Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and estimation. The current method (visual quantification methods) of image quantification is time-consuming and cumbersome, and manual measurement is imprecise because of the natural differences among human eyes’ abilities. Subsequently, objective outcome evaluation can obviate the drawbacks of the current methods and facilitate recording for documenting function and research purposes. To achieve a fast and valuable objective estimation of fluorescence in each image, an algorithm was designed based on machine vision techniques to extract the targeted objects in images that resulted from confocal images and then estimate the covered area to produce a percentage value similar to the outcome of the current method and is predicted to contribute to sustainable biotechnology image analyses by reducing time and labor consumption. The results show strong evidence that t-designed objective algorithm evaluations can replace the current method of manual and visual quantification methods to the extent that the Intraclass Correlation Coefficient (ICC) is 0.9.
In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic
... Show MoreIraq has confronted a huge political transformations after 2003 which resembled and presented rapid changes from totalitarian regime into democracy's system , this phenomenon has become a feature embodied in a new political system, specifically is being a price for previous deprivation and despotism .So that, the nature of political work has been changed as a result of practicing new democratic values ,but the real challenges appeared by depending on the conformity and political compromise in dealing with all of crises and problems in the political life .
The future of political work in this nascent democracy could be prepared according to fulfillment an active doings values stretched on national unity and forgiveness from one side ,t
The provision of electric power is necessary for the advancement of the country's economy. It is the main engine of the economy and its various activities. It is an indicator of social welfare and it is considered as the basic pillars for achieving sustainable development (economic, social, environmental and institutional) by raising the levels of performance and meeting local needs. The problem of research was the absence of a program to audit the performance of the electricity sector contributes to ensure the application of sustainable development. The research was based on the hypothesis that the preparation of a proposed program to audit the performance of the electricity sector contributes to the achievement of The researchers sough
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra
... Show MoreThis article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.
Municipal solid waste is one of the most important environmental problems in the world and is an important source of environmental pollution and contributes significantly to the pollution of the basic environmental elements of soil, water and air. The management of municipal waste in general is a process of monitoring, collection, treatment or recycling if possible or disposal of waste. This term is used for waste produced by some human activities. States provide this process to mitigate the negative effects of waste on the environment, health and appearance of the city. It is possible to find solutions to the problem of solid waste and make it an important source of income and contribute to securing employment oppor
... Show MoreThe research deals with metaphors as being one of the primary means used by Lyudmila Ulitskaya when writing the novel " Sincerely Yours Shurik ", to form diverse and multifaceted collective female images of representatives of the classic psychological patterns presented in the work. This research reflects the results of the study related to the work of Lyudmila Yevkinevna Ulitskaya, an actress of modern Russian prose. The novel "The Sincerely to You Shorek" is one of Ludmila Ulitskaya's creations (the year of writing - 2003), which, like her other works, is distinguished by a unique presentation style, rich vocabulary, lexical and semantic diversity, and a special style of writing. writer. The main objective of the research is to look at th
... Show MoreThere are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case com
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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