The diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced n

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

The railways network is one of the huge infrastructure projects. Therefore, dealing with these projects such as analyzing and developing should be done using appropriate tools, i.e. GIS tools. Because, traditional methods will consume resources, time, money and the results maybe not accurate. In this research, the train stations in all of Iraq’s provinces were studied and analyzed using network analysis, which is one of the most powerful techniques within GIS. A free trial copy of ArcGIS®10.2 software was used in this research in order to achieve the aim of this study. The analysis of current train stations has been done depending on the road network, because people used roads to reach those train stations. The data layers for this st

It is noted in the title that the paper studies the viewpoint in the novel The Dog and the Long Night by the Iranian novelist Shahranoush Parsi Pour and in the novel Alibaba's Sad Night by the Iraqi novelist Abdulkhaliq Ar-Rikabi. Both are well known novelists, and about whose stories and novels many critical books, MA theses, and Ph.D. dissertations have been written. Also, some of their literary works have won prizes. Here, the researcher shed light on the concept of viewpoint, its types, and its importance in novels in general. This was done along with tackling the two viewpoints in both novels, where similarities and differences were identified. For this end, the researcher has adopted the analytic-descriptive appro

It is very known  how great is the  role of the Jewish writers in the system of the Zionist movement. The movement relied on writers and writers to carry out their programs, especially those pertaining to the creation of a "national homeland" for Jews. Most Jewish writers sang of  Palestine even though they were not born there.

    On such a  basis, we have followed closely the writings of writers, critics and others by the end of the nineteenth century and the beginning of the twentieth century. We found that these writings are based on one common question: What is the fate of the Jewish people?

    Most of these writings were accompanied by Theodor Herzl's proj

Compressing an image and reconstructing it without degrading its original quality is one of the challenges that still exist now a day. A coding system that considers both quality and compression rate is implemented in this work. The implemented system applies a high synthetic entropy coding schema to store the compressed image at the smallest size as possible without affecting its original quality. This coding schema is applied with two transform-based techniques, one with Discrete Cosine Transform and the other with Discrete Wavelet Transform. The implemented system was tested with different standard color images and the obtained results with different evaluation metrics have been shown. A comparison was made with some previous rel

    With the freedom offered by the Deep Web, people have the opportunity to express themselves freely and discretely, and sadly, this is one of the reasons why people carry out illicit activities there. In this work, a novel dataset for Dark Web active domains known as crawler-DB is presented. To build the crawler-DB, the Onion Routing Network (Tor) was sampled, and then a web crawler capable of crawling into links was built. The link addresses that are gathered by the crawler are then classified automatically into five classes. The algorithm built in this study demonstrated good performance as it achieved an accuracy of 85%. A popular text representation method was used with the proposed crawler-DB crossed by two different supervise

Due to the increased of information existing on the World Wide Web (WWW), the subject of how to extract new and useful knowledge from the log file has gained big interest among researchers in data mining and knowledge discovery topics.
Web miming, which is a subset of data mining divided into three particular ways, web content mining, web structure mining, web usage mining. This paper is interested in server log file, which is belonging to the third category (web usage mining). This file will be analyzed according to the suggested algorithm to extract the behavior of the user. Knowing the behavior is coming from knowing the complete path which is taken from the specific user.
Extracting these types of knowledge required many of KDD

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t

 Internet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR)