• Geophysics and Geophysical Exploration
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• v.10 no.2
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• pp.124-130
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• 2007

Least squares ($l^2$ norm) solutions of seismic inversion tend to be very sensitive to data points with large errors. The $l^1$ norm minimization gives more robust solutions, but usually with higher computational cost. Iteratively reweighted least squares (IRLS) method gives efficient approximate solutions of these $l^1$ norm problems. I propose an efficient implementation of the IRLS method for a hybrid $l^1/l^2$ minimization problem that behaves as $l^2$ norm fit for small residual and $l^1$ norm fit for large residuals. The proposed algorithm shows more robust characteristics to the decision of the threshold value than the l1 norm IRLS inversion does with respect to the threshold value to avoid singularity.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.2
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• pp.71-82
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• 1984

A programme, called BIPOLE, for the numerical analysis of twotimensional n-p-n bipolar transistors was developed. It has included the SRH and Auger recolnbination processes, the mobility dependence on the impurity density and the electric field, and the band-gap narrowing effect. The finite difference equations of the fundamental semiconductor equations are formulated using Newton's method for Poisson's equation and the divergence theorem for the hole and electron continuity equations without physical restrictions. The matrix of the linearized equations is sparse, symmetric M-matrix. For the solution of the linearized equations ICCG method and Gummel's algorithm have been employed. The programme BIPOLE has been applied to various kinds of the steady-state problems of n-p-n transistors. For the examples of applications the variations of common emitter current gain, emitter and diffusion capacitances, and input and output characteristics are calculated. Three-dimensional representations of some D.C. physical quantities such as potential and charge carrier distributions were displayed. This programme will be used for the nome,rical analysis of the distortion phenom ana of two-dimensional n-p-n transistors. The BIPOLE programme is available for everyone.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.64-73
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• 2011

The problem of Euclidean minimum spanning tree (EMST) is to connect given nodes in a plane with minimum cost. There are many algorithms for the polynomial time problem as EMST. However, for numerous nodes, the algorithms consume an enormous amount of time to find an optimal solution. In this paper, an approximation scheme using a polynomial time approximation scheme (PTAS) algorithm with dividing and parallel processing for the problem is suggested. This scheme enables to construct a large, approximate EMST within a short duration. Although initially devised for the non-polynomial problem, we employ naive PTAS to construct a vast EMST with dynamic programming. In an experiment, the approximate EMST constructed by the proposed scheme with 15,000 input terminal nodes and 16 partition cells shows 89% and 99% saving in execution time for the serial processing and parallel processing methods, respectively. Therefore, our scheme can be applied to obtain an approximate EMST quickly for numerous input terminal nodes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.2 s.314
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• pp.1-10
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• 2007

Branch prediction accuracy is critical for the overall system performance. Branch miss-prediction penalty is the one of the significant performance limiters for improving processor performance, as the pipeline deepens and the instruction issued per cycle increases. In this paper, we propose "Dynamic Per-Branch History Length Fitting Method" by tracking the data dependencies among the register writing instructions. The proposed solution first identifies the key branches, and then it selectively uses the histories of the key branches. To support this mechanism, we provide a history length adjustment algorithm and a required hardware module. As the result of simulation, the proposed mechanism outperforms the previous fixed static method, up to 5.96% in prediction accuracy. Furthermore, our method introduces the performance improvement, compared to the profiled results which are generally considered as the optimal ones.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.90-97
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• 2017

Nowadays, the most of commercial buildings are build-out with complex architecture and decorated with more complicated interiors of buildings so establishing intelligible escape routes becomes an important case of fire or other emergency in a limited time. The commercial buildings are already equipped with multiple exit signs and these exit signs may create confusion and leads the people into different directions under emergency. This can jeopardize the emergency situation into a chaotic state, especially in a complex layout buildings. There are many research focused on implementing different approached to improve the exit sign system with better visual navigating effects, such as the use of laser beams, the combination of audio and video cues, etc. However the digital signage system based emergency exit sign management is one of the best solution to guide people under emergency situations to escape. This research paper, propose an intelligent evacuation route GUIDE that uses the combination centralized Wireless Sensor Networks (WSN) and digital signage for people safety and avoids dangers from emergency conditions. This proposed system applies WSN to detect the environment condition in the building and uses an evacuation algorithm to estimate the safe route to escape using the sensor information and then activates the signage system to display the safe evacuation route instruction GUIDE according to the location the signage system is installed. This paper presented the prototype of the proposed signage system and execution time to find the route with future research directions. The proposed system provides a natural intelligent evacuation route interface for self or remote operation in facility management to efficiently GUIDE people to the safe exit under emergency conditions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.905-915
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• 2007

This paper proposes a filter-based algorithm to adaptively adjust the contention window in IEEE 802.11 DCF. The proposed mechanism is focused on the general and realistic environments that have various conditions regarding to noise, media types and network load. For this flexible adaptation, Filter-based DCF(FDCF) takes a more realistic policy such as median filter concept in the image processing technologies. We can handle these various environments by adjusting the contention window size according to the result of filtering based on history-buffer. We can ignore temporarily and randomly occurred transmission failures due to noise errors and collisions in noisy environments. In addition, by changing the reference number and history-buffer size, FDCF can be extended as a general solution including previous proposed mechanism. We have confirmed that the proposed mechanism can achieve the better performance than those of previous researches in aspects of the throughput and the delay in the realistic environments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.7
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• pp.734-743
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• 2010

In this paper, we analyzed the EMP coupling for the nonuniform transmission lines, such as twisted cables, using the chain matrix algorithm and the multi-conductor analysis. The BLT method is widely used for the EMP coupling analysis of the transmission line, however, it is difficult to apply to the nonuniform transmission lines. In order to analyze the EMP coupling of nonuniform transmission lines, the whole nonuniform transmission line is divided into incremental uniform line sections of the finite numbers, and the coupling in each small sections is now summed up to get the EMP coupling effect of the entire nonuniform transmission line. To verify the proposed EMP coupling analysis method, the result of the EMP coupling simulation is compared with the solution of BLT equations for a uniform transmission line case. The proposed method is applied to the twisted cable over ground in case of being illuminated by the HEMP in order to analyze the EMP coupling.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1253-1262
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• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.839-850
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• 2014

As the social and financial damages caused by APT attack such as 3.20 cyber terror are increased, the technical solution against APT attack is required. It is, however, difficult to protect APT attack with existing security equipments because the attack use a zero-day malware persistingly. In this paper, we propose a host based anomaly detection method to overcome the limitation of the conventional signature-based intrusion detection system. First, we defined 39 features to identify between normal and abnormal behavior, and then collected 8.7 million feature data set that are occurred during running both malware and normal executable file. Further, each process is represented as 83-dimensional vector that profiles the frequency of appearance of features. the vector also includes the frequency of features generated in the child processes of each process. Therefore, it is possible to represent the whole behavior information of the process while the process is running. In the experimental results which is applying C4.5 decision tree algorithm, we have confirmed 2.0% and 5.8% for the false positive and the false negative, respectively.