• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.239-248
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• 2010

This paper describes a collaborative project between academia and industry which focused on improving the marketing and product development strategies for two private label apparel brands of a large regional department store chain in the southeastern United States. The goal of the project was to revitalize product lines of the two brands by incorporating student ideas for new solutions, thereby giving the students practical experience with a real-life industry situation. There were a number of key players involved in the project. A privately-owned department store chain based in the southeastern United States which was seeking an academic partner had recognized a need to update two existing private label brands. They targeted middle-aged consumers looking for casual, moderately priced merchandise. The company was seeking to change direction with both packaging and presentation, and possibly product design. The branding and product development divisions of the company contacted professors in an academic department of a large southeastern state university. Two of the professors agreed that the task would be a good fit for their classes - one was a junior-level Intermediate Brand Management class; the other was a senior-level Fashion Product Development class. The professors felt that by working collaboratively on the project, students would be exposed to a real world scenario, within the security of an academic learning environment. Collaboration within an interdisciplinary team has the advantage of providing experiences and resources beyond the capabilities of a single student and adds "brainpower" to problem-solving processes (Lowman 2000). This goal of improving the capabilities of students directed the instructors in each class to form interdisciplinary teams between the Branding and Product Development classes. In addition, many universities are employing industry partnerships in research and teaching, where collaboration within temporal (semester) and physical (classroom/lab) constraints help to increase students' knowledge and experience of a real-world situation. At the University of Tennessee, the Center of Industrial Services and UT-Knoxville's College of Engineering worked with a company to develop design improvements in its U.S. operations. In this study, Because should be lower case b with a private label retail brand, Wickett, Gaskill and Damhorst's (1999) revised Retail Apparel Product Development Model was used by the product development and brand management teams. This framework was chosen because it addresses apparel product development from the concept to the retail stage. Two classes were involved in this project: a junior level Brand Management class and a senior level Fashion Product Development class. Seven teams were formed which included four students from Brand Management and two students from Product Development. The classes were taught the same semester, but not at the same time. At the beginning of the semester, each class was introduced to the industry partner and given the problem. Half the teams were assigned to the men's brand and half to the women's brand. The teams were responsible for devising approaches to the problem, formulating a timeline for their work, staying in touch with industry representatives and making sure that each member of the team contributed in a positive way. The objective for the teams was to plan, develop, and present a product line using merchandising processes (following the Wickett, Gaskill and Damhorst model) and develop new branding strategies for the proposed lines. The teams performed trend, color, fabrication and target market research; developed sketches for a line; edited the sketches and presented their line plans; wrote specifications; fitted prototypes on fit models, and developed final production samples for presentation to industry. The branding students developed a SWOT analysis, a Brand Measurement report, a mind-map for the brands and a fully integrated Marketing Report which was presented alongside the ideas for the new lines. In future if the opportunity arises to work in this collaborative way with an existing company who wishes to look both at branding and product development strategies, classes will be scheduled at the same time so that students have more time to meet and discuss timelines and assigned tasks. As it was, student groups had to meet outside of each class time and this proved to be a challenging though not uncommon part of teamwork (Pfaff and Huddleston, 2003). Although the logistics of this exercise were time-consuming to set up and administer, professors felt that the benefits to students were multiple. The most important benefit, according to student feedback from both classes, was the opportunity to work with industry professionals, follow their process, and see the results of their work evaluated by the people who made the decisions at the company level. Faculty members were grateful to have a "real-world" case to work with in the classroom to provide focus. Creative ideas and strategies were traded as plans were made, extending and strengthening the departmental links be tween the branding and product development areas. By working not only with students coming from a different knowledge base, but also having to keep in contact with the industry partner and follow the framework and timeline of industry practice, student teams were challenged to produce excellent and innovative work under new circumstances. Working on the product development and branding for "real-life" brands that are struggling gave students an opportunity to see how closely their coursework ties in with the real-world and how creativity, collaboration and flexibility are necessary components of both the design and business aspects of company operations. Industry personnel were impressed by (a) the level and depth of knowledge and execution in the student projects, and (b) the creativity of new ideas for the brands.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.489-499
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• 2012

In this paper, a classifier ensemble framework for remote sensing data classification is presented that combines classification results generated from both different training sets and different classifiers. A core part of the presented framework is to increase a diversity between classification results by using both different training sets and classifiers to improve classification accuracy. First, different training sets that have different sampling densities are generated and used as inputs for supervised classification using different classifiers that show different discrimination capabilities. Then several preliminary classification results are combined via a majority voting scheme to generate a final classification result. A case study of land-cover classification using multi-temporal ENVISAT ASAR data sets is carried out to illustrate the potential of the presented classification framework. In the case study, nine classification results were combined that were generated by using three different training sets and three different classifiers including maximum likelihood classifier, multi-layer perceptron classifier, and support vector machine. The case study results showed that complementary information on the discrimination of land-cover classes of interest would be extracted within the proposed framework and the best classification accuracy was obtained. When comparing different combinations, to combine any classification results where the diversity of the classifiers is not great didn't show an improvement of classification accuracy. Thus, it is recommended to ensure the greater diversity between classifiers in the design of multiple classifier systems.

