• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.179-186
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• 2009

This paper proposes a target speech extraction which restores speech signal of a target speaker form noisy convolutive mixture of speech and an interference source. We assume that the target speaker is known and his/her utterances are available in the training time. Incorporating the additional information extracted from the training utterances into the separation, we combine convolutive blind source separation(CBSS) and non-negative decomposition techniques, e.g., probabilistic latent variable model. The nonnegative decomposition is used to learn a set of bases from the spectrogram of the training utterances, where the bases represent the spectral information corresponding to the target speaker. Based on the learned spectral bases, our method provides two postprocessing steps for CBSS. Channel selection step finds a desirable output channel from CBSS, which dominantly contains the target speech. Reconstruct step recovers the original spectrogram of the target speech from the selected output channel so that the remained interference source and background noise are suppressed. Experimental results show that our method substantially improves the separation results of CBSS and, as a result, successfully recovers the target speech.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.79-87
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• 2006

In this study, we evaluated the performance of a companding strategy as a preprocessing for speech enhancement and noise reduction. The proposed algorithm is based on two tone suppression that is human's hearing characteristics. This algorithm enhances spectral peak of speech signal and reduces background noise, however it has tradeoff characteristics between speech distortion and noise reduction due to limited channel number and nonlinear block. Therefore, we designed two different companding structures that have relative characteristics of noise reduction and speech distortion and found suitable companding structures by difference of individual speech perception ability in noise environment. Thus we proposed speech perception enhancement of cochlear implant user in noise environment with low SNR. The performance of the proposed algorithm was evaluated through 5 normal hearing listeners using noise band simulation. Improvement of speech perception was observed for all subjects and each subject preferred the different type of companding structure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.8-14
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• 2009

In the research field of speech recognition, pinpointing the endpoints of speech utterance even with the presence of background noise is of great importance. These noise present during recording introduce disturbances which complicates matters since what we just want is to get the stationary parameters corresponding to each speech section. One major cause of error in automatic recognition of isolated words is the inaccurate detection of the beginning and end boundaries of the test and reference templates, thus the necessity to find an effective method in removing the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two linear time-domain measurements: the short-time energy, and short-time zero-crossing rate. They perform well for clean speech but their precision is not guaranteed if there is noise present, since the high energy and zero-crossing rate of the noise is mistaken as a part of the speech uttered. This paper proposes a novel approach in finding an apparent threshold between noise and speech based on Lyapunov Exponents (LEs). This proposed method adopts the nonlinear features to analyze the chaos characteristics of the speech signal instead of depending on the unreliable factor-energy. The excellent performance of this approach compared with the conventional methods lies in the fact that it detects the endpoints as a nonlinearity of speech signal, which we believe is an important characteristic and has been neglected by the conventional methods. The proposed method extracts the features based only on the time-domain waveform of the speech signal illustrating its low complexity. Simulations done showed the effective performance of the Proposed method in a noisy environment with an average recognition rate of up 92.85% for unspecified person.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.125-131
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• 2011

Water leak detection system is a system based on wireless sensor networks(WSNs) which detect a leak on water supply, localize the leak position and finally inform a water management center. A traditional leak detection method is to use experienced personnel who walk along a pipeline listening to the sound that is generated by the leaks and their effectiveness depend on the experience of the user. Also making more successful detection, it should be processed at middle of the night when people do not use water, as the result users have to operate the leak detection system at midnight. In this paper, we propose a new method for the water leak detection system based on the WSNs and describe it in detail. Leak detection devices which detect a leakage of water transmit and receive the result of water leak detection with each other by configuring WSNs to improve reliability of the detection result. Also, we analyzed the sound from water flowed in pipeline, proposed the pre-signal processing to separate a leakage sound from noisy sound. And lastly, It is especially important to make a time synchronization with water leak detection devices that are installed on the pipeline, we used 1PPS(1 Pulse Per Second) signal generated by GPS, therefore we could get a precise time synchronization. The proposed system set up in Namyangju and performances were evaluated.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.182-187
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• 2010

In the various fields of Civil Engineering, shear modulus is very important input parameters to design many constructions and to analyze ground behaviors. In general, a shear wave velocity profile is decided by various experiments before constructing a structure and, analysis and design are carried out by using decided shear wave velocity profile of the site. However, if civil structures are started to construct, the shear wave velocity will be increased more than before constructions because of confining pressure increase by the load of structure. The evaluation of the change in shear wave velocity profile is used very importantly when maintaining, managing, reinforcing and regenerating existing structures. In this study, a non-destructively geotechnical investigation method by using the HWAW method is applied to an evaluation of change in properties of the site according to construction. Generally, the space for experiments is narrow when underground of existing or on-going structures is evaluate, so a prompt non-destructive experiment is required. This prompt non-destructive experiment would be performed by various in-situ seismic methods. However, most of in-situ seismic methods need more space for experiments, so it is difficult to be applied. The HWAW method using the Harmonic wavelet transforms, which is based on time-frequency analysis, determines shear wave velocity profile. It consists of a source as well as short receiver spacing that is 1~3m, and is able to determine a shear wave velocity profile from surface to deep depth by one test on a space. As the HWAW method uses only the signal portion of the maximum local signal/noise ratio to determine a profile, it provides reliability shear modulus profile such as under construction or noisy situation by minimizing effects of noise from diverse vibration on a construction site or urban area. To estimate the applicability of the proposed method, field tests were performed in the change of geotechnical properties according to constructing a minimized modeling bent. Through this study, the change of geotechnical properties of the site was effectively evaluated according to construction of a structure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.366-373
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• 2017

