• Title/Summary/Keyword: Negative event

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Psychosocial Characteristics of Infants with Genital Anomalies and Their Caregivers (생식기 기형을 가진 영유아와 모의 심리 사회적 특성)

  • Lee, Ji-Yeon;Chung, Kyong-Mee;Han, Sang-Won;Jo, Sang Hee;Jung, Hyun Jin;Im, Young Jae
    • Korean Journal of Health Psychology
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    • v.16 no.1
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    • pp.169-187
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    • 2011
  • The present study explored psychosocial characteristics of infants with genital anomalies (GA) and their caregivers against normal controls. Participants were female caregivers and infants between the ages of 6to38months diagnosed with hypospadias(HS;n=103) or cryptorchidism (CR;n=49). Normalcontrols(n=131) were recruited and selected via Internet. Caregivers completed measures on parenting stress, coping style, social support, and infant temperament. Within the GAgroups, HScaregivers reported their greatest parental concerns as infant urination/bodily functioning difficulties whereas CRcaregivers reported worries related to surgical anesthesia issues. Both groups reported concern about their children's potential reproductive problems. Per caregiver report, infants with GA had lower ability to self-soothe. HS infants in particular were perceived as exhibiting greater negative emotion. Compared with controls, HS and CRcaregivers overall employed coping strategies more frequently and had lower interpersonal sensitivity and parental distress. However, HScaregivers emerged as experiencing higher stress when compared to the CRgroup. There were no differences in to tal parenting stress and social support scores between groups. Further, CRcaregivers reported lower levels of family discord than controls. Despite temperament-related differences between infants with GA and normal controls, HS and CRcaregivers reported lower parental distress and greater use of coping skills as compared to controls. Clinical implications are discussed.

Explaining Variance in Children's Recall of a Stressful Experience: Influence of Cognitive and Emotional Individual Differences (스트레스적 경험에 대한 아동 기억의 신뢰성과 인지 및 정서적 개인차 특성들과의 관계)

  • Seungjin Lee
    • Korean Journal of Culture and Social Issue
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    • v.19 no.3
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    • pp.343-365
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    • 2013
  • This study examined the effects of various individual differences on children's memory of a stressful experience. The participants for the current study were children (N=85) aged 4-9 years those who experienced a naturally occurring stressful experience from a dental procedure. There was overall negative relation between the level of stress and children's memory performance. However, more interestingly, the results of this study provided some further evidence that several cognitive (i.e., receptive language ability and working memory capacity) and emotional (i.e., children's general anxiety condition, children's self-report of pain and anxiety about the event) individual difference factors were associated with variations in children's remembering across ages. The results suggest that the relation between stress and children's memory might be impacted in part by children's various individual characteristics. Furthermore, the findings are discussed in the applied context that based on the results clinical and legal professionals can tailor interviews to best meet children's needs and capabilities, and create developmentally and individually sensitive guidelines for interviewing children in the legal system.

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Study on Predicting the Designation of Administrative Issue in the KOSDAQ Market Based on Machine Learning Based on Financial Data (머신러닝 기반 KOSDAQ 시장의 관리종목 지정 예측 연구: 재무적 데이터를 중심으로)

  • Yoon, Yanghyun;Kim, Taekyung;Kim, Suyeong
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.1
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    • pp.229-249
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    • 2022
  • This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea

  • Byunggeon Park;Jongmin Park;Jae-Kwang Lim;Kyung Min Shin;Jaehee Lee;Hyewon Seo;Yong Hoon Lee;Jun Heo;Won Kee, Lee;Jin Young Kim;Ki Beom Kim;Sungjun Moon;Sooyoung, Choi
    • Korean Journal of Radiology
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    • v.21 no.11
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    • pp.1256-1264
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    • 2020
  • Objective: Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19. Materials and Methods: CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis. Results: Eighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021-42.457; p = 0.004), C-reactive protein (CRP) (HR, 1.080 per mg/dL; 95% CI, 1.010-1.156; p = 0.025), and COVID-affected lung proportion (CALP) (HR, 1.067 per percentage; 95% CI, 1.033-1.101; p < 0.001) were significantly associated with CEFS. CRP (HR, 1.164 per mg/dL; 95% CI, 1.006-1.347; p = 0.041) was independently associated with CEFS in the mild pneumonia group (n = 54). Normally aerated lung proportion (NALP) (HR, 0.872 per percentage; 95% CI, 0.794-0.957; p = 0.004) and NALP volume (NALPV) (HR, 1.002 per mL; 95% CI, 1.000-1.004; p = 0.019) were associated with a lower risk of critical events in the severe pneumonia group (n = 28). Conclusion: CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.

