Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration on each subsystem to futher reduce the hardware requirements. The DNN was designed using a system generator and implemented using very hardware description language (VHDL). The system achievments outcomes the superior’s accuracy rate of approximately 99.6 percent in distinguishing bengin from malignant tissue. Also, the hardware resources were reduced by 30 percent from works of literature with an error rate of 7e-4 when using the Kintex-7 xc7k325t-3fbg676 board.
The purpose of the study is the city of Baghdad, the capital of Iraq, was chosen to study the spectral reflection of the land cover and to determine the changes taking place in the areas of the main features of the city using the temporal resolution of multispectral bands of the satellite Landsat 5 and 8 for MSS and OLI sensors respectively belonging to NASA and for the period 1999-2021, and calculating the increase and decrease in the basic features of Baghdad. The main conclusions of the study were, This study from 1999 to 2021 and in two different seasons: the Spring of the growing season and Summer the dry season. When using the supervised classification method to determine the differences, the results showed remarkable changes. Where h
... Show MoreThe concept of sustainability is one of the modern concepts that influenced the quality of the urban plans for the cities, through the interest in the environmental and social aspects as well as the economic aspect and the need to balance to achieve sustainable development.
The research aims to identify the most prominent methods of sustainable urban land use planning and the strategies developed within these approaches to achieve sustainable development. The research started from the problem of a knowledge gap in adopting sustainable approaches and strategies when planning urban land uses for the holy city of Karbala.
In the theoretical aspect, the concepts of sustainable development, sustainable planning methodologies a
... Show MoreA study has been done to find the optimum separators pressures of separation stations. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid discharged from a higher pressure separator into the lower pressure separator. The set of working separators pressures which yield maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures which is the target of this work.
Computer model is used to find the optimum separators pressures. The model employs the Peng-Robinson equation of state for volatile oil. Application of this model shows good improvement of al
The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.
sensor sampling rate (SSR) may be an effective and crucial field in networked control systems. Changing sensor sampling period after designing the networked control system is a critical matter for the stability of the system. In this article, a wireless networked control system with multi-rate sensor sampling is proposed to control the temperature of a multi-zone greenhouse. Here, a behavior based Mamdany fuzzy system is used in three approaches, first is to design the fuzzy temperature controller, second is to design a fuzzy gain selector and third is to design a fuzzy error handler. The main approach of the control system design is to control the input gain of the fuzzy temperature controller depending on the cur
... Show MoreThe Costing Accounting is one the analytic tools which plays important role by support the management in planning& control and decisions-making ,as it became attendant necessity to establish any project whether industrial ,commercial ,service or agriculture ..etc.
The consolidated accounting system has committed the companies to have their active costing system in which the management can obtain their own data, but we found most of the economic units face problems of applying the costing system because of reasons related to the system design itself or might be related to the requirements of the application success.
... Show MoreCircular thin walled structures have wide range of applications. This type of structure is generally exposed to different types of loads, but one of the most important types is a buckling. In this work, the phenomena of buckling was studied by using finite element analysis. The circular thin walled structure in this study is constructed from; cylindrical thin shell strengthen by longitudinal stringers, subjected to pure bending in one plane. In addition, Taguchi method was used to identify the optimum combination set of parameters for enhancement of the critical buckling load value, as well as to investigate the most effective parameter. The parameters that have been analyzed were; cylinder shell thickness, shape of stiffeners section an
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