• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.312-318
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• 2018

We investigated the effect of postharvest treatments of calcium chloride, lysophosphatidyl ethanolamine (LPE) or 1-methylcyclopropene (1-MCP) on fruit quality during simulated marketing in Asian pear (Pyrus pyrifolia Nakai). 'Whangkeumbae' pear fruits were immersed in 0.25, 0.5 or 1.0% $CaCl_2$ solution with or without ultrasound (40kHz) at $25^{\circ}C$ for 3min followed by storage at $1^{\circ}C$ for 30 days simulated as abroad exportation. After simulated marketing at $25^{\circ}C$ and 80% relative humidity (RH) up for 10 days, quality parameters were evaluated. Results indicated that the ultrasound and $CaCl_2$ treatment had a synergic effect on keeping the green skin color which showed lower $a^*$ value. The combination treatment of ultrasound and 0.5% and 1.0% $CaCl_2$ significantly reduced internal browning disorders, although severe skin blemish disorder (20-23%) occurred in 1.0% $CaCl_2$ treatment. 'Wonhwang' pears were immersed in 1,000ppm LPE for 3 minutes or were fumigated in 1,000 ppb 1-MCP for 12 hours, respectively. The results of the fruit quality survey during the 21 days of distribution period are as follows. The 1-MCP treatment was maintained at a constant flesh firmness of 33N or higher during the distribution period. The LPE treated fruits had a lower physiological disorder index than the untreated group, but showed a relatively higher value than the 1-MCP treated group. In the case of 1-MCP treatment, the fruit respiration rate was significantly lower than of untreated control ($6.0mL{\cdot}kg^{-1}{\cdot}hr^{-1}$) during the simulaed marketing period. Consequently, it was expected that the postharvest treatments of 0.5% calcium chloride in pararell with ultrasound and 1-MCP fumigation can help to maintain Asian pear quality during distribution period.

• Progress in Medical Physics
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• v.24 no.4
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• pp.315-322
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• 2013

The aim of this work is to verify the self-quality assurances in medical institutions in Korea through the external audits by the group of experts and have a mutual discussion of the systematic problems. In order to validate the external audits 30 of 80 medical institutions across the nation were picked out considering the regional distribution and the final 25 institutions applied voluntarily to take part in this work. The basic rules were setup that any information of the participants be kept secrete and the measurements be performed with the dosimetry system already verified through intercomparision. The outputs for 2 or more photon beams, the accuracy of gantry rotation and collimator rotation and the poistional accuracy of MLC movement were measured. The findings for the output measurement showed the differences of -0.8%~4.5%, -0.79%~3.01%, and -0.7%~0.07% with respect to that of the verified dosimetry system for the 6MV, 10MV, and 15MV, respectively. For the reference absorbed dose 8 (16%) of 50 photon beams in 25 medical institutions differed 2.0% or greater from the reference value. The coincidences of Field size with x-ray beam and radiation isocenters of Gantry roration and collimator rotation gave the results of within ${\pm}2$ mm for every institute except 2 institutions. The positional accuracy of MLC movement agreed to within ${\pm}1$ mm for every institute. For the beam qualities of 6 MV photon beams kQ values showed the distribution within 0.4% between maximum and minimum. For the protocols 21 institutions (84%) used absorbed dose to water based protocol while 4 insitutions (16%) used air kerma based one. 22 institutions employed the SSD technique while 3 institutions did the SAD one. External audit plays an important role in discovering the systematic problems of self-performing Quality Assurances and having in depth discussion for mutual complementation. Training experts of international level as well as national support system are required so that both the group of experts of medical physicists and government laboratory could perform together periodical and constant external audits.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.2
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• pp.144-150
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• 2010

The agricultural techniques of environmental friendly using the green manure crops have been required recently more to have the safety agricultural products and to reduce the use of fertilizers and agricultural chemicals. The utilization of green manure crops related closely to cropping system would be very important. The purposes of this study are both to investigate the effects of green manure crops of hairy vetch, legume, and rye, gramineae, and to compare the effects between them in rice cultivation. The hairy vetch and rye were treated as green manure crops into paddy soil at 10 days before the rice transplanting. The plant height was increased gradually from the maximum tillering to the heading growth stage, showing that it was the highest with treatment of conventional cultivation in 2007 and the highest with hairy vetch in 2008. The number of tillers was higher with treatment of hairy vetch and hairy vetch+rye than those with the conventional cultivation. Dry weight was also higher with hairy vetch than that with the conventional, while it was lower clearly in rye than those in hairy vetch and conventional. According to the high tilller number and spikelet number per panicle out of the yield components relatively, the yield of rough rice was increased to about 6% and 8% in 2007 and 2008, respectively, comparing with the yield in the conventional cultivation. Based on these results, the hairy vetch would be a good green manure crop in rice cultivation.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.83-98
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• 2015

