• Anxiety and mood
• /
• v.12 no.1
• /
• pp.7-12
• /
• 2016

Objective : This study was conducted to evaluate the relationships between selective attention bias for fear stimuli and hallucination in patients with schizophrenia Method : A total of 66 patients with schizophrenia admitted to psychiatry clinics were included in the study. Selective attention bias was measured by the dot-probe task. Patient symptoms were measured using the Positive and Negative Symptom Scale, Psychotic Symptom Rating Scale (PSYRATS), Korean version of the Scale to Assess Unawareness of Mental Disorder, and Clinical Global Impression-Severity scale. Results : Selective attention bias was correlated with the hallucination subscale of PSYTATS (r=0.268, p=0.029). No correlation was found between selective attention bias and other clinical measures. There was no significant difference, but a statistical trend was found (p=0.092) in hallucination severities between the biased and non-biased groups. Conclusion : The results suggest that selective attention bias for fear stimuli is associated with auditory hallucination. This preliminary study suggests the possibility of correlation between auditory hallucination in the psychotic domain and anxiety of the affective component.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.997-1007
• /
• 2018

Drought monitoring is the important system for disasters by climate change. To perform this, it is necessary to measure the precipitation based on satellite rainfall estimation. The data developed in this study provides two kinds of satellite data (raw satellite data and bias-corrected satellite data). The spatial resolution of satellite data is 10 km and the temporal resolution is 1 day. South Korea was selected as the target area, and the original satellite data was constructed, and the bias-correction method was validated. The raw satellite data was constructed using TRMM TMPA and GPM IMERG products. The GRA-IDW was selected for bias-correction method. The correlation coefficient of 0.775 between 1998 and 2017 is relatively high, and TRMM TMPA and GPM IMERG 10 km daily rainfall correlation coefficients are 0.776 and 0.753, respectively. The BIAS values were found to overestimate the raw satellite data over observed data. By using the technique developed in this study, it is possible to provide reliable drought monitoring to Korean peninsula watershed. It is also a basic data for overseas projects including the un-gaged regions. It is expected that reliable gridded data for end users of drought management.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.19 no.5
• /
• pp.467-475
• /
• 2007

This study compared the sea surface wind pattern between model results from KMA operational model (RDAPS) and observational results from QuikSCAT in the 2005-2006 year. The mean spatial distributions of sea surface wind show the prominent seasonal patterns of summer and winter season adjacent to Korean Peninsular. The statistical analysis also shows well seasonal variation of sea surface wind patterns between model and observation results. The BIAS value represents less than -0.5 m/s and -1 m/s in summer and winter seasons, respectively. The spatially averaged correlation coefficient shows larger than 0.7 and 0.8 in summer and winter seasons, respectively. The correlation coefficient of winter season shows higher value than that of summer season in the comparison between model and observation. This results show that the RDAPS model simulate well strong sea surface wind in winter season rather than weak sea surface wind in summer season.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.361-365
• /
• 2002

Rain-rate retrieval using the NOAA/AMSU (Advanced Microwave Sounding Unit) (Zaho et al., 2001) has been implemented at METRI/KMA since 2001. Here, we present the results of the AMSU derived rain-rate and validation result, especially for the rainfall associated with the tropical cyclone for 2001. For the validation, we use rain-rate derived from the ground based radar and/or rainfall observation from the rain gauge in Korea. We estimate the bias score, threat score, bias, RMSE and correlation coefficient for total of 16 tropical cyclone cases. Bias score shows around 1.3 and it increases with the increasing threshold value of rain-rate, while the threat score extends from 0.4 to 0.6 with the increasing threshold value of precipitation. The averaged rain-rate for at all 16 cases is 3.96mm/hr and 1.41mm/hr for the retrieved from AMSU and the ground observation, respectively. On the other hand, AMSU rain-rate shows a much better agreement with the ground based observation over inner part of tropical cyclone than over the outer part (Correlation coefficient for convective region is about 0.7, while it is only about 0.3 over the stratiform region). The larger discrepancy of tile correlation coefficient with the different part of the tropical cyclone is partly due to the time difference in between ice water path and surface rainfall. This results indicates that it might be better to develop the algorithm for different rain classes such as convective and stratiform.

