Automatic Intrusion Detection System Using Deep Recurrent Neural Network Paradigm

Network security field had gained research community attention in the last decade due to its growing importance. This paper addresses directly one vital problem in that field is “Intrusion Detection System” (IDS). As much as many researchers tackle this problem, many challenges arise while converting this research to reliable automatic system. The biggest challenge is to make the system works with low false alarm with new unseen threats. In this paper, we address this challenge by building a descriptive model using different models of deep Recurrent Neural Network (RNNs). (RNN) models has the ability to generalize the knowledge that can be used to identify seen and unseen threats. This generalization comes from RNN capabilities to define in its terms the normal behavior and the deviation accepted to be normal. Four different models of RNN were tested on a benchmark dataset, NSL-KDD, which is a standard test dataset for network intrusion. The proposed system showed superiority over other previously developed systems according to the standard measurements: accuracy, recall, precision and f-measure

Segmental Versus Circumferential Ablation of Pulmonary Veins in Patients with Paroxysmal Atrial Fibrillation

INTRODUCTION: Pulmonary vein isolation (PVI) is the cornerstone of catheter ablation techniques for the treatment of paroxysmal atrial fibrillation (PAF), with significantly improved efficacy compared to antiarrhythmic drugs as shown in CABANA trial. However, the question arises in which PAF patients whether the procedure can be limited to PVs only showing potentials (segmental), or it is really necessary to isolate all PV (circumferential). Even though success rates for circumferential PV ablation (CPVA) have been reported to be higher (up to 90%), than segmental PV ablation, most CPVA procedures previously reported included left atrial linear ablation, additional ablation lesions or lines connecting the mitral valve to the posterior PVs or along the roof of the left atrium which made bias to these studies. AIM: Thus, we initiated this randomized controlled study to evaluate the efficacy of CPVA versus SPVI in subjects undergoing ablation of PAF. METHODS: Our study included 31 consecutive patients who underwent their first radiofrequency ablation for PAF between March 2015 and March 2017. Patients were randomized for circumferential or segmental ablation on the day of the procedure. We had two groups, circumferential (17 patients) and segmental group (14 patients). RESULTS: There was no difference between two groups on our primary endpoint, the recurrence, which was 2 out of 14 patients (14.3%) in the segmental ablation group, compared to 3 out of 17 patients (17.6%) who were circumferential ablated. This difference is statistically insignificant (p = 1). For other endpoints, there was also no statistically significant difference between circumferential and segmental regarding fluoroscopy time, 53.47 ± 8.7 min versus 54.93 ± 15.02 min, p = 0.738, procedure time, 184.18 ±19.28 min versus 191.43 ± 20 min p = 0.315, and even for radio frequency time which was lower in segmental group but did not differ statistically, 35.71 ± 5.73 min versus 34.79 ± 5.29, min p = 0.649. CONCLUSION: The previous studies showed the superiority of circumferential PVI on segmental strategy regarding effectiveness, but in those studies, linear ablations were added to circumferential strategy and done in cases of persistent and PAF. In our randomized study, we compared between two methods in cases of PAF, which showed that segmental ablation is not inferior to circumferential ablation of PVI

Complexation of 1,4-bis (3-(2-pyridyl) pyrazol-1-ylmethyl) benzene (1,4-PPB) with Cu (II), Co (II), and Ni (II):: Spectrophotometric Studies in Mixed Solvent (EtOH-H2O)

The stability and composition of the complexes of 1,4-bis (3-(2-pyridyl) pyrazol-1-ylmethyl) benzene (1,4-PPB) with Cu (II), Co (II), Ni (II): have been investigated using spectrophotometric method in mixed (1:1) solvent of ethanol and water. Various experimental parameters, which include pH, ionic strength, solvent composition, and time, have been studied. The stoichiometry and formation constant of each complex have been evaluated using Job's method. Spectrophotometric results show the formation of 1:1 complexes with stability order of Co > Ni > Cu. Molar absorptivity values of the complexes have also been determined

Three dimensional estimation of vegetation moisture content using dual-wavelength terrestrial laser scanning

