Search
490 articles for “utility”
-
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
-
Vitamin D Mitigates Inflammation and Downregulates Importin α3 in Non-Alcoholic Fatty Liver Disease (NAFLD)
Abstract: Background: Pro-inflammatory cytokines, such as TNF-α, IL-1β, IL-6, and IL-8, seem to play a crucial role in the progression of NAFLD as they activate the transcription factor NF-кB. The activated NF-кBp50/RelA subunits are translocated to the nucleus by Importin α3 and Importin α4. Numerous studies have indicated a negative association between NAFLD and vitamin D levels. Low vitamin D levels have been correlated with histological severity, necro-inflammation, and fibrosis in …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 1–16 Read article
-
Photonic Diagnostics: Harnessing Optical Sensing for Non-Invasive Assessment of Coronary Obstruction
Abstract: Cardiovascular diseases (CVDs) remain the leading cause of mortality globally, with coronary artery blockages primarily atherosclerosis representing a critical challenge. The gold standard for diagnosing coronary artery disease remains invasive coronary angiography, a procedure that, while precise, carries inherent patient risks, high costs, and logistical burdens. Optical sensors, leveraging the principles of light-tissue interaction, offer real-time, high-resolution insights into vascular health, paving the way for early detection of arterial stenoses …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 25–30 Read article
-
64 Bit ALU DESIGN USING VEDIC MATHEMATHICS
Abstract: High-speed arithmetic operations are crucial for better performance in contemporary digital systems. Particularly for high bit-width operations, conventional arithmetic logic units (ALUs) frequently experience increased latency and complexity. This work presents the design and implementation of a 64-bit Arithmetic Logic Unit (ALU) using notions from Vedic mathematics. The suggested design makes use of a Kogge-Stone Adder for effective addition and the Urdhva Tiryagbhyam sutra for quick multiplication. Among other mathematical …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
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
-
Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
-
Formulation and Evaluation of Herbal Skin Cream
Abstract: Herbal cosmetics have gained significant attention in recent years due to increasing consumer preference for natural and safe skincare products. Herbal skin creams are semisolid formulations enriched with plant-derived ingredients that provide therapeutic as well as cosmetic benefits. These formulations are designed to enhance skin health by utilizing bioactive phytoconstituents such as flavonoids, alkaloids, tannins, essential oils, and vitamins. Herbal creams are generally prepared using oil-in-water (O/W) or water-in-oil (W/O) …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 2, 2026 · pp. 20–32 Read article
-
A Study on Fracture Sem Analysis by Optimization of FSW When a Composite Material Al 6061 Mixed with Fly Ash is Done with Cooper Using Anova Method
Abstract: The current study aims to examine how different parameters in friction stir spot welding influence hardness and tensile strength, while identifying the most suitable parameter combinations to enhance the overall quality of the fabricated components. The experimental work involves joining dissimilar materials, where one specimen consists of Aluminum alloy 6061 reinforced with 10% fly ash, and the other is a copper alloy. Various process conditions are altered during testing to …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
-
AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
-
Functional Biomolecules in Animal Nutrition: Biochemical Mechanisms and Their Impacts on Growth Performance and Health Outcomes
Abstract: Functional biomolecules have emerged as critical modulators of animal nutrition, extending beyond conventional nutrient supply to regulate biochemical and physiological processes that determine growth performance and health outcomes. This review synthesizes current knowledge on diverse classes of bioactive compounds, including amino acids, peptides, fatty acids, vitamins, minerals, phytochemicals, and microbial-derived metabolites, and their roles in livestock systems. Emphasis is placed on underlying biochemical mechanisms such as enzyme activation, nutrient signaling …
Published in International Journal of Nutritions · Vol. 3, Issue 2, 2026 Read article
-
Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
-
An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
-
IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
-
Optimization of Surface Roughness and Material Removal Rate in Turning of Al-6061 Using Taguchi Methodology, Fuzzy Logic, and Measurement System Analysis
Abstract: The optimization of machining parameters please a crucial role in improving product quality and productivity in manufacturing processes. This study focuses on the turning of aluminium 6061 alloy, aiming to optimize two key performance measures: Surface Roughness and Material Removal Rate. An integrated approach combining to Taguchi methodology, fuzzy logic and measurement system analysis (MSA) is proposed to achieve this objective. Taguchi design of experiments using and L9 orthogonal array …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
-
Ethical AI and Data Protection in the Era of Industry 5.0
Abstract: This paper provides a comprehensive analysis of the critical intersection between Responsible AI (RAI), data privacy, and the Industry 5.0 paradigm. Industry 5.0, defined by its human-centric, sustainable, and resilient pillars, introduces a fundamental paradox: its core requirement for human-AI collaboration necessitates the collection and processing of granular human data, creating direct conflicts with emerging global data privacy and AI regulations. This research utilizes a systematic integrative review methodology, analyzing …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
-
The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
-
Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
-
Artificial Intelligence in Education: Enhancing Usability and Adoption Among Educators in Digital Classrooms
Abstract: The use of Artificial Intelligence (AI) in education has changed digital learning environments. It provides new tools to improve teaching and boost student engagement. However, even with more AI-enabled technologies available, not all educators are using them equally. This uneven adoption is mainly due to problems with usability, accessibility, and digital readiness. This study addresses the critical gap between the potential of AI in education and its practical utilization by …
Published in Recent Trends in Social Studies · Vol. 3, Issue 2, 2026 Read article
-
ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
-
Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article