Seungwoo Kang¹, Seyha Ros¹, Inseok Song¹, Prohim Tam¹, Sa Math², Seokhoon Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1967-1983, 2023, DOI:10.32604/cmc.2023.045020

Abstract Intelligent healthcare networks represent a significant component in digital applications, where the requirements hold within quality-of-service (QoS) reliability and safeguarding privacy. This paper addresses these requirements through the integration of enabler paradigms, including federated learning (FL), cloud/edge computing, software-defined/virtualized networking infrastructure, and converged prediction algorithms. The study focuses on achieving reliability and efficiency in real-time prediction models, which depend on the interaction flows and network topology. In response to these challenges, we introduce a modified version of federated logistic regression (FLR) that takes into account convergence latencies and the accuracy of the final FL model within healthcare networks. To establish… More >

Dah-Jing Jwo^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2137-2155, 2023, DOI:10.32604/cmc.2023.034308

Abstract The goal of this work is to provide an understanding of estimation technology for both linear and nonlinear dynamical systems. A critical analysis of both the Kalman filter (KF) and the extended Kalman filter (EKF) will be provided, along with examples to illustrate some important issues related to filtering convergence due to system modeling. A conceptual explanation of the topic with illustrative examples provided in the paper can help the readers capture the essential principles and avoid making mistakes while implementing the algorithms. Adding fictitious process noise to the system model assumed by the filter designers for convergence assurance is… More >

Jiarui Wu¹, Yuzhen Kang², Junxiao Feng^1,*

Energy Engineering, Vol.120, No.12, pp. 2783-2802, 2023, DOI:10.32604/ee.2023.029358

Abstract To enhance system stability, solar collectors have been integrated with air-source heat pumps. This integration facilitates the concurrent utilization of solar and air as energy sources for the system, leading to an improvement in the system's heat generation coefficient, overall efficiency, and stability. In this study, we focus on a residential building located in Lhasa as the target for heating purposes. Initially, we simulate and analyze a solar-air source heat pump combined heating system. Subsequently, while ensuring the system meets user requirements, we examine the influence of solar collector installation angles and collector area on the performance of the solar-air… More >

Arafat A. Bhuiyan^a,c, M. Ruhul Amin^b, Jamal Naser^c, A. K. M. Sadrul Islam^a

Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-11, 2015, DOI:10.5098/hmt.6.5

Abstract In this study, the effects of thermal and hydraulic characteristics of wavy fin and tube heat exchanger are investigated. Simulation has been carried out by a commercial computational fluid dynamics code, ANSYS CFX12.0. The main objective of this study is to investigate the flow characteristics in turbulent flow. Results are predicted for the turbulent flow regime (2100≤Re≤7000) and compared with author’s previous work for laminar (400 ≤Re≤1200) and transitional (1300≤Re≤2000) flow regime. Regarding turbulence, the k-ω model was used to predict the turbulent flow characteristics with 5% turbulence intensity. Predicted results were compared with the experimental data for the purpose… More >

Seyed Milad Mirabedin^*

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-6, 2016, DOI:10.5098/hmt.7.17

Abstract This work focuses on numerical validation of natural convection heat transfer of TiO2-water nanofluids in a cylindrical container using COMSOL. The main aim of this study is to examine different available approaches to calculate effective thermal conductivity and compare them with experimental data available in the literature. Simulation results show that for considered mixture, average Nusselt number decreases by increasing Rayleigh number and particle volume fraction. It has been found that only one model was able to represent similar trends for given particle volume fractions, compared to experimental results. More >

Dun Cao¹, Jia Ru¹, Jian Qin¹, Amr Tolba², Jin Wang¹, Min Zhu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1365-1384, 2024, DOI:10.32604/cmes.2023.030260

Abstract Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles, people, transportation infrastructure, and networks, thereby realizing a more intelligent and efficient transportation system. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topological structure of IoV to have the high space and time complexity. Network modeling and structure recognition for 3D roads can benefit the description of topological changes for IoV. This paper proposes a 3D general road model based on discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on… More >

Wenbing Zhao^1,*, Chenxi Huang², Yizhang Jiang³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1015-1017, 2024, DOI:10.32604/cmes.2023.031566

Abstract This article has no abstract. More >

Shariar Md Imtiaz¹, Ki-Chul Kwon¹, F. M. Fahmid Hossain¹, Md. Biddut Hossain¹, Rupali Kiran Shinde¹, Sang-Keun Gil², Nam Kim^1,*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2921-2937, 2023, DOI:10.32604/csse.2023.040205

Abstract This article describes a novel approach for enhancing the three-dimensional (3D) point cloud reconstruction for light field microscopy (LFM) using U-net architecture-based fully convolutional neural network (CNN). Since the directional view of the LFM is limited, noise and artifacts make it difficult to reconstruct the exact shape of 3D point clouds. The existing methods suffer from these problems due to the self-occlusion of the model. This manuscript proposes a deep fusion learning (DL) method that combines a 3D CNN with a U-Net-based model as a feature extractor. The sub-aperture images obtained from the light field microscopy are aligned to form… More >

Shuqin Zhang, Xinyu Su^*, Peiyu Shi, Tianhui Du, Yunfei Han

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 349-377, 2023, DOI:10.32604/cmc.2023.040964

Abstract Cyber Threat Intelligence (CTI) is a valuable resource for cybersecurity defense, but it also poses challenges due to its multi-source and heterogeneous nature. Security personnel may be unable to use CTI effectively to understand the condition and trend of a cyberattack and respond promptly. To address these challenges, we propose a novel approach that consists of three steps. First, we construct the attack and defense analysis of the cybersecurity ontology (ADACO) model by integrating multiple cybersecurity databases. Second, we develop the threat evolution prediction algorithm (TEPA), which can automatically detect threats at device nodes, correlate and map multi-source threat information,… More >

Bishrul Haq¹, Sher Muhammad Daudpota¹, Ali Shariq Imran², Zenun Kastrati^3,*, Waheed Noor⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 115-137, 2023, DOI:10.32604/cmc.2023.040638

Abstract The Internet has become one of the significant sources for sharing information and expressing users’ opinions about products and their interests with the associated aspects. It is essential to learn about product reviews; however, to react to such reviews, extracting aspects of the entity to which these reviews belong is equally important. Aspect-based Sentiment Analysis (ABSA) refers to aspects extracted from an opinionated text. The literature proposes different approaches for ABSA; however, most research is focused on supervised approaches, which require labeled datasets with manual sentiment polarity labeling and aspect tagging. This study proposes a semi-supervised approach with minimal human… More >