• Journal of the Economic Geographical Society of Korea
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• v.12 no.1
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• pp.56-66
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• 2009

As the amount of information is rapidly growing, and the ubiquitous urban environments are emerging, the question which information type to provide and which communication media to support is a major challenge for commercial and public travel-information service providers. The current research reports the first findings of analyses of recent data, collected in metropolitan Seoul, about the acquisition of travel information and the communication media used. The study is based on the assumption that information acquisition and choice of communication medium is strongly context-driven. The study applies CHAID analysis to find homogeneous segments in information acquisition and use of communication media. Findings indicate that transport mode and activity are important determinant of information acquisition and choice of media. The type of travel information acquired co-varies strongly with transport mode and activity. In addition, we found evidence of time of day effects. Similarly, the choice of communication medium depends on the type of travel information searched for, transport mode and activity. The results suggest important implications of managerial and policy measures, in particular the dynamic, contextual market segmentation.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.32-41
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• 2003

In this paper, we implemented a looms management system which supports remote monitoring and scientific management of the looms. In the implemented system, the layout of the looms is placed in the user interface, and each loom's operating state and rate are automatically represented there. The implemented system has aggregate query processing functions for the looms existing in the selected area by the louse and it also has high level query processing functions to support the chart and pivot table; it can be used as a decision support system. The proposed system can detect temporal or persistent problems of the looms. Therefore, it can be used to raise the productivity and to reduce the cost in textile companies by coping with the situation properly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.67-72
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• 2001

Convolutional code and turbo code are used in the forward and backward link of IMT-2000. In this research, we will be in consideration of Viterbi algorithm In this paper, we design Viterbi decoder with 3-bits soft decision and SMT for the convolutional code in the forward link and backward link of IMT-2000 system. The major parameters of 3-bits Viterbi decoder is determined by simulation to have identical performance with the 4-bit soft decision Viterbi decoder.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.37-47
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• 2003

In this paper, a component was designed for a loom in a window, and then a user interface was implemented to be able to connect database and to process various queries. The implemented system has aggregate query processing functions for the loom components existing in the selected area by the mouse and it also supports high level query processing functions represented with chart and pivot table; we can use it as a decision support system. The proposed system can detect temporal or persistent problems in the looms. Therefore, it can be used to raise the productivity and to reduce the cost in textile companies by coping with the situation properly.

• Proceedings of the Safety Management and Science Conference
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• 2006.11a
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• pp.293-297
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• 2006

Recently most universities are suffering from students leaving their majors. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, this paper uses decision tree algorithm which is one of the data mining techniques which conduct grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on students leaving their majors. The dataset consists of 5,115 features through data selection from total data of 13,346 collected from a university in Kangwon-Do during seven years(2000.3.1 $\sim$ 2006.6.30). The main objective of this study is to evaluate performance of algorithms including CHAID, CART and C4.5 for classification of students leaving their majors with ROC Chart, Lift Chart and Gains Chart. Also, this study provides values about accuracy, sensitivity, specificity using classification table. According to the analysis result, CART showed the best performance for classification of students leaving their majors.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.911-920
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• 2009

Airbone software must comply the DO-178B standard in order to be certified by the FAA. The standard requires the unit testing of safety-critical software to meet the coverage criterion called MC/DC(Modified Condition/Decision Coverage). Although MC/DC is known to be effective in finding errors related to safety, it is also true that generating test cases which satisfy the MC/DC criterion is not easy. This paper presents a tool named MD-SAT which generates MC/DC test cases with SAT(SATisfiability) technology. It can be employed for generating diverse test cases in tools implementing various testing techniques including decision table based test, cause-effect graphing, and state-based test.

• International Commerce and Information Review
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• v.13 no.4
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• pp.81-100
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• 2011

With the smart device deployment, the interest in NFC technology is increasing. In this study, to be successful in NFC based business commercialization, we present main factors affecting success of NFC based e-commerce business model. To this end, we conduct NFC and business models, case study methodology through literature review. And then, we suggest representative NFC e-commerce business model cases, and practices that affect the success or failure of the six factors are derived Derived factors are based on inductive learning to apply the technology to create a case study table, and decision trees to bring it, NFC-based commerce business models need to be successful at the strategic implications are present.

• ETRI Journal
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• v.41 no.3
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• pp.358-370
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• 2019

The main aim of this study is to select the optimal set of genes from microarray cancer datasets that contribute to the prediction of specific cancer types. This study proposes the enhancement of the feature selection filter algorithm based on Joe's normalized mutual information and its use for gene selection. The proposed algorithm is implemented and evaluated on seven benchmark microarray cancer datasets, namely, central nervous system, leukemia (binary), leukemia (3 class), leukemia (4 class), lymphoma, mixed lineage leukemia, and small round blue cell tumor, using five well-known classifiers, including the naive Bayes, radial basis function network, instance-based classifier, decision-based table, and decision tree. An average increase in the prediction accuracy of 5.1% is observed on all seven datasets averaged over all five classifiers. The average reduction in training time is 2.86 seconds. The performance of the proposed method is also compared with those of three other popular mutual information-based feature selection filters, namely, information gain, gain ratio, and symmetric uncertainty. The results are impressive when all five classifiers are used on all the datasets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4587-4605
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• 2019

High Efficiency Video Coding (HEVC) suffers from high computational complexity due to its quad-tree structure in motion estimation (ME). This paper exposes an adaptive search range decision algorithm for accelerating HEVC integer-pel ME on GPU which estimates the optimal search range (SR) using a MAP (Maximum A Posteriori) estimator. There are three main contributions; First, we define the motion feature as the standard deviation of motion vector difference values in a CTU. Second, a MAP estimator is proposed, which theoretically estimates the motion feature of the current CTU using the motion feature of a temporally adjacent CTU and its SR without any data dependency. Thus, the SR for the current CTU is parallelly determined. Finally, the values of the prior distribution and the likelihood for each discretized motion feature are computed in advance and stored at a look-up table to further save the computational complexity. Experimental results show in conventional HEVC test sequences that the proposed algorithm can achieves high average time reductions without any subjective quality loss as well as with little BD-bitrate increase.

• Journal of Drive and Control
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• v.18 no.2
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• pp.20-31
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• 2021

An excavator is a construction machine that can perform various tasks such as trenching, piping, excavating, slope cutting, grading, and rock demolishing. In the 2010s, unmanned construction equipment using ICT technology was continuously developed. In this paper, the path design process was studied to implement the output data of the decision stage, and the path design algorithm was developed. For example, the output data of the decision stage were terrain data around the excavator, excavator mechanism information, excavator hydraulic information, the position and posture of the bucket at key points, the speed of the desired bucket path, and the required excavation volume. The result of the path design was the movement of the hydraulic cylinder, boom arm, bucket, and bucket edge. The core functions of the path design algorithm are the function of avoiding impact during the excavation process, the function to calculate the excavation depth that satisfies the required excavation volume, and the function that allows the bucket to pass through the main points of the excavation process while maintaining the speed of the desired path. In particular, in the process of developing the last function, the node tracking method expressed in the path design table was newly developed. The path design algorithm was verified as this path design satisfied the JCMAS H02 requirement.