Search
743 articles for “Network Model”
-
Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
-
Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article
-
Effect of Fragment Size and Contention Window on the Performance of IEEE 802.11 WLANs
Abstract: Wireless communications is, by any measure, the fastest growing segment of the communications industry. The IEEE has standardized the 802.11 protocol for wireless local area networks. The IEEE 802.11 standard has defined two different access mechanisms in order to allow multiple users to access a common channel, the distributed coordination function (DCF) and a centrally controlled access mechanism called the point coordination function (PCF). DCF is a carrier sense multiple …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 3, Issue 2, 2016 · pp. 6–12 Read article
-
Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum–Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 19–35 Read article
-
Triangular Waveform Generation using Mixed Signal Modeling
Abstract: The development of modeling languages such as Verilog-HDL and Verilog-AMS allows the behavior of analogue and mixed signal circuits to be described with a more lucid way as compared to the conventional circuit-level simulators. Mixed-signal simulators are thus providing a new platform for more efficient modeling of mixed signal that contains both the analogue and discrete features which was not previously possible. The non-linear characteristics of many circuits are still …
Published in Journal of VLSI Design Tools and Technology · Vol. 4, Issue 2, 2014 · pp. 8–17 Read article
-
Supply Chain Design Considering Social and Environmental Risks
Abstract: The aim of the research is to design a supply chain taking into account social and environmental risks. In this research, an attempt was made to present a model that, by considering variables close to the real world, simultaneously considers cost and sustainability issues for designing a meat supply chain network, including locating facilities, using technology in them, how products flow in the network, etc. In order to examine the …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 35–43 Read article
-
A Review Of Deep Learning Applications For Speech Processing Improvement
Abstract: Improve the quality of the spoken word is a common goal for many audio and speech signal processing applications. A noisy voice signal's quality and understandability may be improved via speech augmentation. Speech augmentation is critical in a wide range of fields, including hearing aids, ASR, and mobile communication. DNN-based architectures for speech recognition and augmentation have shown to be quite effective in recent years, according to a new study. …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 14–19 Read article
-
An empirical investigation using artificial neural networks to evaluate the manageability of object-oriented systems
Abstract: Software can be called quality software if it produces consistent outputs over multiple time of testing. There can be very much difficulties to modify and maintain the software with poor maintainability. For assessing the characteristics of object-oriented software, such as scale, inheritance, integrity, and coupling, numerous object-oriented metrics have been recommended. In this study, we explore object-oriented variables that have the potential to be significant antecedents of software maintenance. In …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 2, 2022 · pp. 50–58 Read article
-
Estimation Techniques in Image Restoration - A Survey Approach
Abstract: In the present paper a comparative study of various estimation techniques based on neural network, MATLAB, partial differential equation (PDE) and other proposed models for image restoration are been discussed. An image may be distorted, noisy or blurred and not suitable for extracting desired information or data, so it needs to be restored for desired application. Image restoration techniques are oriented towards modeling the degradation, blur and noise and applying …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 11–16 Read article
-
AI-Driven Innovation in Biomaterials: Predictive Modeling and Design for the Future
Abstract: The integration of artificial intelligence (AI) is revolutionizing the field of biomaterials, paving the way for innovative approaches in their development and production. This paper examines the connection between AI and biomaterials, emphasizing the substantial impact of predictive modeling on the evolution of the field. By examining recent research and cutting-edge uses, the document shows how AI-powered predictive modeling has revolutionized biomaterial design, marking a period of unparalleled precision and …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 25–35 Read article
-
Classifying Abnormalities in Heartbeat Sound
Abstract: Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure in their early stages. In the proposed method, various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (mel-frequency cepstral coefficients). Then, a deep learning approach is applied in which the MFCC audio signals are sent to the CNN (convolutional neural …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 24–31 Read article
-
Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
-
ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
-
AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
-
An Intelligent Complexity-Performance Tradeoff Model of Asynchronous Random Access Protocols in Distributed Edge Computing Using Software Science with Halstead
Abstract: The paradigm shift towards Distributed Edge Computing (DEC) has changed the entire world of the Internet of Things (IoT) connectivity to its core and has spawned the need to implement robust Asynchronous Random Access (ARA) protocols to deal with the contention between a huge range of diverse devices that are constrained by their resources. While there is now extensive optimization of these protocols in contemporary research for channel efficiency (throughput, …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 2, 2026 Read article
-
Integration of 5G and Low Earth Orbit (LEO) Satellite Communication for Global Connectivity
Abstract: This integration revolutionizes global connectivity by merging 5G's urban capabilities with LEO's wilderness coverage. This research examines how LEO satellite constellations can complement terrestrial 5G networks to extend high-speed, low-latency connectivity to underserved regions including rural areas, oceans, and airspace. Recent breakthroughs in LEO satellite technology and successful demonstrations of 5G-satellite integration point to a rapidly evolving ecosystem with significant market growth potential. To fully realize the potential of advanced …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 15–32 Read article
-
Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
-
AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
-
Development of a Model on Pavement Condition Index
Abstract: India has one of the most extensive road networks globally, comprising various categories such as National Highways, State Highways, District Roads, and Village Roads. Each category of road plays an impressive role in economic development and connectivity among different important roads. But, the condition of these roads varies effectively due to difference in traffic intensity, construction quality, maintenance practices and climatic condition. The present research work conducted pavement condition surveys …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 1–7 Read article