• Safety and Health at Work
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• v.9 no.2
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• pp.140-143
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• 2018

Background: The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT) is a practical instrument that is currently used in the German woodworking and metalworking industries to monitor safety conditions at workplaces. The 12-item scoring system has three subscales rating technical, organizational, and personnel-related conditions in a company. Each item has a rating value ranging from 1 to 9, with higher values indicating higher standard of safety conditions. Methods: The reliability of this instrument was evaluated in a cross-sectional survey among 128 companies and its validity among 30,514 companies. The inter-rater reliability of the instrument was examined independently and simultaneously by two well-trained safety engineers. Agreement between the double ratings was quantified by the intraclass correlation coefficient and absolute agreement of the rating values. The content validity of the OSH-MAT was evaluated by quantifying the association between OSH-MAT values and 5-year average injury rates by Poisson regression analysis adjusted for the size of the companies and industrial sectors. The construct validity of OSH-MAT was examined by principle component factor analysis. Results: Our analysis indicated good to very good inter-rater reliability (intraclass correlation coefficient = 0.64-0.74) of OSH-MAT values with an absolute agreement of between 72% and 81%. Factor analysis identified three component subscales that met exactly the structure theory of this instrument. The Poisson regression analysis demonstrated a statistically significant exposure-response relationship between OSH-MAT values and the 5-year average injury rates. Conclusion: These analyses indicate that OSH-MAT is a valid and reliable instrument that can be used effectively to monitor safety conditions at workplaces.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.225-234
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• 2022

Innovation is not only one of the factors determining the competitiveness of national regions, but also an engine for economic development, and plays an important role in breaking out of the trap of middle-income countries. This paper constructs a regional innovation index from the perspectives of innovation input, innovation output, and innovation environment, and measures the regional innovation index of 31 provinces, municipalities, and autonomous regions in China from 2006 to 2019 by using principal component analysis and cluster analysis. The results concluded that there are large provincial and municipal differences in China's regional innovation capacities, and the provinces with higher comprehensive levels are mainly concentrated in the southeastern coastal region. Cluster analysis divides the 31 provinces, municipalities, and autonomous regions into five types, and the results find that the respectively developed coastal regions are in the high-level and the high-level regions relying on the advantages of location and national policies.

• Korean Institute of Interior Design Journal
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• no.16
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• pp.29-35
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• 1998

The purpose of this study is to analyze the elements forming interior design and to examine dimensional relationship among the elements which form space through the comparison of the spatial language and semiotics of space for the component of interior design. In addition to that it indtends to derive the principle of design which dominate interior design and the inherent diversified meaning by comparing those elements with the square of semiotic used in semiotics. Through this comparsion the meaning of constituent forming space which can be observed through the comparsion of square of semiotic has redefined flexbility among relational system of elements and this flexible concept make the scope of environment including human being broad and enriched. This study fist of all analyzes various phenomena of social culture review semiotics meta-learning and examines back theoretical ground of semiotics which is needed for space analysis. Second of all in the area of presenting an analysis tool for meaningful analysis this report introduces the square of semiotics which was invented,. A. J. Greimas in order to analyze the meaning of literary work and defind three categories of the progressive research method for the analysis of interior design and research itself. Finally as for the analysis of meaning for interior design this report sets the space and analyzed the space in accordance with the method and research procedure. being

• International Journal of Contents
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• v.15 no.1
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• pp.39-51
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• 2019

Spontaneous speech provides rich information defining the linguistic characteristics of individuals. As such, computational analysis of speech would enhance the efficiency involved in evaluating patients' speech. This study aims to provide a method to differentiate the persons with and without aphasia based on language usage. Ten aphasic patients and their counterpart normal controls participated, and they were all tasked to describe a set of given words. Their utterances were linguistically processed and compared to each other. Computational analyses from PCA (Principle Component Analysis) to machine learning were conducted to select the relevant linguistic features, and consequently to classify the two groups based on the features selected. It was found that functional words, not content words, were the main differentiator of the two groups. The most viable discriminators were demonstratives, function words, sentence final endings, and postpositions. The machine learning classification model was found to be quite accurate (90%), and to impressively be stable. This study is noteworthy as it is the first attempt that uses computational analysis to characterize the word usage patterns in Korean aphasic patients, thereby discriminating from the normal group.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.84-95
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• 2011

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.72-79
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• 2002

This paper presents an efficient face detection algorithm for color images with a complex background. The presented algorithm utilizes the color information and eigenface that is calculated by PCA-LDA (Principle Component Analysis - Linear Discriminant Analysis). The method of using the color information is faster than any other methods. Eigenface includes average information of the whole test faces. Therefore eigenface can decide that the candidate region is a face. The whole process is composed of two steps. First, it finds first face candidates region of skin tone using a color information in image. We can get a size and position of face candidate region. Second, we compare first face candidate region with eigenface, so decide that an image whether include a face or not. The advantages of the proposed approach include that increasing the detection speed by deciding a size and position of first face candidates region. Also, Betting 97% of the detection rate by comparing the eigenfaces calculated in PCA-LDA.

