• Title/Summary/Keyword: Audio Discrimination

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Energy-Aware Data-Preprocessing Scheme for Efficient Audio Deep Learning in Solar-Powered IoT Edge Computing Environments (태양 에너지 수집형 IoT 엣지 컴퓨팅 환경에서 효율적인 오디오 딥러닝을 위한 에너지 적응형 데이터 전처리 기법)

  • Yeontae Yoo;Dong Kun Noh
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.4
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    • pp.159-164
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    • 2023
  • Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.

Audio-visual Spatial Coherence Judgments in the Peripheral Visual Fields

  • Lee, Chai-Bong;Kang, Dae-Gee
    • Journal of the Institute of Convergence Signal Processing
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    • v.16 no.2
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    • pp.35-39
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    • 2015
  • Auditory and visual stimuli presented in the peripheral visual field were perceived as spatially coincident when the auditory stimulus was presented five to seven degrees outwards from the direction of the visual stimulus. Furthermore, judgments of the perceived distance between auditory and visual stimuli presented in the periphery did not increase when an auditory stimulus was presented in the peripheral side of the visual stimulus. As to the origin of this phenomenon, there would seem to be two possibilities. One is that the participants could not perceptually distinguish the distance on the peripheral side because of the limitation of accuracy perception. The other is that the participants could distinguish the distances, but could not evaluate them because of the insufficient experimental setup of auditory stimuli. In order to confirm which of these two alternative explanations is valid, we conducted an experiment similar to that of our previous study using a sufficient number of loudspeakers for the presentation of auditory stimuli. Results revealed that judgments of perceived distance increased on the peripheral side. This indicates that we can perceive discrimination between audio and visual stimuli on the peripheral side.

Survey on Revision and Complements for the Current Curriculum of Herbology (한의과대학 본초학 교육과정의 개정 및 보완을 위한 설문조사 연구)

  • Kim, Hong-Jun;Choi, Go-Ya;Kim, Chul;Lee, Guem-San;Kim, Jung-Hun;Lee, Seung-Ho;Hwang, Sung-Yeoun;Ju, Young-Sung
    • The Journal of Korean Medicine
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    • v.30 no.4
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    • pp.118-128
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    • 2009
  • Objects: This study was conducted to investigate the current educational environment of herbology and to develop a future-oriented curriculum for oriental medicine. The questionnaire used in this research was drawn up based on the current curriculum referring to the current curriculum of herbology and pharmacognosy. Methods: The survey was carried out presenting the questionnaires to a total 12,754 of the students and doctors of oriental medicine through e-mailing five times; of these, 2,074 replied. Results: 1. Among the respondents, about 97% agreed that it was necessary to revise and complement the current curriculum of herbology. 2. The respondents felt that the assigned lecture time of subject was "sufficient" (19%), "insufficient" (39%) and "average" (39%), respectively, and the level of lecture was "insufficient" (37%) or "average" (43%) respectively. According to priority, it showed that the contents which needed complement in lecture were discrimination of medicinal herbs (24%), practical use of action and indications (23%), and correlation with modern disease (21%). In theoretical lectures, 69% of the respondents agreed on the introduction of natural scientific methods 3. In practice, 51% of the respondents replied that the lecture time for practice was insufficient. The contents which needed to be complemented in practice were as follows: audio-visual materials for discrimination of medicinal herbs (22%), concrete exercise for the processing of medicinal herbs (21%), and attempts for the objective discrimination of medicinal herbs using instruments (microscope, analytical instrument, residual pesticide, heavy metal, genetic analysis) (16%). 70% replied that the discrimination of medicinal herbs of high price and rarity was "none or insufficient". 4. 56% replied that it was necessary to introduce and practice physicochemical analysis, and they showed higher requests according to the increase of their educational level. However, 86% replied that they had never experienced concrete attempts for objective discrimination of medicinal herbs, which seemed to indicate that, excepting some schools, practice exercise was rarely performed. Conclusions: According to results, it seems that an urgent review on the current course of herbology and a workshop on the process of experimental practice for professors is needed.

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Classification of Pathological Voice from ARS using Neural Network (신경회로망을 이용한 ARS 장애음성의 식별에 관한 연구)

  • Jo, C.W.;Kim, K.I.;Kim, D.H.;Kwon, S.B.;Kim, K.R.;Kim, Y.J.;Jun, K.R.;Wang, S.G.
    • Speech Sciences
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    • v.8 no.2
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    • pp.61-71
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    • 2001
  • Speech material, which is collected from ARS(Automatic Response System), was analyzed and classified into disease and non-disease state. The material include 11 different kinds of diseases. Along with ARS speech, DAT(Digital Audio Tape) speech is collected in parallel to give the bench mark. To analyze speech material, analysis tools, which is developed local laboratory, are used to provide an improved and robust performance to the obtained parameters. To classify speech into disease and non-disease class, multi-layered neural network was used. Three different combinations of 3, 6, 12 parameters are tested to obtain the proper network size and to find the best performance. From the experiment, the classification rate of 92.5% was obtained.

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A Study on Acoustic Sound Tracking System on 2-Dimensional Plain (2차원적 음원추적에 관한 연구)

  • 문성배;전승환
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 1996.09a
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    • pp.117-124
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    • 1996
  • When navigating in or near an area of restricted visibility it is necessary to be heard the whistle bell and/or the siren of lighthouses or ships at times. Even though we can get the brief informations about the property of sound the direction and range of a sound radiator it is not easy to get the accurate informations for decision making. generally the audio frequency is known as 16-20,000Hz but the earshot is shorten and discrimination of sound is more difficult when there is some noise. The sound pressure is 60dB at the moment when human speaks 1 meter away. Usually the noise pressure in a silent room is 40dB and 60dB on the quiet street. In this study we suggest the basic algorithm to trace the direction and range of the source radiator using the signal received through not a physical sense but the microphone sensors and a series of signal of signal processing.

