• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.235-242
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• 2008

To improve video quality and coding efficiency, H.264/AVC adopted an adaptive rate control. But this method has a problem as it cannot predict an accurate quantization parameter(QP) for the first frame. The first QP is decided among four constant values by using encoder input parameters. It does not consider encoding bits, results in significant fluctuation of the image quality and decreases the average quality of the whole coded sequence. In this paper, we propose a new algorithm for the first frame QP decision in the H.264/AVC encoder. The QP is decided by the existing algorithm and the first frame is encoded. According to the encoded bits, the new initial QP is decided. We can predict optimal value because there is a linear relationship between encoded bits and the new initial QP. Next, we re-encode the first frame using the new initial QP. Experimental results show that the proposed algorithm not only achieves better quality than the state of the art algorithm, but also adopts a rate control forthe sequence that was impossible with the existing algorithm. By reducing fluctuation, subjective quality also improved.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.351-360
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• 2018

Human emotion recognition is a research topic that is receiving continuous attention in computer vision and artificial intelligence domains. This paper proposes a method for classifying human emotions through multiple neural networks based on multi-modal signals which consist of image, landmark, and audio in a wild environment. The proposed method has the following features. First, the learning performance of the image-based network is greatly improved by employing both multi-task learning and semi-supervised learning using the spatio-temporal characteristic of videos. Second, a model for converting 1-dimensional (1D) landmark information of face into two-dimensional (2D) images, is newly proposed, and a CNN-LSTM network based on the model is proposed for better emotion recognition. Third, based on an observation that audio signals are often very effective for specific emotions, we propose an audio deep learning mechanism robust to the specific emotions. Finally, so-called emotion adaptive fusion is applied to enable synergy of multiple networks. The proposed network improves emotion classification performance by appropriately integrating existing supervised learning and semi-supervised learning networks. In the fifth attempt on the given test set in the EmotiW2017 challenge, the proposed method achieved a classification accuracy of 57.12%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.329-335
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• 2018

Satellite images, which are widely used in various applications, are very useful for monitoring the surface of the earth. Since satellite data is obtained from a remote sensor, it contains a lot of noise and errors depending on observation weather conditions during data acquisition and sensor malfunction status. Since the accuracy of the data affects the accuracy and reliability of the data analysis results, noise removal and data restoration for high quality data is important. In this study, we propose a reconstruction system that models the time dependent dynamic characteristics of satellite data using a multi-period harmonic model and performs adaptive data restoration considering the spatial correlation of data. The proposed method is a real-time restoration method and thus can be employed as a preprocessing algorithm for real-time reconstruction of satellite data. The proposed method was evaluated with both simulated data and MODIS NDVI data for six years from 2011 to 2016. Experimental results show that the proposed method has the potentiality for reconstructing high quality satellite data.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.144-153
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• 2009

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.79-87
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• 2018

The purpose of this study was to investigate the relationships among psychological, emotional variables related to the career indecision of college students and to present effective action strategies by searching basic data that can prevent college students from undeciding their career path. In this study, we analyzed the relationship between the variables related to career indecision of college students and the structural equation model to verify the fit of the research model. The results of this study suggest that adaptive perfectionism has a positive effect on career decision self-efficacy and career decision self-efficacy has a negative effect on career indecision and adaptive perfectionism has a negative effect on career indecision by mediating career decision self-efficacy. In addition, maladaptive perfectionism has a negative effect on career decision self-efficacy, and it has a positive effect on career indecision through mediation of career decision self-efficacy. we discussed the implications for career decision making and employment of college students based on the results of the relationship between variables such as perfectionism, career decision self-efficacy, and career indecision.

• Earthquakes and Structures
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• v.11 no.6
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• pp.1101-1121
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• 2016

Base isolation, one of the popular seismic protection approaches proven to be effective in practical applications, has been widely applied worldwide during the past few decades. As the techniques mature, it has been recognised that, the biggest issue faced in base isolation technique is the challenge of great base displacement demand, which leads to the potential of overturning of the structure, instability and permanent damage of the isolators. Meanwhile, drain, ventilation and regular maintenance at the base isolation level are quite difficult and rather time- and fund- consuming, especially in the highly populated areas. To address these challenges, a number of efforts have been dedicated to propose new isolation systems, including segmental building, additional storey isolation (ASI) and mid-storey isolation system, etc. However, such techniques have their own flaws, among which whipping effect is the most obvious one. Moreover, due to their inherent passive nature, all these techniques, including traditional base isolation system, show incapability to cope with the unpredictable and diverse nature of earthquakes. The solution for the aforementioned challenge is to develop an innovative vibration isolation system to realise variable structural stiffness to maximise the adaptability and controllability of the system. Recently, advances on the development of an adaptive magneto-rheological elastomer (MRE) vibration isolator has enlightened the development of adaptive base isolation systems due to its ability to alter stiffness by changing applied electrical current. In this study, an innovative semi-active storey isolation system inserting such novel MRE isolators between each floor is proposed. The stiffness of each level in the proposed isolation system can thus be changed according to characteristics of the MRE isolators. Non-dominated sorting genetic algorithm type II (NSGA-II) with dynamic crowding distance (DCD) is utilised for the optimisation of the parameters at isolation level in the system. Extensive comparative simulation studies have been conducted using 5-storey benchmark model to evaluate the performance of the proposed isolation system under different earthquake excitations. Simulation results compare the seismic responses of bare building, building with passive controlled MRE base isolation system, building with passive-controlled MRE storey isolation system and building with optimised storey isolation system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.405-414
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• 2011

