<p>The demand for internet applications has increased rapidly.  Providing quality of service (QoS) requirements for varied internet application is a challenging task. One important factor that is significantly affected on the QoS service is the transport layer. The transport layer provides end-to-end data transmission across a network. Currently, the most common transport protocols used by internet application are TCP (Transmission Control Protocol) and UDP (User Datagram Protocol). Also, there are recent transport protocols such as DCCP (data congestion control protocol), SCTP (stream congestion transmission protocol), and TFRC (TCP-friendly rate control), which are in the standardization process of Internet Engineering Task

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. E

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The gamma dose rates and specific activity of 137Cs, 60Co and 40K in
samples of soil taken from places near the landfill radiation at Al-
Tuwaitha site were measured using a portable NaI(Tl) detector. The
results of gamma dose rates in samples were ranged from 52.6
nGy.h-1 to 131nGy.h-1. Then the specific activity of 137Cs, 60Co and
40K in soil were determined using high pure germanium (HPGe)
detector. The specific activities were varied from 1.9 to 115500 Bq.
kg-1 for 137Cs, from 6.37 to 616.5 Bq. kg-1 for 60Co, and from 3 to
839.5 Bq. kg-1 for 40K. The corresponding health risk for the annual
effective dose equivalent varied from 1.85×10-14 to 15.7mSv/y. The
results were compared with various internationa

Experimental results on harmonic distortions in 13.56 MHz RF Argon glow discharge using different grounded electrodes areas and electrodes spacing are presented. The experiment is carried out at four pressure values. RF power values used are between 20 and 90 watts. The results indicate significant increase in distortions at two specific values of the cone angle enclosing the two electrodes within its geometrical volume. The computation of the cone head angle gave the symmetry discharge or asymmetry as well as when the angle is small the condition is near symmetry discharge associated with decrease in the nonlinearity.

The study aims to identify the effect of training with weight added to different parts of the body in improving the biomechanical variables of the last step and upgrading the high jump for young people, the research was applied to one of the elite high jumpers for young people, and video imaging and kinetic analysis were conducted to extract the variables under study, and then the jumper underwent For the proposed exercises by 3 training units per week for a period of (8) weeks, in which emphasis was placed on improving the rotational forces (moments) of these parts, and then the post-tests were conducted, and the researcher concluded that the exercises applied and the added weights for all parts of the body (leg, thigh, trunk, and arms) le

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe