In this paper, we introduce an exponential of an operator defined on a Hilbert space H, and we study its properties and find some of properties of T inherited to exponential operator, so we study the spectrum of exponential operator e^T according to the operator T.
This paper constructs a new linear operator associated with a seven parameters Mittag-Leffler function using the convolution technique. In addition, it investigates some significant second-order differential subordination properties with considerable sandwich results concerning that operator.
Abstract: This study aims to investigate the backscattering electron coefficient for SixGe1-x/Si heterostructure sample as a function of primary electron beam energy (0.25-20 keV) and Ge concentration in the alloy. The results obtained have several characteristics that are as follows: the first one is that the intensity of the backscattered signal above the alloy is mainly related to the average atomic number of the SixGe1-x alloy. The second feature is that the backscattering electron coefficient line scan shows a constant value above each layer at low primary electron energies below 5 keV. However, at 5 keV and above, a peak and a dip appeared on the line scan above Si-Ge alloy and Si, respectively, close to the interfacing line
... Show MoreIn this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.
Additionally Maximum likelihood estimation method
... Show MoreBackground: Colorectal cancer (CRC) is a major killer, and nonalcoholic fatty liver disease (NAFLD) affects almost one-quarter of the global population. The aim of the study is to Investigate the correlation between nonalcoholic fatty liver disease (NAFLD) and an increased risk of colorectal cancer (CRC), as well as the relationship between liver function enzymes and specific serum biomarkers in CRC patients with NAFLD. Methods: A case-control study involving 60 participants was conducted from February to August 2022. The patients with colon cancer were examined at Baghdad Medical City's Al-Amal Hospital for Radiation and Nuclear Medicine and Oncology Teaching Hospital, and blood samples were taken. Thirty patients with NAFLD who ha
... Show MoreMany letters and theses written on the subject of consensus, as well as in measurement,
But we tried to address a topic of consensus
Building a blind measuring guide.
We have tried to explain the meaning of convening, then the statement of consensus in language and terminology and then the statement of measurement
Also, we have shown the types of consensus mentioned by the jurists, and this is how much was in the first topic, either
The second section included the statement of the doctrines of the blind in the matter, and then the evidence of each doctrine and discussed.
We followed it with the most correct opinion statement and concluded the research with some of the conclusions we reached through
search.
ان الغرض من هذا البحث هو المزج بين القيود الضبابية والاحتمالية. كما يهدف الى مناقشة اكثر حالات مشكلات البرمجة الضبابية شيوعا وهي عندما تكون المشكلة الضبابية تتبع دالة الانتماء مرة دالة الاتنماء المثلثية مرة اخرى، من خلال التطبيق العملي والتجريبي. فضلا عن توظيف البرمجة الخطية الضبابية في معالجة مشكلات تخطيط وجدولة الإنتاج لشركة العراق لصناعة الأثاث، وكذلك تم استخدام الطرائق الكمية للتنبؤ بالطلب واعتماده
... Show MoreThe aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).