The purpose of this study was to investigate parents' perception and satisfaction of school food materials and supplier performance in Mokpo. To achieve these research objectives, a questionnaire was distributed to parents at 66 schools, and a total of 589 were used in the final analysis. The results of this study were as follows. First, satisfaction of school foodservice, showed the following scores: overall was 3.75, quality of food materials was 3.84, reliability of food suppliers was 3.80, education was 3.53, and information was 3.50. Second, 38.5% of parents participated in receiving school materials. Exactly 80.6% of parents showed intentions to participate. The most difficult thing for receiving materials was comparing quality of food materials (46.3%). Third, the most important factor cited for school food supplier was quality (62.3%) and sanitation and safety (24.1%). Forth, most parents were positive about the possibility of replacing foods used at school with environment friendly products. Local foods were cited for use in school foodservice (92.2%). The reasons were good quality (39.9%) and contribution to the local community (28.5%). In conclusion, parent's perception of school foodservice should increase to improve food material quality of school foodservice. Institutions for certifying are needed to offer high quality food materials at school foodservice and improved communication and education tool between the school and parents.
Nitrogen fertilization and cutting practice were studied on turfgrasses and cover plants to investigate the possibility of maintaining green color during the growing season. Research also involved the effect of the nitrogen on a few morphological characteristics of leaf performance elements which might give an information to coloration and life-span of turf leaves. Treatments in the first experiment undertaken on pot included one N level: 350kgN /ha applied as compound fertilizer in split applications of one-half in mid-May and the rest both in late June and August, and four spring-summer cuts: late May, late June, late July and late August. The soil filled in pot a moderately well-drained sandy loam. In the second experiment(field observation) leaf length and width, inflorescence and flowering, and color performance were also investigated. With nitrogen fertilizer applied on turfs, desirable turf color was maintained during a period of poor coloration in specific seasons such as mid-summer for cool season grasses and late fall for warm season grasses comparing to the non-treatment. However, this was not stimulated by cutting treatment to nitrogen status existed. Cutting effect on coloration was more remarkable in both Korean lawngrass and Manilagrass than in cool season turfgrasses such as Italian rye-grass, perennial ryegrass and tall fescue. Especially down-slide of leaf color in cool season turfgrasses could he detected in mid-summer /early fall season ranging up to mid-September. In early November as well as mid-September, Italian ryegrass, perennial ryegrass and tall fes-cue retained a high level of green color as followed by nitrogen application and cutting treatment, and little detectable variation of leaf color notation between cool season turfgrasses was obtained. However, Korean la'vngrass and Manilagrass failed to retain the green color until early November. Color notations in cool season turfgrasses investigated early November on the final date of the experiment ranged from 5 GY 3/1 to 4/8 in 'Ramultra' Italian ryegrass, 'Reveile' perennial ryegrass and 'Arid' tall fescue, but those in Zoysiagrasses were 7.5 YR 4/8 in Korean lawngrass and 2.5 y 5 /6 in Manilagrass. Life-span of leaves was shorter in Italian ryegrass, perennial ryegrass and tall fescue than in beth Korean lawngrass and Manilagrass with and without nitrogen application. In general, leaves appeared in early May had a long life-span than those appeared in late April or mid-June. Nitrogen application significantly prolonged the green color retaining period in perennial ryegrass, Italian ryegrass, Korean lawngrass and Manilagrass, and this was contrasted with the fact that there was no prolonged life-span of leaves emerging in early May and mid-June in tall fescue. SPAD reading values in 48 turfs and cover plants investigated in the field trial were increasing until late June and again decreasing till September. Increasing trends of reading value could be observed in the middle of October in most of grasses. On the other hand, clovers and reed canarygrasses did not restore their color values even in October. Color differences between inter-varieties, and inter-species occurred during the growing season under the field condition implicated that selection of species and /or cultivars for mixture should be taken into consideration. In Munsell color notation investigated in the final date in the middle of November, 32 cultivars belonged under the category of 5 GY and 10 cultivars under the category of 7.5 GY. This was implying that most of cool season turfs and cover plants grown in the center zone of Korean Peninsula which are able to utilize for landscape use can bear their reasonable green color by early or mid-November when properly managed. The applicable possibilities of SPAD readings and Munsell color notation to determine the color status of turfgrasses and cover plants used in this study were discussed.
