Search results for: ANP (analytic network process)
5847 An Energy-Efficient Distributed Unequal Clustering Protocol for Wireless Sensor Networks
Authors: Sungju Lee, Jangsoo Lee , Hongjoong Sin, Seunghwan Yoo, Sanghyuck Lee, Jaesik Lee, Yongjun Lee, Sungchun Kim
Abstract:
The wireless sensor networks have been extensively deployed and researched. One of the major issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to prolong the lifetime of a wireless sensor networks. In the paper, we compare several clustering protocols which significantly affect a balancing of energy consumption. And we propose an Energy-Efficient Distributed Unequal Clustering (EEDUC) algorithm which provides a new way of creating distributed clusters. In EEDUC, each sensor node sets the waiting time. This waiting time is considered as a function of residual energy, number of neighborhood nodes. EEDUC uses waiting time to distribute cluster heads. We also propose an unequal clustering mechanism to solve the hot-spot problem. Simulation results show that EEDUC distributes the cluster heads, balances the energy consumption well among the cluster heads and increases the network lifetime.Keywords: Wireless Sensor Network, Distributed UnequalClustering, Multi-hop, Lifetime.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24895846 Enhancement of Stereo Video Pairs Using SDNs To Aid In 3D Reconstruction
Authors: Lewis E. Hibell, Honghai Liu, David J. Brown
Abstract:
This paper presents the results of enhancing images from a left and right stereo pair in order to increase the resolution of a 3D representation of a scene generated from that same pair. A new neural network structure known as a Self Delaying Dynamic Network (SDN) has been used to perform the enhancement. The advantage of SDNs over existing techniques such as bicubic interpolation is their ability to cope with motion and noise effects. SDNs are used to generate two high resolution images, one based on frames taken from the left view of the subject, and one based on the frames from the right. This new high resolution stereo pair is then processed by a disparity map generator. The disparity map generated is compared to two other disparity maps generated from the same scene. The first is a map generated from an original high resolution stereo pair and the second is a map generated using a stereo pair which has been enhanced using bicubic interpolation. The maps generated using the SDN enhanced pairs match more closely the target maps. The addition of extra noise into the input images is less problematic for the SDN system which is still able to out perform bicubic interpolation.
Keywords: Genetic Evolution, Image Enhancement, Neuron Networks, Stereo Vision
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14255845 Anomaly Detection using Neuro Fuzzy system
Authors: Fatemeh Amiri, Caro Lucas, Nasser Yazdani
Abstract:
As the network based technologies become omnipresent, demands to secure networks/systems against threat increase. One of the effective ways to achieve higher security is through the use of intrusion detection systems (IDS), which are a software tool to detect anomalous in the computer or network. In this paper, an IDS has been developed using an improved machine learning based algorithm, Locally Linear Neuro Fuzzy Model (LLNF) for classification whereas this model is originally used for system identification. A key technical challenge in IDS and LLNF learning is the curse of high dimensionality. Therefore a feature selection phase is proposed which is applicable to any IDS. While investigating the use of three feature selection algorithms, in this model, it is shown that adding feature selection phase reduces computational complexity of our model. Feature selection algorithms require the use of a feature goodness measure. The use of both a linear and a non-linear measure - linear correlation coefficient and mutual information- is investigated respectivelyKeywords: anomaly Detection, feature selection, Locally Linear Neuro Fuzzy (LLNF), Mutual Information (MI), liner correlation coefficient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21845844 Morphing Human Faces: Automatic Control Points Selection and Color Transition
Authors: Stephen Karungaru, Minoru Fukumi, Norio Akamatsu
Abstract:
In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. This method is fully automatic in that it can morph two face images by automatically detecting all the control points necessary to perform the morph. A face detection neural network, edge detection and medium filters are employed to detect the face position and features. Five control points, for both the source and target images, are then extracted based on the facial features. Triangulation method is then used to match and warp the source image to the target image using the control points. Finally color interpolation is done using a color Gaussian model that calculates the color for each particular frame depending on the number of frames used. A real coded Genetic algorithm is used in both the image warping and color blending steps to assist in step size decisions and speed up the morphing. This method results in ''very smooth'' morphs and is fast to process.
