• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.77-83
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• 2009

This paper proposes a new noise-biased compensation of minimum statistics(MS) method using a nonlinear function and a priori speech absence probability(SAP) for speech enhancement in non-stationary noisy environments. The minimum statistics(MS) method is well known technique for noise power estimation in non-stationary noisy environments. It tends to bias the noise estimate below that of true noise level. The proposed method is combined with an adaptive parameter based on a sigmoid function and a priori speech absence probability (SAP) for biased compensation. Specifically. we apply the adaptive parameter according to the a posteriori SNR. In addition, when the a priori SAP equals unity, the adaptive biased compensation factor separately increases ${\delta}_{max}$ each frequency bin, and vice versa. We evaluate the estimation of noise power capability in highly non-stationary and various noise environments, the improvement in the segmental signal-to-noise ratio (SNR), and the Itakura-Saito Distortion Measure (ISDM) integrated into a spectral subtraction (SS). The results shows that our proposed method is superior to the conventional MS approach.

• Bulletin of the Korean Mathematical Society
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• v.38 no.1
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• pp.29-53
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• 2001

This note presents a an indirect adaptive control scheme for first-order continuous-time systems. The estimated plant model is controllable and then the adaptive scheme is free from singularities. The singularities are avoided through a modification of the estimated plant parameter vector so that its associated Sylvester matrix is guaranteed to be nonsingular. That properties is achieved by ensuring that the absolute value of its determinant does not lie below a positive threshold. A modification scheme based on the achievement of a modified diagonally dominant Sylvester matrix of the parameter estimates is also given as an alternative method. This diagonal dominance is achieved through estimates modification as a way to guarantee the controllability of the modified estimated model when a controllability measure of the ‘a priori’ estimated model fails. In both schemes, the use of a hysteresis switching function for the modification of the estimates is not required to ensure the nonsingularity of the Sylvester matrix of the estimates.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.71-89
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• 2003

Although many studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective in the classification problems. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques. This study proposes the linearly combining methodology of different classification techniques. The methodology is developed to find the optimal combining weight and compute the weighted-average of different techniques' outputs. The proposed methodology is represented as the form of mixed integer programming. The objective function of proposed combining methodology is to minimize total misclassification cost which is the weighted-sum of two types of misclassification. To simplify the problem solving process, cutoff value is fixed and threshold function is removed. The form of mixed integer programming is solved with the branch and bound methods. The result showed that proposed methodology classified more accurately than any of techniques individually did. It is confirmed that Proposed methodology Predicts significantly better than individual techniques and the other combining methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.575-583
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• 2013

In ad hoc networks, a distributed timing synchronization is studied using a firefly-inspired approach. We illuminate the exiting synchronization algorithm based on the theory of pulse-coupled oscillators so that the algorithm can be applied to multi-carrier systems through packet-based communications, where nodes communicate over an orthogonal frequency-division multiple access air interface. As our main result, we introduce a new sync-code detector, which optimally designs both the coupling function and the detection threshold when various network parameters such as the number of nodes in the network and network topology are given a priori. Computer simulations are performed to show the convergence to a synchronized state in realistic network environments.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.3
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• pp.234-243
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• 2015

It is required to have the capability to predict the impact point of the ballistic target in order to assign the firing unit with high engagement possibility for the interception in the ballistic target defense systems. In this paper, a novel method is proposed to predict the impact point of the ballistic target using a flight phase discrimination algorithm given the insufficient measurements on the partial trajectory. The flight of a ballistic target is composed of a boost phase and a ballistic phase with different dynamics. The flight phase is discriminated by using the normalized innovation distance between measurements and a priori estimated measurements. The threshold and tolerance in the flight phase discrimination are determined from the probabilistic characteristics of the estimation error. Monte Carlo simulations are performed to verify the proposed method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.8
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• pp.1152-1163
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• 1998

In the present work, the image processing technique for measurement of drop sizes has been improved. Firstly, the local processing concept was adopted in addition to the global processing technique to take account of non-uniformity of the illumination intensity ; thereby, basically, the measurement error can be reduced. Also, the unfocussed image of drops can be eliminated more precisely since the elimination process is based on the local normalized contrast. Secondly the algorithms to process the partially detected or overlapped drop images and the non-spherical drop images were developed. Finally, the improved algorithm was tested by using an artificially prepared image-frame, where the partial or overlapped particles and the non-spherical particles are mixed with the normal spherical ones (with their true size-distributions known a priori). The results showed that both the recognition rate of the number of particles and the measurement accuracy were improved prominently.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.967-970
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• 2014

An efficient peak detection algorithm in magnitude spectrum is proposed to distinguish the M-frequency shift keying(FSK) signals from other digitally modulated signal. In addition, recognition of the modulation order estimation of FSK signals is also studied based on the fact that the magnitude spectrum of FSK signals reveals the number of peaks equal to the modulation order. When no a priori information about the signals, we utilize the histogram of the magnitude spectrum to determine the threshold which is important factor in peak detection algorithm. The simulation results show high probability of classification under 500 symbols and signal-to-noise ratio(SNR) higher than 4dB.

• Safety and Health at Work
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• v.11 no.4
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• pp.385-396
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• 2020

Teachers are facing various job demands with psychosocial aspects being fundamental due to the nature of the occupation. Although teachers' work is associated with different psychosocial health risks, little is known on how to identify and tackle those. Thus, a systematic literature search as per the PRISMA statement was conducted via MEDLINE (PubMed), PSYNDEX (PubPsych), and ScienceDirect. Two reviewers independently screened 2261 titles and abstracts and 169 full-texts. According to the inclusion criteria established a priori, articles from peer-reviewed journals (English or German) on psychosocial risk management in teachers were incorporated. Despite a comprehensive and sensitive search, only four publications could be identified, outlining a process to implement risk management and different assessment tools. Taken together, data presented in the articles were scarce. Recommendations for process steps and the assessment of psychosocial risks can be derived from the findings. To implement effective psychosocial risk management in the teaching profession, further research is needed, though. Effective and practicable approaches, which are accepted by the target group, should be further developed and investigated. Relevant causes of occupational strain in the teaching profession must be identified and assessed reliably. Low-threshold interventions should be implemented, and the outcome must be evaluated afterward.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.323-328
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• 2004

The development of group-specific tissue probability maps (TPM) provides a priori knowledge for better result of cerebral tissue classification with regard to the inter-ethnic differences of inter-subject variability. We present sequential procedures of group-specific TPM and evaluate the age effects in the structural differences of TPM. We investigated 100 healthy volunteers with high resolution MRI scalming. The subjects were classified into young (60, 25.92+4.58) and old groups (40, 58.83${\pm}$8.10) according to the age. To avoid any bias from random selected single subject and improve registration robustness, average atlas as target for TPM was constructed from skull-stripped whole data using linear and nonlinear registration of AIR. Each subject was segmented into binary images of gray matter, white matter, and cerebrospinal fluid using fuzzy clustering and normalized into the space of average atlas. The probability images were the means of these binary images, and contained values in the range of zero to one. A TPM of a given tissue is a spatial probability distribution representing a certain subject population. In the spatial distribution of tissue probability according to the threshold of probability, the old group exhibited enlarged ventricles and overall GM atrophy as age-specific changes, compared to the young group. Our results are generally consistent with the few published studies on age differences in the brain morphology. The more similar the morphology of the subject is to the average of the population represented by the TPM, the better the entire classification procedure should work. Therefore, we suggest that group-specific TPM should be used as a priori information for the cerebral tissue classification.

• Journal of the Korean earth science society
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• v.23 no.7
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• pp.587-596
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• 2002

A super ensemble model was developed for the seasonal prediction of regional precipitation in Korea using the lag correlated large scale predictors, based on the empirical orthogonal function (EOF) analysis and multiple linear regression model. The predictability of this model was also evaluated by cross-validation. Correlation between the predicted and the observed value obtained from the super ensemble model showed 0.73 in spring, 0.61 in summer, 0.69 in autumn and 0.75 in winter. The predictability of categorical forecasting was also evaluated based on the three classes such as above normal, near normal and below normal that are clearly defined in terms of a priori specified by threshold values. Categorical forecasting by the super ensemble model has a hit rate with a range from 0.42 to 0.74 in seasonal precipitation.