Multi-Category Sentiment Analysis for Social Opinion Related to Artificial Intelligence on Social Media (소셜 미디어 상에서의 인공지능 관련 사회적 여론에 대한 다 범주 감성 분석)

  • Lee, Sang Won;Choi, Chang Wook;Kim, Dong Sung;Yeo, Woon Young;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.51-66
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    • 2018
  • As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

Analysis of Growth-Decline Type and Factors Influencing Growth Commercial Area Using Sales Data in Alley Commercial Area - Before and After COVID-19 - (골목상권 매출액 데이터를 활용한 성장-쇠퇴 유형화와 성장상권 영향요인 분석 - 코로나19 전후를 대상으로 -)

  • Jiwan Park;Leebom Jeon;Seungil Lee
    • Journal of the Korean Regional Science Association
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    • v.39 no.1
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    • pp.53-66
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    • 2023
  • Due to COVID-19, the external activities of urban residents have greatly shrunk, causing a lot of damage to the commercial district, such as a decrease in population and sales. The downturn in commercial districts means the collapse of the infrastructure of the national economy, and can have serious side effects on the local economy and individual lives. Therefore, it is necessary to look at the alley commercial area, which is closely related to the national local economy, and pay attention to the damage and stagnation of the alley commercial area where small business owners are concentrated. The purpose of this study is to classify alley commercial districts into growth commercial districts and decline commercial districts by using commercial sales time series data and DTW time series group analysis for the pre- and post-COVID-19 period. The main findings of the study are as follows. First, using the time series data on commercial sales before and after COVID-19, the alley commercial districts were divided into growth commercial districts and decline commercial districts, and it was confirmed that the distribution of growth commercial districts and decline commercial districts was regionally different. Therefore, it is necessary to actively manage commercial districts in areas where many declining commercial districts are distributed, and it is required to prepare policies for each region in consideration of the spatial distribution of declining commercial districts. Second, during the COVID-19 period, face-to-face essential industries, density of guest facilities, and population density negatively affected the sustainability of commercial districts, which is the opposite of previous studies. This is the result of empirically confirming the specificity of the COVID-19 period and the negative effects of the integrated economy, and can be used as basic data for effective commercial district management and policy preparation in the event of a national disaster in the future. Third, the characteristics of the background of the commercial district had a significant effect on the sustainability of the commercial district, and the negative effect of the attracting facilities inducing population concentration in the background area was found. This suggests that it is necessary to consider the characteristics of the background as well as the inside of the commercial district when establishing policies to revitalize the commercial district and support small business owners in a national disaster situation.

An Intelligence Support System Research on KTX Rolling Stock Failure Using Case-based Reasoning and Text Mining (사례기반추론과 텍스트마이닝 기법을 활용한 KTX 차량고장 지능형 조치지원시스템 연구)

  • Lee, Hyung Il;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.1
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    • pp.47-73
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    • 2020
  • KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

Correlates of Subjective Well-being in Korean Culture (한국문화에서 주관안녕에 영향을 미치는 사회심리 요인들)

