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Institution

Pusan National University

EducationBusan, South Korea
About: Pusan National University is a education organization based out in Busan, South Korea. It is known for research contribution in the topics: Population & Catalysis. The organization has 24124 authors who have published 45054 publications receiving 819356 citations. The organization is also known as: Busan National University & Pusan University.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the intrinsic epoxy groups on the graphene were utilized for reaction with stearic acid to minimize the negative impact of the normal functionalization method on the π-electronic system of graphene.
Abstract: Graphene, prepared by the thermal reduction of graphite oxide (GO), was modified with stearic acid to enhance its lipophilicity. A novel method, using the intrinsic epoxy groups on the graphene, was utilized for reaction with stearic acid to minimize the negative impact of the normal functionalization method on the π-electronic system of graphene. Gravimetric analysis, thermogravimetric analysis (TGA), Fourier transform infrared (FTIR) spectroscopy, and X-ray photoelectron spectroscopy (XPS) showed that the stearic acid was effectively attached to the graphene. In addition, Raman spectroscopy and electric conductivity of the graphene showed that this novel modification method, utilizing intrinsic defects, did not damage the π-electronic system of the sp2 bonded carbons. The dispersion of graphene in a low density polyethylene (LDPE) matrix was enhanced; consequently, the reinforcing effect in tensile testing was improved by the lipophilic modification. The crystallization behavior observed by differential...

186 citations

Journal ArticleDOI
TL;DR: A botnet detection system based on a two-level deep learning framework for semantically discriminating botnets and legitimate behaviors at the application layer of the domain name system (DNS) services is proposed.
Abstract: Internet of Things applications for smart cities have currently become a primary target for advanced persistent threats of botnets. This article proposes a botnet detection system based on a two-level deep learning framework for semantically discriminating botnets and legitimate behaviors at the application layer of the domain name system (DNS) services. In the first level of the framework, the similarity measures of DNS queries are estimated using siamese networks based on a predefined threshold for selecting the most frequent DNS information across Ethernet connections. In the second level of the framework, a domain generation algorithm based on deep learning architectures is suggested for categorizing normal and abnormal domain names. The framework is highly scalable on a commodity hardware server due to its potential design of analyzing DNS data. The proposed framework was evaluated using two datasets and was compared with recent deep learning models. Various visualization methods were also employed to understand the characteristics of the dataset and to visualize the embedding features. The experimental results revealed substantial improvements in terms of F 1-score, speed of detection, and false alarm rate.

185 citations

Journal ArticleDOI
TL;DR: A new funnel variable is defined so that the funnel virtual control forces the tracking error to fall within funnel boundary, and adaptive FESN method is also proposed to improve the approximation performance in conventional neural network algorithms.
Abstract: This paper presents a funnel dynamic surface control combined with fuzzy echo state networks (FESNs) for the prescribed tracking performance of a strict feedback multi-input-multi-output (MIMO) nonlinear dynamic system. A new funnel variable is defined so that the funnel virtual control forces the tracking error to fall within funnel boundary, and adaptive FESN method is also proposed to improve the approximation performance in conventional neural network algorithms. A strict feedback controller and adaptive laws for estimating the uncertainties were derived using the recursive steps of dynamic surface control based on the Lyapunov stability theory. Lyapunov stability analysis confirmed the boundedness and convergence of the closed-loop system. The performance of the proposed control scheme was validated by simulations and experimental applications to the tracking control of a MIMO nonlinear system and a robot manipulator.

185 citations

Journal ArticleDOI
TL;DR: Findings support a role for GRIP in the synaptic anchoring of AMPA receptors but also suggest that GRIP has additional functions unrelated to the binding of AMpa receptors.
Abstract: The NMDA and AMPA classes of ionotropic glutamate receptors are concentrated at postsynaptic sites in excitatory synapses. NMDA receptors interact via their NR2 subunits with PSD-95/SAP90 family proteins, whereas AMPA receptors bind via their GluR2/3 subunits to glutamate receptor-interacting protein (GRIP), AMPA receptor-binding protein (ABP), and protein interacting with C kinase 1 (PICK1). We report here a novel cDNA (termed ABP-L/GRIP2) that is virtually identical to ABP except for additional GRIP-like sequences at the N-terminal and C-terminal ends. Like GRIP (which we now term GRIP1), ABP-L/GRIP2 contains a seventh PDZ domain at its C terminus. Using antibodies that recognize both these proteins, we examined the subcellular localization of GRIP1 and ABP-L/GRIP2 (collectively termed GRIP) and their biochemical association with AMPA receptors. Immunogold electron microscopy revealed the presence of GRIP at excitatory synapses and also at nonsynaptic membranes and within intracellular compartments. The association of native GRIP and AMPA receptors was confirmed biochemically by coimmunoprecipitation from rat brain extracts. A majority of detergent-extractable GluR2/3 was complexed with GRIP in the brain. However, only approximately half of GRIP was associated with AMPA receptors. Unexpectedly, immunocytochemistry of cultured hippocampal neurons and rat brain at the light microscopic level showed enrichment of GRIP in GABAergic neurons and in GABAergic nerve terminals. Thus GRIP is associated with inhibitory as well as excitatory synapses. Collectively, these findings support a role for GRIP in the synaptic anchoring of AMPA receptors but also suggest that GRIP has additional functions unrelated to the binding of AMPA receptors.

185 citations

Journal ArticleDOI
TL;DR: The illustrated figures would serve as a suitable guide to understand how ANOVA determines the mean difference problems by using between and within group variance differences.
Abstract: Analysis of variance (ANOVA) is one of the most frequently used statistical methods in medical research. The need for ANOVA arises from the error of alpha level inflation, which increases Type 1 error probability (false positive) and is caused by multiple comparisons. ANOVA uses the statistic F, which is the ratio of between and within group variances. The main interest of analysis is focused on the differences of group means; however, ANOVA focuses on the difference of variances. The illustrated figures would serve as a suitable guide to understand how ANOVA determines the mean difference problems by using between and within group variance differences.

185 citations


Authors

Showing all 24296 results

NameH-indexPapersCitations
Hyun-Chul Kim1764076183227
Taeghwan Hyeon13956375814
George C. Schatz137115594910
Darwin J. Prockop12857687066
Mark A. Ratner12796868132
Csaba Szabó12395861791
David E. McClelland10760272881
Yong Sik Ok10285441532
C. M. Mow-Lowry10137866659
I. K. Yoo10143732681
Haijun Yang10040335114
Buddy D. Ratner9950135660
Dong Jo Kim9849736272
Shuzhi Sam Ge9788340865
B. J. J. Slagmolen9634962356
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202391
2022302
20213,260
20203,069
20193,039
20182,718