• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Bio-Environment Control
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• v.25 no.2
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• pp.106-110
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• 2016

In this study, a planting density-growth-harvest (PGH) chart was developed to easily read the growth and harvest factors such as crop growth rate, relative growth rate, shoot fresh weight, shoot dry weight, harvesting time, marketable rate, and marketable yield of common ice plant (Mesembryanthemum crystallinum L.). The plants were grown in a nutrient film technique (NFT) system in a closed-type plant factory using fluorescent lamps with three-band radiation under a light intensity of $140{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ and a photoperiod of 12 h. Growth and yield were analyzed under four planting densities ($15{\times}10cm$, $15{\times}15cm$, $15{\times}20cm$, and $15{\times}25cm$). Shoot fresh and dry weights per plant increased at a higher planting density until reached an upper limit and yield per area was also same tendency. Crop growth rate, relative growth rate and lost time were described using quadratic equation. A linear relationship between shoot dry weight and fresh weights was observed. PGH chart was constructed based on the growth data and making equations. For instance, with within row spacing (= 20 cm) and fresh weight per plant at harvest (= 100 g), we can estimate all the growth and harvest factors of common ice plant. The planting density, crop growth rate, relative growth rate, lost time, shoot dry weight per plant, harvesting time, and yield were $33plants/m^2$, $20g{\cdot}m^{-2}{\cdot}d^{-1}$, $0.27g{\cdot}g^{-1}{\cdot}d^{-1}$, 22 days, 2.5 g/plant, 26 days after transplanting, and $3.2kg{\cdot}m^{-2}$, respectively. With this chart, we could easily obtain the growth factors such as planting density, crop growth rate, relative growth rate, lost time and the harvest factors such as shoot fresh and dry weights, harvesting time, marketable rate, and marketable yield with at least two parameters, for instance, planting distance and one of harvest factors of plant. PGH charts will be useful tools to estimate the growth and yield of crops and to practical design of a closed-type plant production system.

• Journal of The Korean Association For Science Education
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• v.34 no.8
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• pp.703-718
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• 2014

This study sought to investigate learning progressions for astronomical systems which synthesized the motion and structure of Earth, Earth-Moon system, solar system, and the universe. For this purpose we developed ordered multiple-choice items, applied them to elementary and middle school students, and provided validity evidence based on the consequence of assessment for interpretation of learning progressions. The study was conducted according to construct modeling approach. The results showed that the OMCs were appropriate for investigating learning progressions on astronomical systems, i.e., based on item fit analysis, students' responses to items were consistent with the measurement of Rasch model. Wright map analysis also represented that the assessment items were very effective in examining students' hypothetical pathways of development of understanding astronomical systems. At the lower anchor of the learning progression, while students perceived the change of location and direction of celestial bodies with only two-dimensional earth-based view, they failed to connect the locations of celestial bodies with Earth-Moon system model, and they could recognized simple patterns of planets in the solar system and milky way. At the intermediate levels, students interpreted celestial motion using the model of Earth rotation and revolution, Earth-Moon system, and solar system with space-based view, and they could also relate the elements of astronomical structures with the models. At the upper anchor, students showed the perspective change between space-based view and earth-based view, and applied it to celestial motion of astronomical systems, and they understood the correlation among sub-elements of astronomical systems and applied it to the system model.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.643-651
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• 2001

