• Journal of Families and Better Life
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• 제11권2호
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• pp.13-29
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• 1993

The Purpopse of this study are to classify the lifestyles of urban housewives with automobiles living in Gwangju to see their relationship between lifestyle and demographic social and econo-mic variables and to see the relationship between lifestyle and prepurchase information search activity. For these purpose a survey was conducted using questionaires on 410 The data was collected from March 8 to March 20 1993 and analyzed by factor analysis cluster analysis Duncan test {{{{ chi ^2 }} }}- t e s t a nd ANOVA. The findings are classified into 7 types: enjoyable convenience type (15.6%) conservative sound and thrifty type(17.3%) rationative type (13.2%) thrifty life type (11.0%) passive-inactive type(8.3%) fashion-pursuity type(12.9%) 2) The lifestyles of he respondents showed significant difference according to their age education level employment status. length marriage consumer education and type of housing. 3) The lifestyles of the respondents showed a difference only automobile attitude While showing no significant difference by automobile size information sources of automobile priority of automobile attitude and time spent in searching information The lifestyle of respondents showed a difference by automobile price size quality secuity warranty service and maintenance cost. 4) Among the lifestyle patterns of the respondents the passive-inactive type and rationative typ were positive about all the prepurchase information activity of automobile.

• Asia pacific journal of information systems
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• 제25권4호
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• pp.626-641
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• 2015

Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

• Review of Culture and Economy
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• 제17권2호
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• pp.3-28
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• 2014

The characteristics of performing arts differ from those of utilitarian goods in terms of economics. Factors other than price need to be considered to understand the demand for performing arts. Audience surveys as well as econometric demand studies have confirmed that socio-economic factors such as age, income, employment, and education are major determinants of the demand for performing arts. This study focused on the attributes of concerts rather than consumer characteristics to determine the concerts audiences select in terms of transaction cost. Genre, price, internet search trends, and the purpose of performance as well as price are tested as determinants of demand by using the data set for a major concert hall in Seoul. Genre and the specific purpose of concerts influence the demand for concerts. Internet search trends of the performer are used as indicators of popularity and information exposure, which are positively correlated with demand. This result supports the hypothesis that larger audiences would attend concerts that require lower information search costs. To note, price has a positive effect on demand in the higher price range, which means that concerts at higher prices attract larger audiences, whereas normal goods have a negative slope in the demand curve. This result can be explained by the hypothesis that consumers use price as an indicator of the quality expected of a concert. Transaction cost for selecting classical concerts thus forms an inverse-U shape curve against ticket price. These results provide some explanation of why audiences of classical music choose to attend concerts at high ticket prices while offering evidence in favor of the hypothesis that performing arts are selected in a social context.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제46권1호
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• pp.46-55
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• 2009

We study the problem of searching documents containing each of several keywords (conjunctive keyword search) over encrypted documents. A conjunctive keyword search protocol consists of three entities: a data supplier, a storage system such as database, and a user of storage system. A data supplier uploads encrypted documents on a storage system, and then a user of the storage system searches documents containing each of several keywords. Recently, many schemes on conjunctive keyword search have been suggested in various settings. However, the schemes require high computation cost for the data supplier or user storage. Moreover, up to now, their securities have been proved in the random oracle model. In this paper, we propose efficient conjunctive keyword search schemes over encrypted documents, for which security is proved without using random oracles. The storage of a user and the computational and communication costs of a data supplier in the proposed schemes are constant. The security of the scheme relies only on the hardness of the Decisional Bilinear Diffie-Hellman (DBDH) problem.

• KIPS Transactions on Software and Data Engineering
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• 제7권3호
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• pp.77-90
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• 2018

Software Defect Prediction (SDP) is a field of study that identifies defective modules. With insufficient local data, a company can exploit Cross-Project Defect Prediction (CPDP), a way to build a classifier using dataset collected from other companies. Most machine learning algorithms for SDP have used more than one parameter that significantly affects prediction performance depending on different values. The objective of this study is to propose a parameter selection technique to enhance the performance of CPDP. Using a Harmony Search algorithm (HS), our approach tunes parameters of cost-sensitive boosting, a method to tackle class imbalance causing the difficulty of prediction. According to distributional characteristics, parameter ranges and constraint rules between parameters are defined and applied to HS. The proposed approach is compared with three CPDP methods and a Within-Project Defect Prediction (WPDP) method over fifteen target projects. The experimental results indicate that the proposed model outperforms the other CPDP methods in the context of class imbalance. Unlike the previous researches showing high probability of false alarm or low probability of detection, our approach provides acceptable high PD and low PF while providing high overall performance. It also provides similar performance compared with WPDP.