• Near Infrared Analysis
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• v.1 no.2
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• pp.21-27
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• 2000

Temperature-dependent changes in near-infrared (NIR) spectra have been measured for oleic acid, and nonanoic acid in the pure liquid state. Particular attention has been paid to the 5400-4800 cm$\^$-1/ region where a number of combination bands appear. The NIR spectra of oleic acid show that a band at 5303 cm$\^$-1/ increases with temperature while that at 5270 cm/sup-1/ decreases. It ha been found from their second derivative spectra that these spectral changes take place stepwisely with two break points at 30 and 53$\^{C}$, which correspond to the phase transition temperatures oleic acid reported previously. Principle component analysis (PCA) has been carried out for the NIR spectra of oleic acid in the 5400-4800 cm$\^$-1/ region measured over a temperature range of 15-80$\^{C}$. core plots of the first and second principal components (PCs) show that the NIR spectra are classified into three groups; the spectra measured in the temperature range of 15-30$\^{C}$, those in the range of 31-53$\^{C}$, and those in the range of 54-80$\^{C}$. These temperature ranges correspond to those for quasi-smectic liquid crystal, disordered liquid crystal, and isotropic liquid of oleic acid in the pure liquid state. In other words, PCA provides unambiguous evidence for the phase transitions. similar studies have been carried out for petroselinic acid and nonanoic acid in the pure liquid states, but they do not show any evidence for phase transitions.

• Food Science and Preservation
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• v.30 no.4
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• pp.602-616
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• 2023

Fifteen types of rice collected from Kurdistan region-Iraq were investigated by principal component analysis (PCA) in terms of physical properties and cooking characteristics. The dimensions of evaluated grains correspond to 5.05-8.75 mm for length, 1.54-2.47 mm for width, and 1.37-1.95 for thickness. The equivalent diameter was in the range of 5.23-10.03 mm, and the area took 13.30-28.25 mm². The sphericity analysis values varied from 0.32 to 0.56, the aspect ratio from 0.17 to 0.39, and the volume of the grain was measured in the range from 4.48 to 17.74 mm³, hectoliter weight values were 730-820 kg/m³, and true density from 0.6 to 0.96 g/cm³. The broken grain ratio was 1.5-18.3%, thousand kernel weight corresponded to 15.88 to 22.42 g. The water uptake ratios for 30 min of soaking were increased at 60℃ compared to 30 and 45℃. The PCA was used to study the correlation of the most effective factors. Results of PCA showed that the first (PC1) and second (PC2) components retained 63.4% and 34.8% of the total variance, which PC1 was mostly related to hectoliter, broken ratio, and moisture content characteristics while PC2 was mostly concerned with hardness and true density. For cooking properties, the PC1 and PC2 retained 88.5% and 9.3% of the total variance, respectively. PC1 was mostly related to viscosity, spring value, and hardness after cooking, while PC2 was mostly concerned with spring value, hardness before cooking, and hardness after cooking.

• KCID journal
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• v.17 no.2
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• pp.17-27
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• 2010

In order to manage the water quality in reservoir, it is necessary to understand the temporal and spatial variation of reservoirs and to classify the reservoirs. In this research, agricultural reservoirs are classified according to physical characteristics (depth, residence time, shape of the reservoir etc) and water quality using multivatriate analysis (PCA and CA). CA (Cluster Analysis) method classify reservoirs into several groups as a similarity of the reservoirs, but it is difficult to indicate a full list to the one table. In case of PCA (Principle Component Analysis) method, it has the advantage for the classification on the reservoirs depending on the water quality similarity and also it is useful to analyze the relationship between related factors through correlation analysis. However PCA is limited to classify into several groups based on the characteristics of the reservoirs and each user should be classified as randomly subjective according to the relative position of the reservoir in the figure. In conclusions, compared to conventional reservoirs classification methods, both CA and PCA methods are considered to be a classification method that describes the nature of the reservoir well, but classification results has a restriction on use, so further research will be needed to complement.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.107-114
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• 2009

Human walking is essential and important mean of transportation. Pedestrian safety is recently important because accidents often happen while walking. This research is showing that Walking-environmental factors have effect on safety while walking. At first, exact 15 factors and conduct survey in the preceding research. After that, exact 4 important factors through factor analysis. At result of Multiple regression analysis, null hypothesis has proved to be true by satisfying therms which is F-value 9.211 and P-value 0.000. and come to the conclusion that walking-environmental factors influence pedestrian safety. 4 important factors can be listed by below. Pedestrian-road characteristic, landscape characteristic, commercial characteristic, walking characteristics by following influence. Especially, landscape characteristic and pedestrian-road characteristic can be vital factors.