Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Image and video compression play a major role in the world today, allowing the storage and transmission of large multimedia content volumes. However, the processing of this information requires high computational resources, hence the improvement of the computational performance of these compression algorithms is very important. The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based compression algorithm for multimedia contents, namely images, achieving high compression ratios, maintaining good image quality, Rodrigues et al. [2008]. However, in comparison with other existing algorithms, this algorithm takes some time to execute. Therefore, two parallel implementations for GPUs were proposed by Ribeiro [2016] and Silva [2015] in CUDA and OpenCL-GPU, respectively. In this dissertation, to complement the referred work, we propose two parallel versions that run the MMP algorithm in CPU: one resorting to OpenMP and another that converts the existing OpenCL-GPU into OpenCL-CPU. The proposed solutions are able to improve the computational performance of MMP by 3 and 2:7 , respectively. The High Efficiency Video Coding (HEVC/H.265) is the most recent standard for compression of image and video. Its impressive compression performance, makes it a target for many adaptations, particularly for holoscopic image/video processing (or light field). Some of the proposed modifications to encode this new multimedia content are based on geometry-based disparity compensations (SS), developed by Conti et al. [2014], and a Geometric Transformations (GT) module, proposed by Monteiro et al. [2015]. These compression algorithms for holoscopic images based on HEVC present an implementation of specific search for similar micro-images that is more efficient than the one performed by HEVC, but its implementation is considerably slower than HEVC. In order to enable better execution times, we choose to use the OpenCL API as the GPU enabling language in order to increase the module performance. With its most costly setting, we are able to reduce the GT module execution time from 6.9 days to less then 4 hours, effectively attaining a speedup of 45 .

Contributions to HEVC Prediction for Medical Image Compression

Medical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which allow easier and more accurate medical diagnosis. However, this increase in resolution demands a growing amount of data to be stored and transmitted. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compression where either near-lossless or lossless coding is required. In this dissertation, two different approaches to improve lossless coding of volumetric medical images, such as Magnetic Resonance and Computed Tomography, were studied and implemented using the latest standard High Efficiency Video Encoder (HEVC). In a first approach, the use of geometric transformations to perform inter-slice prediction was investigated. For the second approach, a pixel-wise prediction technique, based on Least-Squares prediction, that exploits inter-slice redundancy was proposed to extend the current HEVC lossless tools. Experimental results show a bitrate reduction between 45% and 49%, when compared with DICOM recommended encoders, and 13.7% when compared with standard HEVC.

Impact of financial crisis on earnings management in listed companies of Portugal and UK

Firm’s financial information is essential to stakeholders’ decision making. Although not always financial statements show the firm’s real image. This study examines listed firms from Portugal and UK. Firms have different purposes to manipulate earnings: some strive for influencing investors’ perception about a particular company, some try to provide better position for gaining finance from credit institutions or paying less tax to tax authorities. Usually, this behaviour is induced when firms have financial problems. Consequently, the study also aims to see the impact of financial crisis on earnings management. We try to answer question how does extent of firms’ involvement in earnings management change when the world undergoes financial crisis. Furthermore, we also compare two countries with different legal forces in terms of quality of accounting to see the main differences. We used a panel data methodology to analyse financial data from 2004 till 2014 of listed firms from Portugal and UK. Beneish (1999) model was applied to categorize manipulator and non-manipulator firms. Analysing accounting information according to Beneish’s ratios, findings suggest that financial crisis had certain impact on firms’ tendency to manipulate financial results in UK although it is not statistically significant. Moreover, besides the differences between Portugal and UK, results contradict the common view of legal systems’ quality, as UK firms tend to apply more accounting techniques for manipulation than the Portuguese ones. Our main results also confirm that some UK firms manipulate ratios of receivables’ days, asset quality index, depreciation index, leverage, sales and general administrative expenses whereas Portuguese firms manipulate only receivables’ days. Finally, we also find that the main reason to manipulate results is not to influence the cost of obtained funds neither to minimize tax burden since net profit does not explain the ratios used in the Beneish model. Results suggest that the main concern to listed firms manipulate results is to influence financial investors perception.