• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.174-178
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• 2015

This paper presents a new method for forecasting construction project cost and time at completion or at any intermediate time horizon of the project duration. The method is designed to overcome identified limitations of current applications of earned value method in forecasting project cost and time. The proposed method usesfuzzy set theory to model uncertainties associated with project performance and it integrates the earned value technique and the contractors' judgement. The fuzzy set theory is applied as an alternative approach to deterministic and probabilistic methods. Using fuzzy set theory allows contractors to: (1) perform risk analysis for different scenarios of project performance indices, and (2) perform different scenarios expressing vagueness and imprecision of forecasted project cost and time using a set of measures and indices. Unlike the current applications of Earned Value Method(EVM), The proposed method has a numberof interesting features: (1) integrating contractors' judgement in forecasting project performance; (2) enabling contractors to evaluate the risk associated with cost overrun in much simpler method comparing with that of simulation, and (3) accounting for uncertainties involved in the forecasting project cost.

• Journal of the military operations research society of Korea
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• v.8 no.1
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• pp.53-70
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• 1982

This thesis develops a more realistic and applicable new set covering model that is adjusted and supplied by the existing set covering models, and induces an algorithm for solving the new set covering model, and applies the new model and the algorithm to an actual set covering problems. The new set covering model introduces a probabilistic covering aistance ($0{\eqslantless}p{\eqslantless}1$)or time($0{\eqslantless}p{\eqslantless}1$) instead of a deterministic covering distance(0 or 1) or time (0 or 1) of the existing set covering model. The existing set covering model has not considered the merit of the overcover of customers. But this new set covering model leads a concept of this overcover to a concept of the parallel system reliability. The algorithm has been programmed on the UNIVAC 9030 for solving large-scale covering problems. An application of the new set covering model is presented in order to determine the locations of the air surveillance radars as a set covering problem for a case-study.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.85-90
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• 2008

In this paper, we propose a new robot cleaning algorithm, which we call SetClean. The new algorithm cleans from the most less complex area. Sometimes, when the cleaning completion time can be longer or can not be estimated, cleaning larger area first is better than optimizing the whole time for cleaning. To do this, SetClean algorithm divides the whole area into cleanable sub-areas using Set Cover algorithm and cleans the area in the order of high efficiency that maximize the cleanable area per unit time. SetClean algorithm decides the navigation flow by considering not only the size of the area but also the distance from the current robot location to the area to be cleaned and the delay time caused by the number of turns within the area. The experimental results show the mechanism and performance of the SetClean algorithm.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.2
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• pp.119-128
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• 2017

Purpose: The purpose of this study was to measure the average actual treatment time at the time of Tomotherapy treatment. We want to investigate the time required for the procedure in the treatment process that affects the actual treatment time. Patients and Methods: We measured the time required by the procedure in 31 patients who were treated with tomography therapy. Beam-on time, Image registration time, Set-up with scan time and Actual treatment time were measured and stepwise regression analysis was performed. Result: The average treatment time per a patient was 21.44 - 23.92 minutes. Beam-on time, Image registration time, and Set-up with Scan time were the important factors affecting the actual treatment time. The biggest influence was Beam-on time and Registration time was less affected by analysing. Conclusion: The average treatment time per a patient in tomotherapy treatment was $22.68{\pm}3.37$ minutes. The Approximately 21 patients are expected to be treated within 8 hours of regular work time. However, if the treatment is interrupted or the time of the procedure is changed during the treatment process, it affects the schedule of the daily treatment patients and the workload is expected to increase.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.5 s.335
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• pp.9-14
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• 2005

Simulation method for a pure radio-frequency (rf) mode of reflection-type and a pure rf mode of transmission-type radio-frequency single-electron transistor (RF-SET) operation is introduced. In this method, the solutions of differential equations based on Kirchhoff's law are obtained self-consistently at frequency-domain. Also, the steady-sate single-electron transistor (SET) current model and the time-dependent SET current model are used in this method. The reflected wave of a typical reflection-type RF-SET and the transmitted wave of a typical transmission-type RF-SET are calculated, and the accuracy of our developed method including the steady-state SET current model is verified with the method introduced by reference 2. At high frequency over GHz, results of our developed method including the time-dependent SET current model are considerably different from that including the steady-state SET current model. At high frequency over GHz, an exact time-dependent SET current model is needed to analyze RF-SET operation.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.13-26
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• 1992

Set-up reduction is an important aspect of the Japanese Just-In-Time (JIT) and Zero Inventory (ZI) concepts. In this paper, we first analyze the effects of set-up cost reduction on tatal inventory, average lot size and forecast horizon in the dynamic lot size model. We also examine the various effects of set-up cost reduction in the EOQ model and explain why many Japanese firms try to cut set-up cost and/or set-up time greatly.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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• pp.694-700
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• 1998

PSC box bridge by MSS construction method may not be set at cross section at one step. Web and bottom flange(U member) would be set at first, top flange will be set later with a time lag. In this case, U member and top flange concrete have different strain history. As two different aged section behaves as the composite section, there would happen the redistribution of stress. This is come from time-dependent strain characteristics of concrete itself. In this study, two models are considered, one with considering the set time of cross section and the other without. By performing longitudinal analysis of two models on considering construction stage, the stress differences of two are compared. As the analysis results show a considerable differences in the stresses of cross section between two models, the set time of cross section is needed for rational design f PSC box girder bridge.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.571-574
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• 2005

This paper gives some sufficient conditions for a given polyhedral set which is represented as a set of linear inequalities to be positive D-invariant for uncertain linear discrete-time systems in the case such that the systems matrices depend linearly on uncertain parameters whose ranges are given intervals. Further, the results will be applied to uncertain linear continuous systems in the sense of the above by using Euler approximation.

• Journal of Biosystems Engineering
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• v.39 no.2
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• pp.101-110
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• 2014

Purpose: The purpose of this study is to develop a system to optimize drying potential energy of the exhausted hot air by changing relative humidity of the air. This study modified the conventional drying method into a drying method changing exhaust cycle and time in order to control the relative humidity of the exhausted hot air during drying process. Method: A valve on the vent was controlled according to a preset time to change the exhaust cycle and time. This study analyzed the influence of the two different types of drying method on the drying characteristics, required energy, and quality of the dried peppers: conventional drying method exhausting hot air continuously and new drying method controlling exhaust cycle and time. Results: Drying characteristics based on exhaust time showed that drying time increased with exhaust time, and specific energy consumption was reduced by 28% from 18.39 MJ/kg (conventional method) to 13.24 MJ/kg when exhaust time was set to one minute. Drying characteristics based on heating time showed that drying time increased with heating time and specific energy consumption was reduced by 30% from 18.39 MJ/kg (conventional method) to 12.87 MJ/kg when exhaust time was set to 22 minutes. Drying characteristics based on exhaust cycle showed that drying time increased with exhaust cycle, and specific energy consumption was reduced by 31% from 18.39 MJ/kg (conventional method) to 12.69 MJ/kg when exhaust time was set to one minute and exhaust cycle was set to 22 minutes before drying and 40 minutes after drying. The quality of the dried red peppers showed that capsaicin, color, and sugar content were high as 34.87 mg/100g, 66.33, and 11.87%, respectively, when exhaust time was set to one minute and exhaust cycle was set to 22 minutes before drying and 40 minutes after drying. Conclusions: In order to utilize the drying potential energy of the exhausted air during drying process, the conventional drying method was modified into the drying method controlling exhaust cycle and time. The results showed that drying with exhaust cycle of one minute was more efficient in terms of drying time, required energy, and quality of the dried peppers than the one with exhaust cycle of 20~40 minutes.