Transcribing Latin Manuscripts in Respect to Linguistics

Current text detection software, although can transcribe modern languages with high accuracy, has flaws detecting texts and transcribing original Latin manuscripts sufficiently. This paper proposes a general approach for transcribing Latin manuscripts in respect to linguistics and develops a system to transcribe Latin manuscripts containing intricate abbreviations, which combines basic object detection algorithms with linguistics. We used methods from image processing and made changes based on the characteristics of Latin.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Evaluating the Risk of Roof Fall in Phosphate Mines: Case Study of the Shanshuya Phosphate Mine in China

AbstractRoof fall in phosphate mines seriously endangers the safety of the mining activity. In this paper, the risk of roof fall occurring in phosphate mines is evaluated using the underground phosphate mine in Shanshuya, China, as an engineering background. The factors affecting roof fall in phosphate mines are analyzed, and an index system for evaluating the risk of roof fall in phosphate mine is established. Four evaluation models are employed to evaluate the risk of roof fall occurring: a set pair analysis model based on combination weights, a comprehensive fuzzy model based on hierarchical analysis, an approximately ideal ranking model based on entropy weight, and a gray relational analysis model. The evaluation results of the first two models are moderate risk with a bias toward intense risk. And the evaluation results of the last two models are slight risk with a bias toward moderate risk and moderate risk with a bias toward slight risk, respectively. The suitability of each of the evaluation models is analyzed which reveals that the evaluation results obtained using the different models are inconsistent. A combined evaluation method based on the four original evaluation models is subsequently proposed. Application of the combined evaluation method to the Shanshuya phosphate mine produces results that the roof fall risk is moderate with a bias toward slight risk. It is consistent with the actual situation in this phosphate mine. The results of the study can be used to provide technical support to engineers evaluating the risk of roof fall occurring in similar phosphate mines

A Microseismicity-Based Method of Rockburst Intensity Warning in Deep Tunnels in the Initial Period of Microseismic Monitoring

Rockburst disasters in deep tunnels cause serious casualties and economic losses. It is a great challenge to make a warning for rockbursts in geotechnical engineering. In this work, a microseismicity-based rockburst intensity warning method is proposed that is suitable for use in deep tunnels in the initial period of microseismic (MS) monitoring. The method first involves collecting information on a sample of no more than five cases. Then, the event to be analyzed is combined with the sample events and subjected to cluster analysis. Finally, a rockburst intensity warning is generated according to the results of the cluster analysis or after a second cluster analysis. It is a comprehensive, multi-parameter rockburst intensity warning method that only needs a few rockburst cases for input which makes it suitable in the initial period of MS monitoring. The method also incorporates the novel idea of a second cluster analysis. An engineering application based on deep tunnels in the Jinping II hydropower station in Sichuan Province, China, shows that the rockburst intensity warning results based on the proposed method agree well with the actual situations in four tests carried out. The method will enrich the techniques used to warn of rockbursts based on microseismicity

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data

Sidelobe Suppression with Resolution Maintenance for SAR Images via Sparse Representation

Severe sidelobe interference is one of the major problems with traditional Synthetic Aperture Radar (SAR) imaging. In the observation scene of sea areas, the number of targets in the observation scene is so small that targets can be regarded as sparse. Taking this into account, a method of sidelobe suppression, on the basis of sparsity constraint regularization, is proposed to reduce sidelobes of Gaofen-3 (GF-3) images in sea areas of the image domain. This proposed method has a prominent sidelobe suppression effect with resolution maintenance and without destruction of amplitude and phase information. This method can also be applied to SAR images of other satellites. In addition to the employment of peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) in evaluating sidelobe suppression level, AE (amplitude error) and PE (phase error) are firstly defined for the evaluation of amplitude and phase-preserving quality, respectively. Through the proposed method, AE and PE values are nearly unchanged and the PSLR and ISLR are significantly reduced. The method, as an important part of the quality-improvement project of GF-3, has been successfully applied to the sidelobe suppression of GF-3 data

General Signal Model for Multiple-Input Multiple-Output GMTI Radar

Multiple-input multiple-output (MIMO) ground moving target indication (GMTI) radar has been studied recently because of its excellent performance. In this paper, a general signal model is established for the MIMO GMTI radar with both fast-time and slow-time waveforms. The general signal model can be used to evaluate the performance of the MIMO GMTI radar with arbitrary waveforms such as the ideal orthogonal, code division multiple access (CDMA), frequency-division multiple access (FDMA), time division multiple access (TDMA), and Doppler division multiple access (DDMA) waveforms. We proposed a range-compensation method to eliminate the range-dependence of the FDMA waveforms. The simulation results indicate that the improved performance of FDMA waveforms is achieved utilizing the range-compensation method

Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm