• Korea Science and Art Forum
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• v.27
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• pp.277-288
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• 2017

The number of science museums in Korea has expanded quantitatively from 72 in 2008 to 128 in 2016. This study started with the fact that the government puts a lot of budget into building a science museum, but there are more than one quarter of science museums with less than 50 spectators per day and many inefficient institutions. The number of visitors is an important factor in improving the efficiency of the science museum operation. The purpose of this study is to analyze the relation between the service quality of the science museum and the customer satisfaction and the intention to revisit and to find out what kind of effort should be concentrated in the science museum to attract more visitors. Questionnaires were written in the exhibition, education, and culture fields of the Gwacheon National Science Museum. The results were derived by frequency analysis, reliability analysis, factor analysis, and multiple regression analysis. The results and contents of the study are as follows. First, in the field of exhibition, the quality of exhibition facilities was expected to affect customer satisfaction and intention to return, but did not have a meaningful relationship. Second, the education sector has been found to affect customer satisfaction and return intention in all aspects of service quality (operation and contents, instructors, educational facilities and environment). Third, in the field of culture (event), the quality of the cultural program influences the visitor satisfaction, but it does not affect the intention to revisit. The science museum can provide satisfaction to visitors by combining activities such as science and arts. Despite the limitations, it is necessary to make efforts to improve the visitor satisfaction and revisit by proceeding with the convergence research on the entire National Science Museum in the future.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.97-112
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• 2023

Background: In modern society, the importance of Public Design has become increasingly significant in contributing to the enhancement of urban functionality and the quality of life of citizens. Smart Public Facilities have played a pivotal role in enriching user experience by improving accessibility, convenience, and safety, and in elevating the value of the city. This research recognizes the importance of Public Facilities and explores the potential of Smart Public Facilities in solving urban challenges and progressing towards sustainable and Inclusive cities. Method: The literature review comprehensively examines existing theories and research results on Smart Public Facilities. The case study analyzes actual examples of Smart Public Facilities implemented in cities both domestically and internationally, drawing out effects, user satisfaction, and areas for improvement. Through analysis and discussion, the results of the case studies are evaluated, discussing the potential development of Smart Public Facilities. Results: Smart Public Facilities have been found to bring positive changes in various aspects such as urban management, energy efficiency, safety, and information accessibility. In terms of urban management, they play a crucial role in optimization, social Inclusiveness, environmental protection, fostering citizen participation, and promoting technological innovation. These changes create a new form of urban space, combining physical space and digital technology, enhancing the quality of life in the city. Conclusion: This research explores the implications, current status, and functions of Smart Public Facilities in service and design aspects, and their impact on the urban environment and the lives of citizens. In conclusion, Smart Public Facilities have brought about positive changes in the optimization of urban management, enhancement of energy efficiency, increased information accessibility, User-Centric design, increased interaction, and social Inclusiveness. Technological innovation and the integration of Public Facilities have made cities more efficient and proactive, enabling data-based decision-making and optimized service delivery. Such developments enable the creation of new urban environments through the combination of physical space and digital technology. The advancement of Smart Public Facilities indicates the direction of urban development, where future cities can become more intelligent, proactive, and User-Centric. Therefore, they will play a central role in Public Design and greatly contribute to improving the urban environment and the quality of life of citizens.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.4 no.1
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• pp.31-71
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• 1968

