This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise Jaccard index of the membership of the multipaths to their clusters. The multipaths generated by C2CM were transformed using the directional cosine transform (DCT) and the whitening transform (WT). The transformed dataset was clustered using SC and 3CAM-SC. The clustering performance was validated using the Jaccard index by comparing the reference multipath dataset with the calculated multipath clusters. The results show that the effectiveness of SC is similar to the state-of-the-art clustering approaches. However, 3CAM-SC outperforms SC in all channel scenarios. SC can be used in indoor scenarios based on accuracy, while 3CAM-SC is applicable in indoor and semi-urban scenarios. Thus, the clustering approaches can be applied as alternative clustering techniques in the field of channel modeling.
One hundred and eighty five urine samples were collected eight isolates (4.3%) were obtained and diagnosed as Staphylococcus aureus. Among 8 isolates, 5 (62.5%) S. aureus isolates were found to be enterotoxigenic, most of isolates produced at least two types of Staphylococcal enterotoxins (SEs). The production of enterotoxins in the presence or absence of Thymol extracts (aqueous and alcoholic) were estimated using a reversed passive latex agglutination (SET-RPLA) kit. The extracts reduced enterotoxin production compared with the control. Enterotoxin inhibition was observed for enterotoxin C production at minimal inhibitory concentrations (MIC) at 400 µg/ml, whereas production of enterotoxins A, B, and
... Show MoreJoining tissue is a growing problem in surgery with the advancement of the technology and more precise and difficult surgeries are done. Tissue welding using laser is a promising technique that might help in more advancement of the surgical practice. Objectives: To study the ability of laser in joining tissues and the optimum parameters for yielding good welding of tissues. Methods: An in-vitro study, done at the Institute of Laser, Baghdad University during the period from October 2008 to February 2009. Diode and Nd-YAG lasers were applied, using different sessions, on sheep small intestine with or without solder to obtain welding of a 2-mm length full thickness incision. Different powers and energies were used to get maximum effect. Re
... Show MorePeriodontitis is a chronic inflammatory disease resulted from aggravated immune response to a dysbiotic subgingival microbiota of a susceptible host. Consequences of periodontitis are not only limited to the devastating effect on the oral cavity but extends to affect general health of the individual and also exerts economic burdens on the health systems worldwide. Despite these serious outcomes of periodontitis; however, they are avoidable by early diagnosis with proper preventive measures or non-invasive interventions at earlier stages of the disease. Clinically, diagnosis of periodontitis could be overlooked due to certain limitations of the conventional diagnostic methods such as periodontal charting and radiographs. Utilization of re
... Show MoreCompressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp
... Show MoreThe aim of this research is to find out why some matrix verbs are no longer complemented by the two types of infinitive clauses as it is the case in Elizabethan English . At that time (when Shakespeare was writing ), the same matrix verb triggers the two types of infinitive clauses as its complex transitive complementation .Such free variation is not possible in Present –Day English . In this corpus – based study , it is shown that the choice of the form of the infinitive clause is not free; there are certain syntactic ,sem- antic constraints that dete, - infinitive.
This study deals with the estimation of critical load of unidirectional polymer matrix composite plates by using experimental and finite element techniques at different fiber angles and fiber volume fraction of the composite plate.
Buckling analysis illustrated that the critical load decreases in nonlinear relationship with the increase of the fiber angle and that it increases with the increase of the fiber volume fraction.
The results show that the maximum value of the critical load is (629.54 N/m) at (q = 0°) and (Vf = 40 %) for the finite element method, while the minimum val
... Show MoreThis paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreGenerally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co
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