In this paper, we propose a variable weighted average (VWA) learning method in order to improve the performance of the fuzzy ART neural network that has been developed by Grossberg. In a conventional method, the Fast Commit Slow Recode (FCSR), when an input pattern falls in a category, the representative pattern of the category is updated at a fixed learning rate regardless of the degree of similarity of the input pattern. To resolve this issue, a variable learning method proposes reflecting the distance between the input pattern and the representative pattern to reduce the FCSR's category proliferation issue and improve the pattern recognition rate. However, these methods still suffer from the category proliferation issue and limited pattern recognition rate due to inevitable excessive learning created by use of fuzzy AND. The proposed method applies a weighted average learning scheme that reflects the distance between the input pattern and the representative pattern when updating the representative pattern of a category suppressing excessive learning for a representative pattern. Our simulation results show that the newly proposed variable weighted average learning method (VWA) mitigates the category proliferation problem of a fuzzy ART neural network by suppressing excessive learning of a representative pattern in a noisy environment and significantly improves the pattern recognition rates.

• 전자공학회논문지 IE
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• v.47 no.4
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• pp.39-47
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• 2010

This paper proposes a numerical analysis to prove that the performance of the differential phase detections (DPDs) with the decision feedback, such as the decision feedback DPD (DF-DPD) and the DPD with recursively generated phase reference (DPD-RGPR), approach the performance of the coherent detection with differential decoding. The conventional differential phase detection for M-ary DPSK can make the receiver architecture simple, while it can make the bit-error rate (BER) performance poor because of the previous noisy phase as a reference phase. To improve the BER performance of the conventional differential detection, multiple symbol differential detection methods, including DF-DPD and DPD-RGPR, have been proposed. However, the studies on the analysis and on the comparison of these methods have been little performed. Then, this paper mathematically intends to analyze and compare the performance of the DPDs with the decision feedback. The analysis results show that the DPDs with the decision feedback can have the performance equal to that of the coherent detection with differential decoding and be available for the noncoherent detection in the improved performance. Considering the hardware complexity, the DPD RGPR with the simple detection process by using the recursively generated phase reference can be more simply implemented than the DF-DPD based on the architecture whose complexity increases according to the increasing detection length.

• Journal of The Korean Association For Science Education
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• v.35 no.3
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• pp.499-508
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• 2015

The purposes of this study are to investigate elementary students' perception of science classroom through an analysis of students' answer to an open-ended question and to suggest a framework for the analysis of science classroom culture, as the first step to develop an analysis tool for qualitative exploration of science classroom culture. We analyzed 571 responses and developed an analysis framework with six categories (i.e. major factors; power structure of a classroom community; focused domains of the science classroom; student concerns; atmosphere of science classroom; participation form). The details of the six categories can be summarized as follows: (1) major factors were revealed to be practical work, fun, teacher, community and others; (2) the power structure of classroom community was in the order of peer students, teacher, and individual student himself/herself; (3) the focused domains of the science classroom perceived by students were more about affective and behavioral domains than cognitive one; (4) major student concerns were teachers' teaching, having practical work, and the understanding of and the sharing of knowledge and opinions (5) science classroom atmosphere was noisy and pranky but fun and interesting; (6) the students participation forms were to be total participation or voluntary participation or cooperative practice. Through this study, not only suggesting the framework, but we could also get implications for the cultural aspects of science classroom based on the results of data analysis in this study.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.279-286
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• 1991

Much of the working population in developing countries are engaged in shift work now and the number of shift workers is not expected to decrease in the future mostly because the need for continuity of production is increasing. Therefore, the possible effects of shift work on health are of particular interest, and in fact, there have been many epidemiological studies on shift work since the first world war. However, no studies on health effects of shift work have been reported in Korea, and the existing studies in western world have arrived at quite different conclusions mainly because the conditions of work other than shift work, such as age and selection of workers, work environment, and labor conditions also influence the health of workers. This study was firstly carried out in Korea to investigate the health risks related to shift work with 2,093 female workers randomly selected from three major manufacturing industries in proportion to total number of female workers in those industries. Differences of work conditions other than shift work in this study were adjusted by multivariate analysis. Ma findings obtained from this study are as follows : 1. There were significant differences between shift and day workers in the distribution of age, type of industry, condition of noise and dust, regularity of mealtime, working position, and working duration. Shift workers tended to be younger, to have shorter working duration, to have more irregular mealtime, to work in standing position, and to work under more noisy and dusty environment than day workers. 2. Univariate analysis showed that shift work increased the Todai Health Index (THI) scores of digestive tract, respiratory tract, and mental instability symptom categories. Shift work also increased days of sickness absence and number of industrial accident per 100 workers per month. 3. Multivariate analysis that adjusted the differences of demographic, occupational and non-occupational health-related working conditions showed that digestive tract symptom and mental instability symptom scores were significantly higher in shift workers than those in day workers. Based on these study results, it is concluded that the shift work has significant effects on some psychophysiological conditions of the workers and the effects are also influenced by several other personal and working conditions.