• Journal of Veterinary Clinics
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• v.31 no.4
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• pp.267-271
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• 2014

Accurate determination of in vivo oocyte maturation is particularly critical for dog cloning compared to other assisted reproductive technologies because oocytes in metaphase II stage have to be recovered in order to undergo somatic cell nuclear transfer right after its recovery. The aim of present study was to evaluate the reliability and to set a reference range of a chemiluminescence enzyme immunoassay (CLEIA) compared to radioimmunoassay (RIA) method to retrieve in vivo matured oocytes. Serum progesterone concentration during proestrus and estrus was analyzed by RIA and CLEIA to determine ovulation day (Day 0). On Day 3, in vivo oocytes were recovered surgically and evaluated microscopically maturation status after staining nucleus with bisbenzimidazole dye. Mean progesterone concentration by CLEIA ($7.64{\pm}0.06ng/ml$) was significantly higher than by RIA ($6.46{\pm}0.04ng/ml$, P < 0.0001). It was not different between CLEIA ($10.01{\pm}0.34ng/ml$) and RIA values ($7.91{\pm}0.14ng/ml$, P < 0.05) on Day 0, but significantly higher CLEIA level on Day -1 and Day 1 ($6.41{\pm}0.15$ and $14.25{\pm}0.44ng/ml$) was assessed compared to RIA ($4.95{\pm}0.10$ and $11.29{\pm}0.34ng/ml$). However, with both methods, progesterone level was significantly increased from Day -1 to Day 2. To determine oocyte maturation with CLEIA method, a wider and higher reference range has to be considered.

• Korean Journal of Optics and Photonics
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• v.16 no.3
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• pp.182-190
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• 2005

The fiber Raman amplifier(FRA) is a distinctly advantageous technology. Due to its wider, flexible gain bandwidth, and intrinsically lower noise characteristics, FRA has become an indispensable technology of today. Various FRA modeling methods, with different levels of convergence speed and accuracy, have been proposed in order to gain valuable insights for the FRA dynamics and optimum design before real implementation. Still, all these approaches share the common platform of coupled ordinary differential equations(ODE) for the Raman equation set that must be solved along the long length of fiber propagation axis. The ODE platform has classically set the bar for achievable convergence speed, resulting exhaustive calculation efforts. In this work, we propose an alternative, highly efficient framework for FRA analysis. In treating the Raman gain as the perturbation factor in an adiabatic process, we achieved implementation of the algorithm by deriving a recursive relation for the integrals of power inside fiber with the effective length and by constructing a matrix formalism for the solution of the given FRA problem. Finally, by adiabatically turning on the Raman process in the fiber as increasing the order of iterations, the FRA solution can be obtained along the iteration axis for the whole length of fiber rather than along the fiber propagation axis, enabling faster convergence speed, at the equivalent accuracy achievable with the methods based on coupled ODEs. Performance comparison in all co-, counter-, bi-directionally pumped multi-channel FRA shows more than 102 times faster with the convergence speed of the Average power method at the same level of accuracy(relative deviation < 0.03dB).

• Journal of radiological science and technology
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• v.6 no.1
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• pp.131-181
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• 1983

