Search results for: Turkey real estate sector
470 Modeling and Control of Direct Driven PMSG for Ultra Large Wind Turbines
Authors: Ahmed M. Hemeida, Wael A. Farag, Osama A. Mahgoub
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This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbine simulator that is able to produce realistic and validated conditions that occur in real ultra MW wind turbines. Three different packages are used to simulate this model, namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind simulator developed by National Renewable Energy Laboratory (NREL). The wind turbine mechanical parts are modeled by FAST (Fatigue, Aerodynamics, Structures and Turbulence) code which is also developed by NREL. Simulink is used to model the PMSG, full scale back to back IGBT converters, and the grid.Keywords: FAST, Permanent Magnet Synchronous Generator(PMSG), TurbSim, Vector Control and Pitch Control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5590469 Hybrid Structure Learning Approach for Assessing the Phosphate Laundries Impact
Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed
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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).
Keywords: Classification, Bayesian network; structure learning, K2 algorithm, expert knowledge, surface water analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 498468 A Case Study of Applying Virtual Prototyping in Construction
Authors: Stephen C. W. Kong
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The use of 3D computer-aided design (CAD) models to support construction project planning has been increasing in the previous year. 3D CAD models reveal more planning ideas by visually showing the construction site environment in different stages of the construction process. Using 3D CAD models together with scheduling software to prepare construction plan can identify errors in process sequence and spatial arrangement, which is vital to the success of a construction project. A number of 4D (3D plus time) CAD tools has been developed and utilized in different construction projects due to the awareness of their importance. Virtual prototyping extends the idea of 4D CAD by integrating more features for simulating real construction process. Virtual prototyping originates from the manufacturing industry where production of products such as cars and airplanes are virtually simulated in computer before they are built in the factory. Virtual prototyping integrates 3D CAD, simulation engine, analysis tools (like structural analysis and collision detection), and knowledgebase to streamline the whole product design and production process. In this paper, we present the application of a virtual prototyping software which has been used in a few construction projects in Hong Kong to support construction project planning. Specifically, the paper presents an implementation of virtual prototyping in a residential building project in Hong Kong. The applicability, difficulties and benefits of construction virtual prototyping are examined based on this project.Keywords: construction project planning, prefabrication, simulation, virtual prototyping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2809467 Emulation of a Wind Turbine Using Induction Motor Driven by Field Oriented Control
Authors: L. Benaaouinate, M. Khafallah, A. Martinez, A. Mesbahi, T. Bouragba
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This paper concerns with the modeling, simulation, and emulation of a wind turbine emulator for standalone wind energy conversion systems. By using emulation system, we aim to reproduce the dynamic behavior of the wind turbine torque on the generator shaft: it provides the testing facilities to optimize generator control strategies in a controlled environment, without reliance on natural resources. The aerodynamic, mechanical, electrical models have been detailed as well as the control of pitch angle using Fuzzy Logic for horizontal axis wind turbines. The wind turbine emulator consists mainly of an induction motor with AC power drive with torque control. The control of the induction motor and the mathematical models of the wind turbine are designed with MATLAB/Simulink environment. The simulation results confirm the effectiveness of the induction motor control system and the functionality of the wind turbine emulator for providing all necessary parameters of the wind turbine system such as wind speed, output torque, power coefficient and tip speed ratio. The findings are of direct practical relevance.
Keywords: Wind turbine, modeling, emulator, electrical generator, renewable energy, induction motor drive, field oriented control, real time control, wind turbine emulator, pitch angle control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1357466 A Theoretical Analysis for Modeling and Prediction of the Jet Engine Emissions
Authors: Jamal S. Yassin
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This paper is to formulate a mathematical model to predict the amounts of the emissions produced from the combustion process of the gas turbine unit of the jet engine. These emissions have bad impacts on the environment if they are out of standards, which cause real threats to all type of life on the earth. The amounts of the emissions from the gas turbine engine are functions to many operational and design factors. In landing-takeoff (LTO) these amounts are not the same as in taxi or cruise of the plane using jet engines, because of the difference in the activity period during these operating modes. These emissions can be affected by several physical and chemical variables, such as fuel type, fuel to air ratio or equivalence ratio, flame temperature, combustion pressure, in addition to some inlet conditions such as ambient temperature and air humidity. To study the influence of these variables on the amounts of these emissions during the combustion process in the gas turbine unit, a computer program has been developed by using the visual basic 6 software. Here, the analysis of the combustion process is carried out by considering it as a chemical reaction with shifting equilibrium to find the products of the combustion of the octane fuel, at different equivalence ratios, compressor pressure ratios (CPR) and combustion temperatures. The results obtained have shown that there is noticeable influence of the equivalence ratio, CPR, and the combustion temperature on the amounts of the main emissions which are considered pollutants, such as CO, CO2 and NO.
Keywords: Mathematical model, gas turbine unit, equivalence ratio, emissions, shifting equilibrium.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 724465 Toward Delegated Democracy: Vote by Yourself, or Trust Your Network
Authors: Hiroshi Yamakawa, Michiko Yoshida, Motohiro Tsuchiya
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The recent development of Information and Communication Technology (ICT) enables new ways of "democratic" decision-making such as a page-ranking system, which estimates the importance of a web page based on indirect trust on that page shared by diverse group of unorganized individuals. These kinds of "democracy" have not been acclaimed yet in the world of real politics. On the other hand, a large amount of data about personal relations including trust, norms of reciprocity, and networks of civic engagement has been accumulated in a computer-readable form by computer systems (e.g., social networking systems). We can use these relations as a new type of social capital to construct a new democratic decision-making system based on a delegation network. In this paper, we propose an effective decision-making support system, which is based on empowering someone's vote whom you trust. For this purpose, we propose two new techniques: the first is for estimating entire vote distribution from a small number of votes, and the second is for estimating active voter choice to promote voting using a delegation network. We show that these techniques could increase the voting ratio and credibility of the whole decision by agent-based simulations.
Keywords: Delegation, network centrality, social network, voting ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1775464 Analysis of Incidences of Collapsed Buildings in the City of Douala, Cameroon from 2011-2020
Authors: T. G. L. J. Bikoko, J. C. Tchamba, S. Amziane
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This study focuses on the problem of collapsed buildings within the city of Douala over the past ten years, and more precisely within the period from 2011 to 2020. It was carried out in a bid to ascertain the real causes of this phenomenon, which has become recurrent in the leading economic city of Cameroon. To achieve this, it was first necessary to review some works dealing with construction materials and technology as well as some case histories of structural collapse within the city. Thereafter, a statistical study was carried out on the results obtained. It was found that the causes of building collapses in the city of Douala are: Neglect of administrative procedures, use of poor quality materials, poor composition and confectioning of concrete, lack of Geotechnical study, lack of structural analysis and design, corrosion of the reinforcement bars, poor maintenance in buildings, and other causes. Out of the 46 cases of failure and collapse of buildings within the city of Douala, 7 of these were identified to have had no geotechnical study carried out, giving a percentage of 15.22%. It was also observed that out of the 46 cases of structural failure, 6 were as a result of lack of proper structural analysis and design giving a percentage of 13.04%. Subsequently, recommendations and suggestions are made in a bid to placing particular emphasis on the choice of materials, the manufacture and casting of concrete as well as the placement of the required reinforcements. All this guarantees the stability of a building.
