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743 articles for “Network Model”
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EMOTION RECOGNITION FROM ELECTROENCEPHALOGRAM SIGNAL AND EYE MOVEMENT BASED ON DEEP LEARNING
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 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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A Comparison of Different Generative AI Models
Abstract: Generative models have significantly advanced the field of artificial intelligence by allowing machines to produce complex and realistic outputs such as images, text, and other forms of data. Among the leading frameworks in this domain are generative adversarial networks (GANs), variational autoencoders (VAEs), and architectures based on Transformers. Each model offers specific benefits and drawbacks concerning design structure, training demands, and range of applications. This paper provides a detailed comparison …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 16–22 Read article
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Supply Chain Strategy, Supply Chain Flexibility and its Impact on Supply Chain Performance: A Statistical Modeling Approach
Abstract: In the cutting edge aggressive business condition, the associations coordinate their businesses deliberately within supply chain network. Current research is an attempt to highlight the impact practices in context of supply chain (i.e. strategy and flexibility) on performance in a sample of the automobile industry in India. With the assistance of quantitative research, a poll gets ready and an overview was directed among the respondents. A measurable instrument used to …
Published in Journal of Production Research & Management · Vol. 9, Issue 2, 2019 · pp. 29–34 Read article
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Forecasting of Factors Affecting Thermiston Work Productivity Estimation by Using Artificial Neural Network
Abstract: The research aims to find factors affecting of Thermiston work productivity and the derivation of an equation to predict the rates of Thermiston work productivity by using artificial neural network technology and compared with traditional methods. The Artificial Neural Network with multilayer by back-propagation error technique for modeling the productivity estimation is used, it is founded that the ANN are able to manage to, can predict the productivity for Thermiston …
Published in Journal of Construction Engineering, Technology & Management · Vol. 7, Issue 1, 2017 · pp. 10–21 Read article
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Simulation and Analysis of S-CSRR PIFA for C-band 5G wireless networks
Abstract: In this paper, S-CSRR (Square-Complementary Split Ring Resonator) Planar Inverted F Antenna model is designed and simulated in the HFSS software. For compact and portable devices being preferred in 5G technology, the proposed antenna is helpful. The PIFA antenna with metamaterials (MTM) is beneficial for 4G and 5G wireless communication applications and covers C-band frequencies. The C-band frequency range of 3300-4200 MHz and 4400-5000 MHz is used in the research. …
Published in Journal of Microwave Engineering and Technologies · Vol. 9, Issue 2, 2022 · pp. 15–25 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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Transforming Human Resources Leveraging AI Across the Associate Lifecycle for Strategic Success
Abstract: AI is taking the lead in changing the game in human resources by mitigating challenges and optimizing processes throughout the entire associate lifecycle. From pre-hire, AI helps with interview bias, enhances hire projections, and supports talent acquisition with predictive analytics. Once onboarded, AI helps with compensation benchmarking, automates performance feedback with the mitigation of bias, and analyzes associate sentiment through NLP and LLMs. In the middle of the life cycle, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 30–36 Read article
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Controller Performance Assessment (CPA) of Intelligent Control for Non-linear System
Abstract: The objective of this paper is to design and undertake comparative analysis of classical and intelligentcontrollers for nonlinear system. These controllers are compared based on controller performanceassessment in which the different parameters as overshoot, steady-state error, rise time, settling time,response of reference change and output variance are analyzed. To achieve these objectives, the water tankcontrol problem as nonlinear system has been built in Simulink and implementations traditionally classicalcontroller and advance …
Published in Journal of Control & Instrumentation · Vol. 1, Issue 1-2-3, 2011 · pp. 25–33 Read article
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A Feasibility Analysis on New Drainage Channel to Control Flooding in Southwest Chennai Using Hydraulic Model
Abstract: Flood Management plays a major role in minimizing the socio-economic loss in a watershed. In the urban context, flood is due to uncontrolled settlements of migrated population along the length of surplus carrying channels. This study focuses on feasibility analysis of existing drainage channel and proposed drainage channel network as structural management measure for a watershed, proposed by public work department of Chennai to reduce the impact of flood. In …
Published in Journal of Water Resource Engineering and Management · Vol. 2, Issue 1, 2015 · pp. 1–7 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article
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Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article
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Fuzzy Variable Frame Analysis for Speech Recognition
Abstract: AbstractRecent works in machine learning has focused on models such as support vector machine (SVM), artificial neural network (ANN) and long short-term memory (LSTM), for automatically controlling the generalization and parameterization of the optimization process. This paper presents a fuzzy interpretation frame analysis procedure using LSTM classifier for noisy speech at word level using thresholding and local maxima procedure at framing level for the recognition process. Front end MFCC procedure …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 9–18 Read article
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Classification of PQ Disturbances in Induction Motor using Neuro-Fuzzy
Abstract: This paper presents a methodology of classification of PQ disturbances in the supply to induction motor using ANFIS. Wavelet transform is applied to the stator currents for the extraction of the signature indicating the variations in the supply. These wavelet coefficients are fed as input to ANFIS. This data has been divided into two sets: 37 training data set and 38 testing data set. The training data set has been …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 1–8 Read article
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Securities Control in Ad Hoc Network on Scatternet
Abstract: This study presents and evaluates an ad hoc network formatting algorithm. The algorithm is discussed to feature the specifications of Bluetooth under a designed purpose, a limited range device with a host and numbers of connected devices wirelessly. There are many research and analyses done till today’s date for the selection of secured devices. Proposed solutions have been evaluated utilizing the Open Web Application Security Project (OWASP). Nowadays, Bluetooth is …
Published in Journal Of Network security · Vol. 10, Issue 2, 2022 · pp. 24–29 Read article
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Performance Evaluation of 5G transmission system and Simulation Modeling
Abstract: Orthogonal multiple access (OFDMA) is a very important technology for the fifth generation (5G) wireless communication networks to provide the need of the flexible demands of users on lower latency rate, high level of reliability, good amount of connectivity, large fairness, and high data throughput. The key idea behind MIMO based 5G networks are to provide multiple users in common resource block. The MIMO OFDM principle is the main framework …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 21–32 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article