• Journal of the Society of Naval Architects of Korea
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• v.46 no.3
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• pp.232-248
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• 2009

Numerical methodology to solve ship springing problem, which is basically fluid-structure interaction problem, was explored in this study. Solution of this hydroelasticity problem was sought by coupling higher order B-spline Rankine panel method and finite element method in time domain, each of which is introduced for fluid and structure domain respectively. Even though varieties of different combinations in terms of numerical scheme are possible and have been tried by many researchers to solve the problem, no systematic study regarding the characteristics of each scheme has been done so far. Here, extensive case studies have been done on the numerical schemes especially focusing on the iteration method, FE analysis of beam-like structure, handling of forward speed problem and so on. Two different iteration scheme, Newton style one and fixed point iteration, were tried in this study and results were compared between the two. For the solution of the FE-based equation of motion, direct integration and modal superposition method were compared with each other from the viewpoint of its efficiency and accuracy. Finally, calculation of second derivative of basis potential, which is difficult to obtain with accuracy within grid-based method like BEM was discussed.

• Journal of the Korean Society of Propulsion Engineers
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• v.5 no.3
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• pp.33-40
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• 2001

In order to investigate the operating characteristics of a supersonic steam ejector, the axisymmetric, compressible, Reynolds-averaged, Wavier-Stokes computations are performed using a finite volume method. The secondary and back pressures of the ejector system with a second throat are changed to investigate their effects on the suction mass flow. Three operation modes of the steam ejector system, the critical mode, subcritical mode and back flow mode, are discussed to predict the critical suction mass flow. The present computations are validated with some experimental results. The secondary and back pressures of the supersonic steam ejector significantly affect the critical suction mass flow. The present computations predict the experimented critical mass flow with fairly good accuracy A good correlation is obtained for the critical suction mass flow. The present results show that provided the primary nozzle configuration and secondary pressure are blown, we can predict the critical mass flow with good accuracy.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.635-641
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• 2006

Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and infer the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.39-44
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• 2006

Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning(CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and index the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

• Wind and Structures
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• v.10 no.2
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• pp.99-119
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• 2007

Estimations of wind flow over terrain are often needed for applications such as pollutant dispersion, transport safety or wind farm location. Whilst field studies offer very detailed information regarding the wind potential over a small region, the cost of instrumenting a natural fetch alone is prohibitive. Wind tunnels offer one alternative although wind tunnel simulations can suffer from scale effects and high costs as well. Computational Fluid Dynamics (CFD) offers a second alternative which is increasingly seen as a viable one by wind engineers. There are two issues associated with CFD however, that of accuracy of the predictions and set-up and simulation times. This paper aims to address the two issues by demonstrating, by way of an investigation of wind potential for the Askervein Hill, that a good level of accuracy can be obtained with CFD (10% for the speed up ratio) and that it is possible to automate the simulations in order to compute a full wind rose efficiently. The paper shows how a combination of script and session files can be written to drive and automate CFD simulations based on commercial software. It proposes a general methodology for the automation of CFD applied to the computation of wind flow over a region of interest.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.1
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• pp.17-25
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• 2008

To achieve the unidirectional airflow in a cleanroom, we need to predict accurately the static pressure losses at the lower plenum and to control properly the opening pressure ratio of access floor panels based on these pressure losses. At first, the present study proposed a correlation to predict the velocity distribution at the lower plenum, because the accuracy to predict pressure losses at the lower plenum depends on how to calculate the velocity correctly against the inner structures at the lower plenum. In the second place, this study proposed correlations which considered the effect of inner structures such as columns, ducts and equipments at the lower plenum on pressure losses. In order to test the accuracy of these correlations, we compared air flow patterns before regulating the opening ratio of access floor with those after regulating. Results after regulating the opening ratio of access floor show good unidirectional uniform airflow pattern. So the present method can be used as an important tool to control the air flow in a cleanroom.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2305-2314
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• 2023

