• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.30 no.2
• /
• pp.75-82
• /
• 2002

It is useful to detect the tracking error with an optimal view in the presence of measurement origin uncertainty. In this paper, after the investigation of the targer error dependent on the detection threshold as well as the detection and false alarm probabilities in a clutter environment, a new algorothm that optimizes the threshold of validation region for target trackinf is proposed. The performance of the algorithm is demonstrated through computer simulations.

• Korean Journal of Remote Sensing
• /
• v.20 no.5
• /
• pp.353-359
• /
• 2004

This study proposes an approach to unsupervisedly estimate the number of classes and the parameters of defining the classes in order to train the classifier. In the proposed method, the image is segmented using a spatial region growing based on hierarchical clustering, and fuzzy training is then employed to find the sample classes that well represent the ground truth. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes. The experimental results show that the new scheme proposed in this study could be used to select the regions with different characteristics existed on the scene of observed image as an alternative of field survey that is so expensive.

• Journal of the Korean Society of Visualization
• /
• v.20 no.2
• /
• pp.28-37
• /
• 2022

Flow characteristics of jet impingement over concave hemispherical surface with effusion cooling holes is relatively more complex than that of a flat surface, so the experimental validation for computational fluid dynamics (CFD) results is important. In this study, experimental results were compared with simulation results obtained by assuming different turbulence models. The vortex was observed in the region between the central jets where the recirculation structure appeared. The different patterns of vorticity distributions were observed for each turbulence models due to different interaction of the injected jet flow. Among them, the transition k-kl-ω model predicted similarly not only the jet potential core region with higher velocity, but also the recirculation region between the central jets. From the validation, it may be helpful to accurately predict heat and mass transfer in jet impingement/effusion hole system.

• Journal of the Society of Naval Architects of Korea
• /
• v.49 no.1
• /
• pp.6-13
• /
• 2012

As ocean resources in shallow water areas are being exhausted, deep sea development is becoming common these days. Therefore floating type offshore structures are more competitive than fixed type structures, and FPSO is the most popular one these days. FPSO's are generally operated in a specific region and positioned to meet mostly head or bow waves in order to reduce roll motions. However this makes these vessels more vulnerable to green water around the bow region, and therefore the bow shape must be properly designed to mitigate green water damage. In the present study, experimental results for three different FPSO bow shapes in regular head waves were analyzed and compared to each other. Also CFD computations were carried out as a sample validation case for the database built for CFD code validation.

• Asian Journal of Atmospheric Environment
• /
• v.12 no.3
• /
• pp.193-203
• /
• 2018

The operational aerosol retrieval algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements was recently updated and named collection 6 (C6). The C6 MODIS aerosol algorithm, a substantially improved version of the collection 5 (C5) algorithm, uses an enhanced aerosol optical thickness(AOT) retrieval process consisting of new surface reflection and aerosol models. This study reports on the estimation and validation of the two latest versions, the C5 and C6 MODIS aerosol products over the East Asian region covering $20^{\circ}N$ to $56^{\circ}N$ and $80^{\circ}E$ to $150^{\circ}E$. This study also presents a comparative validation of the two versions(C5 and C6) of algorithms with different methods(Dark Target(DT) and Deep Blue (DB) retrieval methods) from the Terra and Aqua platforms to make use of the Aerosol Robotic Network (AERONET) sites for the years 2000-2016. Over the study region, the spatially averaged annual mean AOT retrieved from C6 AOT is about 0.035 (5%) less than the C5 counterparts. The linear correlations between MODIS and AERONET AOT are R = 0.89 (slope = 0.86) for C5 and R = 0.95 (slope = 1.00) for C6. Moreover, the magnitude of the mean error in C6 AOT-the difference between MODIS AOT and AERONET AOT-is 40% less than that in C5 AOT.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.394-397
• /
• 2006

Gridded products of surface wind/wind-stress over the world ocean have been constructed by using satellite scatterometer as the Japanese Ocean Flux data sets with Use of Remote-sensing Observation (J-OFURO) data. Our previous validation study in the tropical Pacific using TAO/Triton and NDBC buoys revealed high reliability of our products. In this study, the Kuroshio Extension Observatory (KEO) buoy data are used for validation of other gridded wind-stress products including the NCEP-1 and 2 in the western North Pacific region where there have been few in-situ data. Results reveal that our J-OFURO product has almost zero mean difference and smallest root-mean-square (RMS) difference, while the NCEP-1 and 2 ones significantly positive biases and relatively high RMS difference. Intercomparison between the J-OFURO and NCEP products in a wide region of the North Pacific covered by the westerly winds exhibits that the NCEPs have larger magnitudes in the wind stress than the J-OFURO's, suggesting overestimation of the NCEPs.

