• Advances in nano research
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• v.12 no.2
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• pp.197-212
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• 2022

The purpose of this study is to develop an automatic software system for bone age evaluation and to evaluate its accuracy in testing and feasibility in clinical practice. 20394 left-hand radiographs of healthy children (2-18 years old) were collected from China Skeletal Development Survey data of 1998 and China Skeletal Development Survey data of 2005. Three experienced radiologists and China-05 standard maker jointly evaluate the stages of bone development and the reference bone age was determined by consensus. 1020 from 20394 radiographs were picked randomly as test set and the remaining 19374 radiographs as training set and validation set. Accuracy of the automatic software system for bone age assessment is evaluated in test set and two clinical test sets. Compared with the reference standard, the automatic software system based on RUS-CHN for bone age assessment has a 0.04 years old mean difference, ±0.40 years old in 95% confidence interval by single reading, a 85.6% percentage agreement of ratings, a 93.7% bone age accuracy rate, 0.17 years old of MAD, 0.29 years old of RMS; Compared with the reference standard, the automatic software system based on TW3-C RUS has a 0.04 years old mean difference, a ±0.38 years old in 95% confidence interval by single reading, a 90.9% percentage agreement of ratings, a 93.2% bone age accuracy rate, a 0.16 years of MAD, and a 0.28 years of RMS. Automatic software system, AI-China-05 showed reliably accuracy in bone age estimation and steady determination in different clinical test sets.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.93-102
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• 2023

Objectives: With the evolution of direct reading sensors, it is possible to monitor several substances through telecommunication. However, there are some limitations on the use of direct reading technologies in the Occupational Safety and Health Act in South Korea, which only applies to detector tubes, noise, heat, and carbon monoxides. The number of chemicals and their amount of use have been continuously increasing in South Korea. The Ministry of Employment and Labor (MoEL) has concerns about worker's health because exposure is only covered for about 1.2% of all distributed chemicals. Using a direct reading monitor with photoionization detectors (PID-DRMs), gases and vapors chemicals can be measured. Based on the data, business owners are able to create corrective strategies, provide better working routines, and select correct respiratory equipment. PID-DRMs are less expensive and easier to handle for an owner voluntarily controlling chemicals emitted in the workplace. However, there are several limitations on using these PID-DRMs to the degree that the MoEL has not been able to select a legal monitor. The aim of this study was to review previous studies related to PID-DRMs and identify the characterization and limitation on PID-DRMs. Methods: To search for related studies on PID-DRMs, key words were used including direct reading monitors/instruments and/or photoionization detectors. Through that, four domestic and 15 international studies were reviewed. Results: Studies on PID-DRMs were conducted by chamber (enclosed, dynamic, walk-in) and in the field (experimental environment, actual environment). The concentration of PID-DRMs and charcoal tubes were compared for a single substance or mixture, or within the PID-DRMs. There was a high correlation between the two concentrations, but it did not meet the accuracy criteria (95% confidence interval, within 25%) of the NIOSH technical report (2012). In addition, differences in measured values occurred according to environmental factors (temperature, humidity) and high concentration, and concentration values tended to be underestimated due to contamination of the sensor. As a way to improve the accuracy of PID concentration, it was proposed to use correction factors, charcoal tube-based correction factors, or to calibrate the PID-DRMs in the same environment as the workplace. Conclusions: PID-DRMs can likely be used by business owners for the purpose of voluntarily managing the workplace environment, and it is expected that it will be possible to use them as legal equipment if a PID sensor can be upgraded and the limitations of the sensor (temperature, humidity, high concentration evaluation, sensor pollution) can be overcome in the near future.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.476-484
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• 2014

The purpose of this study was to investigate the characteristics of reading, writing fluency of the underachieving children and stuttering children and school-aged children and frequency of errors. The participants were 15 underachieving children and 15 stuttering children and 15 school-aged children without disabilities. All participants were required to conduct reading, writing, speaking tasks. First, work for the reading tasks were different among the underachieving children and stuttering children and school-aged children. Second, writing tasks were not different among the groups in the writing fluency, but it was lacking in accuracy, which is stuttering, speaking fluency as well as their language fluency is suggesting the need for diagnosis and intervention. Third, this type of errors of writing tasks is showed higher levels of ommission, substitution, grammatical errors in the underachieving children group. The therapy of reading of stuttering also consider a treatment program that can be configured in the combined writing tasks.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2017-2025
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• 2021

Objective: To evaluate the accuracy and clinical efficacy of a hybrid Greulich-Pyle (GP) and modified Tanner-Whitehouse (TW) artificial intelligence (AI) model for bone age assessment. Materials and Methods: A deep learning-based model was trained on an open dataset of multiple ethnicities. A total of 102 hand radiographs (51 male and 51 female; mean age ± standard deviation = 10.95 ± 2.37 years) from a single institution were selected for external validation. Three human experts performed bone age assessments based on the GP atlas to develop a reference standard. Two study radiologists performed bone age assessments with and without AI model assistance in two separate sessions, for which the reading time was recorded. The performance of the AI software was assessed by comparing the mean absolute difference between the AI-calculated bone age and the reference standard. The reading time was compared between reading with and without AI using a paired t test. Furthermore, the reliability between the two study radiologists' bone age assessments was assessed using intraclass correlation coefficients (ICCs), and the results were compared between reading with and without AI. Results: The bone ages assessed by the experts and the AI model were not significantly different (11.39 ± 2.74 years and 11.35 ± 2.76 years, respectively, p = 0.31). The mean absolute difference was 0.39 years (95% confidence interval, 0.33-0.45 years) between the automated AI assessment and the reference standard. The mean reading time of the two study radiologists was reduced from 54.29 to 35.37 seconds with AI model assistance (p < 0.001). The ICC of the two study radiologists slightly increased with AI model assistance (from 0.945 to 0.990). Conclusion: The proposed AI model was accurate for assessing bone age. Furthermore, this model appeared to enhance the clinical efficacy by reducing the reading time and improving the inter-observer reliability.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.145-166
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• 2021

The study was aimed at verifying the effectiveness of Book-Coding reading education as a reader activity of older elementary school children at a time when high-dimensional thinking abilities were formed. To this end, 30 fifth-grade children of N Elementary School in N-si, Gyeonggi-do, comprised of 15 students from a reading education program using Book-Coding, and 15 students from a reading comprehension program, and applied the reading education program over a total of 12 sessions. The main results of the study are summarized as follows. First, when the effects of the convergence reading education program using Book-Coding on the logical thinking ability of the students in the upper grades in the elementary school were analyzed, all the six sub-factors of logical thinking ability, that is, conservation logic, proportional logic, variable controlling logic, probabilistic logic, correlational inference logic, and combinational logic, were proved to have statistically more meaningful difference than the group writing a book report. Second, the analysis result of the influence of the convergence reading education program using Book-Coding on the creativity of the students in the upper grades of the elementary school showed that all the 13 elements of curiosity, persistence, effectiveness, independence, adventurousness, openness, knowledge, imagination, originality, sensitivity, fluency, flexibility, and accuracy were statistically meaningfully different compared to the book report group. Third, when it was analyzed how the convergence reading education program using Book-Coding affected the creative personality of the elementary school students, all the six factors of curiosity, task commitment, independence, awareness of risk, and openness of thinking, and aesthetics were found out to have a statistically more meaningful difference than the group that wrote a book report.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1837-1851
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• 2016

Newspaper reader mobile applications using text-to-speech (TTS) function enable blind people to read newspaper contents. But, tables cannot be easily read by the reader program because most of the tables are stored as images in the contents. Even though we try to use OCR (Optical character reader) programs to recognize letters from the table images, it cannot be simply applied to the table reading function because the table structure is unknown to the readers. Therefore, identification of exact location of each table cell that contains the text of the table is required beforehand. In this paper, we propose an efficient image processing algorithm to recognize all the cells in tables by identifying columns and rows in table images. From the cell location data provided by the table column and row identification algorithm, we can generate table structure information and table reading scenarios. Our experimental results with table images found commonly in newspapers show that our cell identification approach has 100% accuracy for simple black and white table images and about 99.7% accuracy for colored and complicated tables.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.3
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• pp.18-27
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• 2015

