• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.177-184
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• 2001

For two kinds of the multi-stage centrifugal pump with diffuser vanes and return channel vanes the meanline performance prediction is applied to get information of hydraulic performance at each internal flow station, because only flange-to-flange test curves are available. As a first step of redesign fur higher efficiency, the impeller geometry is numerically investigated in the present study. Quasi-3D inviscid loading distributions are obtained, for the two impellers, using the state-of-the-art method of impeller 3D design, which provides a guide to optimal redesign. Full 3D turbulent flow fields are thereafter analyzed, using the specialized CFD code, to confirm the redesign results. The inherent limitation of the traditional graphic method of impeller design, which most of domestic pump manufacturers are now employing, is found.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.118-129
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• 2013

In this study, we intend to identify key financial variables that can accurately classify Green IT leaders against Green IT followers. In particular, we build and compare single and meta-classifiers to identify the relationship between environmental performance and financial performance, while focusing on selecting and interpreting a final prediction model with a smaller set of financial performance indicators. Our experimental results demonstrate that several key variables representing the size, financial resources, operational efficiency, and risk-taking tendency of an organization can successfully identify Green IT leaders with approximately 90% of accuracy. In addition, we find that Green IT leaders show a higher utilization rate of Web pages as a green marketing channel than Green IT followers while they share common layouts of Web publication to build green IT brands with some differences.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.342-351
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• 2000

The paper is concerned about the discovery of new physics of the old oriental philosophy of the yin-Yang '||'&'||' five elements. the physical properties of Five Elements are defined, similarly as in thermodynamics, as five different characteristic state in a cyclic system of nature or a human body. Wood is defined as "warm and soft", Fire as "hot and dispersive", Earth as "agglomerating and sticky", Metal as "tensile and crystallizing", and Water as "cool and slippery" state, respectively. Based on the physics of Five Elements and Qi channel theory, five different constitution classification s are made according to the shape of human face, such as long, inverse triangle, circle, square, and triangle geometry, respectively.Since the constitution implies the relative size or strength of 5 major organs, this theory can be applies successfully to the prediction of the susceptibility to specific diseases as well as the analyses of personal character such as emotion and sensibility. The specific character is analyzed with four different aspects; that is, the first and second are caused by the positive and negative side of the strongest organ, the third character by determined the weakest organ, and finally the fourth by the abnormal psychology due to serious illness.bnormal psychology due to serious illness.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.374-379
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• 2004

This paper proposes an algorithm for human sensibility evaluation using 4-channel EEG signals of the prefrontal and the parietal lobes. The algorithm uses an artificial neural network and the multiple templates. The linear prediction coefficients are used as the feature parameters of human sensibility. Comfortableness for chairs and temperature/humidity are evaluated. Many conventional researches have emphasized that a wave of left prefrontal lobe is activated in case of positive sensibility and that of right prefrontal lobe is activated in case of negative sensibility. So the power ratio of a wave is obtained from FFT computation and the results are compared. The results of the comfortableness evaluation for temperature and humidity showed that the outputs of the proposed algorithm coincided with corresponding sensibilities depending on the task of the temperature and the humidity. The . conventional method using a wave is hardly related with comfortableness. And it is also observed that the uncomfortable state due to the high temperature and humidity can be easily changed to the comfortable state by small drop of the temperature and the humidity. It seems to be good results to get 66.7％ of evaluation performance in spite of using EEG and the subject independent approach.

• Nuclear Engineering and Technology
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• v.35 no.5
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• pp.426-441
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• 2003

A reactor inlet header break experiment, B9401, performed in the RD-14M multi channel test facility was analyzed using RELAP5/MOD3.2 and RELAP5/CANDU[1]. The RELAP5 has been developed for the use in the analysis of the transient behavior of the pressurized water reactor. A recent study showed that the RELAP5 could be feasible even for the simulation of the thermal hydraulic behavior of CANDU reactors. However, some deficiencies in the prediction of fuel sheath temperature and transient behavior in athe headers were identified in the RELAP5 assessments. The RELAP5/CANDU has been developing to resolve the deficiencies in the RELAP5 and to improve the predictability of the thermal-hydraulic behaviors of the CANDU reactors. In the RELAP5/CANDU, critical heat flux model, horizontal flow regime map, heat transfer model in horizontal channel, etc. were modified or added to the RELAP5/MOD3.2. This study aims to identify the applicability of both codes, in particular, in the multi-channel simulation of the CANDU reactors. The RELAP5/MOD3.2 and the RELAP5/CANDU analyses demonstrate the code's capability to predict reasonably the major phenomena occurred during the transient. The thermal-hydraulic behaviors of both codes are almost identical, however, the RELAP5/CANDU predicts better the heater sheath temperature than the RELAP5/MOD3.2. Pressure differences between headers govern the flow characteristics through the heated sections, particularly after the ECI. In determining header pressure, there are many uncertainties arisen from the complicated effects including steady state pressure distribution. Therefore, it would be concluded that further works are required to reduce these uncertainties, and consequently predict appropriately thermal-hydraulic behaviors in the reactor coolant system during LOCA analyses.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.11
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• pp.59-68
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• 2010

