In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

Objectives: Serratia marcescens is a gram-negative pathogen of many species. The ability of S. marcescens to form biofilms and its potent innate resistance to antimicrobials and cleaning solutions are both essential for its pathogenicity and survival. The present study was conducted to investigate the effect of glyceryl trinitrate (GTN) on the biofilm of S. marcescens, as an alternative for antibiotic therapy. Methods: Different specimens, including ear swabs, burns, mid-stream urine, wound swabs, and sputum, were collected from patients who were brought to Al-Ramadi Hospital, Iraq. All samples were cultured, and the colonies that were obtained were detected using the VITEK® 2 compact. The ability of biofilms to develop was e

Inelastic transverse magnetic dipole electron scattering form
factors in 48Ca have been investigated through nuclear shell model
in an excited state energy Ex= 10.23 MeV which is so called
"mystery case" with different optional choices like effective
interaction, restricted occupation and core polarization interaction.
40Ca as an inert core will be adopted and four orbits with eight
particles distributed mainly in 2p1f model space and in some extend
restricted to make sure about the major accuse about this type of
transition. Theoretical results have been constituted mainly with
experimental data and compared with some important theoretical
results of the same transition.

An experimental and theoretical analysis was conducted for simulation of open circuit cross flow heat
exchanger dynamics during flow reduction transient in their secondary loops. Finite difference
mathematical model was prepared to cover the heat transfer mechanism between the hot water in the
primary circuit and the cold water in the secondary circuit during transient course. This model takes under
consideration the effect of water heat up in the secondary circuit due to step reduction of its flow on the
physical and thermal properties linked to the parameters that are used for calculation of heat transfer
coefficients on both sides of their tubes. Computer program was prepared for calculation purposes which
cover a

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the