Paddlewheel-driven circulation in a culture pond has been simulated based on the depth integrated 2 dimensional hydrodynamic model. Acceleration by paddlewheel is expressed as shaft force divided by water mass discharged by paddlewheel blades. The model has been calibrated and applied to culture ponds as following steps:- i) The model predicted velocities at every 10 m along longitudinal direction from the paddlewheel. The model was calibrated comparing the results with the measured values at mass correction factor $\alpha$ and dimensionless eddy viscosity constant $\gamma$, respectively, in a range $15\~20$ and 6. ii) Wind shear stress was simulated under conditions of direction $0^{\circ}C,\;90^{\circ}C\;and\;180^{\circ}C$ and speed 0.0, 2.5, 5.0 and 7.5 m/s. Change rate of current speed was <$1\%$ at wind in parallel or opposite direction to the paddlewheel-driven jet flow, while $4\%$ at orthogonal angle. iii) The model was then applied to 2 culture ponds located at the Western coast of Korea. The measured and predicted currents for the ponds were compared using the regression analysis. Analysis of flow direction and speed showed correlation coefficients 0.8928 and 0.6782 in pond A, 0.8539 and 0.7071 in pond B, respectively. Hence, the model is concluded to accurately predict circulation driven by paddlewheel such that it can be a useful tool to provide pond management strategy relating to paddlewheel operation and water quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.23-34
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• 2004

Video camera can be a useful tool to capture images for use in colorimeter. However the RGB signals generated by different video camera are not equal for the same scene. The video camera for use in colorimeter is characterized based on the CIE standard colorimetric observer. One method of deriving a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values is least squares polynomial modeling. However it needs tedious experiments to obtain camera transfer matrix under various white balance point for the same camera. In this paper, a new method to obtain camera transfer matrix under different white balance by using 3${\times}$3 camera transfer matrix under a certain white balance point is proposed. According to the proposed method camera transfer matrix under any other white balance could be obtained by using colorimetric coordinates of phosphor derived from 3${\times}$3 linear transfer matrix under the certain white balance point. In experimental results, it is demonstrated that proposed method allow 3${\times}$3 linear transfer matrix under any other white balance having a reasonable degree of accuracy compared with the transfer matrix obtained by experiments.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.157-175
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• 2012

It is difficult to evaluate the performance of process innovation of e-procurement which has large scale and complex processes. The existing evaluation methods for measuring the effects of process innovation have been mainly done with statistically quantitative methods by analyzing operational data or with qualitative methods by conducting surveys and interviews. However, these methods have some limitations to evaluate the effects because the performance evaluation of e-procurement process innovation should consider the interactions among participants who are active either directly or indirectly through the processes. This study considers the e-procurement process as a complex system and develops a simulation model based on MAS(Multi-Agent System) to evaluate the effects of e-procurement process innovation. Multi-agent based simulation allows observing interaction patterns of objects in virtual world through relationship among objects and their behavioral mechanism. Agent-based simulation is suitable especially for complex business problems. In this study, we used Netlogo Version 4.1.3 as a MAS simulation tool which was developed in Northwestern University. To do this, we developed a interaction model of agents in MAS environment. We defined process agents and task agents, and assigned their behavioral characteristics. The developed simulation model was applied to G2B system (KONEPS: Korea ON-line E-Procurement System) of Public Procurement Service (PPS) in Korea and used to evaluate the innovation effects of the G2B system. KONEPS is a successfully established e-procurement system started in the year 2002. KONEPS is a representative e-Procurement system which integrates characteristics of e-commerce into government for business procurement activities. KONEPS deserves the international recognition considering the annual transaction volume of 56 billion dollars, daily exchanges of electronic documents, users consisted of 121,000 suppliers and 37,000 public organizations, and the 4.5 billion dollars of cost saving. For the simulation, we analyzed the e-procurement of process of KONEPS into eight sub processes such as 'process 1: search products and acquisition of proposal', 'process 2 : review the methods of contracts and item features', 'process 3 : a notice of bid', 'process 4 : registration and confirmation of qualification', 'process 5 : bidding', 'process 6 : a screening test', 'process 7 : contracts', and 'process 8 : invoice and payment'. For the parameter settings of the agents behavior, we collected some data from the transactional database of PPS and some information by conducting a survey. The used data for the simulation are 'participants (government organizations, local government organizations and public institutions)', 'the number of bidding per year', 'the number of total contracts', 'the number of shopping mall transactions', 'the rate of contracts between bidding and shopping mall', 'the successful bidding ratio', and the estimated time for each process. The comparison was done for the difference of time consumption between 'before the innovation (As-was)' and 'after the innovation (As-is).' The results showed that there were productivity improvements in every eight sub processes. The decrease ratio of 'average number of task processing' was 92.7% and the decrease ratio of 'average time of task processing' was 95.4% in entire processes when we use G2B system comparing to the conventional method. Also, this study found that the process innovation effect will be enhanced if the task process related to the 'contract' can be improved. This study shows the usability and possibility of using MAS in process innovation evaluation and its modeling.

