• Journal of Digital Convergence
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• v.19 no.8
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• pp.249-255
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• 2021

This study proposed a method for determining weights for the eight quality characteristics, such as functionality, reliability, usability, maintainability, portability, efficiency, security, and interoperability, which are suggested by international standards, focusing on software test reports. Currently, the test results for software quality evaluation apply the same weight to 8 quality characteristics to obtain the arithmetic average. Weights for 8 quality characteristics were applied using the results from text analysis, and weights were applied using the results of text analysis of test reports for two products. It was confirmed that the average of test reports according to the weighted quality characteristics was more efficient.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.209-216
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• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. This paper presents a software cost estimation method using a support vector machine. Support vector machine is one of the efficient techniques for classification, and it is the classification method of input data based on Maximum-Margin Hyperplane. But SVM has the problem of the selection of optimal parameters, because it is dependent on user's parameters. This paper selects optimized SVM parameters using advanced method, and estimates software development cost. The proposed approach outperform some recent results reported in the literature.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.269-270
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• 2023

재해, 재난 발생 시에 구조대가 건물 내부나 지하철 등, 특정 구역 내의 대피하지 못한 잔류인원을 제대로 파악하데 어려움을 겪는다. 이를 개선하고자 YOLO와 DeepSORT를 활용하여 통행자를 인식하여 특정 구역의 잔류인원을 파악하고 이를 서버를 통해 확인할 수 있는 시스템을 개발하였다. 실시간 객체인식 알고리즘인 YOLOv4-tiny와 실시간 객체추적기술인 DeepSORT 알고리즘을 이용하여 제안한 방법을 Ubuntu환경에서 구현하고, 실내 상황에 맞춰 통행자 동선을 고려해서 적용하였다. 개발한 시스템은 인식된 통행자 객체방향으로 출입을 구분하여 데이터를 서버에 저장한다. 이에 따라 재해 발생 시 구역의 잔류인원을 파악하여 빠르고 효율적으로 요구조자 위치와 인원을 예측할 수 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.339-341
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• 2024

본 논문에서는 전기 자동차 배터리 팩 설계에서 성능 예측을 위해 전산유체해석 및 Long Short-Term Memory (LSTM)를 활용한다. 두 계산 모두의 예측이 상당한 유사성을 나타내며, 전산유체해석은 시스템 유체 역학을 고려한 상세한 물리 모델을 제공하고, LSTM은 시계열 데이터를 기반으로 한 딥러닝 모델로 효과적으로 패턴을 파악, 향후 온도 상승을 예측한다. 결과는 두 접근 모두가 효과적인 예측을 제공하며 향후 전기 자동차 배터리 팩 설계 및 최적화에서 종합적인 접근의 필요성을 강조한다. 특히, LSTM 기반 예측에 소요되는 시간은 계산 유체 역학의 약 25%로, 약 일주일 정도로 빠르게 확인 가능하다. 이는 현대 산업 환경에서 시간적 효율성이 중요한 측면을 강조하며, 계산 유체 역학의 상세한 물리 모델링과 LSTM의 빠른 예측 속도를 결합한 설계 방법론을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.127-140
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• 2013

We explored the relationship between the level of change awareness and deployment of software process improvement (SPI) approaches using a competing values framework. To measure awareness level of organization's change, we used DICE framework provides means for predicting the outcome of change management initiatives. The four factors for organizaton's change: duration, integrity, commitment, and effort are evaluated and a score is calculated. The DICE(R) score is used to classify projects into win, worry, or woe zones. In this paper, we apply the DICE(R) score as an independent variable to predict the outcome of a software process improvement. Our results indicated that the Organization have a higher chance of success have the better outcome in software process improvement.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.585-596
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• 2020

The purpose of this study is to examine effects of maker education for high-school students on attitude toward software education, creative problem solving, and computational thinking. The program was designed to develop an artificial intelligence robot using mBlock and Arduino and implemented at a maker space. We analyzed 19 students among 20 who participated in the program, the result of paired t-test indicated significant increase in all variables. Also, we performed a multiple regression analysis to investigate predictors of perceived achievement and satisfaction. The finding demonstrated an initial attitude toward software education was found to be the significant predictor of perceived achievement and satisfaction. With the results, we confirmed maker education enhances attitude toward software education, creative problem solving, and computational thinking. Lastly, we discussed the implications and limitations and suggested the direction for future research.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.510-518
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• 2023

This paper introduces a MATLAB graphical user interface (GUI) based software for performance analysis of navigation message and wide area differential correction of regional navigation satellite system (RNSS). This software was developed to analyze satellite orbit/clock-related performance of navigation message and wide area differential correction simulating RNSS for regions near Korea based on different distributions of monitor and reference stations. As a result of software operation, navigation message and wide area differential correction are given as output in MATLAB file format. From the analysis of output, it was confirmed that valid navigation message and wide area differential correction could be generated from the results about statistical feature of orbit and clock prediction errors, cm-level fitting errors for navigation message parameters, and 81.9% enhancement in range error for wide area differential correction.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Korean Chemical Engineering Research
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• v.49 no.3
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• pp.361-366
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• 2011

By using Monte Carlo simulation method we developed a new molecular simulation software which can be used to predict the thermodynamic properties of organic compounds. Starting from molecular structure and intermolecular potential function, rigorous statistical mechanical principles give a probability distribution for the behavior of a system containing many molecules, which enables us to calculate macroscopic thermodynamic properties of the system. The software developed in this work, cheMC, is based on Windows platform providing with easy access. One can efficiently administrate simulations by using an intuitive interface equipped with visualization tool and chart generation. It is expected that molecular simulations supplement the equation of state approach and will play a more important role in the study of thermodynamic properties.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.2
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• pp.202-209
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• 2008

Application of wind turbine generator system (WTGS) needs researches for performance prediction, pitch control, and optimal operation method. Recently a new type WTGS is developed and under testing. The notable feature of this WTGS is that it consists of two rotor systems positioned horizontally at upwind and downwind locations, and a generator installed vertically inside the tower. In this paper, a nonlinear simulation software developed for the performance prediction of the Dual Rotor WTGS and testing of various control algorithm is introduced. This software is hybrid in the sense that FORTRAN is extensively used for the purpose of computation and Matlab/Simulink provides a user friendly GUI-like environment.