• Korean Journal of Food Science and Technology
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• v.29 no.3
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• pp.502-508
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• 1997

Rice bran dietary fiber extract, which was obtained after termamyl treatment of defatted rice bran contained $27.3{\sim}30.5%$ protein, $49.7{\sim}54.1%$ insoluble dietary fiber, and $1.9{\sim}2.7%$ soluble dietary fiber. Extrusion decreased the insoluble dietary fiber content but increased the soluble dietary fiber content, while roasting did not. Influence those content. Each mineral element content was depended upon heat processing method. Extrusion increased the water binding capacity and L value, while roasting reduced the water binding capacity and L value. Scanning electron microscopy showed damaged cell walls for extruded sample compared to roasted one which had fully collapsed cell walls. The increase of water absorption, developing time, and stability and the of MTI of wheat flour-dietary fiber extract composites with addition of dietary fiber extract were observed by Farinograph. Rice bran dietary fiber extract had an effect on the bread making resulting in increase of bread weight and color of crumb and crust, and decrease of bread volume and texture. As a result of sensory evaluation, appearance, texture, overall acceptability were significantly different from control but flavor and taste were not different significantly up to 6% level. Heat treated samples had differences in mean values, but not significant differences statistically.

• Progress in Medical Physics
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• v.16 no.1
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• pp.10-15
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• 2005

IAEA's guidance levels have been provided for western people to the end. Guidance levels lower than the IAEA'S will be necessary in view of Korean people's proportions. Therefore, we need to develope the standard doses for Korean people. And we conducted a nationwide survey of patient dose from x-ray examinations in Korea. In this study, the 278 institutions were selected from Members Book of Korean Hospital Association. The valid response rate was approximately 57.9%. Doses were calculated from the questionnaires by NDD method. We obtained the results were as follows; 1) General radiographic equipments were distributed for 42.0%, fluoroscopic equipments 29.4%, dental equipments 13.2%, CT units 8.1 % and mamographic units 7.2%. 2) According to classification by rectification, three-phase equipments were 29.9%, inverter-type generators 29.5%, single-phase equipments 25.5%, constant voltage units 9.0% and unknown units 6.0%. 3) According to classification by receptor system, film-screen types were 46.8%, CR types 26.8%, DR types 17.7% and unknown types 8.9%. 4) The number of examinations were chest 49.2%, spine 16.8% and abdomen 12.7%. 5) Patient doses were head AP 3.44 mGy, abdomen AP 4.25 mGy and chest PA 0.39 mGy.

• Journal of Animal Science and Technology
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• v.44 no.5
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• pp.585-592
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• 2002

This study was conducted to investigate the effect of nutrient level (metabolizable energy and crude protein, 2,843kcal/kg and 19.46% at 2 to 3 week, 3,072kcal/kg and 18.38% at 4 to 6 week, 3,109 kcal/kg and 17.26% at 7 to 8week, respectively, and feeding form was ground $\longrightarrow$ crumble $\longrightarrow$ pellet in control, ground $\longrightarrow$ crumble $\longrightarrow$ pellet in treatment 1, crumble $\longrightarrow$ crumble $\longrightarrow$ pellet in treatment 2, pellet $\longrightarrow$ pellet $\longrightarrow$ pellet in treatment 3 for broiler during 8 weeks. Also the effects of supplemented with charcoal(1%) in total mixed treatment feed was investigated. The crude protein, crude fat in broiler meat ranged from 22.22${\sim}$23.40%, and 0.30${\sim}$0.45%, respectively. Especially, treatment 2 was lower than other treatment (P<0.05). The heating loss tend to be increased at control. Shear force and pH tend to be decreased at T3(1.21kg, 5.89). Control and T2 were significantly lighter in color (‘L’) than the T1 and the ‘a’ ranged from 0.19${\sim}$0.85 and T1 was the lowest ‘b’ among other treatment. The panel test, texture, Aroma were not significantly among the an experimental group (P<0.05). Myristic acid and arachidonic acid of T1 was significantly higher than that other treatment and oleic acid, U/S(unsaturated/ saturated) rate T2 was significantly higher than other experimental group(P<0.05). Among amino acid, cystine, glutamic acid, valine, iso-leucine, leucine, lysine, arginine in T1 and T2 was higher than control and T3.

• The Korean Journal of Nuclear Medicine
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• v.36 no.1
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• pp.1-7
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• 2002

Positron Emission Tomography (PET) is a nuclear medicine imaging modality that consists of systemic administration to a subject of a radiopharmaceutical labeled with a positron-emitting radionuclide. Following administration, its distribution in the organ or structure under study can be assessed as a function of time and space by (1) defecting the annihilation radiation resulting from the interaction of the positrons with matter, and (2) reconstructing the distribution of the radioactivity from a series of that used in computed tomography (CT). The nuclides most generally exhibit chemical properties that render them particularly desirable in physiological studies. The radionuclides most widely used in PET are F-18, C-11, O-15 and N-13. Regarding to the number of the current PET Centers worldwide (based on ICP data), more than 300 PET Centers were in operation in 2000. The use of PET technology grew rapidly compared to that in 1992 and 1996, particularly in the USA, which demonstrates a three-fold rise in PET installations. In 2001, 194 PET Centers were operating in the USA. In 1994, two clinical and research-oriented PET Centers at Seoul National University Hospital and Samsung Medical Center, was established as the first dedicated PET and Cyclotron machines in Korea, followed by two more PET facilities at the Korea Cancer Center Hospital, Ajou Medical Center, Yonsei University Medical Center, National Cancer Center and established their PET Center. Catholic Medical School and Pusan National University Hospital have finalized a plan to install PET machine in 2002, which results in total of nine PET Centers in Korea. Considering annual trends of PET application in four major PET centers in Korea in Asan Medical Center recent six years (from 1995 to 2000), a total of 11,564 patients have been studied every year and the number of PET studies has shown steep growth year upon year. We had 1,020 PET patients in 1995. This number increased to 1,196, 1,756, 2,379, 3,015 and 4,414 in 1996,1997,1998,1999 and 2000, respectively. The application in cardiac disorders is minimal, and among various neuropsychiatric diseases, patients with epilepsy or dementia can benefit from PET studios. Recently, we investigated brain mapping and neuroreceptor works. PET is not a key application for evaluation of the cardiac patients in Korea because of the relatively low incidence of cardiac disease and less costly procedures such as SPECT can now be performed. The changes in the application of PET studios indicate that, initially, brain PET occupied almost 60% in 1995, followed by a gradual decrease in brain application. However, overall PET use in the diagnosis and management of patients with cancer was up to 63% in 2000. The current medicare coverage policy in the USA is very important because reimbursement policy is critical for the promotion of PET. In May 1995, the Health Care Financing Administration (HCFA) began covering the PET perfusion study using Rubidium-82, evaluation of a solitary pulmonary nodule and pathologically proven non-small cell lung cancer. As of July 1999, Medicare's coverage policy expanded to include additional indications: evaluation of recurrent colorectal cancer with a rising CEA level, staging of lymphoma and detection of recurrent or metastatic melanoma. In December of 2001, National Coverage decided to expand Medicare reimbursement for broad use in 6 cancers: lung, colorecctal, lymphoma, melanoma, head and neck, and esophageal cancers; for determining revascularization in heart diseases; and for identifying epilepsy patients. In addition, PET coverage is expected to further expand to diseases affecting women, such as breast, ovarian, uterine and vaginal cancers as well as diseases like prostate cancer and Alzheimer's disease.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.1-14
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• 2008

According to technology acceptance model(TAN) which is one of the most important research models for explaining IT users' behavior, on intention of using IT is determined by usefulness and ease of use of it. However, TAM wouldn't explain the performance of using IT while it has been considered as a very good model for prediction of the intention. Many people would not be confirmed in the performance of using IT until they can control it at their will, although they think it useful and easy to use. In other words, in addition to usefulness and ease of use as in TAM, controllability is also should be a factor to determine acceptance of IT. Especially, there is a very close relationship between controllability and ease of use, both of which explain the other sides of control over the performance of using IT, so called perceived behavioral control(PBC) in social psychology. The objective of this study is to identify the relationship between ease of use and controllability, and analyse the effects of both two beliefs over performance and intention in using IT. For this purpose, we review the issues related with PBC in information systems studies as well as social psychology, Based on a review of PBC, we suggest a research model which includes the relationship between control and performance in using IT, and prove its validity empirically. Since it was introduced as qa variable for explaining volitional control for actions in theory of planned behavior(TPB), there have been confusion about concept of PBC in spite of its important role in predicting so many kinds of actions. Some studies define PBC as self-efficacy that means actor's perception of difficulty or ease of actions, while others as controllability. However, this confusion dose not imply conceptual contradiction but a double-faced feature of PBC since the performance of actions is related with both self-efficacy and controllability. In other words, these two concepts are discriminated and correlated with each other. Therefore, PBC should be considered as a composite concept consisting of self-efficacy and controllability, Use of IT has been also one of important areas for predictions by PBC. Most of them have been studied by analysis of comparison in prediction power between TAM and TPB or modification of TAM by inclusion of PBC as another belief as like usefulness and ease of use. Interestingly, unlike the other applications in social psychology, it is hard to find such confusion in the concept of PBC in the studies for use of IT. In most of studies, controllability is adapted as PBC since the concept of self-efficacy is included in ease of use explicitly. Based on these discussions, we can suggest perceived use control(PUC) which is defined as perception of control over the performance of using IT and composed of controllability and ease of use as sub-concepts. We suggest a research model explaining acceptance of IT which includes the relationships of PUC with attitude and performance of using IT. For empirical test of our research model, two user groups are selected for surveying questionnaires. In the first group, there are freshmen who take a basic course for Microsoft Excel, and the second group consists of senior students who take a course for analysis of management information by Excel. Most of measurements are adapted ones that have been validated in the other studies, while performance is real score of mid-term in each class. In result, four hypotheses related with PUC are supported statistically with very low significance level. Main contribution of this study is suggestion of PUC through theoretical review of PBC. Specifically, a hierarchical model of PUC are derived from very rigorous studies in the relationship between self-efficacy and controllability with a view of PBC in social psychology. The relationship between PUC and performance is another main contribution.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• KDI Journal of Economic Policy
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• v.13 no.1
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• pp.115-134
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• 1991

The role of pension plans in the macroeconomy has been a subject of much interest for some years. It has come to be recognized that pension plans may alter basic macroeconomic behavior patterns. The net effects on both savings and labor supply are thus matters for speculation. The aim of the present paper is to provide quantitative results which may be helpful in attaching orders of magnitude to some of the possible effects. We are not concerned with the providing empirical evidence relating to actual behavior, but rather with deriving the macroeconomic implications for a alternative possibilities. The pension plan interacts with the economy and the population in a number of ways. Demographic variables may thus affect both the economic burden of a national pension plan and the ability of the economy to sustain the burden. The tax transfer process associated with the pension plan may have implications for national patterns of saving and consumption. The existence of a pension plan may have implications also for the size of the labor force, inasmuch as labor force participation rates may be affected. Changes in technology and the associated changes in average productivity levels bear directly on the size of the national income, and hence on the pension contribution base. The vehicle for the analysis is a hypothetical but broadly realistic simulation model of an economic- demographic system into which is inserted a national pension plan. All income, expenditure, and related aggregates are in real terms. The economy is basically neoclassical; full employment is assumed, output is generated by a Cobb-Douglas production process, and factors receive their marginal products. The model was designed for use in computer simulation experiments. The simulation results suggest a number of general conclusions. These may be summarized as follows; - The introduction of a national pension plan (funded system) tends to increase the rate of economic growth until cost exceeds revenue. - A scheme with full wage indexing is more expensive than one in which pensions are merely price indexed. - The rate of technical progress is not a critical element in determining the economic burden of the pension scheme. - Raising the rate of benefits affects its economic burden, and raising the age of eligibility may decrease the burden substantially. - The level of fertility is an element in determining the long-run burden. A sustained low fertility rate increases the proportion of the aged in total population and increases the burden of the pension plan. High fertility has inverse effects.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Wetlands Research
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• v.18 no.3
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• pp.301-312
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• 2016

This study has performed comparative analysis on characteristics of contaminated 35 tributaries on seasonal variation/point discharge load/pollutant distribution of water quality factors(8) in order to understand the effect of the watershed in Nakdong River Basin. As a results, the water quality of $BOD_5$(Biochemical Oxygen Demand), Chl-a(Chlorophyll a) and Fecal E. Coli shows II grade at tributaries of more than 50% without COD(Chemical Oxygen Demand), TP(Total Phosphate), TOC(Total Oxygen Carbon) and TN(Total Nitrogen) factors. The specific discharge(Q) were occupied about 54.4% (19 sites) as $0.05m^3/sec/km^2$ value. Among these results, the contaminant level of Dalseocheon, Hyeonjicheon, Seokkyocheon 1, Uriyeongcheon and Dasancheon was also high, which has to consider a discharged pollutant load(kg/day). The 35 major tributaries of Nakdong River were included in 7 mid-watershed, such as Nakdong Waegwan, Geumho River, Nakdong Goryung, Nakdong Changnyung, Nam River, Nakdong Milyang, Nakdong River Hagueon. Especially, the discharged pollutant load of Nam River and Geumho River also was high according to the amount of discharge such as Kachang dam, Gongsan dam and Nam river dam. Seasonal difference of the water quality factors such as $BOD_5$, TN, SS and Q was observed largely, on the other hand the TP and Chl-a was not. This is guessed due to the precipitation effect of site, biological and physicochemical degradation properties of pollutant and etc. The co-relationship between the seasonal difference and water quality factors was observed using a Pearson correlation coefficients. Besides, the Multiple Regression analysis using a Stepwise Regression method was conducted to understand the effect between seasonal difference and water quality factors/regression equations. As a result, the Multiple Regression analysis was adapted in the spring, summer and autumn without the winter, which was observed high at spring, summer and autumn in the order COD/TP, Chl-a/TOC, TOC/COD/$BOD_5$ water quality factors, respectively.

• Journal of the Korean Society of Radiology
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• v.18 no.4
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• pp.327-334
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• 2024

The purpose of this study is to develop a customized foot disease analysis and management system for diabetic patients to prevent foot ulcers in diabetic foot disease patients. This system utilizes image analysis technology to measure not only foot pressure, but also ankle deformation, body balance, and foot wounds. Through various data, it is possible to accurately analyze the state of foot deformation, and based on this, the exact state of deformation of the foot of a patient with diabetic foot disease was identified and a customized insole was produced. This study was conducted to examine the satisfaction level of using an application that checks the status of diabetic foot disease wounds and to identify the degenerative status of diabetic foot disease patients and foot disease patients by wearing customized insoles and to survey the satisfaction of wearing insoles. As a result of the study, the knee angle measured for plantar pressure was -0.8 ± 1.3 degrees and ranged from a minimum of -2.4 degrees to a maximum of 1.1 degrees, and there was no significant difference in valgus knee between both lower extremities (p = 0.534). There was a significant difference in tibial angle between both lower extremities (p < 0.001). Ankle angle on the left side was 2.6 ± 2.0 degrees, ranging from a minimum of 0 degrees to a maximum of 6.3 degrees, and on the right, it was 4.5 ± 2.1 degrees, with a distribution of minimum 1.5 degrees to a maximum of 9.1 degrees. There was a significant difference in ankle angle between both lower extremities (p = 0.011). They responded that they felt an average of 4.3 points of satisfaction with the plantar pressure measurement application. Respondents responded that they felt an average of 3.9 points of satisfaction with the use of customized insoles.