Search results for: restarting application
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3224

Search results for: restarting application

1154 Study of Stress Wave Propagation with NHDMOC

Authors: G.Y. Zhang , M.L. Xu, R.Q. Zhang, W.H. Tang

Abstract:

MOC (method of cell) is a new method of investigating wave propagating in material with periodic microstructure, and can reflect the effect of microstructure. Wave propagation in periodically laminated medium consisting of linearly elastic layers can be treated as a special application of this method. In this paper, it was used to simulate the dynamic response of carbon-phenolic to impulsive loading under certain boundary conditions. From the comparison between the results obtained from this method and the exact results based on propagator matrix theory, excellent agreement is achieved. Conclusion can be made that the oscillation periodicity is decided by the thickness of sub-cells. In the end, the NHDMOC method, which permits studying stress wave propagation with one dimensional strain, was applied to study the one-dimensional stress wave propagation. In this paper, the ZWT nonlinear visco-elastic constitutive relationship with 7 parameters, NHDMOC, and corresponding equations were deduced. The equations were verified, comparing the elastic stress wave propagation in SHPB with, respectively, the elastic and the visco-elastic bar. Finally the dispersion and attenuation of stress wave in SHPB with visco-elastic bar was studied.

Keywords: MOC, NHDMOC, visco-elastic, wave propagation

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1153 Application of Tocopherol as Antioxidant to Reduce Decomposition Process on Palm Oil Biodiesel

Authors: Supriyono, Sumardiyono, Rendy J. Pramono

Abstract:

Biodiesel is one of the alternative fuels promising for substituting petrodiesel as energy source which has an advantage as it is sustainable and eco-friendly. Due to the raw material that tends to decompose during storage, biodiesel also has the same characteristic that tends to decompose during storage. Biodiesel decomposition will form higher acid value as the result of oxidation to double bond on a fatty acid compound on biodiesel. Thus, free fatty acid value could be used to evaluate degradation of biodiesel due to the oxidation process. High free fatty acid on biodiesel could impact on the engine performance. Decomposition of biodiesel due to oxidation reaction could prevent by introducing a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. Biodiesel made from high free fatty acid (FFA) crude palm oil (CPO) by using two steps esterification is vulnerable to oxidation process which is resulted in increasing on the FFA value. Tocopherol also known as vitamin E is one of the antioxidant that could improve the stability of biodiesel due to decomposition by the oxidation process. Tocopherol 0.5% concentration on palm oil biodiesel could reduce 13% of increasing FFA under temperature 80 °C and exposing time 180 minute.

Keywords: Antioxidant, biodiesel, decomposition, oxidation, tocopherol.

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1152 Application of Tocopherol as Antioxidant to Reduce Decomposition Process on Palm Oil Biodiesel

Authors: Supriyono, Sumardiyono, Rendy J. Pramono

Abstract:

Biodiesel is one of the alternative fuels promising for substituting petrodiesel as energy source which has an advantage as it is sustainable and eco-friendly. Due to the raw material that tends to decompose during storage, biodiesel also has the same characteristic that tends to decompose during storage. Biodiesel decomposition will form higher acid value as the result of oxidation to double bond on a fatty acid compound on biodiesel. Thus, free fatty acid value could be used to evaluate degradation of biodiesel due to the oxidation process. High free fatty acid on biodiesel could impact on the engine performance. Decomposition of biodiesel due to oxidation reaction could prevent by introducing a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. Biodiesel made from high free fatty acid (FFA) crude palm oil (CPO) by using two steps esterification is vulnerable to oxidation process which is resulted in increasing on the FFA value. Tocopherol also known as vitamin E is one of the antioxidant that could improve the stability of biodiesel due to decomposition by the oxidation process. Tocopherol 0.5% concentration on palm oil biodiesel could reduce 13% of increasing FFA under temperature 80 °C and exposing time 180 minute.

Keywords: Antioxidant, biodiesel, decomposition, oxidation, tocopherol.

