• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• The Korean Journal of Nuclear Medicine
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• v.24 no.2
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• pp.244-253
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• 1990

Sixty-four patients with paradoxical ventricular wall motion noticed both in angiocardiography or 2-dimensional echocardiography were assessed by ECG gated blood pool scan (GBPS). Endless cine loop image, phase and amplitude images and paradox image obtained by visual inspection of each cardiac beat or Fourier transformation of acquired raw data were investigated to determine the incremental value of GBPS with these processing methods for identification of paradoxical ventricular wall motion. The results were as follows: 1) Paradoxical wall motions were observed on interventricular septum in 34 cases, left ventricular free wall in 26 and right ventricular wall in 24. Underlying heart diseases were ischemic (23 cases) valvular(9), congenital heart disease (12), cardiomyopathy (5). pericardial effusion(5), post cardiac surgery(3), col pulmonale (2), endocarditis(1) and right ventricular tumor(1). 2) Left ventricular ejection fractions of patients with paradoxical left ventricular wall motion were significantly lower than those with paradoxical septal motion(p<0.005). 3) The sensitivity of each processing methods for detecting paradoxical wall motion was 76.9% by phase analysis, 74.6% by endless cine loop mapping and 68.4% by paradox image manipultion respectively. Paradoxial motions visualized only in phase, paradox or both images were appeared as hypokinesia or akinesia in cine loop image. 4) All events could be identified by at least one of above three processing methods, however only 34 cases (48.4%) showed the paradoxical molies in all of the three images. By these findings, we concluded that simultaneous inspection of all above three processing methods-endless cine loop, phase analysis and paradox image-is necessary for accurate identification and assessment of paradoxical ventricular wall motion when performing GBPS.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• Journal of Ocean Engineering and Technology
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• v.31 no.1
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• pp.69-79
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• 2017

This paper presents the operations of a multi-beam echo sounder (MBES) installed on the deep-sea remotely operated vehicle (ROV) Hemire. Hemire explored hydrothermal vents in the Forecast volcano located near the Mariana Trench in March of in 2006. During these explorations, we acquired profiling points on the routes of the vehicle using the MBES. Information on the position, depth, and attitude of the ROV are essential to obtain higher accuracy for the profiling quality. However, the MBES installed on Hemire does not have its own position and depth sensors. Although it has attitude sensors for roll, pitch, and heading, the specifications of these sensors were not clear. Therefore, we had to merge the high-performance sensor data for the motion and position obtained from Hemire into the profiling data of the MBES. Then, we could properly convert the profiling points with respect to the Earth-fixed coordinates. This paper describes the integration of the MBES with Hemire, as well as the coordinate conversion between them. Bathymetric maps near the summit of the Forecast volcano were successfully collected through these processes. A comparison between the bathymetric maps from the MBES and those from the Onnuri Research Vessel, the mother ship of the ROV Hemire for these explorations, is also presented.

• Journal of the Korea Convergence Society
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• v.7 no.3
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• pp.159-165
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• 2016

The purpose of this study is to investigate the change in the positive psychology movement of capital represented by the performance of physical disabilities to participate in swimming classes for 10 weeks. The study was conducted with 30 to 40-men group participation handicapped total of 21 patients (10 patients) and non-participation group (11 patients), the duration of the experiment was performed three times a week for 10 weeks, 50 minutes. Data processing is a dictionary, post-test data was calculated the mean and standard deviation, experimental design group two won repeated measures analysis of variance for (swimming participating groups, miserable Lady) and time (before and after) using the SPSS 21.0 statistical program It was performed (2-way [2] RM ANOVA), all the statistical significance level was set at .05. Study, classroom participation of the handicapped swimmer can see that has had a positive effect positive psychological capital.

• Journal of the Korean Geographical Society
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• v.38 no.5
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• pp.667-685
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• 2003

To address the requirements of gap analysis for species protection, as well as the needs of state and federal agencies for detailed digital land cover, a 43-class map at the vegetation alliance level was created for the state of Kansas using multi-temporal Thematic Mapper imagery. The mapping approach included the use of three-date multi-seasonal imagery, a two-stage classification approach that first masked out cropland areas using unsupervised classification and then mapped natural vegetation with supervised classification, visualization techniques utilizing a map of small multiples and field experts, and extensive use of ancillary data in post-hoc processing. Accuracy assessment was conducted at three levels of generalization (Anderson Level I, vegetation formation, and vegetation alliance) and three cross-tabulation approaches. Overall accuracy ranged from 51.7% to 89.4%, depending on level of generalization, while accuracy figures for individual alliance classes varied by area covered and level of sampling.

