• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3211-3230
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• 2014

Recently, sparse coding has achieved remarkable success in image representation tasks. In practice, the performance of clustering can be significantly improved if limited label information is incorporated into sparse coding. To this end, in this paper, a novel semi-supervised algorithm, called constrained sparse concept coding (CSCC), is proposed for image representation. CSCC considers limited label information into graph embedding as additional hard constraints, and hence obtains embedding results that are consistent with label information and manifold structure information of the original data. Therefore, CSCC can provide a sparse representation which explicitly utilizes the prior knowledge of the data to improve the discriminative power in clustering. Besides, a kernelized version of our proposed CSCC, namely kernel constrained sparse concept coding (KCSCC), is developed to deal with nonlinear data, which leads to more effective clustering performance. The experimental evaluations on the MNIST, PIE and Yale image sets show the effectiveness of our proposed algorithms.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.94-102
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• 2021

This study addresses a method for 3D reconstruction using acoustic data with heterogeneous sonar devices: Forward-Looking Multibeam Sonar (FLMS) and Profiling Sonar (PS). The challenges in sonar image processing are perceptual ambiguity, the loss of elevation information, and low signal to noise ratio, which are caused by the ranging and intensity-based image generation mechanism of sonars. The conventional approaches utilize additional constraints such as Lambertian reflection and redundant data at various positions, but they are vulnerable to environmental conditions. Our approach is to use two sonars that have a complementary data type. Typically, the sonars provide reliable information in the horizontal but, the loss of elevation information degrades the quality of data in the vertical. To overcome the characteristic of sonar devices, we adopt the crossed installation in such a way that the PS is laid down on its side and mounted on the top of FLMS. From the installation, FLMS scans horizontal information and PS obtains a vertical profile of the front area of AUV. For the fusion of the two sonar data, we propose the probabilistic approach. A likelihood map using geometric constraints between two sonar devices is built and a monte-carlo experiment using a derived model is conducted to extract 3D points. To verify the proposed method, we conducted a simulation and field test. As a result, a consistent seabed map was obtained. This method can be utilized for 3D seabed mapping with an AUV.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1691-1696
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• 2010

The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliabilitybased design optimization are examples of the most famous methodologies. The statistical moments of a performance function and the constraints corresponding to probability conditions are involved in the formulation of these methodologies. Therefore, it is essential to effectively and accurately calculate them. The sensitivities of these methodologies have to be determined when nonlinear programming is utilized during the optimization process. The sensitivity of statistical moments and probability constraints is expressed in the integral form and limited to the normal random variable; we aim to expand the sensitivity formulation to nonnormal variables. Additional functional calculation will not be required when statistical moments and failure or satisfaction probabilities are already obtained at a design point. On the other hand, the accuracy of the sensitivity results could be worse than that of the moments because the target function is expressed as a product of the performance function and the explicit functions derived from probability density functions.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.5
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• pp.481-491
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• 2014

In this paper, we discussed a problem for improving the throughput of a crankshaft manufacturing line in an automotive factory in which the budget for purchasing new machines and installing additional buffers is limited. We also considered the constraint of available space for both of machine and buffer. Although this problem seems like a kind of buffer allocation problem, it is different from buffer allocation problem because additional machines are also considered. Thus, it is not easy to calculate the throughput by mathematical model, and therefore simulation model was developed using $ARENA^{(R)}$ for estimating throughput. To determine the investment plan, a modified Arrow Assignment Rule under some constraints was suggested and it was applied to the real case.

