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194 articles for “conventional frame”
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Review of Diagrid and Conventional Frame Systems for Modern Building Design
Abstract: The demand for high-rise buildings in modern cities has accelerated the development of structural systems that balance safety, efficiency, and architectural innovation. Conventional moment-resisting frames, though widely adopted, often become inefficient in tall structures due to higher material consumption and greater lateral displacements under seismic and wind loading. Diagrid systems, defined by their diagonally inclined members forming triangulated grids, provide an alternative approach with enhanced lateral stiffness, reduced drift, and …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 47–53 Read article
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Static and Dynamic Analysis of Conventional, Diagrid and Hexagrid Systems Across Different Storey Heights
Abstract: In structural engineering, multi-storey buildings’ seismic resilience in earthquake-prone areas is crucial. The seismic performance of proposed multi-story buildings with different heights (G+13, G+19, and G+27) is thoroughly examined in this study using traditional structural systems that are octagrid and hexagrid. Under seismic zone III conditions, the study evaluates important parameters such as storey drifts and storey displacements using the Response Spectrum Method. Each structural system's seismic response is assessed …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 2, 2025 · pp. 36–47 Read article
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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 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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Comparative Performance Assessment of Shear Wall and Diagrid Systems in an Octagonal Tall High-Rise Building under Seismic and Wind Loads
Abstract: The increasing demand for high-rise structures due to rapid urbanization necessitates the adoption of efficient lateral load-resisting systems to ensure structural safety, stability, and serviceability. This study presents a comparative evaluation of the seismic and wind performance of a Ground plus Fiftystorey high-rise building with an octagonal plan, incorporating different structural configurations such as shear wall arrangements and a diagrid system. A total of six analytical models, including a conventional …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 Read article
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Performance Forecasting in Solo Sports: Leveraging Psychometrics, Economic Analysis, and Cultural Insights for Predictive Excellence
Abstract: The science of performance forecasting in solo sports has transcended traditional metrics, embracing a multidisciplinary approach. This paper explores the integration of psychometrics, economic analysis, and cultural insights to predict athletic success. By leveraging psychological profiling, economic factors, and cultural dynamics, this study aims to establish a comprehensive model for forecasting athlete performance with heightened accuracy. In the realm of solo sports, where individual prowess dictates success, traditional performance forecasting …
Published in Recent Trends in Sports · Vol. 1, Issue 1, 2024 · pp. 35–44 Read article
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Structural Optimization of FDM-Processed ASA Polymer Frames through Acetone Solvent Welding, Variable Infill Strategy, and Layer Orientation: Experimental Validation via Quadcopter Flight Testing
Abstract: Acrylonitrile styrene acrylate (ASA) is an amorphous terpolymer with superior UV resistance compared to acrylonitrile butadiene styrene (ABS), as its acrylate rubber phase lacks photodegradation-prone carbon–carbon double bonds. This study proposes acetone solvent welding as a polymer joining method to produce monolithic structures from FDM-processed ASA components, addressing three processing challenges: achieving structural continuity through polymer chain interdiffusion at solvent-wetted interfaces, correcting thermal warping via post-print geometric correction during welding, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 689–703 Read article
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A Theoretical Model for a Fermi–Boson Hybrid Particle in Nuclear and Particle Physics
Abstract: We present a theoretical model for a Fermi–Boson Hybrid Particle (FBHP) that unifies fermionic half-integer spin matter fields with bosonic integer-spin force fields within a single quantum framework. By extending conventional quantum field theory, a hybrid creation operator is formulated that combines fermionic and bosonic operators through a continuous mixing parameter, allowing smooth interpolation between Fermi–Dirac and Bose–Einstein statistical behaviour. A generalized statistical mechanics formalism is developed, leading to quantitative …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 10–18 Read article
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Punjab’s Wetlands as Inland Analogues of Marine Ecosystems: Status, Stressors and CommunityLed Conservation.
Abstract: Aquatic and wetland ecosystems in Punjab, India, represent ecologically significant yet increasingly degraded socioecological systems embedded within an intensively managed agrarian landscape. Despite their recognised importance, existing studies largely treat these systems using conventional freshwater ecological frameworks, with limited integration of microbiologically mediated processes and broader ecosystem theories. A key research gap, therefore, lies in the lack of interdisciplinary approaches that can holistically interpret wetland structure, function, and governance across …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 31–51 Read article
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A Comprehensive Guide to Application Development Using Flutter
Abstract: Developers are forced to either write the same application many times for other operating systems or use a similar but inferior solution that compromises native performance and accuracy in favor of portability. Flutter is a toolkit developed by Google that helps programmers create apps that look and feel great on different devices like phones, tablets, and computers. What is special about Flutter is that one can write code once and …
Published in International Journal of Electronics Automation · Vol. 2, Issue 1, 2024 · pp. 35–41 Read article
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Analytical Investigation on Structural Optimization of Commercial Building Using Braced Frames and Masonry Diagonal Strut
Abstract: Enhancing the overall stability and structural performance of commercial buildings are important in particular regions which are prone to various seismic activity. This research emphases on enhancing the seismic performance of commercial buildings by integrating masonry diagonal struts with concentric braced frames. The main aim is to ensure structural safety of a building while also keeping the design economical and efficient. In this study high-rise buildings with 12, 16, and …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 14–23 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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User Centric Design: A Framework for Transforming Design Studios into Smart Workspaces
Abstract: In contemporary design studios, the integration of smart technologies has become imperative to enhance productivity, collaboration, and creativity among designers. This research paper presents a comprehensive framework for the transformation of conventional design studios into smart workspaces, focusing on user-centric design principles. The concept of User-Centric Design emphasizes its departure from traditional design approaches by placing the user experience at the forefront of the creative process. It highlights the increasing …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 1–13 Read article
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Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites with Embedded Memristive Energy Routing for Adaptive Solar Energy Harvesting
Abstract: This dynamic and fast-growing intelligent renewable energy system requires photovoltaic materials that can autonomously adapt to fast-changing environmental conditions. In this study, a novel system is proposed for adaptive harvesting of solar energy based on Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites (NSPMPCs) with embedded memristive energy routing networks. To boost the charge generation and charge transport in the polymer–MXene heterostructure, the flexibility and processability of conductive polymers are integrated with the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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The Perpetuation of Psychological Wounds: A Comprehensive Review of Intergenerational Trauma in Indian Patriarchal Society
Abstract: The transmission of trauma effects from one generation to the next is known as intergenerational trauma, and it is particularly common in patriarchal civilisations such as India. Laws, economy, and social conventions are shaped by patriarchy, a societal framework that primarily gives males power, authority, and advantages. This perpetuates gender inequity and marginalises women. Aim: The purpose of this review is to examine how trauma is transmitted throughout generations in …
Published in International Journal of Trends in Humanities · Vol. 2, Issue 1, 2025 · pp. 20–26 Read article