The governing equations of atmospheric dispersion most often taking the form of a second-order partial differential equation (PDE). Currently, typical computational codes for predicting atmospheric dispersion use the Gaussian plume model that is an analytic solution. A Gaussian model is simple and enables rapid simulations, but it can be difficult to apply to situations with complex model parameters. Recently, a method of solving PDEs using artificial neural networks called physics-informed neural network (PINN) has been proposed. The PINN assumes the latent (hidden) solution of a PDE as an arbitrary neural network model and approximates the solution by optimizing the model. Unlike a Gaussian model, the PINN is intuitive in that it does not require special assumptions and uses the original equation without modifications. In this paper, we describe an approach to atmospheric dispersion modeling using the PINN and show its applicability through simple case studies. The results are compared with analytic and fundamental numerical methods to assess the accuracy and other features. The proposed PINN approximates the solution with reasonable accuracy. Considering that its procedure is divided into training and prediction steps, the PINN also offers the advantage of rapid simulations once the training is over.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.81-88
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• 2023

In the present scenario, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In Perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several perturbation strategies that may be used to protect data privacy. For this experiment, two perturbation techniques based on random projection and principal component analysis were used. These techniques include Improved Random Projection Perturbation (IRPP) and Enhanced Principal Component Analysis based Technique (EPCAT). The Naive Bayes classification algorithm is used for data mining approaches. These methods are employed to assess the precision, run time, and accuracy of the experimental results. The best perturbation method in the Nave-Bayes classification is determined to be a random projection-based technique (IRPP) for both the cardiovascular and hypothyroid datasets.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.235-240
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• 2006

The paper will give an overview of the mission of GalTeC and then concentrate on two main aspects. The first more detailed aspect, is the analysis of the key performance parameters for the Galileo system services and presenting a technical overview of methods and algorithms used. The second more detailed aspect, is the service volume prediction including service dimensioning using the Prediction tool. In order to monitor and validate the Galileo SIS performance for Open Service (OS) and Safety Of Life services (SOL) regarding the key performance parameters, different analyses in the SIS domain and User domain are considered. In the SIS domain, the validation of Signal-in-Space Accuracy SISA and Signal-in-Space Monitoring Accuracy SISMA is performed. For this purpose first of all an independent OD&TS and Integrity determination and processing software is developed to generate the key reference performance parameters named as SISRE (Signal In Space Reference Errors) and related over-bounding statistical information SISRA (Signal In Space Reference Accuracy) based on raw measurements from independent sites (e.g. IGS), Galileo Ground Sensor Stations (GSS) or an own regional monitoring network. Secondly, the differences of orbits and satellite clock corrections between Galileo broadcast ephemeris and the precise reference ephemeris generated by GalTeC will also be compared to check the SIS accuracy. Thirdly, in the user domain, SIS based navigation solution PVT on reference sites using Galileo broadcast ephemeris and the precise ephemeris generated by GalTeC are also used to check key performance parameters. In order to demonstrate the GalTeC performance and the methods mentioned above, the paper presents an initial test result using GPS raw data and GPS broadcast ephemeris. In the tests, some Galileo typical performance parameters are used for GPS system. For example, the maximum URA for one day for one GPS satellite from GPS broadcast ephemeris is used as substitution of SISA to check GPS ephemeris accuracy. Using GalTeC OD&TS and GPS raw data from IGS reference sites, a 10 cm-level of precise orbit determination can be reached. Based on these precise GPS orbits from GalTeC, monitoring and validation of GPS performance can be achieved with a high confidence level. It can be concluded that one of the GalTeC missions is to provide the capability to assess Galileo and general GNSS performance and prediction methods based on a regional and global monitoring networks. Some capability, of which first results are shown in the paper, will be demonstrated further during the planned Galileo IOV phase, the Full Galileo constellation phase and for the different services particularly the Open Services and the Safety Of Life services based on the Galileo Integrity concept.