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  • Open Access


    SARS-CoV-2 and Cancer: What Is the Psychological Impact?
    Experience of Department of Medical Oncology, Hassan-II University Hospital of Fez, Morocco

    SARS-CoV2 et cancer : quel impact psychologique ?
    Expérience du service d’oncologie médicale du centre hospitalier universitaire Hassan-II de Fès, Maroc

    L. Amaadour, I. Lahrch, O. Siyouri, K. Oualla, Z. Benbrahim, S. Arifi, C. Aarab, S. El Fakir, N. Mellas

    Psycho-Oncologie, Vol.17, No.1, pp. 38-43, 2023, DOI:10.3166/pson-2022-0221

    Abstract Background: The Covid-19 disease is a cause for several mental alterations mainly in cancer patients who are already categorized as a vulnerable population.
    Aim: The objective of this study is to characterize psychological disorders caused by Covid-19 infection among cancer patients on systemic treatment.
    Methods: It is a cross-sectional study performed at the Department of Medical Oncology of Hassan-II University Hospital of Fez, Morocco, during a period of four months (peak of the pandemic). Symptoms of anxiety/depression and post-traumatic stress disorder in patients were screened using HADS (Hospital Anxiety and Depression Scale) and PCL-5 (post-traumatic stress disorder checklist version DSM-5)… More >

  • Open Access


    Selection of Metaheuristic Algorithm to Design Wireless Sensor Network

    Rakhshan Zulfiqar1,2, Tariq Javed1, Zain Anwar Ali2,*, Eman H. Alkhammash3, Myriam Hadjouni4

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 985-1000, 2023, DOI:10.32604/iasc.2023.037248

    Abstract The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance. The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’ access network. The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness. Coverage and energy usage are mostly determined by successful sensor placement strategies. Nature-inspired algorithms are the most effective solution for short sensor lifetime. The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks (WSNs’) maximum network coverage. Moreover, it identifies quantity… More >

  • Open Access


    Metaheuristic Optimization with Deep Learning Enabled Smart Grid Stability Prediction

    Afrah Al-Bossly*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6395-6408, 2023, DOI:10.32604/cmc.2023.028433

    Abstract Due to the drastic increase in global population as well as economy, electricity demand becomes considerably high. The recently developed smart grid (SG) technology has the ability to minimize power loss at the time of power distribution. Machine learning (ML) and deep learning (DL) models can be effectually developed for the design of SG stability techniques. This article introduces a new Social Spider Optimization with Deep Learning Enabled Statistical Analysis for Smart Grid Stability (SSODLSA-SGS) prediction model. Primarily, class imbalance data handling process is performed using Synthetic minority oversampling technique (SMOTE) technique. The SSODLSA-SGS model involves two stages of pre-processing… More >

  • Open Access



    Albio D. Gutierreza,*, Hayri Sezerb, Jose L. Ramirezc

    Frontiers in Heat and Mass Transfer, Vol.18, No.1, pp. 1-12, 2022, DOI:10.5098/hmt.18.4

    Abstract This paper presents a computational model along with a thermal comfort criterion aimed at assisting the design of operating rooms (ORs) from the perspective of meeting suitable flow patterns and thermal comfort conditions for the occupants. The computational model is based on the finite volume method (FVM) to describe the air inside ORs along with the human thermoregulation model implemented in virtual mannequins for thermal comfort. The air model considers turbulent fluid motion, species transport and the conservation of energy, including thermal radiation. The human thermoregulation model incorporates two interacting systems of thermoregulation. Namely, the passive system and the active… More >

  • Open Access



    V. W. Bhatkara, Anirban Surb,*, Anindita Royb

    Frontiers in Heat and Mass Transfer, Vol.19, No.1, pp. 1-8, 2022, DOI:10.5098/hmt.19.3

    Abstract In heating, Wet-bulb temperature in HVAC (heating, ventilation, and air conditioning) applications is crucial for building the equipment. But radiation from the surrounding surfaces caused the errors during the thermodynamic wet-bulb temperature measurement. The wet-bulb temperature of moist air is measured in the current work utilising an aspiration psychrometer designed, developed, and built to reduce the error term caused by radiation and convection heat transfer. Wet-bulb temperature is calculated in the experiments using an aspiration psychrometer at various locations throughout the year, both with and without a shield. It has been found that the error term depends on several factors,… More >

