• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.3975-3984
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• 2022

Distributed control system architecture is adopted for I&C systems of Prototype Fast Breeder Reactor, where the geographically distributed control systems are connected to centralized servers & display stations via switched Ethernet networks. TCP/IP communication plays a significant role in the successful operations of this architecture. The communication tasks at control nodes are taken care by TCP/IP offload modules; local area switched network is realized using layer-2/3 switches, which are finally connected to network interfaces of centralized servers & display stations. Safety, security, reliability, and fault tolerance of control systems used for safety-related applications of nuclear power plants is ensured by indigenous design and qualification as per guidelines laid down by regulatory authorities. In the case of commercially available components, appropriate suitability analysis is required for getting the operation clearances from regulatory authorities. This paper details the proposed approach for the suitability analysis of TCP/IP communication nodes, including control systems at the field, network switches, and servers/display stations. Development of test platform using commercially available tools and diagnostics software engineered for control nodes/display stations are described. Each TCP link behavior with impaired packets and multiple traffic loads is described, followed by benchmarking of the network switch's routing characteristics and security features.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2075-2082
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• 2006

This paper presents modeling and optimization techniques for hish efficiency solar cell process on single-crystalline float zone (FZ) wafers. Among a sequence of multiple steps of fabrication, the followings are the most sensitive steps for the contact formation: 1) Emitter formation by diffusion; 2) Anti-reflection-coating (ARC) with silicon nitride using plasma-enhanced chemical vapor deposition (PECVD); 3) Screen-printing for front and back metalization; and 4) Contact formation by firing. In order to increase the performance of solar cells in terms of efficiency, the contact formation process is modeled and optimized using neural networks and genetic algorithms, respectively. This paper utilizes the design of experiments (DOE) in contact formation to reduce process time and fabrication costs. The experiments were designed by using central composite design which consists of 24 factorial design augmented by 8 axial points with three center points. After contact formation process, the efficiency of the fabricated solar cell is modeled using neural networks. Established efficiency model is then used for the analysis of the process characteristics and process optimization for more efficient solar cell fabrication.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.82-91
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• 2018

Objectives: Synchronous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has been used to explore sleep stage dependent functional brain networks. Despite a growing number of sleep studies using EEG-fMRI, few studies have conducted network analysis on whole night sleep due to difficulty in data acquisition, artifacts, and sleep management within the MRI scanner. Methods: In order to perform network analysis for whole night sleep, we proposed experimental procedures and data processing techniques for EEG-fMRI. We acquired 6-7 hours of EEG-fMRI data per participant and conducted signal processing to reduce artifacts in both EEG and fMRI. We then generated a functional brain atlas with 68 brain regions using independent component analysis of sleep fMRI data. Using this functional atlas, we constructed sleep level dependent functional brain networks. Results: When we evaluated functional connectivity distribution, sleep showed significantly reduced functional connectivity for the whole brain compared to that during wakefulness. REM sleep showed statistically different connectivity patterns compared to non-REM sleep in sleep-related subcortical brain circuits. Conclusion: This study suggests the feasibility of exploring functional brain networks using sleep EEG-fMRI for whole night sleep via appropriate experimental procedures and signal processing techniques for fMRI and EEG.

• Journal of the Korean Chemical Society
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• v.18 no.2
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• pp.97-109
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• 1974

The crystal and molecular structure of sulfaguanidine monohydrate, $C_7H_{10}N_4O_2S{\cdot}H_2O$, was determined from visually estimated intensity data from Weissenberg photographs. The crystal data are monoclinic, space group $P2_1$/c with four molecules in a unit cell of dimensions, ${\alpha}=7.57{\pm}0.03,\;b=5.44{\pm}0.02,\;c=24.76{\pm}0.06{\AA},\;{\beta}=91.0{\pm}0.2^{\circ}$. The structure has been solved by an interpretation of a Patterson map and with a help of a direct procedure on a projection. The parameters were refined isotropically by block-diagonal least-squares methods using 1542 observed independent reflections to give R = 0.14. By hydrogen bonding a guanidyl nitrogen of a sulfaguanidine molecule is linked to the sulfonyl oxygens of the other molecules indirectly through two different water molecules. The role of water molecule is both a donor and an acceptor in hydrogen-bonding formation and these hydrogen bonds are tetrahedrally oriented. The hydrogen-bonding networks form infinite molecular layers parallel to (001) plane.

• Analytical Science and Technology
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• v.18 no.5
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• pp.381-385
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• 2005

The title compound, $\{H_2NCH_2CH_2NH_2CH_2CH_2\}\{Cu(H_2O)_6\}(SO_4)_2$, I, has been synthesized under solvo/hydrothermal conditions and their crystal structure analyzed by X-ray single crystallography. Compound I crystallizes in the monoclinic system, $P2_1/n$ space group with a = 6.852(1), b = 10.160(2), $c=11.893(1){\AA}$, ${\beta}=92.928(8)^{\circ}$, $V=826.9(2){\AA}^3$, Z = 2, $D_x=1.815g/cm^3$, $R_1=0.031$ and ${\omega}R_2=0.084$. The crystal structure of the piperazine templated Cu(II)-sulfate demonstrate zero-dimensional compound constituted by doubly protonated piperazine cations, hexahydrated copper cations and sulfate anions. The central Cu atom has a elongated octahedral coordination geometry. The crystal structure is stabilized by three-dimensional networks of the intermolecular $O_{water}-H{\cdots}O_{sulfate}$ and $N_{pip}-H{\cdots}O_{sulfate}$ hydrogen bonds between the water molecules and sulfate anions and protonated piperazine cations. Based on the results of thermal analysis, the thermal decomposition reaction of compound I was analyzed to have three distinctive stages.

