• IE interfaces
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• v.8 no.1
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• pp.45-52
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• 1995

Automated Storage and Retrieval System (AS/RS), which is an element of Computer Integrated Manufacturing (CIM), is a widely used material handling equipment with conveyors and Automatic Guided Vehicles (AGVs). Until now the evaluation of operational policies of AS/RS and control algorithms is done theoretically or by computer simulations. In this study, a real-time control and communication software for an AS/RS is developed for actually moving AS/RS miniature. A PC-based real-time operational program can control the AS/RS directly through the communication port. The operational system has additional functions such as storage/retrieval management, inventory management, statistics management, and protocol simulation. The communication protocol simulator of S/R machine can be used for the controller of an S/R machine.

• ETRI Journal
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• v.31 no.2
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• pp.121-128
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• 2009

In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for structured SVM problems. FSMO is conceptually simple, easy to implement, and faster than the standard support vector machine (SVM) training algorithms for structured SVM problems. Because FSMO uses the fact that the formulation of structured SVM has no bias (that is, the threshold b is fixed at zero), FSMO breaks down the quadratic programming (QP) problems of structured SVM into a series of smallest QP problems, each involving only one variable. By involving only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection. For the various test sets, FSMO is as accurate as an existing structured SVM implementation (SVM-Struct) but is much faster on large data sets. The training time of FSMO empirically scales between O(n) and O($n^{1.2}$), while SVM-Struct scales between O($n^{1.5}$) and O($n^{1.8}$).

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.147-150
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• 1998

The report presents basic functions of Time-delay System Toolbox (for MATLAB) -the general-purpose software package for Computer Aided Design of control systems with delays. The Toolbox is a collection of algorithms, expressed mostly in m-files for simulating and analysis of MIMO linear and nonlinear systems with discrete and distributed (time-varying) delays.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.634-636
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• 2003

Satrec Initiative (Si) is developing a ground processing system for Synthetic Aperture Radar (SAR) data. SAR provides its own illumination and is not dependent on the light from sun, thus permitting continuous day/night operation and all-weather imaging. The system is capable of producing standard level products from SAR signal. Hence, the system should be able to perform matched filtering, range compression, azimuth compression, multi-look image generation, and geocoded image generation. This paper will describe the processing steps including algorithms, design, and accuracy of the Si's SAR processing system by comparing with commercial software.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.417-425
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• 2008

An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.210-224
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• 2019

Given a positive integer k as input, a spatial preference query finds the k best data objects based on the scores (e.g., qualities) of feature objects in their spatial neighborhoods. Several solutions have been proposed for spatial preference queries in Euclidean space. A few algorithms study spatial preference queries in undirected spatial networks where each edge is undirected and the distance between two points is the length of the shortest path connecting them. However, spatial preference queries have not been thoroughly investigated in directed spatial networks where each edge has a particular orientation that makes the distance between two points noncommutative. Therefore, in this study, we present a new method called ALPS+ for processing spatial preference queries in directed spatial networks. We conduct extensive experiments with different setups to demonstrate the superiority of ALPS+ over conventional solutions.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.73-81
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• 2019

Various 3D contents are being developed using Unity 3D game engine. In this paper, the 3D content of horseback riding game, the first VR game in the country, is designed and developed. The existing riding simulator is investigated and compared to the VR riding game developed. We consider various games developed using Unity 3D game engine and serve previously developed tangible games. It is expected that development of VR riding games will prepare a new chapter in VR experience-type games. We propose the content development environment and scenario of VR riding game and present the main algorithms and main modules for real-time synchronization. The developed riding game contents are deployed to the riding system and are operated for commercial use in conjunction with the riding device. Through monitoring VR riding system, problems are derived and improvement measures are proposed. We offer a variety of additional development options to make the game more realistic in the future.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.11-16
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• 2022

Applying predictive analytics to predict software defects has improved the overall quality and decreased maintenance costs. Many supervised and unsupervised learning algorithms have been used for defect prediction on publicly available datasets. Most of these datasets suffer from an imbalance in the output classes. We study the impact of class imbalance in the defect datasets on the efficiency of the defect prediction model and propose a CPP method for handling imbalances in the dataset. The performance of the methods is evaluated using measures like Matthew's Correlation Coefficient (MCC), Recall, and Accuracy measures. The proposed sampling technique shows significant improvement in the efficiency of the classifier in predicting defects.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.225-232
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• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.67-76
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• 2019

Recently, with the advent of the software-based society, many organizations have been providing software developing education, such as coding, to Computer Science majors and non-Computer Science majors. When implementing a program, teachers can let students draw a variety of diagrams, such as flowcharts, UML diagrams, and ERD diagrams ahead. As the importance of computational thinking is increasingly emphasized, abstracting algorithms into diagrams is considered an important educational element. In this paper, we examined the visual literacy and abstract/concrete way of thinking of novice programmers in order to analyze factors affecting the abstraction process of drawing diagrams, and how they influence students' ability to understand diagrams and ability to draw. If we understand what factors influence the abstraction process in this study, we can suggest educational alternatives for future strategies in which teachers will teach students.