• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.903-909
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• 2019

Periodontal disease is observed in many adult persons. However we has not clear know the molecular mechanism and how to treat the disease at the molecular levels. Here, we investigated the molecular differences between periodontal disease and normal controls using gene expression data. In particular, we checked whether the periodontal disease and normal tissues would be classified by machine learning algorithms using gene expression data. Moreover, we revealed the differentially expression genes and their function. As a result, we revealed that the periodontal disease and normal control samples were clearly clustered. In addition, by applying several classification algorithms, such as decision trees, random forests, support vector machines, the two samples were classified well with high accuracy, sensitivity and specificity, even though the dataset was imbalanced. Finally, we found that the genes which were related to inflammation and immune response, were usually have distinct patterns between the two classes.

• Convergence Security Journal
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• v.18 no.4
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• pp.45-52
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• 2018

As the era of the 4th Industrial Revolution has progressed and the information and communication technologies have developed dramatically, the cyber threats will gradually become more intelligent and sophisticated. Therefore, in order to take systematic and prompt action in case of an accident while preparing measures against the threat, the role of intelligence agency is important. However, Korea is having difficulty in responding to the threats due to the lack of support for the national cybersecurity bill or the amendment bill of the National Intelligence Service. In this paper, I examine the cybersecurity function of the intelligence agency, the recent debate trends, and implications for the role of intelligence agency in our current situation. And then I intend to suggest some measures such as concentration on information gathering and analysis, enhancement of cyber threat prediction and response capacity, and strengthening of legal basis as a way to establish the role of intelligence agency for reinforcement of cybersecurity performance system.

• Journal of Gastric Cancer
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• v.21 no.2
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• pp.155-168
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• 2021

Purpose: Previous studies have demonstrated the usefulness of the controlling nutritional status (CONUT) score in nutritional assessment and survival prediction of patients with various malignancies. However, its value in advanced gastric cancer (GC) treated with neoadjuvant chemotherapy and curative gastrectomy remains unclear. Materials and Methods: The CONUT score at different time points (pretreatment, preoperative, and postoperative) of 272 patients with advanced GC were retrospectively calculated from August 2004 to October 2015. The χ² test or Mann-Whitney U test was used to estimate the relationships between the CONUT score and clinical characteristics as well as short-term outcomes, while the Cox proportional hazard model was used to estimate long-term outcomes. Survival curves were estimated by using the Kaplan-Meier method and log-rank test. Results: The proportion of moderate or severe malnutrition among all patients was not significantly changed from pretreatment (13.5%) to pre-operation (11.7%) but increased dramatically postoperatively (47.5%). The pretreatment CONUT-high score (≥4) was significantly associated with older age (P=0.010), deeper tumor invasion (P=0.025), and lower pathological complete response rate (CONUT-high vs. CONUT-low: 1.2% vs. 6.6%, P=0.107). Pretreatment CONUT-high score patients had worse progression-free survival (P=0.032) and overall survival (OS) (P=0.026). Adjusted for pathologic node status, the pretreatment CONUT-high score was strongly associated with worse OS in pathologic node-positive patients (P=0.039). Conclusions: The pretreatment CONUT score might be a straightforward index for immune-nutritional status assessment, while being a reliable prognostic indicator in patients with advanced GC receiving neoadjuvant chemotherapy and curative gastrectomy. Moreover, lower pretreatment CONUT scores might indicate better chemotherapy responses.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.241-257
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• 2020

