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113 articles for “learning experiences”
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An Investigation into the Relationship between Mental Well-being and Decision-making Competency among Young Adults at Chitkara University, Punjab
Abstract: Mental well-being encompasses an individual’s holistic state of understanding their own adaptability and effectively navigating life’s challenges. It denotes the capacity to comprehend, regulate, and express emotions, as well as to maintain satisfying relationships and cope with the stresses of daily life. Decision-making competency (DMC), on the other hand, encapsulates an individual’s ability to take ownership of decision-making processes, ensuring timely and appropriate choices that align with personal values and …
Published in International Journal of Neurological Nursing · Vol. 10, Issue 1, 2024 · pp. 1–25 Read article
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Modeling of Material Removal Rate in Micro EDM Using Neural Network
Abstract: In micro-electrical discharge machining (Micro EDM) machining, material removal rate (MRR) is the particular main output parameter. Here we will discover various machining parameters get an effect on the particular MRR. For production industries, to maximize the results from Micro EDM, appropriate predictive designs for MRR must end up being constructed. This particular report utilizes neural network modeling to predict MRR over the particular machining time for assortment of cutting …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 4, Issue 1, 2018 · pp. 30–39 Read article
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AI-Assisted Conversion and Optimization of Analog-to-Digital Signal Transmission forLow-Power IoT and Edge Devices
Abstract: The booming implementation of Internet of Things (IoT) and edge computing devices is requiring theimplementation of efficient signal transmission mechanisms to balance between performance and energyefficiency. The current paper introduces an AI-assisted conversion and optimization system of the analog-to-digital (A/D) signal transmission, aimed at low-power IoT and edge devices. The given strategy combines both machine learning algorithms and adaptive sampling and quantization methods to optimize the A/D conversion process in …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 2, 2025 Read article
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Machine Learning-Based Channel Estimation for 5G NR Systems: A Comprehensive Review of TDL/CDL Channel Models and CNN Architectures
Abstract: Accurate channel estimation is a fundamental requirement for reliable communications in fifth-generation New Radio (5G NR) systems, where highly dynamic propagation environments impose severe challenges on conventional pilot-based methods. This study provides a thorough analysis of channel estimate methods for 5G NR, including everything from contemporary deep learning (DL) techniques based on Convolutional Neural Networks (CNNs) to traditional Least Squares (LS) and Minimum Mean Square Error (MMSE) estimators. Our analysis …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Case Vignette: “An Effective Strategy to Facilitate Learning of Graduate Nursing Students Regarding Nursing Management of Patient with COPD.”
Abstract: The present study was carried out to explore the impact of case vignette as an effective strategy to facilitate learning among graduate nursing students regarding nursing management for patient with COPD (Chronic Obstructive Pulmonary Disease) sample size 40 students and purposive sampling technique was used. Forty selected samples had already undergone expository teaching on COPD and its nursing management. The present study was modeled on single pre- and post-test experimental …
Published in International journal of Nursing Science Practice and Research · Vol. 8, Issue 2, 2022 · pp. 1–5 Read article
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IoT-Based Fault Detection in Distribution Lines
Abstract: Quickly detecting and pinpointing failures in electrical distribution lines are important for shortening the duration of service interruption, reducing maintenance costs and increasing safety. In this work, we propose a realistic architecture for an Internet-of-Things (IoT)-enabled fault detection system designed for distribution networks. In order to continually assess electrical characteristics including voltage, current, frequency, temperature, and line status, the suggested architecture combines inexpensive, dispersed sensor nodes placed along feeders and …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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Assessment of Clinical and Investigative Profiles and Treatment Approaches in Newborns with Birth Asphyxia Admitted to Pravara Rural Hospital, Loni. [BK]
Abstract: Introduction: The inability to intake sufficient oxygen into the lungs increases the likelihood of hypoxia. Hypoxia is a condition in which there is an inadequate supply of oxygen reaching the body’s cells and tissues. Hypoxia can result in various serious and potentially life-threatening complications. But if you know what to look for, you can manage the condition before it leads to dangerous complications. You may have heard of both hypoxia …
Published in International Journal of Pediatric Nursing · Vol. 10, Issue 2, 2024 · pp. 24–30 Read article
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Comparison of Various Methodologies used for Automating Plant Disease Detection using Image Processing
Abstract: In India, major of economy and development depends on agriculture, so plant disease detection becomeimportant for us so that if any crop is destroyed due to diseases is known to us prior and we can overcomethe loss of crops due to plant diseases. It is better to catch the disease in the initial phase so that the largescaledamage of crops can be prevented. Traditionally, the diseases incurred via the naked …
Published in International Journal of Agrochemistry · Vol. 7, Issue 1, 2021 · pp. 20–23 Read article
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Future Trends in Web Analytics: A Comprehensive Review
Abstract: This review paper explores future trends in web analytics, focusing on their impact on business and technological advancements. The paper discusses critical areas such as advanced data analytics, mobile analytics, offline and online data integration, privacy protection, and data visualisation. Drawing upon scientific literature, the paper highlights the significance of artificial intelligence, machine learning, and sentiment analysis in deepening data insights. Integrating offline and online data and the growing importance …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 12–17 Read article
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Advancing Early Detection of Menkes Disease Through Image Analysis and Biosensor Integration
Abstract: Menkes disease, a rare X-linked recessive disorder of copper metabolism, poses significant challenges in early diagnosis due to its nonspecific initial symptoms. This paper presents a comprehensive approach to enhance the early detection of Menkes disease by leveraging image processing techniques, pattern recognition algorithms, and innovative biosensor technologies. A novel framework is proposed that combines analysis of hair microscopy images, facial feature recognition, and copper-sensitive biosensors to create a multi-modal …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 24–34 Read article
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Malaria Detection using Machine Learning
Abstract: A life-threatening disease called Malaria is caused by parasites that get transmitted intopeople's body by the bites of infected mosquitoes. If Automation is used for the diagnosisprocess of this disease it will enable accurate diagnosis of the disease and hence it willdeliver a reliable health-care to resource-scarce areas. Currently malaria is being diagnosedby performing microscopic tests on blood smears of the patients. They require examinationby a skilled and well experienced …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 6, Issue 1, 2020 · pp. 40–44 Read article
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Identifying Fake News Using Big Data
Abstract: In today's world, where digital information spreads swiftly, the rise of fake news poses a threat to society. This research paper presents a method to address this issue by employing data analytics. To address the issues of misinformation, public manipulation, and threats to democracy we propose a framework. Our strategy incorporates advanced methodologies, including natural language processing, machine learning, and network analysis. Using these techniques, we examine various data sources …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 7–14 Read article
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Virtual Reality in Nursing Education: Enhancing Clinical Training and Competency
Abstract: Background: The integration of virtual reality (VR) in nursing education has emerged as a transformative approach to bridge gaps in clinical training, particularly where traditional hands-on opportunities are limited. This study investigates the effectiveness of VR-based simulation on improving clinical competency and self-efficacy among undergraduate nursing students. Methods: A quasi-experimental, pre-test/post-test design was employed with 60 final-year nursing students divided into control (traditional training) and experimental (VR training) groups. Participants …
Published in International journal of Nursing Science Practice and Research Read article
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Convolutional Neural Network Algorithm for Stress Field Approximation for a Uniaxially Loaded Plate with Holes
Abstract: ABSTRACTKnowing the high stress concentration and its location around a hole is of practical importance in designing engineering structures, effective parameters can be selected in order to achieve minimum stress concentration around the hole(s). The visualisation of the stress distribution is done experimentally or numerically using finite element analysis (FEA). This study involved the approximation of the von Mises stress field distribution around regular holes in finite metallic plates, based …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 1–12 Read article
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E.M.E.R.G.E. (Empowering Mixed-Use Ecosystem Realms for Revenue, Growth, & Expression).
Abstract: Contemporary urban life is increasingly fragmented, with learning, working, socializing, & leisure dispersed across disconnected parts of the city. This disconnection leads to long commutes, enhances dependence on mobility, increases daily stress, and weakens public life & community interaction. Rigid zoning laws & mono-functional building typologies fail to respond to the hybrid, layered, & dynamic patterns of everyday urban life, particularly within the context of emerging digital economies and evolving …
Published in International Journal of Housing and Human Settlement Planning · Vol. 12, Issue 2, 2026 Read article
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A study to assess the effectiveness of teaching learning module regarding attention deficit hyperactivity disorder of children in terms of Knowledge among school teachers at Coimbatore
Abstract: Children with ADHD also may struggle with low self-esteem, troubled relationships and poor performance in school. Teachers are often the first ones to suspect attention deficit/hyperactivity disorder (ADHD) in their students, because they are with them for most of the day and they know how normal students typically behave in classroom situations. The aim of this study is to assess the teachers’ level of knowledge of ADHD and identify some …
Published in International Journal of Pediatric Nursing · Vol. 7, Issue 2, 2021 · pp. 48–52 Read article
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Cost-Constrained Sensor Reduction for Deployment AwareIoT-Based Multiclass Water Quality Monitoring
Abstract: Large-scale Internet of Things deployment for water quality monitoring systems is bounded by the capital and several other costs associated with the multi-dimensional sensor. While prior research demonstrates strong predictive performance using multi- parameter physicochemical sensing, limited attention has been given to explicit sensing cost constraints and deployment feasibility. This work formulates multiclass water quality classification as a cost-constrained learning problem in which sensing dimensionality is minimized subject to bounded …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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A Sensor Integrated Tool for Cutting Force Monitoring in Gantry Milling to Improve Flatness and Surface Finish: Review Study
Abstract: AbstractPrecision machining of sector plates plays a vital role in the efficient functioning of Air Pre-Heaters(APH), which are integral components of thermal power plants. These plates are subjected to harshthermal cycles and mechanical loads, making dimensional accuracy critical. For optimal heatexchange performance and mechanical reliability, it is essential to maintain tight manufacturingtolerances – flatness within ±400 microns and thickness up to 13 mm. Deviation from theseparameters can lead to air …
Published in International Journal of Manufacturing and Materials Processing · Vol. 11, Issue 1, 2025 · pp. 25–45 Read article
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CNN-Based Traffic Sign Recognition with Voice Alerts
Abstract: Traffic sign recognition is a crucial component of intelligent transportation systems, significantly enhancing road safety by aiding both autonomous and human drivers. This paper presents a convolutional neural network-based traffic sign recognition system integrated with voice alerts. Our approach utilizes a deep learning model trained on a comprehensive dataset of traffic signs to accurately identify various road signs in realtime. Upon recognition, the system issues corresponding voice alerts to inform …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–9 Read article
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Study to Evaluate Self-instructional Module on Diabetic Foot Ulcer Prevention Knowledge and Attitude in Selected Tripura Diabetic Patients
Abstract: Introduction and objectives of the study: Today's medical profession faces the "ice berg" disease of diabetes mellitus in India, the "Diabetic Capital of the World". Globally, diabetes is one of the biggest public health issues of the 21st century. It is expected that 578 million people would have diabetes by 2030 and 700 million by 2045. Foot ulcers are the scariest diabetic complication. Up to 25% of diabetics get foot …
Published in International Journal of Medical Surgical Nursing · Vol. 6, Issue 2, 2023 · pp. 19–29 Read article