• Computers and Concrete
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• v.32 no.6
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• pp.625-637
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• 2023

The application of ML approaches in determining the resisting capacity of fire damaged RC columns is introduced in this paper, on the basis of analysis data driven ML modeling. Considering the characteristics of the structural behavior of fire damaged RC columns, the representative five approaches of Kernel SVM, ANN, RF, XGB and LGBM are adopted and applied. Additional partial monotonic constraints are adopted in modelling, to ensure the monotone decrease of resisting capacity in RC column with fire exposure time. Furthermore, additional suggestions are also added to mitigate the heterogeneous composition of the training data. Since the use of ML approaches will significantly reduce the computation time in determining the resisting capacity of fire damaged RC columns, which requires many complex solution procedures from the heat transfer analysis to the rigorous nonlinear analyses and their repetition with time, the introduced ML approach can more effectively be used in large complex structures with many RC members. Because of the very small amount of experimental data, the training data are analytically determined from a heat transfer analysis and a subsequent nonlinear finite element (FE) analysis, and their accuracy was previously verified through a correlation study between the numerical results and experimental data. The results obtained from the application of ML approaches show that the resisting capacity of fire damaged RC columns can effectively be predicted by ML approaches.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1072-1078
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• 2008

In this paper, we propose an efficient superposition coding multiplexing(SCM) method based on power allocation in descending order for fading broadcast channels in which per-user minimum and maximum rate constraints are considered in order to maximize the transmission effectiveness. It consists of three steps as follows. In the first step, a user group is selected to maximize the number of users with whom a transmitter can communicate instantaneously. In the second step, per-user power allocation for each user is done in descending order of transmit power by determining a maximum allowable interference power from all subsequent interfering users in order to guarantee its corresponding minimum rate, and then a residual power is calculated. The final step is performed if some power remains even after the second step. In this step, additional power allocation is performed up to the maximum transmit power to provide the maximum rate to the corresponding user, again in ascending order, starting from the last user in descending order. But, this method does not require power reallocation to subsequent users because tentative power allocation in the second step has been performed in descending order to guarantee the minimum rate for each user, taking into account the maximum allowable interference power from all the subsequent users. Therefore, the proposed method gets more efficient in term of computational complexity when per-user minimum as well as maximum rate constraints exist, especially as the number of users increases.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.939-947
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• 2008

The paper proposes a new formulation of the output feedback pole assignment problem. In this formulation, a unified approach is presented for solving the pole assignment problem with various additional objectives. These objectives include optimizing a variety of performance indices, and imposing constraints on the output feedback matrix structure, e.g. decentralized structure. Conditions for the existence of the output feedback are discussed. However, the thrust of the paper is on the development of a convergent pole assignment algorithm. It is shown that when exact pole assignment is not possible, the method can be used to place the poles close to the desired locations. Examples are provided to illustrate the method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.295-301
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• 2018

This study compares optimization algorithms for efficient estimations of ship's hydrodynamic coefficients. Two constrained algorithms, the interior point and the sequential quadratic programming, are compared for the estimation. Mathematical optimization is designed to get optimal hydrodynamic coefficients for modelling a ship, and benchmark data are collected from sea trials of a training ship. A calibration for environmental influence and a sensitivity analysis for efficiency are carried out prior to implementing the optimization. The optimization is composed of three steps considering correlation between coefficients and manoeuvre characteristics. Manoeuvre characteristics of simulation results for both sets of optimized coefficients are close to each other, and they are also fit to the benchmark data. However, this similarity interferes with the comparison, and it is supposed that optimization conditions, such as designed variables and constraints, are not sufficient to compare them strictly. An enhanced optimization with additional sea trial measurement data should be carried out in future studies.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1081-1084
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• 1998

In this paper, we propose the bus coding technique for low power consumption. For CMOS circuit most power is dissipated as dynamic power for charging and discharging node capacitances.Though the I/O and bus are likely to have the very large capacitances associated with them and dissipate much of the power dissipated by an IC, they have little beenthe special target for power reduction. The conventional Bus-Invert coding method can't decrease the peak power dissipation by 50% because the additional invert signal line can invoke a transition at the time when Bus-Invert coding isn't used to code original bus data. The proposed technique always constraints the Hamming distance between data transferred sequentially to be below the half of the bus width, and thus decrease the I/O peak power dissipation and the I/O average power dissipation.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.357-360
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• 2005

In this paper we consider the well-known semiparametric proportional hazards (PH) models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enable us to estimate the survival curve when n < < p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA(cDNA) data.