Simulated Tornado Optimization

We propose a swarm-based optimization algorithm inspired by air currents of a tornado. Two main air currents - spiral and updraft - are mimicked. Spiral motion is designed for exploration of new search areas and updraft movements is deployed for exploitation of a promising candidate solution. Assignment of just one search direction to each particle at each iteration, leads to low computational complexity of the proposed algorithm respect to the conventional algorithms. Regardless of the step size parameters, the only parameter of the proposed algorithm, called tornado diameter, can be efficiently adjusted by randomization. Numerical results over six different benchmark cost functions indicate comparable and, in some cases, better performance of the proposed algorithm respect to some other metaheuristics.Comment: 6 pages, 15 figures, 1 table, IEEE International Conference on Signal Processing and Intelligent System (ICSPIS16), Dec. 201

A New Method For Digital Watermarking Based on Combination of DCT and PCA

In the digital watermarking with DCT method,the watermark is located within a range of DCT coefficients of the cover image. In this paper to use the low-frequency band, a new method is proposed by using a combination of the DCT and PCA transform. The proposed method is compared to other DCT methods, our method is robust and keeps the quality of cover image, also increases capacity of the watermarking.Comment: Telecommunications Forum Telfor (TELFOR), 2014 22n

Language and culture: the importance of cultural language to enhance the teaching and learning of Persian language in a Persian heritage language school

This research project tries to investigate how the integration of culture and language or Cultural Language can enhance the teaching and learning of the Persian language in a Persian Heritage Language school. Furthermore, it aims to investigate the relationship between Persian Heritage Language and its effect on conserving the cultural awareness of the second and third-generation Muslim Persian - British in London. In this project, I attempt to propose a new framework with a ‘cultural syllabus’ to be incorporated into language education to develop, preserve, and revitalize Persian language skills amongst the future Persian generation living abroad. In another word, my research is aiming to link the teaching of cultural matters with the Persian language to impact positively on the children’s general attainment in the Persian language. To do this, I started to conduct a participatory action research project through the lens of ethnography. I employed four main types of research methods and techniques: classroom observations, focus groups, feedback interviews or conversations and reflection sheets. Three groups of participants took part in this research. The main participants of the investigation were a group of 75 Persian-English bilinguals (boys 35 and girls 40; mean age: 10.3) who have been living in the UK for different lengths of time (mean: 6.9 years). The second group consisted of 5 monolingual Persian teachers in the UK. The third group of participants were sixteen Persian parents who were born in Persia and immigrated to the UK at different ages. The main areas of impact found in data extended to (a) teachers’ personal and professional development; and (b) impact on learners, parents, and the educational environment. In the light of the findings from this project, I found that cultural and Islamic elements with the Persian language should not remain separate entities and insisted that their integration can contribute towards a holistic approach to the teaching and learning of the Persian language. Hence, this research has given important support for the positive impact of cultural familiarity in the culturally-oriented syllabus for language learning enhancement in heritage language contexts. Furthermore, I found that heritage schools like IRIS School allow children a safe haven for exploring cultural and linguistic awareness

Convolutional Deblurring for Natural Imaging

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of Finite Impulse Response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the Point Spread Function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.Comment: 15 pages, for publication in IEEE Transaction Image Processin