• Progress in Medical Physics
• /
• v.9 no.1
• /
• pp.47-53
• /
• 1998

Nuclear Medicine Images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. Anatomical structures useful in the interpretation of SPECT /PET Images were radiolabelled. PET/SPECT Images Provide functional information, whereas MRI mainly demonstrate morphology and anatomical. Fusion or Image Registration improves the information obtained by correlating images from various modalities. Brain Scan were studied on one or more occations using MRI and SPECT. The data were aligned using a point pair methods and surface matching. SPECT and MR Images was tested using a three dimensional water fillable Hoffman Brain Phantom with small marker and PET and MR Image was tested using a patient data. Registration of SPECT and MR Images is feasible and allows more accurate anatomic assessment of sites of abnormal uptake in radiolabeled studies. Point based registration was accurate and easily implemented three dimensional registration of multimodality data set for fusion of clinical anatomic and functional imaging modalities. Accuracy of a surface matching algorithm and homologous feature pair matching for three dimensional image registration of Single Photon Emission Computed Tomography Emission Computed Tomography (SPECT), Positron Emission Tomography (PET) and Magnetic Resonance Images(MRD was tested using a three dimensional water fill able brain phantom and Patients data. Transformation parameter for translation and scaling were determined by homologous feature point pair to match each SPECT and PET scan with MR images.

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.1
• /
• pp.8-14
• /
• 2002

In this paper, we realized a real-time text-independent speaker recognition system using gaussian mixture model, and applied frame level likelihood normalization method which shows its effects in verification system. The system has three parts as front-end, training, recognition. In front-end part, cepstral mean normalization and silence removal method were applied to consider speaker's speaking variations. In training, gaussian mixture model was used for speaker's acoustic feature modeling, and maximum likelihood estimation was used for GMM parameter optimization. In recognition, likelihood score was calculated with speaker models and test data at frame level. As test sentences, we used text-independent sentences. ETRI 445 and KLE 452 database were used for training and test, and cepstrum coefficient and regressive coefficient were used as feature parameters. The experiment results show that the frame-level likelihood method's recognition result is higher than conventional method's, independently the number of registered speakers.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.239-246
• /
• 2023

In this paper, we propose an open-loop algorithm to classify speech and music signals using the spectral flux parameters and Mel Frequency Cepstral Coefficients(MFCC) parameters for the audio coder. To increase responsiveness, the MFCC was used as a short-term feature parameter and spectral fluxes were used as a long-term feature parameters to improve accuracy. The overall voice/music signal classification decision is made by combining the short-term classification method and the long-term classification method. The Gaussian Mixed Model (GMM) was used for pattern recognition and the optimal GMM parameters were extracted using the Expectation Maximization (EM) algorithm. The proposed long-term and short-term combined speech/music signal classification method showed an average classification error rate of 1.5% on various audio sound sources, and improved the classification error rate by 0.9% compared to the short-term single classification method and 0.6% compared to the long-term single classification method. The proposed speech/music signal classification method was able to improve the classification error rate performance by 9.1% in percussion music signals with attacks and 5.8% in voice signals compared to the Unified Speech Audio Coding (USAC) audio classification method.

• Journal of Korea Water Resources Association
• /
• v.49 no.5
• /
• pp.411-422
• /
• 2016

Rainfall-runoff modeling in conjunction with rainfall frequency analysis has been widely used for estimating design floods in South Korea. However, uncertainties associated with underlying distribution and sampling error have not been properly addressed. This study applied a Bayesian method to quantify the uncertainties in the rainfall frequency analysis along with Gumbel distribution. For a purpose of comparison, a probability weighted moment (PWM) was employed to estimate confidence interval. The uncertainties associated with design rainfalls were quantitatively assessed using both Bayesian and PWM methods. The results showed that the uncertainty ranges with PWM are larger than those with Bayesian approach. In addition, the Bayesian approach was able to effectively represent asymmetric feature of underlying distribution; whereas the PWM resulted in symmetric confidence interval due to the normal approximation. The use of long period data provided better results leading to the reduction of uncertainty in both methods, and the Bayesian approach showed better performance in terms of the reduction of the uncertainty.

• Journal of Radiation Protection and Research
• /
• v.43 no.1
• /
• pp.29-38
• /
• 2018

Background: Radon contributing about 42% of annual average dose, mainly comes from soil. In this paper, standard measurement procedures for soil radon exhalation rate are suggested and their measurement uncertainties are analyzed. Materials and Methods: We used accumulation method for estimating surface exhalation rate. The closed-loop measurement system was made up with a RAD7 detector and a surface chamber. Radon activity concentrations in the system were observed as a function of time, with data collection of 5 and 15-minute and the measurement time of 4 hours. Linear and exponential fittings were used to obtain radon exhalation rates from observed data. Standard deviations of measurement uncertainties for two approaches were estimated using usual propagation rules. Results and Discussion: The exhalation rates (E) from linear approach, with 30 minutes measurement time were $44.8-48.6mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.14-2.32atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with relative measurement uncertainty of about 10%. The contributions of fitting parameter A, volume (V) and surface (S) to the estimated measurement uncertainty of E were 59.8%, 30.1% and 10.1%, in average respectively. In exponential fitting, at 3-hour measurement we had E ranged of $51.6-69.2mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.46-3.30atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with about 15% relative uncertainty. Fitting with 4-hour measurement resulted E about $51.3-68.2mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.45-3.25atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with 10% relative uncertainty. The uncertainty contributions in exponential approach were 75.1%, 13.4%, 8.7%, and 2.9% for total decay constant k, fitting parameter B, V, and S, respectively. Conclusion: In obtaining exhalation rates, the linear approach is easy to apply, but by saturation feature of radon concentrations, the slope tends to decrease away from the expected slope for extended measurement time. For linear approach, measurement time of 1-hour or less was suggested. For exponential approach, the obtained exhalation rates showed similar values for any measurement time, but measurement time of 3-hour or more was suggested for about 10% relative uncertainty.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.4
• /
• pp.51-62
• /
• 2012

