Search results for: Multi Layer Perceptron
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2602

Search results for: Multi Layer Perceptron

2512 A Large-Eddy Simulation of Vortex Cell flow with Incoming Turbulent Boundary Layer

Authors: Arpiruk Hokpunna, Michael Manhart

Abstract:

We present a Large-Eddy simulation of a vortex cell with circular shaped. The results show that the flow field can be sub divided into four important zones, the shear layer above the cavity, the stagnation zone, the vortex core in the cavity and the boundary layer along the wall of the cavity. It is shown that the vortex core consits of solid body rotation without much turbulence activity. The vortex is mainly driven by high energy packets that are driven into the cavity from the stagnation point region and by entrainment of fluid from the cavity into the shear layer. The physics in the boundary layer along the cavity-s wall seems to be far from that of a canonical boundary layer which might be a crucial point for modelling this flow.

Keywords: Turbulent flow, Large eddy simulations, boundary layer and cavity flow, vortex cell flow.

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2511 Algorithm and Software Based on Multilayer Perceptron Neural Networks for Estimating Channel Use in the Spectral Decision Stage in Cognitive Radio Networks

Authors: Danilo López, Johana Hernández, Edwin Rivas

Abstract:

The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: Cognitive radio, neural network, prediction, primary user.

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2510 Classification of Potential Biomarkers in Breast Cancer Using Artificial Intelligence Algorithms and Anthropometric Datasets

Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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2509 Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval

Authors: L. Bennaceur Farah, I. R. Farah, R. Bennaceur, Z. Belhadj, M. R. Boussema

Abstract:

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Keywords: Remote sensing, rough surfaces, inverse problems, SAR, radar scattering, Neural networks and Fractals.

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2508 Seismic Excitation of Steel Frame Retrofitted by a Multi-Panel PMC Infill Wall

Authors: Bu Seog Ju, Woo Young Jung

Abstract:

A multi-panel PMC infilled system, using polymer matrix composite (PMC) material, was introduced as new conceptual design for seismic retrofitting. A proposed multi panel PMC infilled system was composed of two basic structural components: inner PMC sandwich infills and outer FRP damping panels. The PMC material had high stiffness-to-weight and strength-to-weight ratios. Therefore, the addition of PMC infill panels into existing structures would not significantly alter the weight of the structure, while providing substantial structural enhancement.

In this study, an equivalent linearized dynamic analysis for a proposed multi-panel PMC infilled frame was performed, in order to assess their effectiveness and their responses under the simulated earthquake loading. Upon comparing undamped (without PMC panel) and damped (with PMC panel) structures, numerical results showed that structural damping with passive interface damping layer could significantly enhance the seismic response.

Keywords: Polymer Matrix Composite (PMC), Panel, Piece-wise linear, Earthquake, FRP.

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2507 Development of Energy Management System Based on Internet of Things Technique

Authors: Wen-Jye Shyr, Chia-Ming Lin, Hung-Yun Feng

Abstract:

The purpose of this study was to develop an energy management system for university campuses based on the Internet of Things (IoT) technique. The proposed IoT technique based on WebAccess is used via network browser Internet Explore and applies TCP/IP protocol. The case study of IoT for lighting energy usage management system was proposed. Structure of proposed IoT technique included perception layer, equipment layer, control layer, application layer and network layer.

Keywords: Energy management, IoT technique, Sensor, WebAccess

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2506 A Metric-Set and Model Suggestion for Better Software Project Cost Estimation

Authors: Murat Ayyıldız, Oya Kalıpsız, Sırma Yavuz

Abstract:

Software project effort estimation is frequently seen as complex and expensive for individual software engineers. Software production is in a crisis. It suffers from excessive costs. Software production is often out of control. It has been suggested that software production is out of control because we do not measure. You cannot control what you cannot measure. During last decade, a number of researches on cost estimation have been conducted. The metric-set selection has a vital role in software cost estimation studies; its importance has been ignored especially in neural network based studies. In this study we have explored the reasons of those disappointing results and implemented different neural network models using augmented new metrics. The results obtained are compared with previous studies using traditional metrics. To be able to make comparisons, two types of data have been used. The first part of the data is taken from the Constructive Cost Model (COCOMO'81) which is commonly used in previous studies and the second part is collected according to new metrics in a leading international company in Turkey. The accuracy of the selected metrics and the data samples are verified using statistical techniques. The model presented here is based on Multi-Layer Perceptron (MLP). Another difficulty associated with the cost estimation studies is the fact that the data collection requires time and care. To make a more thorough use of the samples collected, k-fold, cross validation method is also implemented. It is concluded that, as long as an accurate and quantifiable set of metrics are defined and measured correctly, neural networks can be applied in software cost estimation studies with success

Keywords: Software Metrics, Software Cost Estimation, Neural Network.

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2505 A Consistency Protocol Multi-Layer for Replicas Management in Large Scale Systems

Authors: Ghalem Belalem, Yahya Slimani

Abstract:

Large scale systems such as computational Grid is a distributed computing infrastructure that can provide globally available network resources. The evolution of information processing systems in Data Grid is characterized by a strong decentralization of data in several fields whose objective is to ensure the availability and the reliability of the data in the reason to provide a fault tolerance and scalability, which cannot be possible only with the use of the techniques of replication. Unfortunately the use of these techniques has a height cost, because it is necessary to maintain consistency between the distributed data. Nevertheless, to agree to live with certain imperfections can improve the performance of the system by improving competition. In this paper, we propose a multi-layer protocol combining the pessimistic and optimistic approaches conceived for the data consistency maintenance in large scale systems. Our approach is based on a hierarchical representation model with tree layers, whose objective is with double vocation, because it initially makes it possible to reduce response times compared to completely pessimistic approach and it the second time to improve the quality of service compared to an optimistic approach.

Keywords: Data Grid, replication, consistency, optimistic approach, pessimistic approach.

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2504 A Study of Thermal Convection in Two Porous Layers Governed by Brinkman's Model in Upper Layer and Darcy's Model in Lower Layer

Authors: M. S. Al-Qurashi

Abstract:

This work examines thermal convection in two porous layers. Flow in the upper layer is governed by Brinkman-s equations model and in the lower layer is governed by Darcy-s model. Legendre polynomials are used to obtain numerical solution when the lower layer is heated from below.

Keywords: Brinkman's law, Darcy's law, porous layers, Legendre polynomials, the Oberbeck-Boussineq approximation.

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2503 Automated Textile Defect Recognition System Using Computer Vision and Artificial Neural Networks

Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

Abstract:

Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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2502 Shear-Layer Instabilities of a Pulsed Stack-Issued Transverse Jet

Authors: Ching M. Hsu, Rong F. Huang, Michael E. Loretero

Abstract:

Shear-layer instabilities of a pulsed stack-issued transverse jet were studied experimentally in a wind tunnel. Jet pulsations were induced by means of acoustic excitation. Streak pictures of the smoke-flow patterns illuminated by the laser-light sheet in the median plane were recorded with a high-speed digital camera. Instantaneous velocities of the shear-layer instabilities in the flow were digitized by a hot-wire anemometer. By analyzing the streak pictures of the smoke-flow visualization, three characteristic flow modes, synchronized flapping jet, transition, and synchronized shear-layer vortices, are identified in the shear layer of the pulsed stack-issued transverse jet at various excitation Strouhal numbers. The shear-layer instabilities of the pulsed stack-issued transverse jet are synchronized by acoustic excitation except for transition mode. In transition flow mode, the shear-layer vortices would exhibit a frequency that would be twice as great as the acoustic excitation frequency.

Keywords: Acoustic excitation, jet in crossflow, shear-layer instability.

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2501 Experimental and Numerical Investigation of Air Ejector with Diffuser with Boundary Layer Suction

Authors: Vaclav Dvorak

Abstract:

The article deals with experimental and numerical investigation of axi-symmetric subsonic air to air ejector with diffuser adapted for boundary layer suction. The diffuser, which is placed behind the mixing chamber of the ejector, has high divergence angle and therefore low efficiency. To increase the efficiency, the diffuser is equipped with slot enabling boundary layer suction. The effect of boundary layer suction on flow in ejector, static pressure distribution on the mixing chamber wall and characteristic were measured and studied numerically. Both diffuser and ejector efficiency were evaluated. The diffuser efficiency was increased, however, the efficiency of ejector itself remained low.

Keywords: Air ejector, boundary layer suction, CFD, diffuser.

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2500 Numerical Investigation of Instabilities in Free Shear Layer Produced by NS-DBD Actuator

Authors: Ilya Popov, Steven Hulshoff

Abstract:

A numerical investigation of the effects of nanosecond barrier discharge on the stability of a two-dimensional free shear layer is performed. The computations are carried out using a compressible Navier-Stokes algorithm coupled with a thermodynamic model of the discharge. The results show that significant increases in the shear layer-s momentum thickness and Reynolds stresses occur due to actuation. Dependence on both frequency and amplitude of actuation are considered, and a comparison is made of the computed growth rates with those predicted by linear stability theory. Amplitude and frequency ranges for the efficient promotion of shear-layer instabilities are identified.

Keywords: NS-DBD, plasma, actuator, flow control, instability, shear layer

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2499 Predicting Application Layer DDoS Attacks Using Machine Learning Algorithms

Authors: S. Umarani, D. Sharmila

Abstract:

A Distributed Denial of Service (DDoS) attack is a major threat to cyber security. It originates from the network layer or the application layer of compromised/attacker systems which are connected to the network. The impact of this attack ranges from the simple inconvenience to use a particular service to causing major failures at the targeted server. When there is heavy traffic flow to a target server, it is necessary to classify the legitimate access and attacks. In this paper, a novel method is proposed to detect DDoS attacks from the traces of traffic flow. An access matrix is created from the traces. As the access matrix is multi dimensional, Principle Component Analysis (PCA) is used to reduce the attributes used for detection. Two classifiers Naive Bayes and K-Nearest neighborhood are used to classify the traffic as normal or abnormal. The performance of the classifier with PCA selected attributes and actual attributes of access matrix is compared by the detection rate and False Positive Rate (FPR).

Keywords: Distributed Denial of Service (DDoS) attack, Application layer DDoS, DDoS Detection, K- Nearest neighborhood classifier, Naive Bayes Classifier, Principle Component Analysis.

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2498 A Frequency Dependence of the Phase Field Model in Laminar Boundary Layer with Periodic Perturbations

Authors: Yasuo Obikane

Abstract:

The frequency dependence of the phase field model(PFM) is studied. A simple PFM is proposed, and is tested in a laminar boundary layer. The Blasius-s laminar boundary layer solution on a flat plate is used for the flow pattern, and several frequencies are imposed on the PFM, and the decay times of the interfaces are obtained. The computations were conducted for three cases: 1) no-flow, and 2) a half ball on the laminar boundary layer, 3) a line of mass sources in the laminar boundary layer. The computations show the decay time becomes shorter as the frequency goes larger, and also show that it is sensitive to both background disturbances and surface tension parameters. It is concluded that the proposed simple PFM can describe the properties of decay process, and could give the fundamentals for the decay of the interface in turbulent flows.

Keywords: Phase field model, two phase flows, Laminarboundary Layer

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2497 Effect of Utilization of Geosynthetic on Reducing the Required Thickness of Subbase Layer of a Two Layered Soil

Authors: R. Ziaie Moayed, M. Nazari

Abstract:

This paper tries to study the effect of geosynthetic inclusion on the improvement of the load-settlement characters of two layered soil. In addition, the effect of geogrid and geotextile in reduction of the required thickness of subbase layer in unpaved roads is studied. Considering the vast application of bearing ratio tests in road construction projects, this test is used in present investigation. Bearing ratio tests were performed on two layered soil including a granular soil layer at the top (as the subbase layer) and a weak clayey soil placed at the bottom (as the subgrade layer). These tests were performed for different conditions including unreinforced and reinforced by geogrid and geotextile and three thicknesses for top layer soil (subbase layer). In the reinforced condition the reinforcing element was placed on the interface of the top granular layer and the beneath clayey layer to study the separation effect of geosynthetics. In all tests the soils (both granular and clayey soil layers) were compacted according to optimum water content. At the end, the diagrams were plotted and were compared with each other. Furthermore, a comparison between geogrids and geotextiles behaviors on two layer soil is done in this paper. The results show an increase in compression strength of reinforced specimen in comparison with unreinforced soil sample. The effect of geosynthetic inclusion reduces by increasing the subbase thickness. In addition it was found that geogrids have more desirable behavior rather than geotextiles due to interlocking with the subbase layer aggregates.

Keywords: Bearing ratio, Subgrade, Subbase, Sand layer thickness, Geosynthetic.

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2496 Multi-Case Multi-Objective Simulated Annealing (MC-MOSA): New Approach to Adapt Simulated Annealing to Multi-objective Optimization

Authors: Abdelfatteh Haidine, Ralf Lehnert

Abstract:

In this paper a new approach is proposed for the adaptation of the simulated annealing search in the field of the Multi-Objective Optimization (MOO). This new approach is called Multi-Case Multi-Objective Simulated Annealing (MC-MOSA). It uses some basics of a well-known recent Multi-Objective Simulated Annealing proposed by Ulungu et al., which is referred in the literature as U-MOSA. However, some drawbacks of this algorithm have been found, and are substituted by other ones, especially in the acceptance decision criterion. The MC-MOSA has shown better performance than the U-MOSA in the numerical experiments. This performance is further improved by some other subvariants of the MC-MOSA, such as Fast-annealing MC-MOSA, Re-annealing MCMOSA and the Two-Stage annealing MC-MOSA.

Keywords: Simulated annealing, multi-objective optimization, acceptance decision criteria, re-annealing, two-stage annealing.

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2495 Buildings Founded on Thermal Insulation Layer Subjected to Earthquake Load

Authors: D. Koren, V. Kilar

Abstract:

The modern energy-efficient houses are often founded on a thermal insulation (TI) layer placed under the building’s RC foundation slab.The purpose of the paper is to identify the potential problems of the buildings founded on TI layer from the seismic point of view. The two main goals of the study were to assess the seismic behavior of such buildings, and to search for the critical structural parameters affecting the response of the superstructure as well as of the extruded polystyrene (XPS) layer. As a test building a multi-storeyed RC frame structure with and without the XPS layer under the foundation slab has been investigated utilizing nonlinear dynamic (time-history) and static (pushover) analyses. The structural response has been investigated with reference to the following performance parameters: i) Building’s lateral roof displacements, ii) Edge compressive and shear strains of the XPS, iii) Horizontal accelerations of the superstructure, iv) Plastic hinge patterns of the superstructure, v) Part of the foundation in compression, and vi) Deformations of the underlying soil and vertical displacements of the foundation slab (i.e. identifying the potential uplift). The results have shown that in the case of higher and stiff structures lying on firm soil the use of XPS under the foundation slab might induce amplified structural peak responses compared to the building models without XPS under the foundation slab. The analysis has revealed that the superstructure as well as the XPS response is substantially affected by the stiffness of the foundation slab.

Keywords: Extruded polystyrene (XPS), foundation on thermal insulation, energy-efficient buildings, nonlinear seismic analysis, seismic response, soil–structure interaction.

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2494 A Statistical Prediction of Likely Distress in Nigeria Banking Sector Using a Neural Network Approach

Authors: D. A. Farinde

Abstract:

One of the most significant threats to the economy of a nation is the bankruptcy of its banks. This study evaluates the susceptibility of Nigerian banks to failure with a view to identifying ratios and financial data that are sensitive to solvency of the bank. Further, a predictive model is generated to guide all stakeholders in the industry. Thirty quoted banks that had published Annual Reports for the year preceding the consolidation i.e. year 2004 were selected. They were examined for distress using the Multilayer Perceptron Neural Network Analysis. The model was used to analyze further reforms by the Central Bank of Nigeria using published Annual Reports of twenty quoted banks for the year 2008 and 2011. The model can thus be used for future prediction of failure in the Nigerian banking system.

Keywords: Bank, Bankruptcy, Financial Ratios, Neural Network, Multilayer Perceptron, Predictive Model

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2493 Sliding Mode Control with Fuzzy Boundary Layer to Air-Air Interception Problem

Authors: Mustafa Resa Becan

Abstract:

The performance of a type of fuzzy sliding mode control is researched by considering the nonlinear characteristic of a missile-target interception problem to obtain a robust interception process. The variable boundary layer by using fuzzy logic is proposed to reduce the chattering around the switching surface then is applied to the interception model which was derived. The performances of the sliding mode control with constant and fuzzy boundary layer are compared at the end of the study and the results are evaluated.

