Optimization of parallel firewalls filtering rules

As filtering policies are getting larger and more complex, packet filtering at firewalls needs to keep low delays. New firewall architectures are needed to enforce security and meet the increasing demand for high-speed networks. Two main architectures exist for parallelization, data-parallel and function-parallel firewalls. In the first, packets are distributed across a set of identical firewalls that implement the entire policy. In the second, each firewall implements a subset of the policy with a fewer number of rules, but the packets have to be duplicated and processed by all the firewalls. This paper proposes a new architecture function-parallel with pre-processing that combines the advantages of both architectures. The proposed architecture has the advantage of not duplicating the data, so that the processing time can be significantly reduced. Moreover, our architecture enables stateful inspection of packets, which is necessary to prevent multiple types of attacks. The performances of this architecture have been proven to be scalable for large security policies.

     

Speech emotion recognition using optimized genetic algorithm-extreme learning machine

Multimedia Tools and Applications - Automatic Emotion Speech Recognition (ESR) is considered as an active research field in the Human-Computer Interface (HCI). Typically, the ESR system is...     

Hilbert Transform and Statistical Analysis for Channel Selection and Epileptic Seizure Prediction

This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.

     

Realtime multi-aircraft tracking in aerial scene with deep orientation network

Tracking the aircrafts from an aerial view is very challenging due to large appearance, perspective angle, and orientation variations. The deep-patch orientation network (DON) method was proposed for the multi-ground target tracking system, which is general and can learn the target’s orientation based on the structure information in the training samples. Such approach leverages the performance of tracking-by-detection framework into two aspects: one is to improve the detectability of the targets by using the patch-based model for the target localization in the detection component and the other is to enhance motion characteristics of the individual tracks by incorporating the orientation information as an association metric in the tracking component. Based on the DON structure, you only look once (YOLO) and faster region convolutional neural network (FrRCNN) detection frameworks with simple online and realtime tracking (SORT) tracker are utilized as a case study. The Comparative experiments demonstrate that the overall detection accuracy is improved at the same processing speed of both detection frameworks. Furthermore, the number of Identity switches (IDsw) has reduced about 67% without affecting the computational complexity of the tracking component. Consequently, the presented method is efficient for realtime ground target-tracking scenarios.     

Pole assignment of multivariable systems using proportional-derivative state feedback

In this article, the parametric solution to the pole assignment problem for multivariable linear time-invariant systems controlled by proportional-derivative (PD) state feedback is developed. The new expressions for the PD gain controllers are derived which describe the available degrees of freedom offered by PD state feedback. The freedom provided by PD state gain matrices is utilised to obtain closed-loop systems with robust and small gain matrices. Two computational algorithms are introduced, and their effectiveness is demonstrated by two simulation examples.     

Mechanical Alloying and Sintering of a Ni/10wt.%Al<Subscript>2</Subscript>O<Subscript>3</Subscript> Nanocomposite and its Characterization

A Ni matrix nanocomposite reinforced by 10 wt.% Al₂O₃ was fabricated by mechanical alloying. The powders mixture was milled up to 24 h in a ball mill. Phase composition and morphology of prepared powders were investigated by X-ray diffraction, scanning electron microscopy and transmission electron microscopy. To obtain compact bodies, pressing was applied on the milled powders; then sintered at different temperatures for 1 h in argon atmosphere. Furthermore, the effect of milling time and sintering temperature on microstructure. Physical, mechanical and electrical properties of the sintered nanocomposite specimens were evaluated. The results show decrease of particle size of milled powders (69 nm) as the time increased up to 24 h of milling with a noticeable presence of agglomerates. On the other hand, relative density, microhardness, compressive strength, elastic modulus and electrical conductivity of the sintered samples were found to progressively increase with the increasing of milling time and sintering temperature. Their maximum values were 97.36%, 1137 MPa, 633 MPa, 21.6 GPa and 9.71 × 10⁵ S/m, respectively, for the sample that was milled for 24 h and sintered at 1200 °C. On the other hand, the increasing milling time tended to decrease the fracture strain while it increased with increase of the sintering temperature.     

Risk evaluation of rock mass sliding in El-Deir El-Bahary valley,Luxor, Egypt

The temple of Hatshepsut is considered as a most interesting ancient architectural monument and its stability is of real concern to human civilization. The temple is completely incised into the rock mass of Gebel Gurnah which is composed of Esna shale overlain by highly fracture Thebes limestone. Recently, two rock falls have occurred. A geotechnical characterization of the site around the temple was carried out. The present work aims to evaluate the probability of further limited circular failures in the Esna shale. This evaluation is achieved by using a near circular failure model based on the behaviour of intact rock, in conjunction with the CSIR rock mass classification system which gives the reduced mechanical properties due to the increase in discontinuity sets and weathering of the rock mass of the mountain around the temple.     

A Clustering Algorithm for Bi‐Criteria Stop Location Design with Elastic Demand

This article proposes a bi‐criteria formulation to find the optimal location of light rapid transit stations in a network where demand is elastic and budget is constrained. Our model is composed of two competing objective functions seeking to maximize the total ridership and minimize the total budget allocated. In this research, demand is formulated using the random utility maximization method with variables including access time and travel time. The transit station location problem of this study is formulated using mixed integer programming and we propose a heuristic solution algorithm to solve large‐scale instances which is inspired by the problem context. The elastic demand is integrated with the optimization problem in an innovative way which facilitates the solution process. The performance of our model is evaluated on two test problems and we carry out its implementation on a real‐world instance. Due to the special shape of the Pareto front function, significant practical policy implications, in particular budget allocation, are discussed to emphasize the fact that the trade‐off between cost and benefit may result in large investments with little outcomes and vice versa.     

Core/shell nanoparticles for multiple biological detection with enhanced sensitivity and kinetics

The paper shows the different methods to attach a molecule to detect streptavidin to a dielectric particle made of a rare-earth oxide core and a polysiloxane shell containing fluorescein. First, the detection of streptavidin binding on a biotinylated gold substrate can be achieved in three ways: the shift of the surface plasmon resonance of the substrate and the double luminescence (organic and inorganic) of the core/shell particle. Second, these detections are efficient even after elimination upon thermal annealing of all the undesired molecules that skew the assays. Finally, the particle that ballasts the protein enhances its binding kinetics and increases the localized surface plasmon resonance shift that detects the binding.     

Effect of Nitrogen Alloying on Sulphur Behaviour during ESR of AISI M41 Steel

In this work, the effects of nitrogen alloying, physical properties and chemical composition of slag used in electro‐slag refining (ESR) on phosphorus and sulphur contents of AISI M41 high speed steel have been studied. The experiments were conducted with two high speed steel grades which were melted in an induction furnace (IF). The first grade is the standard AISI M41 high‐speed steel and the second one is nitrogen alloyed M41 (denoted M41N). The produced ingots were ESR remelted under three grades of calcium fluoride based slag. Results showed that the ESR process has no effect on the phosphorus content in steel but it is a good tool in removing sulphur. This study shows that a high desulphurization rate can be achieved by ESR process by optimizing slag properties where the viscosity and oxidation reactions play an important role in sulphur removal. Nitrogen alloying was found to retard sulphur removal.