• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.3
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• pp.271-279
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• 2012

Total twenty cultivars of potato (Solanum tuberosum L.) were grown at Gangneung where is located in low land of Korea. Their tubers were harvested from 100 to 120 days after planting, and over 150 g of tubers were selected for quality evaluation. Dry matter, starch, amylose in starch, ascorbic acid, protein, individual sugars and mineral were analyzed and mealiness of cooked potatoes were also evaluated by panel test. Dry mater content was the highest in 'Haryeong', 'Jayoung' and 'Shepody', and the biggest starch granules were observed in 'Jayoung' and 'Sinnamjak'. In addition, the content of amylose was highest in 'Haryeong', 'Chudong' and 'Goun'. Mineral content showed the slight difference between cultivars, but it's tendency was not clear. Vitamin C content was highest in 'Jayoung' as 62.5 $mg{\cdot}100g^{-1}$ FW, and 'Chugang' exhibited the highest content of protein. Sugar content was lower in cultivars for single one than double cropping. The lowest sugar content was observed in 'Atlantic' and 'Namseo' among cultivars for single cropping, and in 'Goun' for double cropping. As a result of analysis for quality factors, we could select nine cultivars ('Atlantic', 'Gahwang', 'Gawon', 'Goun', 'Hareong', 'Irish Cobbler', 'Jasim', 'Jayoung' and 'Shepody') with high dry matter content and low reducing sugar as a cultivar group for processing. Additionally, seven cultivars ('Chugang', 'Gawon', 'Goun', 'Hareong', 'Irish Cobbler', 'Jasim' and 'Seohong') with high mealiness and amylose content and five cultivars ('Atlantic', 'Chudong', 'Gahwang', 'Jopung' and 'Jowon') with low mealiness and amylose content were classified as groups for boiled or steam cooking and for soup or pot dishes, respectively.

• Journal of Food Hygiene and Safety
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• v.31 no.4
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• pp.227-249
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• 2016

Arsenic and its compounds vary in their toxicity according to the chemical forms. Inorganic arsenic is more toxic and known as carcinogen. The provisional tolerable weekly intake (PTWI) of $15{\mu}g/kg$ b.w./week established by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) has been withdrawn, while the EFSA panel suggested $BMDL_{0.1}$ $0.3{\sim}8{\mu}g/kg\;b.w./day$ for cancers of the lung, skin and bladder, as well as skin lesions. Rice, seaweed and beverages are known as food being rich in inorganic arsenic. As(III) is the major form of inorganic arsenic in rice and anaerobic paddy soils, while most of inorganic arsenic in seaweed is present as As(V). The inorganic arsenic in food was extracted with solvent such as distilled water, methanol, nitric acid and so on in heat-assisted condition or at room temperature. Arsenic speciation analysis was based on ion-exchange chromatography and high-performance liquid chromatography equipped with atomic absorption spectrometry and inductively coupled plasma mass spectrometry. However, there has been no harmonized and standardized method for inorganic arsenic analysis internationally. The inorganic arsenic exposure from food has been estimated to range of $0.13{\sim}0.7{\mu}g/kg$ bw/day for European, American and Australian, and $0.22{\sim}5{\mu}g/kg$ bw/day for Asian. The maximum level (ML) for inorganic arsenic in food has established by EU, China, Australia and New Zealand, but are under review in Korea. Until now, several studies have conducted for reduction of inorganic arsenic in food. Inorganic arsenic levels in rice and seaweed were reduced by more polishing and washing, boiling and washing, respectively. Further research for international harmonization of analytical method, monitoring and risk assessment will be needed to strengthen safety management of inorganic arsenic of foods in Korea.

• Korean journal of food and cookery science
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• v.16 no.3
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• pp.267-271
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• 2000

