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137 articles for “Net Value Added”
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Adaptive Selective Harmonic Elimination Method for Quasi Z-Source Cascaded Multilevel Inverters in Varying DC Voltage Condition
Abstract: AbstractIn this paper, a new control method for adaptive selective harmonic elimination in a quasi Z-source cascaded multilevel inverter (QZS-CMI) is proposed. According to real condition, the DC sources feeding the inverter are considered to be varying in time. In this condition, the switching angle and shoot-through duty ratio for each module are obtained off-line for different DC source values using particle swarm optimization (PSO) algorithm. The off-line data set …
Published in Trends in Electrical Engineering · Vol. 4, Issue 3, 2014 · pp. 1–9 Read article
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Energy Efficiency and Awareness in Edge Computing: A Critical Review of Challenges, Strategies, and Future Directions"
Abstract: Edge computing enhances distributed systems by processing data near its source, yet its rapid growth, driven by IoT, 5G, and smart applications, escalates energy consumption across billions of devices. This study critically analyzes energy-saving techniques across hardware, software, and network layers, highlighting the role of AI tools and user education in promoting energy awareness. It explores trade offs between energy efficiency and system performance, identifies scalability challenges in large-scale deployments, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 32–36 Read article
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Algorithmic Ecology: A Framework for Achieving Carbon-Neutrality in Global Data Infrastructure
Abstract: The exponential growth of digital infrastructure has positioned data centers as critical enablers of the global digital economy, yet their environmental impact has become a paramount concern. Data centers consumed approximately 205 TWh globally in 2018, representing about 1% of global power usage with a steady 6% growth trend. This review synthesizes current literature on green algorithms and sustainable data center technologies, examining the intersection of artificial intelligence, machine learning …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 33–48 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 · pp. 39–46 Read article
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Cryptocurrency Price Prediction Using Python and ML
Abstract: Predicting the price of crypto currencies is one of the popular case research in the information technological know-how community. Over the last two years, geopolitical and economic problems have risen, global currency values have fallen, stock markets have slumped, and investors have lost their wealth. This has created a new interest in digital currencies. Cryptocurrencies, one of the most well-known digital currencies, are in the limelight as investors want some …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 36–41 Read article
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IoT and Smart Sensors for Structural Health Monitoring: Trends, Challenges, and Future Directions
Abstract: Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, resilience, and sustainability of civil infrastructure systems. In recent years, the convergence of Internet of Things (IoT) technologies and smart sensor systems has revolutionized the field of SHM. This integration enables continuous, real- time monitoring, facilitates predictive maintenance, and reduces the costs associated with structural inspections. IoT-based SHM frameworks leverage wireless sensor networks, cloud computing platforms, and intelligent …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 1–6 Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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Mapping A Contextualized Southern Africa's Innovation Ecosystem: The Emerging Role of Higher Education in Promoting Inclusive Innovation and Rural Industrialization
Abstract: Higher education institutions (HEIs) are increasingly recognized as strategic actors in shaping innovation ecosystems that can respond to persistent socio-economic inequalities in the Global South. In Southern Africa, where rural underdevelopment, youth unemployment, weak industrial bases, and uneven innovation capacities remain pressing concerns, universities are under growing pressure to move beyond their traditional teaching and research mandates and contribute more directly to inclusive development. This paper examines the emerging role …
Published in International Journal of Rural and Regional Development · Vol. 4, Issue 1, 2026 · pp. 14–27 Read article
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Combustion Characteristics of Waterlily (Nymphaea lotus Linn.) Briquettes
Abstract: The effect of binder types (bananas, yams, and cassava) and binders proportion on thermal properties of waterlily (Nymphaea lotus Linn.) briquettes were investigated. Peels from bananas, yams, and cassava were collected from agro processing cottage industry. The peels were washed, sun-dried, and ground using a disk mill and Tyler sieves to a particle sizes of 0.50 mm. The waterlily plants were collected from the river using a drag net, sun-dried, …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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Randomized Latent Vectors for Enhanced Reinforcement Learning Exploration
Abstract: This paper investigates Random Latent Exploration (RLE), a novel reinforcement learning technique that enhances exploration using randomized latent vector conditioning. I evaluate RLE’s performance across various environments, including discrete control tasks (FourRoom), continuous control (IsaacLab), and complex visual domains (Atari games). The core approach augments traditional reward functions with intrinsic rewards, calculated as the dot product between state features and periodically resampled latent vectors. The policy and value networks are …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article
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Socio-Economic Impacts of Rivers State Government Ring Road Project on Residents of Port Harcourt Municipality
Abstract: As nations strive towards improving the socio-economic well-being of its citizens, efficient transportation system in the form of ring roads have become a desideratum for reducing traffic congestion and enhancing movement of goods and services. The paper examines the impacts a ring road can have on residents of project area with emphasis on Port Harcourt. The Hazard and Effect Management Process (HEMP) technique developed by SHELL was used to examine …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 1, 2025 · pp. 42–51 Read article
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An Aggregate-Breakage Percolation Model and ANN-Based Internal Validation for Curvature-Dependent Electrical Conductivity of MWCNT/TPU Nanocomposites
Abstract: Strain-dependent percolation models are mostly built and tested for uniaxial tension, yet many flexible sensors and stretchable devices work mainly in bending, where the outer fibre is stretched, the inner fibre is compressed and the strain changes with thickness. This study extends an aggregate-breakage percolation model, originally formulated for uniaxial strain, to through-thickness bending of a multi-walled carbon nanotube/thermoplastic polyurethane (MWCNT/TPU) nanocomposite. The local strain is taken as ε(y) = …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
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Web Services Approach to Address the Challenges in Tribal Development
Abstract: ABSTRACTIn the world of ever-maturing distributed computing, service oriented architecture (SOA) and representational state transfer (REST) are the popular distributed architectures whereas web services, Windows communication foundation (WCF), .net remoting, etc., are the core components of inter-service communications. In a multi-application environment, applications multiply very fast and consequently inter-communication complexity grows at an alarmingrate. Simplifying the inter-application communication is a long desired goal for several reasons. Specifically, in e-Governance type …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 2, 2012 · pp. 42–54 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Electromagnetic and Dielectric Performance of Polymer–Ceramic Composite Substrates for Fractal-Based IoT-Antenna Fabrication
Abstract: Polymer–ceramic composite substrates play a crucial role in determining the electromagnetic performance, mechanical stability, and thermal reliability of radio-frequency devices. In this work, a polymer-based composite substrate is systematically investigated for its suitability in compact IoT and RFID antenna applications. A fractal-structured antenna is employed as a functional test platform to evaluate the dielectric behavior, impedance characteristics, and radiation efficiency of the composite substrate. Novelty of the proposed reader antenna …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1518–1534 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Will Artificial Intelligence Open a New Door in Anaesthesia Practice?
Abstract: The research used big data obtained from Electronic Medical Records (EMR), Computerised Physician Order Entry (CPOE) systems and picture archiving and communication systems (PACS). The traditional techniques of statistics are difficult to apply on large data or big data of electronic medical records (EMR) due to vastness or complexity. The artificial intelligence technique is valuable means to handle such data of EMR. Other than artificial intelligence, machine learning is very …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 9, Issue 1, 2020 · pp. 29–37 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article