To clarify the breeding behavior of the hybrids between tropical and temperate area rice varieties, investigations were made on heading days and grain sterility. In this study, crosses were made in half way diallel involving 7 varieties: 2 photoperied sensitive Indicas, 2 less sensitive intermediate Indicas, 1 Ponlai Japonica and 2 high temperature sensitive Japonicas. The parents and $F_1$s were grown under 10 hours and 14 hours daylength controlled conditions at both IRRI(International Rice Research Institute, N$14^{\circ}$17') and Suwon(N$37^{\circ}$16'). F2s with their parents were grown at IRRI in the short day season, and at Suwon under natural conditions. Fa lines with their parents were grown at Suwon under natural conditions. Observations were made for heading days and sterility. The results are summarized as follow; 1. Heading days : 1. For the $F_1$s, earliness showed dominance or overdominance to lateness under the 10 hours condition, and dominance or partial dominance under the 14 hours conditions, at both IRRI and Suwon. 2. For the $F_2$s grown at IRRI during the shortday season earliness appeared to be dominant over lateness and segregation was not distinct and continuous. In the early season culture of $F_2$s at Suwon earliness showed partial dominance or was intermediate. In the proper season culture of $F_2$s lateness showed partial dominance or was intermediate. 3. In the combinations between late parental varieties which do not head at Suwon, transgressive segregants bearing effective panicles were obtained. 4. The crosses of parental varieties having long basic vegetative growth duration showed bigger variance in heading days, and significant correlation was found between of parental varieties and the mean coefficient of variance for parental arrays. 5. The means of heading days of F2 populations were significantly correlated with those of $F_1$ or mid-parents. The means of F 8 lines were also highly correlated with the means of $F_2$s, but, the means of $F_3$ lines grown at Suwon and of their parental $F_2$ individual, grown at IRRI were not correlated. 6. A faint heritability was calculated from the regression of $F_3$ lines grown at Suwon on the $F_2$ individuals grown at IRRI for most combinations, especially in the combinations involving shortday sensitive varieties. This implies low efficiency for the selection of heading days of $F_2$ individuals at IRRI to be grown in lines at Suwon. 7. No significant reciprocal effects were measured for $F_1$ and $F_2$ mean heading days. 8. Partitioning the observed photoperiod sensitivity. into two components, parental array mean md the deviation from this array mean, the parental photoperiod sensitivity contributing to the hybrids was measured in terms of general and specific combining ability for photoperiod sensitivity. 9. The photoperiod sensitivity of $F_1$s was higher than that of the parents, and it decreased as the generation progressed in most combinations of tested varieties. 10. The response of heading days to difference of temperature was weaker for $F_1$ hybrids than for the parents. The differences of temperature responses between the longday and shortday treatments were specific for the variety. 2. Sterility : 1. The $F_1$ sterility was specific for the combinations and not correlated to the parental sterility. The sterility of $F_1$s grown under the 10 hours condition was higher than of those grown under 14 hours. These results were the same at both locations, IRRI and Suwon. 2. The high sterile combinations in $F_1$ showed high sterility in $F_2$. The combinations between a high photoperiod sensitive variety and a high temperature sensitive variety showed high sterility and wider variance. 3. The mean sterility of $F_2$s was lower than of $F_1$s and the mean of $F_3$ lines was lower than of $F_2$s. Sterility decreased as the generation progressed, and the differences of $F_3$ sterility of different combinations were not significant. 4. A faint correlation between grain sterility and pollen sterility was observed in $F_2$ populations. 5. No significant reciprocal effects were measured in $F_1$ and $F_2$ sterility. 6. Following Griffing's method, specific combining ability effects were higher than general combining ability effects, especially in the combinations between highly photoperiod sensitive varieties and highly temperature sensitive varieties. 7. No distinct correlations were found between $F_2$ individual sterility grown at IRRI and $F_3$ line sterility grown at Suwon. 8. No distinct correlations were observed between heading days and sterility of $F_2$ individuals.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.12
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• pp.889-896
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• 2013

Advanced Oxidation Processes (AOP) have been interested for removing micropollutants in water. Most of water treatment plants (WTPs) located along the lower part of Nakdong River have adopted the $O_3/BAC$ process and have interesting in peroxone process a kind of AOP. This study evaluated the removal characteristics of residual hydrogen peroxide ($H_2O_2$) combining with the biofiltration process in the next BAC process when the hydrogen peroxide is applied for the WTP operating $O_3/BAC$ process. In the experiment, changing the temperature and the concentration of $H_2O_2$ of influent, the biofiltration process showed rapidly dropped the biodegradability when the $H_2O_2$ concentration was increased and lowered water temperature while BAC process maintained relatively stable efficiency. The influent fixed at $20^{\circ}C$ and the concentration of $H_2O_2$ at 300 mg/L was continuously input for 78 hours. Most of the $H_2O_2$ in the influent did not remove at the biofiltration process controlled 5 to 15 minutes EBCT condition after 24~71 hours operating time while BAC process controlled 5 to 15 minutes EBCT showed 38~91% removal efficiency condition after 78 hours operating time. Besides, after 78 hours continuously input experiment, the biomass and activity of attached bacterial on the biofilter and BAC were $6.0{\times}10^4CFU/g$, $0.54mg{\cdot}C/m^3{\cdot}hr$ and $0.4{\times}10^8CFU/g$, $1.42mg{\cdot}C/m^3{\cdot}hr$ respectively. These biomass and activity values were decreased 99% and 72% in biofilter and 68% and 53% in BAC compared with initial condition. The biodegradation rate constant ($k_{bio}$) and half-life ($t_{1/2}$) in BAC were decreased from $1.173min^{-1}$ to $0.183min^{-1}$ and 0.591 min to 3.787 min respectively according to increasing the $H_2O_2$ concentration from 10 mg/L to 300 mg/L at $5^{\circ}C$ water temperature and the $k_{bio}$ and $t_{1/2}$ were $1.510min^{-1}$ to $0.498min^{-1}$ and 0.459 min to 1.392 min at $25^{\circ}C$ water temperature. By increasing the water temperature from $5^{\circ}C$ to $15^{\circ}C$ or $25^{\circ}C$, the $k_{bio}$ were increased 1.1~2.1 times and 1.3~4.4 times. If a water treatment plant operating $O_3/BAC$ process is considering the hydrogen peroxide for the peroxone process, post BAC could effectively decrease the residual $H_2O_2$, moreover, in case of spilling the $H_2O_2$ into the water process line, these spilled $H_2O_2$ concentration can be able to decrease by increasing the EBCT at the BAC process.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.721-732
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• 2017

