• Title/Summary/Keyword: spectral measures

Search Result 128, Processing Time 0.031 seconds

Characterization of intrinsic molecular structure spectral profiles of feedstocks and co-products from canola bio-oil processing: impacted by source origin

  • Alessandra M.R.C.B., de Oliveira;Peiqiang, Yu
    • Animal Bioscience
    • /
    • v.36 no.2
    • /
    • pp.256-263
    • /
    • 2023
  • Objective: Feed molecular structures can affect its availability to gastrointestinal enzymes which impact its digestibility and absorption. The molecular spectroscopy-attenuated total reflectance Fourier transform infrared vibrational spectroscopy (ATR-FTIR) is an advanced technique that measures the absorbance of chemical functional groups on the infrared region so that we can identify and quantify molecules and functional groups in a feed. The program aimed to reveal the association of intrinsic molecular structure with nutrient supply to animals from canola feedstocks and co-products from bio-oil processing. The objective of this study was to characterize special intrinsic carbohydrate and protein-related molecular structure spectral profiles of feedstock and co-products (meal and pellets) from bio-oil processing from two source origins: Canada (CA) and China (CH). Methods: The samples of feedstock and co-products were obtained from five different companies in each country arranged by the Canola Council of Canada (CCC). The molecular structure spectral features were analyzed using advanced vibrational molecular spectroscopy-ATR-FTIR. The spectral features that accessed included: i) protein-related spectral features (Amide I, Amide II, α-helix, β-sheet, and their spectral intensity ratios), ii) carbohydrate-related spectral features (TC1, TC2, TC3, TC4, CEC, STC1, STC2, STC3, STC4, TC, and their spectral intensity ratios). Results: The results showed that significant differences were observed on all vibrationally spectral features related to total carbohydrates, structural carbohydrates, and cellulosic compounds (p<0.05), except spectral features of TC2 and STC1 (p>0.05) of co-products, where CH meals presented higher peaks of these structures than CA. Similarly, it was for the carbohydrate-related molecular structure of canola seeds where the difference between CA and CH occurred except for STC3 height, CEC and STC areas (p>0.05). The protein-related molecular structures were similar for the canola seeds from both countries. However, CH meals presented higher peaks of amide I, α-helix, and β-sheet heights, α-helix:β-sheet ratio, total amide and amide I areas (p<0.05). Conclusion: The principal component analysis was able to explain over 90% of the variabilities in the carbohydrate and protein structures although it was not able to separate the samples from the two countries, indicating feedstock and coproducts interrelationship between CH and CA.

Average spectral acceleration: Ground motion duration evaluation

  • Osei, Jack Banahene;Adom-Asamoah, Mark
    • Earthquakes and Structures
    • /
    • v.14 no.6
    • /
    • pp.577-587
    • /
    • 2018
  • The quantitative assessment of the seismic collapse risk of a structure requires the usage of an optimal intensity measure (IM) which can adequately characterise the severity of the ground motion. Research suggests that the average spectral acceleration ($Sa_{avg}$) may be an efficient and sufficient alternate IM as compared to the more traditional first mode spectral acceleration, $Sa(T_1)$, particularly during seismic collapse risk estimation. This study primarily presents a comparative evaluation of the sufficiency of the average spectral acceleration with respect to ground motion duration, and secondarily assesses the impact of ground motion duration on collapse risk estimation. By assembling a suite of 100 historical ground motions, incremental dynamic analysis of 60 different inelastic single-degree-of-freedom (SDF) oscillators with varying periods and ductility capacities were analysed, and collapse risk estimates obtained. Linear regression models are used to comparatively quantify the sufficiency of $Sa_{avg}$ and $Sa(T_1)$ using four significant duration metrics. Results suggests that an improved sufficiency may exist for $Sa_{avg}$ when the period of the SDF system increases, particularly beyond 0.5, as compare to $Sa(T_1)$. In reference to the ground motion duration measures, results indicated that the sufficiency of $Sa_{avg}$ is more sensitive to significant duration definitions that consider almost the full wave train of an accelerogram ($SD_{a5-95}$ and $SD_{v5-95}$). In order to obtain a reduced variability of the collapse risk estimate, the 5-95% significant duration metric defined using the Arias integral ($SD_{a5-95}$) should be used for seismic collapse risk estimation in conjunction with $Sa_{avg}$.

