Algorithms Implemented for Cancer Gene Searching and Classifications

Understanding the gene expression is an important factor to cancer diagnosis. One target of this understanding is implementing cancer gene search and classification methods. However, cancer gene search and classification is a challenge in that there is no an obvious exact algorithm that can be implemented individually for various cancer cells. In this paper a research is con-ducted through the most common top ranked algorithms implemented for cancer gene search and classification, and how they are implemented to reach a better performance. The paper will distinguish algorithms implemented for Bio image analysis for cancer cells and algorithms implemented based on DNA array data. The main purpose of this paper is to explore a road map towards presenting the most current algorithms implemented for cancer gene search and classification

Low-cost deep learning UAV and Raspberry Pi solution to real time pavement condition assessment

In this thesis, a real-time and low-cost solution to the autonomous condition assessment of pavement is proposed using deep learning, Unmanned Aerial Vehicle (UAV) and Raspberry Pi tiny computer technologies, which makes roads maintenance and renovation management more efficient and cost effective. A comparison study was conducted to compare the performance of seven different combinations of meta-architectures for pavement distress classification. It was observed that real-time object detection architecture SSD with MobileNet feature extractor is the best combination for real-time defect detection to be used by tiny computers. A low-cost Raspberry Pi smart defect detector camera was configured using the trained SSD MobileNet v1, which can be deployed with UAV for real-time and remote pavement condition assessment. The preliminary results show that the smart pavement detector camera achieves an accuracy of 60% at 1.2 frames per second in raspberry pi and 96% at 13.8 frames per second in CPU-based computer

The Effect of MHD on a Longitudinal Flow of a Fractional Maxwell Fluid between Two Coaxial Cylinders

     قمنا في هذا البحث بحل معادلة مائع ماكسويل التفاضلية ذات الرتبة الكسرية .كان الحل بصيغة دالة ميتاج- لفلر (Mettag-Leffler) . في حالة  فان حلول مائع ماكسويل غير الكسرية حصلنا عليها كحالة محددة من الحل العام.  اخيراً ، تاثير المعلمات المختلفة في حقل السرعة واجهاد القص تم تحليلها من خلال رسم السرعة واجهاد القص.      In this paper fractional Maxwell fluid equation has been solved. The solution is in the Mettag-Leffler form. For  the corresponding solutions for ordinary Maxwell fluid are obtained as limiting case of general solutions. Finally, the effects of different parameters on the velocity and shear stress profile are analyzed through plotting the velocity and shear stress profile

Development of a secure monitoring framework for optical disaggregated data centres

Data center (DC) infrastructures are a key piece of nowadays telecom and cloud services delivery, enabling the access and storage of enormous quantities of information as well as the execution of complex applications and services. Such aspect is being accentuated with the advent of 5G and beyond architectures, since a significant portion of the network and service functions are being deployed as specialized virtual elements inside dedicated DC infrastructures. As such, the development of new architectures to better exploit the resources of DC becomes of paramount importanceThe mismatch between the variability of resources required by running applications and the fixed amount of resources in server units severely limits resource utilization in today's Data Centers (DCs). The Disaggregated DC (DDC) paradigm was recently introduced to address these limitations. The main idea behind DDCs is to divide the various computational resources into independent hardware modules/blades, which are mounted in racks, bringing greater modularity and allowing operators to optimize their deployments for improved efficiency and performance, thus, offering high resource allocation flexibility. Moreover, to efficiently exploit the hardware blades and establish the connections across them according to upper layer requirements, a flexible control and management framework is required. In this regard, following current industrial trends, the Software Defined Networking (SDN) paradigm is one of the leading technologies for the control of DC infrastructures, allowing for the establishment of high-speed, low-latency optical connections between hardware components in DDCs in response to the demands of higher-level services and applications. With these concepts in mind, the primary objective of this thesis is to design and carry out the implementation of the control of a DDC infrastructure layer that is founded on the SDN principles and makes use of optical technologies for the intra-DC network fabric, highlighting the importance of quality control and monitoring. Thanks to several SDN agents, it becomes possible to gather statistics and metrics from the multiple infrastructure elements (computational blades and network equipment), allowing DC operators to monitor and make informed decisions on how to utilize the infrastructure resources to the greatest extent feasible. Indeed, quality assurance operations are of capital importance in modern DC infrastructures, thus, it becomes essential to guarantee a secure communication channel for gathering infrastructure metrics/statistics and enforcing (re-)configurations, closing the full loop, then addressing the security layer to secure the communication channel by encryption and providing authentication for the server and the client

The linguistic structure in the “Dafatir al-Warraq” by Jalal Bargas the Notebooks of the Papermaker novel between the act of notation and the speech of thresholds

