Search results for: cross layer network topology

Authors: P. Wongthongtham, K. Coutinho, A. MacCarthy

Abstract:

Layer-One.X (L1X) blockchain provides the infrastructure layer, and decentralised applications can be created on the L1X infrastructure. L1X tokenomics are important and require a proportional balance between token distribution, nurturing user activity and engagement, and financial incentives. In this paper, we present research in progress on L1X tokenomics describing key concepts and implementations, including token velocity and value, incentive scheme, and broad distribution. Particularly the economic design of the native token of the L1X blockchain, called HeartBit (HB), is presented.

Keywords: tokenisation, layer one blockchain, interoperability, token distribution, L1X blockchain

Procedia PDF Downloads 95

Authors: Kiran P. Kumar, H. M. Nayana, R. Rakshitha, S. Sushmitha

Abstract:

Aircraft noise is a highly concerned problem in the field of the aviation industry. It is necessary to reduce the noise in order to be environment-friendly. Air-frame noise is caused because of the quick separation of the boundary layer over an aircraft body. So, we have to delay the boundary layer separation of an air-frame and engine nacelle. By following a certain procedure boundary layer separation can be reduced by converting laminar into turbulent and hence early separation can be prevented that leads to the noise reduction. This method has a tendency to reduce the noise of the aircraft hence it can prove efficient and environment-friendly than the present Aircraft.

Keywords: airframe, boundary layer, noise, reduction

Procedia PDF Downloads 456

Authors: Vivek Kumar Singh, Tripti Singh

Abstract:

An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

Procedia PDF Downloads 801

Authors: Bruno Coelho Lima, Joao F.A. Martos, Paulo G. P. Toro, Israel S. Rego

Abstract:

The shock tube is a ground-facility widely used in aerospace and aeronautics science and technology for studies on gas dynamic and chemical-physical processes in gases at high-temperature, explosions and dynamic calibration of pressure sensors. A shock tube in its simplest form is comprised of two separate tubes of equal cross-section by a diaphragm. The diaphragm function is to separate the two reservoirs at different pressures. The reservoir containing high pressure is called the Driver, the low pressure reservoir is called Driven. When the diaphragm is broken by pressure difference, a normal shock wave and non-stationary (named Incident Shock Wave) will be formed in the same place of diaphragm and will get around toward the closed end of Driven. When this shock wave reaches the closer end of the Driven section will be completely reflected. Now, the shock wave will interact with the boundary layer that was created by the induced flow by incident shock wave passage. The interaction between boundary layer and shock wave force the separation of the boundary layer. The aim of this paper is to make an analysis of influences of separation of the boundary layer in the reservoir pressure in the shock tube. A comparison among CDF (Computational Fluids Dynamics), experiments test and analytical analysis were performed. For the analytical analysis, some routines in Python was created, in the numerical simulations (Computational Fluids Dynamics) was used the Ansys Fluent, and the experimental tests were used T1 shock tube located in IEAv (Institute of Advanced Studies).

Keywords: boundary layer separation, moving shock wave, shock tube, transient simulation

Procedia PDF Downloads 294

Authors: Ashkan Forootan, Reza Rashedi

Abstract:

Polyethylene has wide usage areas such as blow molding, pipe, film, cable insulation. However, regardless to its growing applications, it has some constraints such as the limited 70C operating temperature. Polyethylene thermo setting procedure whose molecules are knotted and 3D-molecular-network formed , is developed to conquer the above problem and to raise the applicable temperature of the polymer. This paper reports the cross-linking for two different molecular weight grades of LLDPE by adding 0.5, 1, and 2% of DCP (Dicumyl Peroxide). DCP was chosen for its prevalence among various cross-linking agents. Structural parameters such as molecular weight, melt flow index, comonomer, number of branches,etc. were obtained through the use of relative tests as Gel Permeation Chromatography and Fourier Transform Infra Red spectrometer. After calculating the percentage of gel content, properties of the pure and cross-linked samples were compared by thermal and mechanical analysis with DMTA and FTIR and the effects of cross-linking like viscous and elastic modulus were discussed by using various structural paprameters such as MFI, molecular weight, short chain branches, etc. Studies showed that cross-linked polymer, unlike the pure one, had a solid state with thermal mechanical properties in the range of 110 to 120C and this helped overcome the problem of using polyethylene in temperatures near the melting point.

Keywords: LLDPE, cross-link, structural parameters, DCP, DMTA, GPC

Procedia PDF Downloads 283

Authors: Afif Saleh Abugharsa

Abstract:

The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

Procedia PDF Downloads 402

Authors: Malihe Moeinin, Robert Hill, Ferranti Wong

Abstract:

Background: A white spot lesion (WSL) is defined as subsurface enamel porosity from carious demineralisation on the smooth surfaces of the tooth. It appears as a milky white opacity. Lesions shown an apparently intact surface layer, followed underneath by the more porous lesion body. The small pores within the body of the lesion act as diffusion pathway for both acids and minerals, so allowing the demineralisation of enamel to occur at the advancing front of the lesion. Objectives: The objective is to mapthe porosity and its size on WSL with Focused Ion Bean- Scanning Electron Microscopy (FIB-SEM) Method: The basic method used for FIB-SEM consisted of depositing a one micron thick layer of platinum over 25μmx 25μm of the interest region of enamel. Then, making a rough cut (25μmx 5μmx 20μm) with 3nA current and 30Kv was applied with the help of drift suppression (DS), using a standard “cross-sectional” cutting pattern, which ended at the front of the deposited platinum layer. Two adjacent areas (25μmx 5μmx 20μm) on the both sides of the platinum layer were milled under the same conditions. Subsequent, cleaning cross-sections were applied to polish the sub-surface edge of interest running perpendicular to the surface. The "slice and view" was carried out overnight for milling almost 700 slices with 2Kv and 4nA and taking backscattered (BS) images. Then, images were imported into imageJ and analysed. Results: The prism structure is clearly apparent on FIB-SEM slices of WSL with the dissolution of prism boundaries as well as internal porosity within the prism itself. Porosity scales roughly 100-400nm, which is comparable to the light wavelength (500nm). Conclusion: FIB-SEM is useful to characterize the porosity of WSL and it clearly shows the difference between WSL and normal enamel.

Keywords: white spot lesion, FIB-SEM, enamel porosity, porosity

Procedia PDF Downloads 71

Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

Abstract:

We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

Procedia PDF Downloads 115

Authors: Ranbir Singh, Deepinder Kaur

Abstract:

Network security is an important aspect in every field like government offices, Educational Institute and any business organization. Network security consists of the policies adopted to prevent and monitor forbidden access, misuse, modification, or denial of a computer network. Network security is very complicated subject and deal by only well trained and experienced people. However, as more and more people become wired, an increasing number of people need to understand the basics of security in a networked world. The history of the network security included an introduction to the TCP/IP and interworking. Network security starts with authenticating, commonly with a username and a password. In this paper, we study about various types of attacks on network security and how to handle or prevent this attack.

Keywords: network security, attacks, denial, authenticating

Procedia PDF Downloads 378

Authors: Sharon Waichman, Shahaf Froim, Ido Zukerman, Shmuel Barzilai, Shmual Hayun, Avi Raveh

Abstract:

