• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.61-66
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• 2022

Sesamin and sesamolin are major lignan components with a wide range of potential biological activities of sesame seeds. Near infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analysis method widely used for the quantitative determination of major components in many agricultural products. This study was conducted to develop a screening method to determine the lignan contents for sesame breeding. Sesamin and sesamolin contents of 482 sesame samples ranged from 0.03-14.40 mg/g and 0.10-3.79 mg/g with an average of 4.93 mg/g and 1.74 mg/g, respectively. Each sample was scanned using NIRS and calculated for the calibration and validation equations. The optimal performance calibration model was obtained from the original spectra using partial least squares (PLS). The coefficient of determination in calibration (R²) and standard error of calibration (SEC) were 0.963 and 0.861 for sesamin and 0.875 and 0.292 for sesamolin, respectively. Cross-validation results of the NIRS equation showed an R² of 0.889 in the prediction for sesamin and 0.781 for sesamolin and a standard error of cross-validation (SECV) of 1.163 for sesamin and 0.417 for sesamolin. The results showed that the NIRS equation for sesamin and sesamolin could be effective in selecting high lignan sesame lines in early generations of sesame breeding.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.277-284
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• 2020

This thesis interrogates the term a performer's 'spontaneity' as the key principle to approach and enhance contemporary performer's training and acting. Drawing on a number of problematic issues, this thesis particularly examines the paradigm of the subtle bodily movement inform the experience of a performer's spontaneity as embodied and understood in approaching and adapting through text analysis and action. The in-depth process of the relationship between a performer's action and the transformative effects, is central to understanding and adapting the key principle of acting/training that a specific text would pursue through a specific performance by means of what a performer must do on stage. Following the discussion of acting in training and rehearsal, this thesis argues the necessity of an alternative way(s) and model of the performer's work via how the performer's action is sincerely emerged from the moment-by-moment rather than the performer anticipates what comes in the next and therefore pretend to do/be something/someone. Expanding upon the assumptions mentioned above, this thesis provides some pragmatic and descriptive work(s) from the practitioners' concepts and approaches that invites us to reconsider the nature of acting and its adaptability for contemporary performers.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.65-73
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• 2021

This research analyzes the characteristics of Chinese tragic films with Chinese traditional ethical ideology as the core, analyzes its specific performance in the plot and ending setting of the film , and analyzes the director's tragic narrative strategy of cultural reconciliation in the face of political environment to understand the characteristics of Chinese contemporary tragic films.The film is a Chinese contemporary tragic film with The Great Cultural Revolution as its historical background. This film is a representative film of Chinese contemporary tragic films. The classic plot has played a certain role in the expression of Chinese traditional ethical ideology such as fatalism and optimistic attitude to life. The male lead's thought changes interpret the Chinese-style tragedy characteristics containing Chinese traditional ethical ideology. In the setting of the ending, the film broke through the "happy ending" model of Chinese traditional tragedies, and chose the open ending of "one tragedy to the end", further showing the time feature of Chinese contemporary tragic film. The euphemism and tenderness of the film as a tragic film is not only due to the compromise with the political culture of power, but also the result of the director's in-depth understanding of the aesthetics of Chinese tragedy. Through the use of symbolic signs in the film language, it has formed the implicit characteristics of the film narrative in the tragic aesthetic experience. In this paper, the author conducts text analysis for the film and discusses presentation of Director Yimou Zhang's tragic feelings and using the tragic narrative strategy of cultural reconciliation to show his creative wisdom in pursuing artistic breakthroughs under political pressure.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1633-1641
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• 2022

Urban population concentration and indiscriminate development are causing various environmental problems such as air pollution and heat island phenomena, and causing human resources to deteriorate the damage caused by natural disasters. Urban trees have been proposed as a solution to these urban problems, and actually play an important role, such as providing environmental improvement functions. Accordingly, quantitative measurement and analysis of individual trees in urban trees are required to understand the effect of trees on the urban environment. However, the complexity and diversity of urban trees have a problem of lowering the accuracy of single tree detection. Therefore, we conducted a study to effectively detect trees in Dongjak-gu using high-resolution aerial images that enable effective detection of tree objects and You Only Look Once Version 5 (YOLOv5), which showed excellent performance in object detection. Labeling guidelines for the construction of tree AI learning datasets were generated, and box annotation was performed on Dongjak-gu trees based on this. We tested various scale YOLOv5 models from the constructed dataset and adopted the optimal model to perform more efficient urban tree detection, resulting in significant results of mean Average Precision (mAP) 0.663.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.79-85
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• 2022