Keywords: collapse buildings, Douala, structural collapse, Cameroon
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 829463 Design of a Fuzzy Feed-forward Controller for Monitor HAGC System of Cold Rolling Mill
Authors: S. Khosravi, A. Afshar, F. Barazandeh
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In this study we propose a novel monitor hydraulic automatic gauge control (HAGC) system based on fuzzy feedforward controller. This is used in the development of cold rolling mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in the entry steel strip. The proposed method uses a mathematical model of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In order to improve the speed of the controller in rejecting disturbances introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.Keywords: Fuzzy feed-forward controller, monitor HAGC system, dynamic mathematical model, entry strip thickness deviation compensation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2196462 The Impact of the Interest Rates on Investments in the Context of Financial Crisis
Authors: Joanna Stawska
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The main objective of this article is to examine the impact of interest rates on investments in Poland in the context of financial crisis. The paper also investigates the dependence of bank loans to enterprises on interbank market rates. The article studies the impact of interbank market rate on the level of investments in Poland. Besides, this article focuses on the research of the correlation between the level of corporate loans and the amount of investments in Poland in order to determine the indirect impact of central bank interest rates through the transmission mechanism of monetary policy on the real economy. To achieve the objective we have used econometric and statistical research methods like: econometric model and Pearson correlation coefficient. This analysis suggests that the central bank reference rate inversely proportionally affects the level of investments in Poland and this dependence is moderate. This is also important issue because it is related to preparing of Poland to accession to euro area. The research is important from both theoretical and empirical points of view. The formulated conclusions and recommendations determine the practical significance of the paper which may be used in the decision making process of monetary and economic authorities of the country.Keywords: Central bank, financial crisis, interest rate, investments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1588461 Energy Detection Based Sensing and Primary User Traffic Classification for Cognitive Radio
Authors: Urvee B. Trivedi, U. D. Dalal
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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.Keywords: Cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary User (PU), secondary user (SU), Fast Fourier transform (FFT), signal to noise ratio (SNR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1459460 Subjective Evaluation of Spectral and Time Domain Cascading Algorithm for Speech Enhancement for Mobile Communication
Authors: Harish Chander, Balwinder Singh, Ravinder Khanna
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In this paper, we present the comparative subjective analysis of Improved Minima Controlled Recursive Averaging (IMCRA) Algorithm, the Kalman filter and the cascading of IMCRA and Kalman filter algorithms. Performance of speech enhancement algorithms can be predicted in two different ways. One is the objective method of evaluation in which the speech quality parameters are predicted computationally. The second is a subjective listening test in which the processed speech signal is subjected to the listeners who judge the quality of speech on certain parameters. The comparative objective evaluation of these algorithms was analyzed in terms of Global SNR, Segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) by the authors and it was reported that with cascaded algorithms there is a substantial increase in objective parameters. Since subjective evaluation is the real test to judge the quality of speech enhancement algorithms, the authenticity of superiority of cascaded algorithms over individual IMCRA and Kalman algorithms is tested through subjective analysis in this paper. The results of subjective listening tests have confirmed that the cascaded algorithms perform better under all types of noise conditions.
Keywords: Speech enhancement, spectral domain, time domain, PESQ, subjective analysis, objective analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1222459 A Methodology for Creating Energy Sustainability in an Enterprise
Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala
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As we enter the new era of Artificial Intelligence (AI) and cloud computing, we mostly rely on the machine and natural language processing capabilities of AI, and energy efficient hardware and software devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and to sustain the depletion of natural resources. The core pillars of sustainability are Economic, Environmental, and Social, which are also informally referred to as 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core sustainability model in the enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand there is also a growing concern in many industries on how to reduce carbon emission and conserve natural resources while adopting sustainability in the corporate business models and policies. In our paper, we would like to discuss the driving forces such as climate changes, natural disasters, pandemic, disruptive technologies, corporate policies, scaled business models and emerging social media and AI platforms that influence the 3 main pillars of sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increase recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (shared IT services, cloud computing and application modernization) with the vision for a sustainable environment.
Keywords: AI, cloud computing, machine learning, social media platform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 180458 Thermographic Tests of Curved GFRP Structures with Delaminations: Numerical Modelling vs. Experimental Validation
Authors: P. D. Pastuszak
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The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.Keywords: Active thermography, finite element analysis, composite, curved structures, defects.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1698457 Complex-Valued Neural Network in Signal Processing: A Study on the Effectiveness of Complex Valued Generalized Mean Neuron Model
Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy
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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1720456 Partnering with Stakeholders to Secure Digitization of Water
Authors: Sindhu Govardhan, Kenneth G. Crowther
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Modernisation of the water sector is leading to increased connectivity and integration of emerging technologies with traditional ones, leading to new security risks. The convergence of Information Technology (IT) with Operation Technology (OT) results in solutions that are spread across larger geographic areas, increasingly consist of interconnected Industrial Internet of Things (IIOT) devices and software, rely on the integration of legacy with modern technologies, use of complex supply chain components leading to complex architectures and communication paths. The result is that multiple parties collectively own and operate these emergent technologies, threat actors find new paths to exploit, and traditional cybersecurity controls are inadequate. Our approach is to explicitly identify and draw data flows that cross trust boundaries between owners and operators of various aspects of these emerging and interconnected technologies. On these data flows, we layer potential attack vectors to create a frame of reference for evaluating possible risks against connected technologies. Finally, we identify where existing controls, mitigations, and other remediations exist across industry partners (e.g., suppliers, product vendors, integrators, water utilities, and regulators). From these, we are able to understand potential gaps in security, the roles in the supply chain that are most likely to effectively remediate those security gaps, and test cases to evaluate and strengthen security across these partners. This informs a “shared responsibility” solution that recognises that security is multi-layered and requires collaboration to be successful. This shared responsibility security framework improves visibility, understanding, and control across the entire supply chain, and particularly for those water utilities that are accountable for safe and continuous operations.
Keywords: Cyber security, shared responsibility, IIOT, threat modelling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 136455 Data-driven Multiscale Tsallis Complexity: Application to EEG Analysis
Authors: Young-Seok Choi
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This work proposes a data-driven multiscale based quantitative measures to reveal the underlying complexity of electroencephalogram (EEG), applying to a rodent model of hypoxic-ischemic brain injury and recovery. Motivated by that real EEG recording is nonlinear and non-stationary over different frequencies or scales, there is a need of more suitable approach over the conventional single scale based tools for analyzing the EEG data. Here, we present a new framework of complexity measures considering changing dynamics over multiple oscillatory scales. The proposed multiscale complexity is obtained by calculating entropies of the probability distributions of the intrinsic mode functions extracted by the empirical mode decomposition (EMD) of EEG. To quantify EEG recording of a rat model of hypoxic-ischemic brain injury following cardiac arrest, the multiscale version of Tsallis entropy is examined. To validate the proposed complexity measure, actual EEG recordings from rats (n=9) experiencing 7 min cardiac arrest followed by resuscitation were analyzed. Experimental results demonstrate that the use of the multiscale Tsallis entropy leads to better discrimination of the injury levels and improved correlations with the neurological deficit evaluation after 72 hours after cardiac arrest, thus suggesting an effective metric as a prognostic tool.
Keywords: Electroencephalogram (EEG), multiscale complexity, empirical mode decomposition, Tsallis entropy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2052454 Certain Data Dimension Reduction Techniques for application with ANN based MCS for Study of High Energy Shower
Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta
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Cosmic showers, from their places of origin in space, after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of EAS and similar High Energy Particle Showers involve a plethora of experimental setups with certain constraints for which soft-computational tools like Artificial Neural Network (ANN)s can be adopted. The optimality of ANN classifiers can be enhanced further by the use of Multiple Classifier System (MCS) and certain data - dimension reduction techniques. This work describes the performance of certain data dimension reduction techniques like Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Self Organizing Map (SOM) approximators for application with an MCS formed using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN). The data inputs are obtained from an array of detectors placed in a circular arrangement resembling a practical detector grid which have a higher dimension and greater correlation among themselves. The PCA, ICA and SOM blocks reduce the correlation and generate a form suitable for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.Keywords: EAS, Shower, Core, ANN, Location.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1595453 Asset Management for Educational Buildings in Egypt
Authors: M. Abdelhamid, I. Beshara, M. Ghoneim
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In Egypt, the concept of Asset Management (AM) is new; however, the need for applying it has become crucial because deteriorating or losing an asset is unaffordable in a developing country like Egypt. Therefore the current study focuses on educational buildings as one of the most important assets regarding planning, building, operating and maintenance expenditures. The main objective of this study is to develop a SAMF for educational buildings in Egypt. The General Authority for Educational Buildings (GAEB) was chosen as a case study of the current research as it represents the biggest governmental organization responsible for planning, operating and maintaining schools in Egypt. To achieve the research objective, structured interviews were conducted with senior managers of GAEB using a pre designed questionnaire to explore the current practice of AM. Gab analysis technique was applied against best practices compounded from a vast literature review to identify gaps between current practices and the desired one. The previous steps mainly revealed; limited knowledge about strategic asset management, no clear goals, no training, no real risk plan and lack of data, technical and financial resources. Based on the findings, a SAMF for GAEB was introduced and Framework implementation steps and assessment techniques were explained in detail.Keywords: Strategic Asset Management, Educational Building, Framework, Gab Analysis, Developing Country.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2324452 An Efficient Watermarking Method for MP3 Audio Files
Authors: Dimitrios Koukopoulos, Yiannis Stamatiou
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In this work, we present for the first time in our perception an efficient digital watermarking scheme for mpeg audio layer 3 files that operates directly in the compressed data domain, while manipulating the time and subband/channel domain. In addition, it does not need the original signal to detect the watermark. Our scheme was implemented taking special care for the efficient usage of the two limited resources of computer systems: time and space. It offers to the industrial user the capability of watermark embedding and detection in time immediately comparable to the real music time of the original audio file that depends on the mpeg compression, while the end user/audience does not face any artifacts or delays hearing the watermarked audio file. Furthermore, it overcomes the disadvantage of algorithms operating in the PCMData domain to be vulnerable to compression/recompression attacks, as it places the watermark in the scale factors domain and not in the digitized sound audio data. The strength of our scheme, that allows it to be used with success in both authentication and copyright protection, relies on the fact that it gives to the users the enhanced capability their ownership of the audio file not to be accomplished simply by detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark.
