• Korean Management Science Review
• /
• v.11 no.3
• /
• pp.1-11
• /
• 1994

Recent advances in linear programming solution methodology have focused on interior point methods. This powerful new class of methods achieves significant reductions in computer time for large linear programs and solves problems significantly larger than previously possible. These methods can be examined from points of Fiacco and McCormick's barrier method, Lagrangian duality, Newton's method, and others. This study presents a primal-dual log barrier algorithm of interior point methods for linear programming. The primal-dual log barrier method is currently the most efficient and successful variant of interior point methods. This paper also addresses a Cholesky factorization method of symmetric positive definite matrices arising in interior point methods. A special structure of the matrices, called supernode, is exploited to use computational techniques such as direct addressing and loop-unrolling. Two dense matrix handling techniques are also presented to handle dense columns of the original matrix A. The two techniques may minimize storage requirement for factor matrix L and a smaller number of arithmetic operations in the matrix L computation.

• Communications of the Korean Mathematical Society
• /
• v.37 no.3
• /
• pp.905-913
• /
• 2022

We characterize metrizability and submetrizability for point-open, open-point and bi-point-open topologies on C(X, Y), where C(X, Y) denotes the set of all continuous functions from space X to Y ; X is a completely regular space and Y is a locally convex space.

• Bulletin of the Korean Mathematical Society
• /
• v.61 no.1
• /
• pp.195-205
• /
• 2024

In this paper, we consider the set of periodic shadowable points for homeomorphisms of a compact metric space, and we prove that this set satisfies some properties such as invariance and being a G_δ set. Then we investigate implication relations related to sets consisting of shadowable points, periodic shadowable points and uniformly expansive points, respectively. Assume that the set of periodic points and the set of periodic shadowable points of a homeomorphism on a compact metric space are dense in X. Then we show that a homeomorphism has the periodic shadowing property if and only if so is the restricted map to the set of periodic shadowable points. We also give some examples related to our results.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.2
• /
• pp.104-110
• /
• 2016

Dense local image descriptors like SIFT are fruitful for capturing salient information about image, shown to be successful in various image-related tasks when formed in bag-of-words representation (i.e., histograms). In this paper we consider to utilize these dense local descriptors in the object tracking problem. A notable aspect of our tracker is that instead of adopting a point estimate for the target model, we account for uncertainty in data noise and model incompleteness by maintaining a distribution over plausible candidate models within the Bayesian framework. The target model is also updated adaptively by the principled Bayesian posterior inference, which admits a closed form within our Dirichlet prior modeling. With empirical evaluations on some video datasets, the proposed method is shown to yield more accurate tracking than baseline histogram-based trackers with the same types of features, often being superior to the appearance-based (visual) trackers.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2454-2467
• /
• 2015

Increasing traffic and bandwidth requirements bring challenges to the next generation wireless networks (5G). As one of the main technology in 5G networks, Ultra-Dense Network (UDN) can be used to improve network coverage. In this paper, a radio over fiber based model is proposed to solve the load balancing problem in ultra-dense network. Stochastic differential game is introduced for the load balancing algorithm, and optimal load allocated to each access point (RAP) are formulated as Nash Equilibrium. It is proved that the optimal load can be achieved and the stochastic differential game based scheme is applicable and acceptable. Numerical results are given to prove the effectiveness of the optimal algorithm.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.34 no.6
• /
• pp.441-446
• /
• 2014

A 3D ultrasound image is desired in many medical examinations. However, the implementation of a 2D array, which is needed for a 3D image, is challenging with respect to fabrication, interconnection and cabling. A 2D sparse array, which needs fewer elements than a dense array, is a realistic way to achieve 3D images. Because the number of ways the elements can be placed in an array is extremely large, a method for optimizing the array configuration is needed. Previous research placed the target point far from the transducer array, making it impossible to optimize the array in the operating range. In our study, we focused on optimizing a 2D sparse array transducer for 3D imaging by using a simulated annealing method. We compared the far-field optimization method with the near-field optimization method by analyzing a point-spread function (PSF). The resolution of the optimized sparse array is comparable to that of the dense array.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.12
• /
• pp.561-568
• /
• 2021

In recent years, autonomous driving technologies have become a high-value-added technology that attracts attention in the fields of science and industry. For smooth Self-driving, it is necessary to accurately detect an object and estimate its movement speed in real time. CNN-based deep learning algorithms and conventional dense optical flows have a large consumption time, making it difficult to detect objects and estimate its movement speed in real time. In this paper, using a single camera image, fast object detection was performed using the YOLOv5 algorithm, a deep learning algorithm, and fast estimation of the speed of the object was performed by using a local dense optical flow modified from the existing dense optical flow based on the detected object. Based on this algorithm, we present a system that can predict the collision time and probability, and through this system, we intend to contribute to prevent tram accidents.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.12
• /
• pp.1135-1144
• /
• 2013

Deploying small cells is a reliable and influential solution to handle the skyrocketing traffic increase in the cellular network, and the small cell technology is evolving to ultra-dense network (UDN). In this paper we propose a small cell on/off algorithm with a simple but essential framework composed of access point (AP), user equipment (UE), and small cell controller (SCC). We propose Device-Assisted Networking for Cellular grEening (DANCE) algorithms that save the energy consumption by tying to minimize the number of turned-on APs while maintaining the network throughput. In doing so, SCC firstly gathers the feedback messages from UEs and then makes a decision including a set of turned-on APs and user association. DANCE algorithm has several variations depending on the number of bits of the UE's feedback message (1 bit vs. N bit), and is divided into AP-first, UE-first, or Proximity ON according to the criteria of selecting the turned-on APs. We perform extensive simulations under the realistic UDN environment, and the results confirm that the proposed algorithms, compared to the baseline, can significantly enhance the energy efficiency, e.g., more than a factor of 10.

• Interaction and multiscale mechanics
• /
• v.1 no.4
• /
• pp.437-448
• /
• 2008

This paper examined the stability of high-dense dislocation substructures (HDDSs) associated with martensite laths in High Cr steels supposed to be used for FBR, based on a series of dislocation dynamics (DD) simulations. The DD simulations considered interactions of dislocations with impurity atoms and precipitates which substantially stabilize the structure. For simulating the dissociation processes, a point defect model is developed and implemented into a discrete DD code. Wall structure composed of high dense dislocations with and without small precipitates were artificially constructed in a simulation cell, and the stability/instability conditions of the walls were systematically investigated in the light of experimentally observed coarsening behavior of the precipitates, i.e., stress dependency of the coarsening rate and the effect of external stress. The effect of stress-dependent coarsening of the precipitates together with application of external stress on the subsequent behavior of initially stabilized dislocation structures was examined.

• Tunnel and Underground Space
• /
• v.28 no.4
• /
• pp.343-357
• /
• 2018

Algorithm which can analyze the slope failure behavior utilizing the comprehensive information of the dense point of joint poles and the joint set orientations, both of which are obtained statistically, and the defect pattern of pole distribution has been developed. This method overcomes the potential incorrectness of the hemispheric projection method utilizing the joint set orientations only and also enhances the reliability of slope failure analysis. To this end a method capable of calculating the joint dispersion index directly from the joint pole distribution, instead of contour map, has been devised. The representative orientations for the slope failure analysis has been determined by considering the number and orientations of cone angle-dependent joint sets as well as the joint dispersion index. By engaging these representative orientations to the hemispheric projection analysis more reliable slope failure examination has been carried out. Sensitivity analysis for the potentially unstable slope of plane failure mode has been performed. Significance of joint strength index and the external seismic loading on the slope stability has been fully analyzed.