Keywords: Sliding mode control, fuzzy, boundary layer, interception problem.

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2492 Two and Three Layer Lamination of Nanofiber

Authors: Roman Knizek, Denisa Karhankova, Ludmila Fridrichova

Abstract:

For their exceptional properties nanofibers, respectively, nanofiber layers are achieving an increasingly wider range of uses. Nowadays nanofibers are used mainly in the field of air filtration where they are removing submicron particles, bacteria, and viruses. Their efficiency is not changed in time, and the power consumption is much lower than that of electrically charged filters. Nanofibers are primarily used for converting and storage of energy in both air and liquid filtration, in food and packaging, protecting the environment, but also in health care which is made possible by their newly discovered properties. However, a major problem of the nanofiber layer is practically zero abrasion resistance; it is, therefore, necessary to laminate the nanofiber layer with another suitable material. Unfortunately, lamination of nanofiber layers is a major problem since the nanofiber layer contains small pores through which it is very difficult for adhesion to pass through. Therefore, there is still only a small percentage of products with these unique fibers 5.

Keywords: Nanofiber layer, nanomembrane, lamination, electrospinning.

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2491 Bandwidth and Delay Aware Routing Protocol with Scheduling Algorithm for Multi Hop Mobile Ad Hoc Networks

Authors: Y. Harold Robinson, E. Golden Julie, S. Balaji

Abstract:

The scheduling based routing scheme is presented in this paper to avoid link failure. The main objective of this system is to introduce a cross-layer protocol framework that integrates routing with priority-based traffic management and distributed transmission scheduling. The reservation scheme is based on ID. The presented scheme guarantees that bandwidth reserved time slot is used by another packet in which end-to-end reservation is achieved. The Bandwidth and Delay Aware Routing Protocol with Scheduling Algorithm is presented to allocate channels efficiently. The experimental results show that the presented schemes performed well in various parameters compared to existing methods.

Keywords: Integrated routing, scheduling, MAC layer, IEEE 802.11.

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2490 High Efficiency Perovskite Solar Cells Fabricated under Ambient Conditions with Mesoporous TiO2/In2O3 Scaffold

Authors: A. Apostolopoulou, D. Sygkridou, A. N. Kalarakis, E. Stathatos

Abstract:

Mesoscopic perovskite solar cells (mp-PSCs) with mesoporous bilayer were fabricated under ambient conditions. The bilayer was formed by capping the mesoporous TiO2 layer with a layer of In2O3. CH3NH3I3-xClx mixed halide perovskite was prepared through the one-step method and was used as the light absorber. The mp-PSCs with the composite TiO2/In2O3 mesoporous layer exhibited optimized electrical parameters, compared with the PSCs that employed only a TiO2 mesoporous layer, with a current density of 23.86 mA/cm2, open circuit voltage of 0.863 V, fill factor of 0.6 and a power conversion efficiency of 11.2%. These results indicate that the formation of a proper semiconductor capping layer over the basic TiO2 mesoporous layer can facilitate the electron transfer, suppress the recombination and subsequently lead to higher charge collection efficiency.

Keywords: Ambient conditions, high efficiency solar cells, mesoscopic perovskite solar cells, TiO2/In2O3 bilayer.

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2489 Multilayer Neural Network and Fuzzy Logic Based Software Quality Prediction

Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

Abstract:

In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: Software quality, fuzzy logic, perceptron, prediction.

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2488 DAMQ-Based Approach for Efficiently Using the Buffer Spaces of a NoC Router

Authors: Mohammad Ali Jabraeil Jamali, Ahmad khademzadeh

Abstract:

In this paper we present high performance dynamically allocated multi-queue (DAMQ) buffer schemes for fault tolerance systems on chip applications that require an interconnection network. Two virtual channels shared the same buffer space. Fault tolerant mechanisms for interconnection networks are becoming a critical design issue for large massively parallel computers. It is also important to high performance SoCs as the system complexity keeps increasing rapidly. On the message switching layer, we make improvement to boost system performance when there are faults involved in the components communication. The proposed scheme is when a node or a physical channel is deemed as faulty, the previous hop node will terminate the buffer occupancy of messages destined to the failed link. The buffer usage decisions are made at switching layer without interactions with higher abstract layer, thus buffer space will be released to messages destined to other healthy nodes quickly. Therefore, the buffer space will be efficiently used in case fault occurs at some nodes.