• Journal of Distribution Science
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• v.11 no.6
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• pp.41-50
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• 2013

Purpose - Inducing consumers' behavioral intent to use an outlet shopping center is a critical issue for managers since it can be used as a guide for developing marketing strategies. Low prices could lead to a growth in retail purchases, but there might also be a positive relationship between prices and customer perceptions of product quality. The extent to which consumers use price as a predictor of quality may differ according to the availability of important alternative cues such as brand, store name, and identity salience triggered by the store. Consumers can obtain non-economic benefits from marketing exchanges that go beyond basic economic achievement. We argue that identity salience can play a crucial mediating role when consumers, acting as exchange partners, seek to obtain social benefits. This study shows that identity salience could mediate the relationship between identity salience-inducing factors such as multi-finality, prestige and role performance, and consumers' behavioral intent to use an outlet shopping center. Research design, data and methodology - The survey was conducted on college students enrolled in marketing classes. A total of 200 questionnaires were distributed, of which only 194 were returned. After five incomplete questionnaires were excluded, a final sample of 189 was used for empirical analysis. Using a covariance structural analysis in Amos17, we confirmed the fit of the research model and estimated its parameters by using the maximum likelihood method. Results - The results of the hypotheses testing are as follows. First, both identity salience and economic benefits have positive effects on the behavioral intent to use an outlet shopping center. Second, role performance, prestige, and multi-finality have positive effects on identity salience. Finally, the additive analysis of the direct effects of identity salience-inducing factors shows that the role performance, prestige, and multi-finality factors have no direct effects on the behavioral intent to use an outlet shopping center, suggesting that identity salience plays a positive mediating role. Conclusions - This study informs marketers that not only price but shoppers' identity salience directly affects their intent to visit an outlet shopping center. To strengthen shoppers' identity salience, marketers should find ways to help shoppers fulfill their multiple social roles, realize their multiple goals, and achieve prestige. In other words, outlet shopping centers must improve their personal service environment in order to enhance their employees' service quality and assist the execution of multi-finality by minimizing the perceived costs (e.g., travel time, effort) associated with shopping trips, thus making it easier for consumers to combine visits to multiple stores in outlet shopping centers and buy the items required for their consumption goals. Outlet shopping centers must also offer assortments with both breadth and depth in order to help consumers play the social roles their social networks have given them.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.21-28
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• 2010

This paper reports an experimental result on optimizing dissimilarity-based classification(DBC) by simultaneously using a dynamic time warping(DTW) and a multiple fusion strategy(MFS). DBC is a way of defining classifiers among classes; they are not based on the feature measurements of individual samples, but rather on a suitable dissimilarity measure among the samples. In DTW, the dissimilarity is measured in two steps: first, we adjust the object samples by finding the best warping path with a correlation coefficient-based DTW technique. We then compute the dissimilarity distance between the adjusted objects with conventional measures. In MFS, fusion strategies are repeatedly used in generating dissimilarity matrices as well as in designing classifiers: we first combine the dissimilarity matrices obtained with the DTW technique to a new matrix. After training some base classifiers in the new matrix, we again combine the results of the base classifiers. Our experimental results for well-known benchmark databases demonstrate that the proposed mechanism achieves further improved results in terms of classification accuracy compared with the previous approaches. From this consideration, the method could also be applied to other high-dimensional tasks, such as multimedia information retrieval.

• Journal of the Korean Society of Earth Science Education
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• v.11 no.2
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• pp.125-144
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• 2018

The purpose of this study is to analyze the astronomical thinking level of elementary, middle, and high school students using ordered multiple choice items. For this purpose, we constructed a questionnaire comprising three items about spatial thinking and system thinking. This survey was conducted and applied to 1,066 students in the 5th grade, 8th grade, and 11th grade in 12 schools located in Gangwon Province. The collected student response data were analyzed by applying inferential statistics of classical test theory and Rasch model. The results of the analysis were as follows; First, in the level of spatial thinking, students were able to grasp the spatial location and orientation of the celestial body, but were not able to convert the celestial motion of two-dimensional plane into three-dimensional plane, and it was revealed that there is no statistically significant difference in the spatial thinking of students among grade levels. Second, in the level of system thinking, students were able to identify the components and relationship between components of the celestial motion system, but could not identify the patterns of the system, and it was revealed that there was statistically significant difference among the system thinking of students in different grade levels, unlike in spatial thinking. Third, the astronomical thinking expressed in certain context (content) was very similar regardless of grade level, Through this, we could confirm the context-dependency or content-dependency of the astronomical thinking of students. It is expected that the results of this study can be used as basic data for exploring ways to enhance astronomical thinking level in school science classes.