• Journal of Microbiology
• /
• v.43 no.5
• /
• pp.411-416
• /
• 2005

The high-throughput sequencing of microbial genomes has resulted in the relatively rapid accumulation of an enormous amount of genomic sequence data. In this context, the problem posed by the detection of promoters in genomic DNA sequences via computational methods has attracted considerable research attention in recent years. This paper addresses the development of a predictive model, known as the dependence decomposition weight matrix model (DDWMM), which was designed to detect the core promoter region, including the -10 region and the transcription start sites (TSSs), in prokaryotic genomic DNA sequences. This is an issue of some importance with regard to genome annotation efforts. Our predictive model captures the most significant dependencies between positions (allowing for non­adjacent as well as adjacent dependencies) via the maximal dependence decomposition (MDD) procedure, which iteratively decomposes data sets into subsets, based on the significant dependence between positions in the promoter region to be modeled. Such dependencies may be intimately related to biological and structural concerns, since promoter elements are present in a variety of combinations, which are separated by various distances. In this respect, the DDWMM may prove to be appropriate with regard to the detection of core promoter regions and TSSs in long microbial genomic contigs. In order to demonstrate the effectiveness of our predictive model, we applied 10-fold cross-validation experiments on the 607 experimentally-verified promoter sequences, which evidenced good performance in terms of sensitivity.

• Korean Journal of Remote Sensing
• /
• v.16 no.4
• /
• pp.315-325
• /
• 2000

Observations were made to validate ocean color algorithms in the Ulleung Basin, East Sea in May 2000. Small scale and meso-scale surveys were conducted for the validation of ocean color products (nLw: normalized water-leaving radiance and chlorophyll concentration). There were discrepancies between SeaWiFS and in situ nLw showing the current aerosol models of standard SeaWiFS processing software are less than adequate (Gordon and Wang, 1994). Applying the standard SeaWiFS in-water algorithm resulted in an overestimation of chlorophyll concentration. This is because that CDOM absorption was higher than the estimated chlorophyll absorption. TSS concentration was also high. Therefore, the study region deviated from Case 1 waters. The source of these materials seems to be the entrainment of coastal water by the Tsushima Warm Current. Study of the bio-optical properties in other season is desirable.

• Communications of the Korean Mathematical Society
• /
• v.11 no.4
• /
• pp.1147-1157
• /
• 1996

Nonlinear ill-posed problems arise in many application including parameter estimation and inverse scattering. We introduce a least squares regularization method to solve nonlinear ill-posed problems with constraints robustly and efficiently. The regularization method uses Trust-Region approach to handle the constraints on variables. The Generalized Cross Validation is used to choose the regularization parameter in computational tests. Numerical results are given to exhibit faster convergence of the method over other methods.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.4
• /
• pp.161-166
• /
• 2018

In this paper, we propose a method for the random selection of pooling operations for the regularization and reduction of cross validation in convolutional neural networks. The pooling operation in convolutional neural networks is used to reduce the size of the feature map and for its shift invariant properties. In the existing pooling method, one pooling operation is applied in each pooling layer. Because this method fixes the convolution network, the network suffers from overfitting, which means that it excessively fits the models to the training samples. In addition, to find the best combination of pooling operations to maximize the performance, cross validation must be performed. To solve these problems, we introduce the probability concept into the pooling layers. The proposed method does not select one pooling operation in each pooling layer. Instead, we randomly select one pooling operation among multiple pooling operations in each pooling region during training, and for testing purposes, we use probabilistic weighting to produce the expected output. The proposed method can be seen as a technique in which many networks are approximately averaged using a different pooling operation in each pooling region. Therefore, this method avoids the overfitting problem, as well as reducing the amount of cross validation. The experimental results show that the proposed method can achieve better generalization performance and reduce the need for cross validation.