• The Korean Journal of Archival Studies
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• no.39
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• pp.281-318
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• 2014

This article aims to inquire into the decision making system and the sources of the original documents made by means of it in Imperial Japan, the colonial Chosun, GHQ, and the occupied Japan in terms of the post-war treatments of compensation on the Japanese colonial rules. It deals with them from 1910 to 1952 in the perspective of history and archivistics. This article attempts to establish the foundation on which the perception of the documents made in the Imperial Japan, its colony, and the occupied territory would be widened by placing the colonial rules and the compensation on them into a continuous line. The records of Japan's forced occupation of Korea during 1910-1945, and the original records documenting the decision making process of post-war compensation under GHQ, 1945-1952, have been dispersed in Korea, Japan and the United States. This dispersed preservation was mainly due to the complicated decision-making process among Governor-General of Chosun, the Japanese Imperial government, and the GHQ. It was the top-down styled, dual decision making system, in which the critical policies, personnel, and budget had been decided in Imperial homeland, while their implementations were made in the colonies. As a result, the records documenting the whole process of domination have been preserved dispersedly in Japan and its colonies. In particular, the accounts of not yet paid Korean workers that was forced to mobilize in Japan's colonial periods, which is emerging as the diplomatic conflict between Korea and Japan, had been dealt in the decrees of the Japanese government and policy-making of GHQ. It has already been changed to the problem as 'economic cooperation' from the 'debt'. Also, the critical records for post-war compensation were preserved dispersedly in the United States and Japan under the top-down decision making process of GHQ-Japan. Therefore, the dispersed records of 1910-1952 about the colonial rules by the Imperial Japan and the post-war compensation on them must be re-investigated for the adequate documentation in the context of time and space.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.185-193
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• 2006

The on-going pre-environmental investigation at present is performed by separate numerical analysis of each provision which makes integrated pre-environmental investigation is difficult. The application of numerical data is insufficient, which results to the deterioration of environmental investigation result's objectivity. A lot of time and money is required for the investigation. In this study, the spacial analysis function of GIS was applied on the 8 pre-environmental investigation factors. Pre-environmental investigation GIS DMS(Decision Making System) was constructed to make integrated investigation possible through the use of investigation results for each factor. Through the use of the developed pre-environmental investigation GIS DMS and the pre-constructed GIS data, the objectivity of environmental investigation is sufficient and time and cost are reduced. Therefore, this system can be used for pre-environmental investigation during route selection in the initial stages of road construction. Through the numerical and visual data obtained from the system developed in this paper, it is easier to gain the approval of the public. Furthermore, environmental problems due to road construction can be investigated with less time and money during the initial stages of road construction.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.174-185
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• 2020

Leukemia induced death has been listed in the top ten most dangerous mortality basis for human being. Some of the reason is due to slow decision-making process which caused suitable medical treatment cannot be applied on time. Therefore, good clinical decision support for acute leukemia type classification has become a necessity. In this paper, the author proposed a novel approach to perform acute leukemia type classification using sequential neural network classifier. Our experimental result only cover the first classification process which shows an excellent performance in differentiating normal and abnormal cells. Further development is needed to prove the effectiveness of second neural network classifier.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.15-19
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• 2022

This study is to understand the relationship between turnover and various conditions. Turnover refers to workers moving from one company to another, which exists in various ways and forms. Currently, a large number of workers are considering many turnover rates to satisfy their income levels, distance between work and residence, and age. In addition, they consider changing jobs a lot depending on the type of work, the decision-making ability of workers, and the level of education. The company needs to accept the conditions required by workers so that competent workers can work for a long time and predict what measures should be taken to convert them into long-term workers. The study was conducted because it was necessary to predict what conditions workers must meet in order to become long-term workers by comparing various conditions and turnover using regression and decision trees. It used Microsoft Azure machines to produce results, and it found that among the various conditions, it looked for different items for long-term work. Various methods were attempted in conducting the research, and among them, suitable algorithms adopted algorithms that classify various kinds of algorithms and derive results, and among them, two decision tree algorithms were used to derive results.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.71-78
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• 2023

Employee turnover is one of the most important challenges facing modern organizations. It causes job experiences and skills such as distinguished faculty members in universities, rare-specialized doctors, innovative engineers, and senior administrators. HR analytics has enhanced the area of data analytics to an extent that institutions can figure out their employees' characteristics; where inaccuracy leads to incorrect decision making. This paper aims to develop a novel model that can help decision-makers to classify the problem of Employee Turnover. By using feature selection methods: Information Gain and Chi-Square, the most important four features have been extracted from the dataset. These features are over time, job level, salary, and years in the organization. As one of the important results of this research, these features should be planned carefully to keep organizations their employees as valuable assets. The proposed model based on machine learning algorithms. Classification algorithms were used to implement the model such as Decision Tree, SVM, Random Frost, Neuronal Network, and Naive Bayes. The model was trained and tested by using a dataset that consists of 1470 records and 25 features. To develop the research model, many experiments had been conducted to find the best one. Based on implementation results, the Neural Network algorithm is selected as the best one with an Accuracy of 84 percents and AUC (ROC) 74 percents. By validation mechanism, the model is acceptable and reliable to help origination decision-makers to manage their employees in a good manner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1730-1747
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• 2018