Manjungpan Chunhyangga is established by Manjung Kim Sohee. She selectively chose and arranged the songs by Jung Jungryeol, Song Mangap, Jung Eungmin, Kim Yeonsoo, Park Dongsil, and Jung Kwangsil. Kim Sohee once stated that while a major section of Chunhyangga is based on the songs by Jung Jungryeol, Song Mangap, Jung Eungmin, and Kim Yeonsoo, the whole part of Okjungga is derived from Park Dongsil. However, there is not much material that will provide enough information with regard to what musical characteristics Park Dongsilje Chunhyangga possessed. Under the circumstances, the voice of Park Dongsilje, left by Kim Sohee, triggers curiosity on Park Dongsilje Chunhyangga. It can also be construed that there must be a good reason for choosing Park Dongsilje for Okjungga, unlike other parts. Therefore, this paper attempted to find out what the unique features of Par Dongsilje are and what the reasons behind Kim Sohee's musical choice were through comparison and analysis of Kim Sohee's musical features in Okjungga. The following are the results. Firstly, Okjungga is a created verse by its nature and it does not possess specific features to a school. Therefore, the reason for choosing Park Dongsilje could have been based on musical reason rather than verse. Secondly, the lyrics of Park Dongsilje Okjungga is closer to that of Song Mangap rather than that of Jung Jungryeolje. It can be argued that it falls between the two of them. Thirdly, the tone and melody of Park Dongsilje Okjungga falls in the middle section of Dongpyenje and Supyenje. Fourthly, the analysis of Jinyangjo rhythm out of the whole Manjungpan Chunhyangga shows that there are slight differences among Song Mangapje, Jung Jungryeolje, and Jung Eungminje. Park Dongsilje is very unique in the sense that it does not use utbutim in gyemyeonjo part in Manjungpan Chunhyangga. Park Dongsilje Okjungga is a song to which the tone, melody, and sigimsae of Supyeonje is added to lyric butimsae of Dongpyeonje. It can be seemed as simple and less sophisticated because, with its simple lyric butimsae, it shows a less complicated tone utilization rather than Jung Jungryeol. With lighter decoration of music, feelings can be conveyed more directly. That is probably why Kim Sohee commented on Park Dongsilje Chunhyangga that it is the most mournful song for Chunhyang and it is the song that moves anyone who listens to the song. Consequently, Kim Sohee accepted Park Dongsilje Okjungga and she created different feelings to Manjungpan Chunhyangga which has repeatedly displayed the color of Jung Jungryeol. Combining the lyric addition of Dongpyeon style and the melody of Supyeon style can crated a different language.
Pansori of a creative group pansori 2006 demonstration factory floor sound brutal sorigeuk the home of
Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.
An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.
As the population, buying power, and intensity of self-expression of the elderly generation increase, its importance as a market segment is also growing. Therefore, the mass marketing strategy for the elderly generation must be changed to a micro-marketing strategy based on the results of sub-segmentation that suitably captures the characteristics of this generation. Furthermore, as a customer access strategy is decided by sub-segmentation, proper segmentation is one of the key success factors for micro-marketing. Segments or sub-segments are different from sectors, because segmentation or sub-segmentation for micro-marketing is based on the homogeneity of customer needs. Theoretically, complete segmentation would reveal a single voice. However, it is impossible to achieve complete segmentation because of economic factors, factors that affect effectiveness, etc. To obtain a single voice from a segment, we sometimes need to divide it into many individual cases. In such a case, there would be a many segments to deal with. On the other hand, to maximize market access performance, fewer segments are preferred. In this paper, we use the term "sub-segmentation" instead of "segmentation," because we divide a specific segment into more detailed segments. To sub-segment the elderly generation, this paper takes their lifestyles and life stages into consideration. In order to reflect these aspects, various surveys and several rounds of expert interviews and focused group interviews (FGIs) were performed. Using the results of these qualitative surveys, we can define six sub-segments of the elderly generation. This paper uses five rules to divide the elderly generation. The five rules are (1) mutually exclusive and collectively exhaustive (MECE) sub-segmentation, (2) important life stages, (3) notable lifestyles, (4) minimum number of and easy classifiable sub-segments, and (5) significant difference in voices among the sub-segments. The most critical point for dividing the elderly market is whether children are married. The other points are source of income, gender, and occupation. In this paper, the elderly market is divided into six sub-segments. As mentioned, the number of sub-segments is a very key point for a successful marketing approach. Too many sub-segments would lead to narrow substantiality or lack of actionability. On the other hand, too few sub-segments would have no effects. Therefore, the creation of the optimum