• Journal of radiological science and technology
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• v.36 no.2
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• pp.99-110
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• 2013

In the medical field, the necessity of education growth for the professional Radiation Technologists has been emphasized to become experts on radiation and the radiation field is important of the society. Also, in hospitals and companies, important on thesis is getting higher in order to active and cope with rapidly changing internal and external environment and a more in-depth expert training, the necessity of new teaching and learning model that can cope with changes in a more proactive has become. Thesis writing classes brought limits to the in-depth learning as to start a semester and rely on only specific programs besides, inevitable on passive participation. In addition, it does not have a variety opportunity to present, an actual opportunity that can be written and discussed does not provide much caused by instructor-led classes. As well as, it has had a direct impact on the quality of the thesis, furthermore, having the opportunity to participate in various conferences showed the limitations. In order to solve these problems, in this study, writing thesis has organized training operations as a consistent gradual deepening of learning, at the same time, the operational idea was proposed based on the connectivity integrated operating and effective training program & instructional tool for improving the ability to perform the written actual thesis. The development of teaching and learning model consisted of 4 system modeling, scaffolding, articulation, exploration. Depending on the nature of the course, consisting team following the personal interest and the topic allow for connection subject, based on this, promote research capacity through a step-by-step evaluation and feedback and, fundamentally strengthen problem-solving skills through the journal studies, help not only solving the real-time problem by taking wiki-space but also efficient use of time, increase the quality of the thesis by activating cooperation through mentoring, as a result, it was to promote a positive partnership with the academic. Support system in three stages planning subject, progress & writing, writing thesis & presentation and based on cognitive apprenticeship. The ongoing Coaching and Reflection of professor and expert was applied in order to maintain these activities smoothly. The results of this study will introduce actively, voluntarily and substantially join to learners, by doing so, culture the enhancement of creativity, originality and the ability to co-work and by enhance the expertise of based-knowledge, it is considered to be help to improve the comprehensive ability.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.637-648
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• 2009

As the cost of disks decreases, PCs are soon expected to be equipped with a disk of 1TB or more. Assuming that a single person generates 1GB of data per month, 1TB is enough to store data for the entire lifetime of a person. This has lead to the growth of researches on lifelog management, which manages what people see and listen to in everyday life. Although many different lifelog management systems have been proposed, including those based on the relational data model, based on ontology, and based on file systems, they have all advantages and disadvantages: Those based on the relational data model provide good query processing performance but they do not support complex queries properly; Those based on ontology handle more complex queries but their performances are not satisfactory: Those based on file systems support only keyword queries. Moreover, these systems are lack of support for lifelog group management and do not provide a convenient user interface for modifying and adding tags (metadata) to lifelogs for effective lifelog search. To address these problems, we propose a lifelog management system based on the relational data model. The proposed system models lifelogs by using the relational data model and transforms queries on lifelogs into SQL statements, which results in good query processing performance. It also supports a simplified relationship query that finds a lifelog based on other lifelogs directly related to it, to overcome the disadvantage of not supporting complex queries properly. In addition, the proposed system supports for the management of lifelog groups by providing ways to create, edit, search, play, and share them. Finally, it is equipped with a tagging tool that helps the user to modify and add tags conveniently through the ion of various tags. This paper describes the design and implementation of the proposed system and its various applications.