In this paper, we develop a non-visual automatic wrapper to extract data records from search engine results pages which contain important information for computer users. Our wrapper consists of a series of data filter to detect and remove irrelevant data from the web page. In the filtering stages, we incorporate two main ALGORITHMs which are able to check the similarity of data records and to detect and extract the correct data region based on their component sizes. To evaluate the performance of our ALGORITHM, we carry out experimental and deletion tests. Experimental tests show that our wrapper outperforms the existing state of the art wrappers such as ViNT and DEPTA. Deletion studies by replacing our novel techniques with state of the art conventional techniques show that our wrapper design is efficient and could robustly extract data records from search engine results pages. With the speed advantages, our wrapper could be beneficial in processing large amount of web sites data, which could be helpful in meta search engine development.

Ontology MATCHING is an essential aspect of the Semantic Web with a goal of finding alignments among the entities of given ontologies. Ontology MATCHING is a necessary step for establishing interoperation and knowledge sharing among Semantic Web applications. In this study we present an ALGORITHM and a tool developed based on this ALGORITHM to find correspondences among entities of input ontologies. The proposed ALGORITHM uses a new lexical similarity measure and also utilizes structural information of ontologies to determine their corresponding entities. The lexical similarity measure generates a bag of words for each entity based on its label and description information. The structural approach creates a grid for each node in the ontologies. The combination of lexical and structural approaches creates the similarity matrix between the source and target ontologies. The proposed ALGORITHM was tested on a well known benchmark and also compared to other ALGORITHMs presented in the literature. Our experimental results show the proposed ALGORITHM is effective and outperforms other ALGORITHMs.

The traditional method for studying non-stationary signals is spectrogram based on the short-time Fourier transform (STFT). The well known limitation of the STFT is the inherent trade-off between time and frequency resolution. The Wigner-Ville (WV) distribution has the best time-frequency resolution, but its draw back is generating cross-terms. The MATCHING pursuit (MP) distribution based on using the Gaussian atom is always positive, does not include crossterm, and has convenient resolution. In this paper, we have shown in addition to the known properties, the MP distribution can also remove the additive noise inherently. On the other words, we are able to remove the noise just by limiting the ALGORITHM iterations and without paying any additional cost. Although the MP distribution based on using the Gaussian atoms is always positive and it has convenient resolution, according to the MP the time marginal and the frequency marginal will not be obtained accurately. In this paper, it has been shown that by implementing the minimum cross entropy (MCE) technique according to the MP distribution as a priory positive distribution, the new extracted distribution has the most similarity to the MP distribution and it also satisfies the correct time and frequency marginal.

Image MATCHING is known as a vital process in digital photogrammetry. Despite development of many image MATCHING ALGORITHMs, this process still has some difficulties in close range photogrammetry, due to geometric changes which are made by changes in viewpoint. In this paper, an effective and robust image MATCHING approach is presented for wide-baseline image MATCHING. In the proposed method, in order to perform MATCHING operation, after extracting blob-like features in base and input image, using SIFT detector, an elliptical region is constructed for each feature. In the following, in order to control the created geometric changes resulted from changes in the imaging perspective, parameters of this ellipse are calculated by using second moment matrix. In addition, descriptor for each feature is constructed by normalization of the respective ellipse to a circular region with a constant radius. Finally, by applying nearest neighbor method, MATCHING process is done and mismatches are eliminated by implementing epipolar constraint based on RANSAC method. Test results on different close range image datasets, beside the increased accuracy rate of 3 to 8 percent, represents significant function of the proposed method since the results are two times higher than the results finalized using the standard SIFT method.

Spatial data collection is a time/money consuming task in activities related to geospatial sciences. Spatial data integration increases the efficiency of spatial data through cost reduction. Therefore, developing MATCHING ALGORITHMs is of vital importance in spatial data integration, data updating and data accuracy enhancement. The main objective of this research is to design and develop a semi-automatic vector MATCHING system. The developed system simulates human brain process in its MATCHING procedure. Priliminary results are promissing. Further reaseaches are required to examine the system efficiency.

Background: The aim of the present study was to evaluate how left ventricular twist and torsion are associated with sex between sex groups of the same age. Materials and Methods: In this analytical study, twenty one healthy subjects were scanned in left ventricle basal and apical short axis views to run the block MATCHING ALGORITHM; instantaneous changes in the base and apex rotation angels were estimated by this ALGORITHM and then instantaneous changes of the twist and torsion were calculated over the cardiac cycle. Results: The rotation amount between the consecutive frames in basal and apical levels was extracted from short axis views by tracking the speckle pattern of images. The maximum basal rotation angle for men and women were-6. 94° ± 1. 84 and 9. 85° ± 2. 36 degrees (p-value = 0. 054), respectively. Apex maximum rotation for men was-8. 89° ± 2. 04 and for women was 12. 18° ± 2. 33 (p-value < 0. 05). The peak of twist angle for men and women was 16. 78 ± 1. 83 and 20. 95± 2. 09 degrees (p-value < 0. 05), respectively. In men and women groups, the peak of calculated torsion angle was 5. 49° ± 1. 04 and 7. 12± 1. 38 degrees (p-value < 0. 05), respectively. Conclusion: The conclusion is that although torsion is an efficient parameter for left ventricle function assessment, because it can take in account the heart diameter and length, statistic evaluation of the results shows that among men and women LV mechanical parameters are significantly different. This study was mainly ascribed to the dependency of the torsion and twist on patient sex.

Introduction: During recent years, evaluating the relation between mechanical properties of the arterial wall and cardiovascular diseases has been of great importance. On the other hand, motion estimation of the arterial wall using a sequence of noninvasive ultrasonic images and convenient processing methods might provide useful information related to biomechanical indexes and elastic properties of the arteries and assist doctors to discriminate between healthy and diseased arteries. In the present study, a block MATCHING based ALGORITHM was introduced to extract radial motion of the carotid artery wall during cardiac cycles.Materials and Methods: The program was implemented to the consecutive ultrasonic images of the common carotid artery of 10 healthy men and maximum and mean radial movement of the posterior wall of the artery was extracted. Manual measurements were carried out to validate the automatic method and results of two methods were compared.Results: Paired t-test analysis showed no significant differences between the automatic and manual methods (P>0.05). There was significant correlation between the changes in the instantaneous radial movement of the common carotid artery measured with the manual and automatic methods (with correlation coefficient 0.935 and P<0.05).Conclusion: Results of the present study showed that by using a semi-automated computer analysis method, with minimizing the user interfere and no attention to the user experience or skill, arterial wall motion in the radial direction can be extracted from consecutive ultrasonic frames.