• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.47-55
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• 2011

Hemorrhagic shock is a cause of one third of death resulting from injury in the world. Early diagnosis of hemorrhagic shock makes it possible for physician to treat successfully. The objective of this paper was to select an optimal classifier model using physiological signals from rats measured during hemorrhagic experiment. This data set was used to train and predict survival rate using artificial neural network (ANN) and support vector machine (SVM). To avoid over-fitting, we chose the best classifier according to performance measured by a 10-fold cross validation method. As a result, we selected ANN having three hidden nodes with one hidden layer and SVM with Gaussian kernel function as trained prediction model, and the ANN showed 88.9 % of sensitivity, 96.7 % of specificity, 92.0 % of accuracy and the SVM provided 97.8 % of sensitivity, 95.0 % of specificity, 96.7 % of accuracy. Therefore, SVM was better than ANN for survival prediction.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.51-61
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• 2002

In this dissertation, We demonstrated the Travel Time forecasting model in the freeway of multi-section with regard of drives' attitude. Recently, the forecasted travel time that is furnished based on expected travel time data and advanced experiment isn't being able to reflect the time-lag phenomenon specially in case of long distance trip, so drivers don't believe any more forecasted travel time. And that's why the effects of ATIS(Advanced Traveler Information System) are reduced. Therefore, in this dissertation to forecast the travel time of the freeway of multi-section reflecting the time-lag phenomenon & the delay of tollgate, we used traffic volume data & TCS data that are collected by Korea Highway Cooperation. Also keep the data of mixed unusual to applicate real system. The applied model for forecasting is consisted of feed-forward structure which has three input units & two output units and the back-propagation is utilized as studying method. Furthermore, the optimal alternative was chosen through the twelve alternative ideas which is composed of the unit number of hidden-layer & repeating number which affect studying speed & forecasting capability. In order to compare the forecasting capability of developed ANN model. the algorithm which are currently used as an information source for freeway travel time. During the comparison with reference model, MSE, MARE, MAE & T-test were executed, as the result, the model which utilized the artificial neural network performed more superior forecasting capability among the comparison index. Moreover, the calculated through the particularity of data structure which was used in this experiment.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.431-440
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• 2018

In this study, authors predicted probability of resignation of newly employed nurses using TensorFlow, an open source software library for numerical computation and machine learning developed by Google, and suggested strategic human resources management plan. Data of 1,018 nurses who resigned between 2010 and 2017 in single university hospital were collected. After the order of data were randomly shuffled, 80% of total data were used for machine leaning and the remaining data were used for testing purpose. We utilized multiple neural network with one input layer, one output layer and 3 hidden layers. The machine-learning algorithm correctly predicted for 88.7% of resignation of nursing staff with in one year of employment and 79.8% of that within 3 years of employment. Most of resigned nurses were in their late 20s and 30s. Leading causes of resignation were marriage, childbirth, childcare and personal affairs. However, the most common cause of resignation of nursing staff with in one year of employment were maladaptation to the work and problems in interpersonal relationship.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.49-58
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• 2005

In this paper, we proposed a blind watermarking algerian to use characteristics of a scalar quantizer which is the recommended in the JPEG2000 and JPEG. The proposed algorithm shifts a quantization index according to the value of each watermark bit to prevent losing the watermark information during the compression by quantization. Therefore, the watermark is embedded during the process of quantization, not an additional process for watermarking, and is adaptively applied as a assigned quantizer according application areas. Before embedding process, a LFSR(Linear feedback shift register) rearranged the watermark for the security of the watermark itself and in the embedding process, a LFSR is used to hide the watermarking positions. Therefore the embedded watermark can he extracted by only the owner who knows the initial value of LFSR without the original image. The visual recognizable pattern such as a binary image was used as the watermark. The experimental results showed that the proposed algerian satisfies the robustness and imperceptibility corresponding to the major requirement of watermarking. The results showed the largest error rate to be $5.7\%$ for attack. The experimental result which compares the proposed algorithm with the Mohamed algorithm showed that the proposed algorithm was better than it, exactly $4\~5$ times for the attacks of JPEG and JPEG2000.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.325-337
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• 2007

Illegal slash-and-bum fields and slash-and-bum farmers in Korea had increased in spite of Japanese Joseon Government's strong regulations and clearance measures, and land reform after the 1945 Liberation of Korea until 1970s. This study is to inquire into the necessary and sufficient conditions to disappear entirely the matters from 1974 to 1979 that illegal slash-and-bum fields and slash-and-burn farmers continued long in existence until the early 1970s. The findings are as follows; Firstly, the population pressure to agricultural lands that main factor of generation of illegal slash-and-bum fields had decreased rapidly because the rural populations and less income farmers have decreased after 1967. Especially, the decrease of the rural populations had never seen to the 1970s. It is recognised that the social condition for the success in 1970s. Secondly, the continuous economic growth from the early 1960s enabled the Korean government to solve the matter through the sufficient financial investment from the Government. For example, the gross national product (GNP) and the government budget in 1974 increased around 25 times after 1960. It is recognised that the economic condition for the success in 1970s. Finally, it was enabled to remove the concealment from the slash-and-bum farmers and to monitor illegal re-cultivation thoroughly because the development of forest inventory technique using an aerial photograph and the expansion of road facilities. It is recognised that the technical condition for the success in the 1970s.

