Fady Samann^1,2,*, Shavan Askar³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2421-2444, 2024, DOI:10.32604/cmes.2023.031265 - 15 December 2023

Abstract Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms. K-clustering algorithms are simplistic, with fast performance and relative accuracy. However, their implementation depends on the initial selection of clusters number (K), the initial clusters’ centers, and the clustering metric. This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time (LET) as a clustering metric. Realistic traffic flows were considered for three maps, namely Highway, Traffic Light junction, and Roundabout junction, to study the… More >

Gustavo Foronda^1,2, Vanessa Ferreira Amorim de Melo^2,3,*, Claudia Regina Pinheiro de Castro Grau⁴, Ingrid Magatti Piva¹, Glaucia Maria Penha Tavares⁴, Ana Cristina Sayuri Tanaka¹, Nana Miura¹

Congenital Heart Disease, Vol.18, No.6, pp. 649-656, 2023, DOI:10.32604/chd.2023.027987 - 19 January 2024

Abstract Background: Children with congenital heart disease (CHD), even after surgical approaches, and especially those who undergo staged procedures in the first months of life, remain vulnerable to readmissions and complications, requiring very close monitoring and differentiated intervention strategies. Methods: Descriptive and exploratory study, of the experience report type, which presents the process of building the high-risk outpatient clinic for complex congenital heart diseases (AAR) at the Instituto do Coração (InCor). Results: Report of the path taken to structure the AAR, demonstrating the organization, interface with the multidisciplinary team, admission and discharge criteria, training, and patient profile.… More >

Yiteng Zang¹, Biyun Xu², Sizhen Chen¹, Grace Mutale¹, Qiuyun Cao^3,*, Bingwei Chen^1,*

International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1287-1302, 2023, DOI:10.32604/ijmhp.2023.042584 - 29 December 2023

Abstract Psychosis has increasingly become a social problem, emphasizing the need to understand the relationship between mental disorders and personality. This study aimed to investigate the relationship between mental disorders and personality among psychiatric outpatients based on real-world data. Symptom Checklist 90 (SCL-90) and Eysenck Personality Questionnaire (EPQ) were used to evaluate the personality and psychopathological symptoms of patients (n = 8409) in the Psychiatric Outpatient Department at Nanjing Drum Tower Hospital. t-test was used to compare scores between patients and national norms. Pearson’s correlation coefficient and path analysis were used to explore the relationship between mental… More >

Fady Samann^1,*, Shavan Askar²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2715-2734, 2023, DOI:10.32604/cmc.2023.043580 - 26 December 2023

Abstract Clustering schemes in vehicular networks organize vehicles into logical groups. They are vital for improving network performance, accessing the medium, and enabling efficient data dissemination. Most schemes rely on periodically broadcast hello messages to provide up-to-date information about the vehicles. However, the periodic exchange of messages overwhelms the system and reduces efficiency. This paper proposes the Flag-based Vehicular Clustering (FVC) scheme. The scheme leverages a combination of Fitness Score (FS), Link Expiration Time (LET), and clustering status flags to enable efficient cluster formation in a hybrid manner. The FVC relies on the periodic broadcast of… More >

Jiahao Wen, Zhijian Wang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 749-765, 2023, DOI:10.32604/cmes.2023.023865 - 05 January 2023

Abstract Since the existing prediction methods have encountered difficulties in processing the multiple influencing factors in short-term power load forecasting, we propose a bidirectional long short-term memory (BiLSTM) neural network model based on the temporal pattern attention (TPA) mechanism. Firstly, based on the grey relational analysis, datasets similar to forecast day are obtained. Secondly, the bidirectional LSTM layer models the data of the historical load, temperature, humidity, and date-type and extracts complex relationships between data from the hidden row vectors obtained by the BiLSTM network, so that the influencing factors (with different characteristics) can select relevant… More >

Xiaoping Xie^*, Shijie Cheng, Xuyang Li

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2425-2448, 2023, DOI:10.32604/cmes.2023.023116 - 23 November 2022

Abstract This paper proposed method that combined transmission path analysis (TPA) and empirical mode decomposition (EMD) envelope analysis to solve the vibration problem of an industrial robot. Firstly, the deconvolution filter time-domain TPA method is proposed to trace the source along with the time variation. Secondly, the TPA method positioned the main source of robotic vibration under typically different working conditions. Thirdly, independent vibration testing of the Rotate Vector (RV) reducer is conducted under different loads and speeds, which are key components of an industrial robot. The method of EMD and Hilbert envelope was used to More >

S. Stewart Kirubakaran^1,*, V. P. Arunachalam¹, S. Karthik¹, S. Kannan²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1881-1895, 2023, DOI:10.32604/csse.2023.026690 - 01 August 2022

Abstract In the present scenario of rapid growth in cloud computing models, several companies and users started to share their data on cloud servers. However, when the model is not completely trusted, the data owners face several security-related problems, such as user privacy breaches, data disclosure, data corruption, and so on, during the process of data outsourcing. For addressing and handling the security-related issues on Cloud, several models were proposed. With that concern, this paper develops a Privacy-Preserved Data Security Approach (PP-DSA) to provide the data security and data integrity for the outsourcing data in Cloud… More >

Xiaojie Li¹, Yongpeng Ren¹, Hongping Ren¹, Canghong Shi², Xian Zhang¹, Lutao Wang¹, Imran Mumtaz³, Xi Wu¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5021-5037, 2022, DOI:10.32604/cmc.2022.023071 - 14 January 2022

Abstract Recently, deep learning-based image outpainting has made greatly notable improvements in computer vision field. However, due to the lack of fully extracting image information, the existing methods often generate unnatural and blurry outpainting results in most cases. To solve this issue, we propose a perceptual image outpainting method, which effectively takes the advantage of low-level feature fusion and multi-patch discriminator. Specifically, we first fuse the texture information in the low-level feature map of encoder, and simultaneously incorporate these aggregated features reusability with semantic (or structural) information of deep feature map such that we could utilize More >

Benjamin Bric, Paolo Raile^*

International Journal of Mental Health Promotion, Vol.22, No.3, pp. 133-147, 2020, DOI:10.32604/IJMHP.2020.011375 - 14 August 2020

Abstract It was particularly important that the SFU Outpatient Clinic, which plays a relevant role in Vienna’s psychotherapeutic care, has established a corresponding offer during the COVID-19 crisis and continue to provide professional help. In times of insecurity and fear, we have created a safe contact point to which people could turn for help. In the following article the experiences of setting up an innovative psychotherapeutic Helpline, which is in operation since 21st of March 2020 at 12:00 at the psychotherapeutic outpatient clinic of the Sigmund Freud Private University in Vienna, will be discussed. Furthermore, statistical More >

Eun-Joo Choi¹, So Yeon Yoo^2,*

International Journal of Mental Health Promotion, Vol.22, No.2, pp. 93-104, 2020, DOI:10.32604/IJMHP.2020.011059 - 16 June 2020

Abstract Chronic pain has a high prevalence rate and is difficult to treat because it is associated with personality, socio-psychological problems as well as physical pain, and thereby degrades one’s quality of life. This study aimed to determine whether psychosocial factors are associated with quality of life among outpatients with chronic pain. The subjects were selected from patients with chronic pain who were receiving outpatient treatment at the mental health department of a university hospital in Seoul, Korea. The participants were 100 patients and the data were collected using structured questionnaires. Patients’ quality of life More >