• Title/Summary/Keyword: 임펄스

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ESD(Exponential Standard Deviation) Band centered at Exponential Moving Average (지수이동평균을 중심으로 하는 ESD밴드)

  • Lee, Jungyoun;Hwang, Sunmyung
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.115-125
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    • 2016
  • The Bollinger Band indicating the current price position in the recent price action range is obtained by adding/substracting the simple standard deviation (SSD) to/from the simple moving average (SMA). In this paper, we first compare the characteristics of the SMA and the exponential moving average (EMA) in the operator's point of view. A basic equation is obtained between the interval length N of the SMA operator and the weighting factor ${\rho}$ of the EMA operator, that makes the centers of the 1st order momentums of each operator impulse respoinse identical. For equivalent N and ${\rho}$, frequency response examples are obtained and compared by using the discrete time Fourier transform. Based on observation that the SMA operator reacts more excessively than the EMA operator, we propose a novel exponential standard deviation (ESD) band centered at the EMA and derive an auto recursive formula for the proposed ESD band. Practical examples for the ESD band show that it has a smoother bound on the price action range than the Bollinger Band. Comparisons are also made for the gap corrected chart to show the advantageous feature of the ESD band even in the case of gap occurrence. Trading techniques developed for the Bollinger Band can be straight forwardly applied to those for the ESD band.

A research on the emotion classification and precision improvement of EEG(Electroencephalogram) data using machine learning algorithm (기계학습 알고리즘에 기반한 뇌파 데이터의 감정분류 및 정확도 향상에 관한 연구)

  • Lee, Hyunju;Shin, Dongil;Shin, Dongkyoo
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.27-36
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    • 2019
  • In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

A methodology for Identification of an Air Cavity Underground Using its Natural Poles (물체의 고유 Pole을 이용한 지하 속의 빈 공간 식별 방안)

  • Lee, Woojin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.566-572
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    • 2021
  • A methodology for the identification and coordinates estimation of air cavities under urban ground or sandy soil using its natural poles and natural resonant frequencies is presented. The potential of this methodology was analyzed. Simulation models of PEC (Perfect Electric Conductor)s with various shapes and dimensions were developed using an EM (Electromagnetic) simulator. The Cauchy method was applied to the obtained EM scattering response of various objects from EM simulation models. The natural poles of objects corresponding to its instinct characterization were then extracted. Thus, a library of poles can be generated using their natural poles. The generated library of poles provided the possibility of identifying a target by comparing them with the computed natural poles from a target. The simulation models were made assuming that there is an air cavity under urban ground or sandy soil. The response of the desired target was extracted from the electromagnetic wave scattering data from its simulation model. The coordinates of the target were estimated using the time delay of the impulse response (peak of the impulse response) in the time domain. The MP (Matrix Pencil) method was applied to extract the natural poles of a target. Finally, a 0.2-m-diameter spherical air cavity underground could be estimated by comparing both the pole library of the objects and the calculated natural poles and the natural resonant frequency of the target. The computed location (depth) of a target showed an accuracy of approximately 84 to 93%.

Efficient CT Image Denoising Using Deformable Convolutional AutoEncoder Model

  • Eon Seung, Seong;Seong Hyun, Han;Ji Hye, Heo;Dong Hoon, Lim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.3
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    • pp.25-33
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    • 2023
  • Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

Comparison of the acoustical performance of auditoria by shapes using acoustic simulation and listening tests (시뮬레이션과 청감실험을 통한 공연장 형태별 음향성능 비교분석)

  • Chanwoo Kang;Chan-Hoon Haan
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.3
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    • pp.189-202
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    • 2023
  • In this study, the acoustic performance was analyzed by architectural shapes of the hall. There are four architectural shapes of halls. They are rectangular, horseshoe, surround, and fan-shape. Eight acoustic parameters were used to determine the acoustic performance. These are RT60, EDT, C80, BQI, LF, Gmid, G125 and ITDG. First, measurement data of famous concert halls around the world were analyzed. The correlation coefficient R was obtained by regression analysis of the relationship between the subjective ranking of the halls and the acoustic parameters. It was found that BQI, G, and ITDG have higher correlation coefficients R. Also the average of acoustic parameters for each architectural shape were obtained. The total acoustic performance for each shape was calculated by using the correlation coefficient R as a weight for each acoustic parameters. As a result, rectangular halls and horseshoe halls showed good acoustical performances. Second, 3D models of each architectural shape were created and acoustic simulation had been performed. The simulation was performed by creating 3D models of each four shapes of concert halls with the same volume and sound absorption coefficient. Listening test was carried out using the sound source which is created from impulse responses of 3D model. As a result, rectangular hall and horseshoe hall showed the best performance however surround hall and fan-shaped hall showed relatively poor performance.

