Hyun Kwon^1,*, Sanghyun Lee²

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

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 recognition rate of a specific… 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

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 can be used to estimate… 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

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 knowledge fusion. Specifically, for event-type… 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

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 and trusted communication with the… 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

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 is based on a distributed… More >

Omar Said^1,3, Amr Tolba^2,3,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3887-3906, 2021, DOI:10.32604/cmc.2021.016076

Abstract Recently, Internet of Things (IoT) technology has provided logistics services to many disciplines such as agriculture, industry, and medicine. Thus, it has become one of the most important scientific research fields. Applying IoT to military domain has many challenges such as fault tolerance and QoS. In this paper, IoT technology is applied on the military field to create an Internet of Military Things (IoMT) system. Here, the architecture of the aforementioned IoMT system is proposed. This architecture consists of four main layers: Communication, information, application, and decision support. These layers provided a fault tolerant coverage communication system for IoMT things.… More >

chun-chi Li¹, chin-chiang Wang², yin-chia Su², yu-chen Chu², chia-chu Weng²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.2, pp. 31-32, 2009, DOI:10.3970/icces.2009.011.031

Abstract The aim of this paper was to establish the realistic breathing patterns in different exercise conditions by experimental measurement. Generally, the human inhalation rate varies from 15 L/min at rest to 135 L/min for intense exercise and the breathing cycles are varied with different exercise conditions. Previous author have used symmetric Weibel configuration to establish three realistic breathing patterns, i. e., resting (inhalation rate, 15 L/min), light activity (inhalation rate, 30 L/min), and moderate exercise (inhalation rate, 60 L/min). In this study, in addition to reconstructing the three realistic breathing patterns of above mention, we expand the establishment of the… More >

Raju R. Namburu¹, Eric R. Mark, Jerry A. Clarke

CMES-Computer Modeling in Engineering & Sciences, Vol.5, No.5, pp. 443-454, 2004, DOI:10.3970/cmes.2004.005.443

Abstract Computational electromagnetic (CEM) simulations of full-range military vehicles play a critical role in enhancing the survivability and target recognition of combat systems. Modeling of full-range military systems subjected to high frequencies may involve generating large-scale meshes, solving equations, visualization, and analysis of results in the range of billions of unknowns or grid points. Hence, the overall objective of this research is to develop and demonstrate a scalable CEM software environment to address accurate prediction of radar cross sections (RCS) for full- range armored vehicles with realistic material treatments and complex geometric configurations. A software environment consisting of scalable preprocessing, postprocessing,… More >