• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.400-403
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• 2021

Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.113-120
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• 2024

With the advancement of information and communication technology, we can easily generate various forms of data in our daily lives. To efficiently manage such a large amount of data, systematic classification into categories is essential. For effective search and navigation, data is organized into a tree-like hierarchical structure known as a category tree, which is commonly seen in news websites and Wikipedia. As a result, various techniques have been proposed to classify large volumes of documents into the terminal nodes of category trees. However, document classification methods using category trees face a problem: as the height of the tree increases, the number of terminal nodes multiplies exponentially, which increases the probability of misclassification and ultimately leads to a reduction in classification accuracy. Therefore, in this paper, we propose a new node expansion-based classification algorithm that satisfies the classification accuracy required by the application, while enabling detailed categorization. The proposed method uses a greedy approach to prioritize the expansion of nodes with high classification accuracy, thereby maximizing the overall classification accuracy of the category tree. Experimental results on real data show that the proposed technique provides improved performance over naive methods.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.3
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• pp.170-184
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• 2024

With the advancement of autonomous navigation technology in maritime domain, there is an active research on swarming Unmanned Surface Vehicles (USVs) that can fulfill missions with low cost and high efficiency. In this study, we propose a formation control algorithm that maintains a certain shape when multiple unmanned surface vehicles operate in a swarm. In the case of swarming, individual USVs need to be able to accurately follow the target state and avoid collisions with obstacles or other vessels in the swarm. In order to generate guidance commands for swarm formation control, the potential field method has been a major focus of swarm control research, but the method using the potential field only uses the position information of obstacles or other ships, so it cannot effectively respond to moving targets and obstacles. In situations such as the formation change of a swarm of ships, the formation control is performed in a dense environment, so the position and velocity information of the target and nearby obstacles must be considered to effectively change the formation. In order to overcome these limitations, this paper applies a method that considers relative velocity to the potential field-based guidance law to improve target following and collision avoidance performance. Considering the relative velocity of the moving target, the potential field for nearby obstacles is newly defined by utilizing the concept of Velocity Obstacle (VO), and the effectiveness and efficiency of the proposed method is verified through swarm control simulation, and swarm control experiments using a small scaled unmanned surface vehicle platform.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.29-48
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• 2019

Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

• Archives of design research
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• v.18 no.2 s.60
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• pp.155-164
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• 2005

Home-service robots need to have sufficient spatial information about the surroundings for interacting with human intelligently and performing services efficiently. It is very important to investigate the efficient interaction style that supports map building task through human-robot collaboration. We first analyzed map building task with a cleaning robot and drew 4 design factors and tentative solutions, including map building procedure (task-preferred procedure/space- preferred procedure), LCD display installation (robot/robot+remote control), navigation method (push type/pull type), feedback modality(GUI/GUI+TTS). The design factors and tentative solutions were defined as independent variables and levels. This research investigated how those variables affect to the human task performance and behavior in map building tast. 8 kinds of experiment prototypes were built and usability test among 16 house wives was conducted for acquiring empirical data. As the experiment result, in terms of map building procedure, space-preferred procedure indicated better task performance than task-proffered procedure as we expected. For the LCD display installation factor, remote control with LCD display indicated higher task performance and subjective satisfaction. In robot navigation method, it was very difficult to find a significant difference between push type and pull type which contrary to our expectation. In fact, push type indicated higher subjective satisfaction. Also in feedback modality, we have acquired negative feedback an additional TTS operation guidance. It seems that robot's autonomy before achieving spatial information is rudiment condition which means users are just interacting with a mobile appliance. Thus they prefer remote-control-based interaction style in robot map building process as they used in traditional appliance control.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.71-79
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• 2011

Traditionally, a dynamic network model is considered as a tool for solving real-time traffic problems. One of useful and practical ways of using such models is to use it to produce and disseminate forecast travel time information so that the travelers can switch their routes from congested to less-congested or uncongested, which can enhance the performance of the network. This approach seems to be promising when the traffic congestion is severe, especially when sudden incidents happen. A consideration that should be given in implementing this method is that travel time information may affect the future traffic condition itself, creating undesirable side effects such as the over-reaction problem. Furthermore incorrect forecast travel time can make the information unreliable. In this paper, a network-wide travel time prediction model under incidents is developed. The model assumes that all drivers have access to detailed traffic information through personalized in-vehicle devices such as car navigation systems. Drivers are assumed to make their own travel choice based on the travel time information provided. A route-based stochastic variational inequality is formulated, which is used as a basic model for the travel time prediction. A diversion function is introduced to account for the motorists' willingness to divert. An inverse function of the diversion curve is derived to develop a variational inequality formulation for the travel time prediction model. Computational results illustrate the characteristics of the proposed model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.307-315
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• 2023

Korea controls the departure of vessels based on the Maritime Safety Act such that only ships with seaworthiness can navigate in bad weather, but scientific evaluation results and quantitative basis for the designation of ships subject to control are insufficient. Opinions for improvement are being raised for a reasonable departure control operation. The purpose of this study is to evaluate the adequacy of the current departure control standards through actual measurement of tugboats, which are the type of vessels subject to control when a wind and wave advisory is effective, and to present quantitative grounds for improvement of controls. A sensor was installed on the tugboat to measure the ship's three-axis motion and hull acceleration, and the hull motion performance was measured by operating in the sea area with a significant wave height of 3 m. The measured values were compared and analyzed based on seaworthiness evaluation factors and limit value standards. The actual ship was excluded from the current control standard according to tonnage, but as a result of the analysis, the pitch value exceeded the operation standard, and a risk to navigation safety existed. The results of this study suggest the need for additional actual measurement studies that can represent various ship types and specifications and review ship departure control targets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.811-820
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• 2012

GNSS signal is vulnerable to jamming signal because of well-known signal structure and weak signal power. For these reasons, the need for analysis of jamming effects and anti-jamming techniques of is increasing. In this paper, a GNSS signal generator is designed which includes a radio wave propagation model for six kind of tactical environments and a body masking model for the reception environment of a vehicle. The radio wave propagation model for downtown, rural, forest, coastline, waste land and snow or ice area is designed using two-ray model. The body masking model is designed the effect which the antenna is affected by the reception environment of a vehicle and radiation pattern from a user configuration. The performance of generated signals from the GNSS signal generator considering reception environment of a vehicle is evaluated by a commercial GPS L1 receiver(NordNav) in normal and jamming environment. Also, the generated GNSS signal is compared to a commercial GPS L1 H/W based RF signal generator(STR4500). The results show that the designed GNSS signal generator in a normal environment compared to the same navigation performance. In jamming environment, it is shown that the body masking effect and GNSS signal acquisition and tracking loss in compliance with the jamming signal are precisely working in the reception environment of a vehicle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.