After the investigation on, and the analysis of, the educational system for medical technicians and the present educational situation for medical technologies in this country, the following conclusions were drawn. 1. As of March 1983 the current academic system for education in medical technologies included the regular 4-year college courses and those of the 2-year professional junior college courses. But except in the cases on clinical pathology and physical therapy, there were no college-level departments. Particularly, no educational institutions, at whatever level, had a department for working therapies. 2. The total number of credits needed for graduation from a department of medical technologies was 150 points at a regular 4-year college and 85 to 96 points at a 2-year professional college. The obligatory minimum number of credits for a student at a professional college was set at 80 points and above. 3. As for the number of the educational institutions for medical technologies in this country, there were one regular college and 14 professional colleges, a total of 15 institutions. As many as 14 colleges had departments of clinical pathology, 12 had departments of Radiotechnology, 11 had departments of physical therapy, 12 had departments of dental technology, and eight had departments of dental hygiene. 4. The total capacity of the professional colleges in admitting new enrollment each year were 1,920 for clinical pathology, 1,552 for radiology, 1,012 for physical therapy, 1,334 for dental technologies, 828 for dental hygiene, an aggregate of 6,646 for all of the professional college departments. 5. The total number of graduates from the 12 professional colleges by department during the period of 1965-83 were 7,595 for clindical pathology, 4,768 for radiology, 2,821 for physical therapy, 3,000 for dental technologies, and 1,787 for dental hygiene, totalling 19,971 for all departments in the professional colleges. 6. In the state examination for licensed medical technicians, 12,446 have passed from among the total of 26,609 participants, representing a 45% passing ratio. By departments the ratios showed 44% for clinical pathology, 39.7% for radiology, 51.2% for physical therapy, 42.5% for dental technology, 72.5% for dental hygiene and 73.1% for working therapy. 7. As for the degree of satisfaction shown by the people in this field, 52.2 percent of the teaching staffs who responed to the questionaires said they were satisfied with their present profession, while the great majority of medical technicians(66%) replied that they were indifferent to the problem. 8. The degree of satisfaction shown by the students on their enrollment in this particular academic field was generally in the framework of indifference(43.7%), but mere students(36.5%) were satisfied with their choice than those were not satisfied(14.4%) 9. As for the student's opinions on the lectures and practicing hours, a good many students replied that, among such courses as general science and humanities courses the basic medical course, the major course and practicing hours, the hours provided for the general courses(47.1%) and practicing(47.6%) were insufficient. 10. When asked about the contents of their major courses, comparatively few students (23.6%) replied that the courses were too difficult, while a convincing majority(58.5%) said they were neither difficult nor easy. As for the appropriateness of the number of the present teaching staffs, a great majority(71.0%) of the students replied that the level of the teaching personnel in each particular field was insufficient. 11. Among the students who responded to the poll, good part of them(49.5%) wanted mandatory clinical practicing hours, and the the majority of them(64.6%) held the view that the experimental and practicing facilities of their schools were insufficient. 12. On the necessity of the attached hospitals, 71.1% of the teaching staffs and 58.0% of the medical technicians had the opinion that this kind of facility was indispensable. 13. As for the qualifications for applicants to the state examination in the licensing system for medical technicians, 52.2% of the teacher's and 36% of the medical technicians replied that the present system granting the qualifications according to the apprenticeship period should be abolished. 14. On the necessity of improving the present system for education in medical technologies, an overwhelming majority(94.4% of the :caching staffs, 92.0% of the medical technicians and 91.9% of students) of these polled replied that the present system should be changed for the better. 15. On the method of changes for the present educational system, a great majority(89.4% of the teaching staffs, 80.4% of the medical technicians and 90.1% of the students) said that the system must be changed so that it fits into the reality of the present day. 16. As for the present 2-year program for the professional colleges, 61.6% of the teachers, 72.0% of the medical technicians and 38.8% of the students expressed the hope that the academic period would be extended to four regular years, hemming a full-fledged collegelevels program. 17. On the life-long eductional system for medical technicians, there was a considerable number of people who expressed the hope that an open university system(38.9% of the teaching staffs, 36.0% of the medical technicians) and a graduate school system would be set up. 18. As for the future prospects for medical technicians as professionals, the optimists ana pessimists were almost equally divided, and 41.1% of the teaching staffs 36.0% of. the technicians and 50.5% of the students expressed an intermediate position on this issue.

• Asia Marketing Journal
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• v.12 no.4
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• pp.79-111
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• 2011

