• Journal of The Korean Association For Science Education
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• v.18 no.4
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• pp.601-615
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• 1998

Establishing and evaluating science education policies and revising and monitoring the effectiveness of science curriculum should be based upon the results of systematic and scientific research studies. Advanced nations have already been administering and developing national level science assessments for these purposes. The science assessments administered in Korea have been reported having many limitations and problems, and not succeeded in providing data for science education policy making and curriculum reform. The major purpose of the study is developing national level science knowledge assessment system in order to identify longitudinal trends of elementary and secondary school students science knowledge achievements. The research team consisted of science education experts and teachers from various school levels, decided the directions and major elements of national level science knowledge assessment with the consultation of educational evaluation experts. Item developing ability of the researchers was improved by seminars? and workshops on national assessment in advanced nations and developing skills of writing science items. Nearly 500 items were developed and revised. Pilot test was administered with 958 students at various school levels. 380 items were selected and tested with 8766 students, and the characteristics were analyzed in terms of item response theory. The target populations for national level science knowledge assessment are 5th-grade of elementary school, 2nd-grade of middle school, 1st and 2nd-grade of high school students. The proper period for the assessment is February every year. Multi-stage clustered sampling method is desirable and rotated forms are recommendable for the test format. Bridge items should be introduced to compare the results of multiple tests, and various grades. Anchor items should also be used for longitudinal interpretations of the results. The items for elementary school require low to medium abilities, for middle school and first grade of high school require medium to high abilities and for 2nd-grade of high school high abilities. The discrimination ability of the items developed is high.

• Korean Journal of Plant Resources
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• v.32 no.5
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• pp.519-542
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• 2019

Twenty soybean cultivars developed recently were assessed using 27 insertion and deletion (InDel) markers derived from dense variation blocks (dVBs) of soybean genome. The objective of this study is to identify the distinctness and genetic relationships among a total of 169 soybean accessions including new cultivars. The genetic homology between 149 accessions in the soybean barcode system and 20 new cultivars was 61.3% on average with the range from 25.9% to 96.3%, demonstrating the versatile application of these markers for cultivars identification. The phylogenic analysis revealed four subgroups related to their usage. The 80% of cultivars for vegetable and early maturity and the 65.9% of cultivars for bean sprouts were clustered in subgroup I-2 and II-2, respectively, indicating of the limited gene pools of their crossing parents in breeding. On the other hands, the cultivars for soy sauce and tofu with considerable gene flow by genome reshuffling were distributed evenly to several subgroups, I-1 (44.4%), I-2 (26.4%) and II-2 (23.6%). We believe that the 27 InDel markers specific to dVBs can be used not only for cultivar identification and genetic diversity, but also in breeding purposes such as introduction of genetic resources and selection of breeding lines with target traits.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.136-146
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• 2024

This paper introduces the seismic facies classification and mapping of igneous bodies found in the sedimentary sequences of the Yellow Sea shelf area of Korea. In the research area, six extrusive and three intrusive types of igneous bodies were found in the Late Cretaceous, Eocene, Early Miocene, and Quaternary sedimentary sequences of the northeastern, southwestern and southeastern sags of the Gunsan Basin. Extrusive igneous bodies include the following six facies: (1) monogenetic volcano (E.mono) showing cone-shape external geometry with height less than 200 m, which may have originated from a single monogenetic eruption; (2) complex volcano (E.comp) marked by clustered monogenetic cones with height less than 500 m; (3) stratovolcano (E.strato) referring to internally stratified lofty volcanic edifices with height greater than 1 km and diameter more than 15 km; (4) fissure volcanics (E.fissure) marked by high-amplitude and discontinuous reflectors in association with normal faults that cut the acoustic basement; (5) maar-diatreme (E.maar) referring to gentle-sloped low-profile volcanic edifices with less than 2 km-wide vent-shape zones inside; and (6) hydrothermal vents (E.vent) marked by upright pipe-shape or funnel-shape structures disturbing sedimentary sequence with diameter less than 2 km. Intrusive igneous bodies include the following three facies: (1) dike and sill (I.dike/sill) showing variable horizontal, step-wise, or saucer-shaped intrusive geometries; (2) stock (I.stock) marked by pillar- or horn-shaped bodies with a kilometer-wide intrusion diameter; and (3) batholith and laccoliths (I.batho/lac) which refer to gigantic intrusive bodies that broadly deformed the overlying sedimentary sequence.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Korean Journal of Plant Resources
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• v.33 no.5
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• pp.446-459
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• 2020

This study analyzed the phenotypes and chemotypes of 74 tartary buckwheat (Fagopyrum tataricum) germplasms using principal component analysis and cluster analysis. The average seed size of tartary buckwheat germplasm was 5.2 × 3.4 mm, which is smaller than the seed size of common buckwheat. The dark browned colored ovate or elliptic shape was mostly observed in collected germplasm. The average content of rutin was 1,393 mg per 100 g dry weight (DW) in tartary buckwheat seed. Similarly, the flavonoid and polyphenol contents ranged from 253 to 2,669 and 209 to 1,823 mg, respectively, per 100 g DW in the collected germplasm. The three components (PC1, 2, and 3) of principal component analysis revealed 68.55% of the total variance of the collected accessions. Cluster analysis using descriptors showed that 74 accessions were clustered into five groups. The study showed that the most interesting resources for functional breeding programs are: Five resources (HLB1004, HLB1005, HLB1007, HLB1009, and HLB1013) due to the rich rutin, polyphenol, and flavonoid.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.05a
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• pp.91-93
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• 2003