Boron carbide is a ceramic material with superior properties such as high chemical and thermal stability, high hardness and high wear resistance. Moreover, it has a big cross section for neutron absorption and therefore can be employed in nuclear based applications. However, an efficient attachment of boron carbide to a metal such as aluminum can be very challenging, mainly because of the formation of aluminum-carbon bonds that are unstable in humid environment, the affinity of oxygen to the metal and the different thermal expansion coefficients of the two materials that may cause internal stresses and a subsequent failure of the bond. Here, we aimed to achieving a strong and a durable attachment between the boron carbide coating and the aluminum substrate. For this purpose, we applied Ti as a thin intermediate layer that provides a gradual change in the thermal expansion coefficients of the configured layers. This layer is continuous and therefore prevents the formation of aluminum-carbon bonds. Boron carbide coatings with a thickness of 1-5 µm were deposited on the aluminum substrate by pulse-DC magnetron sputtering. Prior to the deposition of the boron carbide layer, the surface was pretreated by energetic ion plasma followed by deposition of the Ti intermediate adhesive layer in a continuous process. The properties of the Ti intermediate layer were adjusted by the bias applied to the substrate. The boron carbide/aluminum bond was evaluated by various methods and complementary techniques, such as SEM/EDS, XRD, XPS, FTIR spectroscopy and Glow Discharge Spectroscopy (GDS), in order to explore the structure, composition and the properties of the layers and to study the adherence mechanism of the boron carbide/aluminum contact. Based on the interfacial bond characteristics, we propose a desirable solution for improved adhesion of boron carbide to aluminum using a highly efficient intermediate adhesive layer.

Keywords: adhesion, boron carbide coatings, ceramic/metal bond, intermediate layer, pulsed-DC magnetron sputtering

Procedia PDF Downloads 143

Authors: Haesook Kim, Ha Na Ra, Mansu Kim, Hyun Gi Kim, Sung Soo Kim

Abstract:

Epoxy-ZrP (α-zirconium phosphate) nanocomposites were coated on inorganic barrier layer such as sputtering and atomic layer deposition (ALD) to improve the barrier properties and protect the layer. ZrP nanoplatelets were synthesized using a reflux method and exfoliated in the polymer matrix. The barrier properties of coating layer were characterized by measuring water vapor transmission rate (WVTR). The WVTR dramatically decreased after epoxy-ZrP nanocomposite coating, while maintaining the optical properties. It was also investigated the effect of epoxy-ZrP coating on inorganic layer after bending and reliability test. The optimal structure composed of inorganic and epoxy-ZrP nanocomposite layers was used in organic light emitting diodes (OLED) encapsulation.

Keywords: α-zirconium phosphate, barrier properties, epoxy nanocomposites, OLED encapsulation

Procedia PDF Downloads 335

Authors: Somayeh Sadat Hashemi Kamangar, Fatemeh Bakouie, Shahriar Gharibzadeh

Abstract:

In this study, we target to exploit Maximum Spanning Trees (MST) of children's semantic networks to investigate their language development. To do so, we examine the graph-theoretic properties of word-embedding networks. The networks are made of words children learn prior to the age of 30 months as the nodes and the links which are built from the cosine vector similarity of words normatively acquired by children prior to two and a half years of age. These networks are weighted graphs and the strength of each link is determined by the numerical similarities of the two words (nodes) on the sides of the link. To avoid changing the weighted networks to the binaries by setting a threshold, constructing MSTs might present a solution. MST is a unique sub-graph that connects all the nodes in such a way that the sum of all the link weights is maximized without forming cycles. MSTs as the backbone of the semantic networks are suitable to examine developmental changes in semantic network topology in children. From these trees, several parameters were calculated to characterize the developmental change in network organization. We showed that MSTs provides an elegant method sensitive to capture subtle developmental changes in semantic network organization.

Keywords: maximum spanning trees, word-embedding, semantic networks, language development

Procedia PDF Downloads 120

Authors: Dana Abed, Mu`Tasim Abdel-Jaber, Nasim Shatarat

Abstract:

This study aims at investigating the influence of cross-sectional size on axial compressive capacity of carbon fiber reinforced polymer (CFRP) wrapped square reinforced concrete short columns. Three sets of columns were built for this purpose: 200x200x1200 mm; 250x250x1500 mm and 300x300x1800 mm. Each set includes a control column and a strengthened column with one layer of CFRP sheets. All columns were tested under the effect of pure axial compression load. The results of the study show that using CFRP sheets resulted in capacity enhancement of 37%, 32% and 27% for the 200×200, 250×250, and 300×300 mm, respectively. The results of the experimental program demonstrated that the percentage of improvement in strength decreased by increasing the cross-sectional size of the column.