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1151 Application of STATCOM-SMES Compensator for Power System Dynamic Performance Improvement

Authors: Reza Sedaghati, Mojtaba Hakimzadeh, Mohammad Hasan Raouf, Mostafa Mirzadeh

Abstract:

Nowadays the growth of distributed generation within the bulk power system is feasible by using the optimal control of the transmission lines power flow. Static Synchronous Compensators (STATCOM) is effective for improving voltage stability but it can only exchange reactive power with the power grid. The integration of Superconducting Magnetic Energy Storage (SMES) with a STATCOM can extend the traditional STATCOM capabilities to four-quadrant bulk power system power flow control and providing exchange both the active and reactive power related to the STATCOM with the ac network. This paper shows how the SMES system can be connected to the ac system via the DC bus of a STATCOM and also analyzes how the integration of STATCOM and SMES allows the bus voltage regulation and power oscillation damping (POD) to be achieved simultaneously. The dynamic performance of the integrated STATCOM-SMES is evaluated through simulation by using PSCAD/EMTDC software and the compensation effectiveness of this integrated compensator is shown.

Keywords: STATCOM-SMES compensator, Power Oscillation Damping (POD), stabilizing, signal, voltage.

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1150 Maximum Power Point Tracking for Small Scale Wind Turbine Using Multilayer Perceptron Neural Network Implementation without Mechanical Sensor

Authors: Piyangkun Kukutapan, Siridech Boonsang

Abstract:

The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: Maximum power point tracking, multilayer perceptron neural network, optimal duty cycle.

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1149 Determining Cluster Boundaries Using Particle Swarm Optimization

Authors: Anurag Sharma, Christian W. Omlin

Abstract:

Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.

Keywords: Particle swarm optimization, self-organizing maps, clustering, data mining.

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1148 Probabilistic Bhattacharya Based Active Contour Model in Structure Tensor Space

Authors: Hiren Mewada, Suprava Patnaik

Abstract:

Object identification and segmentation application requires extraction of object in foreground from the background. In this paper the Bhattacharya distance based probabilistic approach is utilized with an active contour model (ACM) to segment an object from the background. In the proposed approach, the Bhattacharya histogram is calculated on non-linear structure tensor space. Based on the histogram, new formulation of active contour model is proposed to segment images. The results are tested on both color and gray images from the Berkeley image database. The experimental results show that the proposed model is applicable to both color and gray images as well as both texture images and natural images. Again in comparing to the Bhattacharya based ACM in ICA space, the proposed model is able to segment multiple object too.

Keywords: Active Contour, Bhattacharya Histogram, Structure tensor, Image segmentation.

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1147 A Comparative Study of SVM Classifiers and Artificial Neural Networks Application for Rolling Element Bearing Fault Diagnosis using Wavelet Transform Preprocessing

Authors: Commander Sunil Tyagi

Abstract:

Effectiveness of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) classifiers for fault diagnosis of rolling element bearings are presented in this paper. The characteristic features of vibration signals of rotating driveline that was run in its normal condition and with faults introduced were used as input to ANN and SVM classifiers. Simple statistical features such as standard deviation, skewness, kurtosis etc. of the time-domain vibration signal segments along with peaks of the signal and peak of power spectral density (PSD) are used as features to input the ANN and SVM classifier. The effect of preprocessing of the vibration signal by Discreet Wavelet Transform (DWT) prior to feature extraction is also studied. It is shown from the experimental results that the performance of SVM classifier in identification of bearing condition is better then ANN and pre-processing of vibration signal by DWT enhances the effectiveness of both ANN and SVM classifier

Keywords: ANN, Artificial Intelligence, Fault Diagnosis, Pattern Recognition, Rolling Element Bearing, SVM. Wavelet Transform

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1146 Application of Vortex Tubes for Extracting Sediments Using SHARC Software - A Case Study of the Western Canal in the Dez Diversion Weir

Authors: A. H. Sajedi Pour, N. Hedayat, Z. Yazdi

Abstract:

Sediment loads transfer in hydraulic installations and their consequences for the O&M of modern canal systems is emerging as one of the most important considerations in hydraulic engineering projects apriticularly those which are inteded to feed the irrigation and draiange schemes of large command areas such as the Dez and Mogahn in Iran.. The aim of this paper is to investigate the applicability of the vortex tube as a viable means of extracting sediment loads entering the canal systems in general and the water inatke structures in particulars. The Western conveyance canal of the Dez Diversion weir which feeds the Karkheh Flood Plain in Sothwestern Dezful has been used as the case study using the data from the Dastmashan Hydrometric Station. The SHARC software has been used as an analytical framework to interprete the data. Results show that given the grain size D50 and the canal turbulence the adaption length from the beginning of the canal and after the diversion dam is estimated at 477 m, a point which is suitable for laying the vortex tube.