• Journal of Biosystems Engineering
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• v.35 no.3
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• pp.182-188
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• 2010

Post-Harvest processing engineering is a field that studies prevention of the quality change of agricultural products during sorting, packaging, storage, and distribution after harvested. In distribution steps, agricultural products could be damaged by physical force, it is the main reason of low quality and they lost value of commodities. This study was performed to find the vibration characteristics of the peach, and to find the extent of the damage on the peach by fatigue stress. The vibration data was obtained on expressway and the vibration characteristics of peach was used to find the damage on the peach. To analyze the vibration characteristics of peach, the resonance frequency and vibration transmissibility were measured. The resonance frequency of the peach was 167.98 Hz and the transmissibility was 4.06 at resonance point. It was 150 ~ 250 Hz that the transmissibility was more than 1. And the transmissibility in simulated test was measured. When the trasmissibility was more than 1, the range was 15 ~ 65 Hz, and when it was less than 1, the range was 65 ~ 175 Hz. When the transmissibility was about 1, the range was 5 ~ 15 Hz. The damage and the vibration cycle numbers of peaches were compared with input frequency and acceleration. More damage and less cycle number happened in 30 Hz than in 62.5 Hz. The reason was that the transmissibility of 30 Hz was higher and the vibration displacement in lower frequency was more. The more acceleration and cycle number increased, the more the bruising volume of peaches increased. The bruising volume ratio for vibration fatigue was measured according to input acceleration and cycle number. Using measured data, regression models for bruising volume ratio(BVR) was developed as a function of the acceleration(A) and cycle number(CN) as follows. BVR = a * $A^b*$ $(CN)^c$

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.1-9
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• 2020

As the aging problem of the regional industry ecosystem has gradually become serious, research to measure and regenerate the regional industry ecosystem decline has been actively conducted. However, little research has been done on regional industry ecosystem crises. Crisis emerges radically over a short period of time, and it is often impossible to respond by post-response, so you must respond before the crisis occurs. In other words, it is more necessary and required when looking at the crisis early and taking a proactive response from a long-term perspective. Therefore, it is necessary to develop a predictive model that can proactively recognize and respond to the crisis in the regional industry ecosystem. Therefore, this study checked the possibility of predicting the risk of regional industry and market according to the emotional score of the news by using large-scale news data. News sentiment analysis was performed using the Google sentiment analysis API, and this was organized by month to check the correlation between actual events.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.73-79
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• 2019

Research is underway on services and systems that provide real-time alerts for suffocating gases and potentially explosive materials, but currently smart bend type services are lacking. This study supports real-time identification of explosion hazards due to static electricity in the workplace and immediate elimination of accident occurrence factors, real-time monitoring of worker status and workplace hazards (oxygen, hazardous chemical concentration), and immediate warning and data in case of danger. We propose a method of establishing an accident prevention system through analysis. In this way, various accidents that may occur in industrial sites are monitored using IoT-based intelligent sensor nodes, wireless network technology, data processing middleware, and integrated control system, and real-time risk information at the industrial sites is prevented and accidents are prevented. By supporting a safe working environment, the company can significantly reduce costs compared to post-procurement costs.

• Journal of Astronomy and Space Sciences
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• v.32 no.3
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• pp.209-219
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• 2015

The Accurate Ranging System for Geodetic Observation - Mobile (ARGO-M) was successfully developed as the first Korean mobile Satellite Laser Ranging (SLR) system in 2012, and has joined in the International Laser Ranging Service (ILRS) tracking network, DAEdeoK (DAEK) station. The DAEK SLR station was approved as a validated station in April 2014, through the ILRS station "data validation" process. The ARGO-M system is designed to enable 2 kHz laser ranging with millimeter-level precision for geodetic, remote sensing, navigation, and experimental satellites equipped with Laser Retro-reflector Arrays (LRAs). In this paper, we present the design and development of a next generation high-repetition-rate SLR system for ARGO-M. The laser ranging rate up to 10 kHz is becoming an important issue in the SLR community to improve ranging precision. To implement high-repetition-rate SLR system, the High-repetition-rate SLR operation system (HSLR-10) was designed and developed using ARGO-M Range Gate Generator (A-RGG), so as to enable laser ranging from 50 Hz to 10 kHz. HSLR-10 includes both hardware controlling software and data post-processing software. This paper shows the design and development of key technologies of high-repetition-rate SLR system. The developed system was tested successfully at DAEK station and then moved to Sejong station, a new Korean SLR station, on July 1, 2015. HSLR-10 will begin normal operations at Sejong station in the near future.