• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.139-146
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• 2014

Through numerous mobile device technology advances, various multimedia contents is moving towards mobile devices from existing personal computer (PC). These paradigm has emerged taking into account these idea, the so-called N-Screen, N-Screen is user-centric service to provide running and sharing on everywhere via advanced smart system in C-P-N-T (Content, Platform, Network, Terminal). Therefore we must provide securing of various contents, openended platform, and user-centric service for efficient N-Screen service. For These characteristic of N-Screen, this paper propose design and implementation of user location-based N-Screen service system. The proposed system realize user location through user's smart phone and offer automatic streaming service to user. And also, we provide web service-based extended N-Screen service. Thus, user can access various device, such as laptop, tablet, and mobile device.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of Information Technology Applications and Management
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• v.30 no.6
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• pp.53-68
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• 2023

Through the COVID-19 pandemic, the demand for non-face-to-face communication systems has surged, leading to an increased prevalence of virtual interactions across various domains, such as tasks, meetings, orders and deliveries, and even student education. Against this backdrop, interest in the metaverse platform has been on the rise, with metaverse services like Zepeto, Roblox, and Minecraft expanding beyond gaming to encompass educational fields as well. This study aims to identify authenticity factors influencing metaverse platform-based educational services and examine their impact. The authenticity components are defined as integrity, empathy, interactivity, presence, and uniqueness. The study investigates the effects of these authenticity components on both service value and service satisfaction. To achieve this, a survey involving 320 metaverse users was conducted, and the model was subjected to statistical validation. The findings of this research underscore that perceiving metaverse education services, still in the early stages of introduction, as authentic educational methods for learners positively influences satisfaction with the educational service.This study holds significance as it lays the theoretical groundwork for enhancing the authenticity of educational services in virtual space. It defines and proposes authenticity elements for customer satisfaction in metaverse educational services, which are still in their nascent stages. Moving forward, it is anticipated that various studies will be conducted to enhance the value of metaverse education services and achieve higher customer satisfaction as customer experiences evolve and deepen.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.10
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.197-204
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• 2008

The purpose of this paper was to develop a rehabilitation training system which is controlled by electric currents to the Magneto-Rheological dampers system. This system provided the function for the training of the unbalance of the lower extremities. 10 subjects executed the tracing and moving exercises which are presented through the display monitor and confirmed own the capability of performance on the task. The electromyographies of the four muscles in lower extremities were recorded and analyzed in the time and frequency domain the muscles of interest were rectus femoris, biceps femoris, gastrocnemius, tibialis anterior. The experimental results showed that subjects had a task under feedback mode then subjects improve the capability of performance, increasing the in time, decreasing the out time and the distance of body shift. The moving average EMG, spectral energy of four muscle is lower the feedback mode than the constant mode. This could aid the hemiplegic patients to train more easily.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.185-191
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• 2019

During the modern battlefields of multi-batches flight formation attack situation, it is an essential task for a commander to make a proper fire distribution of air defense missile launch platforms for threat targets with effectively and quickly. Pan et al. try to solve this problem using genetic algorithm, but they are fails. This paper gets the initial feasible solution using high threat target first destroying strategy only use 75% available fire of each missile launch platform. Then, the assigned missile is moving to another target in the case of decreasing total threat. As a result of experiment, while the proposed algorithm is polynomial-time complexity greedy algorithm but this can be improve the solution than genetic algorithm.

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.792-811
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• 2023

Recently, Web 3.0 services such as virtual currency, block chain, and NFT are attracting public attention. Users who depended on platforms are moving away from being dependent on service providers and moving to Web 3.0 services. Representative services of Web 3.0 include P2E (Play to Earn) and M2E (Move to Earn). In the case of P2E, various studies have been conducted as it is widely covered in the press and media, but research on M2E is relatively lacking. This study attempts to identify the intention to use M2E by using the expanded technology acceptance model. External factors were selected based on M2E's own characteristics and personal characteristics, a research model was designed, and the proposed hypotheses were verified through factor analysis and goodness of model fit. As a result of the study, it was confirmed that profitability, innovativeness, and self-expression had a positive effect on perceived characteristics, and that perceived usefulness, perceived enjoyment, and social influence had a positive effect on intention to use. Through the research results, practical implications for efficient service operation that meets the needs of users are presented to M2E platform providers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.639-645
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• 2018

This paper is intended to develop a decision model that can be applied to autonomous vehicles and autonomous mobile vehicles. The developed module has an independent configuration for application in various driving environments and is based on a platform for organically operating them. Each module is studied for decision making on lane changes and for securing safety through reinforcement learning using a deep learning technique. The autonomous mobile moving body operating to change the driving state has a characteristic where the next operation of the mobile body can be determined only if the definition of the speed determination model (according to its functions) and the lane change decision are correctly preceded. Also, if all the moving bodies traveling on a general road are equipped with an autonomous driving function, it is difficult to consider the factors that may occur between each mobile unit from unexpected environmental changes. Considering these factors, we applied the decision model to the platform and studied the lane change decision system for implementation of the platform. We studied the decision model using a modular learning method to reduce system complexity, to reduce the learning time, and to consider model replacement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.1-8
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• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.62-71
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• 2013

The passive emitter location method using TDOA and FDOA measurements has higher accuracy comparing to the single TDOA or FDOA based method. Moreover, it is able to estimate the velocity vector of a moving platform. Recently, several non-iterative methods were suggested using the nuisance parameter but the common reference sensor is needed for each pair of sensors. They show also relatively low performance in the case of a long range between the sensor groups and the emitter. To solve this, we derive the estimation method of the position and velocity of a moving platform based on the Gauss-Newton method. In addition, to analyze the estimation performance of the position and velocity, respectively, we decompose the CRLB matrix into each subspace. Simulation results show the estimation performance of the derived method and the CEP planes according to the given geometry of the sensors.