Hyangjin Park¹, Haeryun Cho², So Yeon Yoo^3,*

International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1219-1228, 2023, DOI:10.32604/ijmhp.2023.041490

Abstract This study examined factors related to the psychological well-being of older adults and built and verified a model for predicting psychological well-being. The participants were 350 older adults aged over 60 years who lived in South Korea and were active in the local community. The model proposed in this study was found to be suitable. Depression, self-efficacy, and social support had a direct effect on the psychological well-being of older adults, while depression, activities of daily living (ADLs), and self-efficacy had an indirect effect. Self-efficacy and social support mediated the relationship between depression and psychological well-being, and self-efficacy mediated the… More >

Jinghua Chen^1,#, Zihe Wang^2,#, Fabian Herold³, Alyx Taylor⁴, Jin Kuang¹, Ting Wang¹, Arthur F. Kramer^5,6, Liye Zou^1,*

International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1209-1217, 2023, DOI:10.32604/ijmhp.2023.030539

Abstract A significant portion of emerging adults do not achieve recommended levels of physical activity (PA). Previous studies observed associations between features of emerging adulthood and PA levels, while the potential psychological mechanisms that might explain this phenomenon are not fully understood. In this context, there is some evidence that situated decisions toward physical activity (SDPA) and exercise-intensity tolerance might influence PA level. To provide empirical support for this assumption, the current study investigated whether (i) features of emerging adulthood are linked to SDPA, which, in turn, might affect PA engagement; (ii) exercise-intensity tolerance moderate the relationship between SDPA and PA… More >

Benjamin Lepers^a,∗, Thomas Seitz^a, Guido Link^a, John Jelonnek^a,b, Mark Zink^c

Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-6, 2015, DOI:10.5098/hmt.6.20

Abstract A compact 10 kW microwave applicator operating at 2.45 GHz for fast volumetric heating and thermal cracking of lignite briquettes has been successfully designed and tested. In this paper, the applicator design and construction are presented together with a sequentially coupled electromagnetic, thermal-fluid and mechanical Comsol model. In a first step, this model allows us to calculate the power density inside the lignite material and the temperature distribution in the applicator for different water flow rates. In a second step, the total stress due to the thermal dilatation, the internal pressure inside the ceramic and the contact pressure from the… More >

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 >

Wei Zhang¹, Ping He^2,*, Ting Li², Fan Yang¹, Ying Liu³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1893-1910, 2023, DOI:10.32604/cmc.2023.044253

Abstract Some reconstruction-based anomaly detection models in multivariate time series have brought impressive performance advancements but suffer from weak generalization ability and a lack of anomaly identification. These limitations can result in the misjudgment of models, leading to a degradation in overall detection performance. This paper proposes a novel transformer-like anomaly detection model adopting a contrastive learning module and a memory block (CLME) to overcome the above limitations. The contrastive learning module tailored for time series data can learn the contextual relationships to generate temporal fine-grained representations. The memory block can record normal patterns of these representations through the utilization of… More >

Kalpesh Jadav¹, Vishal Sorathiya^1,*, Walid El-Shafai², Torki Altameem³, Moustafa H. Aly⁴, Vipul Vekariya⁵, Kawsar Ahmed⁶, Francis M. Bui⁶

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2009-2030, 2023, DOI:10.32604/cmc.2023.043168

Abstract Shadow extraction and elimination is essential for intelligent transportation systems (ITS) in vehicle tracking application. The shadow is the source of error for vehicle detection, which causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting, vehicle detection, vehicle tracking, and classification. Most of the existing research is on shadow extraction of moving vehicles in high intensity and on standard datasets, but the process of extracting shadows from moving vehicles in low light of real scenes is difficult. The real scenes of vehicles dataset are generated by self on the Vadodara–Mumbai highway during periods… More >

Youming Guo, Qinmu Wu^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1489-1514, 2023, DOI:10.32604/cmc.2023.042313

Abstract Permanent magnet synchronous motor (PMSM) is widely used in various production processes because of its high efficiency, fast reaction time, and high power density. With the continuous promotion of new energy vehicles, timely detection of PMSM faults can significantly reduce the accident rate of new energy vehicles, further enhance consumers’ trust in their safety, and thus promote their popularity. Existing fault diagnosis methods based on deep learning can only distinguish different PMSM faults and cannot interpret and analyze them. Convolutional neural networks (CNN) show remarkable accuracy in image data analysis. However, due to the “black box” problem in deep learning… More >

Xiaoqi Xin^*, Dezhi Han, Mingming Cui

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2407-2425, 2023, DOI:10.32604/cmc.2023.042308

Abstract Person Search is a task involving pedestrian detection and person re-identification, aiming to retrieve person images matching a given objective attribute from a large-scale image library. The Person Search models need to understand and capture the detailed features and context information of smaller objects in the image more accurately and comprehensively. The current popular Person Search models, whether end-to-end or two-step, are based on anchor boxes. However, due to the limitations of the anchor itself, the model inevitably has some disadvantages, such as unbalance of positive and negative samples and redundant calculation, which will affect the performance of models. To… More >

Jauzak Hussaini Windiatmaja, Delphi Hanggoro, Muhammad Salman, Riri Fitri Sari^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2309-2339, 2023, DOI:10.32604/cmc.2023.041152

Abstract This research presents a reputation-based blockchain consensus mechanism called Proof of Intelligent Reputation (PoIR) as an alternative to traditional Proof of Work (PoW). PoIR addresses the limitations of existing reputation-based consensus mechanisms by proposing a more decentralized and fair node selection process. The proposed PoIR consensus combines Bidirectional Long Short-Term Memory (BiLSTM) with the Network Entity Reputation Database (NERD) to generate reputation scores for network entities and select authoritative nodes. NERD records network entity profiles based on various sources, i.e., Warden, Blacklists, DShield, AlienVault Open Threat Exchange (OTX), and MISP (Malware Information Sharing Platform). It summarizes these profile records into… More >

Ahmed H. Msmali¹, Fazal Dayan^2,*, Muhammad Rafiq³, Nauman Ahmed⁴, Abdullah Ali H. Ahmadini¹, Hassan A. Hamali⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2251-2269, 2023, DOI:10.32604/cmc.2023.040266

Abstract In this article, a Susceptible-Exposed-Infectious-Recovered (SEIR) epidemic model is considered. The equilibrium analysis and reproduction number are studied. The conventional models have made assumptions of homogeneity in disease transmission that contradict the actual reality. However, it is crucial to consider the heterogeneity of the transmission rate when modeling disease dynamics. Describing the heterogeneity of disease transmission mathematically can be achieved by incorporating fuzzy theory. A numerical scheme nonstandard, finite difference (NSFD) approach is developed for the studied model and the results of numerical simulations are presented. Simulations of the constructed scheme are presented. The positivity, convergence and consistency of the… More >