• Journal of Urban Science
• /
• v.11 no.2
• /
• pp.19-24
• /
• 2022

Conventional RC beams for crossing small and medium-sized rivers do not have a cross-sectional area, so the floating debris is accumulated and disasters such as damage to bridges occur. To improve this, the PSC method was invented. However, this also had problems such as transverse curvature, increase in dead weight due to cross-sectional shape, and negative moment generated during serialization, so it was necessary to develop a new type of girder. Therefore, it was intended to propose a LIT(Leton Interaction Thrust) girder bridge that is safer and has better performance than the conventional PSC girder with improved section efficiency. Unlike existing girder bridges, the LIT girder has the feature that the change in the strands of the entire girder occurs only in the vertical direction when the first tension is applied because the tendon arrangement is symmetrical by applying the raised portion. In addition, slab continuation generates a secondary moment that is advantageous to the continuous point, effectively controlling the negative moment and preventing the corrosion of the tendon. The dimensions of the cross section were determined, and the arrangement of the strands was designed to conduct structural analysis and detailed analysis. As a result of the structural analysis, the stress of the girder showed results within the allowable compressive stress, and the deflection showed the result within the allowable deflection. showed results. In addition, a detailed analysis was performed to examine the stress distribution around the girder body and the anchorage area and the stress distribution of the embossed portion, and as a result, the stress of the girder body due to the tension force showed a stable level.

• Steel and Composite Structures
• /
• v.21 no.6
• /
• pp.1347-1368
• /
• 2016

In this article, an exact analytical solution for mechanical buckling analysis of symmetrically cross-ply laminated plates including curvature effects is presented. The equilibrium equations are derived according to the refined nth-order shear deformation theory. The present refined nth-order shear deformation theory is based on assumption that the in-plane and transverse displacements consist of bending and shear components, in which the bending components do not contribute toward shear forces and, likewise, the shear components do not contribute toward bending moments The most interesting feature of this theory is that it accounts for a parabolic variation of the transverse shear strains across the thickness and satisfies the zero traction boundary conditions on the top and bottom surfaces of the plate without using shear correction factors. Buckling of orthotropic laminates subjected to biaxial inplane is investigated. Using the Navier solution method, the differential equations have been solved analytically and the critical buckling loads presented in closed-form solutions. The sensitivity of critical buckling loads to the effects of curvature terms and other factors has been examined. The analysis is validated by comparing results with those in the literature.

• Geophysics and Geophysical Exploration
• /
• v.16 no.1
• /
• pp.36-44
• /
• 2013

We conducted the airborne magnetic and radiometric survey for the characterization of the black shale related and pyrometamorphic uranium deposits distributed in Geumsan area. For the successful characterization of the uranium deposits, the general geological and structural geological features were investigated based on the lithological and linear feature analysis to individual magnetic and radiometric data as the first step. Lithological analysis from the magnetic reduction to the pole and downward continuation map revealed that prominent positive anomalies caused by black and dark gray slate member were clearly recognized as magnetic sources. These results indicate that magnetic survey, even though it is not a direct method for the detection of uranium, can be a useful tool in uranium detection. By the linear feature analysis based on 2nd vertical derivative and curvature map, two linearments corresponded the gray hornfels and black slate member were extracted and in succession, the additional uranium potential zone was inferred. Final discrimination whether uranium-rich or not was confirmed by radiometric and uranium anomaly map. From these analysis, we finally concluded that uranium deposit originated by pyrometamorphic process was confined near the intrusive area only. On the contrary, it was found that black shale related uranium deposit is distributed and extended through out the entire survey area with south-west to north-east direction. In addition, from the linear feature analysis based on radiometric total anomaly map, the typical discontinuous characteristics were recognized in areas where uranium-contained linearments cross the faults. From the above discussion, we concluded that airborne magnetic and radiometric survey are complementary to each other. So it is preferable to carry out simultaneously for the efficient data processing and fruitful interpretation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.7
• /
• pp.3093-3115
• /
• 2020

Network anomaly detection system plays an essential role in detecting network anomaly and ensuring network security. Anomaly detection system based machine learning has become an increasingly popular solution. However, due to the unbalance and high-dimension characteristics of network traffic, the existing methods unable to achieve the excellent performance of high accuracy and low false alarm rate. To address this problem, a new network anomaly detection method based on data balancing and recursive feature addition is proposed. Firstly, data balancing algorithm based on improved KNN outlier detection is designed to select part respective data on each category. Combination optimization about parameters of improved KNN outlier detection is implemented by genetic algorithm. Next, recursive feature addition algorithm based on correlation analysis is proposed to select effective features, in which a cross contingency test is utilized to analyze correlation and obtain a features subset with a strong correlation. Then, random forests model is as the classification model to detection anomaly. Finally, the proposed algorithm is evaluated on benchmark datasets KDD Cup 1999 and UNSW_NB15. The result illustrates the proposed strategies enhance accuracy and recall, and decrease the false alarm rate. Compared with other algorithms, this algorithm still achieves significant effects, especially recall in the small category.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.35 no.11
• /
• pp.155-162
• /
• 2019

