Yang Deng^1,#, Tong Su^1,#, Bin Wu¹, Li Peng², Muyu Chen^1,2,*, Liang Zhang^1,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.072327 - 28 January 2026

Abstract Background: Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined, high-stress environments. Effective non-pharmacological interventions are needed to improve sleep quality and resilience in this population. This study aimed to investigate the effect of virtual reality (VR) combined with forest therapy interventions on psychological resilience and sleep quality among submarine personnel with insomnia symptoms. Methods: Using convenience sampling, 92 submarine personnel with insomnia symptoms undergoing recuperation at a PLA sanatorium between July 2023 and May 2025 were randomly allocated to experimental and control groups (n = 46 each). The control group… More >

Yu Tao¹, Ruopeng Yang^1,2, Yongqi Wen^1,*, Yihao Zhong¹, Kaige Jiao¹, Xiaolei Gu^1,2

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-17, 2026, DOI:10.32604/cmc.2025.068670 - 10 November 2025

Abstract Since Google introduced the concept of Knowledge Graphs (KGs) in 2012, their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition, extraction, representation, modeling, fusion, computation, and storage. Within this framework, knowledge extraction, as the core component, directly determines KG quality. In military domains, traditional manual curation models face efficiency constraints due to data fragmentation, complex knowledge architectures, and confidentiality protocols. Meanwhile, crowdsourced ontology construction approaches from general domains prove non-transferable, while human-crafted ontologies struggle with generalization deficiencies. To address these challenges, this study proposes an Ontology-Aware LLM Methodology for Military Domain More >

Shitharth Selvarajan^1,2,3,*, Hariprasath Manoharan⁴, Taher Al-Shehari⁵, Nasser A Alsadhan⁶, Subhav Singh^7,8

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3541-3557, 2025, DOI:10.32604/cmc.2025.064394 - 03 July 2025

Abstract This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities. A comparable filter is used to improve the visual quality of the photographs by reducing truncations in the existing images. Furthermore, the collected images undergo processing using histogram gradients and a flexible threshold value that may be adjusted in specific situations. Thus, it is possible to reduce the occurrence of overlapping circumstances in collective picture characteristics by substituting grey-scale photos with colorized factors. The proposed method offers additional robust feature representations by imposing a limiting More >

Nigel Walford^*

Revue Internationale de Géomatique, Vol.33, pp. 445-464, 2024, DOI:10.32604/rig.2024.054535 - 25 October 2024

Abstract The impact of World War II on the physical landscape of British towns and cities as a result of airborne assault is well known. However, less newsworthy but arguably no less significant is the impact of the war on agriculture and the countryside, especially in South-East England. This paper outlines the building of an historical Geographical Information System (GIS) from different data sources including the National Farm Survey (NFS), Luftwaffe and Royal Air Force (RAF) aerial photographs and basic topographic mapping for the South Downs in East and West Sussex. It explores the impact and… More >

Hyun Kwon^1,*, Sanghyun Lee²

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 249-263, 2024, DOI:10.32604/cmc.2023.042466 - 30 January 2024

Abstract Deep neural networks perform well in image recognition, object recognition, pattern analysis, and speech recognition. In military applications, deep neural networks can detect equipment and recognize objects. In military equipment, it is necessary to detect and recognize rifle management, which is an important piece of equipment, using deep neural networks. There have been no previous studies on the detection of real rifle numbers using real rifle image datasets. In this study, we propose a method for detecting and recognizing rifle numbers when rifle image data are insufficient. The proposed method was designed to improve the… More >

Seungju Hyun¹, Xyle Ku^1,2, Sungrok Kang¹, Yoonyoung Choi¹, Jaewon Ko¹, Hyunyup Lee^1,*

International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1187-1195, 2023, DOI:10.32604/ijmhp.2023.030745 - 08 December 2023

Abstract Owing to the ubiquitous use of smartphones by soldiers, military researchers have an increasing interest in potentially problematic side effects such as smartphone overdependence. This raises a question regarding the psychological mechanisms underlying the potentially self-damaging use of smartphones. Here, we address this question by analyzing how heterogeneity in commander’s good leadership explains subordinate soldiers’ differences in self-control and smartphone use. Specifically, we found that subordinate soldiers who thought their commander's leadership was good were self-regulated, less dependent on smartphones, less stressed, and finally had good mental health. This result indicates that commander’s good leadership More >

Yuyuan Xiang, Yangli Jia^*, Xiangliang Zhang, Zhenling Zhang

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 97-114, 2023, DOI:10.32604/cmc.2023.040751 - 31 October 2023

Abstract Event extraction stands as a significant endeavor within the realm of information extraction, aspiring to automatically extract structured event information from vast volumes of unstructured text. Extracting event elements from multi-modal data remains a challenging task due to the presence of a large number of images and overlapping event elements in the data. Although researchers have proposed various methods to accomplish this task, most existing event extraction models cannot address these challenges because they are only applicable to text scenarios. To solve the above issues, this paper proposes a multi-modal event extraction method based on… More >

M. Suresh Kumar^1,*, G. A. Sathish Kumar²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 705-725, 2023, DOI:10.32604/iasc.2023.027545 - 06 June 2022

Abstract The growth of Wireless Sensor Networks (WSNs) has revolutionized the field of technology and it is used in different application frameworks. Unmanned edges and other critical locations can be monitored using the navigation sensor node. The WSN required low energy consumption to provide a high network and guarantee the ultimate goal. The main objective of this work is to propose hybrid energy optimization in local aware environments. The hybrid proposed work consists of clustering, optimization, direct and indirect communication and routing. The aim of this research work is to provide and framework for reduced energy More >

Naglaa F. Soliman^1,2, E. A. Alabdulkreem³, Abeer D. Algarni^1,*, Ghada M. El Banby⁴, Fathi E. Abd El-Samie^1,5, Ahmed Sedik⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2545-2563, 2022, DOI:10.32604/cmc.2022.020107 - 29 March 2022

Abstract For military warfare purposes, it is necessary to identify the type of a certain weapon through video stream tracking based on infrared (IR) video frames. Computer vision is a visual search trend that is used to identify objects in images or video frames. For military applications, drones take a main role in surveillance tasks, but they cannot be confident for long-time missions. So, there is a need for such a system, which provides a continuous surveillance task to support the drone mission. Such a system can be called a Hybrid Surveillance System (HSS). This system… More >

Judd W. Moul

Canadian Journal of Urology, Vol.28, No.3, pp. 10668-10668, 2021

Abstract This article has no abstract. More >