• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.289-294
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• 2020

Peptic ulcer disease is a gastrointestinal disorder caused by Helicobacter pylori infection and the use of nonsteroid anti-inflammatory drugs. While many studies have been conducted to find the risk factors of peptic ulcers, there are no studies on the suggestion of peptic ulcer prediction models for Koreans. Therefore, the purpose of this study is to implement peptic ulcer prediction model using machine learning based on demographic information, obesity information, blood information, and nutritional information for middle-aged and elderly people. For model building, wrapper-based variable selection method and naive Bayes algorithm were used. The classification accuracy of the female prediction model was the area under the receiver operating characteristics curve (AUC) of 0.712, and males showed an AUC of 0.674, which is lower than that of females. These results can be used for prediction and prevention of peptic ulcers in the middle and elderly people.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.1-10
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• 2007

The capabilities ofBusiness Process Management Systems (BPMS's) are continuously extended to increase theeffectiveness of the management and enactment of business processes. This paper identifies the challenge ofcase prediction, which for a specific case under the control of a BPMS deals with the estimation of the remaining time until it is completed. An accurate case prediction facility is a valuable tool for the operationalcontrol of business processes, as it enables the pre-active monitoring of time violations. Little research has beencarried out in this area and few commercial tools support case prediction. This paper lists the requirements onsuch a facility and sketches sonae directions to reach a solution. To illustrate the depth of the problem, a smallaspect of the problem is treated in more detail. It involves the complex relations between tasks and resources inbusiness processes, which makes an exact analytical approach mfeasible.

• Journal of Ship and Ocean Technology
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• v.1 no.2
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• pp.41-49
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• 1997

We reviewed various oil-spill models and condensed the integrated information into a prediction model, “Green Sea Ranger”which is applicable to Korean coastal area. The developed software consists of pre- and post-modules for environment setup and display of results and main module for the prediction of oil\`s fate. In the pre-module target areas can be selected from the included geographic information system and various environmental and optional numerical data for the prediction can be input through easy GUI or imported from the database we established. For the fate of the spilt oil we included effects of spreading, advection, evaporation, and emulsification. Preliminary numerical experiment has proved that the developed oil-spill prediction system can be easily utilized in on-site oil recovery operations which usually require a quick and reasonable prediction.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.382-389
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• 2002

Recently, auger-drilled piling has been widely used in urban area to reduce the air pollution and noise. But this construction method that its basic theory was introduced from Japan may be changed depending on the each piling company and construction field condition. Therefore, the design code and management method for auger-drilled piling is not defined yet. Especially, the lack of research on the bearing capacity of auger-drilled piling leads to the absence of rational bearing capacity prediction equation. This paper presents the optimum design code and economical construction method of the auger-drilled piling by proposing the new bearing capacity prediction equation based on the site specific soil types and construction conditions. In this paper, existing bearing capacity prediction equations and current pile load tests were compared. And the end bearing capacity and skin friction characteristics were also analyzed by comparing the results of CAPWAP. From the results of analysis, a reliable bearing capacity prediction equation considered soil types is proposed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.179-188
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• 2004

Bankruptcy prediction is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. Recently, support vector machine (SVM) has been applied to the problem of bankruptcy prediction. The SVM-based method has been compared with other methods such as neural network, logistic regression and has shown good results. Genetic algorithm (GA) has been increasingly applied in conjunction with other AI techniques such as neural network, CBR. However, few studies have dealt with integration of GA and SVM, though there is a great potential for useful applications in this area. This study proposes the methods for improving SVM performance in two aspects: feature subset selection and parameter optimization. GA is used to optimize both feature subset and parameters of SVM simultaneously for bankruptcy prediction.

• Journal of the Korean Society of Marine Environment & Safety
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• v.4 no.1
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• pp.31-40
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• 1998

Through the combination of existing tidal prediction model and numerical tidal model, the efficient tidal prediction system was formulated and applied to the neighboring area of Pusan port. Because all tidal constituents for tidal prediction (69 tidal constituents are normally used) couldn't be considered due to the physical limits on computing process, some errors between the observed and predicted values were inevitably occurred. But it was confirmed that the computed values with maximum 10% of relative errors can be obtained if four major tidal constituents(M2, S2, K1, O1) are used. Thus, if other constituents than four major tidal constituents are additionally used, more accurate values will be obtained. Furthermore, if the database for harmonic constants in coastal waters is made in advance, using the numerical tidal model, prompt tidal prediction can be achieved at any time when it is required.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.49-56
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• 1997

In mobile communications, it is very important that we predict the propagation environments of radiation pattern, in order to decide the service area, select the best location of the best station, design the cell etc. Therefore, by analyzing the propagation prediction model that is varied according to the kind of antenna, the beam angle, the terrain and obstacles, we expect that the economic operating of communication networks, the calling quality and the service of subscriber will be enhanced. In this paper, we select the around of Seji base station in Naju-city Chonnam for modern suburban area and measure the field strength to propose the optimal propagation prediction model for suburban areas. We propose the propagation prediction model that, it is not found in the other models until now, consists of the correction coefficient with the relative differences of antenna effective height of the base station and mobile station for minimizing errors. Finally, comparing the results of the field test with the computer simulation(PPGIS : Propagation Prediction Geographic Information System) results for the Hata model, the Egri model, the Carey model and the propose model, we confirm the property of the proposed model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.5
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• pp.587-596
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• 2008

For Wireless internet service in Metropolitan area, optimum location selection for base station and cell planning are critical process in determining service coverage by accurate prediction of Wave Propagation Characteristics. Due to different kinds of characteristics in service area such as lay of land, natural feature and material, height and width of artificially made building, it has a great impact on the transmission and distance recovery of wireless network service. Therefore, these facts may cause substantial barriers in predicting & analyzing the expected level of service quality and providing it to subscribers. In this thesis, we have simulated the process to improve quality and coverage of the service by adjusting the location of Base station and the antenna angle that influence the service after the basic location of base station is selected according to the wave prediction model. Based on this simulations test, we have demonstrated the results in which subscribers would get higher quality of wireless internet service along with bigger coverage and the improved quality in the same service coverage area through optimization process of base station.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.875-878
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• 2015

In this paper, we propose an intra prediction hardware architecture with less processing time, computations and reduced hardware area for a high performance HEVC encoder. The proposed intra prediction hardware architecture uses common operation units to reduce computational complexity and uses $4{\times}4$ block unit to reduce hardware area. In order to reduce operation time, common operation unit uses one operation unit to generate predicted pixels and filtered pixels in all prediction modes. Intra prediction hardware architecture introduces the $4{\times}4$ PU design processing to reduce the hardware area and uses intemal registers to support $32{\times}32$ PU processmg. The proposed hardware architecture uses ten common operation units which can reduce execution cycles of intra prediction. The proposed Intra prediction hardware architecture is designed using Verilog HDL(Hardware Description Language), and has a total of 41.5k gates in TSMC $0.13{\mu}m$ CMOS standard cell library. At 150MHz, it can support 4K UHD video encoding at 30fps in real time, and operates at a maximum of 200MHz.