• Journal of Bio-Environment Control
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• v.28 no.1
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• pp.16-27
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• 2019

Using virtual reality technology, users can learn and experience many interactions in virtual space like the actual physical space. This study was conducted to develop air flow simulator that allows farmers and consultants to consult air flow through VR devices by creating a greenhouse or pigpen model. It can help educate farmers about the importance of ventilation effects for agricultural facilities. We proposed CFD visualization system by building a virtual reality environment and constructing database of CFD and structure of agricultural facilities. After consultants can set up situations according to environmental conditions, the users experience the visualized air flow of agricultural facility according to the ventilation effects. Also it can provide a quantified environmental distribution in the agricultural facility. Currently, the CFD data in agricultural facilities are established during winter and summer. In order to experience various environmental conditions in the developed system, The experts need to run CFD data under various environmental conditions and register them in the system requirements.

• Smart Media Journal
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• v.9 no.4
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• pp.152-161
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• 2020

In the construction, VR(Virtual Reality) is simply used by users to implement and experience 3D modeling in virtual reality, such as safety, practical education, and promotion. The VR related research includes content development and visualization simulation such as disaster safety evacuation simulation and design education contents. Research on developing suitable VR and presenting directionality is insufficient, which is required in practice. Therefore, in this study, prior to the development of VR suitable for the construction, quantitative evaluation, and analysis based on the judgment of experts are performed. However, the research was conducted on the design stages, which are believed to have high needs and application effects of VR during the lifecycle of construction. There are nine tasks that can be applied to VR in the design stage, and these tasks were evaluated and analyzed using IPA(Importance Performance Analysis) by surveying the level of expectations, importance, and performance. As a result, it was evaluated and analyzed that VR and content development was necessary for the review of member interference and collaboration work for decision making among related stakeholders. The results of this study are expected to be used as basic data for the development of VR to be applied in the design stage to the future.

• Journal of Information Technology Applications and Management
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• v.28 no.3
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• pp.59-75
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• 2021

This study aims to establish a foundation for autonomous driving on campus and communication of abundant university information in the HCI environment in a VR environment where college freshmen can freely travel around campus facilities. The purpose of this study is to develop a three-dimensional VR-style campus tour system to establish a media environment to provide abundant university information guidance services to freshmen in non-face-to-face situations. This study designed a three-dimensional virtual reality campus tour system to solve the problem of discontinuity in which VR360 filming space does not lead to space like reality, and to solve many problems of expertise in VR technology by constructing an integrated production environment of tour system. We aim to solve the problem of inefficiency, which requires a large amount of momentum in virtual space, by constructing a GUI that utilizes the motion of the field of view focus. The campus environment was designed as a three-dimensional virtual reality using a three-dimensional graphic design. In non-face-to-face situations, college freshmen freely transformed the HMD VR device, smartphone, FPS operation mode of the gyroscope sensor. The design elements of the three-dimensional virtual reality campus tour system were classified as ①Visualization of factual experiences, ②Continuity of space movement, ③Operation, automatic operation mode, ④Natural landscape animation, ⑤Animation according to wind direction, ⑥Actual space movement mode, ⑦Informatization of spatial understanding, ⑧GUI by experience environment, ⑨Text GUI by building, ⑩VR360, 3D360 Studio Environment, ⑪Three-dimensional virtual space coupling block module, ⑫3D360-3D Virtual Space Transmedia Zone, ⑬Transformable GUI(VR Device Dual Viewer-Gyro Sensor Full Viewer-FPS Operation Viewer) and an integrated production environment was established with each element. It is launched online (http://vautu.com/u1) by constructing a GUI for free driving mode and college information screens to adapt to college life for freshmen, and designing an environment that can be used simultaneously by current media such as PCs, Android, and iPads. Therefore, it conducted user research, held a development presentation, a forum on excellence in university innovation support projects, and applied it as a system on the website of a particular university. College freshmen will be able to experience university information directly from the web and app to the virtual reality campus environment.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1404-1415
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• 2022

