• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.2
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• pp.127-136
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• 2019

Sweet sorghum (Sorghum bicolor L. Moench), compared to traditional crops, has been evaluated as a useful crop with high adaptability to the environment and various uses, but cultivation has not expanded owing to a lack of related research and information in Korea. This study was conducted to estimate heading date in 'Chorong' sweet sorghum based on climate data of the last 30 years (1989 - 2018) from six regions (Jeonju, Buan, Jeongup, Imsil, Namwon, and Jangsu) in Jellabuk Province. In addition, we compared the growth and quality factors by sowing date (April 10, April 25, May 10, May 25, June 10, June 25, and July 10) in 2018. Days from sowing to heading (DSH) increased to 107, 96, 83, 70, 59, 64, and 65 days in order of the sowing dates, respectively, and the average was 77.7 days. The effective accumulated temperature for heading date was $1,120.3^{\circ}C$. The mean annual temperature was the highest in Jeonju, followed in descending order by Jeongup, Buan, Namwon, Imsil, and Jangsu. The DSH based on effective accumulated temperature gradually decreased in all sowing date treatments in the six regions during the last 30 years. DSH of the six regions showed a negative relationship with mean temperature (sowing date to heading date) and predicted DSH ($R^2=0.9987**$) calculated by mean temperature was explained with a probability of 89% of observed DSH in 2017 and 2018. At harvest, fresh stem weight and soluble solids content were higher in the April and July sowings, but sugar content was higher in the May 10 ($3.4Mg{\cdot}ha^{-1}$) and May 25 ($3.1Mg{\cdot}ha^{-1}$) sowings. Overall, the April and July sowings were of low quality and yield, and there is a risk of frost damage; thus, we found May sowings to be the most effective. Additionally, sowing dates must be considered in terms of proper harvest stage, harvesting target (juice or grain), cultivation altitude, and microclimate.

• Journal of Nutrition and Health
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• v.52 no.3
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• pp.310-322
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• 2019

Purpose: This study examined the food purchases from e-commerce and its relation to eating behaviors or habits in adult women in Incheon and Gyeonggi. Methods: A total of 410 subjects participated in the questionnaire survey. Food purchases in e-commerce and food habits were compared according to age, marital status, and food purchase status in e-commerce of the subjects. Results: Approximately 88% of the subjects had experience of buying foods by e-commerce; more than 40% of the subjects spent less than 100,000 Won buying foods by e-commerce in the past 6 months. The major purchases were coffee and tea, instant food and frozen food, and water and beverages. The reasons for buying foods in e-commerce were cheaper price, convenience of delivery, and variety of food choices. The main factors considered for purchasing foods in e-commerce were price and quality followed by rapid and accurate delivery, and food label and information. Approximately 70% of the subjects were very satisfied or satisfied with their food purchase in e-commerce, and 96% answered that they were willing to buy food in e-commerce again. The perception on the advantages of food purchases in e-commerce was 3.6 points out of 5 and significantly lower in the over 50s and married group. The subjects with experience and high cost of food purchase in e-commerce showed significantly low scores of dietary behaviors and eating habits, which is undesirable. Conclusion: A high percentage of people purchased foods by e-commerce, and they showed undesirable eating habits, especially when the cost of purchasing foods by e-commerce is high. These results showed that purchasing foods in e-commerce may be related to consumers' food habits. Therefore, continuous attention and nutrition guidance for e-commerce consumers are needed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.197-217
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• 2018

Music is one of the most creative act that can express human sentiment with sound. Also, since music invoke people's sentiment to get empathized with it easily, it can either encourage or discourage people's sentiment with music what they are listening. Thus, sentiment is the primary factor when it comes to searching or recommending music to people. Regard to the music recommendation system, there are still lack of recommendation systems that are based on customer sentiment. An algorithm's that were used in previous music recommendation systems are mostly user based, for example, user's play history and playlists etc. Based on play history or playlists between multiple users, distance between music were calculated refer to basic information such as genre, singer, beat etc. It can filter out similar music to the users as a recommendation system. However those methodology have limitations like filter bubble. For example, if user listen to rock music only, it would be hard to get hip-hop or R&B music which have similar sentiment as a recommendation. In this study, we have focused on sentiment of music itself, and finally developed methodology of defining new index for music recommendation system. Concretely, we are proposing "SWEMS" index and using this index, we also extracted "Sentiment Pattern" for each music which was used for this research. Using this "SWEMS" index and "Sentiment Pattern", we expect that it can be used for a variety of purposes not only the music recommendation system but also as an algorithm which used for buildup predicting model etc. In this study, we had to develop the music recommendation system based on emotional adjectives which people generally feel when they listening to music. For that reason, it was necessary to collect a large amount of emotional adjectives as we can. Emotional adjectives were collected via previous study which is related to them. Also more emotional adjectives has collected via social metrics and qualitative interview. Finally, we could collect 134 individual adjectives. Through several steps, the collected adjectives were selected as the final 60 adjectives. Based on the final adjectives, music survey has taken as each item to evaluated the sentiment of a song. Surveys were taken by expert panels who like to listen to music. During the survey, all survey questions were based on emotional adjectives, no other information were collected. The music which evaluated from the previous step is divided into popular and unpopular songs, and the most relevant variables were derived from the popularity of music. The derived variables were reclassified through factor analysis and assigned a weight to the adjectives which belongs to the factor. We define the extracted factors as "SWEMS" index, which describes sentiment score of music in numeric value. In this study, we attempted to apply Case Based Reasoning method to implement an algorithm. Compare to other methodology, we used Case Based Reasoning because it shows similar problem solving method as what human do. Using "SWEMS" index of each music, an algorithm will be implemented based on the Euclidean distance to recommend a song similar to the emotion value which given by the factor for each music. Also, using "SWEMS" index, we can also draw "Sentiment Pattern" for each song. In this study, we found that the song which gives a similar emotion shows similar "Sentiment Pattern" each other. Through "Sentiment Pattern", we could also suggest a new group of music, which is different from the previous format of genre. This research would help people to quantify qualitative data. Also the algorithms can be used to quantify the content itself, which would help users to search the similar content more quickly.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.297-307
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• 2011

This study investigates relation of food safety incidents with climate. Therefore food safety incidents and climate data during 1999 to 2009 have been analyzed. In situ observations of monthly mean temperature, maximum temperature, minimum temperature, precipitation, and relative humidity in 60 observation stations of Korean Meteorological Administration (KMA) have been used in this study. Food safety incidents data have been constructed by searching media reports following Park's method (2009) during the same period. According to the Park's method, 729 events were collected. To analyze its relations, food safety incidents data have been classified into chemical, biological, and physical hazards. Pearson product-moment correlation coefficients have been applied to analyze the relations. The correlation of food safety incidents has negative one with precipitation (-0.48), and positive one with minimum temperature(0.45). Precipitation has been correlated with biological and physical hazards more than chemical hazard. Temperatures (mean temperature, maximum temperature, and minimum temperature) have been correlated closely with chemical hazard than others. Food safety incidents data has been interblended with human behavior factor through decision-making processes in food manufacturing, processing, and consumption phases of "farm-totable" food processing. Act in the preventing damage will be obvious if the hazard were apparent. Therefore abnormal condition could be more dangerous than that of apparent extreme events because apparent events or extreme events become one of alarm over hazards. Therefore, human behavior should be considered as one of the important factors for analysis of food safety incidents. The result of this study can be used as a better case study for food safety researches related to climate change.

• Korean Journal of Poultry Science
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• v.46 no.1
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• pp.31-37
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• 2019

A chicken clathrin-associated adaptor protein $3-{\delta}$ subunit 2 (AP3S2) is a subunit of AP3, which is involved in cargo protein trafficking to target membrane with clathrin-coated vesicles. AP3S2 may play a role in virus entry into host cells through clathrin-dependent endocytosis. AP3S2 is also known to participate in metabolic disease developments of progressions, such as liver fibrosis with hepatitis C virus infection and type 2 diabetes mellitus. Chicken AP3S2 (chAP3S2) gene was originally identified as one of the differentially expressed genes (DEGs) in chicken kidney which was fed with different calcium doses. This study aims to characterize the molecular characteristics, gene expression patterns, and transcriptional regulation of chAP3S2 in response to the stimulation of Toll-like receptor 3 (TLR3) to understand the involvement of chAP3S2 in metabolic disease in chicken. As a result, the structure prediction of chAP3S2 gene revealed that the gene is highly conserved among AP3S2 orthologs from other species. Evolutionarily, it was suggested that chAP3S2 is relatively closely related to zebrafish, and fairly far from mammal AP3S2. The transcriptional profile revealed that chAP3S2 gene was highly expressed in chicken lung and spleen tissues, and under the stimulation of poly (I:C), the chAP3S2 expression was down-regulated in DF-1 cells (P<0.05). However, the presence of the transcriptional inhibitors, BAY 11-7085 (Bay) as an inhibitor for nuclear factor ${\kappa}B$ ($NF{\kappa}B$) or Tanshinone IIA (Tan-II) as an inhibitor for activated protein 1 (AP-1), did not affect the expressional level of chAP3S2, suggesting that these transcription factors might be dispensable for TLR3 mediated repression. These results suggest that chAP3S2 gene may play a significant role against viral infection and be involved in TLR3 signaling pathway. Further study about the transcriptional regulation of chAP3S2 in TLR3 pathways and the mechanism of chAP3S2 upon virus entry shall be needed.

