• Journal of Nutrition and Health
• /
• v.54 no.5
• /
• pp.534-546
• /
• 2021

Purpose: This study aimed at understanding meal kit purchasing behavior and investigating its relationship with the Nutrition Quotient (NQ) of young adults. Methods: We conducted a survey on adults in their 20s and 30s covering their meal kit purchase experience, satisfaction, recognition, and purchase intention, and examined the relationship between the meal kit purchase and their NQ from February to March 2021. Results: Among the 404 subjects, 37.9% of males and 48.0% of females had experience in purchasing a meal kit (p < 0.001). The highest response indicated that the purchase cost of meal kits was 10,000-20,000 Won at a time, and the frequency of purchase was less than once a month. The convenience of cooking was the main reason for the purchase of meal kits, which were consumed mainly in the evening with family. The satisfaction with the purchase experience of a meal kit was rated 3.6 points for males and 3.7 points for females out of 5 points, and the satisfaction experienced by women was significantly higher than men in terms of freshness of ingredients, packaging design, and adequacy of the quantity of content (p < 0.05). Recognition of the meal kit was rated 3.5 points for males and 3.7 points for females out of 5 points. The purchase intention of the meal kit was rated 3.8 points for those with prior purchase experience, 3.2 points for the non-experienced, 3.3 points for males, and 3.6 points for females out of 5 points each (p < 0.001). The NQ score of dietary behavior in females with experience of meal kit purchases was significantly higher than non-experience (p < 0.05). Conclusions: The dietary behavior of female showed a significant difference by the meal kit purchase experience. It is necessary to understand the consumers' meal kit purchasing behavior to enable the development of various health-oriented meal kit products.

• Journal of Life Science
• /
• v.31 no.3
• /
• pp.287-297
• /
• 2021

Cornus officinalis Siebold & Zucc. is traditionally used as an edible and medicinal plant in many countries in East Asia. Previous studies have shown the pharmacological potential of extracts and components of C. officinalis, but comparative analysis of the composition of the leaf, stem, and fruit extracts has been insufficient to date. In the present study, the content of active antioxidant and anti-inflammatory ingredients was verified in different C. officinalis parts (under-ripe sansuyu, ripe sansuyu, seed, leaf, stem, and dried sansuyu). One active component, morroniside, was high in fruit (under-ripe and ripe sansuyu), while loganin was high in fruit (under-ripe sansuyu) and cornin was high in seeds. Total polyphenol contents were highest in fruit (ripe sansuyu) and flavonoids were highest in leaves. DPPH radical scavenging activity was highest in leaves, followed by seeds and then ripe sansuyu extract. The anti-inflammatory efficacy of leaf extracts of C. officinalis (LCO) was further investigated by measuring their effects on levels of nitric oxide (NO) and the pro-inflammatory cytokines interleukin (IL)-1β and IL-6 in RAW 264.7 macrophages. Non-cytotoxic concentrations of LCO effectively decreased the lipopolysaccharide (LPS)-induced expression of inducible NO synthase, resulting in decreased NO production. LCO also significantly suppressed LPS-induced production and expression of IL-1β and IL-6. Taken together, the present findings suggest that C. officinalis leaves have potential as natural materials for the development of antioxidant and anti-inflammatory agents.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.17-32
• /
• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.139-147
• /
• 2021

Livestock manure is used as an organic fertilizer to replace chemical fertilizers after sufficient fermentation in an aerobic bioreactor. On the other hand, liquid manure disposal problems occur repeatedly because soil spraying is restricted during the summer when the crops are growing. To use liquid fertilizer (LF) as an additional nutrient source for crops, it is necessary to reduce the amount of suspended solids (SS) in the liquid fertilizer and secure stability problems against pathogenic microorganisms. This study examined the effects of the simultaneous SS removal and E.coli sterilization in the LF using the microbubble (MB) generator (FeMgO catalyst insertion). The remaining SS were further removed using the integrated microbubble and microfilter system. During the floating process in the MB device, the SS were removed by 57.9%, and the coliform group was not detected (16,200→0 MPN/100 mL). By optimizing the HRT of the integrated system, the removal efficiency of the SS was improved by 92.9% under the 0.1h of HRT condition. After checking the properties of the treated LF, 64.5%, 70.1%, 54.9%, and 51.5% of the TCOD, SCOD, PO4-P, and TN, respectively, were removed. The treated effluent from such an integrated system has a lower SS content than that of the existing LF and does not contain coliforms; therefore, it can be used directly as an additional fertilizer.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.47-64
• /
• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.41 no.1
• /
• pp.16-22
• /
• 2021

This experiment was conducted to study on the growth characteristics and seed productivity of Italian ryegrass (Lolium multiflorum Lam., IRG) planted in the Spring in Gangwon Highland according to the seeding distance (20, 30 and 40 cm). The field was located in highland around 600 m above sea level. The experimental design was randomized block design with three replication and the tested IRG variety was 'Greencall' developed by National Institute of Animal Science (NIAS). IRG was sown on March 26, 2020, and harvested on July 2. The plant height was the shortest at 80.5 cm in the 40 cm seeding distance plot (P<0.05), and there was no significant difference between the 20 and 30 cm seeding distance. The number of spike per square meter (㎡) was significantly higher in the 20 cm seeding distance plot than that of 40 cm (937 vs. 571). The dry matter (DM) content of seed and straw after harvesting was 49.70 and 33.36 % on average, and there was no significant difference between treatments (P>005). However, there was a significant difference in the fresh and DM yield of seeds and straw (P<0.05). DM yield of seeds was significantly higher in 20 cm distance than that of 40 cm, and the yield of straw was the same trend. On the other hand, there was no significant difference in DM yield between 20 cm and 30 cm and also in the feed value of straw after seed harvesting among seeding distance. The average CP, ADF, NDF, and TDN contents were 6.91, 36.76, 61.75 and 59.86%, respectively, and the RFV value was 91. Considering the above results, the production of Italian ryegrass seeds sown in the spring in the highlands of the Gangwon is lower than that of autumn sowing, but it is judged that it needs to be reviewed in case it is unavoidable. In the future, there should be an economic analysis and the development of technology that can increase production.

