• The Journal of Engineering Geology
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• v.32 no.1
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• pp.27-40
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• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.177-185
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• 2008

Accurate monitoring of snow cover is a key component for studying climate and global as well as for daily weather forecasting and snowmelt runoff modelling. The few observed data related to snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) were built for 7 major watersheds in South Korea. The decrease pattern of SCA for time (day) was expressed as exponentially decay function, and the determination coefficient was ranged from 0.46 to 0.88. The SCA decreased 70% to 100% from the maximum SCA when 10 days passed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.423-429
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• 2008

The object of the present study is to estimate the potential effects of climate change and land use on soil erosion in the mid-east Korea. Simulated precipitation by CCCma climate model during 2030-2050 is used to model predicted soil erosion, and results are compared to observation. Simulation results allow relative comparison of the impact of climate change on soil erosion between current and predicted future condition. Expected land use changes driven by socio-economic change and plant growth driven by the increase of temperature and are taken into accounts in a comprehensive way. Mean precipitation increases by 17.7% (24.5%) for A2 (B2) during 2030-2050 compared to the observation period (1966-1998). In general predicted soil erosion for the B2 scenario is larger than that for the A2 scenario. Predicted soil erosion increases by 48%~90% under climate change except the scenario 1 and 2. Predicted soil erosion under the influence of temperature-induced fast plant growth, higher evapotranspiration rate, and fertilization effect (scenario 5 and 6) is approximately 25% less than that in the scenario 3 and 4. On the basis of the results it is said that precipitation and the corresponding soil erosion is likely to increase in the future and care needs to be taken in the study area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.665-673
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• 2008

This study is to assess the future potential climate and land use change impact on streamflow and stream water quality of the study watershed using the established model parameters (I). The CCCma (Canadian Centre for Climate Modelling and Analysis) CGCM2 (Canadian Global Coupled Model) based on IPCC SRES (Special Report Emission Scenarios) A2 and B2 scenarios were adopted for future climate condition, and the data were downscaled by Stochastic Spatio-Temporal Random Cascade Model technique. The future land use condition was predicted by using modified CA-Markov (Cellular Automata-Markov chain) technique with the past time series of Landsat satellite images. The model was applied for the future extreme precipitation cases of around 2030, 2060 and 2090. The predicted results showed that the runoff ratio increased 8% based on the 2005 precipitation (1160.1 mm) and runoff ratio (65%). Accordingly the Sediment, T-N and T-P also increased 120%, 16% and 10% respectively for the case of 50% precipitation increase. This research has the meaning in providing the methodological procedures for the evaluation of future potential climate and land use changes on watershed hydrology and stream water quality. This model result are expected to plan in advance for healthy and sustainable watershed management and countermeasures of climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6A
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• pp.543-560
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• 2010

Safety-related concrete structures in a nuclear power plant must be protected against the impact of flying objects, referred to in the profession as missiles. In practice, the structural verification is usually carried out by means of empirical formulas, which relate the velocity of the impinging missile to the wall thickness needed to prevent scabbing or perforation. The purpose of this study is to reevaluate the predictability of the local effect prediction formulas for the penetration and scabbing depths and perforation thickness. Therefore, available formulas for predicting the penetration depth, scabbing thickness, and perforation thickness of concrete structures impacted by solid missiles are summarized, reviewed, and compared. A series of impact analyses is performed to predict the local effects of the projectile at impact velocities varing from 95 to 215 m/s. The results obtained from the numerical simulations have been compared with tests that were carried out at Kojima to validate numerical modelling. The simulation results show reasonable agreement with the Kojima test results for the overall impact response of the RC slabs. From these results, it seems that the Degen equation give a very good estimate of perforation thickness against a tornado projectile for test data. Finally, the results obtained from the impact analysis have been compared with Degen formula to determine the perforation thickness of the RC slab.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.157-169
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• 2024

The article presents an analysis of innovative teaching technologies as a way to increase students' competitiveness. The author found that innovative technologies in education are information and communication technologies relying on computer-based learning. The structure, content of educational software, organization of Web-space are important when using innovative teaching technologies in English classes. We conducted the study in several stages: comparative analysis, synthesis, classification and systematization of the results of psychological and pedagogical, educational and methodological research; study of legislative acts, periodicals in order to identify the state of the research issue, and determining the directions of its solution, as well as subject, goal and objectives of the study. We used modelling to create situations of foreign language professional communication of future IT specialists. Empirical methods involved questionnaires used for identifying the motives of professional development and determining the features of the educational activities of future IT specialists in the process of training. The methods of mathematical statistics allowed to scientifically describe and systematize the obtained data, to identify the quantitative relationship between the studied phenomena, to analyse and summarize the results. We conducted a socio-psychological study during 2016 - 2019. It involved 255 first- and fourth-year students of National Technical University of Ukraine "Igor Sikorsky Kyiv Poly-technic Institute." Innovative information and communication technologies that improve the educational and cognitive activity of students, as well as increase the level of their knowledge have become important in teaching a foreign language in higher educational institutions. These technologies include MOODLE - Modular Object-Oriented Dynamic Learning Environment, business game, integrated pedagogical technology, case study technology. Thus, the information-rich learning process in combination with the use of innovative technologies, well-organized e-learning, interactive training courses, multimedia tools improves the program of teaching and learning foreign languages in general, and English in particular, improves the level of knowledge of future IT specialists and motivation to study and learn foreign languages, allows students to use a variety of authentic materials. We state that all these factors influence the process of individualization of learning and contribute to the successful mastery of a foreign language.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.28 no.3
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• pp.302-314
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• 2024