Spectral Analysis of On-the-go Soil Strength Sensor Data (이동식 토양 강도 센서 데이터 주파수 분석)

  • Chung, Sun-Ok;Suduth, Kenneth A.;Tan, Jinglu
    • Journal of Biosystems Engineering
    • /
    • v.33 no.5
    • /
    • pp.355-361
    • /
    • 2008
  • As agricultural machinery has become larger and tillage practices have changed in recent decades, compaction as a result of wheel traffic and tillage has caused increasing concern. If strategies to manage compaction, such as deep tillage, could be applied only where needed, economic and environmental benefits would result. For such site-specific compaction management to occur, compacted areas within fields must be efficiently sensed and mapped. We previously developed an on-the-go soil strength profile sensor (SSPS) for this purpose. The SSPS measures within-field variability in soil strength at five soil depths up to 50 cm. Determining the variability structure of SSPS data is needed for site-specific field management since the variability structure determines the required intensity of data collection and is related to the delineation of compaction management zones. In this paper, soil bin data were analyzed by a spectral analysis technique to determine the variability structure of the SSPS data, and to investigate causes and implications of this variability. In the soil bin, we observed a repeating pattern due to soil fracture with an approximate 12- to 19-cm period, especially at the 10-cm depth, possibly due to cyclic development of soil fracture on this interval. These findings will facilitate interpretation of soil strength data and enhance application of the SSPS.

MUSIC-based Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors Using Flux Signal

  • Youn, Young-Woo;Yi, Sang-Hwa;Hwang, Don-Ha;Sun, Jong-Ho;Kang, Dong-Sik;Kim, Yong-Hwa
    • Journal of Electrical Engineering and Technology
    • /
    • v.8 no.2
    • /
    • pp.288-294
    • /
    • 2013
  • The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

Bayesian approach for the accuracy evaluating of the seismic demand estimation of SMRF

  • Ayoub Mehri Dehno;Hasan Aghabarati;Mehdi Mahdavi Adeli
    • Earthquakes and Structures
    • /
    • v.26 no.2
    • /
    • pp.117-130
    • /
    • 2024
  • Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

A Study on the Unsupervised Change Detection for Hyperspectral Data Using Similarity Measure Techniques (화소간 유사도 측정 기법을 이용한 하이퍼스펙트럴 데이터의 무감독 변화탐지에 관한 연구)

  • Kim Dae-Sung;Kim Yong-Il
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
    • /
    • 2006.04a
    • /
    • pp.243-248
    • /
    • 2006
  • In this paper, we propose the unsupervised change detection algorithm that apply the similarity measure techniques to the hyperspectral image. The general similarity measures including euclidean distance and spectral angle were compared. The spectral similarity scale algorithm for reducing the problems of those techniques was studied and tested with Hyperion data. The thresholds for detecting the change area were estimated through EM(Expectation-Maximization) algorithm. The experimental result shows that the similarity measure techniques and EM algorithm can be applied effectively for the unsupervised change detection of the hyperspectral data.

  • PDF

A Speech Waveform Forgery Detection Algorithm Based on Frequency Distribution Analysis (음성 주파수 분포 분석을 통한 편집 의심 지점 검출 방법)

  • Heo, Hee-Soo;So, Byung-Min;Yang, IL-Ho;Yu, Ha-Jin
    • Phonetics and Speech Sciences
    • /
    • v.7 no.4
    • /
    • pp.35-40
    • /
    • 2015
  • We propose a speech waveform forgery detection algorithm based on the flatness of frequency distribution. We devise a new measure of flatness which emphasizes the local change of the frequency distribution. Our measure calculates the sum of the differences between the energies of neighboring frequency bands. We compare the proposed measure with conventional flatness measures using a set of a large amount of test sounds. We also compare- the proposed method with conventional detection algorithms based on spectral distances. The results show that the proposed method gives lower equal error rate for the test set compared to the conventional methods.

