Li-Woei Chen¹, Kun-Lin Tsai^2,*, Fang-Yie Leu³, Wen-Cheng Jiang², Shih-Ting Tseng²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2779-2794, 2024, DOI:10.32604/cmes.2024.052124 - 08 July 2024

Abstract Various mobile devices and applications are now used in daily life. These devices require high-speed data processing, low energy consumption, low communication latency, and secure data transmission, especially in 5G and 6G mobile networks. High-security cryptography guarantees that essential data can be transmitted securely; however, it increases energy consumption and reduces data processing speed. Therefore, this study proposes a low-energy data encryption (LEDE) algorithm based on the Advanced Encryption Standard (AES) for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things (IoT) devices. In the proposed LEDE algorithm, the system time More >

Mohammed Hadwan^1,2,3,*, Mohammed A. Al-Hagery⁴, Mohammed Al-Sarem⁵, Faisal Saeed^5,6

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4675-4689, 2022, DOI:10.32604/cmc.2022.027311 - 21 April 2022

Abstract Different types of pandemics that have appeared from time to time have changed many aspects of daily life. Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown. The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store. A huge number of reviews are written daily by users to express their opinions, which include significant information to improve these applications. The manual processing and extracting of information… More >

Yuanbang Li^*, Wengang Zhou, Chi Xu, Yuchun Shi

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1365-1386, 2022, DOI:10.32604/cmes.2022.019656 - 19 April 2022

Abstract With the widespread use of mobile phones, users can share their location and activity anytime, anywhere, as a form of check-in data. These data reflect user features. Long-term stability and a set of user-shared features can be abstracted as user roles. This role is closely related to the users’ social background, occupation, and living habits. This study makes four main contributions to the literature. First, user feature models from different views for each user are constructed from the analysis of the check-in data. Second, the K-means algorithm is used to discover user roles from user… More >

Yun-Jung Choi^1,#, Eun-jung Ko^2,#, Eun-Joo Choi^2,*, Youn-Joo Um^2,*

International Journal of Mental Health Promotion, Vol.23, No.3, pp. 385-393, 2021, DOI:10.32604/IJMHP.2021.015018 - 23 July 2021

Abstract This study aims to contribute to improving mental health services and establishing a direction for disaster survivors by verifying the effectiveness of the TLS (Training for Life Skills) app, a mental health management mobile application. Altogether, 22 disaster survivors received access to the app (with guidance) for eight weeks; we analyzed its effectiveness by examining each participant’s electroencephalography data, which were collected while they were utilizing the app. The results of this study show that the use of the TLS app had a significant positive effect on emotional quotient, basic rhythm quotient (left brain, right More >