• Imaging Science in Dentistry
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• v.50 no.3
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• pp.237-243
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• 2020

Purpose: The aim of this study was to evaluate the clinical efficacy of a Tanner-Whitehouse 3 (TW3)-based fully automated bone age assessment system on hand-wrist radiographs of Korean children and adolescents. Materials and Methods: Hand-wrist radiographs of 80 subjects (40 boys and 40 girls, 7-15 years of age) were collected. The clinical efficacy was evaluated by comparing the bone ages that were determined using the system with those from the reference standard produced by 2 oral and maxillofacial radiologists. Comparisons were conducted using the paired t-test and simple regression analysis. Results: The bone ages estimated with this bone age assessment system were not significantly different from those obtained with the reference standard (P>0.05) and satisfied the equivalence criterion of 0.6 years within the 95% confidence interval (-0.07 to 0.22), demonstrating excellent performance of the system. Similarly, in the comparisons of gender subgroups, no significant difference in bone age between the values produced by the system and the reference standard was observed (P>0.05 for both boys and girls). The determination coefficients obtained via regression analysis were 0.962, 0.945, and 0.952 for boys, girls, and overall, respectively (P=0.000); hence, the radiologist-determined bone ages and the system-determined bone ages were strongly correlated. Conclusion: This TW3-based system can be effectively used for bone age assessment based on hand-wrist radiographs of Korean children and adolescents.

• Analytical Science and Technology
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• v.21 no.6
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• pp.562-568
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• 2008

A novel two-dimensional cadmium(II)-nickel(II) bimetallic host clathrate, $[Cd{NH_2CH_2CH_2OH}_2Ni(CN)_4]{\cdot}3C_6H_5NH_2{\cdot}H_2O$, 1, has been synthesized and structurally characterized by X-ray single crystallographic method. The clathrate 1 crystallizes in the monoclinic system, space group $P2_1/c$ with a = 14.370(3), b = 7.728(1), c = 28.172(4) ${\AA}$, ${\beta}=97.58(1)^{\circ}$, V = 3101.1(9) ${\AA}^3$, Z = 4. The host framework of the clathrate 1 is built of the cyanide bridges between octahedral Cd(II) atom and square planar Ni(II) atom. The octahedral Cd atoms ligated by two 2-aminoethanol molecules and four cyanide ligands bridged with square planar Ni atoms. The Ni atoms bridges to four Cd atoms via cyanides is made up of puckered quadrangles of composition $\{CdNi(CN)_2\}_2$, all edges are shared. This cyanide bridges form an infinite two-dimensional host networks stacking along b axis. 2-Aminoethanol ligands bond to Cd atom through N atom as a monodentate ligand in the axial position and four cyanides take an equatorial plane with all in trans-configurations. The aniline guest molecules and water molecules are located in between the host layer sheets, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.602-608
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• 2011

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. The NN for the online feedback-error learning can composed that the input layer consists of six units for the inputs $x_i$, i=1~6, the hidden layer consists of two hidden units for hidden outputs $o_j$, j=1~2, and the output layer consists of two units for the outputs ${\tau}_k$, k=1~2. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels. The initial q value was set to [0, 5, ${\pi}$].

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.12a
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• pp.121-129
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• 1999

When continuous media are transmitted over the communication networks, asynchrony which can not maintain temporal relationships among packets may occur due to a random transit delay. There exist two types of synchronization schemes ; for guaranteed or non-guaranteed resource networks. The former which applies a resource reservation technique maintains delay characteristics, however, the latter supply a best-effort service. In this paper, I propose a intra-media synchronization scheme to transmit continuous media on general networks not guaranteeing a bounded delay tome. The scheme controls transmission times of the packets by estimating next delay time with the delay distribution. So, the arriving packets may be maintained within a limited delay boundary, and playout will be performed after buffering to smoothen small delay variations. The continually increasing delay due to network overload causes buffer underflow at the receiver. To solve it, the transmitter is required to speed up instantaneously. Too much increase of transmission-rate may cause network congestion. At that time, the transmitter drops the current packet when informed excessive delay from the receiver.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1164-1174
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• 2020

Purpose To evaluate a deep learning model to predict recurrence of thyroid tumor using preoperative ultrasonography (US). Materials and Methods We included representative images from 229 US-based patients (male:female = 42:187; mean age, 49.6 years) who had been diagnosed with thyroid cancer on preoperative US and subsequently underwent thyroid surgery. After selecting each representative transverse or longitudinal US image, we created a data set from the resulting database of 898 images after augmentation. The Python 2.7.6 and Keras 2.1.5 framework for neural networks were used for deep learning with a convolutional neural network. We compared the clinical and histological features between patients with and without recurrence. The predictive performance of the deep learning model between groups was evaluated using receiver operating characteristic (ROC) analysis, and the area under the ROC curve served as a summary of the prognostic performance of the deep learning model to predict recurrent thyroid cancer. Results Tumor recurrence was noted in 49 (21.4%) among the 229 patients. Tumor size and multifocality varied significantly between the groups with and without recurrence (p < 0.05). The overall mean area under the curve (AUC) value of the deep learning model for prediction of recurrent thyroid cancer was 0.9 ± 0.06. The mean AUC value was 0.87 ± 0.03 in macrocarcinoma and 0.79 ± 0.16 in microcarcinoma. Conclusion A deep learning model for analysis of US images of thyroid cancer showed the possibility of predicting recurrence of thyroid cancer.