• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.57-58
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• 2023

The working time for loading and transporting containers in the container terminal is one of the factors directly related to port productivity, and minimizing working time for these operations can maximize port productivity. Among working time for container operations, the working time of yard tractors(Y/T) responsible for the transportation of containers between berth and yard is a significant portion. However, it is difficult to estimate the working time of yard tractors quantitatively, although it is possible to estimate it based on the practical experience of terminal operators. Recently, a technology based on IoT(Internet of Things), one of the core technologies of the 4th industrial revolution, is being studied to monitoring and tracking logistics resources within the port in real-time and calculate working time, but it is challenging to commercialize this technology at the actual port site. Therefore, this study aims to develop yard tractor working time prediction model to enhance the operational efficiency of the container terminal. To develop the prediction model, we analyze actual port operation data to identify factors that affect the yard tractor's works and predict its working time accordingly.

• Archives of design research
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• v.15 no.1
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• pp.143-152
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• 2002

As the Internet has been a daily instrument of our lives, the numbers of Internet users are increasing rapidly. Especially, we have to pay special attention to about rapid increasing of juvenile users. In the 1990's, Kids are growing up literally surrounded by new technologies and mu1timedia experiences. For these kids, most of the techno1ologies that we adults find surprising or even incredible are a part of their everyday landscape, a fact of life. Currently, only few of research and discussion has gone into understanding this field. And most of these web sites, set importance on furnishing information only. So educational characters of web are not manifested fully as well as children soon get board with learning with Internet so that feel difficulties in searching and accepting information. At this point, we must try to develop educational sites Not only to show information but also to offer a rich and entertaining time for kids while providing playful teaming and increased technological fluency. Fer this purpose, Web site should be all about combining play with learning. Site navigation should be easy and the pages load quickly. The page download time is also being considerable, which could send kids withy mouse-fingers looking for entertainment elsewhere. Everything about the site must have a familiar feel, uses adequate colors to be satisfied with the juveniles. Multimedia can help the communications in the websites. To maximize the educational effect, technological research and continues invest are need, in addition to usability test.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1047-1056
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• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.1075-1084
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• 2024

Efforts to expand the installation of devices that assist visually impaired individuals in their mobility are ongoing, but there are significantly fewer devices installed indoors compared to outdoors, causing considerable inconvenience for indoor navigation. Therefore, this paper aims to address these issues by applying the results of machine learning using YOLO(You Only Look Once) to a Raspberry Pi and by researching techniques to reduce errors through the trilateration method of UWB(Ultra-Wideband) sensors, applying it with a Kalman filter. The research results implemented an object recognition algorithm with a comprehensive accuracy of 91.7% using YOLO technology. Based on this object recognition, the direction (left, right, or front) was determined using the distance difference between two ultrasonic sensors set at an angle difference of 15 degrees. A distance of up to 1.5m was accepted through an infrared sensor to output a warning message according to the distance. The distance between the user's tag and the fixed three anchors was measured indoors through a UWB sensor, and the user's location was also measured indoors by linking the distance value with the three-side positioning technique.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.937-944
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• 2006

Although people's anxiety about the environmental problem has been getting higher, they are not provided good quality of knowledge about the environment. Based on this situation, Ecoblog can be a new type of online community to educate the public in ecological knowledge. Especially, Ecoblog can be utilized as a method of "preventive education", and it will contribute to reduce great amounts of environmental budget to restore contaminated environment to previous condition. Ecoblog also utilizes the concept of blog which user can create and append their site with chosen themes. A weblog or a blog is a non-commercial webpage regularly updated through the use of a blogging software which allows the user to "publish" kinds of amalgamations of text and graphics to the page as posts. The technology offered in Ecoblog is utilizing the concept of 4D place and game metaphor in order to provide users the sense of participation, interaction and immersion among them and the growing community. Thus, it requires applying the CAAD technology by implementing semantically well-defined building data model as a core database to create a 4D virtual community. This research focuses on defining a 4d spatial framework suitable for developing an online ecological community. Through our study, the state-of-the-art of online community has been studied at the first step. Second, the scenario of using EcoBlog described with content, visualization and navigation are defined based on the critical features derived at the first step. Finally, a 4d spatial framework composed of semantic building data model, content and rule database is constructed to propose factors that are necessary to establish an ecological virtual community. In conclusion, our framework could enhance the comprehension and interaction between users and virtual buildings in the ecological community by integrating the concept of game design, 4D CAD and semantic data model. Such framework can be applied to any online community for an educational purpose.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.195-204
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• 2017