This study explores the subject of linguistic structure and text thresholds in Jalal Barjas\u27s novel Dafatir al-Warraq 2020. The novel creates a memorization that makes the narrative language based on a philosophical context of the text thresholds. This crafted a ground for inquiries that the structure of the work evoked from the painful reality we live in today. The language of the narration and its thresholds have taken a mediating role in combining the other elements. Although it was divided against itself, a division that reflects the schizophrenia of the hero and his loss of the correct path. Hence, the study aims to evaluate the language of narration in the light of taking the act of narrative writing as an approach to presenting the story. This led to narrating the novel in the form of notebooks once, and the form of threshold narration (textual threshold) again in its external and internal dimensions. This calls for revealing the regulating relationship of the multiple narrative textual thresholds employed by the novel. The study used the concepts of the narrative method to approach this problem. Among the most prominent findings of the study is that the language of narration was based on the data of what was recorded in the characters notebooks and an influential factor in the constructive narrative of the novel, especially at the level of event and time. This was accompanied by a mature dialogue between the content of the work and its multiple textual thresholds in its external and internal dimensions

Impediments of Total Quality Management Application at Higher Education Institutions

The study aimed to identify the impact of total quality management(TQM) application obstacles on total quality management level application at Jordanian private universities through the identification of  trends in the study sample of constraints of total quality management application, and the level of total quality management application. To achieve the objectives of the study, the researcher developed a questionnaire for the detection of Obstacles of total quality management application (top management obstacles, human resources obstacles, financial resources obstacles, educational technology obstacles, relation with society obstacles, and organizational culture obstacles ) and the level of total quality management. The study sample consisted of  (234 ) academic deans and department chairs at Jordanian private universities.  The sample was selected randomly, and in light of this, data was collected and analyzed using the statistical package for social sciences (SPSS).   The most important findings and conclusions of the research are: 1-       The arithmetic mean of  the estimates of academic deans and department chairs at Jordanian private universities towards the obstacles of total quality management application were high. 2-       The arithmetic mean of  the estimates of academic deans and department chairs at Jordanian private universities towards total quality management application were moderate. 3-       The organizational culture obstacles were ranked first in the impact on the level of total quality management application, it interpreted (36%) of the variance in the level of total quality management application. Keywords: Total Quality Management Obstacles , Total Quality Management Application,  Jordanian Private Universities

Toni Morrison's The Bluest Eye As a Prose Version of T. S. Eliot's The Waste Land

This paper tries to explain the intertextuality between Toni Morrison's The Bluest Eye and T.S Eliot's The Waste Land. The study discusses characters, settings, allusions, events, and themes in both of these literary works to affirm that The Bluest Eye is a prose version of The Waste Land. While Eliot criticizes the ideology of European people, Morrison criticizes the ideology of White Americans who cause pain and suffering for the Blacks. She highlights African Americans' trauma of oppression, and the spiritual decadence of society. She dramatizes and criticizes the social, cultural and racial injustice that dehumanize Black people. Key Words Toni Morrison; T.S Eliot; Intertextuality; Fragmentation; Rebirth

An Organizational Development Assessment Tool for the Jordanian Civil Society Context

Over the last decade, humanitarian and development work has expanded to increasingly complex environments where the number of people in need rises indefinitely, while resources are either inadequate, or remain too scarce, to meet their needs. With donors demanding more measurable results, more robust monitoring, and more detailed data, these trends challenge civil society organizations (CSOs) to improve their performance and work with greater effectiveness and efficiency

A model to enhance the atrial fibrillations’ risk detection using deep learning

Atrial fibrillation (AF) is a complex arrhythmia linked to a variety of common cardiovascular illnesses and conventional cardiovascular risk factors. Although awareness and improved detection of AF have improved over the last decade as the incidence and prevalence of AF has increased, current trends in using machine learning approaches to diagnose AF are still lacking in precision. To determine the true nature of the Electrocardiography (ECG) signal segments, a Convolutional Neural Network (CNN) model was employed to discover hidden information. Fully Connected (FC) layers were then utilized to categorize the ECG data segments as normal or abnormal. The suggested algorithm's findings were compared to state-of-the-art arrhythmia identification algorithms in the literature for the MIT-BIH ECG database. The methodology proved not only to yield high classification performance (98.5%) but also low processing computational advantage where the CNN was the most accurate algorithm used for atrial fibrillation detection hence. To conclude the findings of the research, a model was prepared to test the accuracy of the most common ML algorithms used for AF detection. After comparing the results of the experiment, it was clear that CNN algorithm is the best approach compared to Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)