Keywords: DAMQ, NoC, fault tolerant, odd-even routingalgorithm, buffer space.

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2487 Facile Synthesis of Vertically Aligned ZnO Nanowires on Carbon Layer by Vapour Deposition

Authors: Kh. A. Abdullin, N. B. Bakranov, S. E. Kudaibergenov, S.E. Kumekov, V. N. Ermolaev, L. V. Podrezova

Abstract:

A facile vapour deposition method of synthesis of vertically aligned ZnO nanowires on carbon seed layer was developed. The received samples were investigated on electronic microscope JSM-6490 LA JEOL and x-ray diffractometer X, pert MPD PRO. The photoluminescence spectra (PL) of obtained ZnO samples at a room temperature were studied using He-Cd laser (325 nm line) as excitation source.

Keywords: ZnO nanowires, vapor-phase deposition, Nicatalytic layer, facile method of synthesis, carbon catalytic layer, thephotoluminescence spectra, X-ray spectrum.

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2486 Behavior Factor of Flat Double-Layer Space Structures

Authors: Behnam Shirkhanghah, Vahid Shahbaznejhad-Fard, Houshyar Eimani-Kalesar, Babak Pahlevan

Abstract:

Flat double-layer grid is from category of space structures that are formed from two flat layers connected together with diagonal members. Increased stiffness and better seismic resistance in relation to other space structures are advantages of flat double layer space structures. The objective of this study is assessment and calculation of Behavior factor of flat double layer space structures. With regarding that these structures are used widely but Behavior factor used to design these structures against seismic force is not determined and exact, the necessity of study is obvious. This study is theoretical. In this study we used structures with span length of 16m and 20 m. All connections are pivotal. ANSYS software is used to non-linear analysis of structures.

Keywords: Behavior factor, Double-layer, Intensified resistance, Non-linear analysis

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2485 The Labeled Classification and its Application

Authors: M. Nemissi, H. Seridi, H. Akdag

Abstract:

This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propagation) algorithm through the addition of an extra feature (labels) to all training examples. To classify every new example, tests will be carried out each label. The simplicity of implementation is the main advantage of this approach because no modifications are required in the training algorithms. Therefore, it can be used with others techniques of acceleration and stabilization. In this work, two models of the labeled classification are proposed: the LMLP (Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro Fuzzy Classifier). These models are tested using Iris, wine, texture and human thigh databases to evaluate their performances.

Keywords: Artificial neural networks, Fusion of neural networkfuzzysystems, Learning theory, Pattern recognition.

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2484 Enhancing the Network Security with Gray Code

Authors: Thomas Adi Purnomo Sidhi

Abstract:

Nowadays, network is an essential need in almost every part of human daily activities. People now can seamlessly connect to others through the Internet. With advanced technology, our personal data now can be more easily accessed. One of many components we are concerned for delivering the best network is a security issue. This paper is proposing a method that provides more options for security. This research aims to improve network security by focusing on the physical layer which is the first layer of the OSI model. The layer consists of the basic networking hardware transmission technologies of a network. With the use of observation method, the research produces a schematic design for enhancing the network security through the gray code converter.

Keywords: Network, network security, gray code, physical layer.

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2483 Defect Detection of Tiles Using 2D-Wavelet Transform and Statistical Features

Authors: M.Ghazvini, S. A. Monadjemi, N. Movahhedinia, K. Jamshidi

Abstract:

In this article, a method has been offered to classify normal and defective tiles using wavelet transform and artificial neural networks. The proposed algorithm calculates max and min medians as well as the standard deviation and average of detail images obtained from wavelet filters, then comes by feature vectors and attempts to classify the given tile using a Perceptron neural network with a single hidden layer. In this study along with the proposal of using median of optimum points as the basic feature and its comparison with the rest of the statistical features in the wavelet field, the relational advantages of Haar wavelet is investigated. This method has been experimented on a number of various tile designs and in average, it has been valid for over 90% of the cases. Amongst the other advantages, high speed and low calculating load are prominent.

Keywords: Defect detection, tile and ceramic quality inspection, wavelet transform, classification, neural networks, statistical features.

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