• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.658-667
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• 2021

Our study aimed to analyze and reinterpret, by an acoustic approach, the descriptions of the 18th century prosody and introduce the figurative pronunciation system, which is the International Phonetic Alphabet pioneer. Our methodology compares and analyzes grammars and documents on the transcription system and restructures the prosodic structure. It is certain that the 18th century grammarians widely accepted the prosody theories made by Arnauld & Lancelot of the seventeenth century. In particular, grammar scholars accepted the dichotomous classification of the accent structures as prosodic and oratorical accents. The prosodic accent has a relation to intonation, and the oratorical accent has as its key elements intonation and intensity. Regarding the temporal structure, the lengthening of the final syllable was observed systematically by grammarians of the 18th century. This time structure is similar to that of today. Therefore, we can conclude that the final elongation, an essential characteristic of the modern French accent, has already played an imbued role in 18th century prosody. Despite this, the 18th century grammarians did not assign it the status of accent, as it was a stereotype that matches accent with intonation.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.21-30
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• 2009

The purposes of this paper are to present a selection method of neighboring pixels whose local statistics are similar to the center pixel and combine the selection result with mean curvature diffusion filter to reduce noises in remote sensed imagery. The order of selection of neighboring pixels is critical, especially for finding a pixel belonging to the homogeneous region, since the statistics of the homogeneous region vary according to the selection order. An effective strategy for selecting neighboring pixels, which uses rank-order differences vector obtained by computing the intensity differences between the center pixel and neighboring pixels and arranging them in ascending order, is proposed in this paper. By using region growing method, we divide the elements of the rank-ordered differences vector into two groups, homogeneous rank-ordered differences vector and outlier rank-ordered differences vector. The mean curvature diffusion filter is combined with a line process, which chooses selectively diffusion coefficient of the neighboring pixels belonging into homogeneous rank-ordered differences vector. Experimental results using an aerial image and a TerraSAR-X satellite image showed that the proposed method reduced more efficiently noises than some conventional adaptive filters using all neighboring pixels in updating the center pixel.

• Phonetics and Speech Sciences
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• v.16 no.3
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• pp.39-48
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• 2024

Reading fluency refers to the ability to read sentences or paragraphs accurately, quickly, and with appropriate prosodic expression. Most reading fluency assessments exclude expressive ability because it is difficult to objectively measure. Therefore, in this study, we examined all elements of reading fluency by analyzing prosodic characteristics of reading scenario texts to maximize expressive reading. The subjects were 30 male students in the first and second grades of middle school (15 normal and 15 poor readers). To analyze the accuracy aspect, error types at the syllable level were analyzed for each group, and related acoustic variables were measured and examined in terms of prosodic aspects. The reading accuracy analysis showed that the poor reading group had a higher error rate than the normal. In terms of error types, the normal group showed the order of 'substitution>omission>correction>insertion>repetition', whereas the poor reading group was in the order of 'correction>substitution>repetition/insertion>omission'. For the speech tempo, the dyslexic students were slower than the typical students for all sentence types. The prosodic variables also showed a high frequency of accentual phrases (AP) and intonation phrases (IP) in sentences along with a wide intensity range.

• Clean Technology
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• v.18 no.4
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• pp.379-389
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• 2012

Environmental issues are being paid more attention due to income growth, urban overcrowding, and population growth in Korea. Among the various environmental problems, odor damage is the one of the serious factors. To take example for food waste combination treatment in Su-young wastewater treatment plant in Busan, many complaints occurred because this plant locate around residential areas. The purpose of this work is not only to analyze odorous elements and their contributions but also to evaluate odor quotient (OQ), sum of odor quotient (SOQ), and treatment efficiency of bio-filter. The results of dilution sensory test of complex odor, grinder, leachate, hopper indicated higher order complex odors happen in July and August. The main odorous elements consisted of hydrogen sulfide, ammonia, methly mercaptan and acetaldehyde, which were analyzed by instrumental detection method, and methyl mercaptan was exceeded over 3,571 times of threshold. In addition, result of contribution of odor was methyl mercaptan (49.95 to 59.08%), hydrogen sulfide (20.43 to 29.27%), trimethylamine (8.82 to 13.42%) and acetaldehyde (9.17 to 11.35%). Other facilities were compared with the contribution of the odor using OQ and SOQ during the process. Sulfur compounds, acetaldehyde, and trimethylamine are high contribution of odor using OQ as well as odor intensity of grinding process is highest. As a result, sulfur compounds (e.g., methyl mercaptan and hydrogen sulfide) are highest for OQ and SOQ of grinding process is highest as 7,067. The removal efficiency of deodorization equipment was more than 90.00% in ammonia and amines, but the average efficiency of sulfur compounds was 53.51%. Thus, this facility is more higher contribution of acetaldehyde and trimethylamine than other treatment facilities. And food waste treatment in environmental area needs to consider appropriate capacity and refers to other bio-filter operating conditions.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.3
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• pp.423-430
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• 2003

