Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

The impact of exposure to different sizes of particulate matter (PM1, PM2.5, PM7, and PM10) was evaluated in  Babylon concrete plant workers who had been exposed to concrete dust for at least 10 years.  The effects of  these particles on the hematological parameters, malondialdehyde (MDA) levels, and  antioxidant enzymes (catalase and glutathione peroxidase ) were examined. The results exhibited that the levels of PM2.5 and PM10 were higher than the acceptable limits approved by the National Ambient Air Quality Standards (NAAQS). The blood parameters, namely white blood cells (WBC), red blood cell (RBC) and platelets counts, demonstrated non-significant differences between workers exposed to the PM as compared to the control gro

A steel-concrete composite structure (1) is described. The steel-concrete composite structure comprises a steel member (2) having an upper surface (5) and a plurality of shear connector elements (6) upstanding from the upper surface and a concrete slab (4) having upper and lower surfaces (7, 8). The slab is supported on its lower surface by the upper surface of the steel member. The slab comprises a plurality of through holes (9) between the upper and lower surfaces, each through hole tapering towards the lower surface so as to form an inverted frustally-shaped seating surface (10). The concrete slab is configured and positioned with respect to the steel member such that at least one shear connector element projects into each through hole.

Roller compacted concrete (RCC) is a material with no slumps and is made from the same raw materials as conventional concrete. The roller compacted dam method, the high paste technique, the corps of engineers method, and the maximum density method are all ways of designing RCC. The evolution of RCC has resulted in a substantial change in construction projects, most notably in dams, because of the sluggish pace of conventional placement, consolidation, and compacting. The construction process was accelerated by incorporating RCC into dams, resulting in a shorter construction period. Research shows that the dams that used RCC had completed one to two years sooner than the dams that used regular concrete (Bagheri an

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main