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 show that the proposed system has obtained good results and these results are equal to 86.36%, 49.69%, and 77.65% for detection rate, false alarm rate and accuracy respectively. These results are considered as a better result when it is compared with the other previous basic algorithms. It is possible to conclude that DNA sequence has potential for NIDS solution and it has potential improvement using a better encoding method.
Aggression is a negative form of an anti-social behavior. It is produced because of a particular reason, desire, want, need, or due to the psychological state of the aggressor. It injures others physically or psychologically. Aggressive behaviors in human interactions cause discomfort and disharmony among interlocutors. The paper aims to identify how aggressive language manifests itself in the data under scrutiny in terms of the pragmatic paradigm. Two British literary works are the data; namely, Look Back in Anger by John Osborne (1956), and The Birthday Party by Harold Pinter (1957). This paper endeavors to answer the question of how aggressive language is represented in literature pragmatically? It is hoped to be significant to
... Show MoreThis paper deals with a Twin Rotor Aerodynamic System (TRAS). It is a Multi-Input Multi-Output (MIMO) system with high crosscoupling between its two channels. It proposes a hybrid design procedure that combines frequency response and root locus approaches. The proposed controller is designated as PID-Lead Compensator (PIDLC); the PID controller was designed in previous work using frequency response design specifications, while the lead compensator is proposed in this paper and is designed using the root locus method. A general explicit formula for angle computations in any of the four quadrants is also given. The lead compensator is designed by shifting the dominant closed-loop poles slightly to the left in the s-plane. This has the effect
... Show MoreAmong the available chaotic modulation schemes, differential chaos shift keying (DSCK) offers the perfect noise performance. The power consumption of DCSK is high since it sends chaotic signal in both of 1 and 0 transmission, so it does not represent the optimal choice for some applications like indoor wireless sensing where power consumption is a critical issue. In this paper a novel noncoherent chaotic communication scheme called differential chaos on-off keying (DCOOK) is proposed as a solution of this problem. With the proposed scheme, the DCOOK signal have a structure similar to chaos on-off keying (COOK) scheme with improved performance in noisy and multipath channels by introducing the concept of differential coherency used in DCS
... Show MoreThis study explored the feasibility of removing nickel (Ni) and Pb (II) from water solutions using the adsorption technique by cellulose recovered from office paper waste. Metal removal is required to reduce the direct or indirect exposure of industrial waste to the environment, due to its potential for harm to human health and ecosystems. The release criterion is maintained to keep the efficient wastewater treatment of the metals of concern, which are toxic to both humans and other organisms. The cellulose was first prepared from office paper waste. The removal values can be rationalized as follows: Lead removal efficiencies of were obtained upto %95.0632, while the removals of nickel were obtained as 54.3866%. The adsorption proce
... Show MoreWith the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases
... Show MoreChannel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
... Show MoreThis study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to
Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing
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