• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of Engineering Education Research
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• v.11 no.4
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• pp.11-18
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• 2008

Companies have been making considerable efforts to develop innovative products for better competitiveness in the market, however, the education curriculum for innovative product development (IPD) in domestic universities needs has not been well developed. The present study was intended to identify the needs of students and practitioners regarding teaching subjects, pedagogical methods, and industry-academia collaboration that can be reflected in the development of IPD education curriculum. Through a literature survey 46 IPD teaching subjects of 7 categories (planning, feasibility analysis, concept development, product design, manufacturing process design, production, and ethics & law) were selected. Opinions on the preferences and importances of the teaching subjects, pedagogical methods, and industry-academia collaboration were collected from 53 college students who took courses of product development and 36 practitioners working in product development. While the students preferred the balanced teaching of all the subject categories, the practitioners suggested planning and concept development be taught with high importance; 6 subjects (product development strategy, customer needs identification, market research, concept generation method, design ideation method, and ergonomic design) received high ratings of preference and importance. The students preferred the mix of various pedagogical methods (lecture, discussion, presentation, practice, and case study) and provided needs on each pedagogical method. Lastly, the students wanted an opportunity of learning through industry-academia collaboration and the practitioners provided ideas for mutual benefits between industry and academia. The needs of students and practitioners identified in the study can be effectively applied to develop a better IPD education curriculum.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.15-24
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• 2007

The recognition of postal address images is indispensable for the automatic sorting of postal envelopes. The process of the address image recognition is composed of three steps-address image preprocessing, character recognition, address interpretation. The extracted character images from the preprocessing step are forwarded to the character recognition step, in which multiple candidate characters with reliability scores are obtained for each character image extracted. aracters with reliability scores are obtained for each character image extracted. Utilizing those character candidates with scores, we obtain the final valid address for the input envelope image through the address interpretation step. The envelope sorting rate depends on the performance of all three steps, among which character recognition step could be said to be very important. The good character recognizer would be the one which could produce valid candidates with very reliable scores to help the address interpretation step go easy. In this paper, we propose the method of generating character candidates with reliable recognition scores. We utilize the existing MLP(multilayered perceptrons) neural network of the address recognition system in the current automatic postal envelope sorters, as the classifier for the each image from the preprocessing step. The MLP is well known to be one of the best classifiers in terms of processing speed and recognition rate. The false alarm problem, however, might be occurred in recognition results, which made the address interpretation hard. To make address interpretation easy and improve the envelope sorting rate, we propose promising methods to reestimate the recognition score (confidence) of the existing MLP classifier: the generation method of the statistical recognition properties of the classifier and the method of the combination of the MLP and the subspace classifier which roles as a reestimator of the confidence. To confirm the superiority of the proposed method, we have used the character images of the real postal envelopes from the sorters in the post office. The experimental results show that the proposed method produces high reliability in terms of error and rejection for individual characters and non-characters.

• Journal of the Korean association of regional geographers
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• v.5 no.2
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• pp.1-14
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• 1999

In the course of modernization and globalization, each region in Korea has experienced deep subordination to the center of Seoul and the increase of colonization possibility by world capital. In order to overcome the current situation, above all, the strategies should be developed focusing on daily life and life space. The basis for the development of strategies is the establishment of regional identity on life space. It is because of the reason that life space, or small-scale region has drawn wide attention in the research of geography in recent years. Especially, humanistic geography and new regional geography have developed the concerning theory and methodology, and kept going on the research of small-scale regions. Generally speaking, there have been quite large amount of theoretical discussions on small-scale region in recent years in the field of geography. Empirical researches focusing on a particular small-scale region, however, have been rarely made. It seems related to the deficiency of data materials and the obscurity of research framework of small-scale regional geography. A community paper must be very helpful for the geographic research on small-scale region. As community paper is published based on county('gun'), small or mid-size city('si'), or district of large city('gu'), it deals with small news and daily life information closely attached to the region. Accordingly, it functions as a medium of the formation of regional identity. It is also a valuable source material for the validation of regional identity and for the analysis of identity-shaping mechanism. The geographic interests in community paper, first of all, should be taken shape by the work on the geographical distribution and the periodic change of publication situation of community papers in Korea. Another research subject on community paper is the examination of characteristics of the region by analyzing the news and the advertisements. The news in community paper must be a valuable data source of regional studies in geography. Also, the regional identification process of community people through the community paper could be and should be explored, and how the regional centrality, or self-generation based on the identity is achieved will be an important subject.