number of sub-segments is a critical problem faced by marketers. This paper presents a method of evaluating the fitness of sub-segments that was deduced from the preceding surveys. The presented method uses the degree of homogeneity (DoH) to measure the adequacy of sub-segments. This measure uses quantitative survey questions to calculate adequacy. The ratio of significantly homogeneous questions to the total numbers of survey questions indicates the DoH. A significantly homogeneous question is defined as a question in which one case is selected significantly more often than others. To show whether a case is selected significantly more often than others, we use a hypothesis test. In this case, the null hypothesis (H0) would be that there is no significant difference between the selection of one case and that of the others. Thus, the total number of significantly homogeneous questions is the total number of cases in which the null hypothesis is rejected. To calculate the DoH, we conducted a quantitative survey (total sample size was 400, 60 questions, 4~5 cases for each question). The sample size of the first sub-segment-has no unmarried offspring and earns a living independently-is 113. The sample size of the second sub-segment-has no unmarried offspring and is economically supported by its offspring-is 57. The sample size of the third sub-segment-has unmarried offspring and is employed and male-is 70. The sample size of the fourth sub-segment-has unmarried offspring and is not employed and male-is 45. The sample size of the fifth sub-segment-has unmarried offspring and is female and employed (either the female herself or her husband)-is 63. The sample size of the last sub-segment-has unmarried offspring and is female and not employed (not even the husband)-is 52. Statistically, the sample size of each sub-segment is sufficiently large. Therefore, we use the z-test for testing hypotheses. When the significance level is 0.05, the DoHs of the six sub-segments are 1.00, 0.95, 0.95, 0.87, 0.93, and 1.00, respectively. When the significance level is 0.01, the DoHs of the six sub-segments are 0.95, 0.87, 0.85, 0.80, 0.88, and 0.87, respectively. These results show that the first sub-segment is the most homogeneous category, while the fourth has more variety in terms of its needs. If the sample size is sufficiently large, more segmentation would be better in a given sub-segment. However, as the fourth sub-segment is smaller than the others, more detailed segmentation is not proceeded. A very critical point for a successful micro-marketing strategy is measuring the fit of a sub-segment. However, until now, there have been no robust rules for measuring fit. This paper presents a method of evaluating the fit of sub-segments. This method will be very helpful for deciding the adequacy of sub-segmentation. However, it has some limitations that prevent it from being robust. These limitations include the following: (1) the method is restricted to only quantitative questions; (2) the type of questions that must be involved in calculation pose difficulties; (3) DoH values depend on content formation. Despite these limitations, this paper has presented a useful method for conducting adequate sub-segmentation. We believe that the present method can be applied widely in many areas. Furthermore, the results of the sub-segmentation of the elderly generation can serve as a reference for mature marketing.
As so many marketers get to use diverse sales promotion methods, manufacturer and retailer in a channel often use them too. In this context, diverse issues on sales promotion management arise. One of them is the issue of unplanned buying. Consumers' unplanned buying is clearly better off for the retailer but not for manufacturer. This asymmetric influence of unplanned buying should be dealt with prudently because of its possibility of provocation of channel conflict. However, there have been scarce studies on the sales promotion management strategy considering the unplanned buying and its asymmetric effect on retailer and manufacturer. In this paper, we try to find a better way for a manufacturer in a channel to promote performance through the retailer's sales promotion efforts when there is potential of unplanned buying effect. We investigate via game-theoretic modeling what is the optimal cost sharing level between the manufacturer and retailer when there is unplanned buying effect. We investigated following issues about the topic as follows: (1) What structure of cost sharing mechanism should the manufacturer and retailer in a channel choose when unplanned buying effect is strong (or weak)? (2) How much payoff could the manufacturer and retailer in a channel get when unplanned buying effect is strong (or weak)? We focus on the impact of unplanned buying effect on the optimal cost sharing mechanism for sales promotions between a manufacturer and a retailer in a same channel. So we consider two players in the game, a manufacturer and a retailer who are interacting in a same distribution channel. The model is of complete information game type. In the model, the manufacturer is the Stackelberg leader and the retailer is the follower. Variables in the model are as following table. Manufacturer's objective function in the basic game is as follows:
Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70