• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.5
• /
• pp.741-749
• /
• 2018

The purpose of this study is to propose a rational and scientific damage calculation model in relation to damages caused by bid rigging in construction projects. Previous studies and precedents in relation to calculating damages from bid rigging suggest that the main issue was the lack of consideration in standards for deciding successful bids, selection of inadequate standard comparative markets, insufficiency in analyzing the appropriateness of competitive bid price influence factors, and absence of calculation model verification. In order to improve on these issues, a damage calculation method on alternative tenders for construction projects was proposed. For this calculation model, first, a standard market adequate to the successful bid selection standards was determined, second, an appropriate factor was selected by analyzing the correlation between competitive bid price influence factors, and third, a regression analysis was conducted on the selected factor. Lastly, this was demonstrated through verification of appropriateness, significance & normality of the proposed model and application of actual bid rigging cases. Through the proposed calculation model, this study seeks to serve as a base to prevent opportunity damages for parties involved in related court cases by early resolution of disputes and relief from issues of unfair damage burdens on a particular party.

• The KIPS Transactions:PartB
• /
• v.13B no.7 s.110
• /
• pp.679-688
• /
• 2006

Protein-protein interaction data obtained from high-throughput experiments includes high false positives. In this paper, we introduce a new protein-protein interaction reliability verification system. The proposed system integrates various biological features related with protein-protein interactions, and then selects the most relevant and informative features among them using a feature selection method. To assess the reliability of each protein-protein interaction data, the system construct a classifier that can distinguish true interacting protein pairs from noisy protein-protein interaction data based on the selected biological evidences using a classification technique. Since the performance of feature selection methods and classification techniques depends heavily upon characteristics of data, we performed rigorous comparative analysis of various feature selection methods and classification techniques to obtain optimal performance of our system. Experimental results show that the combination of feature selection method and classification algorithms provide very powerful tools in distinguishing true interacting protein pairs from noisy protein-protein interaction dataset. Also, we investigated the effects on performances of feature selection methods and classification techniques in the proposed protein interaction verification system.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.24 no.1
• /
• pp.15-19
• /
• 2020

Purpose Generative Adversarial Network(GAN) is one of deep learning technologies. This is a way to create a real fake image after learning the real image. In this study, after acquiring artificial intelligence images through GAN, We were compared and evaluated with real scan time images. We want to see if these technologies are potentially useful. Materials and Methods 30 patients who underwent ¹⁸F-FDG Brain PET/CT scanning at Severance Hospital, were acquired in 15-minute List mode and reconstructed into 1,2,3,4,5 and 15minute images, respectively. 25 out of 30 patients were used as learning images for learning of GAN and 5 patients used as verification images for confirming the learning model. The program was implemented using the Python and Tensorflow frameworks. After learning using the Pix2Pix model of GAN technology, this learning model generated artificial intelligence images. The artificial intelligence image generated in this way were evaluated as Mean Square Error(MSE), Peak Signal to Noise Ratio(PSNR), and Structural Similarity Index(SSIM) with real scan time image. Results The trained model was evaluated with the verification image. As a result, The 15-minute image created by the 5-minute image rather than 1-minute after the start of the scan showed a smaller MSE, and the PSNR and SSIM increased. Conclusion Through this study, it was confirmed that AI imaging technology is applicable. In the future, if these artificial intelligence imaging technologies are applied to nuclear medicine imaging, it will be possible to acquire images even with a short scan time, which can be expected to reduce artifacts caused by patient movement and increase the efficiency of the scanning room.

• Journal of the Korean GEO-environmental Society
• /
• v.12 no.7
• /
• pp.5-12
• /
• 2011

When choosing the support pattern of tunnel, the characteristics of rock are identified from the result of the surface geologic survey, boring, and geophysical prospecting and laboratory test. And a rock mass rating is classified and excavation method and standard support pattern are designed considering rock classification, domestic and international construction practices, numerical analysis. According to the revised design standard for tunnel, it was recommended to classify the rock mass rating for the design of tunnel into a rating based on RMR. If necessary, it proposed a flexible standard allowed applying more atomized the rock mass rating and Q-System. Also, the resonable verification of the support pattern must be accompanied because the factors affecting the structure and behavior of ground during the construction of tunnel are the main factors of uncertainty factors such as the nature of ground, ground water and the characteristics of structural materials. These days, such verification method is getting more specialized and diversified. In this study, the empirical method, numerical analysis and comparative analysis of in situ measurements were used to prove the reasonableness in the support pattern by RMR and Q-value on the Imha Dam emergency spillway.

• Journal of the Korean Society of Radiology
• /
• v.16 no.5
• /
• pp.595-602
• /
• 2022

This study tried to suggest the most efficient learning rate for accurate and efficient automatic diagnosis of medical images for chest X-ray pneumonia images using deep learning. After setting the learning rates to 0.1, 0.01, 0.001, and 0.0001 in the Inception V3 deep learning model, respectively, deep learning modeling was performed three times. And the average accuracy and loss function value of verification modeling, and the metric of test modeling were set as performance evaluation indicators, and the performance was compared and evaluated with the average value of three times of the results obtained as a result of performing deep learning modeling. As a result of performance evaluation for deep learning verification modeling performance evaluation and test modeling metric, modeling with a learning rate of 0.001 showed the highest accuracy and excellent performance. For this reason, in this paper, it is recommended to apply a learning rate of 0.001 when classifying the presence or absence of pneumonia on chest X-ray images using a deep learning model. In addition, it was judged that when deep learning modeling through the application of the learning rate presented in this paper could play an auxiliary role in the classification of the presence or absence of pneumonia on chest X-ray images. In the future, if the study of classification for diagnosis and classification of pneumonia using deep learning continues, the contents of this thesis research can be used as basic data, and furthermore, it is expected that it will be helpful in selecting an efficient learning rate in classifying medical images using artificial intelligence.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.34 no.1
• /
• pp.63-66
• /
• 2008

Sunscreen is usually used by people when they are at the beach or outdoor swimming pools. Since the existing methods of and standards for measuring the effects of blocking ultra violet rays do not employ water resistance test methods, the establishment of a water resistance SPF test method is required. In this study, to standardize the SPF evaluation methods for a water resistant sunscreen, proposed measurement methods in this study were compared with those of foreign countries. Selected water resistance SPF experiments confirmed the product's suitability and a verification test was then conducted by establishing the variables of water resistance SPF measurement methods. In the comparative experiment on water resistance SPF given a water temperature of $23{\sim}32$ degrees centigrade showed that temperature did not have any statistically significant effect on water resistance SPF. The changing water flow also did not have any statistically significant effect on the water resistance SPF. Therefore, continuous 20 min water circulation is deemed appropriate as an alternative to the subject's usual activity.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.4
• /
• pp.136-150
• /
• 2022

In this study, a comparative review was conducted on how to use RGB images to obtain river topographic information, which is one of the most essential data for eco-friendly river management and flood level analysis. In terms of the topographic information of river zone, to obtain the topographic information of flow section is one of the difficult topic, therefore, this study focused on estimating the river topographic information of flow section through RGB images. For this study, the river topography surveying was directly conducted using ADCP and RTK-GPS, and at the same time, and orthomosiac image were created using high-resolution images obtained by drone photography. And then, the existing developed regression equations were applied to the result of channel topography surveying by ADCP and the band values of the RGB images, and the channel bathymetry in the study area was estimated using the regression equation that showed the best predictability. In addition, CCHE2D flow modeling was simulated to perform comparative verification of the topographical informations. The modeling result with the image-based topographical information provided better water depth and current velocity simulation results, when it compared to the directly measured topographical information for which measurement of the sub-section was not performed. It is concluded that river topographic information could be obtained from RGB images, and if additional research was conducted, it could be used as a method of obtaining efficient river topographic information for river management.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.4
• /
• pp.33-46
• /
• 2007

HWAW (Harmonic Wavelet Analysis of Wave) method, which is non-destructive method using body and surface waves, has the advantages of obtaining 2D subsurface imaging because it uses a short receiver spacing to obtain the $V_s$ profile of whole depth. Even though the reliability of HWAW method has already been verified by using the numerical simulation in the various layered models, it is very difficult to evaluate the reliability of HWAW in the field because the exact $V_s$ values of the experimental site are unknown. In this study, a model testing site where the material properties and layer information could be controlled was constructed to verify the reliability of HWAW method. The detailed geometry of the testing site was strictly measured by surveying, and 140 vertical and horizontal geophones were established at the boundary of each layer to evaluate the dynamic material properties. Using the interval travel times between the upper and lower geophones, the body wave velocities of each layer were 2 dimensionally obtained as reference data, and comparative study using HWAW method was performed. By comparing 2D Vs profile obtained by HWAW method to the reference data, the reliability of HWAW method was verified.

• Korean Journal of Comparative Education
• /
• v.26 no.3
• /
• pp.103-132
• /
• 2016

This study aims to suggest ways of improving the quality of confirmation hearings for the Secretary of Education in South Korea by: 1) comparing the confirmation process by the presidents in South Korea and the United States; and 2) contrasting procedures and contents of hearings for Education Secretary nominee in South Korea and the United States. As the process of selecting a nominee to be the Secretary of Education started, the Blue House Office of Secretary conducted an investigation on the nominee's personal details, family matters, and etc within a week. The investigation, with very limited time frame, led the selection process to be a mere verification on the nominee's morality. On the other hand, the White House Office of Presidential Personnel carried out a thorough investigation on the nominee collectively with the White House Council, Federal Bureau of Investigation (FBI), and Internal Revenue Service, taking from two to three months. In terms of contents of the hearings, the members of the ruling party mainly asked the nominee for clarification, and his ideas on certain policies, whereas the opposition party focused mostly on verifying his morality. In addition, the committee members led the hearing whilst strongly expressing their own political ideologies. However, in the case of the hearings in the United States, the committee members did not ask any questions to verify the nominee's morality but questions that could help them to get an understanding of the nominee's experience, professionalism, and perspective on nation- wide issues regarding education and federal education policy. As for the procedural characteristics of South Korean hearings, the Committee on Education conducted the hearing with a week of advanced preparation. However, submission of required reports by the nominee, performing confirmation hearings, and reports on the hearing were not mandatory in order to appoint the nominee as the Secretary of Education. On the contrary, in the United States, the members of the Committee on Health, Education, Labor, and Pension spent about a month preparing for the confirmation hearing. For the nominee to be appointed, submission of reports and the committee's approval on the President's nomination were required. Based on the results, this research suggests that it is important to develop a policy that can strengthen the substantiality of the nomination process, to establish a professional agency for personnel investigation, to make a mandatory submission of personal reports before hearings, to extend the time frame for hearing preparation, to secure enough time slot for nominees to respond, and to increase the member's autonomy.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.3
• /
• pp.1-10
• /
• 2005

The purpose of this paper is to conduct an experimental measurement and analysis of cities' morphology. Fractal theory that is an effective tool for evaluating self-similarity and complexity of objects was applied. For the comparative analysis of fractailities and computational verification, two totally different cities in Japan were selected. They are Kitakyushu City, which is a big and fully developed city, and Jinguu Machi of which almost all the area is covered with agricultural land use. After converting vector data to raster data within GIS, fractal dimensions of two cases in Kitakyushu City and one case in Jinguu Machi were calculated. The calculation showed that two parts of Kitakyushu City were already fractal. Jinguu Machi, however, was difficult to find fractality. As a conclusion, fractal was proved to be an useful tool to estimate the shape of cities reflecting their internal spatial structure, that is self-similarity and complexity.