Many TV viewers use mainly portal sites in order to retrieve information related to broadcast while watching TV. However retrieving information that people wanted needs a lot of time to retrieve the information because current internet presents too much information which is not required. Consequentially, this process can't satisfy users who want to consume information immediately. Interactive video is being actively investigated to solve this problem. An interactive video provides clickable objects, areas or hotspots to interact with users. When users click object on the interactive video, they can see additional information, related to video, instantly. The following shows the three basic procedures to make an interactive video using interactive video authoring tool: (1) Create an augmented object; (2) Set an object's area and time to be displayed on the video; (3) Set an interactive action which is related to pages or hyperlink; However users who use existing authoring tools such as Popcorn Maker and Zentrick spend a lot of time in step (2). If users use wireWAX then they can save sufficient time to set object's location and time to be displayed because wireWAX uses vision based annotation method. But they need to wait for time to detect and track object. Therefore, it is required to reduce the process time in step (2) using benefits of manual annotation method and vision-based annotation method effectively. This paper proposes a novel annotation method allows annotator to easily annotate based on face area. For proposing new annotation method, this paper presents two steps: pre-processing step and annotation step. The pre-processing is necessary because system detects shots for users who want to find contents of video easily. Pre-processing step is as follow: 1) Extract shots using color histogram based shot boundary detection method from frames of video; 2) Make shot clusters using similarities of shots and aligns as shot sequences; and 3) Detect and track faces from all shots of shot sequence metadata and save into the shot sequence metadata with each shot. After pre-processing, user can annotates object as follow: 1) Annotator selects a shot sequence, and then selects keyframe of shot in the shot sequence; 2) Annotator annotates objects on the relative position of the actor's face on the selected keyframe. Then same objects will be annotated automatically until the end of shot sequence which has detected face area; and 3) User assigns additional information to the annotated object. In addition, this paper designs the feedback model in order to compensate the defects which are wrong aligned shots, wrong detected faces problem and inaccurate location problem might occur after object annotation. Furthermore, users can use interpolation method to interpolate position of objects which is deleted by feedback. After feedback user can save annotated object data to the interactive object metadata. Finally, this paper shows interactive video authoring system implemented for verifying performance of proposed annotation method which uses presented models. In the experiment presents analysis of object annotation time, and user evaluation. First, result of object annotation average time shows our proposed tool is 2 times faster than existing authoring tools for object annotation. Sometimes, annotation time of proposed tool took longer than existing authoring tools, because wrong shots are detected in the pre-processing. The usefulness and convenience of the system were measured through the user evaluation which was aimed at users who have experienced in interactive video authoring system. Recruited 19 experts evaluates of 11 questions which is out of CSUQ(Computer System Usability Questionnaire). CSUQ is designed by IBM for evaluating system. Through the user evaluation, showed that proposed tool is useful for authoring interactive video than about 10% of the other interactive video authoring systems.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.1
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• pp.52-60
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• 2000