Keywords: Audio watermarking, mpeg audio layer 3, hard instance generation, NP-completeness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1824451 An Anisotropic Model of Damage and Unilateral Effect for Brittle Materials
Authors: José Julio de C. Pituba
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This work deals with the initial applications and formulation of an anisotropic plastic-damage constitutive model proposed for non-linear analysis of reinforced concrete structures submitted to a loading with change of the sign. The original constitutive model is based on the fundamental hypothesis of energy equivalence between real and continuous medium following the concepts of the Continuum Damage Mechanics. The concrete is assumed as an initial elastic isotropic medium presenting anisotropy, permanent strains and bimodularity (distinct elastic responses whether traction or compression stress states prevail) induced by damage evolution. In order to take into account the bimodularity, two damage tensors governing the rigidity in tension or compression regimes are introduced. Then, some conditions are introduced in the original version of the model in order to simulate the damage unilateral effect. The three-dimensional version of the proposed model is analyzed in order to validate its formulation when compared to micromechanical theory. The one-dimensional version of the model is applied in the analyses of a reinforced concrete beam submitted to a loading with change of the sign. Despite the parametric identification problems, the initial applications show the good performance of the model.
Keywords: Damage model, plastic strain, unilateral effect.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1819450 View-Point Insensitive Human Pose Recognition using Neural Network
Authors: Sanghyeok Oh, Yunli Lee, Kwangjin Hong, Kirak Kim, Keechul Jung
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This paper proposes view-point insensitive human pose recognition system using neural network. Recognition system consists of silhouette image capturing module, data driven database, and neural network. The advantages of our system are first, it is possible to capture multiple view-point silhouette images of 3D human model automatically. This automatic capture module is helpful to reduce time consuming task of database construction. Second, we develop huge feature database to offer view-point insensitivity at pose recognition. Third, we use neural network to recognize human pose from multiple-view because every pose from each model have similar feature patterns, even though each model has different appearance and view-point. To construct database, we need to create 3D human model using 3D manipulate tools. Contour shape is used to convert silhouette image to feature vector of 12 degree. This extraction task is processed semi-automatically, which benefits in that capturing images and converting to silhouette images from the real capturing environment is needless. We demonstrate the effectiveness of our approach with experiments on virtual environment.Keywords: Computer vision, neural network, pose recognition, view-point insensitive.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1318449 Development of a Support Tool for Cost and Schedule Integration Managment at Program Level
Authors: H. J. Yang, R. Z. Jin, I. J. Park, C. T. Hyun
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There has been gradual progress of late in construction projects, particularly in big-scale megaprojects. Due to the long-term construction period, however, with large-scale budget investment, lack of construction management technologies, and increase in the incomplete elements of project schedule management, a plan to conduct efficient operations and to ensure business safety is required. In particular, as the project management information system (PMIS) is meant for managing a single project centering on the construction phase, there is a limitation in the management of program-scale businesses like megaprojects. Thus, a program management information system (PgMIS) that includes program-level management technologies is needed to manage multiple projects. In this study, a support tool was developed for managing the cost and schedule information occurring in the construction phase, at the program level. In addition, a case study on the developed support tool was conducted to verify the usability of the system. With the use of the developed support tool program, construction managers can monitor the progress of the entire project and of the individual subprojects in real time.
