Muhammad Saad¹, Maaz Bin Ahmad^1,*, Muhammad Asif², Muhammad Khalid Khan¹, Toqeer Mahmood³, Elsayed Tag Eldin^4,*, Hala Abdel Hameed^5,6

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 687-709, 2023, DOI:10.32604/cmc.2023.038335

Abstract Pandemics have always been a nightmare for humanity, especially in developing countries. Forced lockdowns are considered one of the effective ways to deal with spreading such pandemics. Still, developing countries cannot afford such solutions because these may severely damage the country’s economy. Therefore, this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations smoothly. The novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things (IIoT) and blockchain-enabled technologies. Compared to existing studies, the immutable and tamper-proof contact tracing and quarantine management solution… More >

Junqi Guo^1,2, Qingyun Xiong^1,*, Minghui Yang¹, Ziyun Zhao¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 827-848, 2023, DOI:10.32604/cmc.2023.036450

Abstract Nowadays, smart wearable devices are used widely in the Social Internet of Things (IoT), which record human physiological data in real time. To protect the data privacy of smart devices, researchers pay more attention to federated learning. Although the data leakage problem is somewhat solved, a new challenge has emerged. Asynchronous federated learning shortens the convergence time, while it has time delay and data heterogeneity problems. Both of the two problems harm the accuracy. To overcome these issues, we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity problems.… More >

Wadhah Mohammed M. Aqlan¹, Ghassan Ahmed Ali^2,*, Khairan Rajab², Adel Rajab², Asadullah Shaikh², Fekry Olayah², Shehab Abdulhabib Saeed Alzaeemi^3,*, Kim Gaik Tay³, Mohd Adib Omar¹, Ernest Mangantig⁴

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 665-686, 2023, DOI:10.32604/cmc.2023.039228

Abstract Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production, resulting in a drop in the size of red blood cells. In severe forms, it can lead to death. This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival. Therefore, controlling thalassemia is extremely important and is made by promoting screening to the general population, particularly among thalassemia carriers. Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like… More >

Daniyal Amankeldin¹, Lyailya Kurmangaziyeva², Ayman Mailybayeva², Natalya Glazyrina¹, Ainur Zhumadillayeva^1,*, Nurzhamal Karasheva³

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1091-1108, 2023, DOI:10.32604/csse.2023.039503

Abstract This paper proposes a deep neural network (DNN) approach for detecting fake profiles in social networks. The DNN model is trained on a large dataset of real and fake profiles and is designed to learn complex features and patterns that distinguish between the two types of profiles. In addition, the present research aims to determine the minimum set of profile data required for recognizing fake profiles on Facebook and propose the deep convolutional neural network method for fake accounts detection on social networks, which has been developed using 16 features based on content-based and profile-based features. The results demonstrated that… More >

Zhihan Liu¹, Xiang Li¹, Siqi Liu², Wei Li^1,*, Xiangxu Meng¹, Jing Jia³

Computer Systems Science and Engineering, Vol.47, No.1, pp. 937-954, 2023, DOI:10.32604/csse.2023.039417

Abstract The COVID-19 virus is usually spread by small droplets when talking, coughing and sneezing, so maintaining physical distance between people is necessary to slow the spread of the virus. The World Health Organization (WHO) recommends maintaining a social distance of at least six feet. In this paper, we developed a real-time pedestrian social distance risk alert system for COVID-19, which monitors the distance between people in real-time via video streaming and provides risk alerts to the person in charge, thus avoiding the problem of too close social distance between pedestrians in public places. We design a lightweight convolutional neural network… More >

Alaa Omran Almagrabi^1,*, Rashid Ali², Daniyal Alghazzawi¹, Bander A. Alzahrani¹, Fahad M. Alotaibi¹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 843-853, 2023, DOI:10.32604/csse.2023.037652

Abstract The massive Internet of Things (IoT) comprises different gateways (GW) covering a given region of a massive number of connected devices with sensors. In IoT networks, transmission interference is observed when different sensor devices (SD) try to send information to a single GW. This is mitigated by allotting various channels to adjoining GWs. Furthermore, SDs are permitted to associate with any GW in a network, naturally choosing the one with a higher received signal strength indicator (RSSI), regardless of whether it is the ideal choice for network execution. Finding an appropriate GW to optimize the performance of IoT systems is… More >

Abeer D. Algarni^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1233-1247, 2023, DOI:10.32604/csse.2022.026915

Abstract Exponential increase in the quantity of user generated content in websites and social networks have resulted in the emergence of web intelligence approaches. Several natural language processing (NLP) tools are commonly used to examine the large quantity of data generated online. Particularly, sentiment analysis (SA) is an effective way of classifying the data into different classes of user opinions or sentiments. The latest advances in machine learning (ML) and deep learning (DL) approaches offer an intelligent way of analyzing sentiments. In this view, this study introduces a web intelligence with enhanced sunflower optimization based deep learning model for sentiment analysis… More >

Baoqiang Zhang^1,2, Ling Xiang^3,4,*

International Journal of Mental Health Promotion, Vol.25, No.7, pp. 863-871, 2023, DOI:10.32604/ijmhp.2023.027303

Abstract Social media has become increasingly popular and is now a significant tool for daily communication for many people. The use of social media can cause anxiety and have detrimental impacts on mental health. Cognitive impairment is more likely to affect individuals with anxiety. Investigating the cognitive abilities and mental health of social media users requires the development of new methodologies. This study employed the AX-Continuous Performance Test (AX-CPT) paradigm and the Stroop paradigm to study the cognitive control characteristics of trait anxiety, drawing on psychological experimental methods. Previous studies on whether trait anxiety impairs cognitive control remain controversial, possibly because… More >

Yoshikiyo Kanada^1,#, Shota Suzumura^1,2,#, Soichiro Koyama¹, Kazuya Takeda¹, Kenta Fujimura¹, Takuma Ii¹, Shigeo Tanabe¹, Hiroaki Sakurai^1,*

International Journal of Mental Health Promotion, Vol.25, No.7, pp. 855-861, 2023, DOI:10.32604/ijmhp.2023.028956

Abstract Mental health difficulties can impact students’ motivation, focus, and ability to communicate with others. Students attending medical universities are more likely to experience anxiety, depression, and other mood changes for the first time. However, no study has examined their prevalence among Japanese rehabilitation students. This study investigated the prevalence of anxiety among Japanese rehabilitation students and aimed to identify its predictors. A cross-sectional study was conducted among 148 first-year physical and occupational therapy students at a private medical university in Japan in June 2022. Data on sociodemographic and personal characteristics, such as gender, age, subject major, regular exercise, place of… More >

Yuanyuan Li^1,#, Jinze Mu^2,#, Qingliang Li¹, Huabing Liu³, Xuefeng Yuan^2,*, Deya Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.7, pp. 2079-2085, 2023, DOI:10.32604/phyton.2023.028237

Abstract Infection of plum bark necrosis stem pitting associated virus (PBNSPaV) has been reported in many Prunus species in several countries, causing significant economic losses. The very small proteins encoded by plant viruses are often overlooked due to their short sequences and uncertain significance. However, numerous studies have indicated that they might play important roles in the pathogenesis of virus infection. The role of small hydrophobic protein P6, encoded by the open reading frame 2 of PBNSPaV, has not been well explored. In this study, we amplified the P6 fragment from a PBNSPaV isolate by RT-PCR using specific primers and found… More >