Keywords: Vortex tube, sediments, western canal, SHARCmodel

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1145 Enhanced Performance for Support Vector Machines as Multiclass Classifiers in Steel Surface Defect Detection

Authors: Ehsan Amid, Sina Rezaei Aghdam, Hamidreza Amindavar

Abstract:

Steel surface defect detection is essentially one of pattern recognition problems. Support Vector Machines (SVMs) are known as one of the most proper classifiers in this application. In this paper, we introduce a more accurate classification method by using SVMs as our final classifier of the inspection system. In this scheme, multiclass classification task is performed based on the "one-againstone" method and different kernels are utilized for each pair of the classes in multiclass classification of the different defects. In the proposed system, a decision tree is employed in the first stage for two-class classification of the steel surfaces to "defect" and "non-defect", in order to decrease the time complexity. Based on the experimental results, generated from over one thousand images, the proposed multiclass classification scheme is more accurate than the conventional methods and the overall system yields a sufficient performance which can meet the requirements in steel manufacturing.

Keywords: Steel Surface Defect Detection, Support Vector Machines, Kernel Methods.

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1144 An Expert System for Assessment of Learning Outcomes for ABET Accreditation

Authors: M. H. Imam, Imran A. Tasadduq, Abdul-Rahim Ahmad, Fahd M. Aldosari

Abstract:

Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.

Keywords: Expert system, student outcomes, course learning outcomes, question attributes.

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1143 Numerical Analysis of the Performance of the DU91-W2-250 Airfoil for Straight-Bladed Vertical-Axis Wind Turbine Application

Authors: M. Raciti Castelli, G. Grandi, E. Benini

Abstract:

This paper presents a numerical analysis of the performance of a three-bladed Darrieus vertical-axis wind turbine based on the DU91-W2-250 airfoil. A complete campaign of 2-D simulations, performed for several values of tip speed ratio and based on RANS unsteady calculations, has been performed to obtain the rotor torque and power curves. Rotor performances have been compared with the results of a previous work based on the use of the NACA 0021 airfoil. Both the power coefficient and the torque coefficient have been determined as a function of the tip speed ratio. The flow field around rotor blades has also been analyzed. As a final result, the performance of the DU airfoil based rotor appears to be lower than the one based on the NACA 0021 blade section. This behavior could be due to the higher stall characteristics of the NACA profile, being the separation zone at the trailing edge more extended for the DU airfoil.

Keywords: CFD, vertical axis wind turbine, DU91-W2-250, NACA 0021

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1142 Clarification of the Essential of Life Cycle Cost upon Decision-Making Process: An Empirical Study in Building Projects

Authors: Ayedh Alqahtani, Andrew Whyte

Abstract:

Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process.

Keywords: Building projects, Capital cost, Life cycle cost, Maintenance costs, Operation costs.

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1141 The Customization of 3D Last Form Design Based On Weighted Blending

Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

Abstract:

When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, Customization, Reverse engineering, Weighted morphing, Shape blending.

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1140 Logistics Model for Improving Quality in Railway Transport

Authors: Eva Nedeliakova, Juraj Camaj, Jaroslav Masek

Abstract:

This contribution is focused on the methodology for identifying levels of quality and improving quality through new logistics model in railway transport. It is oriented on the application of dynamic quality models, which represent an innovative method of evaluation quality services. Through this conception, time factor, expected, and perceived quality in each moment of the transportation process within logistics chain can be taken into account. Various models describe the improvement of the quality which emphases the time factor throughout the whole transportation logistics chain. Quality of services in railway transport can be determined by the existing level of service quality, by detecting the causes of dissatisfaction employees but also customers, to uncover strengths and weaknesses. This new logistics model is able to recognize critical processes in logistic chain. It includes service quality rating that must respect its specific properties, which are unrepeatability, impalpability, their use right at the time they are provided and particularly changeability, which is significant factor in the conditions of rail transport as well. These peculiarities influence the quality of service regarding the constantly increasing requirements and that result in new ways of finding progressive attitudes towards the service quality rating.

