• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.365-374
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• 1998

Control Chart is a powerful tool to detect that process is in control or out of control. CIM can have real effect when CIM involve automated quality control. A neural network approach is used for unnatural pattern detecting of control chart. The previous moving window method uses all unnatural pattern that is detected as moving time window. Therefore, It trains a large number of unnatural pattern and takes training time long. In this paper, the proposed method tests a small number of training unnatural pattern which modifies test data without repeating time. We shows that the proposed method has differences In training time and identification rate on the previous moving windows method. As results, we reduced training time and obtain the same identification rate.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.3
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• pp.182-187
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• 2004

In this paper, we propose a PC based distributed controller for a two axis convey table using real-time micro-kernel. PC, Windows program, gives an easy way to implement wealthy GUI and micro-kernel, ${\mu}$C/OS-II, provides a real-time capability to control devices. We built a real-time distributed control system using ${\mu}$C/OS-II kernel which needs to process the tasks for two motors within the desired time to synchronize the motion. We used both semaphore and message mail box for synchronization. Unlike the previous study where we used step motors for the actuator of two axes convey table, we rebuilt the convey table with DC motors and the dedicated position servo which had built in out lab, and then we implemented a realtime distributed control system by putting the micro-kernel into between PC and position servo. Moreover we developed the PC based graphic user interfaces for generating planar drawing image control. Experimental results also presented to show the Proposed control system is useful.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.4
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• pp.75-82
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• 2006

The main objective of this study is to find out the shortest path of the vehicle routing problem with time window constraints by using both genetic algorithm and heuristic. Hard time constraints were considered to the vehicle routing problem in this suggested algorithm. Four different heuristic rules, modification process for initial and infeasible solution, 2-opt process, and lag exchange process, were applied to the genetic algorithm in order to both minimize the total distance and improve the loading rate at the same time. This genetic algorithm is compared with the results of existing problems suggested by Solomon. We found better solutions concerning vehicle loading rate and number of vehicles in R-type Solomon's examples R103 and R106.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.294-303
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• 2023

During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows of required start and completion time. Our approach focused on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.

• ETRI Journal
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• v.46 no.3
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• pp.473-484
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• 2024

We introduce a machine learning-based web application to help travel agents plan a package tour schedule. K-nearest neighbor (KNN) classification predicts the optimal tourists' dwelling time based on a variety of information to automatically generate a convenient tour schedule. A database collected in collaboration with an established travel agency is fed into the KNN algorithm implemented in the Python language, and the predicted dwelling times are sent to the web application via a RESTful application programming interface provided by the Flask framework. The web application displays a page in which the agents can configure the initial data and predict the optimal dwelling time and automatically update the tour schedule. After conducting a performance evaluation by simulating a scenario on a computer running the Windows operating system, the average response time was 1.762 s, and the prediction consistency was 100% over 100 iterations.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.276-284
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• 2009

This paper applies DEA windows analysis in order to determine the efficiency of the Districts of Busan Metropolitan City over time for 5 years (2003 - 2007). This paper used such factors including Number of solutions of civil petitions, Local Tax Collection, and Financial Independent rate as output, Total Labor Costs, Government Employees, Population and Expenditure as inputs. This study concludes that the efficiency of the different District can fluctuate over time to different extents and efficiency of most District decreases from 2003. Indeed, the empirical results reveal that substantial inefficiency exists in some Districts at some point in time. In consequence, this validates the necessity for using DEA windows analysis in preference to an analysis based upon cross-sectional data. This paper shows that Districts' efficiency decreases as Window goes to 1 to 3.

• Journal of the Korea Safety Management & Science
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• v.20 no.2
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• pp.9-20
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• 2018

This study is empirically intended to look into the effects of HVAC management on condensation cause and prevention in indoor swimming pools. The findings are summarized as follows. First, the experience of condensation in indoor swimming pools showed that 132 out of 142 people in total experienced the condensation in indoor swimming pools, which they had a high experience rate of 92.3%. For the location of condensation, the wall joints were 46.8% and the windows were 34.5%, which a total of 72.3% occurred in the wall joints and windows. Second, the effect of construction design, HVAC management and building construction on the cause of condensation in indoor swimming pools showed that building construction had an effect on the cause and location of condensation depending on the seasonal time, partially adopting hypothesis 1. Third, the effect of condensation-causing factors on condensation-preventing factors in indoor swimming pools showed that condensation had a close relationship with air and temperature conditions depending on the time and location of condensation, adopting hypothesis 2. As for the above-stated findings, the HVAC management in indoor swimming pools is an important concern factor that continues to cause condensation despite the development of advanced construction materials. Especially, building construction is a main factor that has a direct effect on condensation in the HVAC management of facilities. This implies that the window management is important in maintaining the wall joints - which can suppress the selective use and defect occurrence of construction materials - or confined spaces for a long time.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.3
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• pp.200-205
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• 2000

In a previous paper, we have discussed the intelligent Windows 95-based data management program(IDPIN) which was developed for effective and efficient management of large amounts of pre-/in-service inspection(PSI/ISI) data of Kori nuclear power plants. The IDPIN program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis of the past are avoided. In this study, the intelligent Windows based data management program(WS-IDPIN) has been developed as an effective data management of PSI/ISI data for the Wolsong nuclear power plants. The WS-IDPIN program includes the modules of comprehensive management and analysis of PSI/ISI results, statistical reliability assessment program of PSI/ISI results(depth and length sizing performance etc), standardization of UT report form and computerization of UT results. In addition, the program can be further developed as a unique PSI/ISI data management expert system which can be part of the PSI/ISI total support system for Korean nuclear power plants.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.163-168
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• 2018

In this paper, we propose and develop a test automation program tool that automates GUI based testing using black box testing technique in Windows environment. The main features of the proposed test automation program tool are as follows. First, an error condition is designated as an image, a screen is captured for each test step, and an error message is detected through comparison of image similarity. Second, the proposed system supports various setting options such as event waiting time during execution and coordinate increment value between each test step. Such black box test automation research was common in environments such as Android and Web, but not in Windows environment. The results of performance evaluation show that the proposed system performs GUI test automation as an image comparison module and confirms that the test is performed normally by confirming process status and error image detection.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.113-122
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• 2012

This paper presents a new stereo matching technique which is based on the matching of feature windows and feature links. The proposed method uses the FAST feature detector to find image features in stereo images and determines the correspondences of the detected features in the stereo images. We define a feature window which is an image region containing several image features. The proposed technique consists of two matching steps. First, a feature window is defined in a standard image and its correspondence is found in a reference image. Second, the corresponding features between the matched windows are determined by using the feature link technique. If there is no correspondence for an image feature in the standard image, it's disparity is interpolated by neighboring feature sets. We evaluate the accuracy of the proposed technique by comparing our results with the ground truth of in a stereo image database. We also compare the matching accuracy and computation time with two conventional feature-based stereo matching techniques.