PhD ThesisLeaf Equivalent Water Thickness (EWT) is a water status metric widely used in vegetation health monitoring. Optical Remote Sensing (RS) data, spaceborne and airborne, can be used to estimate canopy EWT at landscape level, but cannot provide information about EWT vertical heterogeneity, or estimate EWT predawn. Dual-wavelength Terrestrial Laser Scanning (TLS) can overcome these limitations, as TLS intensity data, following radiometric corrections, can be used to estimate EWT in three dimensions (3D). In this study, a Normalized Difference Index (NDI) of 808 nm wavelength, utilized in the Leica P20 TLS instrument, and 1550 nm wavelength, employed in the Leica P40 and P50 TLS systems, was used to produce 3D EWT estimates at canopy level. Intensity correction models were developed, and NDI was found to be able to minimize the incidence angle and leaf internal structure effects. Multiple data collection campaigns were carried out. An indoors dry-down experiment revealed a strong correlation between NDI and EWT at leaf level. At canopy level, 3D EWT estimates were generated with a relative error of 3 %. The method was transferred to a mixed-species broadleaf forest plot and 3D EWT estimates were generated with relative errors < 7 % across four different species. Next, EWT was estimated in six short-rotation willow plots during leaf senescence with relative errors < 8 %. Furthermore, a broadleaf mixed-species urban tree plot was scanned during and two months after a heatwave, and EWT temporal changes were successfully detected. Relative error in EWT estimates was 6 % across four tree species. The last step in this research was to study the effects of EWT vertical heterogeneity on forest plot reflectance. Two virtual forest plots were reconstructed in the Discrete Anisotropic Radiative Transfer (DART) model. 3D EWT estimates from TLS were utilized in the model and Sentinel-2A bands were simulated. The simulations revealed that the top four to five metres of canopy dominated the plot reflectance. The satellite sensor was not able to detect severe water stress that started in the lower canopy layers. This study showed the potential of using dual-wavelength TLS to provide important insights into the EWT distribution within the canopy, by mapping the EWT at canopy level in 3D. EWT was found to vary vertically within the canopy, with EWT and Leaf Mass per Area (LMA) being highly correlated, suggesting that sun leaves were able to hold more moisture than shade leaves. The EWT vertical profiles varied between species, and trees reacted in different ways during drought conditions, losing moisture from different canopy layers. The proposed method can provide time series of the change in EWT at very high spatial and temporal resolutions, as TLS instruments are active sensors, independent of the solar illumination. It also has the potential to provide EWT estimates at the landscape level, if coupled with automatic tree ii segmentation and leaf-wood separation techniques, and thus filling the gaps in the time series produced from satellite data. In addition, the technique can potentially allow the characterisation of whole-tree leaf water status and total water content, by combining the EWT estimates with Leaf Area Index (LAI) measurements, providing new insights into forest health and tree physiology.Egyptian Ministry of Higher Educatio

Effect of Yoghourt Starter Culture and Nickel Oxide Nanoparticles on the Activity of Enterotoxigenic Staphylococcus aureus in Domiati Cheese

Domiati cheese is the most popular type of white soft cheese in Egypt. Staphylococcus aureus is a common microorganism that can easily contaminate Domiati cheese during processing and distribution. Enterotoxigenic S. aureus strains produce staphylococcal enterotoxins (SE) that have been involved in food poisoning outbreaks worldwide. The aim of the present study was to examine the inhibitory effect of yoghourt starter culture and nickel oxide nanoparticles (NiO NPs) on the development of the enterotoxigenic S. aureus together with the enterotoxin production during the manufacturing and storage of Domiati cheese. Fresh cow’s milk was inoculated with S. aureus in a count of six log CFU/mL with the addition of either yoghourt starter culture or NiO Nps. The cytotoxicity of NiO NPs on normal human epithelial cells (HEC) was assessed using the MTT assay. In the current study, the inoculated milk was used for making Domiati cheese and the survival Weibull and log-linear models were fitted to the observed data. The obtained results showed that the mean log count of S. aureus decreased one week earlier by using yoghourt starter culture. Staphylococcal enterotoxin A (SEA) was identified only in the control cheese. Notably, Domiati cheese contained MIC of NiO NPs (35 µg/mL), which resulted in a significant decrease in S. aureus counts since at day 21 of cheese ripening it was not detected (<10 CFU/g). Overall, the current study indicated that the addition of yoghourt starter culture and NiO NPs during the processing of Domiati cheese could be useful candidates against S. aureus and enterotoxin production in the dairy industry

Determination of major and minor elements in dairy products produced in Misurata city – Libya

Concentrations of minor metals (cadmium Cd, lead Pb, copper Cu, Zinc Zn, and chromium Cr) and major nutritional elements (sodium Na, and potassium K) were analyzed in some dairy products (15) produced by four local companies in Misurata-Libya. Minor elements were determined using Atomic Absorption Spectrometer and major elements (Na and K) using Flame Emission Photometer. For heavy metals, the average levels of zinc was the highest, followed by levels of lead, cadmium, and chromium, and finally the levels of copper was the lowest. For major elements, the levels of potassium were higher than sodium in all tested samples. Generally, Heavy metal concentrations varied significantly depending upon the type of the product and significant differences were observed in the mean values of heavy metals in different types of dairy products. However, the levels of heavy metals in fresh milk were lower than the levels in other products (butter milk, yoghurt, and yoghurt drink). Finally, further investigations are needed to identify the cause of elevated heavy metal levels especially in dairy products

DDOS Botnets Attacks Detection in Anomaly Traffic: A Comparative Study.

One of the major challenges that faces the acceptance and growth rate of business and governmental sites is a Botnet-based DDoS attack. A flooding DDoS strikes a victim machine by means of sending a vast amount of malicious traffic, causing a significant drop in the service quality (QoS) in IoT devices. Nonetheless, it is not that easy to detect and tackle flooding DDoS attacks, owing to the significant number of attacking machines, the usage of source-address spoofing, and the common areas shared between legitimate and malicious traffic. New kinds of attacks are identified daily, and some remain undiscovered, accordingly, this paper aims to improve the traffic classification algorithm of network traffic, that hackers use to try to be ambiguous or misleading. A recorded simulated traffic was used for both samples; normal and DDoS attack traffic, approximately 104.000 cases of each, where both datasets -which were created for this study- represent the input data in order to create a classification model, to be used as a tool to mitigate the risk of being attacked. The next step is putting datasets in a format suitable for classification. This process is done through preprocessing techniques, to convert categorical data into numerical data. A classification process is applied to capture datasets, to create a classification model, by using five classification algorithms which are; Decision Tree, Support Vector Machine, Naive Bayes, K-Neighbours and Random Forest. The core code used for classification is the python code, which is controlled by a user interface. The highest prediction, precision and accuracy are obtained using the Decision Tree and Random Forest classification algorithms, which also have the lowest processing time

Phytochemical Screening, Antioxidant Capacity Measurement, and Mineral Content Determination of Thymus vulgaris L. Extracts

The aim of this study was to evaluate the chemical composition and antioxidant activity of Thymus vulgaris L. extracts. T. vulgaris L. is a medicinal plant that has various bioactive compounds. Four different solvents (ethanol, water, ethyl acetate, and chloroform) were used to extract these compounds from the plant. The phytochemical screening of the extracts showed that the ethanolic extract had the highest diversity of compounds, including coumarins, flavonoids, alkaloids, tannins, phenols, carbohydrates, and proteins. The total phenolic and total antioxidant contents of the ethanolic extract were measured by the Folin–Ciocalteu and phosphomolybdenum methods, respectively. The ethanolic extract had a high phenolic content of 77.7 mg gallic acid equivalent/g dry weight, which indicates its potential antioxidant capacity. The mineral content of T. vulgaris L. was also assessed by flame photometry and atomic absorption spectrophotometry after dry digestion. The plant contained five macroelements (K, Na, Ca, Mg, P) and three microelements (Fe, Cu, Zn) in different concentrations. The highest concentration was found for potassium (15259 mg/kg), followed by calcium (5118 mg/kg) and sodium (4793 mg/kg). The lowest concentration was found for phosphorus (1400 mg/kg), which was still higher than the microelements. Among the microelements, zinc had the highest concentration (24.82 mg/kg), followed by iron (17.44 mg/kg) and copper (14.98 mg/kg). The results of this study provide useful information for the users, collectors and practitioners of medicinal plants from polluted areas, as they can evaluate the quality and safety of T. vulgaris L. for human consumption

Spectrophotometric Complex formation Study of Murexide with Nickel and Cobalt in Aqueous Solution

In the present study, the formation constant and the stoichiometry of murexide complexes with Co (II) and Ni (II) have been determined spectrophotometrically in aqueous solution at 25oC. Two experimental parameters governed the complex formation, pH and time, have been investigated. The formation and stoichiometry constants have been determined by two methods: Job's and mole ratio's methods. The absorption maxima for Co-murexide and Ni-murexide complexes were: 480, 460 nm, respectively. The two Spectrophotometric methods confirm the formation of 2:1 (M:L) complexes with stability arrange of: Co &gt; Ni. The formation constants (Kf) determined by the Job's method were as follows: 2.06x1014 and 1.21x1011 for Co-murexide and Ni-murexide, respectively. Also, using mole ratio's method, the formation constants were found to be:&nbsp; 9.18x1011 and 6.01x1011. Molar absorptivity values of the studied complexes have also been determined (by Job's and mole ratio's methods) and the average values were: 18235 and 13284 l/mol.cm for Co and Ni, respectively