Anomaly detection is a method to detect and block abnormal data flows in general users' data sets. The previously known method is a method of detecting and defending an attack based on a signature using the signature of an already known attack. This has the advantage of a low false positive rate, but the problem is that it is very vulnerable to a zero-day vulnerability attack or a modified attack. However, in the case of anomaly detection, there is a disadvantage that the false positive rate is high, but it has the advantage of being able to identify, detect, and block zero-day vulnerability attacks or modified attacks, so related studies are being actively conducted. In this study, we want to deal with these anomaly detection mechanisms, and we propose a new mechanism that performs both anomaly detection and classification while supplementing the high false positive rate mentioned above. In this study, the experiment was conducted with five configurations considering the characteristics of various algorithms. As a result, the model showing the best accuracy was proposed as the result of this study. After detecting an attack by applying the Extra Tree and Three-layer ANN at the same time, the attack type is classified using the Extra Tree for the classified attack data. In this study, verification was performed on the NSL-KDD data set, and the accuracy was 99.8%, 99.1%, 98.9%, 98.7%, and 97.9% for Normal, Dos, Probe, U2R, and R2L, respectively. This configuration showed superior performance compared to other models.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.40-47
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• 2021

In this study, the structural behavior by the details of the lap region with the headed bar was estimated through finite element analysis. To solve the finite element analysis of the anchorage region with complex contact conditions and nonlinear behavior, a quasi-static analysis technique by explicit dynamic analysis was performed. The accuracy of the finite element model was verified by comparing the experimental results with the finite element analysis results. It was confirmed that the quasi-static analysis technique well reflected the behavior of enlarged headed bar connection. As a result of performing numerical analysis using 21 finite element models with various development lengths and transverse reinforcement indexes, it was confirmed that the increase of development length and transverse reinforcement index improved the maximum strength and ductility. However, to satisfy the structural performance, it should be confirmed that both design variables(development length and transverse reinforcement index) must be enough at the design criteria. In the recently revised design standard(KDS 14 20 52 :2021), a design formula of headed bar that considers both the development length and the transverse reinforcing bar index is presented. Also the results of this study confirmed that not only the development length but also transverse reinforcing bars have a very important effect.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.119-129
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• 2021

The process of constructing the DB in the current geotechnical information DB system needs a lot of human and time resource consumption. In addition, it causes accuracy problems frequently because the current input method is a person viewing the PDF and directly inputting the results. Therefore, this study proposes building an automatic digital DB using AI (artificial intelligence) of boring logs. In order to automatically construct DB for various boring log formats without exception, the boring log forms were classified using the deep learning model ResNet 34 for a total of 6 boring log forms. As a result, the overall accuracy was 99.7, and the ROC_AUC score was 1.0, which separated the boring log forms with very high performance. After that, the text in the PDF is automatically read using the robotic processing automation technique fine-tuned for each form. Furthermore, the general information, strata information, and standard penetration test information were extracted, separated, and saved in the same format provided by the geotechnical information DB system. Finally, the information in the boring log was automatically converted into a DB at a speed of 140 pages per second.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.426-436
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• 2022

This study aimed to explore the role of models and reformulations as feedback to English writing in L2 learners' noticing and their writing. 92 participants were placed into three groups; a models group (MG), a reformulations group (RG), a control group (CG), involved in a three-stage writing task. In stage 1, they were asked to perform a 1st draft of writing, while taking notes on the problems they experienced. In stage 2, the MG was asked to compare their writing with a model text and the RG with a reformulated version of it. They were instructed to write down whatever they noticed in their comparison. The CG was asked to just read their writing. In stage 3, all the participants attempted subsequent revisions. The results indicated that all the participants noticed problematic linguistic features the most in a lexical category, and models and reformulations led to higher rate of noticing the problematic linguistic features reported in stage 1 and contributed to subsequent revisions. It was also revealed that the MG and RG significantly improved with their writings of MG and RG on the post-writing test. The findings imply that models and reformulations result in better performance in L2 writing and should be promoted in an English writing class.