Keywords: CFRP, columns, concentric loading, cross-sectional

Procedia PDF Downloads 265

Authors: Khodamorad Nabaki, Jianhu Shen, Xiaodong Huang

Abstract:

This paper develops a method for considering the critical fatigue stress as a constraint in the Bi-directional Evolutionary Structural Optimization (BESO) method. Our aim is to reach an optimal design in which high cycle fatigue failure does not occur for a specific life time. The critical fatigue stress is calculated based on modified Goodman criteria and used as a stress constraint in our topology optimization problem. Since fatigue generally does not occur for compressive stresses, we use the p-norm approach of the stress measurement that considers the highest tensile principal stress in each point as stress measure to calculate the sensitivity numbers. The BESO method has been extended to minimize volume an object subjected to the critical fatigue stress constraint. The optimization results are compared with the results from the compliance minimization problem which shows clearly the merits of our newly developed approach.

Keywords: topology optimization, BESO method, p-norm, fatigue constraint

Procedia PDF Downloads 275

Authors: Ying Li, Yan Li

Abstract:

A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability.

Keywords: neural network, orthogonal basis extreme learning, function approximation

Procedia PDF Downloads 513

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

Abstract:

This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

Procedia PDF Downloads 611

Authors: Ahmad Taghinia, Negar Gholamishaker

Abstract:

GaAs (gallium arsenide) solar cells have gained significant attention for their use in space applications. These solar cells have the potential for efficient energy conversion and are being explored as potential power sources for electronic devices, satellites, and telecommunication equipment. In this study, the aim is to investigate the effect of adding a window layer and a back surface field (BSF) layer made of InₓGa₍₁₋ₓ₎P material to a GaAs single junction solar cell. In this paper, we first obtain the important electrical parameters of a single-junction GaAs solar cell by utilizing a two-dimensional simulator software for virtual investigation of the solar cell; then, we analyze the impact of adding a window layer and a back surface field layer made of InₓGa₍₁₋ₓ₎P on the solar cell. The results show that the incorporation of these layers led to enhancements in Jsc, Voc, FF, and the overall efficiency of the solar cell.

Keywords: back surface field layer, solar cell, GaAs, InₓGa₍₁₋ₓ₎P, window layer

Procedia PDF Downloads 56

Authors: Sopida Vacharasukpo, Sudarat Khwan-On

Abstract:

This paper proposes a high step-up DC-DC converter topology for renewable energy system applications. The proposed converter employs only a single power switch instead of using several switches. Compared to the conventional DC-DC step-up converters the higher voltage gain with small output ripples can be achieved by using the proposed high step-up DC-DC converter topology. It can step up the low input voltage (20-50Vdc) generated from the photovoltaic modules to the high output voltage level approximately 600Vdc in order to supply the three-phase inverter fed the three-phase motor drive. In this paper, the operating principle of the proposed converter topology and its control strategy under the continuous conduction mode (CCM) are described. Finally, simulation results are shown to demonstrate the effectiveness of the proposed high step-up DC-DC converter with its control strategy to increase the voltage step-up conversion ratio.

Keywords: DC-DC converter, high step-up ratio, renewable energy, single switch

Procedia PDF Downloads 1168

Authors: Lina Abou Haibeh, Nadir Hakem, Ousama Abu Safia

Abstract:

In this paper, the performance and quality of Voice over IP (VoIP) calls carried over a Mobile Ad Hoc Network (MANET) which has a number of SIP nodes registered on a SIP Proxy are analyzed. The testing campaigns are carried out in an indoor corridor structure having a well-defined channel’s characteristics and model for the different voice codecs, G.711, G.727 and G.723.1. These voice codecs are commonly used in VoIP technology. The calls’ quality are evaluated using four Quality of Service (QoS) metrics, namely, mean opinion score (MOS), jitter, delay, and packet loss. The relationship between the wireless channel’s parameters and the optimum codec is well-established. According to the experimental results, the voice codec G.711 has the best performance for the proposed MANET topology

Keywords: wireless channel modelling, Voip, MANET, session initiation protocol (SIP), QoS

Procedia PDF Downloads 199

Authors: Dana J. Abed, Mu'tasim S. Abdel-Jaber, Nasim K. Shatarat

Abstract:

In this paper, an experimental study on twelve square columns was conducted to investigate the influence of cross-sectional size on axial compressive capacity of carbon fiber reinforced polymers (CFRP) wrapped square reinforced concrete (RC) short columns subjected to eccentric loadings. The columns were divided into three groups with three cross sections (200×200×1200, 250×250×1500 and 300×300×1800 mm). Each group was tested under two different eccentricities: 10% and 20% of the width of samples measured from the center of the column cross section. Four columns were developed in each arrangement. Two columns in each category were left unwrapped as control samples, and two were wrapped with one layer CFRP perpendicular to the specimen surface. In general; CFRP sheets has enhanced the performance of the strengthened columns compared to the control columns. It was noticed that the percentage of compressive capacity enhancement was decreased by increasing the cross-sectional size, and increasing loading eccentricity generally leads to reduced load bearing capacity in columns. In the same group specimens, when the eccentricity increased the percentage of enhancement in load carrying capacity was increased. The study concludes that the optimum use of the CFRP sheets for axial strength enhancement is for smaller cross-section columns under higher eccentricities.

Keywords: CFRP, columns, eccentric loading, cross-sectional

Procedia PDF Downloads 156

Authors: Manas Tripathi, Arunabha Mukhopadhyay

Abstract:

In Cloud computing environment, cloud servers, sometimes may crash after receiving huge amount of request and cloud services may stop which can create huge loss to users of that cloud services. This situation is called Denial of Service (DoS) attack. In Distributed Denial of Service (DDoS) attack, an attacker targets multiple network paths by compromising various vulnerable systems (zombies) and floods the victim with huge amount of request through these zombies. There are many solutions to mitigate this challenge but most of the methods allows the attack traffic to arrive at Cloud Service Provider (CSP) and then only takes actions against mitigation. Here in this paper we are rather focusing on preventive mechanism to deal with these attacks. We analyze network topology and find most vulnerable paths beforehand without waiting for the traffic to arrive at CSP. We have used Dijkstra's and Yen’s algorithm. Finally, risk assessment of these paths can be done by multiplying the probabilities of attack for these paths with the potential loss.

Keywords: cloud computing, DDoS, Dijkstra, Yen’s k-shortest path, network security

Procedia PDF Downloads 260

Authors: Farhad Reyazat, Richard Werner

Abstract:

This paper contributes to the existent literature by developing a framework that explains how to monitor potential threats to banking sector stability. The study explores structural vulnerabilities at the country level, but also look at bilateral exposures within a network context. The study contributes in analysing of the European banking systemic risk at aggregated level, which integrates the characteristics of bank size, and interconnectedness relative to the size of the economy which ultimate risk belong to, taking to account the concentration ratio of the banking industry within the whole economy. The nature of the systemic risk depends on the interplay of the network topology with the nature of financial transactions over the network, assets and buffer stemming from bank size, correlations, and the nature of the shocks to the financial system. The study’s results illustrate the contribution of banks’ size, size of economy and concentration of counterparty exposures to a given country’s banks in explaining its systemic importance, how much the banking network depends on a few traditional hubs activities and the changes of this dependencies over the last 9 years. The role of few of traditional hubs such as Swiss banks and British Banks and also Irish banks- where the financial sector is fairly new and grew strongly between 1990s till 2008- take the fourth position on 2014 reducing the relative size since 2006 where they had the first position. In-degree concentration index analysis in the study shows concentration index of banking network was not changed since financial crisis 2007-8. In-degree concentration index on first quarter of 2014 indicates that US, UK and Germany together, getting over 70% of the network exposures. The result of comparing the in-degree concentration index with 2007-4Q, shows the same group having over 70% of the network exposure, however the UK getting more important role in the hub and the market share of US and Germany are slightly diminished.