Keywords: Logistics model, quality, railway transport.

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1139 Real Time Remote Monitoring and Fault Detection in Wind Turbine

Authors: Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui

Abstract:

In new energy development, wind power has boomed. It is due to the proliferation of wind parks and their operation in supplying the national electric grid with low cost and clean resources. Hence, there is an increased need to establish a proactive maintenance for wind turbine machines based on remote control and monitoring. That is necessary with a real-time wireless connection in offshore or inaccessible locations while the wired method has many flaws. The objective of this strategy is to prolong wind turbine lifetime and to increase productivity. The hardware of a remote control and monitoring system for wind turbine parks is designed. It takes advantage of GPRS or Wi-Max wireless module to collect data measurements from different wind machine sensors through IP based multi-hop communication. Computer simulations with Proteus ISIS and OPNET software tools have been conducted to evaluate the performance of the studied system. Study findings show that the designed device is suitable for application in a wind park.

Keywords: Embedded System, Monitoring, Wind Turbine, Faults Diagnosis, TCP/IP Protocol, Real Time, Web.

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1138 Electric Field Effect on the Rise of Single Bubbles during Boiling

Authors: N. Masoudnia, M. Fatahi

Abstract:

An experimental study of saturated pool boiling on a single artificial nucleation site without and with the application of an electric field on the boiling surface has been conducted. N-pentane is boiling on a copper surface and is recorded with a high speed camera providing high quality pictures and movies. The accuracy of the visualization allowed establishing an experimental bubble growth law from a large number of experiments. This law shows that the evaporation rate is decreasing during the bubble growth, and underlines the importance of liquid motion induced by the preceding bubble. Bubble rise is therefore studied: once detached, bubbles accelerate vertically until reaching a maximum velocity in good agreement with a correlation from literature. The bubbles then turn to another direction. The effect of applying an electric field on the boiling surface in finally studied. In addition to changes of the bubble shape, changes are also shown in the liquid plume and the convective structures above the surface. Lower maximum rising velocities were measured in the presence of electric fields, especially with a negative polarity.

Keywords: Single bubbles, electric field, boiling, effect.

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1137 Material Handling Equipment Selection using Hybrid Monte Carlo Simulation and Analytic Hierarchy Process

Authors: Amer M. Momani, Abdulaziz A. Ahmed

Abstract:

The many feasible alternatives and conflicting objectives make equipment selection in materials handling a complicated task. This paper presents utilizing Monte Carlo (MC) simulation combined with the Analytic Hierarchy Process (AHP) to evaluate and select the most appropriate Material Handling Equipment (MHE). The proposed hybrid model was built on the base of material handling equation to identify main and sub criteria critical to MHE selection. The criteria illustrate the properties of the material to be moved, characteristics of the move, and the means by which the materials will be moved. The use of MC simulation beside the AHP is very powerful where it allows the decision maker to represent his/her possible preference judgments as random variables. This will reduce the uncertainty of single point judgment at conventional AHP, and provide more confidence in the decision problem results. A small business pharmaceutical company is used as an example to illustrate the development and application of the proposed model.

Keywords: Analytic Hierarchy Process (AHP), Materialhandling equipment selection, Monte Carlo simulation, Multi-criteriadecision making

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1136 DEA Method for Evaluation of EU Performance

Authors: M. Staníčková

Abstract:

The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.

Keywords: CCR CRS model, cluster analysis, DEA method, efficiency, EU, Malmquist index, performance.

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1135 Performance of Air Gap Membrane Distillation for Desalination of Ground Water and Seawater

Authors: Bhausaheb L. Pangarkar, M.G. Sane

Abstract:

Membrane distillation (MD) is a rising technology for seawater or brine desalination process. In this work, an air gap membrane distillation (AGMD) performance was investigated for aqueous NaCl solution along with natural ground water and seawater. In order to enhance the performance of the AGMD process in desalination, that is, to get more flux, it is necessary to study the effect of operating parameters on the yield of distillate water. The influence of operational parameters such as feed flow rate, feed temperature, feed salt concentration, coolant temperature and air gap thickness on the membrane distillation (MD) permeation flux have been investigated for low and high salt solution. the natural application of ground water and seawater over 90 h continuous operation, scale deposits observed on the membrane surface and reduction in flux represents 23% for ground water and 60% for seawater, in 90 h. This reduction was eliminated (less than 14 %) by acidification of feed water. Hence, promote the research attention in apply of AGMD for the ground water as well as seawater desalination over today-s conventional RO operation.

Keywords: MD, ground water, seawater, AGMD.

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1134 NGN and WiMAX: Putting the Pieces Together

Authors: Mohamed K. Watfa, Khaled Abdel Naby, Chetan Govind Bhatia

Abstract:

With the exponential rise in the number of multimedia applications available, the best-effort service provided by the Internet today is insufficient. Researchers have been working on new architectures like the Next Generation Network (NGN) which, by definition, will ensure Quality of Service (QoS) in an all-IP based network [1]. For this approach to become a reality, reservation of bandwidth is required per application per user. WiMAX (Worldwide Interoperability for Microwave Access) is a wireless communication technology which has predefined levels of QoS which can be provided to the user [4]. IPv6 has been created as the successor for IPv4 and resolves issues like the availability of IP addresses and QoS. This paper provides a design to use the power of WiMAX as an NSP (Network Service Provider) for NGN using IPv6. The use of the Traffic Class (TC) field and the Flow Label (FL) field of IPv6 has been explained for making QoS requests and grants [6], [7]. Using these fields, the processing time is reduced and routing is simplified. Also, we define the functioning of the ASN gateway and the NGN gateway (NGNG) which are edge node interfaces in the NGNWiMAX design. These gateways ensure QoS management through built in functions and by certain physical resources and networking capabilities.

Keywords: WiMAX, NGN, QoS, IPv6, Flow Label, ASNGateway

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1133 Density Clustering Based On Radius of Data (DCBRD)

Authors: A.M. Fahim, A. M. Salem, F. A. Torkey, M. A. Ramadan

Abstract:

Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.

Keywords: Clustering Algorithms, Arbitrary Shape of clusters, cluster Analysis.

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1132 Crystalline Structure of Starch Based Nano Composites

Authors: Farid Amidi Fazli, Afshin Babazadeh, Farnaz Amidi Fazli

Abstract:

In contrast with literal meaning of nano, researchers have been achieved mega adventures in this area and every day more nanomaterials are being introduced to the market. After long time application of fossil-based plastics, nowadays accumulation of their waste seems to be a big problem to the environment. On the other hand, mankind has more attention to safety and living environment. Replacing common plastic packaging materials with degradable ones that degrade faster and convert to non-dangerous components like water and carbon dioxide have more attractions; these new materials are based on renewable and inexpensive sources of starch and cellulose. However, the functional properties of them do not suitable for packaging. At this point, nanotechnology has an important role. Utilizing of nanomaterials in polymer structure will improve mechanical and physical properties of them; nanocrystalline cellulose (NCC) has this ability. This work has employed a chemical method to produce NCC and starch bio nanocomposite containing NCC. X-Ray Diffraction technique has characterized the obtained materials. Results showed that applied method is a suitable one as well as applicable one to NCC production.

Keywords: Biofilm, cellulose, nanocomposite, starch.

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1131 Effect of Domestic Treated Wastewater use on Three Varieties of Amaranth (Amaranthus spp.) under Semi Arid Conditions

Authors: El Youssfi L., Choukr-Allah R., Zaafrani M., Mediouni T., Sarr F, Hirich A.

Abstract:

An experiment was implemented in a filed in the south of Morocco to evaluate the effects of domestic treated wastewater use for irrigation of amaranth crop under semi-arid conditions. Three varieties (A0020, A0057 & A211) were tested and irrigated using domestic treated wastewater EC1 (0,92 dS/m) as control, EC3 (3dS/m) and EC6 (6dS/m) obtained by adding sea water. In term of growth, an increase of the EC level of applied irrigation water reduced significantly the plant-s height, leaf area, fresh and dry weight measured at vegetative, flowering and maturity stage for all varieties. Even with the application of the EC6, yields were relatively higher in comparison with the once obtained in normal cultivation conditions. A significant accumulation of nitrate, chloride and sodium in soil layers during the crop cycle was noted. The use of treated waste water for its irrigation is proved to be possible. The variety A211 had showed to be less sensitive to salinity stress and it could be more promising its introduction to study area.

Keywords: Amaranth, salinity, semi-arid, treated waste water.

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1130 Applications of Carbon Fibers Produced from Polyacrylonitrile Fibers

Authors: R. Eslami Farsani, R. Fazaeli

Abstract:

Carbon fibers have specific characteristics in comparison with industrial and structural materials used in different applications. Special properties of carbon fibers make them attractive for reinforcing and fabrication of composites. These fibers have been utilized for composites of metals, ceramics and plastics. However, it-s mainly used in different forms to reinforce lightweight polymer materials such as epoxy resin, polyesters or polyamides. The composites of carbon fiber are stronger than steel, stiffer than titanium, and lighter than aluminum and nowadays they are used in a variety of applications. This study explains applications of carbon fibers in different fields such as space, aviation, transportation, medical, construction, energy, sporting goods, electronics, and the other commercial/industrial applications. The last findings of composites with polymer, metal and ceramic matrices containing carbon fibers and their applications in the world investigated. Researches show that carbon fibers-reinforced composites due to unique properties (including high specific strength and specific modulus, low thermal expansion coefficient, high fatigue strength, and high thermal stability) can be replaced with common industrial and structural materials.

Keywords: Polyacrylonitrile Fibers, Carbon Fibers, Application

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1129 Worker Behavior Interpretation for Flexible Production

Authors: Bastian Hartmann, Christoph Schauer, Norbert Link

Abstract:

This paper addresses the problem of recognizing and interpreting the behavior of human workers in industrial environments for the purpose of integrating humans in software controlled manufacturing environments. In this work we propose a generic concept in order to derive solutions for task-related manual production applications. Thus, we are able to use a versatile concept providing flexible components and being less restricted to a specific problem or application. We instantiate our concept in a spot welding scenario in which the behavior of a human worker is interpreted when performing a welding task with a hand welding gun. We acquire signals from inertial sensors, video cameras and triggers and recognize atomic actions by using pose data from a marker based video tracking system and movement data from inertial sensors. Recognized atomic actions are analyzed on a higher evaluation level by a finite state machine.

Keywords: activity recognition, task modeling, marker-based video-tracking, inertial sensors.

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1128 Business-Intelligence Mining of Large Decentralized Multimedia Datasets with a Distributed Multi-Agent System

Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: Agent-oriented modeling, business Intelligence management, distributed data mining, multi-agent system.

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1127 Application of PSK Modulation in ADS-B 1090 Extended Squitter Authentication

Authors: A-Q. Nguyen. A. Amrhar, J. Zambrano, G. Brown, O.A. Yeste-Ojeda, R. Jr. Landry

Abstract:

Since the presence of Next Generation Air Transportation System (NextGen), Automatic Dependent Surveillance-Broadcast (ADS-B) has raised specific concerns related to the privacy and security, due to its vulnerable, low-level of security and limited payload. In this paper, the authors introduce and analyze the combination of Pulse Amplitude Modulation (PAM) and Phase Shift Keying (PSK) Modulation in conventional ADS-B, forming Secure ADS-B (SADS-B) avionics. In order to demonstrate the potential of this combination, Hardware-in-the-loop (HIL) simulation was used. The tests' results show that, on the one hand, SADS-B can offer five times the payload as its predecessor. This additional payload of SADS-B can be used in various applications, therefore enhancing the ability and efficiency of the current ADS-B. On the other hand, by using the extra phase modulated bits as a digital signature to authenticate ADS-B messages, SADS-B can increase the security of ADS-B, thus ensure a more secure aviation as well. More importantly, SADS-B is compatible with the current ADS-B In and Out. Hence, no significant modifications will be needed to implement this idea. As a result, SADS-B can be considered the most promising approach to enhance the capability and security of ADS-B.

Keywords: ADS-B authentication, ADS-B security, NextGen ADS-B, PSK signature, secure ADS-B.

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1126 SNR Classification Using Multiple CNNs

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: Classification, classifier fusion, CNN, Deep Learning, prediction, SNR.

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1125 RASPE – Risk Advisory Smart System for Pipeline Projects in Egypt

Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

Abstract:

A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. Paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: Expert System, Knowledge Management, Pipeline Projects, Risk Mismanagement.

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