Integrated Framework for Proper Constructability in Bridges Using Value Engineering and Analytical Network Process 'ANP" (Analytical Study): إطار متكامل لتحسين إنشائية الكباري باستخدام الهندسة القيمية وعملية الشبكة التحليلية "ANP" (دراسة تحليلية)

Due to recent environmental and Political requirements, and regulations of the construction industry, in which bridges is one of its important category, deciding its proper constructability is becoming vital. Therefor the objective of this research is to develop a decision model for selecting proper constructability of green bridges constructions, the model was built based on analytical network process (the ANP) soft were program, integrated with value engineering approach. For this analytical study different parameters are identified and ranked to be implemented for the decision model developed on the biases of four surveying studies conducted in this study the results of these surveying's was be analyzed by using the statically analytical program; "SPSS". Model validation and reliability is carried out using the analytical network process (ANP) for statistically analysis using case study which is a cable bridge project constructed in Egypt. ANP proves to be an effective framework for assessing readiness to adopt and facilitating TQM. The result of the study illustrate that the proper constructability alternative in green bridge concept for this determinate project is the concrete box girder type, upon this there is a cost loss of $3, 500 per square meter, equivalent to 50% losses, respect to the life cycle cost this is due to did not using the best alternate of the estimated project. upon the possibility of applying this decision model to such studies of infrastructure projects, and with respect to the results gained; it is recommend to apply the ANP model with respect to VE procedures to bridges projects of all kinds and their determinants, as well as all other construction projects, especially national ones, in future studies, which allows decision- makers to make decisions that aim at the highest quality without any waste in unnecessary costs.

Hybrid Secure Model for Securing Data in The Cloud Computing System by Combining RSA, AES and CP-ABE: نموذج هجين آمن لحماية البيانات في الحوسبة السحابية بدمج RSA وAES وCP-ABE

The cloud healthcare system represents an important application for cloud computing, as it uses the cloud for the operations of storing patient medical data and sharing it between health care service providers and patients, making the security and privacy of e-health system data the main concern of researchers. This paper presents an integrated secure model for the healthcare system in cloud computing that achieves the security and confidentiality of data transferred through cloud computing, by combining the two algorithms AES and RSA with the access control algorithm CP-ABE in order to use the advantages of each of them, where the encryption process is done by a proposed algorithm which is based on the RSA algorithm, the XOR parameter, and the AES algorithm; the secrecy of the AES algorithm has been increased by generating a dynamic key, and the confidentiality of this key has been secured with two encryption levels, the first level using the CP-ABE algorithm and the second level using the RSA algorithm. The proposed model is characterized by meeting the requirements of access control, authentication, and verification for both the transmitter and the receiver, and the results of the application of this model proved its ability to meet the security requirements of the health care system in cloud computing with the lowest possible implementation time, as the execution times were at the transmitter's end (43.2, 43.83, 45.11, 48. 23, 50.77, 52.16, 57.95, 63.2, and 63.35)ms for variable file sizes (37, 50, 100, 150, 200, 256, 512, 1000, and 1024)KB, respectively. The results also showed its superiority in terms of security requirements in cloud computing and the necessary implementation times on studied reference models.

Applying Transfer Learning Using DenseNet121 in Radiographic Image Classification: تطبيق التعلم بالنقل باستخدام شبكة DenseNet121 في تصنيف الصور الشعاعية

The study aims to apply one of the fully connected convolutional neural networks, DenseNet121 network, to a data sample that includes a large group of radiographs through transfer learning technology. Radiography technology is a very important technique in the medical community to detect diseases and abnormalities that may be present, but the interpretation of these images may take a long time and it is subject to error by radiologists who are exposed to external practical factors (such as fatigue resulting from working for long hours, or exhaustion, or thinking about other life matters). To assist radiologists, we have worked on developing a diagnostic model with the help of a deep learning technique to classify radiographic images into two classes: (Normal and Abnormal images), by transferring the selected deep convolutional neural network between a large group of available networks that we studied on the basis of the regions that possibly abnormalities provided by the radiologists for the study sample. We also studied the feasibility of using the well-known VGG16 model on the same data sample and its performance through transfer learning technology and compared its results with the results of the DenseNet121 network. At the end of the research, we obtained a set of good results, which achieved a high diagnostic accuracy of 87.5% in some studied cases, using the DenseNet121 network model, which is considered satisfactory results in the case studied compared to the performance of other models. As for the VGG16 model, it did not give any of the satisfactory results in this field, the accuracy of the classification did not exceed 55% in most cases, and in only two cases it reached about 60% and 62%. The model presented during the research - DenseNet121 model - can be used in the diagnostic process and help in obtaining accurate results in terms of diagnostic results. As for the VGG16 model, it does not give satisfactory results according to the results also obtained during the research, so it is excluded in this type of applications.

