|Commenced in January 2007||Frequency: Monthly||Edition: International||Paper Count: 15|
The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.
Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-ofsample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.
This research paper was aimed to examine the relationship between visitors’ attitude towards the service marketing mix and visitors’ frequency of visit to Bangpu Recreation Centre. Based on a large and uncalculated population, the number of samples was calculated according to the formula to obtain a total of 385 samples. In collecting the samples, systematic random sampling was applied and by using of a Likert five-scale questionnaire for, a total of 21 days to collect the needed information. Mean, Standard Deviation, and Pearson’s basic statistical correlations were utilized in analyzing the data. This study discovered a high level of visitors’ attitude product and service of Bangpu Recreation Centre, price, place, promotional activities, people who provided service and physical evidence of the centre. The attitude towards process of service was discovered to be at a medium level. Additionally, the finding of an examination of a relationship between visitors’ attitude towards service marketing mix and visitors’ frequency of visit to Bangpu Recreation Centre presented that product and service, people, physical evidence and process of service provision showed a relationship with the visitors’ frequency of visit to the centre per year.
Medical image is an integral part of e-health care and e-diagnosis system. Medical image watermarking is widely used to protect patients’ information from malicious alteration and manipulation. The watermarked medical images are transmitted over the internet among patients, primary and referred physicians. The images are highly prone to corruption in the wireless transmission medium due to various noises, deflection, and refractions. Distortion in the received images leads to faulty watermark detection and inappropriate disease diagnosis. To address the issue, this paper utilizes error correction code (ECC) with (8, 4) Hamming code in an existing watermarking system. In addition, we implement the high complex ECC on a graphics processing units (GPU) to accelerate and support real-time requirement. Experimental results show that GPU achieves considerable speedup over the sequential CPU implementation, while maintaining 100% ECC efficiency.
This paper gives a consideration of the achievement of productive level parallel programming skills, based on the data of the graduation studies in the Polytechnic University of Japan. The data show that most students can achieve only parallel programming skills during the graduation study (about 600 to 700 hours), if the programming environment is limited to GPGPUs. However, the data also show that it is a very high level task that a student achieves productive level parallel programming skills during only the graduation study. In addition, it shows that the parallel programming environments for GPGPU, such as CUDA and OpenCL, may be more suitable for parallel computing education than other environments such as MPI on a cluster system and Cell.B.E. These results must be useful for the areas of not only software developments, but also hardware product developments using computer technologies.
Previous the 3D model texture generation from multi-view images and mapping algorithms has issues in the texture chart generation which are the self-intersection and the concentration of the texture in texture space. Also we may suffer from some problems due to the occluded areas, such as inside parts of thighs. In this paper we propose a texture mapping technique for 3D models using multi-view images on the GPU. We do texture mapping directly on the GPU fragment shader per pixel without generation of the texture map. And we solve for the occluded area using the 3D model depth information. Our method needs more calculation on the GPU than previous works, but it has shown real-time performance and previously mentioned problems do not occur.
A one-step conservative level set method, combined with a global mass correction method, is developed in this study to simulate the incompressible two-phase flows. The present framework do not need to solve the conservative level set scheme at two separated steps, and the global mass can be exactly conserved. The present method is then more efficient than two-step conservative level set scheme. The dispersion-relation-preserving schemes are utilized for the advection terms. The pressure Poisson equation solver is applied to GPU computation using the pCDR library developed by National Center for High-Performance Computing, Taiwan. The SMP parallelization is used to accelerate the rest of calculations. Three benchmark problems were done for the performance evaluation. Good agreements with the referenced solutions are demonstrated for all the investigated problems.
With the popularity of the multi-core and many-core architectures there is a great requirement for software frameworks which can support parallel programming methodologies. In this paper we introduce an Eclipse toolkit, JConqurr which is easy to use and provides robust support for flexible parallel progrmaming. JConqurr is a multi-core and many-core programming toolkit for Java which is capable of providing support for common parallel programming patterns which include task, data, divide and conquer and pipeline parallelism. The toolkit uses an annotation and a directive mechanism to convert the sequential code into parallel code. In addition to that we have proposed a novel mechanism to achieve the parallelism using graphical processing units (GPU). Experiments with common parallelizable algorithms have shown that our toolkit can be easily and efficiently used to convert sequential code to parallel code and significant performance gains can be achieved.