This study was conducted to gain basic data for alleviation of gas emission and conservation of healthy soil environment by investigating an aspect of gas emission and microbial diversity due to the supplement of different fertilizers after application with a livestock manure compost in greenhouse soils. Green pepper was cultivated in clay loamy soil from April to August. Before planting, a livestock manure compost was applied with $741mg\;ha^{-1}$ on the basis of the phosphate content contained in compost. And then, deficient nitrogen for cropping was supplemented with either quick-acting fertilizer of urea or a controlled slow release fertilizer made from urea formaldehyde(U/F). $NH_3$ and R $NH_2$ gases emitted from soil showed a low concentration in the early stage but a maximum in 27 days after planting, then decreased rapidly and not detected after 33 days. Their average concentrations were 42% and 85% lower in the treatment of slow release fertilizer than that of urea fertilizer, respectively. $CO_2$ gas emitted under urea fertilization was ranged from 1,200 to $3,200mg{\ell}^{-1}$ and that in slow release fertilizer was $900{\sim}2,650mg\;{\ell}^{-1}$. The average concentration of urea treatment was $2,260mg{\ell}^{-1}$ and 30% higher than that of slow release fertilizer. The treatment of slow release fertilizer with the lapse of cropping time populated larger in numbers of bacteria, actinomycetes, nitrate bacteria and nitrate reduction bacteria, and ratios of bacteria and actinmycetes to fungi than that of urea fertilizer. But the number of fungi was higher in the treatment of urea fertilizer and denitrifying bacteria showed a similar trend in both treatments. The microbial diversity index, which calculated with numbers of 6 species of microorganisms, was decreased with increasing of growing stage in the range of 0.1 to 0.35 and that was higher in the tratment of slow release fertilizer than urea.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.5
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• pp.333-343
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• 2003

This experiment was carried out to improve the utilization of liquid pig manure (LPM) for rice at the two textures of valley soil in 2000 and 2001. The soil textures were coarse loamy and fine loamy in Sachon and Jisan series, respectively. Treatments consisted of no fertilized plot, chemical fertilized plot, LPM 150%, LPM 100%, LPM 100%+NK (top dressing) 30%, LPM 70%+NK 30%, LPM 50%+NK 50% plot. LPM was applied as basal fertilizer compare to nitrogen of chemical fertilized plot. Total N contents in the LPM were 6.0 and $4.5g\;kg^{-1}$ in 2000 and 2001, respectively. After the experiment, P and K contents of soils were not difference between chemical and LPM application plots. But heavy metal contents in soils were slightly higher in LPM application plots than in chemical fertilized plot. Immediately after LPM application, ammonia gas content was $18mg\;kg^{-1}$ in LPM 150% plot, but it was $3mg\;kg^{-1}$ in LPM 50% plot. Two days after LPM application, ammonia gas content was 3 times higher in coarse loamy than in fine loamy soil. After rotary tillage, ammonia gas was not detected at all LPM treatments. This result suggests that rotary tillage can reduce the nasty smell of LPM quickly. Inorganic nitrogen, $NO_3$ and $NH_4$, contents in water of paddy was higher at coarse loamy soil from rice transplanting to tillering stage. After that season, inorganic nitrogen contents of water were not different according to soil texture and treatments. Content of $NH_4-N$ in soil solution was higher at LPM plots than chemical fertilizer plot. Total nitrogen contents in rice plant after harvesting were higher at chemical fertilization plot than LPM application plot, but K contents showed an opposite tendency. Rice yield was decreased only in LPM plots at two soil textures. But yield was not significantly difference between chemical fertilizer and LPM+top dressing plots at coarse loamy soil and increased 5% at LPM 50%+NK 50% plot at fine loamy soil in 2001.

• Korean Journal of Weed Science
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• v.31 no.1
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• pp.34-40
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• 2011

Cover crop can be used to suppress weeds by competition for light and nutrient. Objective of this study was to evaluate the effectiveness of legume cover crops on change of weed community in no-till corn cultivation. Two legume cover crops, hairy vetch and crimson clover were grown in the field, and succeeding corn was sown on 4 May, 2010. The distribution of weed was surveyed at 15 April, 1 June, and 20 August. At 15 April, the weed biomass in hairy vetch field was higher than in crimson clover field. The dominant weeds were Capsella bursa-pastoris L. and Stellaria aquatica L. in hairy vetch and crimson clover fields, respectively. At vegetative stage of corn, occurred weeds in hairy vetch and crimson clover fields were four and six species, respectively, while the weed was occurred with nine species in conventional. Also the dry weight of weed was decreased by 82 and 75% in hairy vetch and crimson clover fields compared to conventional. On the other hand, after harvest of corn, occurred weed in hairy vetch, crimson clover and conventional was five, four and five species, respectively. Dry weight percentage of occurred weed in conventional was 23.5%, and the value was higher than 13.8 and 14.7% in hairy vetch and crimson clover fields, respectively. Stellaria aquatica L. as winter annual weed only occurred in cover crop field during corn growing season. It is these possibilities that low soil temperature and light interception by soil cover of legume cover crop.