• Journal of Science Education
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• v.47 no.2
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• pp.211-224
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• 2023

The purpose of this study is to suggest how to investigate the reliability of the assessment, which consists of items generated by automatic item generation using empirical example data. To achieve this, we analyzed the illustrative assessment data by applying the multivariate generalizability theory, which can reflect the design of responding to different items for each student and multiple error sources in the assessment score. The result of the G-study showed that, in most designs, the student effect corresponding to the true score of the classical test theory was relatively large after residual effects. In addition, in the design where the content domain was fixed, the ranking of students did not change depending on the item types or items. Similarly, in the design where the item format was fixed, the difficulty showed little variation depending on the content domains. The result of the D-study indicated that the original assessment data achieved a sufficient level of reliability. It was also found that higher reliability than the original assessment data could be obtained by reducing the number of items in the content domains of operation, geometry, and probability and statistics, or by assigning higher weights to the domains of letters and formulas, and function. The efficient measurement conditions presented in this study are limited to the illustrative assessment data. However, the method applied in this study can be utilized to determine the reliability and to find efficient measurement conditions for the various assessment situations using automatic item generation based on measurement traits.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.259-260
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• 2012

With increasing interest in alternative energy source for green growth, this document shows that the study of kite flight control is based on the concept of autonomous flight of kite can exploit the energy. Currently, prototype kite was designed and the purpose of its flight test, by manual flight control with Remote Controller, was performed for the feasibility of the full automatic flight control. For the future research, the test data should be collected through the many flight test under various environment.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.378-387
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• 2006

A programming model for ubiquitous sensor network (USN) applications based on Nano-Qplus is proposed. USN applications mean programs of nodes which are components of sensor network such as sensor, router, sink and actuator. Developers can automatically generate programs of USN applications by setting attributes values of nodes using a script after they model a sensor network. A script for setting attributes values of a node is proposed in this paper. The algorithm of automatic code generation is also described. Developers can easily implement USN applications even if they do not know details of low-level communication, data sharing, and collective operations because the applications are automatically generated from a script. They set only attributes values of nodes using the script. Efforts for USN applications development also are reduced because of automatic code generation. Furthermore, developers can correct errors of applications in the early stage of development through ear]y test based on rapid code generation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.50-59
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• 1993

There is basic problem with the current evaluation method for character recognition systems. The current method evaluates the average recognition rate by applying the test data to the target system. The average recognition rate tells no more than and no less than the overall performance and it depends on the data. In this paper we propose a testing method which will analyze the target system and point out its strong points and weak points. This can be made possible through using the data which are generated cy distorting the standard character images according to a carefully controlled manner. This paper will describe how to automatically generate such distorted images. Also we will show the method is actually effective and useful by applying it to evaluating existing recognition algorithms.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.1975-1986
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• 1997

Recent evolution of communication networks has led toward increasingly a complex, large-scale protocol. Protocol conformance tests therefore, which consider only control flow, have many problems on testing data flow, transition condition, delay and so on. We propose, design, and implement the tool to solve these problems. The tool, which solves nondeterminism, generates test suites from an integrated flow graph and excludes infeasible path with reachable tree. The presented tool reduces the length of UIO sequence and is efficient partially to test the path that error rate is high. Our automatic test suite generator provides basis of protocol testing environment and high production.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.40-44
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• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.747-754
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• 2013

This paper describes SCTE(System and Control unit Test Equipment) as an integrated test equipment for airborne SAR system and control unit. SCTE enhances reusability of test equipment by modular design for required functions and strengthens automatic testing and test convenience by providing functions such as script-based testing function and report generation function. Also, it includes a navigation data simulator which can simulate various flight conditions. In this paper, we details SCTE requirements, H/W and S/W design, implementation, and test results with control unit and SAR system.

• International Journal of Contents
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• v.10 no.1
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• pp.1-11
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• 2014

In the current generation of smart mobile devices, object tracking is one of the most important research topics for computer vision. Because human face tracking can be widely used for many applications, collecting a dataset of face videos is necessary for evaluating the performance of a tracker and for comparing different approaches. Unfortunately, the well-known benchmark datasets of face videos are not sufficiently diverse. As a result, it is difficult to compare the accuracy between different tracking algorithms in various conditions, namely illumination, background complexity, and subject movement. In this paper, we propose a new dataset that includes 91 face video clips that were recorded in different conditions. We also provide a semi-automatic ground-truth generation tool that can easily be used to evaluate the performance of face tracking systems. This tool helps to maintain the consistency of the definitions for the ground-truth in each frame. The resulting video data set is used to evaluate well-known approaches and test their efficiency.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.5
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• pp.407-417
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• 2015

For the more accurate prediction on manoeuvring performance of a ship at initial design phase, bare hull manoeuvring coefficients were estimated by RANS(Reynolds Averaged Navier-Stokes) based virtual captive model tests. Hydrodynamic forces and moment acting on the hull during static drift and harmonic oscillatory motions were computed with a commercial RANS code STAR-CCM+. Automatic and consistent mesh generation could be implemented by using macro functions of the code and user dependency could be greatly reduced. Computed forces and moments on KCS and KVLCC 1&2 were compared with the corresponding measurements from PMM(Planar Motion Mechanism) tests. Quite good agreement can be observed between the CFD and EFD results. Manoeuvring coefficients and IMO standard manoeuvres estimated from the computed data also showed reasonable agreement with those from the experimental data. Based on these results, we could confirm that the developed virtual captive manoeuvring model test process could be applied to evaluate manoeuvrability of a ship at the initial hull design phase.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.70-77
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• 2022

This paper proposes database generation and management system for small-pixelized airborne target recognition. The proposed system has five main features: 1) image extraction from in-flight test video frames, 2) automatic image archiving, 3) image data labeling and Meta data annotation, 4) virtual image data generation based on color channel convert conversion and seamless cloning and 5) HOG/LBP-based tiny-pixelized target augmented image data. The proposed framework is Python-based PyQt5 and has an interface that includes OpenCV. Using video files collected from flight tests, an image dataset for airborne target recognition on generates by using the proposed system and system input.