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81 articles for “generative de-sign tools”
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Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform
Abstract: The rapid progress of the Fourth Industrial Revolution has been largely driven by the evolution of artificial intelligence (AI), with notable contributions from technologies such as Generative Pre-trained Transformers (GPT). This revolution has seen the convergence of physical, digital, and biological technologies, leading to transformative impacts across various sectors. Data science, serving as a crucial enabler, has enabled the development of intelligent value chains. However, the application of data science …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Simulation and Analysis of Battery Pack Using the Multi Scale Multi-Domain Battery Model
Abstract: The creation of sophisticated simulation models has been made necessary by the need for reliable and effective battery packs in energy storage systems and electric vehicles. This study focuses on the simulation and analysis of battery packs using a multi-scale multi-domain battery model. The model enables a thorough knowledge of battery pack behavior across a range of operating situations by integrating the electricity, thermal, and mechanical domains. Multi-scale modeling bridges …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 31–46 Read article
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Understanding Leukemogenesis: Challenges and Advancements in Diagnostic Approaches
Abstract: Leukaemia development, or leukemogenesis, is a multifactorial process driven by a complex interplay of environmental, genetic, and epigenetic factors. Despite substantial advancements in technology and medicine, which have enhanced our understanding of the contributing factors, early and accurate diagnosis remains a major challenge due to the overlapping clinical features shared by the various leukaemia subtypes. This study explores the molecular and cellular mechanisms underlying leukemogenesis, while also addressing the difficulties …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Semantic Network Technology and Digital Library
Abstract: In recent years, the volume of information available on the internet has grown rapidly, leading to the need for more effective ways to manage and access high-quality content. Much of this reliable and well-structured information is stored in digital libraries, which serve as centralized hubs for organized knowledge. However, despite their usefulness, managing and navigating these vast collections of data continues to present significant challenges. To address these issues, the …
Published in Current Trends in Information Technology · Vol. 15, Issue 2, 2025 · pp. 13–18 Read article
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Nuclear Power as a Clean Energy Future: A Review
Abstract: The global push for decarbonization necessitates a diverse energy portfolio, and nuclear power, once a subject of intense debate, is re-emerging as a potential cornerstone of a clean energy future. With its capacity for baseload power generation and minimal greenhouse gas emissions during operation, nuclear energy offers a compelling substitute for fossil fuels, particularly in a world grappling with climate change. However, challenges remain regarding safety, waste disposal, and economic …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–11 Read article
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Evaluating TRIZ Methodology in the Conceptual Design Phase of Industrial Products
Abstract: The Theory of Inventive Problem Solving (TRIZ) has emerged as a powerful systematic innovation methodology that enhances creativity and problem-solving efficiency in engineering design. This paper evaluates the application of TRIZ during the conceptual design phase of industrial products, where early-stage decisions critically influence functionality, cost, sustainability, and market competitiveness. TRIZ provides designers with structured tools—such as the 40 Inventive Principles, Contradiction Matrix, Su-Field Analysis, and Trends of Technological Evolution—that …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 27–32 Read article
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Methodology for Evaluating Code Synthesis in Large Language Models: ChatGPT and Copilot: A Review
Abstract: The authors introduce a comprehensive framework to assess the code-generation capabilities of large language models, focusing on ChatGPT and Copilot through a benchmark suite of 25 program synthesis tasks. Their main goal was to show why making proper comparisons is important, they did not focus on choosing the newest models, since they keep changing frequently. The critique examines how the methodology addresses both functional and non-functional aspects of code. In …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
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Monoclonal Antibodies in Next Generation Animal Nutrition: Mapping Nutrient Immune Interaction Networks in Livestock Systems
Abstract: Sustainable livestock production is increasingly constrained by disease pressure, antimicrobial resistance, and declining feed efficiency under intensifying environmental stressors. Conventional nutritional strategies, while essential, remain insufficient to precisely regulate immune function and metabolic resilience. This review explores the emerging role of Monoclonal antibodies as advanced biologics in next generation animal nutrition, with a focus on mapping nutrient immune interaction networks in livestock systems. It synthesizes current knowledge on how nutrients …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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The Integration of Machine Learning in VLSI IC Design
Abstract: It represents the first use of AI in the domain of integrating circuits, which has been impacted by it. The conventional VLSI design process that is now in use is replaced by this technology. The laborious manual concepts created by people have been replaced with automated design innovations. This development would trigger a profound change in the fields of AI education and hardware computation. With the introduction of contemporary chips, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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From Battlefield to Biodiversity: The Evolution of Drones in Modern Conservation Efforts in Wildlife
Abstract: The rapid advancement of drone technology, encompassing unmanned aerial vehicles (UAVs), unmanned aircraft systems (UAS), and remotely piloted aircraft (RPAs), has significantly impacted various fields, particularly environmental management and wildlife conservation. Originally designed for military use, drones have now become essential tools in ecological research, offering a cost-effective and minimally invasive way to monitor and protect ecosystems. These sophisticated "eco-drones" have revolutionized data collection, especially in hard-to-reach and previously inaccessible …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 8–12 Read article
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Data Integration and Visualization in Bioinformatics: Techniques and Challenges
Abstract: Data integration and visualization play essential roles in bioinformatics, facilitating the thorough analysis, and interpretation of intricate biological datasets. In the field of bioinformatics, vast amounts of data are generated from various experimental platforms, such as genomic sequencing, proteomics, transcriptomics, and metabolomics. However, the heterogeneity of these datasets, coupled with their large scale and complexity, presents significant challenges in terms of integration, analysis, and visualization. Data integration techniques aim to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Lab Reagents and Their Importance in Bio-chemistry
Abstract: Biochemical reagents are essential substances in the study of life at the molecular level. These reagents help scientists detect, identify, and quantify bio-molecules such as proteins, carbohydrates, nucleic acids, and enzymes in biological systems. They play a vital role in understanding metabolic reactions and physiological processes within living organisms. Biochemical reagents are generally classified into analytical, diagnostic, enzymatic, chromogenic, and buffer reagents, each serving a specific purpose in laboratory and …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 Read article
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Java’s Enduring Popularity: Unraveling the Factors Behind Its Preference
Abstract: Java remains one of the most widely used programming languages across various industries, owing to its robust architecture, platform independence, and extensive ecosystem. Its versatility, scalability, and security make it a preferred choice for developing a wide range of applications, from enterprise software to mobile and web solutions. This study delves into the key factors contributing to Java’s sustained relevance in software development, highlighting its adaptability to evolving technological trends. …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 8–15 Read article
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Internet of Things in Smart Grid: Applications, challenges, Conditions, Architecture- A Review
Abstract: Future-generation intelligent optimisation in electrical system design is essential for managing electrical networks and distribution systems. It also requires interoperability variations in the implementation of physical or graphical models. The Internet of Things (IoT) plays a significant role in smart grids and distributed electricity systems. IoT enables the monitoring of the smart grid's electrical energy and facilitates the integration of real-time data into electrical grid architecture at various levels. Industrial …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article