This study aimed to compare outcomes of hand-sewn and stapler closure techniques of pancreatic stump in patients undergoing distal pancreatectomy (DP). Impact of stapler closure reinforcement using mesh on outcomes was also evaluated. Literature search was carried out using multiple data sources to identify studies that compared hand-sewn and stapler closure techniques in management of pancreatic stump following DP. Odds ratio (OR) was determined for clinically relevant postoperative pancreatic fistula (POPF) via random-effects modelling. Subsequently, trial sequential analysis was performed. Thirty-two studies with a total of 4,022 patients undergoing DP with hand-sewn (n = 1,184) or stapler (n = 2,838) closure technique of pancreatic stump were analyzed. Hand-sewn closure significantly increased the risk of clinically relevant POPF compared to stapler closure (OR: 1.56, p = 0.02). When stapler closure was considered, staple line reinforcement significantly reduced formation of such POPF (OR: 0.54, p = 0.002). When only randomized controlled trials were considered, there was no significant difference in clinically relevant POPF between hand-sewn and stapler closure techniques (OR: 1.20, p = 0.64) or between reinforced and standard stapler closure techniques (OR: 0.50, p = 0.08). When observational studies were considered, hand-sewn closure was associated with a significantly higher rate of clinically relevant POPF compared to stapler closure (OR: 1.59, p = 0.03). Moreover, when stapler closure was considered, staple line reinforcement significantly reduced formation of such POPF (OR: 0.55, p = 0.02). Trial sequential analysis detected risk of type 2 error. In conclusion, reinforced stapler closure in DP may reduce risk of clinically relevant POPF compared to hand-sewn closure or stapler closure without reinforcement. Future randomized research is needed to provide stronger evidence.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.186-193
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• 2014

This study aimed to analyze spatio-temporal trends of phenological characteristics in South Korea by using MODIS EVI. For the phenology analysis, we had applied double logistic function to MODIS time-series data. Our results showed that starting date of phenology seems to have a tendency along with latitudinal trends. Starting date of phenology of Jeju Island and Mt. Sobeak went back for 0.38, 0.174 days per year, respectively whereas, Mt. Jiri and Mt. Seolak went forward for 0.32 days, 0.239 days and 0.119 days, respectively. Our results exhibited the fluctuation of plant phonological season rather than the change of phonological timing and season. Starting date of plant phenology by spatial distribution revealed tendency that starting date of mountain area was late, and basin and south foot of mountain was fast. In urban ares such as Seoul metropolitan, Masan, Changwon, Milyang, Daegu and Jeju, the phonological starting date went forward quickly. Pheonoligcal attributes such as starting date and leaf fall in urban areas likely being affected from heat island effect and related warming. Our study expressed that local and regional monitoring on phonological events and changes in Korea would be possible through MODIS data.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.22-37
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• 2018

Unmanned aerial vehicles (UAV) have attracted considerable attention both at home and abroad. The UAV is equipped with a camera that shoots images, which is advantageous for access to areas where archaeological investigations are not possible. Moreover, it is possible to acquire three-dimensional spatial image information by modeling the terrain through aerial photographing, and it is possible to specify the interpretation of the terrain of the survey area. In addition, if we understand the change of the terrain through comparison with past aerial photographs, it will be very helpful to grasp the existence of the ruins. The terrain modeling for searching these remains can be divided into two parts. First, we acquire the aerial photographs of the current terrain using the drone. Then, using image registration and post-processing, we complete the image-joining and terrain-modeling using past aerial photographs. The completed modeled terrain can be used to derive several analytical results. In the present terrain modeling, terrain analysis such as DSM, DTM, and altitude analysis can be performed to roughly grasp the characteristics of the change in the form, quality, and micro-topography. Past terrain modeling of aerial photographs allows us to understand the shape of landforms and micro-topography in wetlands. When verified with actual findings and overlapping data on the modelling of each terrain, it is believed that changes in hill shapes and buried Microform can be identified as helpful when used in low-flying applications. Thus, modeling data using aerial photographs is useful for identifying the reasons for the inability to carry out archaeological surveys, the existence of terrain and ruins in a wide area, and to discuss the preservation process of the ruins. Furthermore, it is possible to provide various themes, such as cadastral maps and land use maps, through comparison of past and present topographical data. However, it is certain that it will function as a new investigation methodology for the exploration of ruins in order to discover archaeological cultural properties.