• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.175-181
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• 2022

The condition of infrastructure deteriorates as the service life increases. Since most infrastructure in South Korea were intensively built during the period of economic growth, the proportion of outdated infrastructure is rapidly increasing now. Aging of such infrastructure can lead to safety accidents and even human casualties. To prevent these issues in advance, periodic and accurate inspection is essential. For this reason, the need for research to detect various types of damage using computer vision and deep learning is increasingly required in the field of remotely controlled or autonomous inspection. To this end, this study proposed a neural network structure that can detect concrete damage by classifying it into three types. In particular, the proposed neural network can detect them more accurately through a hierarchical learning technique. This neural network was trained with 2,026 damage images and tested with 508 damage images. As a result, we completed an algorithm with average mean intersection over union of 67.04% and F1 score of 52.65%. It is expected that the proposed damage detection algorithm could apply to accurate facility condition diagnosis in the near future.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.7-15
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• 2023

Recently, as interest in air quality in vehicles increases, the use of fine dust detection sensors for air quality measurement is becoming common. An axial-flow fan is inserted in the fine dust sensor installed in the air conditioning system in the vehicle to prevent dust from sinking directly on the sensor. When the sensor operates, the flow noise caused by the rotation of the axial-flow fan acts as a major noise source of the fine dust sensor. flow noise is recognized as one of the product competitiveness of fine dust sensors. In this study, the noise was gradually reduced at the same flow rate by improving the flow performance of the small axial flow fan. First, a virtual fan performance tester consisting of about 20 million grids was developed to analyze the aerodynamic performance of the target small axial-flow fan. In addition, the flow field was simulated by using compressible Large Eddy Simulation for direct computation of flow noise as well as high-accurate prediction of flow rate. The validity of numerical method are confirmed through the comparison of predicted results with experimental ones. After the effects of pitch angle on flow performance were analyzed using the verified numerical method, the pitch angle was determined to maximize the flow rate. It was found that the flow rate was increased by 8.1 % and noise was reduced by 0.8 dBA when the axial-flow fan with the optimum pitch angle was used.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of Korean Clinical Nursing Research
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• v.29 no.2
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• pp.198-209
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• 2023

Purpose: The purpose of this study was to develop a Korean Adult Patients Delirium Screening Tool (K-APDS) for those admitted to general wards, and to verify its reliability and validity. Methods: For the development of the tool, 12 items were derived through the results of literature review and focus group interviews with general ward nurses, and the content validity was confirmed by experts. To verify the reliability and validity of the developed tool, 317 adult patients who were admitted to general wards of three tertiary general hospitals from October to November 2022 were evaluated by the attending nurse and data were collected. Results: After factor analysis for construct validity verification, two factors were extracted, which explained 60.1% of the total variance. After the validation of the control group, the difference in the delirium incidence scores calculated using the K-APDS between the delirium group and non-delirium group was very significant (Z=-10.82, p<.001). To verify the criterion validity, K-APDS, Delirium Observation Screening, and Pearson's correlation coefficient were checked and found to be .94 (p<.001). The predictive validity test reported that the sensitivity was 91.1%, specificity was 82.4%, positive predictive value was 52.6%, and negative predictive value was 97.8%. The reliability of K-APDS was found to be high with Cronbach's ⍺=.91. Conclusion: K-APDS can screen for delirium with 2 or more points, excellent validity and reliability have been verified. Therefore, this tool could be applied immediately in the clinical field, and will contribute to the early detection of delirium, enabling rapid interventions.

• Research in Plant Disease
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• v.29 no.1
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• pp.52-59
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• 2023

Cucurbit chlorotic yellows virus (CCYV) is a plant virus that causes damage to cucurbit crops such as watermelon and cucumber, and is transmitted by an insect vector known as the whitefly. Since CCYV was first detected on cucumber in Chungbuk in 2018, it has been reported in other areas including Gyeongsang in Korea. In 2020, we performed field surveys of yellowing diseases in the greenhouses growing melon and watermelon in Chungbuk (Jincheon and Eumseong). Reverse transcription-polymerase chain reaction analysis of 79 collected samples including melon, watermelon, and weeds resulted in detection of CCYV in 4 samples: Three samples were singly infected with CCYV and one samples was mixed infected with CCYV, Cucurbit aphid borne yellows virus, and Watermelon mosaic virus. The complete genome sequences of the four collected CCYV melon isolates (ES 1-ES 4) were determined and genetically compared with those of previously reported CCYV isolates retrieved from GenBank. Phylogenetic analyses of RNA 1 and 2 sequences revealed that four ES isolates were clustered in one group and closely related to the CCYV isolates from China. The analysis also revealed very low genetic diversity among the CCYV ES isolates. In general, CCYV isolates showed little genetic diversity, regardless of host or geographic origins. CCYV has the potential to pose a serious threat to melon, watermelon, and cucumber production in Korea. Further studies are needed to examine the pathogenicity and transmissibility of CCYV in weeds and other cucurbits including watermelon.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.178-193
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• 2023

