• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.145-154
• /
• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of the Korea Society for Simulation
• /
• v.30 no.3
• /
• pp.1-9
• /
• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.5
• /
• pp.482-492
• /
• 2019

The naval ship consists of a variety of classes, including patrol, frigate, destroyer and landing ship. There are various means of communication between combat ships belonging to the mobile fleet, including voice network, text message network and tactical data link. The operation at the existing mobile fleet level was conducted mainly on voice and text message, and tactical data link were used mainly to share tactical information between combat ships. This study intended to design HCI for commander like as KDDX of fleet level based on tactical data link, a means of communication between ships, to secure operational control of the mobile fleet. Recently, naval ships have been developed in the organization of various sensors, weapons and tactical data links integrated into the combat management system, and this study also designed the HCI based on the tactical data links integrated in the combat management system. The purpose of this study was to secure the operational efficiency of the tactical data link based on the combat management system in operation of the mobile fleet, and to improve the capability of the fleet commander to recognize the battlefield situation awareness.

• (The)Study of the Eastern Classic
• /
• no.72
• /
• pp.67-95
• /
• 2018

Gyeong-san(經山) Jeong Won-yong(鄭元容, 1783~1873) passed the state examination in 1802(純祖 2), and he has been in office for about 70 years. Jeong Won-yong with excellent administrative ability, he was an important figure in the Sedo politics, and was recognized by many writers for his outstanding writings. Nevertheless, his research results are small. This paper studyed his literary theories as a preliminary to look at Jeong Won-yong's literature in general After examining the features of Jeong Won-yong, there were three main aspects. First, Jeong Won-yong had a negative view of imitation. In particular, he stressed that he should oppose the attitude of unconditionally following Go-in(古人) without considering his capabilities and express his intention. Second, Jeong Won-yong pursued Jin-ui(眞意) when he wrote a poem. He thought rather than think that it is important to decorate a poem, it is important that emotion is exposed to the poem in a natural way. And he tried to unfold his individuality in the poem without copying others. Because if he imitate someone else when he write a poem, it is hard to express his thinking. His negative view of imitation and he pursued Jin-ui(眞意) are closely related. Lastly, Jeong Won-yong considered records important. Jeong Won-yong's record spirit is deeply related to his government service life. Jeong Won-yong who had been in government service all his life, hoped his experience would help manage the country. That's why he thought records were very important. And through this recording behavior, he wanted to get help later on. So it seems that he left a vast works.