• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.911-920
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• 2018

In this study, we performed a study to track the angle between the guided weapon and the target by using the strap-down image seeker, and constructed a test bed that can simulate it visually. This paper describes a method to maintain high-performance feature distribution in the implementation of sparse feature tracking algorithm such as Lucas Kanade's optical flow algorithm for target tracking using image information. We have extended the feature tracking problem to the concept of feature management. To realize this, we constructed visual environment using Unity3D engine and developed image processing simulation using OpenCV. For the co-simulation, dynamic system modeling was performed with Matlab Simulink, the visual environment using Unity3D was constructed, and computer vision work using OpenCV was performed.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.250-265
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• 2020

In the N-Screen environment, HTML5 standard-based content development is inevitable. However, it is still passive the development of HTML5 manipulation type contents due to high development cost and insufficient infrastructure. Therefor we propose an efficient contents development model by convergence multimedia contents (such as video and audio) with HTML5 documents that can implement dynamic manipulation for user interaction. The proposed model is designed to divide the multimedia and iframe areas in the HTML5 layout page included the player for integrated contents control. Interactive HTML5 documents are divided into screen units and provided through iframe. The integrated control player composed based on the HTML5

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.118-133
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• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.1
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• pp.103-111
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• 2021

Naju Seokdanggan, Treasure No. 49, was dismantled and reconstructed due to poor performance. During construction, the crack area was reinforced and the inclination was improved. It is necessary to analyze the stiffness changes before and after the reconstruction of these cultural properties, and to establish a database of related information. In addition, there is a need for research on a scientific non-destructive testing method capable of predicting or evaluating the reinforcing effect. In this study, a simple equation for estimating the overall stiffness of the structural system was derived from information on the elasticity coefficient and the natural frequency measured by vibration tests before and after reconstruction work, and the applicability of the equation was examined. If the stiffness of important cultural properties is regularly investigated by the suggested method, it is judged that it can be used as data to estimate the time when structural safety diagnosis is necessary or when repair or reinforcement is necessary.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.345-353
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• 2022

The purpose of this study is to identify the types for open innovation of SMEs considering strategic- culture mixed typology and environmental dynamism. The analysis results of 182 SMEs classified into 4 groups are as follows. First, type PD had a positive effect on innovation performance in both in-bound and out-bound innovation and had improved performance through in-bound innovation in a dynamic technical environment. While DH had no significant effect on both innovations. Second, PH and DD, strategy-culture mismatched types, had a single effect of innovation that affected performance. No moderating effects of environmental dynamism had been shown in types PH, DD, DH. SMEs that aim for open innovation should strive to improve performance by aligning change-oriented strategy with creative and challenging culture.

• Journal of IKEEE
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• v.26 no.3
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• pp.380-388
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• 2022

The traditional malware detection technologies collect known malicious programs and analyze their characteristics. Then such a detection technology makes a blacklist based on the analyzed malicious characteristics and checks programs in the user's system based on the blacklist to determine whether each program is malware. However, such an approach can detect known malicious programs, but responding to unknown or variant malware is challenging. In addition, since such detection technologies generally monitor all programs in the system in real-time, there is a disadvantage that they can degrade the system performance. In order to solve such problems, various methods have been proposed to analyze major behaviors of malicious programs and to respond to them. The main characteristic of ransomware is to access and encrypt the user's file. So, a new approach is to produce the whitelist of programs installed in the user's system and allow the only programs listed on the whitelist to access the user's files. However, although it applies such an approach, attackers can still perform malicious behavior by performing a DLL(Dynamic-Link Library) injection attack on a regular program registered on the whitelist. This paper proposes a method to respond effectively to attacks using DLL injection.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.2
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• pp.203-210
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• 2022

Purpose : The purpose of this study was to investigate the effect of vestibular sensory stimulation exercise on the limit of stability, dynamic weight shift, and upper and lower extremities reaction time in adult women. Methods : This study was conducted with 30 female. All subjects were randomly and equally assigned to an experimental group and a control group of 15 each. Subjects assigned to the experimental group received vestibular sensory stimulation training for 6 weeks. For the intervention, vestibular sensory stimulation exercises were conducted by referring to the Hamid exercise method and the Cawthorne-Cooksey exercise method, and the control group did not receive any intervention. All subjects were tested for limit of stability, dynamic weight shift, and upper and lower extremities reaction time before and after the intervention. Results : The results of this study showed significant differences between groups in reaction time, moving velocity, and directional control in the limit of stability test after intervention. In the dynamic weight shift test after intervention, there was a significant difference between the groups in the slow directional control of left and right. And in the upper and lower extremities reaction time test after intervention, both scores and reaction time showed significant differences between groups. Conclusion : As a result, the three vestibular sensory stimulation exercises applied in this study improved the limit of stability, dynamic weight shift, and upper and lower extremities reaction time.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.217-223
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• 2022

Subspace clustering for online data streams requires a large amount of memory resources as all subsets of data dimensions must be examined. In order to track the continuous change of clusters for a data stream in a finite memory space, in this paper, we propose a grid-based subspace clustering algorithm that effectively uses memory resources. Given an n-dimensional data stream, the distribution information of data items in data space is monitored by a grid-cell list. When the frequency of data items in the grid-cell list of the first level is high and it becomes a unit grid-cell, the grid-cell list of the next level is created as a child node in order to find clusters of all possible subspaces from the grid-cell. In this way, a maximum n-level grid-cell subspace tree is constructed, and a k-dimensional subspace cluster can be found at the k^th level of the subspace grid-cell tree. Through experiments, it was confirmed that the proposed method uses computing resources more efficiently by expanding only the dense space while maintaining the same accuracy as the existing method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.183-196
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• 2022

Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.103-111
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• 2023

This paper proposes a new data correction technique that transforms anomalies in time series data into normal values. With the recent development of IT technology, a vast amount of time-series data is being collected through sensors. However, due to sensor failures and abnormal environments, most of time-series data contain a lot of anomalies. If we build a predictive model using original data containing anomalies as it is, we cannot expect highly reliable predictive performance. Therefore, we utilizes the LSTM-GAN model to detect anomalies in the original time series data, and combines DTW (Dynamic Time Warping) and GAN techniques to replace the anomaly data with normal data in partitioned window units. The basic idea is to construct a GAN model serially by applying the statistical information of the window with normal distribution data adjacent to the window containing the detected anomalies to the DTW so as to generate normal time-series data. Through experiments using open NAB data, we empirically prove that our proposed method outperforms the conventional two correction methods.