• Journal of Food Hygiene and Safety
• /
• v.35 no.6
• /
• pp.544-551
• /
• 2020

The aim of this study was to develop and validate a simultaneous analytical method for berberine and palmatine, which are representative substances of Phellodendron amurense, and to evaluate the antioxidant activity. We evaluated the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of analytical methods for berberine and palmatine using high-performance liquid chromatography. Our result showed that the correlation coefficients of the calibration curve for berberine and palmatine exhibited 0.9999. The LODs for berberine and palmatine were 0.32 to 0.35 µg/mL and the LOQs were 0.97 to 1.06 µg/mL, respectively. The inter-day and intra-day precision values for berberine and palmatine were from 0.12 to 1.93 and 0.19 to 2.89%, respectively. The inter-day and intra-day accuracies were 98.43-101.45% and 92.39-100.60%, respectively. In addition, the simultaneous analytical method was validated for the detection of berberine and palmatine. Moreover, we conducted FRAP and NaNO2 scavenging activity assays to measure the antioxidant activities of berberine and palmatine, and both showed antioxidant activity. These results suggest that P.amurense could be a potential natural resource for antioxidant activity and that the efficacy can be confirmed by investigating the content of the berberine and palmatine.

• Journal of Nutrition and Health
• /
• v.54 no.6
• /
• pp.644-663
• /
• 2021

Purpose: This study was conducted to evaluate the safety of iodine intake based on ingestion levels and urinary iodine excretion of women of childbearing age (15-45 years old) using data from the 2013-2015 Korea National Health and Nutrition Examination Survey. Methods: Iodine intake was calculated using the 24 hours dietary recall method and urinary iodine excretion. The iodine nutrition database for the analysis of dietary iodine intake was constructed using the food composition database of the Rural Development Administration (RDA), the Korean Nutrition Society (KNS), the Ministries of Food and Drug Safety, China and, Japan. The World Health Organization (WHO) evaluation criteria and hazard quotient (HQ) calculated using biomonitoring equivalents (BE) were applied to evaluate the safety of the iodine intake. Results: Of the study subjects, 15.22% had a urinary iodine concentration level of less than 100 ㎍/L, which was diagnosed as deficient, and 48.16% had an excessive iodine concentration of over 300 ㎍/L. Urinary iodine concentration was 878.71 ㎍/L, iodine/creatinine was 589.00 ㎍/g, and iodine/creatinine was significantly higher at the age of 30-45 years. The dietary iodine intake was 273.47 ㎍/day, and the iodine intake calculated from the urinary iodine excretion was 1,198.10 ㎍/day. Foods with a high contribution to iodine intake were vegetables, seafood, seaweed and processed foods. The HQ was 1.665 when the urinary iodine content was > 1,000 ㎍/L. Conclusion: The results of this study implicate that the urinary iodine concentration, rather than the dietary iodine intake, is more appropriate to evaluate the iodine status under the current situation that a comprehensive iodine database for Koreans has not been established.

• Journal of Intelligence and Information Systems
• /
• v.27 no.4
• /
• pp.49-71
• /
• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• Journal of Plant Biotechnology
• /
• v.49 no.1
• /
• pp.74-81
• /
• 2022

Brassica napus, an oil crop that produces rapeseed oil, is an allotetraploid (AACC, 2n = 38) produced by natural hybridization between B. rapa and B. oleracea. In this study, microspore was cultured using the F₁ developed from a cross between 'EMS26' line with high oleic acid content and 'J8634-B-30' lines. The flower bud size showing the nuclear development at the late uninucleate and binucleate stage with high embryogenesis rate was 2.6 ~ 3.5 mm. Microspores were cultured using only this size and after then most microspore embryo developed into secondary embryos and then regeneration plants obtained from the developed multilobe. The analysis of the ploidy of the plants revealed that 66.7% and 27.8% of the total lines were tetraploids and octoploids, respectively. The sizes of stomatal cells in tetraploids, octoploids, and diploids were 25.5, 35.6, and 19.9 ㎛, respectively, indicating that ploidy level was positively correlated with cell size. Furthermore, 62 tetraploid doubled haploid (DH) lines were selected. The average oleic acid (C18:1) and linolenic acid (C18:3) concentrations of DH were 72.3% and 6.2%, respectively. Oleic acid and linolenic acid concentrations exceeded the two parental values in 5 and 14 DH lines, respectively, suggesting that these two fatty acids had transgressive segregation. Therefore, the DH population can be utilized for the biosynthesis of unsaturated fatty acids in rapeseed and related genes. It can also be used as a breeding material for varieties with high oleic acid concentrations.