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  • Open Access


    Exploratory Study of Intolerance of Uncertainty and Its Cognitive Processes by the Stroop Task among Parents of a Childhood Cancer Survivor

    Etude exploratoire de l’intolérance à l’incertitude et de ses processus cognitifs par la tâche du Stroop chez les parents d’un enfant en rémission de cancer

    Marie Vander Haegen*, Anne-Marie Etienne

    Psycho-Oncologie, Vol.17, No.4, pp. 257-266, 2023, DOI:10.32604/po.2023.043340

    Abstract Introduction. No study has examined the relationship between the factor of intolerance of uncertainty and its effects on the cognitive processes among parents of a childhood cancer survivor. Intolerance of uncertainty is a central factor in generalized anxiety disorder; an anxiety disorder in which impaired processing of cognitive information in the form of cognitive biases is also observed. The aim of the study was to measure, via a classical Stroop test and an emotional Stroop test, the orientation of selective attention in relation to the uncertainty intolerance factor. Methods. 61 parents of a childhood cancer survivor (aged 4 to 6… More >

  • Open Access


    A Clinical Study on the Effect of Group Nostalgia Therapy on Quality of Life and Cognitive Function in Elderly Patients with Depression

    Yan Huang1,*, Xiaoye Liao2, Fen Cai3

    International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1313-1321, 2023, DOI:10.32604/ijmhp.2023.030558

    Abstract Background: Elderly people with depression require special care and attention. However, nostalgia is a complex emotional situation for a person who recalls the missing past. To improve mental health, quality of life, and attitudes toward aging in institutional care, group nostalgia therapy can be a nursing intermediary for the elderly. This study aimed to analyze the effect of group nostalgia therapy on quality of life cognitive function in elderly patients with depression. Methods: A total of 89 participants were enrolled in this study, which was further categorized into a control (n = 40) and a nostalgia therapy group (n =… More >

  • Open Access


    Gender Differences in the Incidence and Related Factors of Low Social Support among Adolescents with Subthreshold Depression

    Yi Shi, Fangfang Shangguan*, Jing Xiao*

    International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1257-1263, 2023, DOI:10.32604/ijmhp.2023.030516

    Abstract Background: Social support is related to depression, but the gender differences and related factors that contribute to low social support among adolescents with subthreshold depression remain to be elucidated. This study explores the relationship between social support and depression, in addition to the gender difference in the incidence of low social support among adolescents with subthreshold depression and its related factors. Methods: A total of 371 Chinese adolescents with subthreshold depression were recruited. All subjects were rated on the Social Support Scale for Adolescents, the Response Style Scale, the Self-Perception Profile for Children, the Individualism-collectivism scale. Results: Binary logistic regression… More >

  • Open Access


    Blockchain-Based Cognitive Computing Model for Data Security on a Cloud Platform

    Xiangmin Guo1,2, Guangjun Liang1,2,*, Jiayin Liu1,2, Xianyi Chen3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3305-3323, 2023, DOI:10.32604/cmc.2023.044529

    Abstract Cloud storage is widely used by large companies to store vast amounts of data and files, offering flexibility, financial savings, and security. However, information shoplifting poses significant threats, potentially leading to poor performance and privacy breaches. Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms, ensuring businesses can focus on business development. To ensure data security in cloud platforms, this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing (HD2C) model. However, the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things (IoT) in the cloud.… More >

  • Open Access


    Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

    R. Saravanan1,*, R. Muthaiah1, A. Rajesh2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2339-2356, 2024, DOI:10.32604/cmes.2023.030898

    Abstract This study develops an Enhanced Threshold Based Energy Detection approach (ETBED) for spectrum sensing in a cognitive radio network. The threshold identification method is implemented in the received signal at the secondary user based on the square law. The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing. Additionally, the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems. In the dynamic threshold, the signal ratio-based threshold is fixed. The threshold is computed by considering the Modified Black Widow Optimization Algorithm (MBWO). So, the proposed… More > Graphic Abstract

    Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

  • Open Access


    The Effect of Sleep and Cognition Enhancement Multimodal Intervention for Mild Cognitive Impairment with Sleep Disturbance in the Community-Dwelling Elderly