The construction industry is the highest safety accident causing industry as 28.55% portion of all industries' accidents in Korea. In particular, falling is the highest accidents type composed of 60.16% among the construction field accidents. Therefore, we analyzed the factors of major disaster affecting the fall accident and then derived feature importances by considering various variables. We used data collected from Korea Occupational Safety & Health Agency (KOSHA) for learning and predicting in the proposed model. We have an effort to predict the degree of occupational fall accidents by using the machine learning model, i.e., Adaboost, short for Adaptive Boosting. Adaboost is a machine learning meta-algorithm which can be used in conjunction with many other types of learning algorithms to improve performance. Decision trees were combined with AdaBoost in this model to predict and classify the degree of occupational fall accidents. HyOperpt was also used to optimize hyperparameters and to combine k-fold cross validation by hierarchy. We extracted and analyzed feature importances and affecting fall disaster by permutation technique. In this study, we verified the degree of fall accidents with predictive accuracy. The machine learning model was also confirmed to be applicable to the safety accident analysis in construction site. In the future, if the safety accident data is accumulated automatically in the network system using IoT(Internet of things) technology in real time in the construction site, it will be possible to analyze the factors and types of accidents according to the site conditions from the real time data.

• International journal of advanced smart convergence
• /
• v.2 no.2
• /
• pp.36-39
• /
• 2013

It is becoming more important as the growing of health information and increasing in cancer patients diagnose over the time gradually. Among the various types of cancer, we focuses on breast cancer diagnosis. The accuracy of breast cancer diagnosis is increasing when the diagnosis is based on evidence and statistics. To do this we use the weka data mining tools and analysis algorithms significantly associated with the decision tree uses rules. In addition, the data pre-processing and cross-validation are used to increase the reliability of the results. The number and cause of the disease becomes important to increase evidence-based medical doctors. As the evidence-based medical, the data obtained from patients in the past through the disease by calculating the probability for future patients to diagnose and predict disease and treatment plan. It can be found by improving the survival rate plays an important role.

• Journal of Industrial Convergence
• /
• v.2 no.2
• /
• pp.127-147
• /
• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.

• Proceeding of Spring/Autumn Annual Conference of KHA
• /
• 2006.11a
• /
• pp.139-143
• /
• 2006

The purpose of this study is to analyze the characteristic of living environment on nursing homes and to examine the current status and problems of the nursing homes by looking into the differences in the spatial uniqueness of living environment in relation to the characteristics of the nursing home. This study utilized a mail survey during July 29 - August 31, 2006 that included a structured questionnaire. The questionnaire largely dealt with the general feature of the facility and the elderly who live there, and the spatial feature of the facility. The study limited its survey to those facilities that were registered to the Ministry of Health and Welfare, which opened after 1995 and that had the capacity of more than 30 people. As a result, the questionnaire was sent to the directors of 344 facilities who were in charge of the nursing home operation and planning. 182 facilities returned the questionnaire and the study used'182 questionnaires for data analysis. The study used the SPSS 12 program to draws the frequency, percentage of the answers and utilized the cross-tab, t-test, ANOVA to analyze the differences.

• Journal of Korean Medical classics
• /
• v.33 no.2
• /
• pp.51-59
• /
• 2020

Objectives : We would like to study what is the most appropriate "feature" to effectively perform authorship attribution of the text of Traditional East Asian Medicine Methods : The authorship attribution performance of the Support Vector Machine (SVM) was compared by cross validation, depending on whether the function words or content words, single word or collocations, and IDF weights were applied or not, using 'Variorum of the Nanjing' as an experimental Corpus. Results : When using the combination of 'function words/uni-bigram/TF', the performance was best with accuracy of 0.732, and the combination of 'content words/unigram/TFIDF' showed the lowest accuracy of 0.351. Conclusions : This shows the following facts from the authorship attribution of the text of East Asian traditional medicine. First, function words play an important role in comparison to content words. Second, collocations was relatively important in content words, but single words have more important meanings in function words. Third, unlike general text analysis, IDF weighting resulted in worse performance.

• Journal of Environmental Science International
• /
• v.23 no.4
• /
• pp.543-552
• /
• 2014

Fixed Electromagnetic Wave Surface Velocimetry (Fixed EWSV) has been started to be used to measure flood discharge in the mountain stream, since it has various advantages such that it works well to continuously measure stream discharge even in the night time as well as very strong weather. On the contrary, the Fixed EWSV only measures single point surface velocity, thus it does not consider varying feature of the transverse velocity profile in the given stream cross-section. In addition, a conventional value of 0.85 was generally used as the ratio for converting the measured surface velocity into the depth-averaged velocity. These aspects could bring in error for accurately measuring the stream discharge. The capacity of the EWSV for capturing rapid flow velocity was also not properly validated. This study aims at conducting error analysis of using the EWSV by: 1) measuring transverse velocity at multiple points along the cross-section to assess an error driven by the single point measurement; 2) figuring out ratio between surface velocity and the depth-averaged velocity based on the concurrent ADCP measurements; 3) validating the capacity of the EWSV for capturing rapid flow velocity. As results, the velocity measured near the center by the fixed EWSV overestimated about 15% of the cross-sectional mean velocity. The converting ratio from the surface velocity to the depth-averaged velocity was 0.8 rather than 0.85 of a conventional ratio. Finally, the EWSV revealed unstable velocity output when the flow velocity was higher than 2 m/s.