One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

 Research in the field of biometric simulation is in the design of various and various industrial products, but it still needs new studies and research that are compatible with scientific and technological development, especially in the field of computing. Recognition, deduction, and simulation of nature, for example, the use of animal bones as tools in cutting, hunting or fighting, in addition to the use of animal drawings in cave drawings as symbols of strength, as well as dance movements and face painting to simulate the natural reality that surrounds humans. This trend developed to include simulation of nature in the formal and functional aspect to reach To vocabulary and solutions that help man in his daily life, the research probl

Praise be to God, Lord of the worlds, and peace and blessings be upon our master Muhammad and his family and companions as follows:
   For God Almighty has swapped for every age a group of religious scholars who give news to the narrators, so that they can lie against the Sunnah of the Mustafa, who is among those who memorized Ibn Al-Mulqin, as he followed the ruler in his book Al-Badr Al-Munir in the Hadith of Al-Sharh Al-Kabeer, and our research included two topics, which we explained in the first topic: The sequels in which the teacher's son Al-Malqin disagreed, and we discussed in the second topic: the followings in which Ibn Al-Malqin agreed to rule.
   This research included important results, th

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

This in vitro study evaluated the influence of chemomechanical caries removal solution on the surface topography of metal-ceramic feldspar porcelain (MAJOR ceramic) and All-ceramic feldspar porcelain (Vita Alpha) using light polarizing microscope. Forty specimens of MAJOR ceramic and forty specimens of Vita Alpha ceramic of (12mm diameter & 3mm height) were prepared .All specimens were polished with silicon polishing burs, cleaned, autoglazed and stored in 37°C before exposure to Carisolv. Thirty specimens of each material randomly exposed to Carisolv gel for 5, 10 and 20 minutes respectively, other ten specimens were not, to act as control group. All specimens were subjected to surface roughness test by profilometer and evalua