• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.249-263
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• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.

• Proceedings of the KACD Conference
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• 2008.05a
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• pp.169-176
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• 2008

The purpose of this study was to evaluate the effect of thickness, filling methods and curing methods on the polymerization of dual cured core materials by means of microhardness test. Two dual cured core materials, MultiCore Flow (Ivoclar Vivadent AG, Schaan, Liechtenstein) and Bis-Core (Bisco Inc., Schaumburg, IL, USA) were used in this study. 2 mm (bulky filled), 4 mm (bulky filled), 6 mm (bulky and incrementally filled) and 8 mm (bulky and incrementally filled)-thickness specimens were prepared with light cure or self cure mode. After storage at $37^{\circ}C$ for 24 hours, the Knoop hardness values (KHN) of top and bottom surfaces were measured and the microhardness ratio of top and bottom surfaces was calculated. The data were analyzed using one-way ANOVA and Scheffe multiple comparison test, with ${\alpha}=0.05$. The effect of thickness on the polymerization of dual cured composites showed material specific results. In 2, 4 and 6 mm groups, the KHN of two materials were not affected by thickness. However, in 8 mm group of MultiCore Flow, the KHN of the bottom surface was lower than those of other groups (p < 0.05). The effect of filling methods on the polymerization of dual cured composites was different by their thickness or materials. In 6 mm thickness, there was no significant difference between bulk and incremental filling groups. In 8 mm thickness, Bis-Core showed no significant difference between groups. However, in MultiCore Flow, the microhardness ratio of bulk filling group was lower than that of incremental filling group (p < 0.05). The effect of curing methods on the polymerization of dual cured composites showed material specific results. In Bis-Core, the KHN of dual cured group were higher than those of self cured group at both surfaces (p < 0.05). However, in MultiCore Flow, the results were not similar at both surfaces. At the top surface, dual cured group showed higher KHN than that of self cured group (p < 0.05). However, in the bottom surface, dual cured group showed lower value than that of self cured group (p < 0.05).

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.4
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• pp.215-221
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• 2022

This study was carried out to investigate the growth characteristics, yield and chemical compositions of rye according to mixing ratio of chemical fertilize r(CF) and liquid swine manure (LSM) in paddy field cultivation. The experimental design was arranged in a randomized block design with three replications. The manure fertilizer ratio of five treatments were CF 100% + LSM 0% (C), CF 70% + LSM 30% (T1), CF 50% + LSM 50% (T2), CF 30% + LSM 70% (T3), and CF 0% + LSM 100% (T4) of rye. At this time, the application of liquid swine manure was based solely on nitrogen. Plant length did not show significant differences among treatments. Ear length, leaf length and leaf width were the longest in C, T3, and T2, respectively (p<0.05). The stem diameter showed in the order of T4 > T3 > T2 > T1 > C, which was thicker as the LSM application rate increased (p<0.05). Fresh, dry matter and total digestible nutrient (TDN) yield were the highest in T4 (p<0.05), whereas the lowest in C treatment. Crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF) and crude fiber content were did not show significant difference among treatments. However, compared to C, crude fat and crude ash were significantly higher in T2 and T3, respectively (p<0.05). Total mineral content decreased significantly as the LSM application rate increased (p<0.05). Total free sugar showed high in T3 and T4 with a high LSM ratio, but showed significantly lower in chemical fertilizer treatment (C) and low LSM treatment (T1) (p<0.05). The analysis of all the above results suggests that the application of LSM is very effective, considering the dry matter yield and the contents of free sugar. In addition, LSM may be possible to grow rye without chemical fertilizer.

• Journal of Nutrition and Health
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• v.56 no.1
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• pp.54-69
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• 2023

Purpose: Proteins are major components of the body and essential nutrients for proper growth and development. However, studies on protein intake in children and adolescents are insufficient. A few previous studies have reported the relationship with growth indicators, but results vary depending on the source of protein. Therefore, the current study investigates the relationship between protein intake and overweight and obesity among children and adolescents in Korea. Methods: Based on the 2014-2019 Korea National Health and Nutrition Examination Survey, 5,567 children and adolescents aged 6-18 years, who participated in a 24-hour dietary recall with information on height and weight, were included in this study. Protein intake was estimated as percentage of total energy (% of energy) and was classified into animal and plant protein according to the food source. Overweight and obesity were defined using the 2017 pediatric and adolescent growth chart. Results: Total protein intake of the subjects was estimated as 14.5% of total energy (animal protein 8.3% and plant protein 6.3%). The group with the highest total protein intake had a higher odds ratio (OR) of overweight/obesity than those with the least protein intake (OR, 1.36, 95% confidence interval (CI), 1.10-1.67, p for trend = 0.003). When classified by food source, the group with the highest animal protein intake had a significantly higher OR of overweight/obesity than subjects with the lowest intake (OR, 1.30, 95% CI, 1.05-1.61, p for trend = 0.016). However, plant protein was not significantly associated with overweight/obesity. Conclusions: These findings suggest that a high intake of animal protein in children and adolescents increases the risk of being overweight and obese. In order to develop normal growth and prevent obesity in the future, it is necessary to determine an appropriate protein intake level through nutrition education programs and prospective studies on balanced protein intake.

• Korean journal of applied entomology
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• v.61 no.4
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• pp.605-614
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• 2022

Two major problems currently threaten human survival on Earth: climate change and the rapid aging of the population in developed countries. Climate change is a result of the increase in greenhouse gas (GHG) concentrations in the atmosphere due to the increase in the use of fossil fuels owing to economic and transportation development. The rapid increase in the age of the population is a result of the rise in life expectancy due to the development of biomedical science and technology and the improvement of personal hygiene in developed countries. To avoid irreversible global climate change, it is necessary to quickly transition from the current fossil fuel-based economy to a zero-carbon renewable energy-based economy that does not emit GHGs. To achieve this goal, the dairy and livestock industry, which generates the most GHGs in the agricultural sector, must transition to using low-carbon emission production methods while simultaneously increasing consumers' preference for low-carbon diets. Although 77% of currently available arable land globally is used to produce livestock feed, only 37% and 18% of the proteins and calories that humans consume come from dairy and livestock farming and industry. Therefore, using edible insects as a protein source represents a good alternative, as it generates less GHG and reduces water consumption and breeding space while ensuring a higher feed conversion rate than that of livestock. Additionally, utilizing the functionality of medicinal insects, such as silkworms, which have been proven to have certain health enhancement effects, it is possible to develop functional foods that can prevent or delay the onset of currently incurable degenerative diseases that occur more frequently in the elderly. Insects are among the first animals to have appeared on Earth, and regardless of whether humans survive, they will continue to adapt, evolve, and thrive. Therefore, the use of various edible and medicinal insects, including silkworms, in industry will provide an important foundation for human survival and prosperity on Earth in the near future by resolving the current two major problems.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.75-82
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• 2023

Data for measuring the flow rate of streams are used as important basic data for the development and maintenance of water resources, and many experts are conducting research to make more accurate measurements. Especially, in Korea, monsoon rains and heavy rains are concentrated in summer due to the nature of the climate, so floods occur frequently. Therefore, it is necessary to measure the flow rate most accurately during a flood to predict and prevent flooding. Thus, the U.S. Geological Survey (USGS) introduces 1, 2, 3 point method using a flow meter as one way to measure the average flow rate. However, it is difficult to calculate the average flow rate with the existing 1, 2, 3 point method alone.This paper proposes a new 1, 2, 3 point method formula, which is more accurate, utilizing one probabilistic entropy concept. This is considered to be a highly empirical study that can supplement the limitations of existing measurement methods. Data and Flume data were used in the number of holesman to demonstrate the utility of the proposed formula. As a result of the analysis, in the case of Flume Data, the existing USGS 1 point method compared to the measured value was 7.6% on average, 8.6% on the 2 point method, and 8.1% on the 3 point method. In the case of Coleman Data, the 1 point method showed an average error rate of 5%, the 2 point method 5.6% and the 3 point method 5.3%. On the other hand, the proposed formula using the concept of entropy reduced the error rate by about 60% compared to the existing method, with the Flume Data averaging 4.7% for the 1 point method, 5.7% for the 2 point method, and 5.2% for the 3 point method. In addition, Coleman Data showed an average error of 2.5% in the 1 point method, 3.1% in the 2 point method, and 2.8% in the 3 point method, reducing the error rate by about 50% compared to the existing method.This study can calculate the average flow rate more accurately than the existing 1, 2, 3 point method, which can be useful in many ways, including future river disaster management, design and administration.