  • Open Access


    Ensemble Model for Spindle Thermal Displacement Prediction of Machine Tools

    Ping-Huan Kuo1,2, Ssu-Chi Chen1, Chia-Ho Lee1, Po-Chien Luan2, Her-Terng Yau1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 319-343, 2023, DOI:10.32604/cmes.2023.026860

    Abstract Numerous factors affect the increased temperature of a machine tool, including prolonged and high-intensity usage, tool-workpiece interaction, mechanical friction, and elevated ambient temperatures, among others. Consequently, spindle thermal displacement occurs, and machining precision suffers. To prevent the errors caused by the temperature rise of the Spindle from affecting the accuracy during the machining process, typically, the factory will warm up the machine before the manufacturing process. However, if there is no way to understand the tool spindle's thermal deformation, the machining quality will be greatly affected. In order to solve the above problem, this study aims to predict the thermal… More >

  • Open Access


    Quantum-Inspired Equilibrium Optimizer for Linear Antenna Array

    Binwen Zhu1, Qifang Luo1,3,*, Yongquan Zhou1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 385-413, 2023, DOI:10.32604/cmes.2023.026097

    Abstract With the rapid development of communication technology, the problem of antenna array optimization plays a crucial role. Among many types of antennas, line antenna arrays (LAA) are the most commonly applied, but the side lobe level (SLL) reduction is still a challenging problem. In the radiation process of the linear antenna array, the high side lobe level will interfere with the intensity of the antenna target radiation direction. Many conventional methods are ineffective in obtaining the maximum side lobe level in synthesis, and this paper proposed a quantum equilibrium optimizer (QEO) algorithm for line antenna arrays. Firstly, the linear antenna… More >

  • Open Access


    Multi-Strategy Boosted Spider Monkey Optimization Algorithm for Feature Selection

    Jianguo Zheng, Shuilin Chen*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3619-3635, 2023, DOI:10.32604/csse.2023.038025

    Abstract To solve the problem of slow convergence and easy to get into the local optimum of the spider monkey optimization algorithm, this paper presents a new algorithm based on multi-strategy (ISMO). First, the initial population is generated by a refracted opposition-based learning strategy to enhance diversity and ergodicity. Second, this paper introduces a non-linear adaptive dynamic weight factor to improve convergence efficiency. Then, using the crisscross strategy, using the horizontal crossover to enhance the global search and vertical crossover to keep the diversity of the population to avoid being trapped in the local optimum. At last, we adopt a Gauss-Cauchy… More >

  • Open Access


    Edge of Things Inspired Robust Intrusion Detection Framework for Scalable and Decentralized Applications

    Abdulaziz Aldribi1,2,*, Aman Singh2,3, Jose Breñosa3,4

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3865-3881, 2023, DOI:10.32604/csse.2023.037748

    Abstract Ubiquitous data monitoring and processing with minimal latency is one of the crucial challenges in real-time and scalable applications. Internet of Things (IoT), fog computing, edge computing, cloud computing, and the edge of things are the spine of all real-time and scalable applications. Conspicuously, this study proposed a novel framework for a real-time and scalable application that changes dynamically with time. In this study, IoT deployment is recommended for data acquisition. The Pre-Processing of data with local edge and fog nodes is implemented in this study. The threshold-oriented data classification method is deployed to improve the intrusion detection mechanism’s performance.… More >

  • Open Access


    Enhanced Deep Learning for Detecting Suspicious Fall Event in Video Data

    Madhuri Agrawal*, Shikha Agrawal

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2653-2667, 2023, DOI:10.32604/iasc.2023.033493


    Suspicious fall events are particularly significant hazards for the safety of patients and elders. Recently, suspicious fall event detection has become a robust research case in real-time monitoring. This paper aims to detect suspicious fall events during video monitoring of multiple people in different moving backgrounds in an indoor environment; it is further proposed to use a deep learning method known as Long Short Term Memory (LSTM) by introducing visual attention-guided mechanism along with a bi-directional LSTM model. This method contributes essential information on the temporal and spatial locations of ‘suspicious fall’ events in learning the video frame in both… More >

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