Performance Comparison for Objective Measures of Speech Quality Evaluation in PCS Wireless Telephone Network (PCS 이동전화망에서의 객관적인 음질평가척도별 성능비교)

  • Kim Nag-Cheol;Kim Kwang-Soo;Jung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • spring
    • /
    • pp.48-51
    • /
    • 1999
  • 본 연구에서는 PCS 이동전화의 객관적 통화품질평가 척도개발을 위한 기초연구로 기존의 CD(Cepstral Distance), MSD (Mel Spectral Distance), BSD(Bark Spectral Distance), PSQM (Perceptual Speech Quality Measure) 척도를 적용하여 그 성능을 비교 분석하였다. 이 척도들을 실제환경에서 수집된 PCS 음성데이터에 대해서 적용하였고 이 결과치와 청취자들의 평가 반응에 의해 얻어진 MOS 결과치와의 상관성을 조사하였다. 실험 결과, BSD와 PSQM 척도의 상관성이 0.81, 0.84로 나타나 CD, MSD보다 성능이 더 우수함을 보였다.

  • PDF

IMAGE CLASSIFICATION OF HIGH RESOLTION MULTISPECTRAL IMAGERY VIA PANSHARPENING

  • Lee, Sang-Hoon
    • Proceedings of the KSRS Conference
    • /
    • 2008.10a
    • /
    • pp.18-21
    • /
    • 2008
  • Lee (2008) proposed the pansharpening method to reconstruct at the higher resolution the multispectral images which agree with the spectral values observed from the sensor of the lower resolution values. It outperformed over several current techniques for the statistical analysis with quantitative measures, and generated the imagery of good quality for visual interpretation. However, if a small object stretches over two adjacent pixels with different spectral characteristics at the lower resolution, the pixels of the object at the higher resolution may have different multispectral values according to their location even though they have a same intensity in the panchromatic image of higher resolution. To correct this problem, this study employed an iterative technique similar to the image restoration scheme of Point-Jacobian iterative MAP estimation. The effect of pansharpening on image segmentation/classification was assessed for various techniques. The method was applied to the IKONOS image acquired over the area around Anyang City of Korea.

  • PDF

Performance Comparison of Objective Measures for Speech Quality for Evaluation in CDMA Mobile Telephone (CDMA 이동전화 통화품질평가를 위한 객관적 음질평가척도별 성능 비교)

  • 이준희;김광수;윤정오
    • Proceedings of the Korea Society for Industrial Systems Conference
    • /
    • 2001.05a
    • /
    • pp.256-260
    • /
    • 2001
  • 본 논문에서는 디지털 이동전화(CDMA) 채널환경을 통과한 왜곡된 전화음성에 대해 객관적 음질평가 척도의 개발을 위한 기초 연구로서 기존의 CD(Cepstral Distance), MSD(Mel Spectral Distance), BSD(Bark Spectral Distance), Modified BSD, PSQM(Perceptual Speech Quality Measure)를 대상으로 객관척도 알고리즘을 성능평가 하였다. 이 척도들은 실제 이동전화 환경에서 수집된 PCS 음성데이터에 대해서 적용하였으며 이 결과치를 주관적 음질평가 방법인 MU와 상관성을 비교 조사하였다. 실험 결과, BSD와 MBSD, 그리고 PSQM 척도의 상관성이 각각 0.80, 0.85, 0.84로 나타났으며 CD, MSD 보다 성능이 상대적으로 더 우수함을 보였다.

  • PDF