Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix contains zeros, so the problem is to find a low-rank matrix. Matrix completion is a heuristic NP-hard problem. It is a minimization problem defined by the matrix nuclear norm. In this paper, nuclear norm, and weighted nuclear norm minimization problems are derived to find a low-rank matrix of implemented Hankel matrix from the signal. A Robust Principal Component used to solve a low-rank-sparse matrix finds a low-rank Hankel matrix by solving a minimization problem numerically. The results show that the given methods are efficient in reconstructing and recovering the signals with a rate of more than 96%, with small values of mean square errors
This study included synthesizing silver nanoparticles (AgNPs) in a green method using AgNO3 solution with glucose exposed to microwave radiation. The prepared NPs were also characterized using ultraviolet and visible (UV-vis) spectroscopy and scanning electron microscopy (SEM). The UV/vis spectroscopy confirmed the production of AgNPs, while SEM analysis showed that the typical spherical AgNPs were 30 nm and 50 nm in size for the NPs prepared using black tea (B) and green tea (G) as reducing agent, respectively. The changes in some of the biochemical parameters related to the liver and kidneys have been analyzed to evaluate the probable toxic effects of AgNPs. 40 adult male mice were included in this study. To assess the probable he
... Show MoreThis work introduces the synthesis and the characterization of N-doped TiO2 and Co3O4 thin films prepared via DC reactive magnetron sputtering technique. N-doped TiO2 thin films was deposited on indium-tin oxide (ITO) conducting substrate at different nitrogen ratios, then the Co3O4 thin film was deposited onto the N-doped TiO2 layer to synthesize a double-layer TiO2-N/Co3O4 Photoelectrochromic device. Several techniques were used to characterize the produces which are x-ray diffraction (XRD), field emission-scanning electron microscopy (FE-SEM), Fourier-transform infrared (FTIR) spectroscopy and UV–Vis spectroscopy. The Photoelectrochromic device was characterized by UV–Vis spectroscopy and the results show that the double-layer N-dope
... Show MoreUntil recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the
... Show MoreLost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show MoreWith the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
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