The adaptive network-based fuzzy inference system (ANFIS) which had a success for time series prediction and system control was applied for modeling the hourly runoff in the Gapcheon watershed. The ANFIS used the antecedent rainfall and runoff as the input. The ANFIS was trained by varying the various simulation factors such as mean areal rainfall estimation, the number of input variables, the type of membership function and the number of membership function. The root mean square error (RMSE), mean peak runoff error (PE), and mean peak time error (TE) were used for validating the ANFIS simulation. The ANFIS predicted runoff was in good agreement with the measured runoff and the applicability of ANFIS for modelling the hourly runoff appeared to be good. The forecasting ability of ANFIS up to the maximum 8 lead hour was investigated by applying the different input structure to ANFIS model. The accuracy of ANFIS for predicting the hourly runoff was reduced as the forecasting lead hours increased. The long-term predictability of ANFIS for forecasting the hourly runoff at longer lead hours appeared to be limited. The ANFIS might be useful for modeling the hourly runoff and has an advantage over the physically based models because the model construction of ANFIS based on only input and output data is relatively simple.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1183-1191
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• 2010

In this paper, I propose an adaptive OFDM CP length algorithm for in PLC systems for smart grid. The proposed scheme calculates the channel delay information at the CP controller of the receiver by taking correlation between a received data frame and the following delayed one. The CP controller, immediately, feeds back the channel delay information to the transmitter. Then, the transmitter adapts CP length for next data frame. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of packet data rate, cumulative packet data rate, and bit error rate (BER). The simulation results showed data gain (which is the amount of the reduced bits) gets larger as the number of packets increase, but the amount of data gain reduced as the number of branches ($N_{br}$) increase. In respects of BER for the cases $N_{br}$ is 3, 4, and 5, performance of the adaptive CP length algorithm and the fixed CP scheme are similar. Therefore, it is confirmed the proposed scheme achieved data rate increment without BER performance reduction compared to the conventional fixed CP length scheme.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.395-408
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• 2020

This paper aims to develop and apply three different machine learning approaches (i.e., artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and wavelet-based neural networks (WNN)) combined with an evolutionary optimization algorithm and the k-fold cross validation for multi-step (days) streamflow forecasting at the catchment located in Algeria, North Africa. The ANN and ANFIS models yielded similar performances, based on four different statistical indices (i.e., root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), correlation coefficient (R), and peak flow criteria (PFC)) for training and testing phases. The values of RMSE and PFC for the WNN model (e.g., RMSE = 8.590 ㎥/sec, PFC = 0.252 for (t+1) day, testing phase) were lower than those of ANN (e.g., RMSE = 19.120 ㎥/sec, PFC = 0.446 for (t+1) day, testing phase) and ANFIS (e.g., RMSE = 18.520 ㎥/sec, PFC = 0.444 for (t+1) day, testing phase) models, while the values of NSE and R for WNN model were higher than those of ANNs and ANFIS models. Therefore, the new approach can be a robust tool for multi-step (days) streamflow forecasting in the Seybous River, Algeria.

• Journal of Korean Academy of Nursing
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• v.9 no.2
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• pp.49-61
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• 1979

A review of this literature and discussions reveal a development of ideas concerning the elements of nursing models. The elements of a nursing model are the nurses view of the human being, nursing's goal, and nursing activities. It has long been recognized that human beings, at one time or another, require nursing care. Varieties of literature were reviewed in regard to the human being as recipient of nursing care through the theory development in nursing. Florence Nightingale initiated the modern era of nursing and described more clearly man as the recipient of nursing care. She looked at man as responding to the laws of nature whether the person was healthy or sick. Henderson added to Nightingale's concept of man , the recipient of nursing care by emphasizing that man is a whole, complete, and independent being. Her view is further specified by her enumeration of the activities the human being must perform. Johnson has developed a very comprehensive view of man as the recipient of nursing care. Man is a behavioral system which has a tendency to achieve and maintain stability in patterns of functioning. Like Nightingale, Johnson sees that similar patterns occur in both health and illness. Johnson postulates that the whole behavioral system of the human is composed of eight sub-systems: affiliative, achievement, aggressive, dependency, eliminative, ingestive, restorative, sexual. Roger's main contribution to the development of nursing models was her emphasis upon unitary man. She pointed out that man is a unified whole, possessing his own integrity and manifesting characteristics that“are more than and different from the sum of his parts.”Rogers focuses on the life processes of the human and points out that these processes have the following characteristics. Wholeness, openness, unidirectionality, pattern and organization, sentence, and thought. According to Roy, man is a biopsychosocial being in constant interaction with a changing environment. To cope with this changing environment, man has certain innate and acquired mechanisms. Man's ability to respond positively or to adapt, depends upon the degree of the change taking place and the state of the person coping with the change. When she analyzes man as an adaptive organism she further describes man as being composed of four adaptive modes: physiological needs, self-concept, role function, and interdependence. Based on the literary review through the theory development in nursing, general approach by a unified nursing model to a view of the recipient of nursing care may be stated as follows: Man is a unified whole composed of subsystems with a flexible and normal line of defense; his internal regulating mechanisms help him to cope with a changing environment; he functions by the principles of homeodynamics.