  • Hahn, Doug-Woong
    • Korean Journal of Culture and Social Issue
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    • v.12 no.5_spc
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    • pp.45-79
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    • 2006
  • The purpose of this paper was to review the results of the subjective well-being(swb) studies performed by Hahn and coworkers in Korean culture. As the correlates of swb, we dealt with demographic/individual difference variables, intrapersonal variables, interpersonal process variables, and Korean cultural variables. We proposed that the components of swb were consisted of quality of life(cognitive swb) and overall happy feelings about one's own life(emotional swb). It was also assumed that a measure of total swb could be calculated by summated mean of cognitive swb and emotional swb measures. The data of the swb studies were analyzed and interpreted according to the above three measures of swb. The results of a nationwide survey(Hahn, 2004) from age of 19 to 75 years ald(n=2,230) showed significant simple correlation coefficients between the following demographic/individual difference variables and swb: Gender difference in swb was found(total swb r=.08, p<.001; life satisfaction r=.10, p<.001; overall emotional swb r=.05, p<.05). Men were happier than women in terms of all three measures of swb. It was also found that women appeared to experience greater positive and negative emotions. Correlation between age and emotional swb(r=.09, p<.001) was significant, but life satisfaction was not significant(r=.04, n.s). Correlations between economic status and swb were also significant(total swb r =.23, p<.001; life satisfaction r=.15 p<.001; overall emotional swb r=.15, p<.001l). Although existence of father was negatively related to emotional swb(r=-.05, p<.05), the existence of mother was not related to any of swb measures. Similarly existence of brothers was related positively to overall emotional swb, but existence of sisters was not. Though existence of son was not related to swb, daughter contributed negatively to swb(total swb -.12, p<.01; life satisfaction -.09, p<.05; emotional swb r=-.12, p<.01). We assumed that family member-in-Iaw also contributed to swb because the extended dose social networks were important in Korean culture. The results showed that the following family member-in-law variables were related to swb: Parents-in-law(total swb r=.11, p<.01; life satisfaction r=.10, p<.01; emotional swb r=.10, p<.01), father-in-law(total swb r=.11, p<.01; life satisfaction r=.11, p<.01; emotional swb r=.06, n.s). The result suggested that especially father-in-law contributed to swb through financial and social support. Correlations between emotional experiences in everyday life and swb were also presented. The range of correlation coefficients between the positive emotion measures and swb were r=.30~.48(p<.001) when the above two measures obtained at same time. But the range decreased to r=.19~32(p<.001) when the swb measure was obtained 9 month later longitudinally. Intercorrelations between positive emotional experience; and life satisfaction were r=.37~58(p<.001) when two measures were obtained at same time. We also examined the effects of the intrapersonal cognitive responses to the most stressful life event upon swb. The results of nationwide survey(n=1,021) showed that self-disclosure(total swb r=.09, p<.010; life satisfaction r=.10, p<.01; emotional swb r=.07, p<.01), rumination(total swb r=-.17, p<.001), thought avoidance(total swb r=.12, p<.001; life satisfaction r=-.08; emotional swb r=-.12, p<.001) and suppression(total swb r=-.13, p<.001; life satisfaction r=-.08, p<.05: emotional swb r=-.13, p<.001) contributed to swb. It was also suggested that mismatch between self-guide and regulatory focus contributed negatively to emotional swb. It was also found that social comparison motives and fulfillment of the motives contributed to swb. The results of a survey research(n=363 college students) revealed that the higher the general social comparison motive, the lower the swb(total swb r=-.15, P<.01: life satisfaction r=-.17. p<.01; emotional swb r=-.10, p<.05). It was also found that satisfaction level of self-evalution motive contributed positively to swb(total swb r=-.14. p<.01: life satisfaction r=-.12, p<.05; emotional swb r=.15, p<.001). Both of self-improvement motive(r=.13, p<.05) and satisfaction level of self-improvement motive(r=.12, p<.05) contributed positively to emotional swb, respectively. The above results suggested that swb was depended upon the interaction effect of social comparison motive; and level of fulfillment of the motives. We also reported the significant multiple predictors of swb in a sample of age from 60years to 89years olds. The results of multiple regression analysis showed that the significant multiple predictors of swb were past illness(β=.174, p<.001), economic status(β=.418, p<.001), marital satisfaction(β=.0841, p<.001), satisfaction of offsprins(β=.065, p<.01), expectation level of social support from offsprings(β=-.049, p<.001), and negative emotions(β=-.454. p<.001) among 16 social psychological factors. It was also found that swb was an important multiple predictors of physical health. This finding was replicated in a longitudinal study. Both of positive and negative emotional experiences were significant multiple predictors of physical health one year later. The results of the discriminant analysis showed both of total swb and positive emotional experiences contributed to discriminate the happy and healthy olds from unhappy and unhealthy olds. We paper also examined the effects of the nonnative social behaviors upon swb in Korean culture. The main hypotheses of the study(Hahn, 2006, in press) was that the important nonnative behaviors would influence on swb through both of the mediation processes of adjustment to social relationships and psychological stress. The survey data were collected from 2,129 adults age of 19 to 75, from 7 regional areas in Korea. The results of the study revealed that almost all of correlation coefficients between 15 normative social behaviors and the above three criteria w-ere significant. The fitness test results of the covariance structural equation model showed that all of the fitness indices were satisfactory (GFI=.974, AGFI=.909, NNFI=.922, NFI=.973, CFI=.974. RMR=.049, RMSEA=.073). The results of the analysis revealed that the following five path coeffi6ents from behaviors to social adjustment were significant; behavior tor family and family members(t=5.87, p<.001), courteous behavior(t=4.39, p<.001), faithful behavior (t=2.15. p<.05). collectivistic behavior(t=8.31, p<.001). Seven path coefficients from the normative behaviors to psychological stress were significant; behavior for family and family members (t=-4.63, p<.001), faithful behavior(t=-3.86, p<.001). suppression of emotional expression(t=3.99, p<.001), trustworthy and dependable behavior(t=-2.21, p<.05), collectivistic behavior(t=3.72, p<.001), effortful and diligent behavior(t=2.94, p<.001), husbandry and saving behavior(t=3.40, p<.001). The above results suggested that four normative behaviors among seven behaviors contributed negatively to psychological stress in current Korean society. The results abo confirmed the hypothesized paths from social adjustment (t=10.40, p<.001) to swb and from psychological stress(t=-19.74, p<.001) to swb. The important results of the study were discussed in terms of the Confucian traditions and recent social changes in Korean culture. Finally limitations of this review paper were discussed and the suggestions for the future study were also proposed.

