• Korean Journal of Materials Research
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• v.21 no.5
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• pp.273-276
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• 2011

Ultraviolet (UV) light emitting diodes (LEDs) were grown on a patterned n-type GaN substrate (PNS) with 200 nm silicon-di-oxide (SiO2) nano pattern diameter to improve the light output efficiency of the diodes. Wet etched self assembled indium tin oxide (ITO) nano clusters serve as a dry etching mask for converting the SiO2 layer grown on the n-GaN template into SiO2 nano patterns by inductively coupled plasma etching. PNS is obtained by n-GaN regrowth on the SiO2 nano patterns and UV-LEDs were fabricated using PNS as a template. Two UV-LEDs, a reference LED without PNS and a 200 nm PNS UV-LEDs were fabricated. Scanning Electron microscopy (SEM), Transmission Electron Microscopy (TEM), X-Ray Diffraction (XRD), Photoluminescence (PL) and Light output intensity- Input current- Voltage (L-I-V) characteristics were used to evaluate the ITO-$SiO_2$ nanopattern surface morphology, threading dislocation propagation, PNS crystalline property, PNS optical property and UVLED device performance respectively. The light out put intensity was enhanced by 1.6times@100mA for the LED grown on PNS compared to the reference LED with out PNS.

• Atmosphere
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• v.17 no.1
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• pp.87-99
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• 2007

Simulation results of Asian Dust Aerosol Model (ADAM) for the period of April 7-9, 2006 were analyzed, comparing with observed PM10 data. ADAM simulated around ten times lower than on-site PM10 concentration in the source regions: Zhurihe, Tongliao, Yushe, Dalian and Huimin. As the result of this low concentration, transported amounts of Asian Dust were under-estimated as well. In order to quantify a forecasting accuracy, Bias and RMSE were calculated. Even though remarkably negative Biases and high RMSEs were observed, ADAM simulation had followed well up the time of dust outbreak and a transported path. However, the emission process to generate dust from source regions requires a great enhancement. The PM10 concentration at the surface reached up to $2,300{\mu}gm^{-3}$ at Baeknyoungdo and Seoul (Mt. Gwanak), up to $1,750{\mu}gm^{-3}$ at KGAWO about 18:00 LST in April 8, respectively; however, ADAM did not simulate the same result on its second peak. It is considered that traveling Asian dust might have been lagged over the Korean peninsula by the blocking of surface high pressure. Moreover, the current RDAPS's 30 km grid resolution (which ADAM adopts as the meteorological input data) might not adequately represent small-scale atmospheric motions below planetary boundary layer.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.723-735
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• 2020

This study is reported the adhesion failure in adhesive bonded composite and specifically for the T-joint structure. Three-dimensional finite element analysis has been performed using a commercial tool and the necessary outcomes are obtained via an eight noded solid element (Solid 185-element) from the library of ANSYS. The structural analysis input has been incurred through ANSYS parametric design language (APDL) code. The normal and shear stress distributions along different layers of the joint structure have been evaluated as the final outcomes. Based on the stress distributions, failure location in the composite joint structure has been identified by using the Tsai-Wu stress failure criterion. It has been found that the failure index is maximum at the interface between flange and web part of the joint (top layer) which indicates the probable location of failure initiation. This kind of failures are considered as adhesion failure and the failure propagation is governed by strain energy release rate (SERR) of fracture mechanics. The different adhesion failure lengths are also considered at the failure location to calculate the SERR values i.e. mode I fracture (opening), mode II fracture (sliding) and mode III fracture (tearing) along the failure front. Also, virtual crack closure technique (VCCT) principle of fracture mechanics steps is used to calculate the above said SERRs. It is found that the mode I SERR is more dominating compared to other two modes of failure for the joint considered. Finally, the influences of various parametric (geometrical and material) effect on SERR of the joint structure are evaluated and discussed in details.

• Environmental Engineering Research
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• v.21 no.4
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• pp.333-340
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• 2016

An Artificial Neural Network including a Radial Basis Function (RBF) and a Time Delay Neural Network (TDNN) was used to predict total dissolved solid (TDS) in the river Zayanderud. Water quality parameters in the river for ten years, 2001-2010, were prepared from data monitored by the Isfahan Regional Water Authority. A factor analysis was applied to select the inputs of water quality parameters, which obtained total hardness, bicarbonate, chloride and calcium. Input data to the neural networks were pH, $Na^+$, $Mg^{2+}$, Carbonate ($CO{_3}^{-2}$), $HCO{_3}^{-1}$, $Cl^-$, $Ca^{2+}$ and Total hardness. For learning process 5-fold cross validation were applied. In the best situation, the TDNN contained 2 hidden layers of 15 neurons in each of the layers and the RBF had one hidden layer with 100 neurons. The Mean Squared Error and the Mean Bias Error for the TDNN during the training process were 0.0006 and 0.0603 and for the RBF neural network the mentioned errors were 0.0001 and 0.0006, respectively. In the RBF, the coefficient of determination ($R^2$) and the index of agreement (IA) between the observed data and predicted data were 0.997 and 0.999, respectively. In the TDNN, the $R^2$ and the IA between the actual and predicted data were 0.957 and 0.985, respectively. The results of sensitivity illustrated that $Ca^{2+}$ and $SO{_4}^{2-}$ parameters had the highest effect on the TDS prediction.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.48-53
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• 2001

In this paper, selectively attentive learning method has been proposed to improve the learning speed of multilayer Perceptron based on the error backpropagation algorithm. Three attention criterions are introduced to effectively determine which set of input patterns is or which portion of network is attended to for effective learning. Such criterions are based on the mean square error function of the output layer and class-selective relevance of the hidden nodes. The acceleration of learning time is achieved by lowering the computational cost per iteration. Effectiveness of the proposed method is demonstrated in a speaker adaptation task of isolated word recognition system. The experimental results show that the proposed selective attention technique can reduce the learning time more than 60% in an average sense.