• Journal of Korean Society of Forest Science
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• v.86 no.1
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• pp.69-79
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• 1997

The purpose of this study is to acquire essential data to reduce the amount of woody debris resulted from the debris flow. This research examined topographic characteristics of the channelbed affecting generation, movement and storage of woody debris and woody characteristics related to number, sizes, shapes, decay, storage direction to mountainous stream. 1. The number of woody debris had a tendency to increase in proportion to stream width, but it was hardly affected by longitudinal gradient of stream. Especially, the greater amount of woody debris was stored at wide section of the stream with compound channel, and it was found in deposits of channelbed rather than in the present channel. 2. Total woody debris over 10cm in diameter and over 2m in length was 402 units and storage number was 35.3 units per 100m of stream. Average diameter of breast height and length were 14cm and 4m, respectively. The woody debris appeared shorter in length and greater in diameter at down-stream than up-stream. 3. Since woody debris met sediments and bed-materials of great roughness in moving, the greater amount of woody debris without root was found in up-stream and down-stream, but deformed woody debris was discovered in upper stream. Decay of woody debris was more severe in down-stream and woody debris on rotting process was found down-stream. 4. Storage direction of woody debris was mainly parallel to center line of stream, and rate of parallel and perpendicularity was 276 and 126 units, respectively. But, as woody debris storing to the perpendicular direction was unstable, the traveling debris could easily be stored. Therefore, some counterplan was required to prevent the traveling woody debris. 5. Tree species of woody debris was mainly larch, which occupied about two third of total woody debris(256 units). The woody debris of larch is easy to move due to hitting of channelbed materials or lower channelbed fluctuation because the lower part of larch is weaker than its upper part. Therefore, the section of the tree species planting in the riparian vegetation needs much more carefulness.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Tuberculosis and Respiratory Diseases
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• v.43 no.2
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• pp.210-220
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• 1996

Background : Neutrophils or monocytes separated in vitro by the adherence to plastic surface are known to be activated by surface adherence itself and subsequent experimental data might be altered by surface adherence. In the process of surface adherence, adhesion molecules have a clear role in intracellular signal pathway of cellular activation. Human alveolar macrophages(HAM) are frequently purified by the adherence procedure after bronchoalveolar lavage. But the experimental data of many reports about alveolar macrophages have ignored the possibility of adhesion-induced cellular activation. Method : Bronchoalveolar lavage was performed in the person whose lung of either side was confirmed to be normal by chest CT. With the measurement of hydrogen peroxide release from adherent HAM to plastic surface and non-adherent HAM with or without additional stimulation of phorbol myristate acetate(PMA) or N-formyl-methionyl-leucyl-phenylalanine (fMLP), we observed the effect of the adherence to plastic surface. We also evaluated the effect of various biological surfaces on adhesion-induced activation of HAM. Then, to define the intracellular pathway of signal transduction, pretreatment with cycloheximide, pertussis toxin and anti-CD11/CD18 monoclonal antibody was done and we measured hydrogen peroxide in the culture supernatant of HAM. Results : 1) The adherence itself to plastic surface directly stimulated hydrogen peroxide release from human alveolar macrophages and chemical stimuli such as phorbol myristate acetate(PMA) or N-formyl-methionyl-leucyl-phenylalanine(fMLP) colud not increase hydrogen peroxide release in these adherent macrophages which is already activated. 2) PMA activated human alveolar macrophages irrespective of the state of adhesion. However, fMLP stimulated the release of hydrogen peroxide from the adherent macrophages, but not from the non-adherent macrophages. 3) HAM adherent to A549 cell(type II alveolar epithelium-like human cell line) monolayer released more hydrogen peroxide in response to both PMA and fMLP. This adherence-dependent effect of fMLP was blocked by pretreatment of macrophages with cycloheximide, pertussis toxin and anti-CD18 monoclonal antibody, Conclusion : These results suggest that the stimulatory effect of PMA and fMLP can not be found in adherent macrophage because of the activation of human alveolar macrophage by the adherence to plastic surface and the cells adhered to biologic surface such as alveolar epithelial cells are appropriately responsive to these stimuli. It is also likely that the effect of fMLP on the adherent macrophage requires new protein synthesis via G protein pathway and is dependent on the adhesion between alveolar macrophages and alveolar epithelial cells by virtue of CD11/CD18 adhesion molecules.

• Journal of the Korean Vacuum Society
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• v.18 no.1
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• pp.66-72
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• 2009

The detection methods are required to monitor and diagnose the abnormality on the insulation condition inside a gas-insulated switchgear (GIS). Due to a good sensitivity to the products decomposed by partial discharges (PDs) in $SF_6$ gas, the development of a SWNT gas sensor is actively in progress. However, a few numerical studies on the diffusion mechanism of the $SF_6$ decomposition products by PD have been reported. In this study, we modeled $SF_6$ decomposition process in a chamber by calculating temperature, pressure and concentration of the decomposition products by using a commercial CFD program in conjunction with experimental data. It was assumed that the mass production rate and the generation temperature of the decomposition products were $5.04{\times}10^{-10}$ [g/s] and over 773 K respectively. To calculate the concentration equation, the Schmidt number was specified to get the diffusion coefficient functioned by viscosity and density of $SF_6$ gas instead rather than setting it directly. The results showed that the drive potential is governed mainly by the gradient of the decomposition concentration. A lower concentration of the decomposition products was observed as the sensors were placed more away from the discharge region. Also, the concentration increased by increasing the discharge time. By installing multiple sensors the location of PD is expected to be identified by monitoring the response time of the sensors, and the information should be very useful for the diagnosis and maintenance of GIS.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.