• Knowledge Management Research
• /
• v.22 no.1
• /
• pp.155-181
• /
• 2021

The purpose of this study is to verify the correlation between leader's machiavellianism and turnover intention. To this end, we tried to investigate the overall mechanism of the research model through the mediating effect of hindsight bias. To verify the hypothesis, surveys were conducted twice with 335 employees working at companies with more than 300 employees in various occupations. As a result of the study, first, it was found that the machiavellianism of the leader had a positive significant effect on the employee turnover intention. Second, it was found that hindsight bias had a positive significant mediating effect between the leader's machiavellianism and employee turnover intention. It can be inferred that the higher the machiavellianism tendency of the leader, the higher the hindsight bias is experienced and the negative impact on the effectiveness of the organization, the higher the employee turnover intention. Therefore, this study in-depth verifies the mechanism between the leader's machiavellianism, hindsight bias, and employee turnover intentions, suggesting new implications from a perspective different from the existing research flow, and suggesting future research tasks and limitations on the role of leaders.

• Genomics & Informatics
• /
• v.15 no.1
• /
• pp.38-47
• /
• 2017

Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.

• Journal of Distribution Science
• /
• v.12 no.9
• /
• pp.83-93
• /
• 2014

Purpose - This study attempted to identify any influencing relationships, between the antecedent variables and the members' innovative work behavior, which were expected to influence organizational performance based on the extended theory of planned behavior (ETPB). Research design, data, and methodology - The survey was conducted on SMEs in Seoul and its metropolitan area. A total of 158 copies of effective questionnaires were used and were analyzed through correlation analysis, regression analysis, and multiple regression. Results - Self-efficacy, value, intrinsic motivation, and self-enhancing bias have been found to have a positive relationship with innovative work behavior. In addition, transformational leadership was found to moderate the existence of a statistically significant negative influence between value, intrinsic motivation, and innovative work behavior. Conclusions - The results suggest that leaders will be successful in winning members' trust through conducting their behaviors in accordance with the applicable ethical and moral standards and through their fair, transparent, and legitimate management practices with an attitude of 'taking the initiative and setting an example', and this will help solve such problems.

• Journal of The Korean Astronomical Society
• /
• v.39 no.2
• /
• pp.31-40
• /
• 2006

Near-IR $H_2$ emission features in the northern region of the Orion A giant molecular cloud were observed in the $CO\;J\;=\;1\;{\rightarrow}\;0$ line in search of CO outflows. Out of the 30 sources surveyed, CO line wings were detected toward 28 positions, suggesting a strong correlation between $H_2$ jets and CO outflows. Blueshifted wings were detected toward 26 positions while redshifted wings were detected toward 15 positions, which suggests that there is a bias in the source selection. The bias is more severe in OMC 3 than in OMC 2. Since the protostars in OMC 3 are younger and more deeply embedded, the bias may be caused by the difference of extinction between blueshifted and redshifted outflows. Some physical parameters of the outflows were derived from the line profiles.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.3
• /
• pp.79-84
• /
• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.

• Journal of The Korean Association For Science Education
• /
• v.36 no.6
• /
• pp.935-946
• /
• 2016

This study aims to explore cognitive biases relating the core competences of science and instructional strategy in reducing the level of cognitive biases. The literature review method was used to explore cognitive biases and science education experts discussed the relevance of cognitive biases to science education. Twenty nine cognitive biases were categorized into five groups (limiting rational causal inference, limiting diverse information search, limiting self-regulated learning, limiting self-directed decision making, and category-limited thinking). The cognitive biases in limiting rational causal inference group are teleological thinking, availability heuristic, illusory correlation, and clustering illusion. The cognitive biases in limiting diverse information search group are selective perception, experimenter bias, confirmation bias, mere thought effect, attentional bias, belief bias, pragmatic fallacy, functional fixedness, and framing effect. The cognitive biases in limiting self-regulated learning group are overconfidence bias, better-than-average bias, planning fallacy, fundamental attribution error, Dunning-Kruger effect, hindsight bias, and blind-spot bias. The cognitive biases in limiting self-directed decision-making group are acquiescence effect, bandwagon effect, group-think, appeal to authority bias, and information bias. Lastly, the cognitive biases in category-limited thinking group are psychological essentialism, stereotyping, anthropomorphism, and outgroup homogeneity bias. The instructional strategy to reduce the level of cognitive biases is disused based on the psychological characters of cognitive biases reviewed in this study and related science education methods.