Source signature encoding of a vertical source array to separate the emitted direct wave from its ghost

Marine air-gun sources can be sequence-encoded by firing their individual elements independently over a short period of time. Using near-orthogonal firing sequences, whose crosscorrelation is minimal, as encoding sequences for multiple sets of air-gun sources, enables us to exploit their orthogonality as a separation feature. We find that, by distributing air guns over depths from 5 to 30 m, firing sequences can be designed whose direct, down-going wavefield is close to orthogonal to its source-ghost wavefield. The fundamentally new aspect of this approach is that the source-ghost signal is no longer just a time-delayed, opposite-polarity version of the down-going wavefield, but due to the different air-gun depths results in a different source sequence. This enables the consideration of the ghost wavefield as a separate source. We generate a set of such firing sequences by minimizing the crosscorrelation of these wavefields and optimizing their respective autocorrelations to achieve sharp peaks. The obtained, optimized firing sequences are then used for marine seismic source encoding. By adapting a multifrequency algorithm originally developed for simultaneous source separation, we determine that the ghost-source wavefield can be separated as a separate source from the direct, down-going wavefield.

Multitudinous of remedial medical image using stationary wavelet transform

Image fusion is becoming more popular in various field nowadays. The quality of accuracy and perception has been achieved with this con-cept. The field that is in urgent need of more contrast images and quality output of body organs image reproduction is medicine. This paper proposes the concept of introducing the image fusion in the area of body imaging to get a more accurate and contrast images for the identifi-cation of the tumor or any other mal-functionalities in the human body. The image fusion is enhanced with the choice of more efficient and contrast uplifting technique called stationary wavelet form. This technique accepts the input of two different perceptive images of the finicky region and enhances their details in the resulting image. The advantageous part of the technique outputs the more detailed edge separation feature which further more allows the fast diagnosis of the any defect prevailing currently in the place subjected to the imaging test. This technique also paves the way to get the more reliable and meticulous result in the future when the world starts embracing the advantage of automation in the field of medicine.

Study of the interface between Na-rich and Li-rich phases in a Na-inserted spinel Li4Ti5O12 crystal for an electrode of a sodium-ion battery

Na-rich phase growth and phase-separation feature in the Na-inserted spinel Li4Ti5O12 negative electrode was revealed by XRD and TEM imaging.

Ensemble Classification System for Scientific Chart Recognition from PDF Files

Portable Document Format (PDF) is the most frequently used universal document format on the Internet and E-Publishing. Wide usage of PDF files has increased the need of conversion tools that convert PDF file content to text or HTML formats. A PDF converter can be categorized into two domains, namely, text recognition and graphics recognition. This paper focus on graphic recognition, especially chart type identification, which is concerned with developing algorithms that has the ability to determine the type of a given chart image from a PDF file. In the proposed system, initially an enhanced connected component and statistical feature based method is used to separate the chart region from other regions. The chart region is then analyzed and grouped as either 2-dimensional or 3-dimensional chart. After separating the graphic component from the text components, feature extraction is performed. The features can be grouped as object features, texture features and shape features. The combined feature vector is then classified using ensemble classification system. Experimental results show that the chart separation, feature extraction and ensemble classification models significantly improve the quality of chart identification.

Perceptual Dimensions Underlying Vowel Lipreading Performance

This study was concerned with the extraction, description, and verification of visual perceptual features underlying vowel lipreading performance. Ten viewers with normal hearing rated the visual similarity of pairs of 15 vowels and diphthongs presented in an /h_g/ context by four speakers. Multidimensional scaling techniques were used to extract potential perceptual features which were then labeled by the experimenters. The resulting perceptual dimensions were correlated with physical measurements of lip shape to evaluate the adequacy of the feature labels. The results indicated that the traditional extended-rounded vowel feature and a vertical lip separation feature were the characteristics most prominent in judging the stimuli. In addition, a feature related to overall area of maximum lip opening and two features unique to diphthong perception were tentatively identified.