Keywords: systemic risk, counterparty risk, financial stability, interconnectedness, banking concentration, european banks risk, network effect on systemic risk, concentration risk

Procedia PDF Downloads 462

Authors: Aisulu Tileukulova, Zhexebay Dauren

Abstract:

Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

Procedia PDF Downloads 321

Authors: Farheen Tabassum, Shoab Ahmed Khan

Abstract:

The brutality of attacks on networks and decisive infrastructures are on the climb over recent years and appears to continue to do so. Distributed Denial of service attack is the most prevalent and easy attack on the availability of a service due to the easy availability of large botnet computers at cheap price and the general lack of protection against these attacks. Application layer DDoS attack is DDoS attack that is targeted on wed server, application server or database server. These types of attacks are much more sophisticated and challenging as they get around most conventional network security devices because attack traffic often impersonate normal traffic and cannot be recognized by network layer anomalies. Conventional techniques of single-hosted security systems are becoming gradually less effective in the face of such complicated and synchronized multi-front attacks. In order to protect from such attacks and intrusion, corporation among all network devices is essential. To overcome this issue, a collaborative intrusion detection system (CIDS) is proposed in which multiple network devices share valuable information to identify attacks, as a single device might not be capable to sense any malevolent action on its own. So it helps us to take decision after analyzing the information collected from different sources. This novel attack detection technique helps to detect seemingly benign packets that target the availability of the critical infrastructure, and the proposed solution methodology shall enable the incident response teams to detect and react to DDoS attacks at the earliest stage to ensure that the uptime of the service remain unaffected. Experimental evaluation shows that the proposed collaborative detection approach is much more effective and efficient than the previous approaches.

Keywords: Distributed Denial-of-Service (DDoS), Collaborative Intrusion Detection System (CIDS), Slowloris, OSSIM (Open Source Security Information Management tool), OSSEC HIDS

Procedia PDF Downloads 338

Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

Abstract:

Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

Procedia PDF Downloads 364

Authors: Buse T. Aydın, Enver Ozdemir

Abstract:

In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 133

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives.

Keywords: s-triazines, QSRR, chemometrics, chromatography, molecular descriptors

Procedia PDF Downloads 371

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

Abstract:

Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

Procedia PDF Downloads 65

Authors: Yair Bleiberg, Michael Werman

Abstract:

Coordinate-based Multi-Layer Perceptrons (MLPs) are known to have difficulty reconstructing high frequencies of the training data. A common solution to this problem is Positional Encoding (PE), which has become quite popular. However, PE has drawbacks. It has high-frequency artifacts and adds another hyper hyperparameter, just like batch normalization and dropout do. We believe that under certain circumstances, PE is not necessary, and a smarter construction of the network architecture together with a smart training method is sufficient to achieve similar results. In this paper, we show that very simple MLPs can quite easily output a frequency when given input of the half-frequency and quarter-frequency. Using this, we design a network architecture in blocks, where the input to each block is the output of the two previous blocks along with the original input. We call this a Fibonacci Network. By training each block on the corresponding frequencies of the signal, we show that Fibonacci Networks can reconstruct arbitrarily high frequencies.

Keywords: neural networks, positional encoding, high frequency intepolation, fully connected

Procedia PDF Downloads 63

Authors: Maryam Hamedanlou, Shahla Hajializadeh

Abstract:

The transdermal drug delivery system is one of the types of novel drug delivery system that the drug is absorbed into the skin. The major considerations for designing and producing transdermal patch are small size, suitable drug release and good adhering. In this study, drug-in-adhesive transdermal patch contained non-steroidal anti-inflammatory ketoprofen is prepared. Also, the effect of non-woven fabric and plastic backing layers on adhesion properties is assessed. The results of the test, demonstrated the use of plastic backing layer increases tack and peel rather than non-woven fabric type. The balance tack with plastic backing layer patch is 6.7 (N/mm2), and the fabric one is 3.8 (N/mm2), and their peel is 9.2 (N/25mm) and 8.3 (N/25mm) by arrangement.

Keywords: transdermal drug delivery system, single layer patch of ketoprofen, plastic layer, fabric backing layer

Procedia PDF Downloads 231