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  • Open Access

    REVIEW

    Recent progress in microbial cell surface display systems and their application on biosensors

    HAIYING CHEN, YUQING WU, BAOJIAN HUANG, LEI HAN*

    BIOCELL, Vol.47, No.6, pp. 1213-1223, 2023, DOI:10.32604/biocell.2023.028035

    Abstract Microbial cell surface display technology is a recombinant technology to express target proteins on the cell membrane, which can be used to redesign the cell surface with functional proteins and peptides. Bacterial and yeast surface display systems are the most common cell surface display systems of prokaryotic and eukaryotic proteins, that are widely applied as the core elements in the field of biosensors due to their advantages, including enhanced stability, high yield, good safety, expression of larger and more complex proteins. To further promote the performance of biosensors, the biomineralized microbial surface display technology was proposed. This review summarized the… More >

  • Open Access

    ARTICLE

    Improved Transient Search Optimization with Machine Learning Based Behavior Recognition on Body Sensor Data

    Baraa Wasfi Salim1, Bzar Khidir Hussan2, Zainab Salih Ageed3, Subhi R. M. Zeebaree4,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4593-4609, 2023, DOI:10.32604/cmc.2023.037514

    Abstract Recently, human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare systems. Even though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs, physical human action recognition (HAR) through body sensors gives useful information about the lifestyle and functionality of an individual. This article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based Behavior Recognition (ITSOML-BR) technique using body sensor data. The presented ITSOML-BR technique collects data from… More >

  • Open Access

    ARTICLE

    Modeling of Sensor Enabled Irrigation Management for Intelligent Agriculture Using Hybrid Deep Belief Network

    Saud Yonbawi1, Sultan Alahmari2, B. R. S. S. Raju3, Chukka Hari Govinda Rao4, Mohamad Khairi Ishak5, Hend Khalid Alkahtani6, José Varela-Aldás7,*, Samih M. Mostafa8

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2319-2335, 2023, DOI:10.32604/csse.2023.036721

    Abstract Artificial intelligence (AI) technologies and sensors have recently received significant interest in intellectual agriculture. Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture. Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques. Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist. With this motivation, this study develops a modified black widow optimization with a… More >

  • Open Access

    ARTICLE

    Human Personality Assessment Based on Gait Pattern Recognition Using Smartphone Sensors

    Kainat Ibrar1, Abdul Muiz Fayyaz1, Muhammad Attique Khan2, Majed Alhaisoni3, Usman Tariq4, Seob Jeon5, Yunyoung Nam6,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2351-2368, 2023, DOI:10.32604/csse.2023.036185

    Abstract Human personality assessment using gait pattern recognition is one of the most recent and exciting research domains. Gait is a person’s identity that can reflect reliable information about his mood, emotions, and substantial personality traits under scrutiny. This research focuses on recognizing key personality traits, including neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, in line with the big-five model of personality. We inferred personality traits based on the gait pattern recognition of individuals utilizing built-in smartphone sensors. For experimentation, we collected a novel dataset of 22 participants using an android application and further segmented it into six data chunks… More >

  • Open Access

    ARTICLE

    Improved Hybrid Swarm Intelligence for Optimizing the Energy in WSN

    Ahmed Najat Ahmed1, JinHyung Kim2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2527-2542, 2023, DOI:10.32604/csse.2023.036106

    Abstract In this current century, most industries are moving towards automation, where human intervention is dramatically reduced. This revolution leads to industrial revolution 4.0, which uses the Internet of Things (IoT) and wireless sensor networks (WSN). With its associated applications, this IoT device is used to compute the received WSN data from devices and transfer it to remote locations for assistance. In general, WSNs, the gateways are a long distance from the base station (BS) and are communicated through the gateways nearer to the BS. At the gateway, which is closer to the BS, energy drains faster because of the heavy… More >

  • Open Access

    ARTICLE

    Home Automation-Based Health Assessment Along Gesture Recognition via Inertial Sensors

    Hammad Rustam1, Muhammad Muneeb1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Tamara Al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2331-2346, 2023, DOI:10.32604/cmc.2023.028712

    Abstract Hand gesture recognition (HGR) is used in a numerous applications, including medical health-care, industrial purpose and sports detection. We have developed a real-time hand gesture recognition system using inertial sensors for the smart home application. Developing such a model facilitates the medical health field (elders or disabled ones). Home automation has also been proven to be a tremendous benefit for the elderly and disabled. Residents are admitted to smart homes for comfort, luxury, improved quality of life, and protection against intrusion and burglars. This paper proposes a novel system that uses principal component analysis, linear discrimination analysis feature extraction, and… More >

  • Open Access

    ARTICLE

    Automatic Recognition of Construction Worker Activities Using Deep Learning Approaches and Wearable Inertial Sensors

    Sakorn Mekruksavanich1, Anuchit Jitpattanakul2,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2111-2128, 2023, DOI:10.32604/iasc.2023.033542

    Abstract The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturing firm are vital for the rapid and accurate diagnosis of work performance, particularly during the training of a new worker. Various techniques for identifying and detecting worker performance in industrial applications are based on computer vision techniques. Despite widespread computer vision-based approaches, it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where camera deployment is problematic. Through the use of wearable inertial sensors, we propose a deep learning method for automatically recognizing the activities of construction workers. The… More >

  • Open Access

    ARTICLE

    Efficient Gait Analysis Using Deep Learning Techniques

    K. M. Monica, R. Parvathi*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6229-6249, 2023, DOI:10.32604/cmc.2023.032273

    Abstract Human Activity Recognition (HAR) has always been a difficult task to tackle. It is mainly used in security surveillance, human-computer interaction, and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things (IoT). Human Activity Recognition data can be recorded with the help of sensors, images, or smartphones. Recognizing daily routine-based human activities such as walking, standing, sitting, etc., could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network (2D CNN) MODEL, Long Short Term Memory (LSTM) Model, Bidirectional long short-term memory (Bi-LSTM) are used… More >

  • Open Access

    ARTICLE

    IOT Assisted Biomedical Monitoring Sensors for Healthcare in Human

    S. Periyanayagi1, V. Nandini2,*, K. Basarikodi3, V. Sumathy4

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2853-2868, 2023, DOI:10.32604/csse.2023.030538

    Abstract The Internet of Things (IoT) is a concept that refers to the deployment of Internet Protocol (IP) address sensors in health care systems to monitor patients’ health. It has the ability to access the Internet and collect data from sensors. Automated decisions are made after evaluating the information of illness people records. Patients’ health and well-being can be monitored through IoT medical devices. It is possible to trace the origins of biological, medical equipment and processes. Human reliability is a major concern in user activity and fitness trackers in day-to-day activities. The fundamental challenge is to measure the efficiency of… More >

  • Open Access

    ARTICLE

    IoT-Deep Learning Based Activity Recommendation System

    Sharmilee Kannan1,*, R. U. Anitha2, M. Divayapushpalakshmi3, K. S. Kalaivani4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2001-2016, 2023, DOI:10.32604/csse.2023.031965

    Abstract The rising use of mobile technology and smart gadgets in the field of health has had a significant impact on the global community. Health professionals are increasingly making use of the benefits of these technologies, resulting in a major improvement in health care both in and out of clinical settings. The Internet of Things (IoT) is a new internet revolution that is a rising research area, particularly in health care. Healthcare Monitoring Systems (HMS) have progressed rapidly as the usage of Wearable Sensors (WS) and smartphones have increased. The existing framework of conventional telemedicine’s store-and-forward method has some issues, including… More >

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