The 2-dimensional arrangement method of nodes has been used in most of RF (Radio Frequency) based communication network simulations. However, this method is not useful for the an none-obstacle 3-dimensional space networks in which the propagation delay speed in communication is very slow and, moreover, the values of performance factors such as the communication speed and the error rate change on the depth of node. Such a typical example is an underwater communication network. The 2-dimensional arrangement method is also not useful for the RF based network like some WSNs (Wireless Sensor Networks), IBSs (Intelligent Building Systems), or smart homes, in which the distance between nodes is short or some of nodes can be arranged overlapping with their different heights in similar planar location. In such cases, the 2-dimensional network simulation results are highly inaccurate and unbelievable so that they lead to user's erroneous predictions and judgments. For these reasons, in this paper, we propose a method to place uniformly and randomly communication nodes in 3-dimensional network space, making the wireless link with neighbor node possible. In this method, based on the communication rage of the node, blocks are generated to construct the 3-dimensional network and a node per one block is generated and placed within a block area. In this paper, we also introduce an algorithm based on this method and we show the performance results and evaluations on the average time in a node generation and arrangement, and the arrangement time and scatter-plotted visualization time of all nodes according to the number of them. In addition, comparison with previous studies is conducted. As a result of evaluating the performance of the algorithm, it was found that the processing time of the algorithm was proportional to the number of nodes to be created, and the average generation time of one node was between 0.238 and 0.28 us. ultimately, There is no problem even if a simulation network with a large number of nodes is created, so it can be sufficiently introduced at the time of simulation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Steel and Composite Structures
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• v.48 no.1
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• pp.43-57
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• 2023

The impacts of waste tire rubber (WTR) on the bending conduct of reinforced concrete beams (RCBs) are investigated in visualization of experimental tests and 3D finite element model (FEM) using both ANSYS and SAP2000. Several WTR rates are used in total 4 various full scale RCBs to observe the impact of WTR rate on the rupture and bending conduct of RCBs. For this purpose, the volumetric ratios (Vf) of WTR were chosen to change to 0%, 2.5%, 5% and 7.5% in the whole concrete. In relation to experimental test consequences, bending and rupture behaviors of the RCBs are observed. The best performance among the beams was observed in the beams with 2.5% WTR. Furthermore, as stated by test consequences, it is noticed that while WTR rate in the RCBs is improved, max. bending in the RCBs rises. For test consequences, it is clearly recognized as WTR rate in the RCB mixture is improved from 0% to 2.5%, deformation value in the RCB remarkably rises from 3.89 cm to 7.69 cm. This consequence is markedly recognized that WTR rates have a favorable result on deformation values in the RCBs. Furthermore, experimental tests are compared to 3D FEM consequences via using ANSYS software. In the ANSYS, special element types are formed and nonlinear multilinear misses plasticity material model and bilinear misses plasticity material model are chosen for concrete and compression and tension elements. As a consequence, it is noticed that each WTR rates in the RCBs mixture have dissimilar bending and rupture impacts on the RCBs. Then, to observe the impacts of WTR rate on the constructions under near-fault ground motions, a reinforced-concrete building was modelled via using SAP2000 software using 3-D model of the construction to complete nonlinear static analysis. Beam, column, steel haunch elements are modeled as nonlinear frame elements. Consequently, the seismic impacts of WTR rate on the lateral motions of each floor are obviously investigated particularly. Considering reduction in weight of structure and capacity of the members with using waste tire rubber, 2.5% of WTR resulted in the best performance while the construction is subjected to near fault earthquakes. Moreover, it is noticeably recognized that WTR rate has opposing influences on the seismic displacement behavior of the RC constructions.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Korean Journal of Environment and Ecology
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• v.34 no.3
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• pp.259-270
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• 2020

Plants Social Network (PSN) was first used in recent studies to incorporate the plant sociology methods for the understanding of plant society with the social network analysis methods that have recently attracted attention in the social science and visualize and analyze a PSN. The process of construction and analysis on PSN proceeds in the order of setting up the survey area, investigating the appearance plants species on plots of 100㎡, analyzing the interspecific association, building the sociogram, and analyzing the network structure and centrality. This study established a PSN by investigating the appearance species after installing 708 plots to include various dominant vegetational physiognomies in Busan Metropolitan City, where coastal and inland vegetation could be observed simultaneously. The survey found a total of 195 species, including 42 species of evergreen, 151 species of deciduous trees, and 2 species of semi-evergreen trees. The interspecies binding analysis was performed with the focus on the total number of species. It showed the number of friendly species in the order of Eurya japonica (47 species), Trachelospermum asiaticum (46 species), Linder glauca (44 species), Sorbus alnifolia (44 species), and Ligustrum japonicum (41 species). Based on it, we generated a sociogram using Gephi 0.9.2 program. The sociogram was divided into groups that appeared mostly on the coast and those that did not, reflecting the geographical distribution characteristics of forest vegetation in Busan. The analysis of the network structured showed 1,709 links and an average of 17.5 species having interspecies binding with a species. The density was 0.09, the diameter was 5, and the average path distance was 2.268. We concluded that various PSNs should be established in the future for precise comparative analysis of network characteristics in the social science field. In the PSN of Busan Metropolitan City, Eurya japonica, Linder glauca, Ligustrum japonicum, and Trachelospermum asiaticum showed high centrality.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.