In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

The aim of t his p aper is t o const ruct t he (k,r)-caps in t he p rojective 3-sp ace PG(3,p ) over Galois field GF(4). We found t hat t he maximum comp let e (k,2)-cap which is called an ovaloid, exist s in PG(3,4) when k = 13. Moreover t he maximum (k,3)-cap s, (k,4)-cap s and (k,5)-caps.

في هذا البحث نحاول تسليط الضوء على إحدى طرائق تقدير المعلمات الهيكلية لنماذج المعادلات الآنية الخطية والتي تزودنا بتقديرات متسقة تختلف أحيانا عن تلك التي نحصل عليها من أساليب الطرائق التقليدية الأخرى وفق الصيغة العامة لمقدرات K-CLASS. وهذه الطريقة تعرف بطريقة الإمكان الأعظم محدودة المعلومات" LIML" أو طريقة نسبة التباين الصغرى" LVR" والتي تمثل حسب الصيغة (14.2) الوجه الآخر لطريقة الLIML والتي تشتهر في تقدير معلمات معادل

BACKGROUND: CRC is one of the most common cancers in the world. K-ras is proto-oncogene with GTPase activity that is lost when the gene is mutated. Analysis of K-ras mutational status is very important for CRC treatment, being the most important predictors of resistance to targeted therapy. OBJECTIVE: This study aims to determine the frequency and spectrum of K-ras mutation among Iraqi patients with sporadic CRC. PATIENTS, MATERIALS AND METHODS: This study enrolled 35 cases with sporadic CRC; their clinicopathological parameters were analyzed. The FFPE blocks were used for DNA extraction; PCR amplification of K-ras gene and hybridization of allele-specific oligoprobes were performed. The assay covers 29 mutations in the K-ras gene (codons 1

في هذا البحث نحاول تسليط الضوء على إحدى طرائق تقدير المعلمات الهيكلية لنماذج المعادلات الآنية الخطية والتي تزودنا بتقديرات متسقة تختلف أحيانا عن تلك التي نحصل عليها من أساليب الطرائق التقليدية الأخرى وفق الصيغة العامة لمقدرات K-CLASS. وهذه الطريقة تعرف بطريقة الإمكان الأعظم محدودة المعلومات "LIML" أو طريقة نسبة التباين الصغرى"LVR

          Using sodium4-((4,5-diphenyl-imidazol-2-yl)diazenyl)-3-hydroxynaphthalene-1-sulfonate (SDPIHN) as a chromogenic reagent in presence of non-ionic surfactant (Triton x-100) to estimate the chromium(III)  ion if the wavelength of this reagent 463 nm to form a dark greenish-brown complex in wavelength 586 nm at pH=10,the complex was stable for longer than 24 hours. Beer's low, molar absorptivity 0.244×10⁴L.mol^-1.cm^-1, and Sandal's sensitivity 0.021 µg/cm² are all observed in the concentration range 1-11 µg/mL. The limits of detection (LOD) and limit of quantification (LOQ), respectively, were 0.117 µg/mL and 0.385µg/mL. (mole ratio technique, job's method) were employed to

The researcher aims to Diagnose the reality of research variables, strategic leadership and decision support systems, and their impact on crisis management in the General Company for Steel Industries because of their important role in preventing crises and reducing their occurrence for the research company in particular and other companies in general affiliated with the Ministry of Industry and Minerals, as well as clarifying theoretical concepts of research variables As it included the answer to questions related to the research problem, including (Is there an impact of the strategic leadership in managing crises if decision support systems are used), and the researcher adopted the descriptive and analytical approach in its comp

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener