• Journal of Korean Society for Geospatial Information Science
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• v.14 no.1 s.35
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• pp.85-91
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• 2006

Recently, slope failures are happen to natural disastrous when they occur in mountainous areas adjoining highways in Korea. The accidents associated with slope failures have increased due to rapid urbanization of mountainous areas. Therefore, Regular maintenance is essential for all slope and needs maintenance of road safety as well as road function. In this study, we take priority of making a database of risk factor of the failure of a slope before assesment and analysis. The purpose of this paper is to recommend a standard of Slope Management Information Sheet(SMIS) like as Hazard Map. The next research, we suggest to pre-estimated model of a road slope using Logistic Regression Model.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.39-49
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• 2022

The purpose of this study was to systematic review about randomized controlled trials the characteristics and effect of non-pharmacological intervention on depressive symptom in elderly with mild cognitive impairment. We searched studies published from January 2011 to July 2021 in 3 databases. A total 1,455 studies were found and included 11 studies in final analysis. Methodological quality was assessment with the Cochrane's RoB(risk of bias) tool. Geriatric Depression Scale(GDS) was the most used as the assessment tool for identifying the depressive symptom. Intervention were yoga, psychosocial intervention, cognitive training, health education, multi-component intervention, game training, aerobic/pulmonary physiotherapy, art therapy, music reminiscence activity, memory specificity training, cognitive stimulation therapy and SWTW(sleep well, think well) program. Among the intervention programs, yoga, multi-component intervention and game training were effective in improving depressive symptom. This study provided a clinical evidence for planning and implementing intervention on depressive symptom in elderly with mild cognitive impairment.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.129-141
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• 2006

The vertical soil pressure developed in the granular layer of asphalt pavement system is influenced by various factors, including the wheel load magnitude, the loading speed, and asphalt pavement temperature. This research observed the distribution of vertical soil pressure in pavement supporting layer by investigating measured data from soil pressure gage in the KHC Test Road. The existing specification of subbase and subgrade compaction was also evaluated with measured vertical pressure. The finite element analysis was conducted to verify the accuracy of results with measured data because it can maximize research capacity without significant field test. The test data was collected from A5, A7, A14, and A15 test sections at August, September, and November 2004 and August 2005. Those test sections and test data were selected because they had best quality. The size of influence area was evaluated and the vertical pressure variation was investigated with respect to load level, load speed, and pavement temperature. The lower speed, higher load level, and higher pavement temperature increased the vertical pressure and reduced the area of influence. The finite element result showed the similar trend of vertical pressure variation in comparison with measured data. The specification of compaction quality for subbase and subgrade is higher than the level of vertical pressure measured with truck load so that it should be lurker investigated.

• Journal of Korean Society of Steel Construction
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• v.24 no.1
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• pp.119-128
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• 2012

In this study, experimental vibration tests are performed on a real full-scale railway steel plate girder bridge, which resides in open-space environments. Using experimental modal analysis techniques, the modal parameters of the railway steel plate girder bridge yielded by the modal testing of the impact hammer are compared and investigated with the natural frequencies and mode shapes obtained by finite element analysis. This work focuses on the application of model updating techniques to measured experimental data and output-only data from an analytical vibration study that takes into account various geometric and material properties of the bridge members. A finite element model of the railway bridge structure is used to verify the modal experimental results. It is subsequently updated using the corresponding modal identification technique. The basic database is provided to evaluate damage, which can be determined based on the changes in the element properties, resulting from the process of updating the finite element model benchmark and experimental data.

• Convergence Security Journal
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• v.20 no.3
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• pp.115-123
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• 2020

Cyber Attack have evolved more and more in recent years. One of the best countermeasure to counter this advanced and sophisticated cyber threat is to predict cyber attacks in advance. It requires a lot of information and effort to predict cyber threats. If we use Open Source Intelligence(OSINT), the core of recent information acquisition, we can predict cyber threats more accurately. In order to predict cyber threats using OSINT, it is necessary to establish a Database(DB) for cyber attacks from OSINT and to select factors that can evaluate cyber threats from the established DB. We are based on previous researches that built a cyber attack DB using data mining and analyzed the importance of core factors among accumulated DG factors by AHP technique. In this research, we present a method for quantifying cyber threats and propose a cyber threats prediction model based on artificial neural networks.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.1
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• pp.8-14
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• 2004

Model-based inversion tools for eddy current signals have been developed by combining neural networks and finite element modeling, for quantitative flaw characterization in steam generator tubes. In the present work, interpretation of experimental eddy current signals was carried out in order to validate the developed inversion tools. A database was constructed using the synthetic flaw signals generated by the finite element model. The hybrid neural networks composed of a PNN classifier and BPNN size estimators were trained using the synthetic signals. Experimental eddy current signals were obtained from axisymmetric artificial flaws. Interpretation of flaw signals was conducted by feeding the experimental signals into the neural networks. The interpretation was excellent, which shows that the developed inversion tools would be applicable to the Interpretation of real eddy current signals.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.2
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• pp.39-59
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• 2007

With the rapid spread of the practice of collecting and treating data by using a data base system, it's increasingly more critical to approach data sets in the same manner as general records in the collection, evaluation, preservation, and utilization process. Despite the importance, however, the interest level in data sets in Korea's records management is very low. In order to suggest basic items to regard data sets as records and manage them systematically, this study examined the descriptive elements of data set records. descriptive elements of data set records were suggested by comparing and analyzing those ones adopted by the agencies that regarded data sets as records and provided the concerned service as well as the descriptive rules of electronic records set by the advanced nations in records management based on the descriptive areas of ISAD(G).

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.261-271
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• 2003

A condition evaluation procedure for the pavement foundations using multi-load level Falling Weight Deflectometer(FWD) deflections is presented in this paper. A dynamic finite element program incorporating a stress-dependent material model, was used to generate the synthetic deflection database. Based on this synthetic database, the relationships between surface deflections and critical responses, such as stresses and strains in base and subgrade layers, have been established. FWD deflection data, Dynamic Cone Penetrometer(UP) data, and repeated load resilient modulus testing results used in developing this procedure were collected from the Long Term Pavement Performance (LTPP) and North Carolina Department of Transportation (NCDOT) database. Research effort focused on investigation of the effect of the FWD load level on the condition evaluation procedures. The results indicate that the proposed procedure can estimate the pavement foundation conditions. It is also found that structurally adjusted Base Damage Index (BDI) and Base Curvature Index (BCI) are good indicators for the prediction of stiffness characteristics of aggregate base and subgrade respectively. A FWD test with a load of 66.7 kN or less does not improve the accuracy of this procedure. Results from the study for the nonlinear behavior of a pavement foundations indicate that the deflection ratio obtained from multi-load level deflections can predict the type and quality of the pavement foundation materials.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.197-206
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• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.569-583
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• 2018

The purpose of this study is to identify the collapse characteristics by analyzing various factors causing collapse based on field survey and existing data on rock slopes occurring in the construction of roads and industrial complexes in Gyeongsangnam - do area. In the case of the slope where the slope has been directly surveyed, the analysis of the collapse characteristics can be used for the prediction and prevention of slope failure through the continuous collection of the slope data, database construction, management and analysis. The evaluation items used in the collapse characteristics of slope were selected among the items that can be regarded as objective evaluation items among the overlapping factors by comparing the evaluation items frequently used for the evaluation of the existing slope stability among various factors. The type of destruction of the rock slope depends on the type of carcass of the bedrock, such as planar fracture, wedge fracture, onho fracture, and conduction fracture, which are different from each other. And the slope stability analysis should be performed accordingly.