• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• BMB Reports
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• v.39 no.1
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• pp.68-75
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• 2006

In higher plants, P450s participate in the biosynthesis of many important secondary metabolites. Here we reported for the first time the isolation of a new cytochrome P450 cDNA that expressed in a stem-specific manner from Camptotheca acuminata (designated as CaSS), a native medicinal plant species in China, using RACE-PCR. The full-length cDNA of CaSS was 1735 bp long containing a 1530 bp open reading frame (ORF) encoding a polypeptide of 509 amino acids. Bioinformatic analysis revealed that CASS contained a heme-binding domain PFGXGRRXCX and showed homology to other plant cytochrome P450 monooxygenases and hydroxylases. Southern blotting analysis revealed that there was only one copy of the CaSS present in the genome of Camptotheca acuminata. Northern blotting analysis revealed that CaSS expressed, in a tissue-specific manner, highly in stem and lowly in root, leaf and flower. Our study suggests that CaSS is likely to be involved in the phenylpropanoid pathway.

• The Korean Journal of Petroleum Geology
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• v.11 no.1 s.12
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• pp.9-17
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• 2005

In the main target area of the block II, Targe-scale faults occur below the unconformity developed around 1 km in depth. The contrast of seismic velocity around the unconformity is generally so large that the strong multiples and the radical velocity variation would deteriorate the quality of migrated section due to serious distortion. More than 15 kinds of data processing techniques have been applied to improve the image resolution for the structures farmed from this active crustal activity. The bad and noisy traces were edited on the common shot gathers in the first step to get rid of acquisition problems which could take place from unfavorable conditions such as climatic change during data acquisition. Correction of amplitude attenuation caused from spherical divergence and inelastic attenuation has been also applied. Mild F/K filter was used to attenuate coherent noise such as guided waves and side scatters. Predictive deconvolution has been applied before stacking to remove peg-leg multiples and water reverberations. The velocity analysis process was conducted at every 2 km interval to analyze migration velocity, and it was iterated to get the high fidelity image. The strum noise caused from streamer was completely removed by applying predictive deconvolution in time space and ${\tau}-P$ domain. Residual multiples caused from thin layer or water bottom were eliminated through parabolic radon transform demultiple process. The migration using curved ray Kirchhoff-style algorithm has been applied to stack data. The velocity obtained after several iteration approach for MVA (migration velocity analysis) was used instead or DMO for the migration velocity. Using various testing methods, optimum seismic processing parameter can be obtained for structural and stratigraphic interpretation in the Block II, Yellow Sea Basin.

• Journal of Korean Society of Steel Construction
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• v.29 no.1
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• pp.49-60
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• 2017

As well as the strength check, fatigue life check is also mainly required for designing mooring lines of the floating structures. In general, forces which induce dynamic structural response significantly affect to fatigue design of the mooring lines. So, waves are mainly considered as the governing loading for fatigue design of the mooring lines. In this study, characteristics of the fatigue damage of the mooring lines for submerged floating tunnels (SFT) under irregular waves are investigated. For this study time domain hydrodynamic analysis is used to obtain motion of the tunnel and tension and stresses of the mooring lines under the specific environmental conditions. Also, the Rainflow-counting method, the Palmgren-Miner's rule, and S-N curves for floating offshore structures presented by DNV recommendation is applied to calculate the fatigue damage due to the fluctuating stresses. Referring to the design plactice of the tendon pipes for TLP (tension-leg platform), which is very similar structural system to SFT, it is assumed that a 100 year return period wave attacks the SFT systems during 48 hours and the fatigue damages due to the environmental loading are calculated. Following the analysis sequence, the effects of the tunnel draft, spacing and initial inclination angle of the mooring lines on the fatigue damage under the specific environmental loadings are investigated.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.493-500
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• 2019

In this study, sensitivity analysis of sediment transport scaling factors in Delft3D-Morphology was performed to examine the effect those parameters on simulation results of cross-shore profile changes. For numerical experiments, one-year wave time series data which were observed in 2018 on the Maengbang coast in Gangwon prefecture were applied as external force. Bathymetric data observed in January and October of the same year were used as initial bathymetric data and annual bathymetric change data, respectively. The simulation performance of the model was evaluated based on the Brier Skill Score index for each part by dividing an arbitrary cross section within the calculation domain into the onshore and offshore parts. As a result, it was found thet the f_BED variable has a slight effect on the simulation results. The f_BEDW and f_SUSW variables show good simulation performance in onshore part when the value less than 0.5 is applied and vice versa. Among the experimental conditions, the optimal combinations of variables are f_BED = 1.0, f_BEDW = 1.0, f_SUSW = 0.1 for the onshore region and f_BED = 1.0, f_BEDW = 1.0, f_SUSW = 0.5 for the offshore region. However, since these combinations were derived based on the observation data on Maengbang beach in 2018, users should be careful when applying those results to other areas.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.1
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• pp.9-18
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• 2016

The slender structures such as high rise building or marine riser are highly susceptible to dynamic force exerted by fluid-structure interactions among which vortex-induced vibration(VIV) is the main cause of dynamic unstability of the structural system. If VIV occurs in natural frequency regime of the structure, fatigue failure likely happens by so-called lock-in phenomenon. This study presents the numerical analysis of dynamic behavior of both structure and fluid in the lock-in regimes and investigates the subjacent phenomena to hold the resonance frequency in spite of the change of flow condition. Unsteady and laminar flow was considered for a two-dimensional circular cylinder which was assumed to move freely in 1 degree of freedom in the direction orthogonal to the uniform inflow. Fluid-structure interaction was implemented by solving both unsteady flow and dynamic motion of the structure sequentially in each time step where the fluid domain was remeshed considering the movement of the body. The results show reasonable agreements with previous studies and reveal characteristic features of the lock-in phenomena. Not only the lift force but also drag force are drastically increasing during the lock-in regime, the vertical displacement of the cylinder reaches up to 20% of the diameter of the cylinder. The correlation analysis between lift and vertical displacement clearly show the dramatic change of the phase difference from in-phase to out-of-phase when the cylinder experiences lock-in. From the results, it can be postulated that the change of phase difference and flow condition is responsible for the resonating behavior of the structure during lock-in.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.831-843
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• 2015

This study estimates MODIS-derived evapotranspiration data quality by revised RS-PM algorithm in Seolmacheon test basin. We used latent flux with eddy covariance method to evaluate MODIS-derived spatial evapotranspiration and gap-filled these data by three methods (FAO-PM, MDV and Kalman Filter) and to quantify daily evapotranspiration. Gap-filled daily evapotranspiration data was used to evaluate evapotranspiration computed by revised RS-PM algorithm derived MODIS satellite images. For the water budget analysis, we used soil moisture content that is quantified to average individual soil moisture rate observed by TDR (Time Domain Reflectometry) sensor at soil depth. The soil moisture variation is calculated in consideration from initial to final soil moisture content. According to the result of this study, evapotranspiration computed by revised RS-PM algorithm is very larger than eddy covariance data gap-filled by three methods. Also, water budget characteristics is not closed. We could analysis that MODIS-derived spatial evapotranspiration does not represent actual evapotranspiration in Seolmacheon.

• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.132-138
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• 2003

The use of long rails in high-speed railway bridges causes additional stresses due to nonlinear behaviours between the rail and bridge decks in the neighbourhood of the deck joints. In the seismic response analysis of high-speed railway bridges, since structural response is highly sensitive to properties of the ground motion, spatial variation of the ground excitation affects responses of the bridges, which in turn affect stresses in the rails. In addition, it is shown that high-speed trains need very long distances to stop when braking under seismic occurrence corresponding to operational earthquake performance level so that verification of the safe stoppage of the train is also required. In view of such additional stresses due to long rails, sensibility of structural response to the properties of the ground motion and braking distance needed by the train to stop safely, this paper proposes and establishes a time domain nonlinear dynamic analysis method that accounts for braking loads, spatial variation of the ground motion and material nonlinearities of rails to analyze long rail stresses in high-speed railway bridges subjected to seismic event. The accuracy of the proposed method is demonstrated through an application on a typical site of the Korean high-speed railway.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.