• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1356-1376
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• 2023

Software effort estimation is one of the most difficult tasks in software development whereas predictability is also of equal importance for strategic management. Accurate prediction of the actual cost that will be incurred in software development can be very beneficial for the strategic management. This study discusses the latest trends in software estimation focusing on analogy-based techniques to show how they have improved the accuracy for software effort estimation. It applies the standard deviation technique to the expected value of analogy-based estimates to improve accuracy. In more than 60 percent cases the applied technique of this study helped in improving the accuracy of software estimation by reducing the Magnitude of Relative Error (MRE). The technique is simple and it calculates the expected value of cost or time and then uses different confidence levels which help in making more accurate commitments to the customers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.1-9
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• 2008

The Logistic cone is studied as a most desirable for the software testing effort. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull cure as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing- effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• ETRI Journal
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• v.30 no.6
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• pp.865-867
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• 2008

A conventional environment adaptation for robust speech recognition is usually conducted using transform-based techniques. Here, we present a discriminative adaptation strategy based on a multi-condition-trained model, and propose a new method to provide universal application to a new environment using the environment's specific conditions. Experimental results show that a speech recognition system adapted using the proposed method works successfully for other conditions as well as for those of the new environment.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.139-146
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• 2003

This paper explains the design and implementation of the ERA(Error Recovery Agent). ERA is a system that is suitable for detecting, sharing and recovering software error based on multimedia distance education system. This system consists of an ED, ES, and ER. ED detects an error by hooking techniques. ES is an agent which is an error sharing system for distributed multimedia distance education system. We propose how an error application can be treated and recovered as 'media' in a multimedia collaborative environment.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.570-581
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• 2018

Recently, a software program has been used in nuclear power plants (NPPs) to digitalize many instrumentation and control systems. To guarantee NPP safety, the reliability of the software used in safetycritical instrumentation and control systems must be quantified and verified with proper test cases and test environment. In this study, a software testing method using a simulation-based software test bed is proposed. The test bed is developed by emulating the microprocessor architecture of the programmable logic controller used in NPP safety-critical applications and capturing its behavior at each machine instruction. The effectiveness of the proposed method is demonstrated via a case study. To represent the possible states of software input and the internal variables that contribute to generating a dedicated safety signal, the software test cases are developed in consideration of the digital characteristics of the target system and the plant dynamics. The method provides a practical way to conduct exhaustive software testing, which can prove the software to be error free and minimize the uncertainty in software reliability quantification. Compared with existing testing methods, it can effectively reduce the software testing effort by emulating the programmable logic controller behavior at the machine level.

• Journal of Ecology and Environment
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• v.41 no.4
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.529-536
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• 2008

Researches about 3-D Positioning system using GPS were carried out many-sided by national organs, laboratories, the worlds of science. And most of researches were development of relative positioning algorithm and its applications. Relative positioning has a merit, which can eliminate error in received signals. But its error increase due to distance of baseline. GPS absolute positioning is a method that decides the position independently by the signals from the GPS satellites which are received by a receiver at a certain position. And it is necessary to correct various kinds of error(clock error, effect of ionosphere and troposphere, multi-path etc.). In this study, results of PPP(Precise Point Positioning) used Bernese GPS software was compared with notified coordinates by the NGII(National Geographic Information Institute) in order to analyze the positional accuracy of permanent GPS sites. And the results were compared with results of AUSPOS - Online GPS Processing Service for comparison with relative positioning.

• Journal of The Korean Association of Information Education
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• v.22 no.2
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• pp.205-212
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• 2018

As a way to improve the software education ability of the pre - service teachers, we conducted programming learning using two types of programming tools (Python and Scratch) at the regular course time. In programming learning, various types of errors, which are factors that continuously hinder interest, achievement and creativity, were collected and analyzed by type. By using the analyzed data, it is possible to improve the ability of pre-service teachers to cope with the errors that can occur in the software education to be taught in the elementary school, and to improve the learning effect. In this study, logic error (37.63%) was the most frequent type that caused the most errors in programming in both conventional language that input text and language that assembles block. In addition, the detailed errors that show a lot of differences in the two languages are the errors of Python (14.3%) and scratch (3.5%) due to insufficient use of grammar and other errors.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.193-199
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• 2014

As the requirement on the quality of the system has increased, the reliability is very important part in terms of enhance stability and to provide high quality services to customers. Many statistical models have been developed in the past years for the estimation of software reliability. We consider the functions for NHPP software reliability model and time series model in software failure data. We estimate parameters for the proposed models from three data sets. The values of SSE and MSE is presented from three data sets. We compare the predicted number of faults with the actual three data sets using the NHPP software reliability model and time series model.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2618-2629
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• 1999

In this paper, we describe the design and implementation of the FDRA(Fault Detection Recovery based on Agent) running on distributed multimedia environment. DOORAE is a good example for distributed multimedia and multimedia distance education system among students and teachers during lecture. It has primitive service agents. Service functions are implemented with objected oriented concept. FDRA is a multi-agent system. It has been environment, intelligent agents interact with each other, either collaboratively or non-collaboratively, to achieve their goals. The main idea is to detect an error by using polling method. This system detects an error by polling periodically the process with relation to session. And, it is to classify the type of error s automatically by using learning rules. The merit of this system is to use the same method to recovery it as it creates a session. FDRA is a system that is able to detect an error, to classify an error type, and to recover automatically a software error based on distributed multimedia environment.