• The Korean Journal of Physiology and Pharmacology
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• v.8 no.6
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• pp.295-300
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• 2004

Serotonin (5-hydroxytroptamine, 5-HT) has been shown to affect the induction of long-term potentiation (LTP) in the cortex such as the hippocampus, the visual cortex and the prefrontal cortex. Fluoxetine, as a selective serotonin reuptake inhibitor, is used in the management of a wide variety of psychological diseases. To study the effect of fluoxetine on the induction of LTP, we recorded the field potential in layer II/III of the frontal cortex from 3-wk-old. LTP was induced in horizontal input by theta burst stimulation (TBS). TBS with two-folds intensity of the test stimulation induced LTP, which was blocked by application of D-AP5 $(50 {\mu}M)$, an NMDA receptor antagonist. Whereas bath application of 5-HT $(10 {\mu}M)$ inhibited the induction of LTP, treatment with the 5-HT depleting agent, para-chloroamphetamine $(PCA,\;10{\mu}M)$, for 2hr did not affect the induction of LTP. Bath application of fluoxetine (1, 3, and $10 {\mu}M)$ suppressed the induction of LTP in concentration-dependent manner, however, fluoxetine did not inhibit the induction of LTP in 5-HT-depleted slices. These results indicate that fluoxetine may inhibit the induction of LTP by modulating serotonergic mechanism in the rat frontal cortex.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.723-731
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• 2016

A core technological base to provide enhanced data rates required by 5G mobile wireless communications is the improved bandwidth efficiency using massive multiple-input multiple-output (MIMO) transmission. MIMO transmission requires the channel estimation using the channel state information reference signaling (CSI-RS) and appropriate beamforming, thus the design of the codebook defining proper beamforming vectors is an important issue. In this paper, we propose a multi-rank codebook based on the discrete Fourier transform (DFT) matrix, by utilizing statistical properties of the channel generated by the spatial channel model (SCM). The proposed method includes a structural change of the precoding matrix indicator (PMI) by considering the phase difference distributions between adjacent antenna elements, as well as the selected codevector characteristics of each transmission layer. Performance gain of the proposed method is evaluated and verified by making the performance comparison to the 3GPP standard codebooks adopted by Long-Term Evolution (LTE) systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.87-91
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• 2005

The cascade-correlation (CC) learning algorithm of Fahlman and Lebiere is one of the most influential constructive algorithm in a neural network. Cascading the hidden neurons results in a network that can represent very strong nonlinearities. Although this power is in principle useful, it can be a disadvantage if such strong nonlinearity is not required to solve the problem. 3 models are presented and compared empirically. All of them are based on valiants of the cascade architecture and output neurons weights training of the CC algorithm. Empirical results indicate the followings： (1) In the pattern classification, the model that train only new hidden neuron to output layer connection weights shows the best predictive ability; (2) In the function approximation, the model that removed input-output connection and used sigmoid-linear activation function is better predictability than CasCor algorithm.

• ETRI Journal
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• v.21 no.4
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• pp.52-64
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• 1999

QoS monitoring is a kind of real-time systems which allows each level of the system to track the ongoing QoS levels achieved by the lower network layers. For these systems, real-time communications between corresponding transport protocol objects is essential for their correct behavior. When two or more entities are employed to perform a certain task as in the case of communication protocols, the capability to do so is called interoperability and considered as the essential aspect of correctness of communication systems. This paper describes a formal approach on modeling and interoperability test case generation of a real-time QoS monitoring protocol. For this, we specify the behavior of flow monitoring of transport layer QoS protocol, i.e., METS protocol, which is proposed to address QoS from an end-to-end's point of view, based on QoS architecture model which includes ATM net work in lower layers. We use a real-time Input/Output finite State Machine to model the behavior of real-time flow monitoring over time. From the modeled real-time I/OFSM, we generate interoperability test cases to check the correctness of METS protocol's flow monitoring behaviors for two end systems. A new approach to efficient interoperability testing is described and the method of interoperability test cases generation is shown with the example of METS protocol's flow monitoring. The current TTCN is not appropriate for testing real-time and multimedia systems. Because test events in TTCN are for message-based system and not for stream-based systems, the real-time in TTCN can only be approximated. This paper also proposes the notation of real-time Abstract Test Suite by means of real-time extension of TTCN. This approach gives the advantages that only a few syntactical changes are necessary, and TTCN and real-time TTCN are compatible. This formal approach on interoperability testing can be applied to the real-time protocols related to IMT-2000, B-ISDN and real-time systems.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.506-514
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• 2016

In this study, HEVC over DVB-T2 systems with a bandwidth of 6 MHz is considered, particularly for the terrestrial 4K-UHDTV broadcasting service in the Republic of Korea. The threshold of visibility carrier-to-noise power ratio (ToV C/N) and the receiver minimum required input level (sensitivity) for satisfying the subjective picture failure (SPF) condition are measured in the laboratory. It is observed, for transmitting 26.37 Mbps data stream correctly, that ToV C/N is 18.8 dB on average, and the receiver sensitivity is varied from minimum -84.2 dBm to maximum -80.0 dBm. Based on the results, the receiver noise floor is calculated by -100 dBm on average.