Many studies have shown that having perception of spatial information is important for air traffic control officer (ATCO) since it helps them understand the current situation and predict the situation it leads to. However, little or no research has been done to investigate if there is any difference at the levels of expertise in perceiving spatial information and predicting a prospective situation. This study investigates the difference between expert and novice ATCO groups in how accurately each group of ATCO perceive spatial information such as position, altitude, speed, and flying direction, and predicting such information they will encounter shortly. In completing a task to watch the movement of airplanes displayed on the computer monitor as a blip, the participants were asked to predict the position, speed, and the altitude of the aircraft in a minute by marking on the sector map. The results show that the expert group performed better in accuracy and had tendency to overestimate on position and altitude; however, no significant difference was found between the two groups in terms of reading a flying direction. Therefore reading a flying direction may not be a reliable indicator to judge expertise of ATCO. But the expert group shows better predicting performance by perceiving spatial information such as airplane's position and altitude with feeling on time. The study suggests that it is important to enhance perceptive skills in ATCO training in improving their expertise in predicting accuracy traffic situation, preventing from air collision, and improving productivity for more efficient air traffic flow. A further study on the relationship between the perception of spatial information and the sense of time in predicting future information and effectiveness as an independent factor would contribute to providing more insights into expertise of ATCOs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1100-1105
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• 2006

Severe distortions of colors in the obtained images have made it difficult for color codes to expand their applications. To reduce the effect of color distortions on reading colors, it will be more desirable to statistically process as many pixels in the individual color region as possible, than relying on some regularly sampled pixels. This process may require segmentation, which usually requires edge detection. However, edges in color codes can be disconnected due tovarious distortions such as zipper effect and reflection, to name a few, making segmentation incomplete. Edge linking is also a difficult process. In this paper, a more efficient approach to reducing the effect of color distortions on reading colors, one that excludes precise edge detection for segmentation, was obtained by employing the k-means clustering algorithm. And, in detecting color codes, the properties of both six safe colors and grays were utilized. Experiments were conducted on 144, 4M-pixel, outdoor images. The proposed method resulted in a color-code detection rate of 100% fur the test images, and an average color-reading accuracy of over 99% for the detected codes, while the highest accuracy that could be achieved with an approach employing Canny edge detection was 91.28%.

• Korean Journal of Cognitive Science
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• v.23 no.4
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• pp.487-515
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• 2012

The purpose of this study was to investigate the effect of the individual differences in cognitive processes on paragraph comprehension. To do so, the lexical decision task and the pattern comparison task were used to measure the low-level cognitive processes. Digit span task was used to test the phonological loop capacity. The individual differences of the central executive processing capacity were measured by operational span task. Reading span task was used to test the working memory capacity related with the sentence processing. Reading times and accuracies of the logically valid inferences and logically void inferences were tested to measure the high-level cognitive processes. Reading times and accuracies for the target sentences with and without prior explicit causal sentence were measured to test individuals' paragraph comprehension abilities. The results showed that the speed of the low-level cognitive processes was related with the speed of the high-level cognitive processes. Also, the accuracy of the low-level cognitive processes was related with the accuracy of the high-level cognitive processes while there was no significant correlation between the speed and the accuracy in any measures of the cognitive processes. Working memory capacity was related with the accuracy of the cognitive processes while it was not significantly correlated with the speed of the cognitive processes. Most importantly, the speed of low-level cognitive processes significantly affected the speed of the paragraph comprehension while the working memory capacity and the high-level cognitive processes had influences on the accuracies of the paragraph comprehension. The speed of the paragraph comprehension had no influence on the accuracies of the paragraph comprehension.