• Journal of Environmental Science International
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• v.6 no.6
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• pp.551-562
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• 1997

Nine districts in Seoul were chosen randomly and a questionnaire containing 23 questions was distributed to survey the perception of noise pollution by the citizens. The results were primarily analyzed to understand the perception of Seoul citizen as a whole, and then analyzed according to 4 demographic variables -district area, age, gender and occupation -to see if there were any possible relation between nonnoise variables and noise annoyance. Actual noise level data measured by the city government were used to compare quantified noise level with the surveyed people's perception. It was found that people consider road traffic noise to be the naix source of noise pollution In Seoul and that most people have experienced annoyance in everyday life. Also it was verified that the responsibility for noise control should be on both city government and the individuals, but It was generally considered that very little effort Is actually put Into solong norse pollution from both groups. From the survey, It could be analyzed that domographic variables do affect people In the awareness of noise pollution, and that one's sensitifty and annoyance due to noise increase as one ages. From the study, It was concluded that noise pollution Is not considered currently as a hazardous problem to most Seoul citizens, however specific noise reduction policies, especially regarding road traffic noise, should be put Into practice In the near future.

• Journal of KSNVE
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• v.13 no.2
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• pp.119-128
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• 2003

Abstract Increasing awareness of industrial noise pollution and emerging stricter standards have made noise an important topic of research in electric motors. The standard three-phase induction motors. see Fig. 1, (abbreviated further as TPIM) are mass-produced as being simple, robust and rather inexpensive, as opposed to other types of electric motors. Electric motors use over half of all electricity consumed in most countries. Typically motors consume 60∼80 ％ of the electricity for those used In the industrial sector and about 20∼35 ％ of the electricity for those used in the commercial sector. For that is important to know their participation to the noise pollution of the environment and the efficient ways of their noise reduction. Each step in determining the ways for TPIM electromagnetic noise reduction including the methods that highlight their efficiency, are presented and explained.

• The Journal of the Acoustical Society of Korea
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• v.32 no.3
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• pp.252-261
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• 2013

The common speech recognition system displays higher recognition performance in a quiet environment, while its performance declines sharply in a real environment where there are noises. To implement a speech recognizer that is robust in different speech settings, this study suggests the method of Parallel Model Combination adaptation using frequency-variant based on environment-awareness (FV-PMC), which uses variants in frequency; acquires the environmental data for speech recognition; applies it to upgrading the speech recognition model; and promotes its performance enhancement. This FV-PMC performs the speech recognition with the recognition model which is generated as followings: i) calculating the average frequency variant in advance among the readily-classified noise groups and setting it as a threshold value; ii) recalculating the frequency variant among noise groups when speech with unknown noises are input; iii) regarding the speech higher than the threshold value of the relevant group as the speech including the noise of its group; and iv) using the speech that includes this noise group. When noises were classified with the proposed FV-PMC, the average accuracy of classification was 56%, and the results from the speech recognition experiments showed the average recognition rate of Set A was 79.05%, the rate of Set B 79.43%m, and the rate of Set C 83.37% respectively. The grand mean of recognition rate was 80.62%, which demonstrates 5.69% more improved effects than the recognition rate of 74.93% of the existing Parallel Model Combination with a clear model, meaning that the proposed method is effective.

• Korean Journal of Otorhinolaryngology-Head and Neck Surgery
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• v.61 no.12
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• pp.669-673
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• 2018

Background and Objectives Tinnitus, a common complaint of workers who are exposed to noise, can cause substantial negative effects on the quality of life of these workers. The aim of this study was to analyze the characteristics of tinnitus in patients with noise-induced hearing loss and the relationship between tinnitus and the duration of noise exposure. Subjects and Method Thirty-three patients with subjective tinnitus and noise-induced hearing loss were included in this study. Tinnitus questionnaire, Tinnitus Handicap Inventory (THI) and audiological examinations were investigated according to the duration of noise exposure. Results There was a significant correlation between the tinnitus loudness and the duration of noise exposure. Patients who had longer periods of noise exposure had a louder tinnitus and higher THI score. However, there is no significant correlation between the characteristics of tinnitus and aging process. Conclusion The duration of noise exposure influences the loudness and distress of tinnitus. An awareness of tinnitus should be considered as part of hearing conservation program.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.1
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• pp.19-27
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• 2009