• Journal of Nutrition and Health
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• v.56 no.4
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• pp.439-453
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• 2023

Purpose: Concerns about accelerated aging are regularly being discussed. This study analyzed the dietary status and nutritional intake of college students who are about to enter their 30s and 40s. We further suggest ways to eat healthily. Methods: Totally, 67 students attending Daegu Catholic University were provided with a three-day meal record and analyzed. Results: The average demographics of the subjects were as follows: age 23.2 ± 2.0 years, height 165.1 ± 9.0 cm, weight 65.4 ± 13.6 kg, and BMI 23.5 ± 3.9 kg/m². Overall, 76.3% of the subjects skipped breakfast. The food intake evaluation according to the food group intake pattern and the recommended number of servings determined that 38.3% of the subjects did not consume fruits and dairy products (GMVFDS = 111001), and both men and women lacked all food groups. Analysis of the nutrient intake state revealed lesser nutrient intake than the estimated energy need. Evaluation of the %RDA found that consumption of phosphorus was above the recommended amount, whereas all other nutrients were below the recommended amount. Men had a higher intake rate of phosphorus (p < 0.01), iron (p < 0.001), and sodium (p < 0.05) than women, whereas the intake rate of dietary fiber was higher in women (p < 0.05). Evaluation of the food intake by 22 food categories revealed that intake of regular grains was more in men than in women (p < 0.05) whereas women consumed significantly more mixed grains (p< 0.01). In protein foods, men consumed more meat (p < 0.01), while women consumed more eggs (p < 0.05) and beans (p < 0.05). Evaluating the fruit intake, juices were more frequently consumed by men than by women (p < 0.05). No differences were obtained in food intake and nutrient intake status according to obesity. Conclusion: Based on these results, there is an urgent requirement for attention and support for university cafeterias in order to induce changes in the eating habits of college students. Among other initiatives, this can be achieved by providing diet improvement programs and menus that consider food preferences.

• Journal of Technology Innovation
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• v.31 no.1
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• pp.29-63
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• 2023

The purpose of this study is to analyze the process of changes in regional science and technology policies in Korea and to seek future development directions. In Korea, regional science and technology policies have been implemented since the introduction of the local autonomy system. Since then, it has been implemented in earnest with the establishment of a central government-level plan. The regional science and technology policies have been developed to this day by interacting with national science and technology policies and regional development policies. Nevertheless, due to the path dependence and lock-in effect in the accumulated process, the regional science and technology policies are still subordinate to central government policies. Thus, the establishment of an independent ecosystem for local science and technology is still insufficient. Furthermore, the gap between regions is deepening, such as the growing of aging population, population decline due to low birth rates, job losses due to the recession of local key industry, and the concentration of the youth population in the metropolitan area. The transformation path such as digital transformation and carbon neutrality paradigm is expected to further widen regional disparities. In order to address a comprehensive problem, the implementing system of regional science and technology policies need to be newly established. A framework for reinvention of regional science and technology policy needed in the era of grand societal challenges have to be developed.

• Korean Journal of Environmental Biology
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• v.41 no.2
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• pp.109-125
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• 2023

This study was conducted to select target fish species as baseline research for accumulation analysis of major hazardous chemicals entering the aquatic ecosystem in Korea and to analyze the impact on fish community. The test bed was selected from a sewage treatment plant, which could directly confirm the impact of the inflow of harmful chemicals, and the Geum River estuary where harmful chemicals introduced into the water system were concentrated. A multivariable metric model was developed to select target candidate fish species for hazardous chemical analysis. Details consisted of seven metrics: (1) commercially useful metric, (2) top-carnivorous species metric, (3) pollution fish indicator metric, (4) tolerance fish metric, (5) common abundant metric, (6) sampling availability (collectability) metric, and (7) widely distributed fish metric. Based on seven metric models for candidate fish species, eight species were selected as target candidates. The co-occurring dominant fish with target candidates was tolerant (50%), indicating that the highest abundance of tolerant species could be used as a water pollution indicator. A multi-metric fish-based model analysis for aquatic ecosystem health evaluation showed that the ecosystem health was diagnosed as "bad conditions". Physicochemical water quality variables also influenced fish feeding and tolerance guild in the testbed. Eight water quality parameters appeared high at the T1 site, indicating a large impact of discharging water from the sewage treatment plant. T2 site showed massive algal bloom, with chlorophyll concentration about 15 times higher compared to the reference site.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.