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

 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris

Choosing an appropriate impression material is a challenge for many dentists, yet an essential component to provide an excellent clinical outcome and improve productivity and profit. The purpose of present study was to compare wettability, tear strength and dimensional accuracy of three elastomeric impression materials, with the same consistencies (light-body). Three commercially available light body consistency and regular set 3M ESPE Express polyvinylsiloxane (PVS), 3M ESPE Permadyne polyether (PE), and Identium (ID), impression materials were comparedTear strength test, contact angle test and linear dimensional accuracy were evaluated for three elastic impression material. Among the three experimental groups PE impression materia

This paper work new and unprecedented definitions of sets, which we have named supra fan, supra. delta fan, supra. semi delta fan sets, which are generated by three sets of specific type of supra open sets, it was utilized supra open, supra delta open, supra. semi delta open sets with special conditions. It is highlighted many details of these new types of fan sets, their axis, blades and their annular sets using tables. Attention is given to the interior and the closure of these three types in supra topological spaces. The research was further enriched numerous and diverse examples. Subsequently, the focus shifted to supra. semi delta fan sets to prove lemma and theorem.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma that represents a set of characteristic of nuclear features in which the diagnosis is depend. AIM: The study aimed to review different variants of PTC which has different malignant potential in correlation with many prognostic and clinical factors in Iraq. PATIENTS AND METHODS: Paraffin blocks of 227 cases of PTC were selected, subtyped, and grouped according to the malignant potential. The prognostic and clinical factors were studied. RESULTS: The mean age was (39.29 ± 12.17) years, with female predominance (86.3%), where (55.5%) of them below 40 years, conventional variant was most common (40.1%), followed by papillary microcarcinoma

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,