• Journal of agricultural medicine and community health
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• v.43 no.4
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• pp.234-249
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• 2018

This study was performed to identify the impact of awareness and educational experiences on cardiopulmonary resuscitation in the ability to execute of cardiopulmonary resuscitation among Korean adults. This study used original data of 2014 Community Health Data Survey. 228,712 participants in this survey were resident in South Korea who is aged 19 or older on July 2014. Participants in this survey were sampled an average of 900 residents(target error ${\pm}3percent$) per community health center of Korea. Data were analyzed by using R 3.1.3 employing chi-squared test, fisher's exact analysis, and logistic regression analysis. Ability to execute CPR was significantly higher in males(3.34 time), higher the education level (1.61 times), the white color occupation (1.14 times), the higher the income level (1.07 times), the higher the education level (0.91 times), non-hypertensive patients (1.12 times), non-diabetic patients (1.16 times), non-dyslipidemic patients (0.86 times), non-stroke patients (0.30 times), CPR education experience group (3.25 times), CPR experience group with manikin-based training (4.30 times), higher subjective health status (1.08 times, 1.16 times) respectively. This study identified that awareness, educational experience, and mannequin-based learning experience of CPR impacted on the ability to execute CPR. Responding to education-related factors could contribute to reducing the rate of out-of-hospital acute cardiac arrest by improving the ability to execute CPR of the general public.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.51-57
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• 2018

Objectives: Previous studies have shown that periodic limb movements in sleep (PLMS) could be one of risk factors for cardiovascular morbidity. The purpose of this study was to investigate the association between PLMS and blood pressure changes during sleep. Methods: We analyzed data from 358 adults (176 men and 182 women) aged 18 years and older who were free from sleep apnea syndrome (Respiratory Disturbance Index < 5) and sleep disorders such as REM sleep behavior disorder or narcolepsy. Demographic characteristics, polysomnography records, and clinical variable data including blood pressure, body mass index, alcohol, smoking, and current medications were collected. In addition, self-report questionnaires including the Beck Depression Index, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were completed. Blood pressure change from bedtime to awakening was compared between the two periodic limb movement index (PLMI) groups [low PLMI ($PLMI{\leq}15$) and high PLMI (PLMI > 15)]. Blood pressure change patterns were compared using repeated measures analysis of variance. Results: Systolic blood pressure in the high PLMI group was lower than that in the low PLMI group (p = 0.036). These results were also significant when adjusted for gender and age, but were not statistically significant when adjusted for BMI, alcohol, smoking, anti-hypertension medication use and sleep efficiency (p = 0.098). Systolic blood pressure dropped by 9.7 mm Hg in the low PLMI group, and systolic blood pressure in the high PLMI group dropped by 2.9 mm Hg. There was a significant difference in delta systolic blood pressure after sleep between the two groups in women when adjusted for age, BMI, alcohol, smoking, antihypertensive medication use and sleep efficiency (p = 0.023). Conclusion: PLMS was significantly associated with a decreasing pattern in nocturnal BP during sleep, and this association remained significant in women when adjusted for age, BMI, alcohol, smoking, antihypertension medication use and sleep efficiency related to blood pressure. We suggest that PLMS may be associated with cardiovascular morbidity.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.486-496
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• 2018

Pine wilt disease (PWD) in Gyeonggi province was first detected in Gwangju in 2007, and ever since has caused extensive damage. Insect vector and host tree in Gyeonggi province are Monochamus saltuarius and Pinus koraiensis, respectively, which are different from the southern region that consist of Monochamus alternatus and Pinus densiflora. Consequently, spread and mortality characteristics may be different, but our understanding is limited. In this research, we utilized the spatial data of newly infected trees in Gyeonggi province from 2008 to 2015 to analyze how it is related to various environmental and human factors, such as elevation, forest type, and road network. We also analyzed the minimum distance from newly infected tree to last year's closest infected tree to examine the dispersal characteristics based on new outbreak locations. Annual number of newly infected trees rapidly increased from 2008 to 2013, which then stabilized. Number of administrative districts with infected trees was 5 in 2012, 11 in 2013, and 15 in 2014. Most of the infected trees was Pinus koraiensis, with its proportion close to 90% throughout the survey period. Mean distance to newly infected trees dramatically decreased over time, from 4,111 m from 2012 to 2013, to approximately 600 m from 2013 to 2014 and 2014 to 2015. Most new infections occurred in higher elevation over time. Distance to road from newly infected trees continuously increased, suggesting that natural diffusion dispersal is increasingly occurring compared to human-influenced dispersal over time.