Digital economy has grown rapidly so that the new business area called 'Internet business' has been dramatically extended as time goes on. However, in the case of Internet business, market shares of individual companies seem to fluctuate very extremely. Thus marketing managers who operate the Internet sites have seriously observed the competition structure of the Internet business market and carefully analyzed the competitors' behavior in order to achieve their own business goals in the market. The newly created Internet business might differ from the offline ones in management styles, because it has totally different business circumstances when compared with the existing offline businesses. Thus, there should be a lot of researches for finding the solutions about what the features of Internet business are and how the management style of those Internet business companies should be changed. Most marketing literatures related to the Internet business have focused on individual business markets. Specifically, many researchers have studied the Internet portal sites and the Internet shopping mall sites, which are the most general forms of Internet business. On the other hand, this study focuses on the entire Internet business industry to understand the competitive circumstance of online market. This approach makes it possible not only to have a broader view to comprehend overall e-business industry, but also to understand the differences in competition structures among Internet business markets. We used time-series data of Internet connection rates by consumers as the basic data to figure out the competition patterns in the Internet business markets. Specifically, the data for this research was obtained from one of Internet ranking sites, 'Fian'. The Internet business ranking data is obtained based on web surfing record of some pre-selected sample group where the possibility of double-count for page-views is controlled by method of same IP check. The ranking site offers several data which are very useful for comparison and analysis of competitive sites. The Fian site divides the Internet business areas into 34 area and offers market shares of big 5 sites which are on high rank in each category daily. We collected the daily market share data about Internet sites on each area from April 22, 2008 to August 5, 2008, where some errors of data was found and 30 business area data were finally used for our research after the data purification. This study performed several empirical analyses in focusing on market shares of each site to understand the competition among sites in Internet business of Korea. We tried to perform more statistically precise analysis for looking into business fields with similar competitive structures by applying the cluster analysis to the data. The research results are as follows. First, the leading sites in each area were classified into three groups based on averages and standard deviations of daily market shares. The first group includes the sites with the lowest market shares, which give more increased convenience to consumers by offering the Internet sites as complimentary services for existing offline services. The second group includes sites with medium level of market shares, where the site users are limited to specific small group. The third group includes sites with the highest market shares, which usually require online registration in advance and have difficulty in switching to another site. Second, we analyzed the second place sites in each business area because it may help us understand the competitive power of the strongest competitor against the leading site. The second place sites in each business area were classified into four groups based on averages and standard deviations of daily market shares. The four groups are the sites showing consistent inferiority compared to the leading sites, the sites with relatively high volatility and medium level of shares, the sites with relatively low volatility and medium level of shares, the sites with relatively low volatility and high level of shares whose gaps are not big compared to the leading sites. Except 'web agency' area, these second place sites show relatively stable shares below 0.1 point of standard deviation. Third, we also classified the types of relative strength between leading sites and the second place sites by applying the cluster analysis to the gap values of market shares between two sites. They were also classified into four groups, the sites with the relatively lowest gaps even though the values of standard deviation are various, the sites with under the average level of gaps, the sites with over the average level of gaps, the sites with the relatively higher gaps and lower volatility. Then we also found that while the areas with relatively bigger gap values usually have smaller standard deviation values, the areas with very small differences between the first and the second sites have a wider range of standard deviation values. The practical and theoretical implications of this study are as follows. First, the result of this study might provide the current market participants with the useful information to understand the competitive circumstance of the market and build the effective new business strategy for the market success. Also it might be useful to help new potential companies find a new business area and set up successful competitive strategies. Second, it might help Internet marketing researchers take a macro view of the overall Internet market so that make possible to begin the new studies on overall Internet market beyond individual Internet market studies.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Analytical Science and Technology
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• v.27 no.3
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• pp.172-180
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• 2014

Fenpyrazamine which is a pyrazole fungicide class for controlling gray mold, sclerotinia rot, and Monilinia in grapevines, stone fruit trees, and vegetables has been registered in republic of Korea in 2013 and the maximum residue limits of fenpyrazamine is set to grape, peach, and mandarin as 5.0, 2.0, and 2.0 mg/kg, respectively. Very reliable and sensitive analytical method for determination of fenpyrazamine residues is required for ensuring the food safety in agricultural products. Fenpyrazamine residues in samples were extracted with acetonitrile, partitioned with dichloromethane, and then purified with silica-SPE cartridge and eluted with hexane and acetone mixture. The purified samples were determined by HPLC-UVD and confirmed with LC-MS and quantified using external standard method. Linear range of fenpyrazamine was between $0.1{\sim}5.0{\mu}g/mL$ with the correlation coefficient (r) 0.999. The average recovery ranged from 71.8 to 102.7% at the spiked level of 0.05, 0.5, and 5.0 mg/kg, while the relative standard deviation was between 0.1 and 7.3%. In addition, limit of detection and limit of quantitation were 0.01 and 0.05 mg/L, respectively. The results revealed that the developed and validated analytical method is possible for fenpyrazamine determination in agricultural product samples and will be used as an official analytical method.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.30-36
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• 2017

SS(Suspended Solid) concentration by soil erosion into river at normal and flood season should be measured. However, to present the variation of SS due to various development project such as EIA(Environmental Impact Assessment), River Master Plan, and so on, it is necessary to estimate not measure SS, but there are not exist how to estimate SS. In the present study, therefore, we propose the hydrologic method of estimating SS concentration using the results of particular frequency flood discharge and sediment discharge by RUSLE method. SS consists of silty and clay soil and colloid particle etc. However, in the present study, silty and clay soils of sediment discharge except send set up SS standards. The flow discharge to estimate SS concentration are 1~2 years for normal season, 30~100 years for flood season. Meanwhile, analysis software for probable rainfall uses Fard2006, probable rainfalls under 2-year frequency are estimated using rainfall data and frequency factor of Gumbel distribution. The results of estimating SS concentration using runoff volume by sediment and flow discharges of silty and cray soils as above method show that reliable level of SS concentration is considered in predevelopment of natural condition and under development of barren condition. Especially, SS concentration takes notice that the value of sediment discharge makes a huge difference according to channel slope, it was confirmed that the value obtained by dividing the SS concentration by the channel slope is relatively constant even though the topographical factors are different. Therefore, if the present study will be proceeded for various watersheds, it will be developed as estimation method of SS concentration.