Mobile robots are used for years as a valuable research and educational tool in form of available open-platform designs and Do-It-Yourself kits. Rapid development and costs reduction of Unmanned Air Vehicles (UAV) and ground based mobile robots in recent years allowed researchers to utilize them as an affordable research platform. Despite of recent developments in the area of ground and airborne robotics, only few examples of Unmanned Surface Vehicle (USV) platforms targeted for research purposes can be found. Aim of this paper is to present the development of open-design USV drone with integrated multi-level control hardware architecture. Proposed catamaran - type water surface drone enables direct control over wireless radio link, separate development of algorithms for optimal propulsion control, navigation and communication with the ground-based control station. Whole design is highly modular, where each component can be replaced or modified according to desired task, payload or environmental conditions. Developed USV is planned to be utilized as a part of the system for detection and identification of marine and lake waste. Cameras mounted to the USV would record sea or lake surfaces, and recorded video sequences and images would be processed by state-of-the-art computer vision and machine learning algorithms in order to identify and classify marine and lake waste.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.617-624
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• 2017

Speech recognition is now one of the most widely used technologies in HCI. Many applications where speech recognition may be used (such as home automation, automatic speech translation, and car navigation) are now under active development. In addition, the demand for speech recognition systems in mobile environments is rapidly increasing. This paper is intended to present a method for instant recognition of the Korean vowel 'ㅡ', as a part of a Korean speech recognition system. The proposed method uses bulk indicators (which are calculated in the time domain) instead of the frequency domain and consequently, the computational cost for the recognition can be reduced. The bulk indicators representing predominant sequence patterns of the vowel 'ㅡ' are learned by neural networks and final recognition decisions are made by those trained neural networks. The results of the experiment show that the proposed method can achieve 88.7% recognition accuracy, and recognition speed of 0.74 msec per syllable.

• Journal of The Korean Association of Information Education
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• v.8 no.1
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• pp.67-77
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• 2004

Recently, the rapid progress of internet technology stirs the widespread development in the educational areas. Internet has been exploited as an effective means to support school information management as well as to supplement traditional off-line teaching-learning methods. Science instruments are very important tools for science-related courses in the elementary schools. However, managing science instruments effectively has not been concerned greatly so far. Only off-line management systems were presented. In this paper, a Web-based science instrument management system is proposed. The proposed Web-based science instrument management system has the following characteristics. First, an extensive model for science instrument management is presented. The proposed model can be used as a standard model for effective management. Second, the system can provide inventory information as well as standard instrument requirements to teachers anytime anywhere. The system helps teachers make decisions on procurement plan. Finally, the user interface is designed to support easy navigation and simple use.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1047-1053
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• 2017

The range data acquired by 2D/3D LIDAR, a core sensor for autonomous navigation of an unmanned ground vehicle, is effectively used for ground modeling and obstacle detection. Within the ambiguous boundary of a road environment, however, LIDAR does not provide enough information to analyze the traversable region. This paper presents a new method to analyze a candidate area using the characteristics of LIDAR reflectivity for better detection of a traversable region. We detected a candidate traversable area through the front zone of the vehicle using the learning process of LIDAR reflectivity, after calibration of the reflectivity of each channel. We validated the proposed method of a candidate traversable region detection by performing experiments in the real operating environment of the unmanned ground vehicle.