• Asia pacific journal of information systems
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• v.15 no.3
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• pp.209-221
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• 2005

One of the most fundamental problems in business is to evaluate the value of each product. The difficulty is that the profit of one product not only comes from its own sales, but also its influence on the sales of other products, i.e., the "cross-selling effect". This study integrates a measure for cross selling and an algorithm for profit estimation. Sales transaction data and post sales survey data from on-line and off-line shopping mall is used to show the effectiveness of the method against other heuristic for profit estimation based on product-specific profitability. We show that with the use of the new method we are able to identify the cross-selling potential of each product and use the information for better product selection.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.1-7
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• 2019

Recently, smart factories have attracted much attention as a result of the 4th Industrial Revolution. Existing factory automation technologies are generally designed for simple repetition without using vision sensors. Even small object assemblies are still dependent on manual work. To satisfy the needs for replacing the existing system with new technology such as bin picking and visual servoing, precision and real-time application should be core. Therefore in our work we focused on the core elements by using deep learning algorithm to detect and classify the target object for real-time and analyzing the object features. We chose YOLO CNN which is capable of real-time working and combining the two tasks as mentioned above though there are lots of good deep learning algorithms such as Mask R-CNN and Fast R-CNN. Then through the line and inside features extracted from target object, we can obtain final outline and estimate object posture.

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.412.2-412
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• 2001

• Journal of Biomedical Engineering Research
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• v.26 no.2
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• pp.87-93
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• 2005

A new method for real-time estimating left ventricular relaxation time constant (T) from the left ventricular (LV) pressure waveform, based on the isovolumic relaxation model, is proposed. The presented method uses a recursive least squares (RLS) algorithm to accomplish real-time estimation. A new criterion to detect the end-point of the isovolumic relaxation period (IRP) for the estimation of T is also introduced, which is based on the pattern analysis of mean square errors between the original and reconstructed pressure waveforms. We have verified the performance of the new method in over 4,600 beats obtained from 70 patients. The results demonstrate that the proposed method provides more stable and reliable estimation of τ than the conventional 'off-line' methods.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.402-409
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• 2019

When a loss of coolant accident (LOCA) occurs in a nuclear power plant, accident scenarios which can prevent core damage are defined based on break size. Current probabilistic safety assessment evaluates that core damage can be prevented under small-break LOCA (SBLOCA) and steam generator tube rupture (SGTR) with rapid cool down (RCD) strategy when all safety injection systems are unavailable. However, previous research has pointed out a limitation of RCD in terms of initiation time. Therefore, RCD success criteria estimation based on allowable coping time under a SBLOCA or SGTR when all safety injection systems are unavailable was performed based on time-line and thermal-hydraulic analyses. The time line analysis assumed a single emergency operating procedure flow, and the thermal hydraulic analysis utilized MARS-KS code with variables of break size, cooling rate, and operator allowable time. Results show while RCD is possible under SGTR, it is impossible under SBLOCA at the APR1400's current cooling rate limitation of 55 K/hr. A success criteria map for RCD under SBLOCA is suggested without cooling rate limitation.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.7-26
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• 1996

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.20-31
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• 2008

In this paper, we propose a single view-based technique for the estimation of human height and position. Conventional techniques for the estimation of 3D geometric information are based on the estimation of geometric cues such as vanishing point and vanishing line. The proposed technique, however, back-projects the image of moving object directly, and estimates the position and the height of the object in 3D space where its coordinate system is designated by a marker. Then, geometric errors are corrected by using geometric constraints provided by the marker. Unlike most of the conventional techniques, the proposed method offers a framework for simultaneous acquisition of height and position of an individual resident in the image. The accuracy and the robustness of our technique is verified on the experimental results of several real video sequences from outdoor environments.

• Korean Management Science Review
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• v.14 no.1
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• pp.131-149
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• 1997

Software cost estimation is an important both for buyers and sellers(developers). We reviewed domestic and foreign researches and practices on software cost estimation with function point method comprehensively, In this paper, we derived four promising alternative function point models. They are an IFPUG(International Function Point User Group)-based model(Model I), a shorthand model for client/sever software systems(Model II), a data-oricnted model for relatively large software projects(Model III), and a general- purpose function point model for non business application softwares as well as business applications(Model IV). Empirical data shows that Model I, II, and IV are very useful function point models. In particular, model II and IV look very useful models since they are concise and accurate. These models can be incorporated in a new improved guideline for software cost estimation. General opinion survey shows that Model I, II and IV are preferable. There are no significant differences in preference between buyers and sellers. The survey also shows that users think function point method is better than step(line of code)-oriented cost estimation methods in many ways including objectivity and estimation accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.873-880
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• 2020

In this paper, we propose a guidance filter to estimate line of sight rate with strapdown seeker measurements and INS(Inertial Navigation System) information. The measurements of proposed guidance filter consisted of the LOS(Line of Sight) and relative position that can be calculated with the seeker's measurements, INS information and known target position, also the filter is based on an asynchronous filter to use outputs of the two sensors that are out of synchronous and period. Through the proposed filter, we can reduce the effect on parasitic loop that can be caused by using large time delay seeker and improve the estimation performance.