• Journal of Korean Elementary Science Education
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• v.20 no.2
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• pp.239-254
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• 2001

The in-depth learning course newly established in the 7th National Curriculum of Science is for students who have mastered regular subject matters on a science topic and want to learn it more deeply or by different ways. Individual learners have their own unique intellectual properties. The study examined the effects of in-depth science learning using multiple intelligence activities on the science inquiry abilities and interests of elementary school children. This study involved two fifth-grade science classes in Busan. Each class was assigned to comparison and experimental group. The science topics covered during the period of the study were Units of Matter and Earth. After studying each regular content formulated by the National Curriculum, the students of comparison group experienced traditional practices of in-depth science, whereas those of experimental one performed the Multiple Intelligence(MI) activities related to the content. Students of both groups were pre- and posttested using the inventories of Science Inquiry Ability and Science Interest. Also, after instruction on the topics, students were interviewed to collect more information related to their loaming. The results are as follows. First, the science inquiry abilities of children were increased by using activities based on MI during the in-depth science teaming. Two inquiry processes, that is, the Prediction which is regarded as one of the basic process skills in science and the Generalization regarded as one of integrated process skills showed statistically significant differences between the groups, although the differences of other skills not significant but more improvements in experimental group than comparison one. Second, the in-depth science loaming through MI contributed to the increasing of interests of the children in science. The scores on Science Interest measured in pretest and posttest with the two groups showed st statistically significant difference. For interest in science instruction, children of experimental group showed high level of interest for the various MI activities, and, although the comparison groups' level of the interest was low, they revealed that they want to experience the MI activities in future instruction of science. Interviews with the children randomly selected from the experimental group when they completed the in-depth programs showed that most of them had much interest in MI activities. Especially, they attributed significant meanings to the experiences of teaming with their friends and doing activities that they want to do. These findings have important implications about usefulness of MI in science instruction. The results also highlight the need for science teachers to provide a variety of experiences and to create environments which encourage the children to use MI to learn a science topic.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.9
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• pp.293-300
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• 2014

TDMA(Time Division Multiple Access) is a channel access scheme for shared medium networks. The shared frequency is divided into multiple time slots, some of which are assigned to a user for communication. Techniques for TDMA can be categorized into two classes: synchronous and asynchronous. Synchronization is not suitable for small scale networks because it is complicated and requires additional equipments. In contrast, in DESYNC, a biologically-inspired algorithm, the synchronization can be easily achieved without a global clock or other infrastructure overhead. However, DESYNC spends a great deal of time to complete synchronization and does not guarantee the maximum time to synch completion. In this paper, we propose a lightweight synchronization scheme, C-DESYNC, which counts the number of participating nodes with GP (Global Packet) signal including the information about the starting time of a period. The proposed algorithm is mush simpler than the existing synchronization TDMA techniques in terms of cost-effective method and guarantees the maximum time to synch completion. Our simulation results show that C-DESYNC guarantees the completion of the synchronization process within only 3 periods regardless of the number of nodes.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1975-1984
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• 2021

Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

• Journal of the Korean Society for information Management
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• v.35 no.4
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• pp.141-164
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• 2018

Recently, as the amount of academic literature has increased rapidly and complex researches have been actively conducted, researchers have difficulty in analyzing trends in previous research. In order to solve this problem, it is necessary to classify information in units of academic papers. However, in Korea, there is no academic database in which such information is provided. In this paper, we propose an automatic classification system that can classify domestic academic literature into multiple classes. To this end, first, academic documents in the technical science field described in Korean were collected and mapped according to class 600 of the DDC by using K-Means clustering technique to construct a learning set capable of multiple classification. As a result of the construction of the training set, 63,915 documents in the Korean technical science field were established except for the values in which metadata does not exist. Using this training set, we implemented and learned the automatic classification engine of academic documents based on deep learning. Experimental results obtained by hand-built experimental set-up showed 78.32% accuracy and 72.45% F1 performance for multiple classification.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.