• Journal of Elementary Mathematics Education in Korea
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• v.10 no.1
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• pp.67-87
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• 2006

This study is to recognize a problem in the practice of performance assessment in elementary school, and to find out some suggestive points for improvement of teaching·learning method in elementary mathematics through assessment by reducing time restriction according to assessment through the practice of self-assessment, peer-assessment and observation, and then by reflecting the results of assessment on teaching learning plan. For that, the questions of study set up are as follows ; 1. How should self-assessment and peer-assessment be applied to in elementary mathematics assessment? 2. How should the time for 'let's play an interesting game' be managed for assessment of elementary mathematics? 3. How should the results of assessment be reflected on the Process of teaching and learning of mathematics? To solve these problems, a researcher of this thesis performed self-assessment, peer-assessment on 40 students of second grade under her charge as a class teacher, and applied observation in the time management process for 'let's play an interesting game' for a semester. self-assessment was made by mathematics journal, self-assessment chart, peer-assessment was by the analysis of conversation record among students in the situations of assessment, and observation was by observation of activity when playing with the results data of play analyzed. the concrete methods of application as follows ; First, mathematics journal was applied $1{\sim}2$ times by each unit with reconstruction into the level of second grade on the basis of the preceding-study models. Second, peer-assessment was applied to the unit-assessment time and the play-activities time by the method of recording·analyzing the contents of conversation among students in the process of assessment. Third, mathematical attitude & dispositions of students making use of the self- assessment table were examined referring to the teaching learning plan. Fourth, the time management for 'let's play an interesting game' was made through the prior recognition of play method and the joyful play-activities by use of the play-plate. Assessment depended on analysis of play-activities results of students making use of an observation form. Fifth, the results of self-assessment, peer-assessment, and observation were analyzed, and then they were made use of as self-observation data, of teacher her/his self, or teaching·learning improvement data. Students' self-assessment datum (mathematics diary, self-assessment sheets, conversation contents in the process of assessment) and observation materials (check lists, Play-activity result materials, conversation contents in the process of play) obtained in the process of application was analyzed as follows ; 1. From the practice of self-assessment in form of mathematics journal, I could obtain not only datum showing how much students was understanding the learning aims by unit time and to any degree they reached but also information about their response to learning datum and favorable type of learning. 2. Assessment by self-assessment chart was useful in planning the mathematics teaching learning process because it helps ascertain mathematical attitude & dispositions of students. 3. Through the application of peer-assessment, students had the opportunity of communicating with other students looking back on his/her explaining process, and teachers could obtain basic materials for assessment of students. 4, In case of time management for 'let's play an interesting game', there was natural extension of play made through time-security by prior looking into the method of play-activity, and then, for a remained time, by making children play a new game. 5, I could easily record the activities of students by use of the observation. form, and make use of it as basic data for descriptive assessment. 6, Each kinds of data obtained from the results of assessment was helpful for securing self-observation materials in the process of teaching learning and for their betterment in mathematics subject. However, because they were in the second grade of elementary school and there was an individual difference, some students could not make use of mathematics diary or self-assessment form properly. In case of these students, assessment data would be obtained through interview or observation. And for effective operation of play, its purpose & method and matters that demand special attention when play-acting should be clearly guided. Also, when applying an effective play in addition to play activities in textbook, to lessons, interesting mathematics lessons could be guided.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1784-1792
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• 2007

This study set out to identify the problems with hat labels and to search for improvement measures by examining and analyzing consumers' practice of managing their hats. It also intended to provide accurate and enough information about how to keep and wash hats and thus help consumers use their hats for a long period. In an attempt to investigate how consumers wash and manage their hats, a survey was carried out to 395 individuals in their twenties and over who owned hats living in urban areas including Seoul, and were quota sampled according to age and gender. The survey period is March to April 2007. The collected data were statistically treated with the SPSS 12.0 program in terms of frequency, percentage, mean, standard error, cross tabulation, t-test, and one-way ANOVA. The findings were as followed. First, the respondents were in the average level of perceiving and practicing the washing methods of their hats. The female respondents who had more experiences with laundering than the males knew and practiced the washing methods for hats better than males. Second, compared to other clothing items, hat wearers were more likely to pay careful attention to their hats by putting their hats in a laundry net and applying a laundry detergent for wool fabrics when using a washing machine or washing their hats with their own hands. And third, most of the hat wearers were aware of the importance of hat labels and showed a lower level of trust in them than other clothing items. The suppliers need to offer accurate and practical labels in order to regain the consumers' trust. Many consumers had some difficulties figuring out the size system of hats. In particular, the male consumers had a low level of perception of labels, which implies that there should be specific efforts to educate them about general labels.