• Journal of Science Education
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• v.47 no.2
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• pp.211-224
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• 2023

The purpose of this study is to suggest how to investigate the reliability of the assessment, which consists of items generated by automatic item generation using empirical example data. To achieve this, we analyzed the illustrative assessment data by applying the multivariate generalizability theory, which can reflect the design of responding to different items for each student and multiple error sources in the assessment score. The result of the G-study showed that, in most designs, the student effect corresponding to the true score of the classical test theory was relatively large after residual effects. In addition, in the design where the content domain was fixed, the ranking of students did not change depending on the item types or items. Similarly, in the design where the item format was fixed, the difficulty showed little variation depending on the content domains. The result of the D-study indicated that the original assessment data achieved a sufficient level of reliability. It was also found that higher reliability than the original assessment data could be obtained by reducing the number of items in the content domains of operation, geometry, and probability and statistics, or by assigning higher weights to the domains of letters and formulas, and function. The efficient measurement conditions presented in this study are limited to the illustrative assessment data. However, the method applied in this study can be utilized to determine the reliability and to find efficient measurement conditions for the various assessment situations using automatic item generation based on measurement traits.

• Applied Chemistry for Engineering
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• v.34 no.2
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• pp.137-143
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• 2023

In this study, natural surfactants were extracted from Medicago sativa L. The O/W emulsification processes with the extracted natural surfactants were optimized using central composite design model-response surface methodology (CCD-RSM) and a 95% confidence interval was used to confirm the reasonableness of the optimization. Herein, independent parameters were the ratio of saponins to total surfactant (P), amount of surfactant (W), and emulsification speed (R), whereas the reaction parameters were the emulsion stability index (ESI), mean droplet size (MDS), and viscosity (V). Using the multiple reaction, the optimal conditions for the ratio of saponins to total surfactant, amount of surfactant, and emulsification speed for O/W emulsification were 49.5%, 9.1 wt%, and 6559.5 rpm, respectively. Under these optimal conditions, the expected values of ESI, MDS, and V as the reaction parameters were 89.9%, 1058.4 nm, and 1522.5 cP, respectively. The values of ESI, MDS, and V from these expected values were 88.7%, 1026.4 nm, and 1486.5 cP, respectively, and the average experimental error for validating the accuracy was about 2.3 (± 0.4)%. Therefore, it was possible to design an optimization process for evaluating the O/W emulsion process with Medicago sativa L. using CCD-RSM.

• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.16-22
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• 2024

Polymer electrolyte membrane fuel cells have the advantage of low operating temperatures and fast startup and response characteristics compared to others. Simulation studies are actively researched because their cost and time benefits. In this study, the resistance of water residual in the gas diffusion layer (GDL) of the unit cell was added to the existing equation to compare the actual data with the model data. The experiments were conducted with a 25 cm² unit cell, and the samples were separated into stopping times of 0, 10, and 60 minutes following primary impedance measurement, activation, and polarization curve data acquisition. This gives 0, 10, and 60 minutes for the residual water in the GDL to evaporate. Without the rest period, the magnitude of the performance improvement was not significantly different at the same potential and flow rate, but the rest period did improve the performance of the membrane electrode assembly when measuring impedance. By changing the magnitude of the resistance reduction to an overvoltage, the voltage difference between the fuel cell model with and without residual water was compared, and the error rate in the high current density region, which is dominated by concentration losses, was reduced.

• Journal of the Korea Concrete Institute
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• v.24 no.3
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• pp.293-303
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• 2012

Recently, as construction technology improved, concrete structures not only became larger, taller and longer but were able to perform various functions. However, if extreme loads such as impact, blast, and fire are applied to those structures, it would cause severe property damages and human casualties. Especially, the structural responses from extreme loading are totally different than that from quasi-static loading, because large pressure is applied to structures from mass acceleration effect of impact and blast loads. Therefore, the strain rate effect and damage levels should be considered when concrete structure is designed. In this study, the low velocity impact loading test of steel fiber reinforced concrete (SFRC) slabs including 0%~1.5% (by volume) of steel fibers, and strengthened with two types of FRP sheets was performed to develop an impact resistant structural member. From the test results, the maximum impact load, dissipated energy and the number of drop to failure increased, whereas the maximum displacement and support rotation were reduced by strengthening SFRC slab with FRP sheets in tensile zone. The test results showed that the impact resistance of concrete slab can be substantially improved by externally strengthening using FRP sheets. This result can be used in designing of primary facilities exposed to such extreme loads. The dynamic responses of SFRC slab strengthened with FRP sheets under low velocity impact load were also analyzed using LS-DYNA, a finite element analysis program with an explicit time integration scheme. The comparison of test and analytical results showed that they were within 5% of error with respect to maximum displacements.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.1-23
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• 2009

The Survey on the Industrial Research and Development(R&D) is the primary source of information on R&D performed by Korea industrial sector. The results of the survey are used to assess trends in R&D expenditures. Government agencies, corporations, and research organizations use the data to investigate productivity determinants, formulate tax policy, and compare individual company performance with industry averages. Recently, Korea Industrial Technology Association(KOITA) has collected the data by complete enumeration. Koita has, currently, considered sample survey because the number of R&D institutions in industry has been dramatically increased. This study develops survey design for the industrial research and development(R&D) statistics by introducing a sample survey. Companies are divided into 8 groups according to the amount of R&D expenditures and firm size or type. We collect the sample from 24 or 8 sampling strata and compare the results with those of complete enumeration survey. The estimates from 24 sampling strata are not significantly different to the results of complete enumeration survey. We propose the survey design as follows: Companies are divided into 11 groups including the companies of which R&D expenditures are unknown. All large companies are included in the survey and medium and small companies are sampled from 70% and 3%. Simple random sampling (SRS) is applied to the small company partition since they show uniform distribution in R&D expenditures. The independent probability proportionate to size (PPS) sampling procedure may be applied to those companies identified as 'not R&D performers'. When respondents do not provide the requested information, estimates for the missing data are made using imputation algorithms. In the future study, new key variables should be developed in survey questionnaires.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.111-119
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• 2019