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A Study on 2-Dimensional Sound Source Tracking System (2차원적 음원추적에 관한 연구)

  • 문성배;전승환
    • Journal of the Korean Institute of Navigation
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    • v.20 no.4
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    • pp.71-79
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    • 1996
  • When navigating in or near an area of restricted visibility, it is necessary to be heard the whistle, bell and/or the siren of lighthouses or ships at times. Even though we can get the brief informations about the property of sound, the direction and range of a sound radiator, it is not enough to get the accurate informations for decision making. Generally the audio frequency is known as 16~20, 000Hz, but the earshot is shorten and discrimination of sound is more difficult when there is some noise. The sound pressure is 60dB at the moment when human speaks 1 meter away. Usually the noise pressures are 40dB in a silent room and 60dB on the quiet street, respectively. It this study, the basic algorithm and a method of signal processing are suggested to trace the direction and range of the source radiator using the signals received through not a physical sense but the microphone sensors.

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Music Genre Classification Based on Timbral Texture and Rhythmic Content Features

  • Baniya, Babu Kaji;Ghimire, Deepak;Lee, Joonwhon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.204-207
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    • 2013
  • Music genre classification is an essential component for music information retrieval system. There are two important components to be considered for better genre classification, which are audio feature extraction and classifier. This paper incorporates two different kinds of features for genre classification, timbral texture and rhythmic content features. Timbral texture contains several spectral and Mel-frequency Cepstral Coefficient (MFCC) features. Before choosing a timbral feature we explore which feature contributes less significant role on genre discrimination. This facilitates the reduction of feature dimension. For the timbral features up to the 4-th order central moments and the covariance components of mutual features are considered to improve the overall classification result. For the rhythmic content the features extracted from beat histogram are selected. In the paper Extreme Learning Machine (ELM) with bagging is used as classifier for classifying the genres. Based on the proposed feature sets and classifier, experiment is performed with well-known datasets: GTZAN databases with ten different music genres, respectively. The proposed method acquires the better classification accuracy than the existing approaches.

A New Approach to the Science Education Assessment Using Partial Credits to Different Science Inquiry Problem Solving Process Types

  • Lee, Hang-Ro;Lim, Cheong-Hwan
    • Journal of the Korean earth science society
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    • v.23 no.2
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    • pp.147-153
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    • 2002
  • Reasonable and reliable assessment method is one of the most important issues in science education, Partial credits method is an effective tool for assessing students' science inquiry problem solving. The purposes of this study were to classify the Problem solving types based on the analysis of the thinking Process, and how much the related science concept and the science process skills were used in solving science inquiry problems, and to describe the possibility and rationality of the assessment method that gives partial credit 128 high school seniors were selected and their answers were analyzed to identify science concepts they used to solve each problem, and the result was used as the criterion in the scientific concept test development. Also, to study the science inquiry problem solving type, 152 high school seniors were selected, and protocols were made from audio-taped data of their problem solving process through a think-aloud method and retrospective interviews. In order to get a raw data needed in statistical comparison of reliability, discrimination and the difficulty of the test and the production of the regression equation that determines the ratio of partial credit, 640 students were selected and they were given a science inquiry problem test, a science process skills test, and a scientific concept test. Research result suggested it is more reasonable and reliable to switch to the assessment method that applies partial credit to different problem solving types based on the analysis of the thinking process in problem solving process, instead of the dichotomous credit method.

Blind Image Quality Assessment on Gaussian Blur Images

  • Wang, Liping;Wang, Chengyou;Zhou, Xiao
    • Journal of Information Processing Systems
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    • v.13 no.3
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    • pp.448-463
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    • 2017
  • Multimedia is a ubiquitous and indispensable part of our daily life and learning such as audio, image, and video. Objective and subjective quality evaluations play an important role in various multimedia applications. Blind image quality assessment (BIQA) is used to indicate the perceptual quality of a distorted image, while its reference image is not considered and used. Blur is one of the common image distortions. In this paper, we propose a novel BIQA index for Gaussian blur distortion based on the fact that images with different blur degree will have different changes through the same blur. We describe this discrimination from three aspects: color, edge, and structure. For color, we adopt color histogram; for edge, we use edge intensity map, and saliency map is used as the weighting function to be consistent with human visual system (HVS); for structure, we use structure tensor and structural similarity (SSIM) index. Numerous experiments based on four benchmark databases show that our proposed index is highly consistent with the subjective quality assessment.

Remote Fault Detection in Conveyor System Using Drone Based on Audio FFT Analysis (드론을 활용하고 음성 FFT분석에 기반을 둔 컨베이어 시스템의 원격 고장 검출)

  • Yeom, Dong-Joo;Lee, Bo-Hee
    • Journal of Convergence for Information Technology
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    • v.9 no.10
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    • pp.101-107
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    • 2019
  • This paper proposes a method for detecting faults in conveyor systems used for transportation of raw materials needed in the thermal power plant and cement industries. A small drone was designed in consideration of the difficulty in accessing the industrial site and the need to use it in wide industrial site. In order to apply the system to the embedded microprocessor, hardware and algorithms considering limited memory and execution time have been proposed. At this time, the failure determination method measures the peak frequency through the measurement, detects the continuity of the high frequency, and performs the failure diagnosis with the high frequency components of noise. The proposed system consists of experimental environment based on the data obtained from the actual thermal power plant, and it is confirmed that the proposed system is useful by conducting virtual environment experiments with the drone designed system. In the future, further research is needed to improve the drone's flight stability and to improve discrimination performance by using more intelligent methods of fault frequency.