Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi

This paper presents a fully computerized method to backup the router configuration file. The method consists of a friendly graphical interface programmed by Java programming language.

    The proposed method is compared with the two existing methods, namely: TFTP server method and Copy/Paste method. The comparison reveals that the proposed method has many advantages over the existing ones. The proposed method has been implemented on Cisco routers (series 2500, 2600 and 2800).

Due to the development that occurs in the technologies of information system many techniques was introduced and played important role in the connection between machines and peoples through internet, also it used to control and monitor of machines, these technologies called cloud computing and Internet of Things. With the replacement of computing resources with manufacturing resources cloud computing named converted into cloud manufacturing.

In this research cloud computing was used in the field of manufacturing to automate the process of selecting G-Code that Computer Numerical Control machine work it, this process was applied by the using of this machine with Radio Frequency Identification and a AWS Cloud services and some of py

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class