The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m³  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45^o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45^o instelled  in the bottom of TESB of vertical SC. The TESB was

    The aim of this work, is to study color filming by using different intensities of fluorescent light, where we evaluate the capture image qualities for the RGB bands and component of L. And we study the relation between the means of RGBL values of the images as a function of the power of fluorescent light circuit . From the results, we show that the mean μ increases rapidly at low power values, then it will reach the stability at high power values.  

This research is based on the descriptive and analytical methodology. The importance of studying labor laws and labor unions in Japan between 1889 and 1946 constitutions is because Japan was out of a feudal phase, and had no idea about the factory system and industrialization in their modern sense before the Meiji era. Generally, its labor system used to be mostly familial, and the economic system was based on agriculture. This called for the enactment of legislations and laws appropriate for the coming phase in Meiji era. Thus, this paper examines the role of Meiji government in enacting labor legislations and laws when he came to power in 1896, and his new constitution in 1889 and the civil code of 1896. It further examines the way Mei

This study is concerned with the concept of offering a point of view as a narrative construction element, especially the element and point of view of the novel to the letter Alcinmatugrave both business taken from masterpieces and literary works in the foundation or set of cinema. On the whole, the narrator participate in mock narrative process and support the narrator visual image, especially stories that need to exist scenes prove added to the image that uses signs of reality to take those marks a new dimension not only across the image, but also the intervention of the narrator in the re-formation of this realism marks surrounding Palms perceived and visible and put markers regularly between what the narrative of privacy and image, fo

Background: The purpose of the study is to determine whether the pre-treatment clinical systemic variables and optical coherence tomographic (OCT) findings are associated with the subsequent response to the intravitreal Bevacisumab (IVB) in eyes with diabetic macular edema (DME).
Patients and Methods: 38 patients (45 eyes) with refractory diabetic macular edema. ; 16 females, 22 males and mean age was 57.5 year. All patients had DME not responded to other treatments. Complete eye examination; BCVA* (represented as LOGMAR for adequate statistical analysis), slitlamp exam, intraocular pressure measurement, stereoscopic biomicroscopy of the macula, and morphologic patterns of diabetic macular edema demonstra

Derivative spectrophotometry is one of the analytical chemistry techniques used
in the analysis and determination of chemicals and pharmaceuticals. This method is
characterized by simplicity, sensitivity and speed. Derivative of Spectra conducted
in several ways, including optical, electronic and mathematical. This operation
usually be done within spectrophotometer. The paper is based on form of a new
program. The program construction is written in Visual Basic language within
Microsoft Excel. The program is able to transform the first, second, third and fourth
derivatives of data and the return of these derivatives to zero order (normal plot).
The program was applied on experimental (trial) and reals values of su

The integral  breadth  method  has been utilized to analyse line

proIiles broadening and lattice strain of CaO at different temperatures

The effect of tcmperattre on crystallite size and strain has also been investigated  . The crystall i tes are found to be highly anisotropic even at high temperatures

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a