• Journal of Information Technology Application
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• v.2 no.1
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• pp.139-160
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• 2000

This paper suggests a technique for evaluating cognitive process when a working group performs its group tasks. First, it review a theory of distributed cognition which provides a theoretical background for investigating group's cognitive process. Then, it presents a procedure for DGOMS(Distributed GOMS) evaluation which is an extension from GOMS. GOMS is an analytica evalutation technique that has been used at the individual level. DGOMS analyzes task completion time and compares workload among group members on the basis of each member's task execution time, communication time, and cognitive workload. DGOMS can be applied to a situation where a group of people are working together for a common goal using a technical subsystem such as information systems.

• ETRI Journal
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• v.37 no.2
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• pp.212-221
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• 2015

As the amount of re-sequencing genome data grows, minimizing the execution time of an analysis is required. For this purpose, recent computing systems have been adopting both high-performance coprocessors and host processors. However, there are few applications that efficiently utilize these heterogeneous computing resources. This problem equally refers to the work of single nucleotide polymorphism (SNP) detection, which is one of the bottlenecks in genome data processing. In this paper, we propose a method for speeding up an SNP detection by enhancing the utilization of heterogeneous computing resources often used in recent high-performance computing systems. Through the measurement of workload in the detection procedure, we divide the SNP detection into several task groups suitable for each computing resource. These task groups are scheduled using a window overlapping method. As a result, we improved upon the speedup achieved by previous open source applications by a magnitude of 10.

• The Journal of Korea Robotics Society
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• v.13 no.3
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• pp.164-173
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• 2018

This paper proposes functional test methods of first-aid gadgets which are special end-effectors, for relief robot. In recent years, researches have been actively conducted on robots that can perform rescue operations on behalf of rescue workers in dangerous areas such as disasters and wars. These special robots mainly perform the task of finding or transporting injured people. However, it is sometimes they necessary to provide first aid in the field. Among the various first-aid operations, gadgets are being developed for oxygen supply, injection, and hemostasis operations that can be used in a defense/civilian area by using robot technology. Previous studies have proposed first-aid gadgets that are suitable for onsite situations and enable robots to perform the given task quickly and accurately. In this paper, we design a test procedure suitable for the functions of first-aid gadgets, summarize the results, and introduce future research directions.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3038-3047
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• 1996

In telerobot systems, visual servoing of a task object for a slave arm with an eye-in-hand has drawn an interesting attention. As such a task ingenerally conducted in an unstructured environment, it is very difficult to define the inverse feature Jacobian matrix. To overcome this difficulty, this paper proposes an auto-tuning fuzzy rule-based visual servo algorithm. In this algorithm, a visual servo controller composed of fuzzy rules, receives feature errors as inputs and generates the change of have position as outputs. The fuzzy rules are tuned by using steepest gradient method of the cost function, which is defined as a quadratic function of feature errors. Since the fuzzy rules are tuned automatically, this method can be applied to the visual servoing of a slave arm in real time. The effctiveness of the proposed algorithm is verified through a series of simulations and experiments. The results show that through the learning procedure, the slave arm and track object in real time with reasonable accuracy.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.435-460
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• 2013

Recommender systems are popular applications that help users to identify items that they could be interested in. A recent research area on recommender systems focuses on detecting several kinds of inconsistencies associated with the user preferences. However, the majority of previous works in this direction just process anomalies that are intentionally introduced by users. In contrast, this paper is centered on finding the way to remove non-malicious anomalies, specifically in collaborative filtering systems. A review of the state-of-the-art in this field shows that no previous work has been carried out for recommendation systems and general data mining scenarios, to exactly perform this preprocessing task. More specifically, in this paper we propose a method that is based on the extraction of knowledge from the dataset in the form of rating regularities (similar to frequent patterns), and their use in order to remove anomalous preferences provided by users. Experiments show that the application of the procedure as a preprocessing step improves the performance of a data-mining task associated with the recommendation and also effectively detects the anomalous preferences.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.197-206
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• 2007