Keywords: Cost∙Schedule integration management, Supporting Tool, UI, WBS, CBS, introduce PgMIS (Program Management Information System), PMIS (Project Management Information System)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1443448 Application of Generalized Stochastic Petri Nets(GSPN) in Modeling and Evaluating a Resource Sharing Flexible Manufacturing System
Authors: Aryanejad Mir Bahador Goli, Zahra Honarmand Shah Zileh
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In most study fields, a phenomenon may not be studied directly but it will be examined indirectly by phenomenon model. Making an accurate model of system, there is attained new information from modeled phenomenon without any charge, danger, etc... there have been developed more solutions for describing and analyzing the recent complicated systems but few of them have analyzed the performance in the range of system description. Petri nets are of limited solutions which may make such union. Petri nets are being applied in problems related to modeling and designing the systems. Theory of Petri nets allow a system to model mathematically by a Petri net and analyzing the Petri net can then determine main information of modeled system-s structure and dynamic. This information can be used for assessing the performance of systems and suggesting corrections in the system. In this paper, beside the introduction of Petri nets, a real case study will be studied in order to show the application of generalized stochastic Petri nets in modeling a resource sharing production system and evaluating the efficiency of its machines and robots. The modeling tool used here is SHARP software which calculates specific indicators helping to make decision.Keywords: Flexible manufacturing system, generalizedstochastic Petri nets, Markov chain, performance evaluation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1893447 Conceptualizing an Open Living Museum Beyond Musealization in the Context of a Historic City: Study of Bhaktapur World Heritage Site, Nepal
Authors: Shyam Sunder Kawan
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Museums are enclosed buildings encompassing and displaying creative artworks, artefacts and discoveries for people’s knowledge and observation. In the context of Nepal, museums and exhibition areas are either adaptive to small gallery spaces in residences or ‘neo-classical palatial complexes’ that evolved during the 19th century. This study accepts the sparse occurrence of a diverse range of artworks and expressions in the country's complex cultural manifestations within vivid ethnic groups. This study explores the immense potential of one such prevalence beyond the delimitation of physical boundaries. Taking Bhaktapur World Heritage Site as a case, the study perpetuates its investigation into real-time life activities that this city and its cultural landscapes ensemble. Seeking the ‘musealization’ as an urban process to induce museums into the city precinct, this study anticipates art-space into urban spaces to offer a limitless experience for this contemporary world. Unveiling art as an experiential component, this study aims in conceptualizing a living heritage as an infinite resource for museum interpretation beyond just educational institute purposes.
Keywords: Living museum, site museum, musealization, contemporary arts, cultural heritage, historic cities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 137446 Active Intra-ONU Scheduling with Cooperative Prediction Mechanism in EPONs
Authors: Chuan-Ching Sue, Shi-Zhou Chen, Ting-Yu Huang
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Dynamic bandwidth allocation in EPONs can be generally separated into inter-ONU scheduling and intra-ONU scheduling. In our previous work, the active intra-ONU scheduling (AS) utilizes multiple queue reports (QRs) in each report message to cooperate with the inter-ONU scheduling and makes the granted bandwidth fully utilized without leaving unused slot remainder (USR). This scheme successfully solves the USR problem originating from the inseparability of Ethernet frame. However, without proper setting of threshold value in AS, the number of QRs constrained by the IEEE 802.3ah standard is not enough, especially in the unbalanced traffic environment. This limitation may be solved by enlarging the threshold value. The large threshold implies the large gap between the adjacent QRs, thus resulting in the large difference between the best granted bandwidth and the real granted bandwidth. In this paper, we integrate AS with a cooperative prediction mechanism and distribute multiple QRs to reduce the penalty brought by the prediction error. Furthermore, to improve the QoS and save the usage of queue reports, the highest priority (EF) traffic which comes during the waiting time is granted automatically by OLT and is not considered in the requested bandwidth of ONU. The simulation results show that the proposed scheme has better performance metrics in terms of bandwidth utilization and average delay for different classes of packets.Keywords: EPON, Inter-ONU and Intra-ONU scheduling, Prediction, Unused slot remainder
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1585445 Optimizing of Fuzzy C-Means Clustering Algorithm Using GA
Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini
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Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3237444 Production and Market of Certified Organic Products in Thailand
Authors: Chaiwat Kongsom, Vitoon Panyakul