The high-speed railway system is mainly composed of tunnel, bridge, and viaduct to meet the straightness needed for keeping the high speed up to 400 km/s. Seismic fragility for the high-speed railway infrastructure can be assessed as two ways: one way is studying each element of infrastructure analytically or numerically, but it requires lots of research efforts due to wide range of railway system. On the other hand, empirical method can be used to access the fragility of an entire system efficiently, which requires case history data. In this study, we collect the 2004 M_W 6.6 Niigata earthquake case history data to develop empirical seismic fragility function for a railway system. Five types of intensity measures (IMs) and damage levels are assigned to all segments of target system for which the unit length is 200 m. From statistical analysis, probability of exceedance for a certain damage level (DL) is calculated as a function of IM. For those probability data points, log-normal CDF is fitted using MLE method, which forms fragility function for each damage level of exceedance. Evaluating fragility functions calculated, we observe that T=3.0 spectral acceleration (SA_T3.0) is superior to other IMs, which has lower standard deviation of log-normal CDF and low error of the fit. This indicates that long-period ground motion has more impacts on railway infrastructure system such as tunnel and bridge. It is observed that when SA_T3.0 = 0.1 g, P(DL>1) = 2%, and SA_T3.0 = 0.2 g, P(DL>1) = 23.9%.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1784-1792
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• 2007

This study set out to identify the problems with hat labels and to search for improvement measures by examining and analyzing consumers' practice of managing their hats. It also intended to provide accurate and enough information about how to keep and wash hats and thus help consumers use their hats for a long period. In an attempt to investigate how consumers wash and manage their hats, a survey was carried out to 395 individuals in their twenties and over who owned hats living in urban areas including Seoul, and were quota sampled according to age and gender. The survey period is March to April 2007. The collected data were statistically treated with the SPSS 12.0 program in terms of frequency, percentage, mean, standard error, cross tabulation, t-test, and one-way ANOVA. The findings were as followed. First, the respondents were in the average level of perceiving and practicing the washing methods of their hats. The female respondents who had more experiences with laundering than the males knew and practiced the washing methods for hats better than males. Second, compared to other clothing items, hat wearers were more likely to pay careful attention to their hats by putting their hats in a laundry net and applying a laundry detergent for wool fabrics when using a washing machine or washing their hats with their own hands. And third, most of the hat wearers were aware of the importance of hat labels and showed a lower level of trust in them than other clothing items. The suppliers need to offer accurate and practical labels in order to regain the consumers' trust. Many consumers had some difficulties figuring out the size system of hats. In particular, the male consumers had a low level of perception of labels, which implies that there should be specific efforts to educate them about general labels.

• Pediatric Infection and Vaccine
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• v.19 no.1
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• pp.19-27
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• 2012

Purpose : As the number of children who attend child care centers has increased, concerns has increased about the effect of child day care on childhood illness. This study was conducted to examine the relationship between experience in child care and common infectious diseases in children under 5 years of age. Methods : Data were collected by surveying 1,000 respondents with children under age 5 through online interviews using a structured questionnaire. The contents of the survey were composed of demographic characteristics, child care facilities usage, experience in infectious diseases, and immunization status Results : Among the 1,000 children <5 years of age, 78.5% attended a child care facility. Rates of common communicable illnesses were higher in children in child care than for children reared exclusively at home. The predominant communicable diseases which the respondents' children experienced, in order of decreasing frequency, were gastroenteritis (47.1%), otitis media (41.8%) and pneumonia (19.1%). The immunization rate of vaccines that are not included the national immunization program (NIP) (Haemophilus influenzae type b vaccine - 76.6%, hepatitis A vaccine - 63.3%, pneumococcal vaccine - 59.4%, rotavirus vaccine - 43.1%) was lower than that of the NIP vaccines (90.4%) Conclusion : Children in child care experience more bouts of common infectious disease, so nationwide policies to prevent or to control the spread of infectious agents in a child-care should be available and appropriate immunization should be emphasized as the most effective method for the control of infectious disease for children.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.133-137
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• 2017

The purpose of this study was to validate for GATE (Geant4 Application for Tomographic Emission) simulation by comparing the results of GATE simulation and experiment in real SPECT system. Futhermore, we want to prove that it is possible that the quantitative research of gamma camera/SPECT imaging for therapeutic radio isotope by using GATE simulation. In this study, the SPECT system on simulation referred to the parameters of Stream-R Forte version 1.2 (Philips Medical System, Best and Heerlen, Netherlands). To understand the I-131 image of gamma camera/SPECT system, we acquired the energy spectrum and measured the full width at half maximum (FWHM) which comes from line spread function (LSF) with and without scatter material in real SPECT system. And to compare with experiment, we also measured the FWHM and acquired the energy spectrum without scatter material in GATE simulation. As a result, without scatter material, the energy peak was almost same location, which are located nearby 364 keV, and other spectrum factors are same tendency in both cases. The FWHM was increased by increasing the distance of source to detector, and the error rate was approximately 3.8%. When we used the line source with scatter material, energy spectrum also indicated similar tendency in both cases. As you confirmed earlier, GATE simulation included real instrument and radioisotope characters for therapeutic radioisotope. Therefore this result that it was possible that various quantitative study for therapeutic radioisotope imaging in gamma camera/SPECT using GATE simulation.