• Journal of the Korean earth science society
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• v.31 no.3
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• pp.214-224
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• 2010

Gravity and Magnetic survey data were analyzed to investigate the geophysical characteristics and regional geological structures of the southwestern Yellow Sea. The set of data about the southwestern part of the Yellow Sea in Korea was one collected by the Korea Ocean Research and Development Institute (KORDI) in 2003, 2004, and 2005. The Yellow Sea has a few basins and the study area also includes parts of the Heuksan Basin and the East China Sea Basin. The bathymetry of the study area ranges from about ?40 m southwestward near China to about 150 m northeastward near Korea. The bathymetry has the gentle rise and fall and the smooth slope. The gravity anomalies, from sea surface gravity and satellite gravity data, reflect the basement rocks rather than the smooth bathymetry. The gravity anomalies are higher on Northeastern part of the study area and lower over the South of the Heuksan Basin. The analytic signal from the Bouguer anomaly shows higher anomalous zones near the boundaries of the basins. The magnetic anomalies and the analytic signal, from the magnetic data, suggest that the complex anomalies on the Northern part are attributed to the volcanic intrusions and that the smooth patterns in the Southern part are based on the lack of the intrusions. The power spectrum analysis of the Bouguer anomalies and the magnetic anomalies indicate that the depth to the Moho discontinuity varies from about 30.2 to 28.3 km and that the depths of the basement rocks and the Eocene discontinuity range from about 8.4 to 8 km and from about 1.5 to 1.7 km, respectively. The inversion of the Bouguer anomaly shows that the Moho depth to the Western part of the study area near China is slightly deeper than the Eastern part near Korea. The result of 2-D gravity modeling has a good coherence with the results of the analytic signal, the power spectrum analysis, and the inversion.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.2
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• pp.120-127
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• 2015

Purpose: The aim was to investigate the effect of implant thread designs on the stress dissipation of the implant. Materials and methods: The threads evaluated in this study included the V-shaped, buttress, reverse buttress, and square-shaped threads, which were of the same size (depth). Building four different implant/bone complexes each consisting of an implant with one of the 4 different threads on its cylindrical body ($4.1mm{\times}10mm$), a force of 100 N was applied onto the top of implant abutment at $30^{\circ}$ with the implant axis. In order to simulate different osseointegration stages at the implant/bone interfaces, a nonlinear contact condition was used to simulate immature osseointegration and a bonding condition for mature osseointegration states. Results: Stress distribution pattern around the implant differed depending on the osseointegration states. Stress levels as well as the differences in the stress between the analysis models (with different threads) were higher in the case of the immature osseointegration state. Both the stress levels and the differences between analysis models became lower at the completely osseointegrated state. Stress dissipation characteristics of the V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration. These results indicated that implant thread design may have biomechanical impact on the implant bed bone until the osseointegration process has been finished. Conclusion: The stress dissipation characteristics of V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.223-231
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• 2018

Recently, due to various environmental problems, blast tracks in tunnel are replaced with concrete tracks, but they have more adverse effects on noise than blast tracks so that additional noise measures are needed. Among these measures, sound-absorbing blocks start to be used due to its easy and quick installation. However, the performance of sound absorption blocks need to be verified under real environmental and operational conditions. In this paper, interior noise levels in KTX train cruising in Dalseong tunnel are measured before and after the installation of sound-absorbing blocks and the measured data are analyzed and compared. Additionally, noise reduction are estimated by modeling the high speed train, the tunnel and absorption blocks. Measurement devices and methods are used according to ISO 3381 and the equivalent sound pressure levels during the cruising time inside the tunnel are computed. In addition to overall SPLs(Sound Pressure Levels), 1/3-octave-band levels are also analyzed to account for the frequency characteristics of sound absorption and equipment noise in a cabin. In addition, to consider the effects of train cruising speeds and environmental conditions on the measurements, the measured data are corrected by using those measured during the train-passing through the tunnels located before and behind the Dalseong tunnel. Analysis of measured results showed that the maximum noise reduction of 6.8 dB (A) can be achieved for the local region where the sound-absorbing blocks are installed. Finally, through the comparison of predicted 1/3-octave band SPLs for the KTX interior noise with the measurements, the understanding of noise reduction mechanism due to sound-absorbing blocks is enhanced.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Knowledge Management Research
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• v.21 no.3
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• pp.249-269
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• 2020

Recently, as the online market has matured, it is facing many problems to prevent the growth. The most common problem is the homogenization of online products, which fails to increase the number of customers any more. Moreover, although the portion of the online market has increased significantly, it now becomes essential to expand offline for further development. In response, many online firms have recently sought to expand their businesses and marketing channels by securing offline spaces that can complement the limitations of online platforms, on top of their existing advantages of online channels. Based on their competitive advantage in terms of analyzing large volumes of customer data utilizing information technologies (e.g., big data and artificial intelligence), they are reinforcing their offline influence as well through this online for offline (O4O) business model. On the other hand, most of the existing research has primarily focused on online to offline (O2O) business model, and there is still a lack of research on O4O business models, which have been actively attempted in various industrial fields in recent years. Since a few of O4O-related studies have been conducted only in an experience marketing setting following a case study method, it is critical to conduct an empirical study on O4O selection attributes and their impact on customer satisfaction and loyalty. Therefore, focusing on China's representative O4O business model, 'Fresh Hema,' this study attempts to identify some key selection attributes specialized for O4O services from the customers' viewpoint and examine the impact of these attributes on customer satisfaction and loyalty. The results of the structural equation modeling (SEM) with 300 O4O (Fresh Hema) experienced customers, reveal that, out of seven O4O selection attributes, four (mobile app quality, mobile payment, product quality, and store facilities) have an impact on customer satisfaction, which also leads to customer loyalty (reuse intention, recommendation intention, and brand attachment). This study would help managers in an O4O area well adapt to rapidly changing customer needs and provide them with some guidelines for enhancing both customer satisfaction and loyalty by allocating more resources to more significant selection attributes, rather than less significant ones.

