches that enhance energy efficiency, with a focus on lightweight materials, improved drive systems, smart control frameworks, and methods for recovering energy. Implementing lighter structural materials allows machine tools to operate with less force, which in …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 30–34 Read article
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ANN Approach to Forecasting the Strength of Nano Silica Incorporated Geopolymer Composite
Abstract: Coal and steel industry by-products, such as fly ash (FA) and blast furnace slag (GGBS), have gained significant attention as precursors for geopolymer concrete (GPC) due to their high aluminosilicate content, offering a sustainable alternative to conventional cement. Nano silica (NS), recognized for its exceptional pozzolanic activity and ability to refine microstructure, has shown potential to enhance the mechanical and durability properties of GPC. This study investigates the influence of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 267–278 Read article