• Journal of the Korean Society of Radiology
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• v.81 no.1
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• pp.21-40
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• 2020

Magnetic resonance imaging (MRI) is an essential modality for the diagnosis of musculoskeletal system defects because of its higher soft-tissue contrast and spatial resolution. With the recent development of MRI-related technology, faster imaging and various image plane reconstructions are possible, enabling better assessment of three-dimensional musculoskeletal anatomy and lesions. Furthermore, the image quality, diagnostic accuracy, and acquisition time depend on the MRI protocol used. Moreover, the protocol affects the efficiency of the MRI scanner. Therefore, it is important for a radiologist to optimize the MRI protocol. In this review, we will provide guidance on patient positioning; selection of the radiofrequency coil, pulse sequences, and imaging planes; and control of MRI parameters to help optimize the MRI protocol for the six major joints of the musculoskeletal system.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.869-879
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• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.236-244
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• 2024

A representative problem in domestic chestnut industry is the high loss of flesh due to excessive knife peeling in order to increase the peeling rate, resulting in a decrease in production efficiency. In this study, a prediction model for weight loss rate of chestnut by stage of knife peeling process was developed as undergarment study to optimize conditions of the machine. 51 control conditions of the two-stage blade peeler used in the experiment were derived and repeated three times to obtain a total of 153 data. Machine learning(ML) models including artificial neural network (ANN) and random forest (RF) were implemented to predict the weight loss rate by chestnut peel stage (after 1st peeling, 2nd peeling, and after final discharge). The performance of the models were evaluated by calculating the values of coefficient of determination (R), normalized root mean square error (nRMSE), and mean absolute error (MAE). After all peeling stages, RF model have better prediction accuracy with higher R values and low prediction error with lower nRMSE and MAE values, compared to ANN model. The final selected RF prediction model showed excellent performance with insignificant error between the experimental and predicted values. As a result, the proposed model can be useful to set optimum condition of knife peeling for the purpose of minimizing the weight loss of domestic chestnut flesh with maximizing peeling rate.

• Advances in nano research
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• v.17 no.3
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• pp.213-219
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• 2024

Nanotechnology is one of the critical factors involved in enhancing the sensitivity of serum biomarker detection. To explore the relationship between serum APN, Cystatin C and MMP-9 levels in patients with hypertension during pregnancy and the severity and prognosis of the disease. A total of 75 cases of hypertensive disorder complicating pregnancy (HDCP) patients who were admitted to the hospital from February 5, 2023 to May 9, 2024, were selected as the study group, and 70 healthy pregnant women who were in the same gestational week were selected as the control group. The serum APN, MMP-9 and Cys C levels of pregnant women and HDCP patients with different disease severity were compared between the two groups, and the receiver characteristic curve (ROC) was used to analyze its diagnostic value. The serum APN, MMP-9 and Cys C levels of HDCP patients with different prognosis were compared, and the factors affecting the prognosis of patients were analyzed by Logistic regression. Nanoparticles could aslo enable the sensitive detection and quantification of APN, Cystatin C, and MMP-9 in serum samples, thus increasing the accuracy of the study. The serum MMP-9 and Cys C levels of pregnant women in the study group were significantly increased, and the APN level was significantly decreased (P<0.05). Serum MMP-9 and Cys C levels in patients with pregnancy-induced hypertension, mild preeclampsia, and severe preeclampsia gradually increased (r=0.768, 0.766; P<0.001), and APN levels gradually decreased (r=-0.748, P< 0.001). In the diagnosis of patients with HDCP, the sensitivity, specificity and AUC of APN single diagnosis were 70.00%, 82.67% and 9.848 respectively. The sensitivity, specificity and AUC of MMP-9 single diagnosis were 82.86%, 74.67% and 298.300 respectively. The sensitivity, specificity and AUC of Cys C single diagnosis were 80.00%, 74.67% and 1.301 respectively. There were significant differences in age, BMI, parity, dysthymia, disease severity, APN, MMP-9 and Cys between patients with poor prognosis of HDCP and patients with good prognosis of HDCP (P<0.001). The patient's age, BMI, disease severity, APN, MMP-9 and Cys Cwere all related to HDCP. They were related risk factors of HDCP (P<0.05).

