The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to results obtained in this paper, KCHS needs less search time than others algorithms and gives very acceptable performance quality.
With the massive presence of the critical approaches &, artistical School, movements, methods, Concepts, & theories, which came to take its chance from arts in general view & the plastic arts in special view. The Searches of fine arts & what this methods present from excitement become the point for many questions, & go to the purposes to be useful. For the artistic Work to come out in aesthetic image, especially on the subject of reading& reception, & entering it into layout of multiple relationships, for the artistic Work to be more simulation of the appearances of the things & interpreted it in Accor.
Dance to aesthetic that Limited by the new method. With those Innovative Visions, & Composite Sy
Basic orientation is to look at identifying conceptual perspective to market self-research and descriptive, as has the marketing theme for the same attention in the practical side before endo scopic In recent years, is marketing an integrated and holistic included many areas not limited to the marketing of goods and services, and even included the marketing of religion, politics and individuals for themselves, as the awareness and concepts that seep into the soul of man from its inception until his arrival to the stage of owning a level of skills or expertise, scientific or all of those things degrees mixed with ambition and aspiration for self-realization takes way to search for opportunities or created, often observe individual
... Show MoreTyphoid fever (TF) is a systemic infection caused by Salmonella Typhi (Salmonella Enterica) transmitted through contaminated water, food, or contact with infected individuals. In various infectious diseases, blood viscosity (BV) is affected by changes in hemoglobin concentrations and acute phase reactants. Inflammatory responses can lead to elevated plasma protein levels and further affect BV. This study aimed to investigate BV changes in patients with acute TF. A cross-sectional study was performed involving 55 patients with acute TF compared to 38 healthy controls. BV and inflammatory parameters were measured in both groups. TF patients showed reduced blood cells compared to healthy controls (p=0.001). Additionally, plasma total protein (
... Show More<span>Deepfakes have become possible using artificial intelligence techniques, replacing one person’s face with another person’s face (primarily a public figure), making the latter do or say things he would not have done. Therefore, contributing to a solution for video credibility has become a critical goal that we will address in this paper. Our work exploits the visible artifacts (blur inconsistencies) which are generated by the manipulation process. We analyze focus quality and its ability to detect these artifacts. Focus measure operators in this paper include image Laplacian and image gradient groups, which are very fast to compute and do not need a large dataset for training. The results showed that i) the Laplacian
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
... Show More