With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Applied Biological Chemistry
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• v.50 no.4
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• pp.295-303
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• 2007

A preliminary diet experiment utilizing Jerusalem artichoke's inulin, lotus leaf powder, nettle powder and eucalyptus powder extract indicated that combining all four elements gave the most effective result. Therefore, a study was conducted to evaluate the effectiveness of combined diet for weight loss. In this study, Sprague-Dawley, male white rats about 200 g in weight was fed with high fat diet for 8 weeks in order to induce obesity followed by 4 week administration of combined diet to look into the effect of the diet. After a total of 12 weeks of feeding, factors relevant to weight, blood, and lipid metabolism by liver in the body were researched and histologic change was examined with optical microscope. In terms of weight change, both high fat diet group and regular diet group gained weight from high fat diet for 8 weeks compared to normal group. Then, for another 4 weeks, while normal group and high fat diet group kept gaining weight, combined diet group which was provided with high fat diet for 8 weeks, lost weight to the normal group level after 3 week administration of diet. However, after the 4th week of administration, the group weighted significantly less than the normal group and the efficiency of diet also significantly dropped. In the biochemical analysis of blood, total cholesterol, LDL-cholesterol, triglyceride, glucose, GOT, GPT, ${\gamma}-GTP$ and creatine showed significant increase in high fat diet group and there was no significant difference between diet group and normal group except for GPT, ${\gamma}-GTP$ and creatine. In the biochemical analysis of liver, there was significant increase in LDL-cholesterol, triglyceride of high fat diet group compared to normal group, while there was no significant difference in term of total cholesterol and HDL-cholesterol. Compared to normal group, diet group had higher HDL-cholesterol, while total cholesterol dropped significantly. There was no significant difference in terms of LDL-cholesterol and triglyceride. Besides, in high fat diet group, observation of histologic change in liver and change in ultrastructure showed volume increase of hepatic cell and severe fatty degeneration in hepatic cell around hepatic vein. However in diet group, like normal group, no pathological change was observed in terms of cytoplasm, nucleus and capillary in hepatocyte and the alignment of hepatocyte had regularity thanks to the administration of combined diet. Therefore, combined diet utilizing Jerusalem artichoke's inulin, lotus leaf powder, nettle powder and eucalyptus powder was proven to be an effective measure to prevent and improve obesity as a result of abnormal adipose deposition.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.37-68
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• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.

• Korean Chemical Engineering Research
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• v.43 no.1
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• pp.153-160
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• 2005

There have been large areas of soil contaminated with high levels of explosives. For this experimental work, 2,4,6-trinitrotoluene (TNT) was tested as a representative explosive contaminant of concern in both aqueous and soil samples and its removal was evaluated using three different chemical treatment methods: 1) the classical Fenton reaction which utilizes hydrogen peroxide ($H_2O_2$) and soluble iron at pH less than 3; 2) a modified Fenton reaction which utilizes chelating agents, $H_2O_2$, and soluble iron at pH 7; and 3) a Fenton-like process which utilizes iron minerals instead of soluble iron and $H_2O_2$, generating a hydroxyl radical. Using classic Fenton reaction, 93% of TNT was removed in 20 h at pH 3 (soil spiked with 300 mg/L of TNT, 3% $H_2O_2$ and 1mM Fe(III)), whereas 21% removed at pH 7. The modified Fenton reaction, using nitrilotriacetic acid (NTA), oxalate, ethylenediaminetetraacetic acid (EDTA), acetate and citrate as representative chelating agents, was tested with 3% $H_2O_2$ at pH 7 for 24 h. Results showed the TNT removal in the order of NTA, EDTA, oxalate, citrate and acetate, with the removal efficiency of 87%, 71%, 64%, 46%, and 37%, respectively, suggesting NTA as the most effective chelating agent. The Fenton-like reaction was performed with water contaminated with 100 mg/L TNT and soil contaminated with 300 mg/L TNT, respectively, using 3% $H_2O_2$ and such iron minerals as goethite, magnetite, and hematite. In the goethite-water system, 33% of TNT was removed at pH 3 whereas 28% removed at pH 7. In the magnetite-water system, 40% of TNT was removed at pH 3 whereas 36% removed at pH 7. In the hematite-water system, 40% of TNT was removed at pH 3 whereas 34% removed at pH 7. For further experiments combining the modified Fenton reaction with the Fenton-like reaction, NTA, EDTA, and oxalate were selected with the natural iron minerals, magnetite and hematite at pH 7, based on the results from the modified Fenton reaction. As results, in case magnetite was used, 79%, 59%, and 14% of TNT was removed when NTA, oxalate, and EDTA used, respectively, whereas 73%, 25%, and 19% removed in case of hematite, when NTA, oxalate, and EDTA used, respectively.