• The Transactions of the Korea Information Processing Society
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• v.13 no.9
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• pp.395-403
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• 2024

Recently, with the advancement of technology, the automotive industry has seen an increase in network connectivity. CAN (Controller Area Network) bus technology enables fast and efficient data communication between various electronic devices and systems within a vehicle, providing a platform that integrates and manages a wide range of functions, from core systems to auxiliary features. However, this increased connectivity raises concerns about network security, as external attackers could potentially gain access to the automotive network, taking control of the vehicle or stealing personal information. This paper analyzed abnormal messages occurring in CAN and confirmed that message occurrence periodicity, frequency, and data changes are important factors in the detection of abnormal messages. Through DBC decoding, the specific meanings of CAN messages were interpreted. Based on this, a model for classifying abnormalities was proposed using the GRU model to analyze the periodicity and trend of message occurrences by measuring the difference (residual) between the predicted and actual messages occurring within a certain period as an abnormality metric. Additionally, for multi-class classification of attack techniques on abnormal messages, a Random Forest model was introduced as a multi-classifier using message occurrence frequency, periodicity, and residuals, achieving improved performance. This model achieved a high accuracy of over 99% in detecting abnormal messages and demonstrated superior performance compared to other existing models.

• Research in Plant Disease
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• v.30 no.3
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• pp.256-267
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• 2024

We have developed FBcastS (Fire Blight Forecasting System), a cloud-based information system that leverages the K-Maryblyt forecasting model. The FBcastS provides an optimal timing for spraying antibiotics to prevent flower infection caused by Erwinia amylovora and forecasts the onset of disease symptoms to assist in scheduling field scouting activities. FBcastS comprises four discrete subsystems tailored to specific functionalities: meteorological data acquisition and processing, execution of the K-Maryblyt model, distribution of web-based information, and dissemination of spray timing notifications. The meteorological data acquisition subsystem gathers both observed and forecasted weather data from 1,583 sites across South Korea, including 761 apple or pear orchards where automated weather stations are installed for fire blight forecast. This subsystem also performs post-processing tasks such as quality control and data conversion. The model execution subsystem operates the K-Maryblyt model and stores its results in a database. The web-based service subsystem offers an array of internet-based services, including weather monitoring, mobile services for forecasting fire blight infection and symptoms, and nationwide fire blight monitoring. The final subsystem issues timely notifications of fire blight spray timing alert to growers based on forecasts from the K-Maryblyt model, blossom status, pesticide types, and field conditions, following guidelines set by the Rural Development Administration. FBcastS epitomizes a smart agriculture internet of things (IoT) by utilizing densely collected data with a spatial resolution of approximately 4.25 km to improve the accuracy of fire blight forecasts. The system's internet-based services ensure high accessibility and utility, making it a vital tool in data-driven smart agricultural practices.

• Radiation Oncology Journal
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• v.26 no.4
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• pp.237-246
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• 2008

Purpose: Three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) were found to reduce the incidence of acute and late rectal toxicity compared with conventional radiation therapy (RT), although acute and late urinary toxicities were not reduced significantly. Acute urinary toxicity, even at a low-grade, not only has an impact on a patient's quality of life, but also can be used as a predictor for chronic urinary toxicity. With bladder filling, part of the bladder moves away from the radiation field, resulting in a small irradiated bladder volume; hence, urinary toxicity can be decreased. The purpose of this study is to evaluate the impact of bladder volume on acute urinary toxicity during RT in patients with prostate cancer. Materials and Methods: Forty two patients diagnosed with prostate cancer were treated by 3DCRT and of these, 21 patients made up a control group treated without any instruction to control the bladder volume. The remaining 21 patients in the experimental group were treated with a full bladder after drinking 450 mL of water an hour before treatment. We measured the bladder volume by CT and ultrasound at simulation to validate the accuracy of ultrasound. During the treatment period, we measured bladder volume weekly by ultrasound, for the experimental group, to evaluate the variation of the bladder volume. Results: A significant correlation between the bladder volume measured by CT and ultrasound was observed. The bladder volume in the experimental group varied with each patient despite drinking the same amount of water. Although weekly variations of the bladder volume were very high, larger initial CT volumes were associated with larger mean weekly bladder volumes. The mean bladder volume was $299{\pm}155\;mL$ in the experimental group, as opposed to $187{\pm}155\;mL$ in the control group. Patients in experimental group experienced less acute urinary toxicities than in control group, but the difference was not statistically significant. A trend of reduced toxicity was observed with the increase of CT bladder volume. In patients with bladder volumes greater than 150 mL at simulation, toxicity rates of all grades were significantly lower than in patients with bladder volume less than 150 mL. Also, patients with a mean bladder volume larger than 100 mL during treatment showed a slightly reduced Grade 1 urinary toxicity rate compared to patients with a mean bladder volume smaller than 100 mL. Conclusion: Despite the large variability in bladder volume during the treatment period, treating patients with a full bladder reduced acute urinary toxicities in patients with prostate cancer. We recommend that patients with prostate cancer undergo treatment with a full bladder.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.6 no.1
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• pp.24-31
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• 2003

