• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.193-200
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• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.341-346
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• 2018

Supramax bulk carriers cover a wide range of ocean transportation requirements, from major to minor bulk cargoes. Market forecasting for this segment has posed a challenge to researchers, due to complexity involved, on the demand side of the forecasting model. This paper addresses this issue by using technical indicators as input features, instead of complicated supply-demand variables. Artificial neural networks (ANN), one of the most popular machine-learning tools, were used to replace classical time-series models. Results revealed that ANN outperformed the benchmark binomial logistic regression model, and predicted direction of the spot market with more than 70% accuracy. Results obtained in this paper, can enable chartering desks to make better short-term chartering decisions.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.688-690
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• 2002

최근 인터넷 교육은 실시간 자료처리 및 양방향 지도가 가능하여 과속 인터넷 서비스를 기반으로 한 e-Learning의 수요가 날로 증가하고 있고 그에 부응하여 많은 교육용 웹 애플리케이션이 만들어지고 있다. 하지만 길 애플리케이션의 중요성과 복잡성이 증가하는 반면에 체계적이지 못한 개발 프로세스와 스크래치 수준의 개발 환경에 의해 길 애플리케이션은 품질 저하와 생산성 저하를 가져오게 되었다. 따라서, 교육용 길 애플리케이션의 비효율적인 개발 방식의 개선을 위해 INI(Instruction navigation Implementation)모델을 제시함으로써 교육용 웹 애플리케피션 개발을 체계적으로 이끌고 모델을 통한 추적성을 제공함으로써 유지보수성의 지원이 가능하다. 또한, 학습자 개개인의 수준에 맞는 컨텐츠의 제공과 적절한 피드백으로 반복학습을 통한 교육의 질적 제고를 목표로 한다.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.17-20
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• 2001

This study is regarding the autonomous navigation of the mobile robot which operates through a sensor, the Omnnidirectional Vision System which makes it possible to retrieve the real-time movements of the objects and the walls accessing the robot from all directions and to shorten the processing time. After attempting to extend the field of view by using the reflection system and then learning the point of all directions of 2$\pi$ from the robot at the distance, robot recognizes three-dimensional world through the simple image process, the transform procedure and constant monitoring of the angle and distance from the peripheral obstacles. This study consists of 3 parts: Part 1 regards the process of designing Omnnidirectional Vision System and part 2 the image process, and part 3 estimates the implementation system through the comparative study process and three-dimensional measurements.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1997.10a
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• pp.175-183
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• 1997

The Jiao Guan Ship was a sea ship, used by Zhang Baogao, the Silla great sea merchant, in the marine trade with china during the 8th cetury A.D. and the 9th century A.D. Studying on the Ship type of the Jiao Guan Ship is the urgent problem to be solved, in the sphere of learning abuot the history of communication between China and Korea. The authors take the initial probe into this subject , by researching Zhang Baogao's marie activities, and point out that the Jiao Guan Ship's original type should be the Sha Ship which was the sea ship sailing the sea in northern China , in the tang Dynasty. At the same time, the authors estimate the constructions and equipment of the ship.

• Journal of Navigation and Port Research
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• v.35 no.2
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• pp.179-185
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• 2011

This paper aims to examine the use of the Balanced Scorecard in a not-for-profit organization (the Korea Shipping Association). The KSA has begun using the Balanced Scorecard paradigm in its strategic planning process. In this paper an overview is presented of the basic concepts of the Balanced Scorecard including the financial perspective, customer perspective, internal process perspective, and learning and growth perspective. The accounting system and its pros and cons of the KSA are then surveyed in terms of its performance evaluation. The application of the Balanced Scorecard approach to the KSA is discussed in detail. Implications in using the Balanced Scorecard are discussed. Finally, conclusions regarding the use of the Balanced Scorecard in a not-for-profit organization are presented. Through this paper, the comprehensive understanding of the performance evaluation for not-for-profit organizations as the KSA would be promoted.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.302-306
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• 2021

Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.252-253
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• 2023

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.484-496
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• 2013

With diffusion of various mobile devices, mobile learning has been one of the dominant learning styles in education fields. The purpose of this research is to examine the difference between students' perceived importance-performance of mobile learning satisfaction. The researchers reviewed the literature looking for variables which affect influential factors of students' mobile learning satisfaction such as system, contents, service, use, and outcome. As a result of t-test, the performance is lower than the importance of all the influential factors. Also, according to the result of Importance-Performance Analysis(IPA) matrix, it was noted that system factor is the most crucial factor in improving mobile learners' satisfaction. This result implies that offering technical support and simplifying the navigation design for mobile learning are urgently required.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.