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411 articles for “power optimization”
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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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A Review of Solar-Powered Electric Vehicle Models Handling Unpredictable Changes in Modern Power Grids
Abstract: The transition to Electric Vehicles (EVs) is a critical strategy for mitigating global warming and reducing dependence on diminishing fossil fuel reserves. However, the environmental benefits of EVs are significantly diminished if the charging power is sourced from carbon-intensive electrical grids. To achieve true sustainability, it is vital to integrate Renewable Energy Sources (RES), particularly solar energy, into the charging infrastructure. Beyond transportation, EVs offer a unique opportunity to act …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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A review on polyhouse monitoring system
Abstract: The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming practices, offering innovative solutions to enhance productivity, sustainability, and resource efficiency. This study explores the role of loT-based systems in smart agriculture, focusing on applications such as environmental monitoring, automated irrigation, crop health prediction, and precision farming. The reviewed systems utilize advanced sensors to monitor parameters like temperature, humidity, soil moisture, and light intensity, transmitting real-time …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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Solar Grow Net: Autonomous Greenhouse Monitoring and Control System
Abstract: This paper presents the development of an IoT-based, solar-powered greenhouse monitoring and control system designed to optimize environmental conditions for plant growth. The system uses multiple sensors to measure parameters such as temperature, humidity, soil moisture, air quality, and light intensity. Based on sensor readings, actuators including water pumps, fans, and lighting systems are automatically triggered to maintain ideal growing conditions. An ATmega328 microcontroller controls the entire system, while solar …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 Read article
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Nanomedicine in Combination with Artificial Intelligence (AI): Transforming Cancer Treatment
Abstract: The convergence of nanomedicine and artificial intelligence (AI) holds transformative potential for advancing cancer treatment, particularly in liver cancer. Nanomedicine enables the development of targeted drug delivery systems, enhanced imaging modalities, and precise therapeutic interventions, while AI facilitates data-driven decision-making, personalized treatment plans, and predictive analytics. This synergistic approach can significantly improve the diagnosis, treatment, and monitoring of liver cancer by optimizing the use of nanoparticle-based therapies. AI-powered algorithms can …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 27–30 Read article
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Development of Compact RF Filters for Modern Wireless Communication Systems
Abstract: Modern wireless communication systems such as 5G, 6G, Internet of Things (IoT), satellite communication, radar systems, and smart wireless networks require compact and highly efficient RF filters for reliable signal transmission and interference suppression. RF filters are important components that allow desired frequency signals to pass while rejecting unwanted frequencies and noise. With the rapid growth of wireless devices and limited spectrum resources, the demand for miniaturized, low-loss, multi-band, and …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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A Review on Design Optimization of Automotive Conventional Differential System for Rear Wheel Drive
Abstract: The following review paper provides a thorough explanation of the limitations of the automotive conventional differential system under various circumstances and suggests a viable solution for each constraint by enhancing the differential unit's design and construction. The conventional differential used in automotive (CAR, TRUCKS etc.) is the system which is used to transmit power from the engine to the rear wheels of the vehicle via the propeller shaft, hence we …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 39–51 Read article
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Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications
Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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Energy Harvesting Circuits with Piezoelectric Material: Design, Integration, and Optimization
Abstract: Piezoelectric energy harvesters (PHE) have drawn significant interest as a method of harvesting environment energy to power because of its compatibility and high energy density. Integrating piezoelectric energy harvesters into wireless sensor networks, Internet of Things (IoT)) devices, and wearable electronics enhances their functionality and also increases sustainability. This integration can be lead to the development of self-powered devices that can operate continuously without the need for external power sources. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1028–1039 Read article
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Multipurpose Farming Robot Control
Abstract: Conventional agricultural practices frequently involve a significant amount of manual labor and are prone to inefficiencies and resource waste.The relevance of incorporating robotics and mobile technology into agriculture lies in addressing several critical challenges faced by the industry. The implementation of IoT technology in smart farming systems. It covers various IoT applications in agriculture, such as environmental monitoring, automated irrigation, and precision farming, highlighting the benefits and challenges of IoT …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 2, 2024 · pp. 19–25 Read article
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Experimental Study of Roughness Analysis of AISI 316L Material using Fiber and CO2 LBM
Abstract: Laser beam machines have gained significant attention as a precise and versatile method for cutting and shaping materials in various industries. This study investigates the surface roughness characteristics of SS 316L, a commonly used stainless steel, when subjected to laser beam machining using both fiber and CO2 laser sources. The aim of this research is to compare the effects of these two laser types on the final surface finish of …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 12–21 Read article
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Advancements in Photocatalysis: Applications in Environmental Remediation
Abstract: The study of radioluminescence, a phenomenon where materials emit light upon exposure to ionizing radiation, has expanded significantly in recent years, finding applications in various fields, including environmental remediation, radiation detection, and dosimetry. This paper reviews recent advancements in radioluminescent technologies, particularly focusing on Radioluminescent Isotope Cells (RLICs) and semiconductor colloidal quantum dots (cQDs). The use of RLICs, particularly those based on 63Ni, demonstrates enhanced energy conversion efficiency through optimized …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 2, 2024 · pp. 39–44 Read article
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Review on Sustained Released Matrix Tablet
Abstract: Pharmaceuticals often use sustained release dose forms to prolong the therapeutic agent’s presence in the bloodstream and maintain a consistent plasma profile. The matrix governs the drug’s release rate. Hydroxypropyl methyl cellulose, a release retardant, is a key excipient in formulations due to its ability to promote sustained release. Techniques that include wet granulation, direct compression, or the dispersion of solid particles within a porous matrix, integrating polymers, like polymethyl …
Published in Trends in Drug Delivery · Vol. 12, Issue 2, 2025 · pp. 60–69 Read article
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Machine Learning-Driven Polymer Composite Smart Skin for Integrated Sensing in Soft Robotic Systems
Abstract: Soft robotics has grown rapidly, but its progress is still constrained by the limitations of current sensing skins. Most polymer-based sensors provide either flexibility or sensitivity, yet they struggle to deliver real-time communication and adaptive intelligence when deployed in complex robotic environments. This disconnect between material performance and system-level responsiveness forms a critical bottleneck for practical deployment. Existing approaches often treat tactile sensing and wireless communication as separate problems. As …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 121–136 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article