Korean Twitter Emotion Classification Using Automatically Built Emotion Lexicons and Fine-Grained Features

In recent years many people have begun to express their thoughts and opinions on Twit-ter. Naturally, Twitter has become an ef-fective source to investigate people’s emo-tions for numerous applications. Classifying only positive and negative tweets has been ex-ploited in depth, whereas analyzing finer emo-tions is still a difficult task. More elaborate emotion lexicons should be developed to deal with this problem, but existing lexicon sets are mostly in English. Moreover, building such lexicons is known to be extremely labor-intensive or resource-intensive. Finer-grained features need to be taken into account when determining finer-emotions, but many exist-ing works still utilize coarse features that have been widely used in analyzing only the po-larity of emotion. In this paper, we present a method to automatically build fine-grained emotion lexicon sets and suggest features that improve the performance of machine learning based emotion classification in Korean Twitter texts.

Fuzzy Study on the Winning Rate of Football Game Betting

This study aims to find variables that affect the winning rate of the football team before a match. Qualitative variables such as venue, match importance, performance, and atmosphere of both teams are suggested to predict the outcome. Regression analysis is used to select proper variables. In this study, the performance of the football team is based on the opinions of experts, and the team atmosphere can be calculated with the results of the previous five games. ELO rating represents the state of the opponent. Also, the selected qualitative variables are expressed in fuzzy numbers using fuzzy partitions. A fuzzy regression model for the winning rate of the football team can be estimated by using the least squares method and the least absolute method. It is concluded that the stadium environment, ELO rating, team performance, and importance of the match have effects on the winning rate of Korean National Football (KNF) team from the data on 118 matches

Risk Factors of Emergence Agitation in Adults Undergoing General Anesthesia for Nasal Surgery

ObjectivesTo identify the incidence and the risk factors of emergence agitation in adults undergoing general anesthesia for nasal surgery.MethodsWe retrospectively examined 792 patients aged ≥18 years who underwent general anesthesia for elective nasal surgery between July 2012 and August 2013. Patients in the postanesthesia care unit with a Richmond Agitation Sedation Scale≥+1 at any time were considered to have emergence agitation.ResultsThe overall incidence of emergence agitation is 22.2%. From multivariate regression analysis, the following six variables were found to be significantly associated with emergence agitation (P<0.05): younger age, recent smoking, sevoflurane anesthesia, postoperative pain on the numerical rating scale (NRS)≥5, presence of a tracheal tube, and presence of a urinary catheter. Presence of a tracheal tube was the greatest risk factor, increasing the risk of developing emergence agitation by approximately fivefold (odds ratio, 5.448; 95% confidence interval, 2.973 to 9.982). Younger age was also a strong risk factor (odds ratio, 0.975 for each 1-year increase; 95% confidence interval, 0.964 to 0.987). Current smoking, sevoflurane anesthesia, postoperative pain of NRS≥5, and the presence of a urinary catheter nearly doubled the risk of emergence agitation.ConclusionEmergence agitation following general anesthesia is a common complication in adult nasal surgery patients. To reduce the occurrence and consequences of agitation episodes, elimination of the associated risk factors is necessary, especially in at-risk patients

FESD: a Functional Element SNPs Database in human

We have created the Functional Element SNPs Database (FESD) that categorizes functional elements in human genic regions and provides a set of single nucleotide polymorphisms (SNPs) located within each area. In the FESD, the human genic regions were divided into 10 different functional elements, such as promoter regions, CpG islands, 5′-untranslated regions (5′-UTRs), translation start sites, splice sites, coding exons, introns, translation stop sites, polyadenylation signals and 3′-UTRs, and subsequently, all the known SNPs were assigned to each functional element at their respective position. With the FESD web interface, users can select a set of SNPs in the specific functional elements and get their flanking sequences for genotyping experiments, which will help in finding mutations that contribute to the common and polygenic diseases. A web interface for the FESD is freely available at http://combio.kribb.re.kr/ksnp/resd/

The association between sialolithiasis and smoking, alcohol drinking and obesity in Korea: a nested case-control study

Smoking and alcohol consumption are the most common social habits in patients with sialolithiasis. Moreover, obesity has been reported to have a significant association with poor oral hygiene, one of the causes of sialolithiasis. The purpose of this study was to evaluate the relationships among tobacco smoking, drinking alcohol, obesity and sialolithiasis in a Korean population. The Korean National Health Insurance Service-Health Screening Cohort, which includes patients ≥40 years old, was assessed from 2002 to 2013. A total of 947 sialolithiasis participants were matched with 3788 control subjects at a ratio of 1:4 with respect to age group, sex, income group, region of residence, hypertension, diabetes, and dyslipidemia. We analyzed the participants previous histories of smoking (current or past smokers compared to nonsmokers) and alcohol consumption (≥ 1 time per week compared to < 1 time per week) in the sialolithiasis and control groups. Obesity was measured using body mass index (BMI, kg/m2), which was categorized as < 18.5 (underweight), ≥ 18.5 and < 23 (normal), ≥ 23 and < 25 (overweight), ≥ 25 and < 30 (obese I), and ≥ 30 (obese II). Crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression analyses. The rate of smoking was higher in the sialolithiasis group (32.4% [307/947]) than in the control group (29.1% [1103/3788], P = 0.047). The adjusted OR of smoking for the sialolithiasis group was 1.31 (95% CI = 1.08–1.59, P = 0.006). Alcohol consumption and obesity were not statistically significantly related to sialolithiasis. The odds of smoking were increased in sialolithiasis patients compared with control subjects in the population ≥ 40 years of age.This work was supported in part by a research grant (NRF-2018-R1D1A1A0– 2085328 and NRF-2019-R1G1A1–099842) from the National Research Foundation (NRF) of Korea

COMPARISON STUDY OF EXPERIMENTS AND PREDICTIONS OF WAVE KINEMATICS FOR ROGUE WAVE

To investigate the wave kinematics under the rogue wave crest, a series of experiments were performed in 2-D wave tank with the application of PIV technique to measure the velocities under the free surface. Three different prediction methods of linear extrapolation, Wheeler stretching, and modified stretching were applied to estimate water wave kinematics and compared with PIV experimental results under the highest wave crest of irregular wave trains satisfying with rogue wave criteria. Also, the cut-off frequency dependence for three prediction methods was investigated with varying spectral peak frequencies to estimate wave kinematics including velocities and accelerations in horizontal and vertical directions. It was suggested that the cut-off frequency for the reasonable prediction of the wave kinematics under the rogue wave crest could be chosen three times of spectral peak wave frequency for the linear extrapolation and higher frequency than four times of spectral peak wave frequency for Wheeler stretching and modified stretching method