Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

 The current work utilizes the peel and pulp of the Iraqi eggplant to remove Alizarin Red S dye (ARS) from an aqueous solution. The isotherms of adsorption were studied and the factors that the effect them: temperature, the effect of surface nature and effect of ionic strength. The isotherms of adsorption of ARS on the peel were found obey the Freundlich, equation, but the isotherms of adsorption on the pulp were found to obey the Langmuir equation. At different temperatures, the adsorption process was studied, and it was found that when the temperature decreased, the adsorption increased. Based on the data we obtained in practice, the thermodynamic functions (∆H, ∆G, ∆S) were calculated as the process was exothermic, spontan

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

The establishment of a high quality service in oral health care achieved by a member of dental professional is an important feature of any system of peer review in dentistry. This protocol attempts to discuss two crucial elements (I) suitability and feasibility of treatment modality and (II) quality of treatment performed to Iraqi patients. The Iraq endodontic society is designing a standardized protocol for endodontic treatment following the quality guidelines of European society of Endodontology (2006) to meet the highest standard of care generally given by competent practitioners. The Iraqi endodontic society has the expertise and professional responsibility clinically relevant to empower the dental profession through creating significan

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th