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321 articles for “Scaling Model”
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A New Computational Method for Dust and Gas Dynamics in Protoplanetary Discs
Abstract: The simultaneous evolution of dust and gas in protoplanetary discs regulates essential events in planet formation, such as dust accumulation, migration, and the initiation of gravitational instabilities. Nevertheless, precisely modelling this interaction continues to provide a significant computing problem owing to the extensive variety of spatial and temporal scales involved. In this study, we introduce an innovative computational framework for simulating dust-gas dynamics in protoplanetary discs, integrating a two-fluid hydrodynamical …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 35–46 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Introduction to Biological Networks and their Contributions to Systems Biology
Abstract: Biological networks provide a conceptual framework to represent and analyze the intricate interconnections among the numerous components that make up living systems. This review paper elucidates the foundational principles of networks and their diverse applications in systems biology, highlighting their crucial role in understanding the inherent complexity of biological processes. Utilizing graph theory, these networks represent entities like genes, proteins, and metabolites as nodes, with their interactions depicted as edges. …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 53–70 Read article
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Convolutional Neural Network Based Ripeness Detection of Fruits
Abstract: The accurate and efficient assessment of fruit ripeness plays a crucial role in ensuring the quality of fruits and optimizing supply chain management. This paper presents a novel approach for the automated detection of apple and banana ripeness using Convolutional Neural Networks (CNNs). The suggested method supports the capability of CNNs to learn hierarchical features from images, variations in color and shape associated with different ripeness stages. The online dataset …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 2, 2024 · pp. 30–36 Read article
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Adaptive Task Scheduling and Resource Optimization Using AI Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, specialized schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that can learn, forecast, and react to the actual real-world conditions in the system. Artificial intelligence middleware is also an attractive solution to this …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 23–31 Read article
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Design of Solar and Wind Power Generation System
Abstract: AbstractIn current year’s generation of electricity victimization, the various kinds of renewable sources square measure specifically evaluated within the economic performance of the overall instrumentality. Solar power and wind power have received considerable attention worldwide. The bestowed methodology is applied to gauge the potential of Solar (photovoltaic) –wind hybrid system to provide electricity for a community and different state. It has helped in reducing pollution and thereby overcoming global warming. …
Published in Trends in Opto-electro & Optical Communication · Vol. 8, Issue 3, 2018 · pp. 8–16 Read article
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A Five-Layer Architectural Framework for Sustainable and Scalable AI Systems
Abstract: Artificial Intelligence (AI) is not only about algorithms. AI works like a full “stack” of layers, from electricity to real-world user applications. In this paper, we explain a simple and student-friendly Five- Layer Architecture of AI: (1) Energy, (2) Chips, (3) Infrastructure, (4) Models, and (5) Applications. Each layer supports the next layer, like a cake with multiple layers. If any layer is weak, AI systems become slow, costly, or …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Effects of Reels and short videos on human mind and Academic Life
Abstract: The rapid rise of short-form video platforms such as Instagram Reels, TikTok, and YouTube Shorts has fundamentally reshaped the way people consume information and entertainment. While these applications offer quick engagement and social connection, their excessive use has raised serious concerns about their psychological and academic impacts. This research investigates the relationship between short-form video addiction, mindfulness, academic anxiety, and academic engagement among university students. Drawing upon the theoretical framework …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 22–33 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 Read article
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Revolutionizing Agriculture: Botani Scan’s Deep Learning for Plant Disease Diagnosis
Abstract: Crop disease detection is of key importance because of its role in food safety but infrastructural issues still hamper diagnosis in most regions worldwide. Accurate plant disease identification is essential to secure food, predicting yield decline and managing epidemic outbursts. The advent of digital cameras along with the progress of computer vision technology brings to light the mounting demands for the development of automated disease detection methods in precision agriculture, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 Read article
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Neuroinformatics and Its Impact on the Future of Brain-Computer Interface Technology
Abstract: Neuroinformatics, a multidisciplinary field combining neuroscience, information technology, and data science, plays a crucial role in advancing brain-computer interface (BCI) technology. By leveraging large-scale neural data, machine learning algorithms, and computational models, neuroinformatics enhances our understanding of brain function and improves the design and development of BCIs. The integration of neuroinformatics into BCI systems offers new possibilities for interpreting complex brain signals, facilitating real-time communication between the brain and external …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 9–18 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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Computer Data Processing and Empirical Economics
Abstract: This is an article on empirical economics and computer data processing that discusses how computational technology have changed empirical research methods. It analyses how computer systems have changed data management, statistical modelling, and econometric analysis, focussing on large-scale data processing, algorithmic efficiency, and repeatability. Forecasting, policy simulation, and panel data analysis are key uses. The paper also addresses data quality, computational, and ethical issues in economic data use. The paper …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 09–20 Read article
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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 1–11 Read article
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DATABASE-DRIVEN ENERGY MANAGEMENT IN ELECTRIC VEHICLES
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Sustainable Waste Management through Polymer Recycling: A Review of Business Model and Managerial Innovation
Abstract: Plastic and other polymeric materials have transformed modern life by providing durability, versatility, and cost-effective solutions across industries such as packaging, healthcare, construction, and transportation. However, their extensive use and improper disposal have created significant environmental concerns, including plastic pollution, landfill accumulation, and marine ecosystem degradation. This review synthesizes existing literature on polymer recycling with a focus on business-model innovation and managerial practices that can support sustainable waste management at …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 155–166 Read article
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Modelling and Control of Grid-Connected PV–Battery Hybrid System Using Dynamic Voltage Restorer for Enhanced Power Quality
Abstract: The integration of large-scale photovoltaic (PV) systems into modern power grids introduces significant challenges in maintaining power quality, including voltage sags, swells, and harmonics. To address these issues, this study presents a comprehensive modelling and control framework for a grid-connected PV–Battery hybrid system equipped with a Dynamic Voltage Restorer (DVR). The PV array is modelled using detailed mathematical equations, while the DC–DC converter incorporates advanced Maximum Power Point Tracking (MPPT) …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 43–58 Read article
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AbhiGyam: A Machine Learning Model-driven Research Platform for Assessing Accessibility Infrastructure in Indian Cities
Abstract: This work presents AbhiGyam, a machine learning-driven research platform designed to streamline and automate the assessment of accessibility infrastructure in Indian cities. AbhiGyam leverages the Google Maps API to transmit street view images to the backend, where computer vision techniques are implemented using OpenAI's CLIP (Contrastive Language-Image Pre-training) model to identify objects such as ramps, sidewalks, crosswalks, and parking spaces. The accuracy of the model is validated using labeled data …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 84–91 Read article
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A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article
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The Impact of Bacteria and Biostimulants on Crude Oil Breakdown in Loamy Soil
Abstract: This study investigates the influence of bacteria and biostimulants—specifically Bryophyllum pinnatum leaves soaked in both water and ethanol—on the degradation of crude oil in loamy soil. A laboratory-scale bioremediation setup was employed using a batch reactor model and first-order degradation kinetics to assess total petroleum hydrocarbon (TPH) breakdown under controlled conditions. Various analytical tools and procedures, including gas chromatography (Agilent 6890) and microbial media such as nutrient agar and mineral …
Published in International Journal of Pollution: Prevention & Control · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article