The present study was designed to develop the standardized formula for the preparation Jeung-Pyun with added raw soy flour and to investigate the applicability of Jeung-Pyun as the substitute of regular pizza crust made with wheat flour. The effect of adding raw soy flour at 3%, 5% level on fermentation time and viscosity of batters and texture and general desirability of Jeung-Pyun pizza were also studied. As the level of raw soy flour was increased the time required for 1 st and 2nd fermentation decreased and viscosity of batters increased significantly. Jeung-Pyun crust after steaming found to have appropriate texture and form for a substitute of wheat flour pizza crust. Texture parameters determined by QST showed that Jeung-Pyun crust with added raw soy flour had lower values in hardness, cohesiveness and gumminess without any significant difference. However, chewiness of 5% raw soy flour group was significantly lower than control group. Texture of Jeung-Pyun crust and general desirability of Jeung-Pyun pizza were determined by sensory evaluation. Textural parameters of Jeung-Pyun crust were evaluated on the basis of hardness, cohesiveness, adhesiveness, tenderness and wetness. As a result of sensory evaluation Jeung-Pyun crust made with 5% raw soy flour had significant lower values in hardness, cohesiveness, tenderness and wetness than the control. However, the textural parameters between control and 3 % raw soy flour group were not significantly different. Jeung-Pyun pizza with topping were evaluated by sensory panel. Jeung-Pyun pizza made with 3% raw soy flour received the highest score in apperance and general desirability without any significant difference. 5% raw soy flour group had significantly lower score in general desirability among 3 treatment groups. In conclusion, Jeung-Pyun crust made by traditional Jeung-Pyun preparation method will be a good alternative to replace wheat flour pizza crust. Adding raw soy flour at 3% level did not affect the quality of Jeung-Pyun crust and had an effect of promoting fermentation. Jeung-Pyun Pizza crust was expected to have tender texture and slower retrogradation rate than regular pizza crust with wheat flour.

• Journal of Korea Technology Innovation Society
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• v.10 no.4
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• pp.654-686
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• 2007

To estimate and analyze an interested science and technology level in any case requires three basic informations: (1) relative positions of our technology level, (2) other relevant technology level of the world best country holding the state of the art technology, and (3) its theoretical or practical maximum level within a certain period of time. Further, additional information from analyzing its respective rate of technology changes is necessary. It seems that most previous empirical or case studies on technology level have not considered third and fourth informations seriously, and thus critically have missed important findings from a dynamic point of view on the matter. A dynamic approach considering types of development processes and paths as well as current position needs an application of a concept of technology development stages and respective growth curves. This paper proposes a new method of approach and application by implementing relatively simple types of the growth curve(S-curve) such as logistic and Comports curves and applying estimation results of these curves to ten core technologies of the growth engines for the next future generation in Korea. The study implies that Korean science and technology level in general clearly gets higher as it approaches to a recent time of period, but relative technology gap from the world best in terms of catching-up period does not get better or narrower in case of at least part of the concerned technologies such as bio new drugs and human organs, and intelligence robots. The possibility does exist that some of our concerned technologies shooting for the next future generation may not come to the world highest level in the near future. The purpose of this study is to propose possibilities of catching-up, if any, by estimating its relevant type of growth pattern by way of measuring and analyzing technology level and by analyzing the technology development process through a position analysis. At this stage this study tries to introduce a new theoretical approach of estimating technology level and its application to existing case study results(data) from Korea Institute of Science and Technology Planning and Evaluation(KISTEP) and Korea Institute of Industrial Technology Evaluation and Planing(ITEP), for years of 2004 and 2006 respectively. The study has some limitations in terms of accuracy of measuring(estimating) a relevant growth curve to a particular technology, feasibility of applying estimated results, accessing and analyzing panel experts opinions. Hence, it is recommended that further study would follow soon enough to verify practical applicability and possible expansion of the study results.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.6
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• pp.834-839
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• 2007

This study was designed to determine the optimal ratio of dropwort powder in castella by adding the powder at levels of 0, 3, 6, 9, and 12% respectively. The properties of the castella were analyzed by specific gravity, specific volume, color determinations, texture properties and sensory evaluation. The Specific gravity increased with increasing amount of dropwort powder. However, the specific volume decreased with increasing dropwort powder. For the color values, as more dropwort powder was added, the L-value decreased. The castella with 9% dropwort powder had a higher hardness, gumminess, and chewiness. A sensory panel perceived that the external and internal color of the castella become darker with the dropwort powder substitution and the grain size decreased with increasing amount dropwort powder, while sweet taste showed no significant difference. The order of overall preference was DP 9>DP 6>DP 12>CON>DP 3. Therefore, the substitution of 9% of wheat flour with dropwort powder was recommended in the production of castella.

• Korean Journal of Environment and Ecology
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• v.29 no.6
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• pp.936-946
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• 2015

This study is aimed to analyze the reduction performance of building energy consumption according to planting base types of panel-type green walls which can be applied to existing buildings. The performance was compared to the general performance of green walls that have demonstrated effects of improving the thermal environment and reducing building energy consumption in urban areas. The number of planting base types was 4 in total, and simulations were conducted to analyze the thermal conductivity, thermal transmittance, and overall building energy consumption rate of each planting base type. The highest thermal conductivity by the planting base type was Case C (0.053W/mK), followed by Case B (0.1W/mK) and Case D (0.17W/mK). According to the results of energy simulation, the most significant reduction of cooling peak load per unit area was Case C (1.19%), followed by Case B (1.14%) and Case D (1.01%) when compared to Case A to which green wall was not applied; and the most significant reduction of heating peak load per unit area was estimated to be Case C (2.38%), followed by Case B (1.82%) and case D (1.50%) when compared to Case A. The amount of yearly cooling and heating energy use per unit area showed 3.04~3.22% of reduction rate. The amount of the 1st energy use showed 5,844 kWh/yr of decrease on average for other types when compared to Case A. The amount of yearly $CO_2$ emission showed 996kg of decrease on average when compared to Case A to which the green wall was not applied. According to the results of energy performance evaluation by planting location, the most efficient energy performance was eastward followed by westward, southward and northward. According to the results of energy performance evaluation by planting location by green wall ratio, it was found that as the ratio of green wall increased, the energy performance displayed better results, showing approx. double reduction rate in energy consumption at 100% of green wall ratio than the reduction rate at 20% to 80% of green wall ratio.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.6
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• pp.850-856
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• 2005

The sensory and safety of cook-chilled Buchu-jeon were evaluated to provide to foodservice operation during chilled storage for 5 days. The sensory evaluations of cook-chilled Buchu-jeon were conducted according to 3 reheating methods which was frying pan, steam/convection oven and microwave oven. The sensory evaluations were made on 4 sensory attributes (taste, odor, color, and texture) by a 9-member panel using quantitative descriptive analysis (QDA). The Buchu-jeon reheated in the steam/convection oven, after 1 day storage at $3^{\circ}C$, obtained higher score in taste, odor and texture than the ones reheated in a frying pan and microwave oven. Three reheating methods didn't show any difference in taste, odor, color, and texture of Buchu-jeon at $3^{\circ}C$ for 3 days. The Buchun-jeon reheated in microwave oven at $3^{\circ}C$ for 5 days had a significant $(p\leq0.05)$ lower score odor and color than the ones reheated in frying pan and steam/convection oven. The safety of Buchu-jeon was also evaluated by measuring total count, coliform count, psychrotrophic count, acid value and peroxide value during 5 days of storage periods at $4^{\circ}C$C. Total counts of Pajeon was ranged from $5.0\times10^{1}$ CFU/g to $2.2\times10^{2}$ CFU/g and the coliform and psychrotroph were not detected at most experiments. The acid values were ranged from 1.80 to 2.18 mg of KOH/g of fat until 5 days at $4^{\circ}C$. And the peroxide values were ranged from 4.44 to 17.87 meq of peroxide/kg of fat until 5 days of storage period. Therefore, these results demonstrated that the cook-chilled Buchu-jeon is microbiologically and chemically safe during 5 days of storage period at refrigeration temperature.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Journal of the Korea Concrete Institute
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• v.26 no.4
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• pp.429-440
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• 2014

Since the World Trade Center and Pentagon attacks in 2001, terror, military attack, or man-made disaster caused impact, explosion, and fire accident have frequently occured on civil infrastructures. However, structural behavior researches on major Prestressed Concrete (PSC) infrastructures such as bridges, tunnels, Prestressed Concrete Containment Vessel (PCCVs), and LNG tanks under extreme loading are significantly lacking. Especially, researches on possible secondary fire scenarios after terror, bombing, collision of vehicles and vessels on concrete structures have not been performed domestically where most of the past researches related to extreme loadings on structures focused on an independent isolated extreme loading scenario. Due to the outcry of public concerns and anxiety of potential terrorist attacks on major infrastructures and structures, a study is urgently needed at this time. Therefore, in this study, the bi-directional prestressed concrete $1400{\times}1000{\times}300mm$ panels applied with 430 kN prestressing force using unbonded prestressing thread bars were experimentally evaluated under impact, fire, and impact-fire combined loadings. Due to test site restrictions, impact tests were performed with 14 kN impactor with drop heights of 10m and 3.5 m to evaluate impact resistance capacity. Also, fire and impact-fire combined loading were tested using RABT fire loading curve. The measured residual strength capacities of PSC and RC specimens applied with impact, fire, impact-fire combined loadings were compared with the residual strength capacity of undamaged PSC and RC specimens for evaluation. The study results can be used as basic research data for related research areas such as protective design and numerical simulation under extreme loading scenarios.