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1781 articles for “R S Data analysis” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Green Human Resource Management: Awareness, Perception, and Its Impact on Employee Well-being and Work-Life Balance
Abstract: This study explores the growing significance of Green Human Resource Management (Green HRM) and its impact on employee well-being and work-life balance. As organizations face increasing pressure to adopt sustainable and environmentally responsible practices, Green HRM emerges as a strategic approach that aligns ecological objectives with human resource policies. The research aims to assess employee awareness and perception of Green HRM initiatives and how these perceptions influence their job satisfaction, …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 2, 2025 Read article
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A Module to Connect Different Sensors to The Existing Varun Main Controller Device
Abstract: This research paper presents the development of a sensor interface module that expands the data acquisition capabilities of existing Varun main controller devices. Traditional agriculture frequently makes decisions based on past performance, which can result in inefficiencies and have an adverse effect on the environment. By utilizing sensor technology and data analysis, precision agriculture presents a possible option. This method gathers real-time data on a range of agricultural factors by …
Published in Recent Trends in Sensor Research & Technology · Vol. 10, Issue 3, 2023 · pp. 30–43 Read article
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Enhancing Pattern Recognition in Social Networking Dataset using Data Mining Techniques
Abstract: Databases today can range in size more than terabytes. Within these masses of data lies hidden information of strategic importance. But when there are so many trees, how do we draw meaningful conclusions about the forest? The newest answer is data mining, which is being used both to increase revenues and to reduce costs. Data mining is a process that uses a variety of data analysis tools to discover patterns …
Published in Journal Of Network security · Vol. 1, Issue 2-3, 2013 · pp. 1–7 Read article
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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Productivity Improvement Using Kaizen-Muda Elimination
Abstract: In today's fiercely competitive business environment, achieving operational excellence and sustainable growth is paramount for organizations across diverse industries. The Kaizen philosophy, rooted in Japanese principles, offers a powerful framework for driving continuous improvement by systematically identifying and eliminating waste, or "muda." This paper explores the concept of Kaizen and its application in eradicating muda, paving the way for enhanced productivity, cost reduction, and a competitive advantage. Kaizen, which translates …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 1–6 Read article
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Flooding of Urban Drainage Systems: Risk Analysis Study
Abstract: Floods are considered as to be among the most severe natural disasters because of their unpredictability, their overwhelming power and the difficulty to assess the related risks. Consequently, flooding damage is inevitable. This paper focuses on the identification of potential flood hazards in urban drainage systems. The flooding causes and modes are analyzed by two main methods: fault tree and event tree. The frequencies of natural events and operational obstacles …
Published in Journal of Water Resource Engineering and Management · Vol. 6, Issue 3, 2019 · pp. 1–5 Read article
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A Review of Code Defect Likelihood Using ML Methods
Abstract: AbstractSoftware begets defects and defects are inevitable in software design and coding. This paper focused on five machine learning analysis models (MLAM); Support Vector Machine, Random Forest, K-Nearest Neighbor, Classification and Regression Tree, and Linear Discriminant Analysis. These models are trained to detect software defects using the software defect dataset from Promise data repository. The collected dataset is preprocessed to reduce the amount of redundant features using a dimension reduction …
Published in Journal of Open Source Developments · Vol. 7, Issue 3, 2020 · pp. 1–6 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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Knowledge, Awareness, and Perceptions of Cervical Cancer and Screening Among Women in Rural South India
Abstract: Background: Cervical cancer is still a major public health problem in South India, with rising figures of morbidity and mortality, in spite of progress in prevention, early detection, and treatment. Cervical cancer is the second leading cause of death due to cancer among Indian women, with around 123000 new cases and 67000 deaths every year. The delay in diagnosing CVD and low participation in screening programs is due to poor …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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Bayesian Inference to Time Series Data Mining
Abstract: The time series data mining (TSDM) framework is a fundamental contribution to the field of time series analysis and data mining in the recent past. Methods based on the TSDM framework are able to successfully characterize and predict complex, nonperiodic, irregular and chaotic time series. The TSDM methods overcome limitations including stationarity and linearity requirements of traditional time series analysis techniques by adopting data mining concepts for analyzing time series. …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 3, 2014 · pp. 10–14 Read article
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Bibliometric Analysis of Open Access Journals in Mathematics Indexed in DOAJ Database
Abstract: Abstract The article reports the findings of bibliometric analysis of open access journals available in the subject of ‘Mathematics’ indexed in directory of open access journals (DOAJ). The bibliometric attributes used are; journals with subject heading ‘mathematics’, country of publication, language used in journals, publisher of journals, co-relation of mathematical journals with other subject fields, peer review policy, archiving policy, security and standard features followed by journals. Total 556 journals …
Published in Journal of Advancements in Library Sciences · Vol. 3, Issue 2, 2016 · pp. 50–88 Read article
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Cancer biology and Sequencing technology: A new era for personalized patient care.
Abstract: Cancer is one of the most deadly diseases causing high mortality around the world. Lot of efforts are being made to be able to device a proper treatment for cancers. The majority treatments for various types of cancers comprise of surgery, radiation, chemotherapy, hormone therapy, immune therapy, and targeted therapy. These methods of treatment may not be fully able to get rid of cancer but able to extend the life …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 4, Issue 3, 2017 · pp. 1–14 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Evaluate the effect of knowledge, skills, and self-efficacy on home care of tracheostomy among caregivers of clients attending head & neck cancer opd at TMH with a view to develop pictographic pamphlet
Abstract: Statement of problem: Evaluate the effect of knowledge, skills, and self-efficacy on home care of tracheostomy among caregivers of clients attending head & neck cancer OPD at TMH with a view to develop pictographic pamphlet. The research approach used in this study was a survey approach and the design was descriptive one group pre-test post-test design. Samples were caregiver of patients with tracheostomy attending the head and neck OPD and …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 3, 2023 · pp. 1–15 Read article
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Real-time Water Quality Analysis Using Fuzzy Logic
Abstract: Nowadays the availability of safe drinking water is very difficult. In our project we are analysing water quality using different parameters like pH, turbidity, temperature and TDS for determining its safety level by monitoring the data from the readings. Moreover, we have a monitoring system for the data and also a webpage where all the data from these system is displayed. The sensors are connected to an Arduino Nano microcontroller …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 2, 2026 · pp. 01–11 Read article
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IoT-Based Diabetes Management: Advancements and Challenges in Healthcare
Abstract: The integration of the Internet of Things (IoT) into healthcare has revolutionized disease management by enabling real-time monitoring, data analysis, and proactive interventions. This paper explores how IoT applications can significantly enhance diabetes management by providing sustainable and innovative healthcare solutions. Leveraging IoT-enabled devices such as Continuous Glucose Monitoring (CGM) systems, smart wearables, and remote patient monitoring tools, diabetes care can be personalized and made more efficient, reducing long-term complications. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Impact of Environmental Degradation on Steel City of Odisha: A Geospatial Approach
Abstract: Earth has always had an abundance of natural resources, but as the number of people on the planet grew, so did their needs, and they were taken from the environment at an ever-increasing rate. Depending on the kind of pollutant, the duration and intensity of exposure, as well as other elements like an individual's health risks and the combined effects of several pollutants or stressors, the effects of air pollution …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 2, 2025 · pp. 28–40 Read article