• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.100-106
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• 2022

The relationships between river length and weir density versus fish species observed were analyzed for 210 local rivers in the Seomjin River system (SJR). A nonlinear exponential relationship between river length and number of fish species were observed. Model coefficient was 0.03 and coefficient of determinant (R²) was 0.59, meaning that about 59.0% of total variance was explained by river length variable. Predicted value by model and observed number of species showed a difference. About 110 local rivers (about 52.4%) showed lower value than predictive value. The average index of weir's density (IWD) in the SJR was about 2.7/km, which was significantly higher than that of other river basins. As a result of nonparametric 2-Kimensional Kolmogorov-Smirnov (2-DKS) analysis based on the IWD, the threshold value affecting fish diversity was about 2.5/km (D_max=0.048, p<0.05). Above the threshold value, it means that the number of fish species would be decreased. In fact, the ratio of the expected species to the observed species was lowered to less than 70%, when the IWD is higher than the threshold value. To maintain aquatic ecological connectivity in future, it is necessary to manage IWD below the threshold value.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.426-434
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• 2022

Bubbles generated by various causes in the ocean are known to persist for long periods of time. Although the volume occupied by bubbles in the ocean is small, the presence of bubbles in ocean due to resonance and attenuation greatly affects the acoustic properties. Accordingly, bistatic reverberation experiment was performed in the ocean where artificial bubbles exist. A number of transducers and receivers were installed on 6 buoys arranged in a hexagonal shape, and blowing agents were dropped in the center of the buoy to generate bubbles. For reverberation modeling that reflects acoustic characteristics changed by bubbles, the spatial distribution of bubbles was estimated using video data and received signals. A measurement-based bubble spectral shape was used, and it was assumed that the bubble density within the spatial distribution of the estimated bubble was the same. As a result, it was confirmed that the bubble reverberation was simulated in a time similar to the measured data regardless of the bubble density, and the bubble reverberation level similar to the measured data was simulated at a void fraction of about 10^-7 ~ 10^-6.8.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.446-460
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• 2022

In this paper, we propose an algorithm to improve target detection rate degradation due to direct blast in a bi-static sonar systems with high duty cycle using an adaptive filters. It is very important to suppress the direct blast in the aforementioned sonar systems because it has a fatal effect on the actual system operation. In this paper, the performance was evaluated by applying the Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms to the simulation and sea experimental data. The beam signals of the target and direct blast bearings were used as the input and desired signals, respectively. By optimizing the difference between the two signals, the direct blast is removed and only the target signal is remained. As a result of evaluating the results of the matched filter in the simulation, it was confirmed that the direct blast was removed to the noise level in both Linear Frequency Modultated (LFM) and Generalized Sinusoidal Frequency Modulated (GSFM), and in the case of GSFM, the target sidelobe decreased by more than 20 dB, thereby improving performance. In the sea experiment, it was confirmed that the LFM reduced the level of the transmitted direct wave by 10 dB, the GSFM reduced the level of the transmitted direct wave by about 4 dB, and the side lobe of the target decreased by about 4 dB, thereby improving the performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.107-112
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• 2022

This study was conducted to investigate the effects of mulching materials in extensive green roof system by comparing and analyzing the soil moisture content and growth response of Lychnis cognata according to the types of organic mulching materials. The experimental group consisted of a control group that did not use mulching material (Cont.) and a total of five treatment groups, including cocochip (C.O), woodchip (W.O), straw (S.T), and sawdust (S.A), depending on the mulching material. The soil moisture content according to the type of organic mulching material was high in the order of W.O > S.T > Cont. > C.O > S.A, and there was a significant difference especially in S.A. The plant height showed good growth in the order of S.T > Cont. > C.O > W.O > S.A, and there was no significant difference by mulching materials in other growth items except for plant height. Both the chlorophyll and plant water contents were superior to those of untreated group, so the treatment of organic mulching materials is considered to be effective in maintaining the chlorophyll and plant water contents of Lychnis cognata. In particular, the soil moisture content was affected by the characteristics of the mulching material itself. Based on these results, it is required to use a mulching material suitable for the characteristics of each plant in extensive green roof system and it is considered that this can be overcome through organic mulching when selecting a plant species that is weak to water stress.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.227-237
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• 2022

The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.374-385
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• 2022

Purpose: Even if a damage is applied to the dust of the construction site containing the first-class carcinogen, it is dismissed or 5~30% of the amount of noise damage compensation is paid., Because of such loopholes, some construction companies are neglecting the dust management of the construction site, and the damage of the workers and the residents in the construction site continues. Method: The purpose of this study is to examine the problems of the calculation criteria of damage compensation amount of construction site dust, the measurement of dust concentration, the analysis of measurement data (the data of electric signboard measuring device by the mining scattering method), the prediction and evaluation methods such as modeling, and to suggest improvement measures. Result: It is found that it is impossible to calculate the amount of damages from dust damage in the construction site by calculating the current dust damage compensation amount and dust concentration modeling and measurement. Conclusion: It will receive an application for compensation for damage within the site where damage is expected (about 100m in the straight line and the boundary line of the site), and present a method of calculating the amount of compensation that differentially evaluates dust damage to the degree of dust management and compliance with dust-related legal standards.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.169-175
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• 2022

Korea's construction industry has a shortage and aging of construction manpower, low productivity compared to other industries, and a high rate of industrial accidents. The Ministry of Land, Infrastructure and Transport is preparing for the 4th industrial revolution and is expanding investment in construction automation and innovative growth engines to improve productivity in the construction industry. In order for new technologies to be utilized in the road construction field, the accuracy of the technologies and the applicability of each type of work must be evaluated. In this study, the accuracy of the mobile mapping system was tried to verify based on the relevant work regulations, and to suggest the applicability of the mobile mapping system to high-speed driving tracks through data acquisition and analysis on road construction sites. The accuracy of the equipment used in the study was verified in accordance with the relevant work regulations, and the possibility of applying the mobile mapping system used for the study to road construction surveying was presented with a maximum error of less than 10cm in the horizontal and vertical directions. In addition, the possibility of utilizing the road construction survey using the mobile mapping system was presented through comparison with the existing method for data acquisition time for construction surveying, production of construction status survey results, and calculation of heatmap and earthworks. In the future, the use of construction status surveying of the mobile mapping system will greatly improve the efficiency of construction work.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.281-288
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• 2022

In this study, four algorithms (Soft, Standard, Detail, Bone) were used for general CT scan (Before MAR) images and MAR (After MAR) images for patients with metal implants inserted into the hip joint. was applied to compare and analyze Noise, SNR, and CNR to find out the optimal algorithm for quantitative evaluation. As the analysis method, Image J program, which can calculate image analysis and area and pixel values on the image reconstructed with four algorithms, was used. In order to obtain Noise, SNR, and CNR, the HU mean value and HU SD value were obtained by designating the bone (ischium) closest to the metal implant in the image for the measurement site, and the background noise was the surrounding muscle. The region of interest (ROI) was equally designated as 15 × 15 mm in consideration of the size of the bone, and the values of SNR and CNR were calculated according to the given equation. As a result, for noise, After MAR and Soft algorithms showed the lowest noise, and SNR and CNR showed the highest for Before MAR and Soft algorithms. Therefore, the soft algorithm is judged to be the most appropriate algorithm for metal implant hip joint CT.