A comprehensive numerical study is carried out to investigate for the understanding of the flow evolution and flame development in a supersonic combustor with normal injection of ncumally injecting hydrogen in airsupersonic flows. The formulation treats the complete conservation equations of mass, momentum, energy, and species concentration for a multi-component chemically reacting system. For the numerical simulation of supersonic combustion, multi-species Navier-Stokes equations and detailed chemistry of H2-Air is considered. It also accommodates a finite-rate chemical kinetics mechanism of hydrogen-air combustion GRI-Mech. 2.11[1], which consists of nine species and twenty-five reaction steps. Turbulence closure is achieved by means of a k-two-equation model (2). The governing equations are spatially discretized using a finite-volume approach, and temporally integrated by means of a second-order accurate implicit scheme (3-5).The supersonic combustor consists of a flat channel of 10 cm height and a fuel-injection slit of 0.1 cm width located at 10 cm downstream of the inlet. A cavity of 5 cm height and 20 cm width is installed at 15 cm downstream of the injection slit. A total of 936160 grids are used for the main-combustor flow passage, and 159161 grids for the cavity. The grids are clustered in the flow direction near the fuel injector and cavity, as well as in the vertical direction near the bottom wall. The no-slip and adiabatic conditions are assumed throughout the entire wall boundary. As a specific example, the inflow Mach number is assumed to be 3, and the temperature and pressure are 600 K and 0.1 MPa, respectively. Gaseous hydrogen at a temperature of 151.5 K is injected normal to the wall from a choked injector.A series of calculations were carried out by varying the fuel injection pressure from 0.5 to 1.5MPa. This amounts to changing the fuel mass flow rate or the overall equivalence ratio for different operating regimes. Figure 1 shows the instantaneous temperature fields in the supersonic combustor at four different conditions. The dark blue region represents the hot burned gases. At the fuel injection pressure of 0.5 MPa, the flame is stably anchored, but the flow field exhibits a high-amplitude oscillation. At the fuel injection pressure of 1.0 MPa, the Mach reflection occurs ahead of the injector. The interaction between the incoming air and the injection flow becomes much more complex, and the fuel/air mixing is strongly enhanced. The Mach reflection oscillates and results in a strong fluctuation in the combustor wall pressure. At the fuel injection pressure of 1.5MPa, the flow inside the combustor becomes nearly choked and the Mach reflection is displaced forward. The leading shock wave moves slowly toward the inlet, and eventually causes the combustor-upstart due to the thermal choking. The cavity appears to play a secondary role in driving the flow unsteadiness, in spite of its influence on the fuel/air mixing and flame evolution. Further investigation is necessary on this issue. The present study features detailed resolution of the flow and flame dynamics in the combustor, which was not typically available in most of the previous works. In particular, the oscillatory flow characteristics are captured at a scale sufficient to identify the underlying physical mechanisms. Much of the flow unsteadiness is not related to the cavity, but rather to the intrinsic unsteadiness in the flowfield, as also shown experimentally by Ben-Yakar et al. [6], The interactions between the unsteady flow and flame evolution may cause a large excursion of flow oscillation. The work appears to be the first of its kind in the numerical study of combustion oscillations in a supersonic combustor, although a similar phenomenon was previously reported experimentally. A more comprehensive discussion will be given in the final paper presented at the colloquium.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.2
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• pp.16-26
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• 2016

In this paper, we collected information on Palgyeong of the Gangneung area that were scattered around several literatures, and analyzed and interpreted regional distribution, elements of scenery and inherent meanings from various angles. we shed light on the origin and the meaning of Palgyeong, which have been passed down in the Gangneung area. Palgyeong of the Gangneung area have been accumulated and expanded for a long period of time, since Goryeo up to the modern times, and it does not simply reflect the beauty of natural scenery, but also reflect historical facts and sentiments rooted in this region. In addition, given the comprehensive veiw of Palgyeong of the Gangneung area and in consideration of its type and distribution of the eight sceneries the most common format is similar to Sosang(瀟湘類似型). What are repeatedly appearing among them include 'smoke from cooking supper' and 'catching fish', showing the living conditions of local residents of Gangneung at the time, which refers to the fact that Palgyeong consisted of village units. Palgyeong in the Gangneung area are distributed in diverse ranges between the city and Nujung. Most of Palgyeong are clustered in the east of Gangneung city and in the region tangent to Gangdong-myeon and Gujeong-myeon. When we consider the situation where most of Palgyeong in the Gangneung area are distributed in this region, it suggests that the region occupies the heart of scenery of Gangneung. Palgyeong of the Gangneung area consists of 60% natural factors, 36% humanity factors, and 4% other factors, where the natural factors hold the beauty of nature itself and the humanities and other factors hold the legends and history contained in the targets. The sceneries expressed by Palgyeong cannot be individually separated. Namedaecheon, Jukdobong, Sumseokcheon, Sumdulmaeul, Gunseongang, Pungho and Kyungpoho were connected to Nujung and Hongjamam, and they eventually became a panorama. Hansongjung, Hwanseondeung, Hansongsa, Pungho and Gunseongang are related to Hwarang of Silla and have become representative historical sceneries of the Gangneung area. Judging from the fact that currently non-existing sceneries such as Kyeonjodo, Hansongjung and Gulsansa remained in Palgyeong and been passed, Palgyeong have positioned imaginary spaces of the Gangneung people beyond simply expressing sceneries. In conclusion, Palgyeong in the Gangneung area are aesthetical objects and while at the same time, they are historical and cultural space, and furthermore, we can see that they still remain as imaginary spaces.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.