Theory of selective excitation in Stimulated Raman Scattering

A semiclassical model is used to investigate the possibility of selectively exciting one of two closely spaced, uncoupled Raman transitions. The duration of the intense pump pulse that creates the Raman coherence is shorter than the vibrational period of a molecule (impulsive regime of interaction). Pulse shapes are found that provide either enhancement or suppression of particular vibrational excitations.Comment: RevTeX4,10 pages, 5 figures, submitted to Phys.Rev.

Classification of closed and open shell pistachio nuts using principal component analysis of impact acoustics

An algorithm was developed to separate pistachio nuts with closed-shells from those with open-shells. It was observed that upon impact on a steel plate, nuts with closed-shells emit different sounds than nuts with open-shells. Two feature vectors extracted from the sound signals were melcepstrum coefficients and eigenvalues obtained from the principle component analysis of the autocorrelation matrix of the signals. Classification of a sound signal was done by linearly combining feature vectors from both mel-cepstrum and PCA feature vectors. An important property of the algorithm is that it is easily trainable. During the training phase, sounds of the nuts with closed-shells and open-shells were used to obtain a representative vector of each class. The accuracy of closed-shell nuts was more than 99% on the test set

Detection of fungal damaged popcorn using image property covariance features

Covariance-matrix-based features were applied to the detection of popcorn infected by a fungus that causes a symptom called " blue-eye" . This infection of popcorn kernels causes economic losses due to the kernels' poor appearance and the frequently disagreeable flavor of the popped kernels. Images of kernels were obtained to distinguish damaged from undamaged kernels using image-processing techniques. Features for distinguishing blue-eye-damaged from undamaged popcorn kernel images were extracted from covariance matrices computed using various image pixel properties. The covariance matrices were formed using different property vectors that consisted of the image coordinate values, their intensity values and the first and second derivatives of the vertical and horizontal directions of different color channels. Support Vector Machines (SVM) were used for classification purposes. An overall recognition rate of 96.5% was achieved using these covariance based features. Relatively low false positive values of 2.4% were obtained which is important to reduce economic loss due to healthy kernels being discarded as fungal damaged. The image processing method is not computationally expensive so that it could be implemented in real-time sorting systems to separate damaged popcorn or other grains that have textural differences. © 2012 Elsevier B.V

Cepstrum based feature extraction method for fungus detection

In this paper, a method for detection of popcorn kernels infected by a fungus is developed using image processing. The method is based on two dimensional (2D) mel and Mellin-cepstrum computation from popcorn kernel images. Cepstral features that were extracted from popcorn images are classified using Support Vector Machines (SVM). Experimental results show that high recognition rates of up to 93.93% can be achieved for both damaged and healthy popcorn kernels using 2D mel-cepstrum. The success rate for healthy popcorn kernels was found to be 97.41% and the recognition rate for damaged kernels was found to be 89.43%. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE)

Classification of closed- and open-shell pistachio nuts using voice-recognition technology

An algorithm using speech recognition technology was developed to distinguish pistachio nuts with closed shells from those with open shells. It was observed that upon impact with a steel plate, nuts with closed shells emit different sounds than nuts with open shells. Features extracted from the sound signals consisted of mel-cepstrum coefficients and eigenvalues obtained from the principle component analysis (PCA) of the autocorrelation matrix of the sound signals. Classification of a sound signal was performed by linearly combining the mel-cepstrum and PCA feature vectors. An important property of the algorithm is that it is easily trainable, as are most speech-recognition algorithms. During the training phase, sounds of nuts with closed shells and with open shells were used to obtain a representative vector of each class. During the recognition phase, the feature vector from the sample under question was compared with representative vectors. The classification accuracy of closed-shell nuts was more than 99% on the validation set, which did not include the training set

Detection of insect damaged wheat kernels by impact acoustics

Insect damaged wheat kernels (IDK) are characterized by a small hole bored into the kernel by insect larvae. This damage decreases flour quality as insect proteins interfere with the bread-making biochemistry and insect fragments are very unsightly. A prototype system was set up to detect IDK by dropping them onto a steel plate and processing the acoustic signal generated when kernels impact the plate. The acoustic signal was processed by three different methods: 1) modeling of the signal in the time domain, 2) computing time domain signal variances in short time windows, and 3), analysis of the frequency spectra magnitudes. Linear discriminant analysis was used to select a subset of features and perform classification. 98% of un-damaged kernels and 84.4% of IDK were correctly classified. © 2005 IEEE

Detection of underdeveloped hazelnuts from fully developed nuts by impact acoustics

Shell-to-kernel weight ratio is a vital measurement of quality in hazelnuts as it helps to identify nuts that have underdeveloped kernels. Nuts containing underdeveloped kernels may contain mycotoxin-producing molds, which are linked to cancer and are heavily regulated in international trade. A prototype system was set up to detect underdeveloped hazelnuts by dropping them onto a steel plate and recording the acoustic signal that was generated when a kernel hit the plate. A feature vector comprising line spectral frequencies and time-domain maxima that describes both the time and frequency nature of the impact sound was extracted from each sound signal and used to classify each nut by a support-vector machine. Experimental studies demonstrated accuracies as high as 97% in classifying hazelnuts with underdeveloped kernels

Detection of empty hazelnuts from fully developed nuts by impact acoustics

Shell-kernel weight ratio is the main determinate of quality and price of hazelnuts. Empty hazelnuts and nuts containing undeveloped kernels may also contain mycotoxin producing molds, which can cause cancer. A prototype system was set up to detect empty hazelnuts by dropping them onto a steel plate and processing the acoustic signal generated when kernels impact the plate. The acoustic signal was processed by five different methods: 1) modeling of the signal in the time domain, 2) computing time domain signal variances in short time windows, 3) analysis of the frequency spectra magnitudes, 4) maximum amplitude values in short time windows, and 5) line spectral frequencies (LSFs). Support Vector Machines (SVMs) were used to select a subset of features and perform classification. 98% of fully developed kernels and 97% of empty kernels were correctly classified

Isotopic analysis of faunal material from South Uist, Western Isles, Scotland

This paper reports on the results from stable isotope analysis of faunal bone collagen from a number of Iron Age and later sites on the island of South Uist, in the Western Isles, Scotland. This preliminary investigation into the isotopic signatures of the fauna is part of a larger project to model the interaction between humans, animals, and the broader environment in the Western Isles. The results demonstrate that the island fauna data fall within the range of expected results for the UK, with the terrestrial herbivorous diets of cattle and sheep confi rmed. The isotopic composition for pigs suggests that some of these animals had an omnivorous diet, whilst a single red deer value might be suggestive of the consumption of marine foods, such as by grazing on seaweed. However, further analysis is needed in order to verify this anomalous isotopic ratio