• Water Engineering Research
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• v.1 no.2
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• pp.95-105
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• 2000

A method is presented which enables easily the computation of the suspended sediment discharge as the mean sediment concentration and mean flow velocity. This method has significant advantages over the traditional method, which principally depend on a set of measured concentration data. The method is based on both a new sediment concentration and mean sediment concentration equations which have been derived from the entropy concept used in statistical mechanics and information theory: (1) The sediment concentration distribution equations derived, are capable of describing the variation of the concentration in the vertical direction. (2) The mean concentration equation derived, is capable of calculating easily the mean concentration by using only one measured concentration in open channel. The present study mainly addresses the following two subjects : (1) new sediment concentration and mean sediment concentration equations are derived from the entropy concept : (2) An efficient and useful method of suspended sediment-discharge measurements is developed which can facilitate the estimation of suspended sediment-discharge in open channel. Flume and laboratory data are used to carry out the research task outlined above. An efficient method for determining the suspended sediment-discharge in the open channel has been developed. The method presented also is efficient and applicable in estimating the sediment transport in rivers and the sediment deposit in the reservoirs, and can drastically reduce the time and cost of sediment measurements.

• Speech Sciences
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• v.11 no.1
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• pp.7-20
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• 2004

In this paper, we propose a two-step noise compensation algorithm in feature extraction for achieving robust speech recognition. The proposed method frees us from requiring a priori information on noisy environments and is simple to implement. First, in frequency domain, the Harmonics-based Spectral Subtraction (HSS) is applied so that it reduces the additive background noise and makes the shape of harmonics in speech spectrum more pronounced. We then apply a judiciously weighted variance Feature Vector Normalization (FVN) to compensate for both the channel distortion and additive noise. The weighted variance FVN compensates for the variance mismatch in both the speech and the non-speech regions respectively. Representative performance evaluation using Aurora 2 database shows that the proposed method yields 27.18% relative improvement in accuracy under a multi-noise training task and 57.94% relative improvement under a clean training task.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.1-19
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• 2018

Effective internal communication is known to have a positive impact on business performance, but there is a lack of research on the effects of online channels for workplace communication. This study using regression analysis examines how task-technology fit, information richness, self-efficacy, perceived ease of use, and perceived usefulness related to online communication channels affect not only the satisfaction with the tools but also the effectiveness of them. Additionally, we verify how the organizational culture of online and offline communication shows the control effect. As a result, all five variables were positively correlated with internal communication channels satisfaction, and we found that the organizational culture of online and offline communication controls the relationship between online communication channels satisfaction and effectiveness.

• Korean Journal of Child Studies
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• v.36 no.6
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• pp.85-100
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• 2015

This study divided elementary school 6th graders of into a higher academic achievement group (n=19) and a lower academic achievement group (n=19) in order to examine the tendency of left and right hemisphere preferences, characteristics and relationships of learning ability factors by means of EEG. For this purpose, brain waves in performing higher cognitive tasks for 5 min. were measured with a two-channel (Fp1, Fp2) EEG measurement system and hemisphere preference was measured by means of a questionnaire. Our results were as follows. First, hemisphere preference indicated that the higher group showed a left hemisphere tendency and the lower group indicated a right hemisphere tendency. Second, the first learning ability test found that the higher group performed its task rapidly with higher levels of concentration and cognitive strength and lower loading and the lower group conducted its task more slowly with lower levels of concentration and cognitive strength and higher loading. The second test showed that the higher group performed its task rapidly with lower levels of concentration.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.57-75
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• 2015

In evaluating the performance of a dual-hop wireless link, the effects of large and small scale fading has to be considered. To overcome this fading effect, several schemes, such as multiple-input multiple-output (MIMO) with orthogonal space time block codes (OSTBC), different combining schemes at the relay and receiving end, and orthogonal frequency division multiplexing (OFDM) are used in both the transmitting and the relay links. In this paper, we first make compare the performance of a two-hop wireless link under a different combination of space diversity in the first and second hop of the amplify-and-forward (AF) case. Our second task in this paper is to incorporate the weak signal of a direct link and then by applying the channel model of two random variables (one for a direct link and another for a relayed link) we get very impressive result at a low signal-to-noise ratio (SNR) that is comparable with other models at a higher SNR. Our third task is to bring other three schemes under a two-hop wireless link: use of transmit antenna selection (TAS) on both link with weak direct link, distributed Alamouti scheme in two-hop link and single relay antenna with OFDM subcarrier. Finally, all of the schemes mentioned above are compared to select the best possible model. The main finding of the paper is as follows: the use of MIMO on both hops but application TAS on both links with weak direct link and the full rate OFDM with the sub-carrier for an individual link provide a better result as compared to other models.

• Journal of Digital Contents Society
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• v.7 no.1
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• pp.47-52
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• 2006

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 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 n wave is obtained from for 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.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.258-270
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• 2020

A new task of using the Jacobian-Free-Newton-Krylov (JFNK) method for the PWR core transient simulations involving neutronics, thermal hydraulics and mechanics is conducted. For the transient scenario of PWR, normally the Picard iteration of the coupled coarse-mesh nodal equations and parallel channel TH equations is performed to get the transient solution. In order to solve the coupled equations faster and more stable, the Newton Krylov (NK) method based on the explicit matrix was studied. However, the NK method is hard to be extended to the cases with more physics phenomenon coupled, thus the JFNK based iteration scheme is developed for the nodal method and parallel-channel TH method. The local gap conductance is sensitive to the gap width and will influence the temperature distribution in the fuel rod significantly. To further consider the local gap conductance during the transient scenario, a 1D mechanics model is coupled into the JFNK scheme to account for the fuel thermal expansion effect. To improve the efficiency, the physics-based precondition and scaling technique are developed for the JFNK iteration. Numerical tests show good convergence behavior of the iterations and demonstrate the influence of the fuel thermal expansion effect during the rod ejection problems.

• The Journal of Information Systems
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• v.12 no.2
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• pp.21-39
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• 2003

Many people including teachers and students' parents must assist each student who will be a hero of future to develop their potential abilities and acquire various skills. Counseling is a fundamental thing to achieve this goal. But, in reality, it is usually difficult to do counseling which makes it possible to establish desirable self-view and world view expertly and systema tically because of burdensome task of teachers, spatial and time limit and students' extracurri cular activities. Taking advantages of computer networking, this research was designed to solve various problematic situations we can usually face with in school and home, to reduce limitations among three parties: teachers, parents and students, and to keep record continuously on the process and contents of counseling. And, also, this research is focused to web-based counseling network that makes possible to build database system easily adapts to specialty of each schools. Web based counseling system will provide these advantages: 1. Through analyzing and editing which will be done by expert In of accumulated database, to realize more systematic and expert database will be possible. 2. Owing to the physical characteristic of cyber space, counseling will be done any time and anywhere the computer is. 3. Because it is possible to minimize social limitations on physical condition, communication channel and anonymity of cyber space, counseling will be relatively easy to perform. 4. The contents of counseling will be automatically recorded on the database.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.71-77
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• 2015

Currently, numerous (broadcasting) programs are being provided to viewers, which makes it hard for viewers to select a program to watch. Especially, surfing channels watching the program videos (which is the most general manner of searching a program) became a time consuming task of performing several tens of channel changes (a channel change takes about 0.7 second). In the paper, a data service for guiding programs using the multi-view of program videos is proposed. The data service allows viewers to navigate all program videos without channel changes. To implement the data service, a method for composing and transmitting multi-view videos with the meta data for handling each video of the multi-view has been devised and a Java API has been implemented to clip, resize, and display parts of the multi-view videos.