• KSBB Journal
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• v.29 no.4
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• pp.285-296
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• 2014

Although the problems of the algal blooms have been world-widely observed in freshwater, estuary, and marine throughout the year, it is not yet certain what are the basic causes of such blooms. Consequently, it is very difficult to predict when and where algal blooms occur. The constituents of the Asian dust are in a good agreement with the elements required for the algal growth, which suggests some possible relationship between the algal blooms and the Asian dust. There have been frequently algal blooms in drinking water from rivers or lakes. However, there is no any algal blooms in upwelling waters where the Asian dust cannot penetrate into the soil due to its relatively weak settling velocity (size of particles, $4.5{\pm}1.5{\mu}m$), which implies the possible close relationship of the Asian dust with algal blooms. The present initiative study is thus intended firstly in Korea to illustrate such a relationship by reviewing typical previous studies along with 12 years of weekly iron profiles (2001~2012) and two slant culture experiments with the dissolved Asian dust. The result showed bacterial suspected colonies in the slant culture experiment that are qualitatively in a good agreement with the recent Japanese studies. Since the diatoms require cheap energy (8%) compared to other phytoplankton (100%) to synthesize their cell walls by silicate, the present results can be used to predict algal blooms by diatoms if the concentrations of iron and silicate are available during spring and fall. It can be postulated that the algal blooms occur only if the environmental factors such as light, nutrients, calm water surface layer, temperature, and pH are simultaneously satisfied with the requirements of the micronutrients of mineral ions supplied by the Asian dust as enzymatic cofactors for the rapid bio-synthesis of the macromolecules during algal blooms. Simple eco-friendly methods to regulate the algal blooms are suggested for the initial stage of blooming with limited area: 1) to cover up the water surface with black curtain and inhibit photosynthesis during the day time, 2) to blow air (20.9%) or pure oxygen into the bottom of the water and inhibit rubisco for carbon uptake and nitrate reductase for nitrogen uptake activities in algal growth during the night, 3) to eliminate the resting spores or cysts by suction of bottom sediments as deep as 5 cm to prevent the next year germinations.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.5
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• pp.700-707
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• 1997

In order to express exactly the total resistance of bottom trawl nets subjected simultaneously to the water flow and the bottom friction, the influence of frictional force was added to the formular for the flow resistance of trawl nets obtained by previous papev and the experimental data obtained by other investigators were analyzed by the formula. The analyzation produced the total resistance R (kg) expressed as $$R=4.5(\frac{S_n}{S_m})^{1.2}S\;v^{-1.8}+20(Bv)^{1.1}$$ where $S(m^2)$ was the wall area of nets, $S_m\;(m^2)$ the cross-sectional area of net mouths, $S_n\;(m^2)$ the area of nets projected to the plane perpendicular to the water flow, B (m) the made-up circumference at the fore edge of bag parts, and v(m/sec) the dragging velocity. From the viewpoint that expressing R in the form of $R=kSv^2$ was a usual practice, however, the resistant coefficient $k(kg{\cdot}sec^2/m^4)$ was compared with the factors influencing it by reusing the experimental data. The comparison gave that the coefficient k might be expressed approximately as a function of BL only and so the resistance R (kg) as $$R=18{\alpha}B^{0.5}L\;v^{1.5}$$ where L (m) was the made-up total length of nets and $\alpha=S/BL$. But the values of a in the nets did not deviate largely from their mean, 0.48, for all the nets and so the general expression of R (kg) for all the bottom trawl nets could be written as $$R=9\;B^{0.5}\;L\;v^{1.5}$$.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Journal of Wetlands Research
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• v.16 no.4
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• pp.303-318
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• 2014

Baseflow gives a significant contribution to stream function in the regions where climatic characteristics are seasonally distinct. In this regard, variable baseflow can make it difficult to maintain a stable water supply, as well as causing disruption to the stream ecosystem. Changes in land use can affect both the direct flow and baseflow of a stream, and consequently, most other components of the hydrologic cycle. Baseflow estimation depends on the observed streamflow in gauge watersheds, but accurate predictions of streamflow through modeling can be useful in determining baseflow data for ungauged watersheds. Accordingly, the objectives of this study are to 1) improve predictions of SWAT by applying the alpha factor estimated using RECESS for calibration; 2) estimate baseflow in an ungauged watershed using the WHAT system; and 3) evaluate the effects of changes in land use on baseflow characteristics. These objectives were implemented in the Gapcheon watershed, as an ungauged watershed in South Korea. The results show that the alpha factor estimated using RECESS in SWAT calibration improves the prediction for streamflow, and, in particular, recessions in the baseflow. Also, the changes in land use in the Gapcheon watershed leads to no significant difference in annual baseflow between comparable periods, regardless of precipitation, but does lead to differences in the seasonal characteristics observed for the temporal distribution of baseflow. Therefore, the Guem River, into which the stream from the Gapcheon watershed flows, requires strategic seasonal variability predictions of baseflow due to changes in land use within the region.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.