Rajesh Singh¹, Anita Gehlot¹, Ritika Saxena², Khalid Alsubhi³, Divya Anand^1,*, Irene Delgado Noya^4,5, Shaik Vaseem Akram¹, Sushabhan Choudhury²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1217-1233, 2023, DOI:10.32604/cmc.2023.023894 - 22 September 2022

Abstract Stress is now a serious disease that exists due to changes in working life and food ecosystems around the world. In general, it is difficult for a person to know if they are under stress. According to previous research, temperature, heart rate variability (HRV), humidity, and blood pressure are used to assess stress levels with the use of instruments. With the development of sensor technology and wireless connectivity, people around the world are adopting and using smart devices. In this study, a bio signal detection device with Internet of Things (IoT) capability with a galvanic… More >

Abeer Abdulaziz AlArfaj¹, Nada Ali Hakami^2,*, Hanan Ahmed Hosni Mahmoud¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1423-1439, 2023, DOI:10.32604/iasc.2023.028067 - 19 July 2022

Abstract Social Media such as Facebook plays a substantial role in virtual communities by sharing ideas and ideologies among different populations over time. Social interaction analysis aids in defining people’s emotions and aids in assessing public attitudes, towards different issues such as violence against women and children. In this paper, we proposed an Arabic language prediction model to identify the issue of Violence-Induced Stress in social media. We searched for Arabic posts of many countries through Facebook application programming interface (API). We discovered that the stress state of a battered woman is usually related to her… More >

Juyoung Park^1,*, Jung Hee Lee¹, Junseong Bang^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 965-976, 2021, DOI:10.32604/cmes.2021.014669 - 24 May 2021

Abstract

We propose a mobile system, called PotholeEye⁺, for automatically monitoring the surface of a roadway and detecting the pavement distress in real-time through analysis of a video. PotholeEye⁺ pre-processes the images, extracts features, and classifies the distress into a variety of types, while the road manager is driving. Every day for a year, we have tested PotholeEye⁺ on real highway involving real settings, a camera, a mini computer, a GPS receiver, and so on. Consequently, PotholeEye⁺ detected the pavement distress with accuracy of 92%, precision of 87% and recall 74% averagely during driving at an average speed of

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Yuanyuan Xue^1,2, Qi Li¹, LingFeng¹

Computer Systems Science and Engineering, Vol.34, No.3, pp. 151-164, 2019, DOI:10.32604/csse.2019.34.151

Abstract Stress is a common problem all over the world. More and more teenagers today have to cope with different stressor events coming from school, family, peer relation, self-cognition, romantic relation, etc. Over-stress without proper guidance will lead to a series of potential problems including physical and mental disorders, and even suicide due to the shortage of teen’ s psychological endurance and controllability. Therefore, it is necessary and important to timely sense adolescents’ stress and help them release the stress properly. In this paper, we present a micro-blog based system called TeenSensor, aiming to detect teens… More >