In this paper, we present a new method to complete Dynamic Spectrum Access by modifying the reward function. Partially Observable Markov Decision Process (POMDP) is an eligible algorithm to predict the upcoming spectrum opportunity. In POMDP, Reward function is the last portion and very important for prediction. However, the Reward function has only two states (Busy and Idle). When collision happens in the channel, reward function indicates busy state which is responsible for the throughput decreasing of secondary user. In this paper, we focus the difference between busy and collision state. We have proposed a new algorithm for reward function that indicates an additional state of collision which brings better communication opportunity for secondary users. Secondary users properly utilize opportunities to access Primary User channels for efficient data transmission with the help of the new reward function. We have derived mathematical belief vector of the new algorithm as well. Simulation results have corroborated the superior performance of improved reward function. The new algorithm has increased the throughput for secondary user in cognitive radio network.

• Bulletin of the Korean Chemical Society
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• v.18 no.12
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• pp.1274-1280
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• 1997

The photodissociation dynamics of CH2I2 has been studied at 304 nm by state-selective photofragment translational spectroscopy. Velocity distributions, anisotropy parameters, and relative quantum yields are obtained for the ground I(2P3/2) and spin-orbit excited state I*(2P1/2) iodine atoms, which are produced from photodissociation of CH2I2 at this wavelength. These processes are found to occur via B1 ← A1 type electronic transitions. The quantum yield of I*(2P1/2) is determined to be 0.25, indicating that the formation of ground state iodine is clearly the favored dissociation channel in the 304 nm wavelength region. From the angular distribution of dissociation products, the anisotropy parameters are determined to be β(I)=0.4 for the I(2P3/2) and β(I*)=0.55 for the I*(2P1/2) which substantially differ from the limiting value of 1.13. The positive values of anisotropy parameter, however, show that the primary processes for I and I* formation channels proceed dominantly via a transition which is parallel to I-I axis. The above results are interpreted in terms of dual path formation of iodine atoms from two different excited states, i.e., a direct and an indirect dissociation via curve crossing between these states. The translational energy distributions of recoil fragments reveal that a large fraction of the available energy goes into the internal excitation of the CH2I photofragment; < Eint > /Eavl=0.80 and 0.82 for the I and I* formation channels, respectively. The quantitative analysis for the energy partitioning of available energy into the photofragments is used to compare the experimental results with the prediction of direct impulsive model for photodissociation dynamics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5800-5818
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• 2018

Interference may occur when several co-located wireless body area networks (WBANs) share the same channel simultaneously, which is compressed by resource scheduling generally. In this paper, a QoS-aware Adaptive Coloring (QAC) scheduling algorithm is proposed, which contains two components: interference sets determination and time slots assignment. The highlight of QAC is to determine the interference graph based on the relay scheme and adapted to the network QoS by multi-coloring approach. However, the frequent resource assignment brings in extra energy consumption and packet loss. Thus we come up with a launch condition for the QAC scheduling algorithm, that is if the interference duration is longer than a threshold predetermined, time slots rescheduling is activated. Furthermore, based on the relative distance and moving speed between WBANs, a prediction model for interference duration is proposed. The simulation results show that compared with the state-of-the-art approaches, the QAC scheduling algorithm has better performance in terms of network capacity, average delay and resource utility.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.11-14
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• 2018

The aim of this study is to rectify the misclassified image features and enhance the performance of image classification tasks by incorporating a channel- coding technique, widely used in telecommunication. Specifically, the proposed algorithm employs the error - correcting mechanism of convolutional coding combined with the convolutional neural networks (CNNs) that are the state - of- the- arts image classifier s. We develop an encoder and a decoder to employ the error - correcting capability of the convolutional coding. In the encoder, the label values of the image data are converted to convolutional codes that are used as target outputs of the CNN, and the network is trained to minimize the Euclidean distance between the target output codes and the actual output codes. In order to correct misclassified features, the outputs of the network are decoded through the trellis structure with Viterbi algorithm before determining the final prediction. This paper demonstrates that the proposed architecture advances the performance of the neural networks compared to the traditional one- hot encoding method.

• ETRI Journal
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• v.44 no.4
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• pp.672-685
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• 2022

This article proposes a subject-independent application of brain-computer interfacing (BCI). A 32-channel Electroencephalography (EEG) device is used to measure imagined speech (SI) of four words (sos, stop, medicine, washroom) and one phrase (come-here) across 13 subjects. A deep long short-term memory (LSTM) network has been adopted to recognize the above signals in seven EEG frequency bands individually in nine major regions of the brain. The results show a maximum accuracy of 73.56% and a network prediction time (NPT) of 0.14 s which are superior to other state-of-the-art techniques in the literature. Our analysis reveals that the alpha band can recognize SI better than other EEG frequencies. To reinforce our findings, the above work has been compared by models based on the gated recurrent unit (GRU), convolutional neural network (CNN), and six conventional classifiers. The results show that the LSTM model has 46.86% more average accuracy in the alpha band and 74.54% less average NPT than CNN. The maximum accuracy of GRU was 8.34% less than the LSTM network. Deep networks performed better than traditional classifiers.