APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023

Average interstellar extinction curves for Galaxy and Large Magellanic Cloud (LMC) over the range of wavelengths (1100 A0 – 3200 A0) were obtained from observations via IUE satellite. The two extinctions of our galaxy and LMC are normalized to Av=0 and E (B-V)=1, to meat standard criteria. It is found that the differences between the two extinction curves appeared obviously at the middle and far ultraviolet regions due to the presence of different populations of small grains, which have very little contribution at longer wavelengths. Using new IUE-Reduction techniques lead to more accurate result.

This research is devoted to design and implement a Supervisory Control and Data Acquisition system (SCADA) for monitoring and controlling the corrosion of a carbon steel pipe buried in soil. A smart technique equipped with a microcontroller, a collection of sensors and a communication system was applied to monitor and control the operation of an ICCP process for a carbon steel pipe. The integration of the built hardware, LabVIEW graphical programming and PC interface produces an effective SCADA system for two types of control namely: a Proportional Integral Derivative (PID) that supports a closed loop, and a traditional open loop control. Through this work, under environmental temperature of 30°C, an evaluation and comparison were done for

Mobile ad hoc network security is a new area for research that it has been faced many difficulties to implement. These difficulties are due to the absence of central authentication server, the dynamically movement of the nodes (mobility), limited capacity of the wireless medium and the various types of vulnerability attacks. All these factor combine to make mobile ad hoc a great challenge to the researcher. Mobile ad hoc has been used in different applications networks range from military operations and emergency disaster relief to community networking and interaction among meeting attendees or students during a lecture. In these and other ad hoc networking applications, security in the routing protocol is necessary to protect against malic

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer