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134 articles for “learning environments”
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Algorithmic Approaches for Data Mining and Machine Learning
Abstract: ABSTRACTTrends and technology always innovative and comes with some new. Sometimes technologies are introduces in more user friendly environment. In such version of technology advancement are also incorporated. Data mining is a best widespread knowledge attainment approach for knowledge discovery. The naval trends Machine learning also have a big interfere of data mining. Infect most of the data mining algorithm and methods are utilized for machine learning with minor amendment …
Published in International Journal of Distributed Computing and Technology · Vol. 6, Issue 2, 2020 · pp. 24–29 Read article
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Use of Natural Language Processing for Hate Speech Detection on SocialMedia:
Abstract: The exponential growth of social media platforms has led to an increase in user- generated content, enhancing global connectivity but also facilitating the spread of harmful language, including hate speech. Addressing this issue requires robust, Naïve Bayes, Decision Tree, K-Nearest Neighbours (KNN), Linear Regression, and Random Forest—were tested, with Linear Regression achieving the highest accuracy automated systems for detecting and mitigating offensive content. This paper presents a comprehensive analysis of …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 9–16 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Configuring HTTP and DNS Server in Cisco Packet Tracer
Abstract: Setting up the server that will host the website requires the process of configuring HTTP. In order to do this, the server must be configured to use the correct domain name, the port number must be specified so that the server can listen for HTTP requests, and the IP address must be specified so that the server can respond to HTTP requests. The Cisco Packet Tracer network simulation software's HTTP …
Published in International Journal of Broadband Cellular Communication · Vol. 8, Issue 2, 2022 · pp. 19–27 Read article
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Deep Learning Techniques for Optimizing Resource Allocation and Sustainability in the Next Generation of 6G Wireless Networks
Abstract: The upcoming sixth generation (6G) of wireless communication networks aims to meet challenging requirements such as ultra-reliable low-latency services, massive connectivity for billions of smart devices, and intelligent automation across highly diverse environments. Along with these goals, the issues of energy efficiency and environmental sustainability are becoming equally important, as the rising number of users and traffic volumes will directly increase power demand and carbon emissions. To lower total energy …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 Read article
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Intelligent Data Analytics on Cloud Infrastructure:Real-Time Insights and Managed Service Models
Abstract: This paper examines the integration of advanced data analytics and machine learning within modern cloud infrastructure, highlighting how organizations can transform large volumes of unstructured data into actionable business insights that drive competitive advantage. Cloud platforms leverage scalability and elasticity to efficiently process and analyze massive datasets in real time, allowing enterprises to identify hidden patterns, detect operational anomalies early, and generate accurate forecasts of future outcomes. A key factor …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 36–46 Read article
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Network Intrusion Detection Using Wireshark and Machine Learning
Abstract: The growth of networked devices has highlighted the desire for advanced intrusion detection (IDS) tools to protect digital systems from evolving cyber threats. Traditional IDS systems are often difficult to adapt to the threat environment because they rely on predefined signature lists. This study presents a new approach that combines Wireshark, a widely used network packet analysis tool, with advanced machine learning for intrusion detection. Our system leverages Wireshark's data …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 23–31 Read article
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Anxiety Level of High School Students In Online Learning in Kendal, Central Java, Indonesia
Abstract: COVID-19 has suddenly changed everyday life, where the learning system, which is usually done face-to-face, either in the school environment or in the practice area, has turned online. This method is almost applied throughout the world, including Indonesia. The advantage of this method is that the learning process is no longer limited by time and space. The online learning process causes students to experience anxiety. The purpose of this study …
Published in International Journal of Nursing Critical Care · Vol. 7, Issue 1, 2021 · pp. 23–27 Read article
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Satellite Image Classification using Deep Learning
Abstract: Satellite imagery is essential for lots of applications along with catastrophe response, regulation enforcement, and monitoring an environment. These packages require the guide identity of objects and facilities in imagery. Because the geographical areas to be protected are large and the analysts needed to do the searches are scarce, automation is required. Yet traditional item detection and category algorithms are too inaccurate and unreliable to clear up the problem. Deep …
Published in International Journal of Software Computing and Testing · Vol. 8, Issue 1, 2022 · pp. 29–36 Read article
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A Roadmap for Cloud Computing for Higher Education
Abstract: ABSTRACTAdvancement of technology provides new opportunities for improving teaching and learning. The new technology provides opportunity individual to personalize the environment where they work. Here in this paper we try to explore the educational potential of cloud computing to exploit its affordability in teaching in context of higher education. Cloud computing has important place for higher education both as powerful platform and computing tool. Though cloud computing provide number of …
Published in International Journal of Software Computing and Testing · Vol. 6, Issue 2, 2020 · pp. 36–44 Read article
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Real-Time Traffic Management System Utilizing Machine Learning Techniques
Abstract: AbstractThe rapid increase in the number of vehicles on roads has created significant challenges forconventional traffic management systems, which struggle to efficiently regulate traffic flow undervarying conditions. Traditional traffic signals operate on fixed timing cycles, failing to adapt tofluctuating vehicle densities across different lanes. This inefficiency results in unnecessary delays,increased congestion, longer travel times, and excessive fuel consumption. Additionally, fixed-timingsignals do not account for dynamic traffic patterns, leading to bottlenecks …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 24–31 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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Data Science for Environmental Modelling
Abstract: Abstract: Soil moisture is a critical Earth system variable linking atmospheric, hydrological, and ecological processes. However, observations are sparse and fragmented: in situ gauges provide point data, satellite missions (SMAP, SMOS, Sentinel-1) offer broad coverage at coarse resolutionQ, and land‐surface models (GLDAS, ERA5, etc.) yield estimates with their own biase. Here we propose a conceptual framework for integrated environmental data modelling, combining rainfall, temperature, and soil moisture information with machine …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 · pp. 33–40 Read article
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Data Science for Environmental Modelling
Abstract: Abstract: Soil moisture is a critical Earth system variable linking atmospheric, hydrological, and ecological processes. However, observations are sparse and fragmented: in situ gauges provide point data, satellite missions (SMAP, SMOS, Sentinel-1) offer broad coverage at coarse resolutionQ, and land‐surface models (GLDAS, ERA5, etc.) yield estimates with their own biase. Here we propose a conceptual framework for integrated environmental data modelling, combining rainfall, temperature, and soil moisture information with machine …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 Read article
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Performance Analysis of Hybrid Signal Processing Methods in Modern Communication Networks
Abstract: Modern communication networks require high-speed, reliable, and energy-efficient signal transmission for applications such as wireless communication, satellite systems, Internet of Things (IoT), smart healthcare, and next-generation 5G/6G networks. Traditional signal processing techniques often face limitations in dynamic communication environments due to interference, noise, latency, and bandwidth constraints. Hybrid signal processing methods combine multiple techniques including analog-digital processing, adaptive filtering, beamforming, machine learning, and intelligent optimization to enhance communication performance and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 22–35 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: Abstract This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 1–7 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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Sustainable Development and Renewable Energy in India through Education
Abstract: In this paper we have to discuss about the sustainable development and renewable energy in India through education. This research was featured to perceive in our time is how to sustain our study. It also discusses the multiple difficulties that may be had to face in the course of teaching out to the goal spectator. There has been overhauling of teacher education programmes across the land, Hence it is essential …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 7, Issue 2, 2021 · pp. 11–16 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