Purpose: As diagnostic tools for Hirschsprung's disease (HD), barium enema and rectal biopsy have radiation exposure and invasiveness respectively; however anorectal manometry does not have these disadvantages. We therefore performed this study to evaluate the diagnostic efficacy of anorectal manometry. Methods: We reviewed medical records of infants with one or two symptoms of vomiting, abdominal distension, chronic diarrhea or constipation who had a anorectal manometry followed by barium enema and/or biopsy from July 1995 to May 2002. We evaluated the sensitivity, specificity and predictive value of anorectal manometry and barium enema for diagnosis of HD. We also measured sphincter length, median value of balloon volume at which rectoanal inhibitory reflex (RAIR) occurred. Results: All 61 patients received anorectal manometry, 33 of 61 received barium enema. 18 of 61 were diagnosed as HD according to histology and 43 of 61 were evaluated as a control. The sensitivity, specificity, positive predictive value, negative predictive value of anorectal manometry and barium enema for diagnosis of HD were 1.00, 0.91, 0.82, 1.00 and 0.93, 0.67, 0.70, 0.92 respectively. The mean value of sphincter length in control was $1.68{\pm}0.67$ cm and correlated with age, weight and significantly longitudinal length. The median value of balloon volume at which RAIR occurred was 10 mL and did not correlated with age, weight and longitudinal length. Conclusion: This study suggests that anorectal manometry is an excellent initial screening test for Hirschsprung's disease because of its safety and accuracy.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.143-155
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• 2018

The Natural Landscape Rating System was introduced in the amendment of the NATURAL ENVIRONMENT CONSERVATION ACT in 2006. For landscape preservation, the system aims to consider the effects of development projects or plans implemented in a natural landscape on skylines, scenic resources, and view corridors. Currently, a lack of consistency in standards for determining Landscape Control Points (LCP) to assess landscape impact lowers the accuracy and reliability of the assessment results. As the perception of and the impact on a landscape varies, depending on the location of the LCP, it is necessary to establish a reasonable set of criteria to select viewpoints and avoid unreliability in the assessment due to unclear criteria. The intent of this study is to propose an objective and reasonable set of criteria for LCP selection to effectively measure the impact on the landscape from development projects that anticipate a change in the landscape and, ultimately, to suggest basic analysis methods to assess the landscape impact of development projects and to monitor the landscape in the future. Among the development projects affecting natural landscapes, as reported in the statement of the environmental impact assessment, cases of construction of a single building or other small-scale development projects were studied. Four spot development projects were analyzed in depth for their landscape impacts, in order to make recommendations for the LCP selection procedure, which aims to widen the scope of selection according to the direction of viewpoints from the target site. The existing results of analysis based on LCP have limitations because they failed to cover the viewshed of the target buildings when there are topographical changes in the surroundings. As a solution to this problem, a new viewshed analysis method has been proposed, with a focus on the development site and target buildings, rather than viewpoints, as used in past analysis.

• The Journal of Korean Academy of Sensory Integration
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• v.13 no.1
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• pp.13-22
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• 2015

Objective : The aim of this study is to verify validity of Long Form Assessment, which is an Interactive Metronome $measure^{(R)}$(LFA-IM), as a measurement of praxis of children. Methods : The study was implemented from March 2015 to July 2015. Twenty-five children with Attention Deficit Hyperactivity Disorder (ADHD) and those without ADHD (age of 6~11) were selected from a local university hospital and community in Gyeoung-Nam province and Busan for this study. In order to examine discriminative validity of LFA-IM, Bruininks-Oseretsky Test of Motor Proficiency, second edition (BOT-2) was used to compare the difference of results with LFA-IM for both children with- and without ADHD. For concurrent validity, correlation between LFA-IM and BOT-2 was investigated using spearman correlation coefficients. Results : For the comparison between children with ADHD and children without ADHD, there were significant differences in the total scores of LFA-IM (p<.05). Regarding the concurrent validity, there was a strong negative correlation between the total scores of LFA-IM and BOT-2 (p<.05). In addition, there was high correlation between LFA-IM and BOT-2 for the area of hand control (rs=-.532), and high negative correlation for the area of fine-motor accuracy (rs=-.447), hand dexterity (rs=-.532), and balance control (rs=-.623) (p<.05). Conclusion : This study identified validities of LFA-IM as an assessment of praxis of children. The results showed that it is appropriate to evaluate praxis of children with the total score of LFA-IM and, thus, it is believed that LFA-IM has a potential clinical utility. However, there should be more researches with large number of subjects.