Guiding Principles in The Study of Neighborhoods as a Basis for the city Formation and Its Development "Homs city as a case of study": المبادئ التوجيهية في دراسة المجاورات السكنية كأساس لتشكيل المدينة وتطوّرها "مدينة حمص كحالة دراسية"

The city has grown and developed with time over several eras, and at each stage different concepts were defined in city planning, such as the residential neighborhood theory that Berry identified and considered it as the smallest planning unit that contributes to the formation of the city. The concepts of residential neighborhood have developed by a number of planners and have social, economic and urban dimensions. It is essential that it cannot be ignored when developing any plan for neighborhoods or cities, but these dimensions have differed between countries and planners, and it was necessary to set some guidelines in their planning as a primary goal to show their role in the formation of cities as the smallest component in the city formation in order to avoid the many problems In the processes of urban, population and economic development in general. From this logic, the research dealt with a theoretical and analytical study of the theoretical concepts of residential neighborhoods for some planners and identifying the elements of residential neighborhoods and their basic components in order to reach an analytical approach to assess residential neighborhoods and determine the guidelines for their study. Then, some international, Arab and local experiences were studied according to those principles in order to draw some important results, and project them to the city of Homs to demonstrate the importance and role of residential neighborhoods as a basis for the formation and development of residential neighborhoods and cities. The guidelines necessary to be available in the study of residential neighborhoods were deduced, and by conducting a comparative approach between the research experiences, it was noted that the environmental and regional dimension was provided in most by 100%, as well as the availability of the appropriate radius by 90%, except that there are bicycles and pedestrians paths and the movement of people with special needs was 10% which needs to be developed and improved. The research recommends adoption the concluded guidelines because they include all urban and planning aspects and meet the resident social and economic needs and thus contribute to the city formation (urban, economic and social). The research also recommends following a basic idea in the study of the neighborhood so that it achieves the possibility of dividing it into residential groups that contain service centers according to radii suitable for the movement of the population on foot (between 400- 500 m) with securing an area for regional or city services, and attention to sustainability and the provision of the green element. And work to limit the movement of pedestrians according to special paths, taking into account the movement of people with special needs, and securing the necessary site coordination elements.

STUDY OF THE THERMAL EXPANSION COEFFICIENT OF SEVERAL SAND MIXTURES USED IN THE CASTING TECHNOLOGY: دراسة معامل التمدد الحراري لعدة خلائط من الرمال المستخدمة في تقنية الصب

The casting technology is one of the most important production processes, because of its special characteristics and features such as the ability to produce complex shapes and a wide range of compositions. This work aims to study several mixtures of sand with different structures in terms of permeability, strength, thermal expansion coefficient, comparing them, study the effect of the elements involved in the composition of these mixtures on those parameters, and create a database that can be used both in modeling processes or mold design, as when designing the sand mold The value of the sand expansion of the mold must be taken into account, otherwise the designer will face the problem of the possibility of exit some dimensions of the final product from the permissible range and thus rejecting the product, Or the product is undergone to deformations resulting from the expansion of mold sands, which must be avoided when designing the mold Knowing the characteristics of those sand mixtures helps the investor in choosing the most appropriate mixture for the required casting process in terms of engineering specifications or quantity, with the aim of less costly production by saving in choosing the most appropriate and least expensive sand mixture that serves the desired purpose.

Simulating NACA Equations Used in Optimizing Wind Turbine Blade Design: محاكاة معادلات NACA واستخدامها لتحسين تصميم شفرة العنفة الريحية

Aerodynamic scientists are interested in geometry definition and possible geometric shapes that would be useful in design. This paper illustrates a simulation of a NACA four digits airfoil blade profile using MATLAB. As airfoil design became more sophisticated, this basic approach has been modified to include additional variables, and suggestions for the chord line length at the root and at the end of the blade. as well as changes in the twisting angle of the blade and its thickness, this helps to reduce the weight of the blade significantly Simulating NACA equations is very useful in obtaining coordinates of airfoil curvature for the whole series of NACA four digits, which is very effective in optimizing blade design. In order to get an optimal operating performance and high efficiency for the airfoil, the blade surface must be smooth and does not suffer any discontinuities or undefined cases, which cause separation of the boundary layer during the airflow, and get as a result great energy losses. Therefore, the conditions for the continuity of the blade was extracted using mathematical analysis, so the air flow does not suffer any interruptions which reduce the efficiency. This enable us to determine the locations of the maximum thickness of the blade sections on the chord along the blade, in addition to specifying conditions for the chord line length at the root and at the end of the blade which keep the blade curvature continuous and doesn’t have any irregular points, which also facilities writing the necessary programs.

Modeling of Discrete Networked Control Systems in State Space for Electrical Power System with Time Delays: نمذجة نظم التحكم الشبكية المتقطعة في فضاء الحالة لنظام قدرة كهربائية مع وجود التأخيرات الزمنية

Electrical power systems distributed over wide geographical areas are exposed to a set of factors that affect their stability. The most important factors are the time delays between their subsystems. In this paper, a flexible modeling method was concluded consisting of a set of generalized rules and conditions that apply to any network controlled system to ensure its stability with time delays between the elements of the controlled network. In addition, a linear quadratic regulator (LQR) controller was implemented. The aim of the LQR controller is to reduce the negative impact of the time delay on the stability of the electrical power system. The study was applied to a networked electrical power system consisting of three-generation stations distributed in three separate geographical areas. Computer simulations using MATLAB showed a remarkable improvement in the stability of the discrete networked system through the speed of damping the vibrations in the system, and the system ability to be stable at certain limits of the time delay.