The teeth bleaching with bleaching agent is widely used at recent times. Until yet the exact mechanism of the bleaching agent isn't known but it is thought that is by the complex reduction-oxidation reaction of the decomposed free radical from bleaching agent through various ways. In other words, it is supposed that the teeth are whitened by agent's changing chemical structures of stain-causing materials. The purpose of this study is to exam the change of the dentinal character by bleaching agent and to evaluate the safety of this agent. For this study, after applying 10% carbamide peroxide to enamel of human premolar for 6 hours a day for 2 weeks we examined changes of surface morphology, microhardness, composition and contents of minirals in human dentin using SEM, microhardness tester, FT-Raman spectrometer and EPMA and got following results. There was no significant difference in surface morphologic change when we examined the effect of 10% carbamide peroxide which penetrated into dentin after applied on enamel surface comparing with result from specimen in distilled water No change was shown on the surface of peritubular and intertubular dentin within the nanometeric range. The microhardness between bleached teeth and teeth stored in distilled water showed no statistically significant difference FT-Raman spectra of dentin exhibited no change of the component in human dentin. Only the least change in peaks of organic and inorganic materials were detected in Raman intencity. The total content of mineral elements in dentin with no treatment, stored only in distilled water and stored in distilled water after bleaching were $98.73{\pm}1.89,\;98.56{\pm}2.11\;and\;97.47{\pm}2.51$ respectively. Also they showed no statistically significant difference. From above results, the effect of 10% carbamide peroxide bleaching on structure of dentin is very low and the results may confirm the safety of this bleaching agent.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.183-196
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• 2017

Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.

• Korean Journal of Ecology and Environment
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• v.49 no.4
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• pp.296-307
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• 2016

Ecological restoration is an eco-technology, which heals the nature damaged by human activity by imitating organization and function of the integrate nature and thereby provide an inhabitable space for diverse organisms. Such an ecological restoration has to be carried out by applying restoration plan prepared based on the results of diagnostic evaluation discussed in the diversified respects. This study aims to prepare an ecological restoration plan of the damaged forest ecosystem in Mt. Moodeung National Park. To arrive at the goal, first of all, we diagnosed quality of forest landscape established in Mt. Moodeung National Park based on natural (topography, climate, and distribution of vegetation) and artificial (land use, linear landscape element) factors. In addition, we evaluated the integrity of each zone divided by linear landscape element quantitatively based on geometric property and land use intensity. As the result of analysis, topography of Mt. Moodeung National Park tended to be depended on weathering property of parent rock and vegetation zones were divided to three vegetation zones. Based on land use pattern, deciduous broad-leaved forest, evergreen needle-leaved forest, and mixed forest occupied about 90% of Mt. Moodeung National Park. Mean score of forest landscape quality was shown in $69.86{\pm}11.41$. As a result, forest landscape elements in Mt. Moodeung National Park were influenced greatly by human activity and the degree was depended on topographic condition. This study suggested the synthetic restoration plan to improve ecological quality of Mt. Moodeung National Park based on the results of diagnostic evaluation.

• Journal of Food Hygiene and Safety
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• v.32 no.3
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• pp.179-186
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• 2017

For more efficient and proactive safety control of imported food, new trend in U.S. is emerging, which assesses the food safety control systems of exporting countries using Systems Recognition Assessment Tool and helps ensure safety of imported foods. This study examines trends in development and application of assessmemnt tool and country assessment reports in U.S. where an active discussion on this issue is in progress. The expert interviews were also conducted. U.S. Systems Recognition Assessment Tool was developed by FDA to recognize the potential value in leveraging the expertise of foreign food safety systems and help ensure safety of imported food. The tool is comprised of ten standards and provides an objective framework for determining the robustness of trading partners' overall food safety systems. Using its own tool, the U.S. FDA conducted a preliminary assessment of the food safety control systems of New Zealand and Canada. According to the U.S.-New Zealand and the U.S.-Canada assessment reports, the overall structure of the systems was similar between the countries. In summarizing the opinions of experts, such a trend in National Food Safety Control System Assessment may be utilized in the sanitary assessment and the control of imported food border inspection frequency before importing food. It would contribute to more effective distribution of national budget and increased public trust. Additionally, international collaboration as well as securing of qualified experts and sufficient budget appear to be crucial to further increase the utility of National Food Safety Control Systems Assessment. In conclusion, firstly, it is critically important for the competent authority of South Korea to proactively respond to international trend in National Food Safety Control System Assessment by identifying the details of its background, assessment purpose, core assessment elements, and assessment procedures. Secondly, it is necessary to identify and complement the weaknesses of Korea's food safety control system by reviewing it with U.S. Systems Recognition Assessment Tool. Thirdly, by adapting the assessment results from imported countries' food safety control systems to the imported food inspection intensity, the resources previously used in inspecting the imported food from accredited countries can be redistributed to inspecting the imported food from unaccredited countries, and it would contribute to more efficient imported food safety control. Fourthly, the competent authority of South Korea should also consider developing its own assessment tool designed to reflect the unique characteristics of its food safety control system and international guidelines.

• Journal of the Mineralogical Society of Korea
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• v.5 no.2
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• pp.109-121
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• 1992

For the purpose of mineralogical and chemical study on the topazes from various localities of world(Brzail, China, India, Nigeria and Sri Lanka), electron microprobe analysis(EPMA), neutron activation analysis(NAA), X-ray diffractometry, Raman spectroscopy, etch test, scanning electron microscopy, refractive index, specific gravity, fluid inclusion were performed. The chemical composition in topaz was discussed along with its physical and structural properties. Variations in the unit-cell dimension and physical properties of topaz were found to have a close relations in the unit-cell dimension and physical properties of topaz were found to have a close relationship with extent of substitution of $OH^-\;for\;F^-$. According to neutron activation analyses, the trace elements had no effects on the physical properties of topaz. Raman spectra showed that the peaks of topaz were different in intensity from one locality to another. Etching defects in topaz includes negative crystal defect o point-bottom pit(India, Nigeria) and net work defect of curl-bottom pit(Brazil, China). Fluid inclusions in topaz may be classiffied into liquid $CO_2$-bearing inclusion, gaseous inclusion, halite, sylvite-bearing inclusion and liquid inclusion. The results of this study can be useful to devising artificial coloring methods for topaz with different mineralogical compositions.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.