• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.350-358
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• 2021

In modern years, the performance of the students is analysed with lot of difficulties, which is a very important problem in all the academic institutions. The main idea of this paper is to analyze and evaluate the academic performance of the college students with bipolar disorder by applying data mining classification algorithms using Jupiter Notebook, python tool. This tool has been generally used as a decision-making tool in terms of academic performance of the students. The various classifiers could be logistic regression, random forest classifier gini, random forest classifier entropy, decision tree classifier, K-Neighbours classifier, Ada Boost classifier, Extra Tree Classifier, GaussianNB, BernoulliNB are used. The results of such classification model deals with 13 measures like Accuracy, Precision, Recall, F1 Measure, Sensitivity, Specificity, R Squared, Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, TPR, TNR, FPR and FNR. Therefore, conclusion could be reached that the Decision Tree Classifier is better than that of different algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.437-440
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• 2022

In modern society, the use of the image processing field is increasing rapidly due to the 4th industrial revolution and the development of IoT technology. In particular, edge detection is widely used in various fields as an essential preprocessing process in image processing applications such as image classification and object detection. Conventional methods for detecting an edge include a Sobel edge detection filter, a Roberts edge detection filter, a Prewitt edge detection filter, Laplacian of Gaussian (LoG), and the like. However, existing methods have the disadvantage of showing somewhat insufficient performance of edge detection characteristics in a low-light level environment with low contrast. Therefore, this paper proposes an edge detection algorithm based on contrast analysis to increase edge detection characteristics even in low-light level environments.

• Advances in nano research
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• v.12 no.5
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• pp.529-547
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• 2022

Graphene is one of the strongest, stiffest, and lightest nanoscale materials known to date, making it a potentially viable and attractive candidate for developing lightweight structural composites to prevent high-velocity ballistic impact, as commonly encountered in defense and space sectors. In-plane twist in bilayer graphene has recently revealed unprecedented electronic properties like superconductivity, which has now started attracting the attention for other multi-physical properties of such twisted structures. For example, the latest studies show that twisting can enhance the strength and stiffness of graphene by many folds, which in turn creates a strong rationale for their prospective exploitation in high-velocity impact. The present article investigates the ballistic performance of twisted bilayer graphene (tBLG) nanostructures. We have employed molecular dynamics (MD) simulations, augmented further by coupling gaussian process-based machine learning, for the nanoscale characterization of various tBLG structures with varying relative rotation angle (RRA). Spherical diamond impactors (with a diameter of 25Å) are enforced with high initial velocity (V_i) in the range of 1 km/s to 6.5 km/s to observe the ballistic performance of tBLG nanostructures. The specific penetration energy (E_p^*) of the impacted nanostructures and residual velocity (V_r) of the impactor are considered as the quantities of interest, wherein the effect of stochastic system parameters is computationally captured based on an efficient Gaussian process regression (GPR) based Monte Carlo simulation approach. A data-driven sensitivity analysis is carried out to quantify the relative importance of different critical system parameters. As an integral part of this study, we have deterministically investigated the resonant behaviour of graphene nanostructures, wherein the high-velocity impact is used as the initial actuation mechanism. The comprehensive dynamic investigation of bilayer graphene under the ballistic impact, as presented in this paper including the effect of twisting and random disorder for their prospective exploitation, would lead to the development of improved impact-resistant lightweight materials.

• Journal of Plant Biotechnology
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• v.38 no.2
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• pp.162-168
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• 2011

High salinity is a common stress condition that adversely affects plant growth and crop production. In response to various environmental stresses, plants activate a number of defense genes that function to increase the tolerance. To isolate Arabidopsis genes that are involved in abiotic stress responses, we carried out genetic screening using various mutant lines. Among them, the blh8 ($\b{B}$EL1-$\b{L}$ike $\b{H}$omeodomain $\underline{8}$) mutant specifically shows chlorotic phenotypes to ionic (specifically, $Na^+$ and $K^+$) stresses, but no differences in root growth. In addition, BLH8 is related to plant development and abiotic stress as predicted by a Graphical Gaussian Model (GGM) network program. It implies that BLH8 functions as a putative transcription factor related to abiotic stress responses. Collectively, our results show that gene network analysis is a useful tool for isolating genes involved in stress adaptation in plants.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1184-1192
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• 2004

A real-time pupil detection system that detects the pupil movement from the real-time video data achieved by the visual light camera for general purpose personal computer is proposed. It is implemented with three steps; at first, face region is detected using the Haar-like feature detection scheme, and then eye region is detected within the face region using the template-based scheme. Finally, pupil movement is detected within the eye region by convolution of the horizontal and vertical histogram profiling and Gaussian filter. As results, we obtained more than 90% of the detection rate from 2375 simulation images and the data processing time is about 160㎳, that detects 7 times per second.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.114-123
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• 2002

Called VISTA (Variable-stability In-flight Simulator Test Aircraft), the one-of-a-kind NF-l6D has a simulation system that can mimic several aircraft. Though housed in an F-l6 Fighting Falcon airframe, VISTA can also act like the F-15 Eagle or the Navy's F-14 Tomcat. More importantly, such flexibility allows for improved training and consolidation of some sorties. Consequently USAF Test Pilot School students will have an opportunity to learn how to test future integrated cockpits. In this paper we will use the multiple model adaptive estimation (MMAE) and the multiple model adaptive controller (MMAC) techniques to model the aircraft's flight control system containing the longitudinal and lateral-directional axes. Single and dual actuator and sensor failures will also be included in the simulation. White Gaussian noise will be included to simulate the effects of atmospheric disturbances.

• Proceedings of the KIEE Conference
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• 1995.07c
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• pp.1262-1264
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• 1995

The question-"How fast a electron tunnels a potential barrier?" looks like simple, but is controversy for more than 40 years. Because "tunneling" involves complicated internal processes and its definition is ambiguous. Recent experiments showed that the phase time is the best model of tunneling time among other times-for example, dwell time, Larmor clock time etc. In this paper, we simulated the tunneling time for Gaussian wave packet by program InterQuanta and compared with the phase time. In particular we focused on the effect of wave packet spreading in momentum space(or real space) which is not expressed by the phase time formula.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.558-570
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• 2018

Recently, object detection is a critical function for any system that uses computer vision and is widely used in various fields such as video surveillance and self-driving cars. However, the conventional methods can not detect the objects clearly because of the dynamic background change in the beach. In this paper, we propose a new technique to detect humans correctly in the dynamic videos like shores. A new background modeling method that combines spatial GMM (Gaussian Mixture Model) and temporal GMM is proposed to make more correct background image. Also, the proposed method improve the accuracy of people detection by using SVM (Support Vector Machine) to classify people from the objects and KCF (Kernelized Correlation Filter) Tracker to track people continuously in the complicated environment. The experimental result shows that our method can work well for detection and tracking of objects in videos containing dynamic factors and situations.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.337-339
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• 2004

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.56-58
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• 1996

The Preisach model needs a density function to simulate the hysteresis phenomena. To obtain this function, many experimental data obtained from the first order transition curves are required to get accurate density function. However, it is difficult to perform this procedure, especially for the hard magnetic materials. In this paper, we compare the density function obtained from the experimental data with that computed from the mathematical function like the Gaussian function, and propose a simple technique to get mathematical equation of the density function or Everett function which is obtained from the initial curve, major and minor loop.