• Korean Journal of Cognitive Science
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• v.7 no.1
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• pp.57-74
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• 1996

This paper presents a comparison of recognition performance of the features used inthe recent handwritten korean character recognition.This research aims at providing the basis for feature selecion in order to improve not only the recognition rate but also the efficiency of recognition system.For the comparison of feature performace,we analyzed the characteristics of theose features and then,classified them into three rypes:global feature(image transformation)type,statistical feature type,and local/ topological feature type.For each type,we selected four or five features which seem more suitable to represent the characteristics of korean alphabet,and performed recongition experiments for the first consonant,horizontal vowel,and vertical vowel of a korean character, respectively.The classifier used in our experiments is a multi-layered perceptron with one hidden layer which is trained with backpropagation algorithm.The training and test data in the experiment are taken from 30sets of PE92. Experimental results show that 1)local/topological features outperform the other two type features in terms of recognition rates 2)mesh and projection features in statical feature type,walsh and DCT features in global feature type,and gradient and concavity features in local/topological feature type outperform the others in each type, respectively.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.896-904
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• 2004

In this paper, We present an efficient variable rate speech coder for spectral efficiency and packet processing technique for packet loss compensation of a voice codec with 10msec frame in VoIP service. Through disconnecting the users from the spectral resource during silence interval of about 60% period, a variable rate voice coder based on a voice activity detection(VAD) can increase spectral gain by two times. The performance of the method was analyzed by variation of detected voice activity factor and degraded speech frame ratio under various background noise level, and compared those of G.729B of ITU-T 8kbps standard speech codec. A method to compensate lost packets utilized addition of recovery data to a main stream and error concealment scheme for speech quality enhancement, the performance is verified by reconstructed speech quality. The proposed scheme can achieve spectral gain by two times or enhance speech quality by 3dB through reserved bandwidth of VAD. Therefore, the proposed method can enhance a spectral efficiency or speech quality of VoIP.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.577-590
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• 2013

Shamir's (k,n)-threshold secret sharing scheme is not secure against cheating by attacker because the signature of participants is omitted. To prevent cheating, many schemes have been proposed, and a proactive secret sharing is one of those. The proactive secret sharing is a method to update shares in the secret sharing scheme at irregular intervals. In this paper, a proactive image secret sharing scheme over $GF(2^8)$ is proposed for the first time. For the past 30 years, Galois field operation is widely used in order to perform the efficient and secure bit operation in cryptography, and the proposed scheme with update phase of shadow image over $GF(2^8)$) at irregular intervals provides the lossless and non-compromising of secret image. To evaluate security and efficiency of images (i.e. cover and shadow images) distortion between the proposed scheme and the previous schemes, embedding capacity and PSNR are compared in experiments. The experimental results show that the performances of the embedding capacity and image distortion ratio of the proposed scheme are superior to the previous schemes.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.35-44
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• 2000

In this paper, we propose a new trajectory model for characterizing segmental features and their interaction based upon a general framework of hidden Markov models. Each segment, a sequence of vectors, is represented by a trajectory of observed sequences. This trajectory is obtained by applying a new design matrix which includes transitional information on contiguous frames, and is characterized as a polynomial regression function. To apply the trajectory to the segmental HMM, the frame features are replaced with the trajectory of a given segment. We also propose the likelihood of a given segment and the estimation of trajectory parameters. The obervation probability of a given segment is represented as the relation between the segment likelihood and the estimation error of the trajectories. The estimation error of a trajectory is considered as the weight of the likelihood of a given segment in a state. This weight represents the probability of how well the corresponding trajectory characterize the segment. The proposed model can be regarded as a generalization of a conventional HMM and a parametric trajectory model. The experimental results are reported on the TIMIT corpus and performance is show to improve significantly over that of the conventional HMM.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.74-82
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• 2016

In this paper, a new automatic speech recognition (ASR) was proposed where ultrasonic doppler signals were used, instead of conventional speech signals. The proposed method has the advantages over the conventional speech/non-speech-based ASR including robustness against acoustic noises and user comfortability associated with usage of the non-contact sensor. In the method proposed herein, 40 kHz ultrasonic signal was radiated toward to the mouth and the reflected ultrasonic signals were then received. Frequency shift caused by the doppler effects was used to implement ASR. The proposed method employed multi-channel ultrasonic signals acquired from the various locations, which is different from the previous method where single channel ultrasonic signal was employed. The PCA(Principal Component Analysis) coefficients were used as the features of ASR in which hidden markov model (HMM) with left-right model was adopted. To verify the feasibility of the proposed ASR, the speech recognition experiment was carried out the 60 Korean isolated words obtained from the six speakers. Moreover, the experiment results showed that the overall word recognition rates were comparable with the conventional speech-based ASR methods and the performance of the proposed method was superior to the conventional signal channel ASR method. Especially, the average recognition rate of 90 % was maintained under the noise environments.