Designing a Virtual Platform for Modeling Nodes in Wireless Sensor Networks at the Central Processing Unit Level: تصميم منصة برمجية افتراضية لنمذجة العقد ضمن شبكات الحساسات اللاسلكية على مستوى وحدة المعالجة المركزية

Wireless sensor network simulation programs provide representation for an actual system, without needing to deploy real testbed which is highly constrained by the available budget, and the direct operations inside physical layer in most of these programs are hidden and work implicitly. This is what motivated us to build a kernel for a virtual simulation platform to be able to simulate protocol operations and algorithms at the node processing unit level, The proposed system aims to observe the execution of operations at the low level of the wireless sensor physical infrastructure with the ability to modify at this level. That give the improvers of wireless sensor nodes the ability to test their ideas without needing to use physical environment. We have built the functionality operations which are related to the platform kernel at several stages. We defined (as a first step) the essential operations inside a virtual microprocessor that uses a partial set pf MIPS instructions, and built the kernel of minimized virtual WSN simulator depending on the proposed microprocessor, that means we can add any number of nodes inside the GUI of the WSN simulator kernel, and these nodes use the proposed virtual microprocessor . Then we improved this platform by adding the instruction set of a real microprocessor that is used in wireless sensor network nodes. Finally, (and to ease and simplify the interaction operation between program GUI of the platform kernel and the user), we have built simplified compiler that allows user to deal with microprocessor GUI inside each node, and to clarify protocol and algorithm operations by a set of orders and functions without needing to deal with low level language (Assembly language) in a direct way. The simulation results have presented high flexibility and performance to this platform in observing the operation sequence inside wireless sensor nodes at assembly level, in addition to focus on some parameters that are related to microprocessor inside each node.

Sustainable Architectural Design of the Residential Compound Towers in Aleppo City Using the Genetic Algorithm: التصميم المعماري المستدام للأبراج السكنية التراكبية في مدينة حلب باستخدام الخوارزمية الجينية

This research aims to find innovative design solution to create sustainable compound residential towers in Aleppo city, for the reconstruction phase, by using the concept of sustainability and benefiting from natural energy sources. International organizations and many countries are interested in applying sustainable architecture standards, reducing emissions, mitigating pollution, and reducing long- term operating costs for buildings by making the most of natural resources. Tower buildings are among the most important design models that have been subject to the concepts of sustainability and their applications, due to their consumption of large amounts of energy. This research presents a study of a sustainable design for a residential compound tower, for the reconstruction phase in Aleppo city, using the genetic algorithm within the Grasshopper program. The tower design Idea depends on developing and linking the basic design idea of ​​the project with main design determinants such as dimensions, heights and other variables, including location and climatic characteristics, and then creating a barometric chart for these connections within the Grasshopper program. This chart links to the Galapagos tool, which is responsible for running the genetic algorithm. The random structure is generated when the algorithm started, and as a result of the cross- breeding, more advanced generations are created. The process continues to reach the most appropriate environmentally sustainable form to reduce the heat load acquired in summer. The model is evaluated environmentally using Ladybug simulation software, to provide solutions for modular residential towers that fit the local environment of Aleppo city. The results of the research showed that the solar heat load was reduced by adopting the genetic algorithm to find the most suitable configuration for the tower. The amount of reduction is 35% between the initial solutions and the final approved solution. The research also revealed that the use of green roofs reduces the heat load by 20%. The research also showed the effect of using shading facades. On the southern, western and eastern directions, the heat gain was reduced by 5%.

Comparison between the different Artificial Neural Network (ANN) accuracy in diagnosis of asthma: مقارنة بين اختلاف دقة الشبكات العصبية الاصطناعية في تشخيص مرض الربو

Asthma is a chronic disease that is caused by inflammation of airways. Diagnosis, predication and classification of asthmatic are one of the major attractive areas of research for decades by using different and recent techniques, however the main problem of asthma is misdiagnosis. This paper simplifies and compare between different Artificial Neural Network techniques used to solve this problem by using different algorithms to getting a high level of accuracyin diagnosis, prediction, and classification of asthma like: (data mining algorithms, machine learning algorithms, deep machine learning algorithms), depending and passing through three stages: data acquisition, feature extracting, data classification. According to the comparison of different techniques the high accuracy achieved by ANN was (98.85%), and the low accuracy of it was (80%), despite of the accuracy achieved by Support Vector Machine (SVM) was (86%) when used Mel Frequency Cepstral Coefficient MFCC for feature extraction, while the accuracy was (99.34%) when used Relief for extracting feature. Based in our comparison we recommend that if the researchers used the same techniques they should to return to previous studies it to get high accuracy.