• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.383-392
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• 2006

In this paper, we propose a new relevance feedback algorithm using Probabilistic Neural Networks(PNN) while supporting multi-class learning. Then, to validate the effectiveness of our feedback approach, we incorporate the proposed algorithm into our region-based image retrieval tool, FRIP(Finding Regions In the Pictures). In our feedback approach, there is no need to assume that feature vectors are independent, and as well as it allows the system to insert additional classes for detail classification. In addition, it does not have a long computation time for training because it only has four layers. In the PNN classification process, we store the user's entire past feedback actions as a history in order to improve performance for future iterations. By using a history, our approach can capture the user's subjective intension more precisely and prevent retrieval performance errors which originate from fluctuating or degrading in the next iteration. The efficacy of our method is validated using a set of 3000 images derived from a Corel-photo CD.

• Journal of the KSME
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• v.32 no.7
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• pp.613-619
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• 1992

짧은 시간의 주행 실험과 랜덤 응답 해석을 통한 차체의 피로수명을 해석하는 방법을 제시하 였다. 주파수 영역에서 다축 응력을 폰 미제스 응력으로 변환시키고 응력 진폭의 확률 분포를 와이블 분포를 고려하여 처리함으로써 더욱 신뢰도가 큰 해석이 되도록 하였다. 여기에 제시된 해석 과정은 일반적으로 적용 가능한 것이므로, 양산 전 단계의 차체 피로 설계에 좋은 참고가 될 것이다.

• Journal of KIISE
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• v.43 no.2
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• pp.186-195
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• 2016

This paper proposes a vehicle license plate detection method in real road environments using 8 bit-MCT features and a landmark-based Adaboost method. The proposed method allows identification of the potential license plate region, and generates a saliency map that presents the license plate's location probability based on the Adaboost classification score. The candidate regions whose scores are higher than the given threshold are chosen from the saliency map. Each candidate region is adjusted by the local image variance and verified by the SVM and the histograms of the 8bit-MCT features. The proposed method achieves a detection accuracy of 85% from various road images in Korea and Europe.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.11-19
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• 2016

In this paper, we propose an automatic segmentation method of renal parenchyma on abdominal CT image using graph-cuts with shape constraint based on multi-probabilistic atlas. The proposed method consists of following three steps. First, to use the various shape information of renal parenchyma, multi-probabilistic atlas is generated by cortex-based similarity registration. Second, initial seeds for graph-cuts are extracted by maximum a posteriori (MAP) estimation and renal parenchyma is segmented by graph-cuts with shape constraint. Third, to reduce alignment error of probabilistic atlas and increase segmentation accuracy, registration and segmentation are iteratively performed. To evaluate the performance of proposed method, qualitative and quantitative evaluation are performed. Experimental results show that the proposed method avoids a leakage into neighbor regions with similar intensity of renal parenchyma and shows improved segmentation accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.59-68
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• 2017

Random process plays a major role in wireless communication system to analytically derive the probability distribution function of the various statistical distribution. In this paper, we derive the decreasing function of the exponential distribution under the given condition which is expressed as wireless channel condition. The probability distribution function of Gaussian, Laplacian, Rayleigh and Nakagami distribution are also derived. Extensive simulation results of these statistical distributions are provided to prove that random process has a significant role in the wireless communications. In addition, the Rayleigh and Rician channels show specific examples of visible distance communication and invisible distance channel environment. This paper is motivated by that we assume a block fading channel model, where the channel is constant during a transmission block and changes independently between consecutive transmission block, can achieve a better performance in high SNR regime with i.i.d channel. This algorithm for realizing these transforms can be applied to the Kronecker MIMO channel.

• Journal of IKEEE
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• v.15 no.3
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• pp.198-204
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• 2011

In this letter, another analytical approach for the opportunistic amplify-and-forward (OAF) relay systems is proposed over Rayleigh fading channels. Based on set-operation at the selected relay node, its selection probability as the best relay is derived and then, the probability density function (PDF) of the received instantaneous signal-to-noise ratio (SNR) is expressed as a more tractable form in which the number of summations and the length of each summation are specified. Then, the average error rate, outage probability, and average channel capacity are obtained as approximated closed-forms. Simulation results are finally presented to validate that the proposed analytical expressions can be a unified frame work covering all Rayleigh fading channel conditions. Furthermore, it is confirmed that OAF schemes can outperform the other non-selective schemes on the average error rate, outage probability, and average channel capacity.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.17-24
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• 2007

Critical practicality problems are cause to search the presentation and contents according to user request and purpose in previous internet system. Recently, there are a lot of researches about dynamic adaptable ontology based system. We designed ontology based educational system which uses discrete probability and user profile. This system provided advanced usability of contents by ontology and dynamic adaptive model based on discrete probability distribution function and user profile in ontology educational systems. This models represents application domain to weighted direction graph of dynamic adaptive objects and modeling user actions using dynamically approach method structured on discrete probability function. Proposed probability analysis can use that presenting potential attribute to user actions that are tracing search actions of user in ontology structure. This approach methods can allocate dynamically appropriate profiles to user.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.177-184
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• 2021

This paper proposes an assessment method using probability-based index for safe and successful underwater docking of autonomous underwater vehicles(AUVs) to the docking stations(DSs). The proposed method assesses the probability of docking according to the degree to which the state of the AUV is consistent with the state criteria for docking. The assessment is performed within a specific area considering the kinematic constraints and docking plans of the AUV. The assessment process is defining probability density function, calculating probabilities for reaching the docking station according to the difference to position and heading criteria, and computing the probability-based index in real-time. We verify the validity of the proposed method through analyzing the data acquired on operation test.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.285-292
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• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.67-77
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• 2003

Watermark detection has a crucial role in copyright protection and authentication for multimedia Because be the correlation -based algorithm which has widely been used in the watermark detection doesn't utilize the distributional characteristics of cover image to be marked, its performance is not optimum. So a new detection algorithm is proposed which is optimum for multiplicative watermark embedding. By relying on statistical decision method, the proposed method is derived according to the Bayes decision theory. Neyman Pearson criterion, and distribution of wavelet coefficients, thus Permitting to minimize the missed detection probability subject to a given false detection probability The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation -based method.