The aim of this study was to investigate differences in the achievement standards from the 2015 to the 2022 revised national science curriculum and to present the implications for science teaching under the revised curriculum. Achievement standards relevant to primary science education were therefore extracted from the national curriculum documents; conceptual domains in the two curricula were analyzed for differences; various kinds of centrality were computed; and the Louvain algorithm was used to identify clusters. These methods revealed that, in the revised compared with the preceding curriculum, the total number of nodes and links had increased, while the number of achievement standards had decreased by 10 percent. In the revised curriculum, keywords relevant to procedural skills and behavior received more emphasis and were connected to collaborative learning and digital literacy. Observation, survey, and explanation remained important, but varied in application across the fields of science. Clustering revealed that the number of categories in each field of science remained mostly unchanged in the revised compared with the previous curriculum, but that each category highlighted different skills or behaviors. Based on those findings, some implications for science instruction in the classroom are discussed.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.11-20
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• 2022

The general non-destructive inspection method for anchor bolts in Korea applies visual inspection and hammering inspection, but it is difficult to check corrosion or fatigue cracks of anchor bolts in the part included in the foundation or in the part where the nut and base plate are installed. In reality, objective investigation is difficult because inspection is affected by the surrounding environment and individual differences, so it is necessary to develop non-destructive inspection technology that can quantitatively estimate these defects. Inspection of the anchor bolts of domestic road facilities is carried out by visual inspection, and since the importance of anchor bolts such as bridge bearings and fall prevention facilities is high, the life span of bridges is extended through preventive maintenance by developing non-destructive testing technology along with existing inspection methods. Through the development of this technology, non-destructive testing of anchor bolts is performed and as a technology capable of preemptive/active maintenance of anchor bolts for road facilities, practical use is urgently needed. In this paper, the possibility of detecting defects in anchor bolts such as corrosion and cracks and reliability were experimentally verified by applying the ultrasonic test among non-destructive inspection techniques. When the technology development is completed, it is expected that it will be possible to realize preemptive/active maintenance of anchor bolts by securing source technology for improving inspection reliability.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.43-54
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• 2006

The scope of this paper covers the applications of bender element tests in consolidation, tomography, and liquefaction. Loading and unloading time during consolidation are evaluated based on shear wave velocity. As S-wave velocity is dependent on effective stress, the loading step may be determined. However, cautions are required due to the different mechanism between the settlement and effective stress criteria. The stress history may be evaluated because the S-wave shows the cement controlled regime and stress controlled regimes. A fixed frame complemented with bender elements permits S-wave tomography The tomography system is tested at low confinement within a true triaxial cell. Results show that shear wave velocity tomography permits monitoring changes in the velocity field which is related to the average effective stress. To monitor the liquefaction phenomenon, S-wave trans-illumination is implemented with a high repetition rate to provide detailed information on the evolution of shear stiffness during liquefaction. The evolution of shear wave propagation velocity and attenuation parallel the time-history of excess pore pressure during liquefaction. Applications discussed in this paper show that bender elements can be a very effective tool for the detection of shear waves in the laboratory.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.383-391
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• 2017

In image processing, image segmentation has been studied by various methods in a long time. Image segmentation is the process of partitioning a digital image into multiple objects and face detection is a typical image segmentation field being used in a variety of applications that identifies human faces in digital images. In this paper, we propose a method for extracting the contours of faces included in images. Using the Viola-Jones algorithm, to do this, we detect the approximate locations of faces from images. But, the Viola-Jones algorithm could detected the approximate location of face not the correct position. In order to extract a more accurate face region from image, we use skin color in this paper. In details, face region would be extracted using the analysis of horizontal and vertical histograms on the skin area. Finally, the face contour is extracted using snake algorithm for the extracted face area. In this paperr, a modified snake energy function is proposed for face contour extraction based snake algorithm proposed by Williams et al.[7]

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.931-936
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• 2008

Surveying by using terrestrial LiDAR(Light Detection And Ranging) is more rapid than by using total station which enables tunnel section profile surveying to be done in suitable time and minimize centerline error, occurrence of overcut and undercut. Therefore, utilization of terrestrial LiDAR has increased more and more in section profile survey and measurement field Moreover, studies of terrestrial LiDAR for accurate and efficient utilization is now ongoing vigorously. Average end area formula, which was generally used to calculate overcut and undercut, was compared with existing methods such as total station survey and photogrammetry. However, there are no criteria of spacing distance for calculating overcut and undercut through terrestrial LiDAR surveying which can acquire 3D information of whole tunnel. This research performed reverse engineering to decide optimal spacing distance when surveying tunnel section profile by comparing whole tunnel volume and tunnel volume in difference spacing distance. This result was utilized to produce CAD drawing for the test tunnel site where there is no design drawings. In addition to this, efficiency of LiDAR and accuracy of CAD drawing was compared with targetless total station surveying of tunnel section profile. Finally, error analysis of target coordinate's accuracy and incidence angle was done in order to verify the accuracy of terrestrial LiDAR technology.