• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.175-190
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• 2022

Abusive supervision occurs in a social context in which third-party observers react and interact with the abused victims and supervisors. Despite the importance of third-party observers' behavior in abusive supervision, research on abusive supervision has mainly focused on the dyadic relationship between direct victims and supervisors. Although in recent years research on third parties' reactions to peer abusive supervision has attracted growing attention, there are still insufficient studies examining the topic especially within domestic research in Korea. As such, this study comprehensively reviews empirical studies on third parties' reactions to peer abusive supervision and aims to broaden the scope of research in the field. Firstly, the results of previous studies show that the effects of observed peer abusive supervision are mediated by cognitive and affective processes. Secondly, previous studies are found to investigate the boundary conditions where the effects of observed peer abusive supervision can be amplified or mitigated with regard to various outcomes. Overall, compared to research on direct victims, research on third-party observers of abusive supervision is found to capture a wider spectrum of responses. In order to explain the mechanisms of this phenomena, this study thoroughly examines theoretical assumptions presented in previous studies and categorizes them into five theory types. Finally, this study identifies a couple of central methodological issues, including common method bias and inadequate model specification in the literature and suggests future research directions.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.157-165
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• 2006

The change of external/internal factors of the cell rquires specific biological functions to maintain life. Such functions encourage particular genes to jnteract/regulate each other in multiple ways. Accordingly, we applied a linear decomposition model IFSA, which derives hidden variables, called the 'expression mode' that corresponds to the functions. To interpret gene interaction/regulation, we used a cross-correlation method given an expression mode. Linear decomposition models such as principal component analysis (PCA) and independent component analysis (ICA) were shown to be useful in analyzing high dimensional DNA microarray data, compared to clustering methods. These methods assume that gene expression is controlled by a linear combination of uncorrelated/indepdendent latent variables. However these methods have some difficulty in grouping similar patterns which are slightly time-delayed or asymmetric since only exactly matched Patterns are considered. In order to overcome this, we employ the (IFSA) method of [1] to locate phase- and shut-invariant features. Membership scoring functions play an important role to classify genes since linear decomposition models basically aim at data reduction not but at grouping data. We address a new function essential to the IFSA method. In this paper we stress that IFSA is useful in grouping functionally-related genes in the presence of time-shift and expression phase variance. Ultimately, we propose a new approach to investigate the multiple interaction information of genes.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.217-223
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• 2008

Amylose and protein contents are important traits determining the edible quality of rice, especially in East Asian countries. Near-Infrared Reflectance Spectroscopy (NIRS) has become a powerful tool for rapid and nondestructive quantification of natural compounds in agricultural products. To test the practically of using NIRS for estimation of brown rice amylose and protein contents, the spectral reflectances ($400{\sim}2500\;nm$) of total 9,483 accessions of rice germplasm in Rural development Administration (RDA) Genebank ere obtained and compared to chemically determined amylose and protein content. The protein content of tested 119 accessions ranged from 6.5 to 8.0% and 25 accessions exhibited protein contents between 8.5 to 9.5%. In case of amylose content, all tested accessions ranged from 18.1 to 21.7% and the grade from 18.1 to 19.9% includes most number of accessions as 152 and 4 accessions exhibited amylose content between 20.5 to 21.7%. The optimal performance calibration model could be obtained from original spectra of brown rice using MPLS (Modified Partial Least Squares) with the correlation coefficients ($r_2$) for amylose and protein content were 0.865 and 0.786, respectively. The standard errors of calibration (SEC) exhibited good statistic values: 2.078 and 0.442 for amylose and protein contents, respectively. All these results suggest that NIR spectroscopy may serve as reputable and rapid method for quantification of brown rice protein and amylose contents in large numbers of rice germplasm.

• KSBB Journal
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• v.24 no.1
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• pp.1-8
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• 2009

In the past decade, we have observed rapid advances in the development of biochips in many fields including medical and environmental monitoring. Biochip experiments involve immobilizing a ligand on a solid substrate surface, and monitoring its interaction with an analyte in a sample solution. Metal nanoparticles can display extinction bands on their surfaces. These charge density oscillations are simply known as the localized surface plasmon resonance (LSPR). The high sensitivity of LSPR has been utilized to design biochips for the label-free detection of biomolecular interactions with various ligands. LSPR-based optical biochips and biosensors are easy to fabricate, and the apparatus cost for the evaluation of optical characteristics is lower than that for the conventional surface plasmon resonance apparatus. Furthermore, the operation procedure has become more convenient as it does not require labeling procedure. In this paper, we review the recent advances in LSPR research and also describe the LSPR-based optical biosensor constructed with a core-shell dielectric nanoparticle biochip for its application to label-free biomolecular detections such as antigen-antibody interaction.