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The objective of this study was to assess the production and market of certified organic products in Thailand. A purposive sampling technique was used to identify a sample group of 154 organic entrepreneurs for the study. A survey and in-depth interview were employed for data collection. Also, secondary data from organic agriculture certification body and publications was collected. Then descriptive statistics and content analysis technique were used to describe about production and market of certified organic products in Thailand. Results showed that there were 9,218 farmers on 213,183.68 Rai (83,309.2 acre) of certified organic agriculture land (0.29% of national agriculture land). A total of 57.8% of certified organic agricultural lands were certified by the international certification body. Organic farmers produced around 71,847 tons/year and worth around THB 1,914 million (Euro 47.92 million). Excluding primary producers, 471 operators involved in the Thai organic supply chains, including processors, exporters, distributors, green shops, modern trade shops (supermarket shop), farmer’s markets and food establishments were included. Export market was the major market channel and most of organic products were exported to Europe and North America. The total Thai organic market in 2014 was estimated to be worth around THB 2,331.55 million (Euro 58.22 million), of which, 77.9% was for export and 22.06% was for the domestic market. The largest exports of certified organic products were processed foods (66.1% of total export value), followed by organic rice (30.4%). In the domestic market, modern trade was the largest sale channel, accounting for 59.48% of total domestic sales, followed by green shop (29.47%) and food establishment (5.85%). To become a center of organic farming and trading within ASEAN, the Thai organic sector needs to have more policy support in regard to agricultural chemicals, GMO, and community land title. In addition, appropriate strategies need to be developed.
Keywords: Certified organic products, production, market, Thailand.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2879443 Hand Gesture Recognition Based on Combined Features Extraction
Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Bernd Michaelis
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Hand gesture is an active area of research in the vision community, mainly for the purpose of sign language recognition and Human Computer Interaction. In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Our system is based on three main stages; automatic segmentation and preprocessing of the hand regions, feature extraction and classification. In automatic segmentation and preprocessing stage, color and 3D depth map are used to detect hands where the hand trajectory will take place in further step using Mean-shift algorithm and Kalman filter. In the feature extraction stage, 3D combined features of location, orientation and velocity with respected to Cartesian systems are used. And then, k-means clustering is employed for HMMs codeword. The final stage so-called classification, Baum- Welch algorithm is used to do a full train for HMMs parameters. The gesture of alphabets and numbers is recognized using Left-Right Banded model in conjunction with Viterbi algorithm. Experimental results demonstrate that, our system can successfully recognize hand gestures with 98.33% recognition rate.Keywords: Gesture Recognition, Computer Vision & Image Processing, Pattern Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4020442 Trade-off Between NOX, Soot and EGR Rates for an IDI Diesel Engine Fuelled with JB5
Authors: M. Gomaa, A. J. Alimin, K. A. Kamarudin
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Nowadays, the focus on renewable energy and alternative fuels has increased due to increasing oil prices, environment pollution, and also concern on preserving the nature. Biodiesel has been known as an attractive alternative fuel although biodiesel produced from edible oil is very expensive than conventional diesel. Therefore, the uses of biodiesel produced from non-edible oils are much better option. Currently Jatropha biodiesel (JBD) is receiving attention as an alternative fuel for diesel engine. Biodiesel is non-toxic, biodegradable, high lubricant ability, highly renewable, and its use therefore produces real reduction in petroleum consumption and carbon dioxide (CO2) emissions. Although biodiesel has many advantages, but it still has several properties need to improve, such as lower calorific value, lower effective engine power, higher emission of nitrogen oxides (NOX) and greater sensitivity to low temperature. Exhaust gas recirculation (EGR) is effective technique to reduce NOX emission from diesel engines because it enables lower flame temperature and oxygen concentration in the combustion chamber. Some studies succeeded to reduce the NOX emission from biodiesel by EGR but they observed increasing soot emission. The aim of this study was to investigate the engine performance and soot emission by using blended Jatropha biodiesel with different EGR rates. A CI engine that is water-cooled, turbocharged, using indirect injection system was used for the investigation. Soot emission, NOX, CO2, carbon monoxide (CO) were recorded and various engine performance parameters were also evaluated.
Keywords: EGR, Jatropha biodiesel, NOX, Soot emission.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3279441 Entropy Based Spatial Design: A Genetic Algorithm Approach (Case Study)
Authors: Abbas Siefi, Mohammad Javad Karimifar
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We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.
Keywords: Spatial design of experiments, maximum entropy sampling, computer experiments, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1644