• ETRI Journal
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• 제29권6호
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• pp.736-744
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• 2007

We propose a fast macroblock (MB) mode prediction and decision algorithm based on temporal correlation for P-slices in the H.264/AVC video standard. There are eight block types for temporal decorrelation, including SKIP mode based on rate-distortion (RD) optimization. This scheme gives rise to exhaustive computations (search) in the coding procedure. To overcome this problem, a thresholding method for fast inter mode decision using a MB tracking scheme to find the most correlated block and RD cost of the correlated block is suggested for early stop of the inter mode determination. We propose a two-step inter mode candidate selection method using statistical analysis. In the first step, a mode is selected based on the mode information of the co-located MB from the previous frame. Then, an adaptive thresholding scheme is applied using the RD cost of the most correlated MB. Secondly, additional candidate modes are considered to determine the best mode of the initial candidate modes that does not satisfy the designed thresholding rule. Comparative analysis shows that a speed-up factor of up to 70.59% is obtained when compared with the full mode search method with a negligible bit increment and a minimal loss of image quality.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.271-275
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• 2006

This paper describes the design and realization of full attitude system based on MEMS IMU and GPS carrier phase. The work can be divided into two parts: First, initial heading is determined by using two GPS receivers. And this paper discusses the usage of space geometry conditions to reduce the range of ambiguity search. The method presented in this paper was tested on the static. On the static condition, an accuracy better than 0.06 degrees for heading for 3.48m long baseline has been achieved. Integration of GPS and low cost MEMS IMU are used to realize the real-time heading attitude system. Second, level attitude (pitch and roll) is determined using the method of frequency-velocity for the feedback control. At the same time, the method using the attitude based on MEMS IMU to help determination of the range of ambiguity search is proposed. The results done on the sea show that an alternative means to provide real-time, cost-effective, accurate and reliable attitude information for attitude surveys. Though motivated by a big ships application, the design can be applied to other vehicles.

• Journal of Power Electronics
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• 제5권3호
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• pp.173-179
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• 2005

In this paper, a very low cost and robust sensing method for the rotor position of a TSRM(Toroidal Switched Reluctance Motors) is described. Position information of the rotor is essential for SRM drives. The rotor position sensor such as an opto-interrupter or high performance encoder is generally used for the estimation of rotor position. However, these discrete position sensors not only add complexity and cost to the system but also tend to reduce the reliability of the drive system. In order to solve these problems, in the proposed method, rotor position detection is achieved using voltage waveforms induced by the time varying flux linkage in the search coils, and then the appropriate phases are excited to drive the SRM. But the search coil's EMF is generated only when the motor rotates. Therefore the rotor position sensing method using squared Euclidean distance at a standstill is also examined. The simulation and experimental results are presented to verify the performance of the proposed method in this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제39C권9호
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• pp.767-773
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• 2014

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and there have been various systems which have been recently studied. For a successful economic ship routing system, it is needed to properly control an engine power or change a geographical path considering weather forecast. An optimal geographical path is difficult to be determined, though, because it is a minimal dynamic-cost path search problem where the actual fuel consumption is dynamically variable by the weather condition when the ship will pass the area. In this paper, we propose an geographical path-search algorithm based on evolutionary strategy to efficiently search a good quality solution out of tremendous candidate solutions. We tested our approach with the shortest path-based sailing method over seven testing routes and observed that the former reduced the estimated fuel consumption than the latter by 1.82% on average and the maximum 2.49% with little difference of estimated time of arrival. In particular, we observed that our method can find a path to avoid bad weather through a case analysis.

• The KIPS Transactions:PartD
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• 제16D권6호
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• pp.859-870
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• 2009

Despite the surge in the research for keyword search method over relational database, only little attention has been devoted to studying on relational data stream.The research for keyword search over relational data stream is intense interest because streaming data is recently a major research topic of growing interest in the data management. In this regard we first analyze the researches related to keyword search methodover relational data stream, and then this paper focuses on the method of minimizing the join cost occurred while processing keyword search queries. As a result, we propose an advanced keyword search method that can yield more meaningful results for users on relational data streams. We also propose a query optimization method using layered-clustering for efficient query processing.