Multi-view video plus depth (MVD) is a mainstream format of 3D scene representation in free viewpoint video systems. The advanced 3D extension of the high efficiency video coding (3D-HEVC) standard introduces new prediction tools to improve the coding performance of depth video. However, the depth video in 3D-HEVC is time consuming. To reduce the complexity of the depth video inter coding, we propose a fast coding unit (CU) size and mode decision algorithm. First, an off-line trained Bayesian model is built which the feature vector contains the depth levels of the corresponding spatial, temporal, and inter-component (texture-depth) neighboring largest CUs (LCUs). Then, the model is used to predict the depth level of the current LCU, and terminate the CU recursive splitting process. Finally, the CU mode search process is early terminated by making use of the mode correlation of spatial, inter-component (texture-depth), and inter-view neighboring CUs. Compared to the 3D-HEVC reference software HTM-10.0, the proposed algorithm reduces the encoding time of depth video and the total encoding time by 65.03% and 41.04% on average, respectively, with negligible quality degradation of the synthesized virtual view.

• Water for future
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• v.29 no.3
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• pp.197-205
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• 1996

Flow carrying capacity of water distribution systems is getting reduced by deterioration of pipes in the systems. The objective of this study is to develop a managerial decision-making model for the rehabilitation of water distribution systems with a minimum cost. The decisions made by the model also satisfy the requirements for the discharge and pressure at demanding nodes in the system. The replacement cost, pipe break repair cost, and pumping cost are considered in the economic evaluation of the decision along with the break ratio and interest ratio to determine the optimal replacement time for each pipe. Then, the hydraulic integrity of the water distribution system is checked for the decision by a pipe network simulator, KYPIPE, if the discharge and pressure requirements, the decision made for the optimal replacement time is revised until the requirements are satisfied. The model is applied to an existing water distribution system, the Metropolita Water Supply Project (1st Phase). The result shows that the decisions for the replacement time determined by the economix analysis are accepted as optimal and the hydraulic integrity of the system is in good condition.

• Structural Engineering and Mechanics
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• v.71 no.2
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• pp.139-151
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• 2019

In a project schedule, it is possible to reduce the time required to complete a project by allocating extra resources for critical activities. However, accelerating a project causes additional expense. This issue is addressed by finding optimal set of time-cost alternatives and is known as the time-cost trade-off problem in the literature. The aim of this study is to identify the optimal set of time-cost alternatives using a multiobjective teaching-learning-based optimization (TLBO) algorithm integrated with the non-dominated sorting concept and is applied to successfully optimize the projects ranging from a small to medium large projects. Numerical simulations indicate that the utilized model searches and identifies optimal / near optimal trade-offs between project time and cost in construction engineering and management. Therefore, it is concluded that the developed TLBO-based multiobjective approach offers satisfactorily solutions for time-cost trade-off optimization problems.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.277-296
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• 2016

There is a need for rapid and objective assessment of concrete bridge decks for maintenance decision making. Infrared Thermography (IRT) has great potential to identify deck delaminations more objectively than routine visual inspections or chain drag tests. In addition, it is possible to collect reliable data rapidly with appropriate IRT cameras attached to vehicles and the data are analyzed effectively. This research compares three infrared cameras with different specifications at different times and speeds for data collection, and explores several factors affecting the utilization of IRT in regards to subsurface damage detection in concrete structures, specifically when the IRT is utilized for high-speed bridge deck inspection at normal driving speeds. These results show that IRT can detect up to 2.54 cm delamination from the concrete surface at any time period. It is observed that nighttime would be the most suitable time frame with less false detections and interferences from the sunlight and less adverse effect due to direct sunlight, making more "noise" for the IRT results. This study also revealed two important factors of camera specifications for high-speed inspection by IRT as shorter integration time and higher pixel resolution.

• Journal of KIBIM
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• v.10 no.1
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• pp.1-8
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• 2020

In managing building facilities, spatial information is the basic data for decision making. However, the method of acquiring spatial information is not easy. In many cases, the site and drawings are often different due to changes in facilities and time after construction. In this case, the site data should be scanned to obtain spatial information. The scan data actually contains spatial information, which is a great help in making space related decisions. However, to obtain scan data, an expensive LiDAR (Light Detection and Ranging) device must be purchased, and special software for processing data obtained from the device must be available.Recently, SLAM (Simultaneous localization and mapping), an advanced map generation technology, has been spreading in the field of robotics. Using SLAM, 3D spatial information can be obtained quickly in real time without a separate matching process. This study develops and tests whether SLAM technology can be used to obtain spatial information for facility management. This draws considerations for developing a SLAM device for real-time remote scanning for facility management. However, this study focuses on the system development method that acquires spatial information necessary for facility management through SLAM technology. To this end, we develop a prototype, analyze the pros and cons, and then suggest considerations for developing a SLAM system.