The rapid proliferation of oil/gas drilling and wind turbine installations with jack-up rig-formed structures increases structural safety requirements, due to the greater risks of operational collisions during use of these structures. Therefore, current industrial practices and regulations have tended to increase the required accidental collision design loads (impact energies) for jack-up rigs. However, the existing simplified design approach tends to be limited to the design and prediction of local members due to the difficulty in applying the increased uniform impact energy to a brace member without regard for the member's position. It is therefore necessary to define accidental load estimation in terms of a reasonable collision scenario and its application to the structural response analysis. We found by a collision probabilistic approach that the kinetic energy ranged from a minimum of 9 MJ to a maximum 1049 MJ. Only 6% of these values are less than the 35 MJ recommendation of DNV-GL (2013). This study assumed and applied a representative design load of 196.2 MN for an impact load of 20,000 tons. Based on this design load, the detailed design of a leg structure was numerically verified via an FE analysis comprising three categories: linear analysis, buckling analysis and progressive collapse analysis. Based on the numerical results from this analysis, it was possible to predict the collapse mode and position of each member in relation to the collision load. This study provided a collision strength assessment between attendant vessels and a jack-up rig based on probabilistic collision scenarios and nonlinear structural analysis. The numerical results of this study also afforded reasonable evaluation criteria and specific evaluation procedures.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.189-201
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• 2022

In this study, we propose factor augmentation to improve forecasting power of cryptocurrency return. We consider financial and economic variables as well as psychological aspect for possible factors. To be more specific, financial and economic factors are obtained by applying principal factor analysis. Psychological factor is summarized by news sentiment analysis. We also visualize such factors through impulse response analysis. In the modeling perspective, we consider ARIMAX as the classical model, and random forest and deep learning to accommodate nonlinear features. As a result, we show that factor augmentation reduces prediction error and the GRU performed the best amongst all models considered.

• Geomechanics and Engineering
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• v.28 no.4
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• pp.335-346
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• 2022

Buckling failure is a typical slope instability mode that should be paid more attention to. It is difficult to provide systematic guidance for the monitoring and management of such slopes due to unclear mechanism. Here we examine buckling failure as the potential instability mode for a slope above a railway tunnel in southwest China. A comprehensive model test system was developed that can be used to conduct buckling failure experiments. The displacement, stress, and strain of the slope were monitored to document the evolution of buckling failure during the experiment. Monitoring data reveal the deformation and stress characteristics of the slope with different slipping mass thicknesses and under different top loads. The test results show that the slipping mass is the main subject of the top load and is the key object of monitoring. Displacement and stress precede buckling failure, so maybe useful predictors of impending failure. However, the response of the stress variation is earlier than displacement variation during the failure process. It is also necessary to monitor the bedrock near the slip face because its stress evolution plays an important role in the early prediction of instability. The position near the slope foot is most prone to buckling failure, so it should be closely monitored.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.396-416
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• 2021

Objectives: This study was conducted to analyze the trends of government R&D (R&D) projects related to laboratory safety over the past 20 years. Methods: We collected publications from various databases(DBs) with words such as laboratory(ies), lab(s), researcher(s), laboratory worker(s), safety, environment, hazard(s), risk(s), and so on. Selected publications were analyzed by the research funds and the number of projects according to the investment subject and research characteristics. Results: About 93% of the total R&D budget went to government policy projects, not scientific research. Second, from the perspective of 'safety management activities', most of the research is related to management and inspection at the organizational level. Issues that need to be discussed at the national level like policy governance are not included. Third, focusing on the 'safety management cycle', there were few studies related to 'prediction' or 'post-response'. Fourth, when an analysis framework combining the perspectives of 'safety management activities' and 'safety management cycle' is applied, most of the budget is spent on infrastructure such as digital management systems, whereas basic knowledge for prevention and production of evidence was very few. Conclusions: In order to prevent policy planning without policy evaluation, implementation without strategy, and evaluation without evidence, it is necessary to expand investment in empirical research on risks, research on the effectiveness of current application methods, and research on theory development. The government budget for laboratory safety-related projects should be managed separately from the R&D budget for scientific research. Although less than 5% of the budget allocated to scientific research is the total budget, an optical illusion occurs because both the project budget and the scientific research budget are counted as R&D budgets.

• Steel and Composite Structures
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• v.44 no.2
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• pp.155-169
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• 2022

In the present paper an analytical model was developed to study the non-linear vibrations of Functionally Graded Carbon Nanotube (FG-CNT) reinforced doubly-curved shallow shells using the Multiple Scales Method (MSM). The nonlinear partial differential equations of motion are based on the FGM shallow shell hypothesis, the non-linear geometric Von-Karman relationships, and the Galerkin method to reduce the partial differential equations associated with simply supported boundary conditions. The novelty of the present model is the simultaneous prediction of the natural frequencies and their mode shapes versus different curvatures (cylindrical, spherical, conical, and plate) and the different types of FG-CNTs. In addition to combining the vibration analysis with optimization algorithms based on the genetic algorithm, a design optimization methode was developed to maximize the natural frequencies. By considering the expression of the non-dimensional frequency as an objective optimization function, a genetic algorithm program was developed by valuing the mechanical properties, the geometric properties and the FG-CNT configuration of shallow double curvature shells. The results obtained show that the curvature, the volume fraction and the types of NTC distribution have considerable effects on the variation of the Dimensionless Fundamental Linear Frequency (DFLF). The frequency response of the shallow shells of the FG-CNTRC showed two types of nonlinear hardening and softening which are strongly influenced by the change in the fundamental vibration mode. In GA optimization, the mechanical properties and geometric properties in the transverse direction, the volume fraction, and types of distribution of CNTs have a considerable effect on the fundamental frequencies of shallow double-curvature shells. Where the difference between optimized and not optimized DFLF can reach 13.26%.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.617-631
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• 2022

In this paper the viscoelastic responses of four experimental steel-concrete composite beams subjected to highly variable environmental conditions are investigated by means of a finite element (FE) model. Concrete specimens submitted to stepped stress changes are also evaluated to validate the current formulations. Here, two well-known approaches commonly used to solve the viscoelastic constitutive relationship for concrete are employed. The first approach directly solves the integral-type form of the constitutive equation at the macroscopic level, in which aging is included by updating material properties. The second approach is postulated from a rate-type law based on an age-independent Generalized Kelvin rheological model together with Solidification Theory, using a micromechanical based approach. Thus, conceptually both approaches include concrete hardening in two different manners. The aim of this work is to compare and analyze the numerical prediction in terms of long-term deflections of the studied specimens according to both approaches. To accomplish this goal, the performance of several well-known model codes for concrete creep and shrinkage such as ACI 209, CEB-MC90, CEB-MC99, B3, GL 2000 and FIB-2010 are evaluated by means of statistical bias indicators. It is shown that both approaches with minor differences acceptably match the long-term experimental deflection and are able to capture complex oscillatory responses due to variable temperature and relative humidity. Nevertheless, the use of an age-independent scheme as proposed by Solidification Theory may be computationally more advantageous.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.515-535
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• 2022

The strength models for fiber-reinforced polymer (FRP)-confined normal strength concrete (NC) cylinders available in the literature have been suggested based on small databases using limited variables of such structural members portraying less accuracy. The artificial neural network (ANN) is an advanced technique for precisely predicting the response of composite structures by considering a large number of parameters. The main objective of the present investigation is to develop an ANN model for the axial strength of FRP-confined NC cylinders using various parameters to give the highest accuracy of the predictions. To secure this aim, a large experimental database of 313 FRP-confined NC cylinders has been constructed from previous research investigations. An evaluation of 33 different empirical strength models has been performed using various statistical parameters (root mean squared error RMSE, mean absolute error MAE, and coefficient of determination R²) over the developed database. Then, a new ANN model using the Group Method of Data Handling (GMDH) has been proposed based on the experimental database that portrayed the highest performance as compared with the previous models with R²=0.92, RMSE=0.27, and MAE=0.33. Therefore, the suggested ANN model can accurately capture the axial strength of FRP-confined NC cylinders that can be used for the further analysis and design of such members in the construction industry.