Effect of Noise on Density Differences of Tissue in Computed Tomography (컴퓨터 단층촬영의 조직간 밀도차이에 대한 노이즈 영향)

  • Yang, Won Seok;Son, Jung Min;Chon, Kwon Su
    • Journal of the Korean Society of Radiology
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    • v.12 no.3
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    • pp.403-407
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    • 2018
  • Currently, the highest cancer death rate in Korea is lung cancer, which is a typical cancer that is difficult to detect early. Low-dose chest CT is being used for early detection, which has a greater lung cancer diagnosis rate of about three times than regular chest x-ray images. However, low-dose chest CT not only significantly reduces image resolution but also has a weak signal and is sensitive to noise. Also, air filled lungs are low-density organs and the presence of noise can significantly affect early diagnosis of cancer. This study used Visual C++ to set a circle inside a large circle with a density of 2.0, with a density of 1.0, which is the density of water, in which five small circle of mathematics have different densities. Gaussian noise was generated by 1%, 2%, 3%, and 4% respectively to determine the effect of noise on the mean value, the standard deviation value, and the relative noise ratio(SNR). In areas where the density difference between the large and small circles was greatest in the event of 1 % noise, the SNR in the area with the greatest variation in noise was 4.669, and in areas with the lowest density difference, the SNR was 1.183. In addition, the SNR values can be seen to be high if the same results are obtained for both positive and negative densities. Quality was also clearly visible when the density difference was large, and if the noise level was increased, the SNR was reduced to significantly affect the noise. Low-density organs or organs in areas of similar density to cancers, will have significant noise effects, and the effects of density differences on the probability of noise will affect diagnosis.

Analysis on TV News Frame on Whistle-Blower: Focused on News Coverages on 'Kim Yong Chul' Claiming Samsung Group's Slush Fund (내부고발에 대한 텔레비전 뉴스 프레임: '김용철' 변호사의 삼성비리 고발사건을 중심으로)

  • Kim, Nam-Il
    • Korean journal of communication and information
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    • v.43
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    • pp.117-151
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    • 2008
  • This paper regards former Samsung lawyer Kim Yong-Chul's action of claiming Samsung Group's slush fund as typical Whistle-Blowing from inside. News frames in KBS, SBS TV were examined through comparative analysis. In formal feature, 'episodic news frame' hold an absolute majority in both stations. From news sources, the group of whistle-blower such as lawyer Kim Yong-Chul and civic groups was confronted with Samsung and state authorities including the Prosecutor, financial agencies. Analysis on the theme of news coverages demonstrated 5 frames: 'public announcing frame', 'news of conflict frame' 'demanding a close inquiry frame', 'declaration of conscience frame', 'causing social upheaval frame', Analysis result shows that 'public announcing frame' was most frequently used in reporting and there was distinction between KBS and SBS in 'declaration of conscience frame' and 'causing social upheaval frame'. Relatively KBS preferred 'declaration of conscience frame' and SBS would use 'causing social upheaval frame', from which reciprocal relation as media ownership could be analogized. Both media tend to make light of in-depth news coverages on structural issues or essential settlement and it is shown that both stations treated this situation with intriguing audiences as stressing sensitive parts in this event. Follow-up of changing process of 'declaration of conscience frame' through diachronic analysis on framing informs that additional exposure of 'Lee Yong Chul', former secretary in Nov 19, 2007 influenced increasing of frequency of using 'declaration of conscience frame'. However, news reporting on whistle-blower in KBS and SBS generally adheres to passive attitude of following changes in the surroundings rather than playing an active role in improving social recognition on whistle-blowing, which can induce to the spread of negative feature on it. Thus it is assumed that terrestial television broadcasting should regard whistle-blowing as contradiction in social structures and active depth reporting seems to be neded for improving social recognition on whistle-blowing.

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