• Journal of the Korean Society of Clothing and Textiles
• /
• v.46 no.5
• /
• pp.868-889
• /
• 2022

Fashion companies are using a big data approach as a key strategic analysis to predict and forecast sales. This study investigated the effectiveness of the past sales, web search volume, information amount, brand promotion, and the advertising endorser on the sales forecasting model. The study conducted the autoregressive distributed lag (ARDL) time series model using the internal and external social big data of a national fashion brand. Results indicated that the brand's past sales, search volume, promotion, and amount of advertising endorser information amount significantly affected the sales forecast, whereas the brand's advertising endorser search volume and information amount did not significantly influence the sales forecast. Moreover, the brand's promotion had the highest correlation with sales forecasting. This study adds to information-searching behavior theory by measuring consumers' brand involvement. Last, this study provides digital marketers with implications for developing profitable marketing strategies on the basis of consumers' interest in the brand and advertising endorser.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.570-574
• /
• 1990

Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge. detection methods. The left ventricular diastolic volume and systolic volume and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

• Journal of Biomedical Engineering Research
• /
• v.8 no.2
• /
• pp.177-188
• /
• 1987

Detection of left ventricular boundary for the functional analysis of LV(left ventricle) is obtained using automatic boundary detection algorithm based on dynamic program ming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge detection methods. The left ventricular diastolic volume and systolic volume were computed after this automatic boundary detection, and these volume data were applied to analyze LV ejection fraction.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.6
• /
• pp.350-360
• /
• 1988

As the capacity of DC motor is increased, we should recheck several encountered problems like volume increase. Particularly, when a large DC motor should be installed within the limited space, it is necessary to minimize the volume of motor for the effective utilization of the limited space. This paper describes the procedure and the method of finding optimum design of a large DC motor. The result of the optimization will decide the basic dimensions of a large DC motor. The flexible tolerance method and polyhedron searching method are used in this optimization. This result of simulation of the existing large DC motors is compared with the data of the existing large DC motors to confirm the validity of this optimum design.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.8 s.101
• /
• pp.911-917
• /
• 2005

There were many attempts to reduce noise behind the noise barrier using active control techniques. Omoto(1993) Shao(1997) and Yang(2001) tried to actively control the diffracted noise behind the barrier and main concerns were about the arrangement methods for the control sources. Baek (2004) tried to get better results using the simulated annealing method and the sequential searching technique. The main goal of this study is to develop and compare the performance of several optimization techniques including those mentioned above, hybrid version of simulated annealing and genetic algorithm for the optimal control source positions of active noise barrier system. The simulation results show fairly similar performance lot the small size of searching problem. However, as the number of control sources are increased, the performance of simulated annealing algorithm and genetic algorithm are better than the others. Simulations are also made to show the performance of the selected optimal control source positions not only at the receiver position but at the surrounding volume of the receiver position and plotted the noise reduction level in 3-D.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.429-430
• /
• 2018

The introduction of mobile devices increased the need to apply limitations such as mobile devices' memory, speed, energy, and bandwidth on the designs of searching images. There is a demand to reduce such limitations on searching images on the mobile phone. Hence, this paper proposes a design that adds tags on pictures to manage the images in mobile environment, allowing efficient searches and deletion of duplicate files based on the similarities of the images. The proposed method does not compromise its efficiency by increasing costs; it also reduces the volume of data needed for mobile devices.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.6
• /
• pp.2427-2435
• /
• 2013

Design hourly volume and the K-factor, first proposed by FHWA in the 1950s, is based on the 30th hourly traffic volume during a year (out of 8,760 hours). It was used when surveying the traffic volume was laborious in the past and is still being used now although it leaves some to be desired for practical applications. More reasonable K-factor for better design, based on theoretical evidence, is needed. This paper proposes the knee searching method based on simple linear regression to find out the inflection point of the volume ranking curve that describe the annual 8,760 hourly traffic volumes. The method was applied to the Chungcheong province's national highway, and the results were compared to the existing guidelines' values of K-factors. Identified design hourly traffic volumes ranked between 43rd to 694th, which is much lower than the 30th volume, meaning that some overdesign examples are inevitable if the conventional $30^{th}$ volume is used.

• The Research Journal of the Costume Culture
• /
• v.26 no.2
• /
• pp.251-263
• /
• 2018

As mobile shopping has increased in the new media age, fashion consumers' decision making and product consumption processes have changed. The volume of consumer-driven information has expanded since media and social networking sites have enabled consumers to share information they obtain. The purpose of this study was to determine the factors affecting information searching strategies and information sharing about fashion products. An online survey collected data from 466 respondents, relating to the influence of product price level and consumer SNS commitment level on information search and information sharing. Experimental design of three product price level and two consumer SNS commitment level was used. Analysis of the data identified factors in fashion information searching as ongoing searching, prepurchase web portal information search, and prepurchase marketing information search. For low-price fashion products, prepurchase product-detail influenced intention to share information. For mid-priced products, ongoing search significantly affected intention to share information. Both ongoing search and prepurchase marketing information search showed significant effects for high-price products. Consumers who are more committed to SNS engaged in significantly more searching in all aspects of information search factors. Significant interaction effect was detected for consumer SNS commitment level and product price level. When consumers with low consumer SNS commitment search for information on lower-priced fashion products, they are less likely do a prepurchase web portal information search.

• Journal of International Society for Simulation Surgery
• /
• v.2 no.1
• /
• pp.26-32
• /
• 2015

Purpose When a surgeon examines the morphology of skull of patient, locations of craniometric landmarks of 3D computed tomography(CT) volume are one of the most important information for surgical purpose. The locations of craniometric landmarks can be found manually by surgeon from the 3D rendered volume or 2D sagittal, axial, and coronal slices which are taken by CT. Since there are many landmarks on the skull, finding these manually is time-consuming, exhaustive, and occasionally inexact. These inefficiencies raise a demand for a automatic localization technique for craniometric landmark points. So in this paper, we propose a novel method through which we can automatically find these landmark points, which are useful for surgical purpose. Materials and Methods At first, we align the experimental data (CT volumes) using Frankfurt Horizontal Plane (FHP) and Mid Sagittal Plane(MSP) which are defined by 3 and 2 cranial landmark points each. The target landmark of our experiment is the anterior nasal spine. Prior to constructing a statistical cubic model which would be used for detecting the location of the landmark from a given CT volume, reference points for the anterior nasal spine were manually chosen by a surgeon from several CT volume sets. The statistical cubic model is constructed by calculating weighted intensity means of these CT sets around the reference points. By finding the location where similarity function (squared difference function) has the minimal value with this model, the location of the landmark can be found from any given CT volume. Results In this paper, we used 5 CT volumes to construct the statistical cubic model. The 20 CT volumes including the volumes, which were used to construct the model, were used for testing. The range of age of subjects is up to 2 years (24 months) old. The found points of each data are almost close to the reference point which were manually chosen by surgeon. Also it has been seen that the similarity function always has the global minimum at the detection point. Conclusion Through the experiment, we have seen the proposed method shows the outstanding performance in searching the landmark point. This algorithm would make surgeons efficiently work with morphological informations of skull. We also expect the potential of our algorithm for searching the anatomic landmarks not only cranial landmarks.

• The Korea Journal of Herbology
• /
• v.36 no.5
• /
• pp.1-14
• /
• 2021

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public's interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic. Methods : Using the "Naver DataLab (http://datalab.naver.com)" service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume. Results : 'Cheonsangap (천산갑, 穿山甲, Manitis Squama)' was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias. Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.