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98 articles for “Time-dependent analysis”
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Construction Sequence Analysis of High-Rise Structure with Creep and Shrinkage Effect
Abstract: This study deals with a time-dependent analysis of reinforced concrete G+40 RC frame structures considering the construction sequence with the effect of creep and shrinkage analysis. Because of the non-mechanical deformations induced by the time-dependent deformations of concrete, concrete structures usually present different behaviors when the construction sequences are changed, despite having the same structural configurations. Therefore, the time-dependent effects of concrete such as creep and shrinkage must be taken …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 10–25 Read article
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Seismic Response Characterization of Vertically Irregular Multi-Storey Buildings Incorporating Mass and Stiffness Variations Using E-TABS Software
Abstract: The increasing demand for innovative architectural designs has led to the widespread use of vertically irregular configurations in high-rise reinforced concrete (RC) buildings. However, such irregularities significantly influence structural performance under seismic loading conditions, leading to complex structural behaviour and stress concentration at specific levels This study focuses on evaluating the seismic behaviour of vertically irregular multi-storey buildings using nonlinear time history analysis, which provides a realistic representation of structural …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 3, 2026 Read article
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A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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Seismic Analysis of Alternate Outrigger System
Abstract: In regions characterized the concept of construction sequence analysis, explain that this method involves analyzing a structure's behavior over time, considering the chronological order of construction stages. Introduce the crucial aspects of time-dependent effects, specifically creep and shrinkage, explain that these factors cause deformations in concrete over time and can significantly influence the structural behavior of buildings. In this study deals with non-linear construction stage analysis of G+14 structure as …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 1, 2024 · pp. 16–25 Read article
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POLYMER AND COMPOSITE-BASED GEOSYNTHETIC REINFORCEMENTS FOR SEISMIC STABILITY OF SOIL RETAINING STRUCTURES: MATERIALS, MECHANICS, AND PERFORMANCE REVIEW
Abstract: Geosynthetic materials based on polymer and composites have become important items for the structural performance and seismic resilience of the reinforced soil retaining systems. Mechanically stabilized earth walls in recent geotechnical engineering practice are increasingly based on enhanced polymeric reinforcements for enhanced tensile strength, durability, flexibility, and energy dissipation under dynamic loading. High-density polyethylene, polypropylene, polyester, and fiber-reinforced polymer composites are usually used. The present review focus on the recent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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From Noise to Insight: An Academic Study of Electrical Signal Processing
Abstract: Electrical signal processing is very important for turning raw, often noisy data into useful and actionable information. This article gives a simple and easy-to-understand summary of the basic ideas and methods used in electrical signal processing, such as filtering, signal representation, modulation, and spectrum analysis. The focus is on how to effectively eliminate noise and interference to improve the quality and dependability of signals. The conversation connects ideas from theory …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Comparative Study of Time Slice Windows Analysis and Impacted As-Planned Analysis for Data Center Construction Projects Using Primavera P6 24.12 Version
Abstract: Data centers are IT infrastructure that needs to be precisely scheduled and coordinated. Significant financial losses and operational failures may result from building delays. Stakeholders can assign blame and comprehend the reasons behind delays with the aid of forensic delay analysis. Because of their unique approaches and legal acceptability, TSWA, and IAPA are commonly used among the many strategies. These methods provide various ways to analyze project schedules and pinpoint …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 1, 2026 · pp. 33–51 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Triple-Threat Analysis: Measuring Mythril, Slither and Oyente Against Real-World Smart Contract Vulnerabilities
Abstract: Smart contracts have become fundamental building blocks of blockchain ecosystems, yet their immutable nature makes security vulnerabilities particularly devastating. This pa- per presents a comprehensive evaluation of three prominent static analysis tools—Mythril, Slither, and Oyente—for detecting vulnerabilities in Ethereum smart contracts. Through systematic experimentation with real-world contract categories (voting sys- tems, land registries, and crowdfunding platforms), we quantify the effectiveness of each tool across eight critical vulnerability types, including reentrancy, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 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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Comparative Performance Study: Deterministic vs. Probabilistic Models in Retail Chains
Abstract: The finished goods, raw materials, and product stock that a business has on hand for sale are referred to as inventory. They enable the companies to achieve their sales levels and are a chance to cost control and decision making. It is a huge asset to a manufacturing firm. Inventory model permits forecasting of quantities of raw material, inventory and spare parts of the equipment to a very high level …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 1–6 Read article
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Design and Development of a Smart Automated Packaging System for Poultry Drumsticks
Abstract: The present work aims to design and implement an automated packaging system for poultry drumsticks that enhances operational efficiency, product quality, and adaptability. The integrated system offers a solution that complies with industrial quality and safety standards by sorting products, getting accurate weighing, and efficiently portioning food into 1-kilogram standardized units. By effectively reducing human involvement, operational inefficiencies, workforce requirements, and contamination hazards, the automation system becomes sufficiently adaptable to …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Time and Frequency Response of Non-uniform Overhead Lines Under Corona
Abstract: This study presents an efficient and direct technique for determining both the time and frequency responses of non-uniform overhead power transmission lines operating under corona conditions. The assumed-line's non-uniformity is due to the conductors’ sag. Expressions will be presented for the location-dependent line surge impedance and the unevenly distributed lines’ electrical parameters. The analysis starts with solving the relevant system of differential and algebraic equations, subject to the boundary conditions. …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 25–33 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Analysis of Project Management Optimization Using CPM and PERT in a Dynamic Business Environment
Abstract: In the current fast-changing business environment, organizations must remain agile and strategically responsive to unpredictable challenges such as supply chain disruptions, shifting consumer demands, and evolving market trends. Project management techniques like the Critical Path Method (CPM) and the Program Evaluation and Review Technique (PERT) serve as valuable tools in helping businesses manage these complexities effectively. CPM is a time-focused method that identifies the longest sequence of dependent tasks in …
Published in Journal of Construction Engineering, Technology & Management · Vol. 15, Issue 3, 2025 Read article
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Enhancing Construction Safety Performance Through Artificial Intelligence: A Systematic Review
Abstract: The construction industry is still one of the most dangerous sectors globally because of its dynamic working environment, the employment of heavy machinery, and the complexity of operational processes. Traditional safety management methods are largely dependent on manual monitoring and reactive measures, which are not always effective for accident prevention. In recent years, Artificial Intelligence (AI) has been recognized as a revolutionary technology in construction safety, with capabilities such as …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 13–30 Read article
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Solar Tracking System and Battery Management
Abstract: This project focuses on optimizing renewable energy systems by combining a dual-axis solar tracking mechanism with a smart Battery Management System (BMS) to improve solar energy harvesting and storage. The system uses an Arduino Uno microcontroller and Light Dependent Resistors (LDRs) to track the sun's position, enabling the solar panel to adjust its orientation in real-time for optimal sunlight exposure throughout the day. At the same time, the integrated IoT-based …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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Smart Air Quality Monitoring System using IoT
Abstract: This paper presents the design and implementation of a Smart Air Quality Monitoring System using the ESP32 Wi-Fi microcontroller integrated with an MQ-2 gas sensor and a DHT-11 temperature and humidity sensor. The system continuously monitors environmental parameters including air quality (smoke, LPG, CO, and other combustible gases), temperature, and relative humidity in real time. The acquired sensor data is transmitted wirelessly to the Blynk IoT platform, enabling users to …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article