Globally, customer appreciation and demand for quieter products has driven noise control engineers to develop efficient and quieter products in a relatively short time. In the vehicles and ship industry, noise has become an important attribute because of the competitive market and increasing customer awareness. Noise reduction is often achieved through structural modifications by typical approaches. In the present paper, author describes a fundamental study on optimum design of curvature. Bezier curve. and rib attachment to reduce noise from simple panel using a genetic algorithm(GA). The acoustic optimization procedure employed p-FEM for structural analysis, the Rayleigh integral method for acoustic analysis and the GA for searching optimum design. In the optimization procedure. the objective function to be minimized is the average sound power radiated from an objective structure over a given frequency range $0{\sim}300$ Hz.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1203-1208
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• 2009

Green IT based u-City means that u-City having Green IT concept. If we adopt the situation awareness or not, the processing of Green IT may be reduced. For example, if we recognize a lot of speech sound on CCTV in u-City environment, it takes a lot of processing time and cost. However, if we want recognize emergency sound on CCTV, it takes a few reduced processing cost. So, for detecting emergency state dynamically through CCTV, we propose our advanced speech recognition system. For the purpose of that, we adopt HMM (Hidden Markov Model) for feature extraction. Also, we adopt Wiener filter technique for noise elimination in many information coming from on CCTV in u-City environment.

• The Journal of the Acoustical Society of Korea
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• v.33 no.4
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• pp.248-254
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• 2014

Among acoustic signal analysis tasks, acoustic context awareness is one of the most formidable tasks in terms of complexity since it requires sophisticated understanding of individual acoustic events. In conventional context awareness methods, individual acoustic event detection or recognition is employed to generate a relevant decision on the impending context. However this approach may produce poorly performing decision results in practical situations due to the possibility of events occurring simultaneously or the acoustically similar events that are difficult to distinguish with each other. Particularly, the babble noise acoustic event occurring at a bus or subway environment may create confusion to context awareness task since babbling is similar in any environment. Therefore in this paper, a frequency-cepstral feature vector is proposed to mitigate the confusion problem during the situation awareness task of binary decisions: bus or metro. By employing the Support Vector Machine (SVM) as the classifier, the proposed feature vector scheme is shown to produce better performance than the conventional scheme.

• Journal of Navigation and Port Research
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• v.40 no.2
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• pp.83-87
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• 2016

The maritime industry is expanding at an alarming rate hence there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking module designed herein comprises determining existing states of high dynamic target warship, state prediction and state compensation due to random noise. This is achieved by first analyzing the process of tracking followed by design of a tracking algorithm that uses ${\alpha}-{\beta}-{\gamma}$ tracking filter under a random noise. The algorithm involves initializing the state parameters which include position, velocity, acceleration and the course. This is then followed by state prediction at each time interval. A weighted difference of the observed and predicted state values at the $n^{th}$ observation is added to the predicted state to obtain the smoothed (filtered) state. This estimation is subsequently employed to determine the predicted state in the next radar scan. The filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from a pre-determined value of the damping parameter, ${\xi}$. The smoothed, predicted and the observed positions are used to compute the twice distance root mean square (2drms) error as a measure of the ability of the tracking module to manage the noise to acceptable levels.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.71-78
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• 2013

In this paper, we propose a method to infer the user's behavior and situation through collected data from multi-sensor equipped with a smart clothing and it was implemented as a smartphone App. User context reasoning and behavior determine is very difficult using single sensor depending on the measured value of the sensor varies from environmental noise. So, the reasoning and the digital filter algorithms to determine user behavior reducing noise and are required. In this paper, we used EWMA, Kalman Filter and SVM processing behavior for 3-axis value as a representative value of one.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.53-54
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• 2015

The maritime industry is expanding at an alarming rate and as such there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking system described herein comprises determining existing states of own ship, state prediction and state compensation caused by random noise. The purpose of this paper is to analyze the process of tracking and develop a tracking algorithm by using ${\alpha}-{\beta}-{\gamma}$ tracking filter under a random noise or irregular motion for use in a warship. The algorithm involves initializing the input parameters of position, velocity and course. The actual positions are then computed for each time interval. In addition, a weighted difference of the observed and predicted position at the nth observation is added to the predicted position to obtain the smoothed position. This estimation is subsequently employed to determine the predicted position at (n+1). The smoothed values, predicted values and the observed values are used to compute the twice distance root mean square (2drms) error as a measure of accuracy of the tracking module.