The high commitment of a revenue officer makes to raise efficiency, can be directly related to task result and validity. The fundamental process through trust in superior, consisting the core of tax execution, needs to be studied significantly. This study is proposed to verify the practical influence of trust in superior with respect to productivity, participation in decision-making, and concentration. These factors are important prerequisites with respect to task processing of a tax revenue officer. As the result of analysis, the more trust in superior effects on the statue of productivity, participation in decision-making and concentration. It is the proof that the trust in superior procedure contributes in the aspects of productivity, participation in decision-making and concentration through the process of encouraging organizational validity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.173-183
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• 2018

It is a very difficult task to establish a collaborative procedure in a new business that requires multilateral collaboration or to revise the regulation by analyzing and proving objectively the problems in the collaborative process conducted already by multilateral collaboration. In this paper, we proposed an optimization model for collaborative process to establish the operation procedure between collaborative parties using PERT/CPM network diagram which allows us to calculate the processing time. In order to verify the effectiveness and usefulness of our model for the collaboration process optimization developed in this study, we applied the developed collaborative procedure to student selection of the work-and-study-in-parallel course associated with a degree executed by Ministry of Employment and Labor. This study can be useful not only for newly establishing or reconfiguring collaborative procedures but also for standardizing the business procedures for building information systems between collaborative organizations.

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.575-589
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• 2018

It is well known that the incidence angle of seismic excitation has an influence on the structural response of buildings, and this effect can be more significant in the case of near-fault signals. However, current seismic codes do not include detailed requirements regarding the direction of application of the seismic action and they have only recently introduced specific provisions about near-fault earthquakes. Thus, engineers have the task of evaluating all the relevant directions or the most critical conditions case by case, in order to avoid underestimating structural demand. To facilitate the identification of the most critical incidence angle, this paper presents a procedure which makes use of a two-degree of freedom model for representing a building. The proposed procedure makes it possible to avoid the extensive computational effort of multiple dynamic analyses with varying angles of incidence of ground motion excitation, which is required if a spatial multi-degree of freedom model is used for representing a building. The procedure is validated through the analysis of two case studies consisting of an eight- and a six-storey reinforced concrete frame building, selected as representative of existing structures located in Italy. A set of 124 near-fault ground motion records oriented along 8 incidence angles, varying from 0 to 180 degrees, with increments of 22.5 degrees, is used to excite the structures. Comparisons between the results obtained with detailed models of the two structures and the proposed procedure are used to show the accuracy of the latter in the prediction of the most critical angle of seismic incidence.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.1
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• pp.1-15
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• 2014

Refinery plant producing petroleum products from crude oil has significantly contributed to the creation of the national interests as a leading engineering industries. However, domestic Engineering Procurement Construction (EPC) companies are facing heavy competition for orders. Domestic EPC companies as EPC contractors are faced with some problems such as undertaking responsibility for FEED packages produced by other FEED companies. But domestic EPC contractors are unfamiliar to development and validation of FEED packages. It causes poor profitability and lower competitiveness of domestic companies. It is necessary for domestic companies to have capability to perform FEED activities in order to overcome these limitations instead of focusing on EPC phase after FEED phase. The systematic procedure is needed to perform the FEED activities, however, there are present difficulties on it due to the lack of experience in FEED packages development which require various engineering knowledge of chemical process, mechanics, electrics, instrumentation, civil engineering. This study has applied systems engineering method which is multi-disciplinary approach to derive and verify the solution to meet the customer's needs when the complex system is developed to task execution process development of FEED activities for refinery plant. The problems that may occur in the future were identified in advance by taking into account the various stakeholders and system context through the application of systems engineering. It helps to develop the task execution process systematically. The developed task execution process of FEED activities is planned to make effectiveness verified by engineering professionals experienced in FEED and continually enhance this process by field application.