Comparison of brain wave values in emotional analysis using video (영상을 이용한 감정분석에서의 뇌파 수치 비교)

  • Jae-Hyun Jo;Sang-Sik Lee;Jee-Hun Jang;Jin-Hyoung Jeong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.6
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    • pp.519-525
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    • 2023
  • The human brain constantly emits electrical impulses, which is called brain waves, and brain waves can be defined as the electrical activity of the brain generated by the flow of ions generated by the biochemical interaction of brain cells. There is a study that emotion is one of the factors that can cause stress. Brain waves are the most used in the study of emotions. This paper is a study on whether emotions affect stress, and showed two images of fear and joy to four experimenters and divided them into three stages before, during, and after watching. As a measurement tool, brain waves at the positions of Fp1 and Fp2 were measured using the NeuroBrain System, a system that can automate brain wave measurement, analysis, brain wave reinforcement, and suppression training with remote control. After obtaining the brain wave data for each emotion, the average value was calculated and the study was conducted. As for the frequency related to stress, the values of Alpha and SMR, Low Beta, and High Beta were analyzed. Brainwave analysis affects stress depending on the emotional state, and "fear" emotions cause anxiety by raising Beta levels, resulting in higher Mind Stress levels, while "joy" emotions lower Beta levels, resulting in a significant drop in Mind Stress.

The Measurement Algorithm for Microphone's Frequency Character Response Using OATSP (OATSP를 이용한 마이크로폰의 주파수 특성 응답 측정 알고리즘)

  • Park, Byoung-Uk;Kim, Hack-Yoon
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.2
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    • pp.61-68
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    • 2007
  • The frequency response of a microphone, which indicates the frequency range that a microphone can output within the approved level, is one of the most significant standards used to measure the characteristics of a microphone. At present, conventional methods of measuring the frequency response are complicated and involve the use of expensive equipment. To complement the disadvantages, this paper suggests a new algorithm that can measure the frequency response of a microphone in a simple manner. The algorithm suggested in this paper generates the Optimized Aoshima's Time Stretched Pulse(OATSP) signal from a computer via a standard speaker and measures the impulse response of a microphone by convolution the inverse OATSP signal and the received by the microphone to be measured. Then, the frequency response of the microphone to be measured is calculated using the signals. The performance test for the algorithm suggested in the study was conducted through a comparative analysis of the frequency response data and the measures of frequency response of the microphone measured by the algorithm. It proved that the algorithm is suitable for measuring the frequency response of a microphone, and that despite a few errors they are all within the error tolerance.

Development of 3D Viewer for Tree Cavity using Pulse Ultrasound (펄스 초음파를 이용한 수목 공동부 3D 구현 프로그램 제작)

  • Son, Jungmin;Kang, Sunghoon;Moon, Jongwook;Yoon, Seokkyu;Park, Jikoon
    • Journal of the Korean Society of Radiology
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    • v.15 no.2
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    • pp.265-271
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    • 2021
  • The pattern of the tree's internal swelling depends on many causes. Since it is difficult to detect these various causes of swelling with a general method, if the state of swelling for a long time cannot be confirmed, serious damage to the trees may occur due to enlargement of the swelling area. In the method of acquiring a tree tomography image, an impulse passing through the tree is generated by tapping the sensor with a rubber mallet, and the moving speed is recorded. In this paper, to measure cracks, cavities, and swelling due to physical damage, we developed a 3D viewer that can know the internal state of a tree using a tree cross-section image acquired from Arbotom to determine the degree of swelling inside the tree. Based on this, we tried to present data that can be referred to when surgical operation of trees is required. In order to acquire a tomographic image of a tree, 6 sensors were attached to the three Yangpala and Maple trees, and a 1 m-long tree was measured using the Arbotom program, and a 3D image was implemented through the 3D Viewer created using MATLAB. In addition to simply acquiring images, the cross-sectional length and volume of the tree were measured. In the actually produced 3D Viewer, the length of the part where the swelling of the maple tree occurred was 33.12 cm, and the swelling of the yangpala tree was measured as 21.41 cm. The volume of the maple tree was measured to be 78.832 ㎤. As a result of comparing the cross-sectional image of the Arbotom and the 3D image, the same result as the real aspect of the tree was obtained, so it can be judged that the reliability of the manufactured software is also secured, and data to be applied to the surgical tree operation through the created Viewer is provided. It is believed that the damage will be minimized.