According to the Lighthill and Whitham's shock wave model, a shock wave exists even in a homogeneous speed condition. They referred this wave as unobservable- analogous to a radio wave that cannot be seen. Recent research has attempted to identify how such a counterintuitive conclusion results from the Lighthill and Whitham's shock wave model, and derive a new asymptotical shock wave model. The asymptotical model showed that the shock wave in a homogenous speed traffic stream is identical to the ambient vehicle speed. Thus, no radio wave-like shock wave exists. However, performance tests of the asymptotical model using numerical values have not yet been performed. We investigated the new asymptotical model by examining the implications of the new model, and tested it using numerical values based on a test scenario. Our investigation showed that the only difference between both models is in the third term of the equations, and that this difference has a crucial role in the model output. Incorporation of model parameter${\alpha}$ is another distinctive feature of the asymptotical model. This parameter makes the asymptotical model more flexible. In addition, due to various choices of ${\alpha}$ values, model calibration to accommodate various traffic flow situations is achievable. In Lighthill and Whitham's model, this is not possible. Our numerical test results showed that the new model yields significantly different outputs: the predicted shock wave speeds of the asymptotical model tend to lean toward the downstream direction in most cases compared to the shock wave speeds of Lighthill and Whitham's model for the same test environment. Statistical tests of significance also indicate that the outputs of the new model are significantly different than the corresponding outputs of Lighthill and Whitham's model.

• Korean Journal of Human Ecology
• /
• v.19 no.2
• /
• pp.375-387
• /
• 2010

The Technology Acceptance Model (TAM) presented by Davis (1989) has been regarded as highly explanatory as well as the clearest model in explaining consumers' adoption of innovative technology or products. Existing studies have expanded the model by adding related external variables to improve the explanation depending on the type of innovative technology. This study expanded TAM by adding two more variables, namely consumers' technology innovation and clothing involvement considering the feature of smart clothing. The objectives of this study are as follows: 1. to suggest the extended TAM in explaining the adoption process of smart clothing, 2. to verify the differences in the path hypotheses according to the type of smart clothing. A total of 815 effective samples were collected from adults over 20 years old, and AMOS 5.0 package was employed for data analysis. As a result, it was proved that the extended TAM was appropriate for explaining the process of adopting smart clothing according to the path hypotheses of smart clothing types. Technology innovation and clothing involvement were confirmed as antecedent variables in affecting TAM. The perceived usefulness appeared to be a more crucial variable than the perceived ease of use and attitude was found to be an important parameter in adopting smart clothing. Considering the path hypotheses of MP3 playing clothes, perceived usefulness had a direct influence on acceptance intention unlike other types of smart clothing. As for photonic clothes, the influence of perceived ease of use on attitude was supported while it was rejected in the case of MP3 playing clothes and sensing sportswear.

• Aerospace Engineering and Technology
• /
• v.13 no.2
• /
• pp.29-37
• /
• 2014

Telemetry, satellite event and error information are used to check the satellite status in ground station. Different from telemetry which only informs the parameter value, event and error gives explicit information of a certain operation or status. Event also contains ground action information because every command execution is logged as event. Currently, those information is gathered and applied only for monitoring of the satellite. However, the load of the operation is getting grown because of the excessively increased information of the satellite with the number of satellite increasement. Also, the process of reporting problem to developer (or an expert) induce time delay for satellites fault management. In this paper, we propose a satellite operation assistant system which collects event sequence and stores in different group by its feature, and then recommends or executes an appropriate action for the identified abnormal state. This system is applicable to on board system for resolving LEO-satellite autonomous fault situation since is has limited contact time.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.9
• /
• pp.101-108
• /
• 2020

Recommender system is a must-have feature of e-commerce, since it provides customers with convenience in selecting products. Collaborative filtering is a widely-used and representative technique, where it gives recommendation lists of products preferred by other users or preferred by the current user in the past. Recently, researches on the recommendation system using deep learning artificial intelligence technologies are actively being conducted to achieve performance improvement. This study develops a collaborative filtering based recommender system using restricted Boltzmann machines of the deep learning technology by utilizing user ratings. Moreover, a learning parameter update algorithm is proposed for learning efficiency and performance. Performance evaluation of the proposed system is made through experimental analysis and comparison with conventional collaborative filtering methods. It is found that the proposed algorithm yields superior performance than the basic restricted Boltzmann machines.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.24 no.1
• /
• pp.33-41
• /
• 2011

This study presents modeling technologies applicable to an unbonded post-tension system using a finite element software package. In this study, both direct modeling method and multiple spring method were used. The direct modeling method adopts tube-to-tube contact elements to represent the physical feature of a post-tension system. The multiple spring method uses virtual tendons attached to the real tendons using a number of rigid axial springs that freely rotate at the ends. Both modeling technologies provide accurate predictions. However, only the multiple spring method provides numerically stable and reliable responses with a consideration of concrete tension stiffening effects. Therefore, the multiple spring method turned out to be a generally applicable modeling technology for the unbonded post-tension system. Comparisons were made for the analytical and experimental results for the verification of the selected method, and parameter studies were carried out to confirm the appropriateness of the modeling assumptions and parameters adopted in the analysis.