    Eun Kyoung Han, Hae Kyoung Son*

    International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1197-1208, 2023, DOI:10.32604/ijmhp.2023.041560

    Abstract Dementia prevalence has soared due to population aging. In Mild Cognitive Impairment (MCI) as a pre-dementia stage, sleep disturbances have raised much interest as a factor in a bidirectional relationship with cognitive decline. Thus, this study developed the Sleep and Cognition Enhancement Multimodal Intervention (SCEMI) based on Lazarus’ multimodal approach and conducted a randomized controlled experiment to investigate the effects of the novel program on sleep and cognition in MCI elderly. The participants were 55 MCI elderly with sleep disturbances at two dementia care centers located in S-city, Gyeonggi-do, South Korea (n = 25 in the experimental group and n… More >

  • Open Access


    Serial Multiple Mediation of the Relationship between Positive Coping Style and Post-Traumatic Growth among Chinese College Students in the Aftermath of COVID-19

    Qi Li, Jinsheng Hu*, Peng Wan

    International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1173-1186, 2023, DOI:10.32604/ijmhp.2023.030343


    Given the ongoing character of COVID-19, higher-education students encountered multifaceted pressures brought about by the pandemic and had to overcome many difficulties during this period. Accordingly, it is imperative to identify the factors that may have protective effects on the social functioning and mental status of college students in the aftermath of COVID-19. This cross-sectional study sought to ascertain the internal mechanism of positive coping (PC) styles affecting post-traumatic growth (PTG) and considered the mediating roles of cognitive reappraisal (CR), psychological resilience (PR), and deliberate rumination (DR), which are essential for understanding how and to what extent these factors shaped… More >

  • Open Access


    Exercise Recommendation with Preferences and Expectations Based on Ability Computation

    Mengjuan Li, Lei Niu*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 263-284, 2023, DOI:10.32604/cmc.2023.041193

    Abstract In the era of artificial intelligence, cognitive computing, based on cognitive science; and supported by machine learning and big data, brings personalization into every corner of our social life. Recommendation systems are essential applications of cognitive computing in educational scenarios. They help learners personalize their learning better by computing student and exercise characteristics using data generated from relevant learning progress. The paper introduces a Learning and Forgetting Convolutional Knowledge Tracking Exercise Recommendation model (LFCKT-ER). First, the model computes studentsʼ ability to understand each knowledge concept, and the learning progress of each knowledge concept, and the model consider their forgetting behavior… More >

  • Open Access


    AI-Driven FBMC-OQAM Signal Recognition via Transform Channel Convolution Strategy

    Zeliang An1, Tianqi Zhang1,*, Debang Liu1, Yuqing Xu2, Gert Frølund Pedersen2, Ming Shen2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2817-2834, 2023, DOI:10.32604/cmc.2023.037832

    Abstract With the advent of the Industry 5.0 era, the Internet of Things (IoT) devices face unprecedented proliferation, requiring higher communications rates and lower transmission delays. Considering its high spectrum efficiency, the promising filter bank multicarrier (FBMC) technique using offset quadrature amplitude modulation (OQAM) has been applied to Beyond 5G (B5G) industry IoT networks. However, due to the broadcasting nature of wireless channels, the FBMC-OQAM industry IoT network is inevitably vulnerable to adversary attacks from malicious IoT nodes. The FBMC-OQAM industry cognitive radio network (ICRNet) is proposed to ensure security at the physical layer to tackle the above challenge. As a… More >

  • Open Access


    Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

    Nitin Mittal1, Rohit Salgotra2,3, Abhishek Sharma4, Sandeep Kaur5, S. S. Askar6, Mohamed Abouhawwash7,8,*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3159-3177, 2023, DOI:10.32604/iasc.2023.041059

    Abstract The optimization of cognitive radio (CR) system using an enhanced firefly algorithm (EFA) is presented in this work. The Firefly algorithm (FA) is a nature-inspired algorithm based on the unique light-flashing behavior of fireflies. It has already proved its competence in various optimization problems, but it suffers from slow convergence issues. To improve the convergence performance of FA, a new variant named EFA is proposed. The effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions, and simulation results show its superior performance compared to biogeography-based optimization (BBO), bat algorithm, artificial bee colony, and FA. As an… More >

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