Search
717 articles for “data utility”
-
LoRa and LoRaWAN in the IoT: Performance, Challenges, and Future Opportunities
Abstract: This paper provides a broad overview of both LoRa and LoRaWAN technologies in the context of Internet of Things (IoT). The market need for communication technology to be low-power and long-range continues to grow, and LoRa and LoRaWAN are emerging as viable options for enabling widespread IoT applications in a variety of applications. This review offers structured and comparative assessment of their functionality in different environments, such as urban, rural, …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 2, 2026 Read article
-
Internet of Things Connectivity Using Millimetre Wave: A Study
Abstract: Internet of Things(IoT) is undergoing rapid development, which is connecting millions of devices and causing sectors to undergo transformation. On the other hand, given this increase, the constraints of conventional wireless communication technologies are being stretched to their limits. Millimetre wave, often known as mmWave, is a high-frequency band that has the potential to revolutionise Internet of Things connectivity by providing much higher capacity levels and lower latency levels. Microwave …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 18–30 Read article
-
Role of Blockchain Technology in Health Record Management
Abstract: Maintaining thorough medical records is essential to raising a healthy population in the fast-paced world of global development. Intimidating data breaches have been the consequence of the traditional centralized strategy to maintaining health records, yet it has proven vulnerable. The 2017 Ponemon Cost of Data Breach Study estimated that each compromised healthcare record could incur a significant cost of approximately $380. Regrettably, the 2016 Breach Barometer Report revealed that case …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 1, 2024 · pp. 29–35 Read article
-
Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
-
Fertile Data: Advanced Strategies for Crop Optimization Through Machine Learning Processing
Abstract: The venture, titled "FertileData: Advanced Strategies for Crop Optimization Through Machine Learning processing" is created utilizing HTML, CSS, and JavaScript for the front conclusion, and Python for the back conclusion. In a nation like India, where a noteworthy parcel of the populace depends on agribusiness for their vocation, joining progressed advances such as Machine Learning and Profound Learning into cultivating hones can revolutionize the industry. This venture presents a user-friendly …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 25–35 Read article
-
Digital Voting System Using Blockchain
Abstract: The advent of blockchain technology has ushered in a new era of secure, transparent, and decentralized systems, providing a promising foundation for various applications, including electronic voting (e-voting). This report examines the development and deployment of a blockchain-based e-voting system designed to tackle the ongoing issues of security, transparency, and voter privacy in elections. The system utilizes blockchain's core features, including immutability, decentralization, and cryptographic security, to establish a secure …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 8–14 Read article
-
Utilizing AWS Advanced Services for Modernizing and Refactoring Legacy Systems to Achieve Cloud-Native Capabilities
Abstract: Updating and restructuring outdated systems is essential for organizations seeking to harness the scalability, adaptability, and robustness offered by cloud-native architectures. Legacy systems can obstruct innovation because of their rigid structure, expensive maintenance, and inability to scale effectively. Amazon Web Services (AWS) provides a comprehensive suite of advanced services that enable the efficient transformation of such systems into modern, cloud-native solutions. This paper explores strategies and best practices for utilizing …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 44–65 Read article
-
CMOS-Based Process-Scalable Analog Circuits for Machine Learning: A Comprehensive Review and Future Directions.
Abstract: Analog computing techniques are gaining attention for machine learning (ML) applications due to their ability to reduce computational complexity. Continuous operations such as addition and subtraction offer a simpler and more efficient approach compared to probabilistic product decoding, which can be sensitive to noise and inconsistent measurements. This paper presents a simulated VLSI implementation of a broadcast edge connection, independent of the MOS component model, along with experimental results. The …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 8–17 Read article
-
Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
-
Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
-
Unlocking Synergies: Exploring The Nexus Between Sustainable Building Practices, Green Polymers, and Occupant Health Through SPSS Statistical Analysis
Abstract: This study examines the significance of utilising environmentally friendly polymers in the construction industry, specifically looking at the perspectives of individuals occupying buildings that have used green building design techniques. The focus is on the occupants' perceptions of the efficiency, comfort, and health of the materials used. Green polymers, which are essential for sustainable building, have the potential to completely transform infrastructure development. The materials mentioned include of natural fibre …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 241–252 Read article
-
Effect of Mindfulness-Based Yoga Practices on Anxiety and Attention Level Among High School Children in a Selected High School, Bhubaneswar, Odisha
Abstract: Background: In a world filled with endless pressures and expectation, school-aged children often find themselves navigating through a labyrinth of stressors and anxiety. from the moment they wake up their tiny minds are bombarded with worries about exams, social interaction.it is in these moments of chose that the ancient practice of yoga emerges as a gentle beacon of hope, offering solace and tranquility to these young souls. The study main …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
-
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
-
High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
-
Li-Fi based Underwater Audio and Data Transmission System
Abstract: Visible Light Communication, or Li-Fi (Light Fidelity), is a wireless optical networking technique used for communication (VLC). Due to its lack of RF communication's drawbacks, such as water absorption and scattering, Li-Fi has the potential to completely transform underwater communication. This project suggests utilizing two Arduinos, a solar panel, a speaker, a display, an amplifier, a laser, a battery, and other components to create a Li-Fi based underwater audio and …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 2, 2024 · pp. 23–29 Read article
-
AI and ML in the Chemical Industry: A Review of Transformative Applications and Future Prospects
Abstract: The chemical industry, a key growth indicator of the global manufacturing ecosystem, is experiencing a digital transformation driven mainly by advancements in Artificial Intelligence (AI) and Machine Learning (ML) in this sector. These technologies are totally revolutionizing current and traditional methodologies by significantly improving process efficiency, reducing costs of manufacturing, accelerating R&D, and improving safety and sustainability standards. Proper utilization of Artificial intelligence (AI) and machine learning (ML) in chemical …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
-
Socioeconomic Inequalities in Utilisation of AYUSH Systems of Medicine in North-East India: Evidence from NSS 79th (2022–2023) Round on AYUSH
Abstract: Background: Socioeconomic inequality in healthcare Utilisation continues despite policy focus on universal health coverage and Sustainable Development Goal 3. India's traditional, complementary, and alternative medicine systems are generally termed as AYUSH. AYUSH has been consolidated into the national health policy; however, empirical findings on its distributive equity persist as limited. This study estimates and decomposes socioeconomic inequality in Utilisation of AYUSH systems of medicine among the adult age group 15 …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 29–42 Read article
-
Intelligent Planning of Transmission Networks: Addressing Uncertainties Through Artificial Intelligence
Abstract: Power grid planning is a critical aspect of power grid topology, traditionally relying on manual methods that are prone to various uncertainties. These uncertainties, both subjective (stemming from human judgment) and objective (resulting from data limitations), can significantly affect the reliability and efficiency of the planning process. This paper presents an artificial intelligence (AI) method aimed at improving the smart planning of transmission networks. By utilizing AI, the proposed method …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 40–46 Read article
-
A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
-
Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article