Keywords: color transition, genetic algorithms morphing, warping
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28235843 Developments for ''Virtual'' Monitoring and Process Simulation of the Cryogenic Pilot Plant
Authors: Carmen Maria Moraru, Iuliana Stefan, Ovidiu Balteanu, Ciprian Bucur, Liviu Stefan, Anisia Bornea, Ioan Stefanescu
Abstract:
The implementation of the new software and hardware-s technologies for tritium processing nuclear plants, and especially those with an experimental character or of new technology developments shows a coefficient of complexity due to issues raised by the implementation of the performing instrumentation and equipment into a unitary monitoring system of the nuclear technological process of tritium removal. Keeping the system-s flexibility is a demand of the nuclear experimental plants for which the change of configuration, process and parameters is something usual. The big amount of data that needs to be processed stored and accessed for real time simulation and optimization demands the achievement of the virtual technologic platform where the data acquiring, control and analysis systems of the technological process can be integrated with a developed technological monitoring system. Thus, integrated computing and monitoring systems needed for the supervising of the technological process will be executed, to be continued with the execution of optimization system, by choosing new and performed methods corresponding to the technological processes within the tritium removal processing nuclear plants. The developing software applications is executed with the support of the program packages dedicated to industrial processes and they will include acquisition and monitoring sub-modules, named “virtually" as well as the storage sub-module of the process data later required for the software of optimization and simulation of the technological process for tritium removal. The system plays and important role in the environment protection and durable development through new technologies, that is – the reduction of and fight against industrial accidents in the case of tritium processing nuclear plants. Research for monitoring optimisation of nuclear processes is also a major driving force for economic and social development.
Keywords: Monitoring system, process simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19735842 Development of One-Axis Didactic Solar Tracker for Photovoltaic Panels
Authors: L. J. de Bessa Neto, M. R. B. Guerra Vale, F. K. O. M. Varella Guerra
Abstract:
In recent years, solar energy has established itself as one of the main sources of renewable energy, gaining a large space in electricity generation around the world. However, due to the low performance of photovoltaic panels, technologies need to be sought to maximize the production of electricity. In this regard, the present study aims to develop a prototype of solar tracker for didactics applications, controlled with the Arduino® platform, that enables the movement of photovoltaic plates in relation to the sun positions throughout the day through an electromechanical system, optimizing, thus, the efficiency of solar photovoltaic generation and improvements for the photovoltaic effect. The solar tracking technology developed in this work was presented of the shape oral and practical in two middle schools in the municipality of Mossoró/RN, being one of the public network and other of the private network, always keeping the average age of the students, in the case, around 16 years, contemplating an average of 60 students in each of the visits. Thus, it is concluded that the present study contributed substantially to the dissemination of knowledge concerning the photovoltaic solar generation, as well as the study of solar trackers, thus arousing the interest and curiosity of the students regarding the thematic approached.
Keywords: Alternative energy, solar tracker, energy efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9115841 On-line Handwritten Character Recognition: An Implementation of Counterpropagation Neural Net
Authors: Muhammad Faisal Zafar, Dzulkifli Mohamad, Razib M. Othman
Abstract:
On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. This work evaluates the use of the counter- propagation neural network (CPN) and presents feature extraction mechanism in full detail to work with on-line handwriting recognition. The obtained recognition rates were 60% to 94% using the CPN for different sets of character samples. This paper also describes a performance study in which a recognition mechanism with multiple thresholds is evaluated for counter-propagation architecture. The results indicate that the application of multiple thresholds has significant effect on recognition mechanism. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples.
Keywords: On-line character recognition, character digitization, counter-propagation neural networks, extreme coordinates.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24315840 Taking People, Process and Partnership on Board for Participatory Decision Making
Authors: B. Mikulskienė
Abstract:
Public administration institutions in cooperation with politicians are not the sole policy decision makers in full meaning any longer. Meanwhile, a special role, namely steering the decision making process, could be delegated to them. Despite the wide scientific discussion on different aspects what has direct impact on policy creation, there is a lack of holistic practical managerial advice, which could integrate infrastructure of policy decision making with intellectual capital and with interconnection of partnership. The proposed harmonized decision making model of process, people and partnership entitled by acronym HM-3P is analyzed as a framework for implementation of public administration steering role seeking the coherent social involvement in policy decision making.Keywords: participatory decision making, partnership, stakeholders.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14545839 Artificial Intelligence in Penetration Testing of a Connected and Autonomous Vehicle Network
Authors: Phillip Garrad, Saritha Unnikrishnan
Abstract:
The increase in connected and autonomous vehicles (CAV) creates more opportunities for cyber-attacks. Cyber-attacks can be performed with malicious intent or for research and testing purposes. As connected vehicles approach full autonomy, the possible impact of these cyber-attacks also grows. This review analyses the challenges faced in CAV cybersecurity testing. This includes access and cost of the representative test setup and lack of experts in the field A review of potential solutions to overcome these challenges is presented. Studies have demonstrated Artificial Intelligence (AI) as a promising technique to reduce runtime, enhance effectiveness and comprehensively cover all the standard test aspects in penetration testing in other industries. However, this review has identified a significant gap in the systematic implementation of AI for penetration testing in the CAV cybersecurity domain. The expectation from this review is to investigate potential AI algorithms, which can demonstrate similar improvements in runtime and efficiency for a CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.
Keywords: Cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4915838 Just-In-Time for Reducing Inventory Costs throughout a Supply Chain: A Case Study
Authors: Faraj Farhat El Dabee, Rajab Abdullah Hokoma
Abstract:
Supply Chain Management (SCM) is the integration between manufacturer, transporter and customer in order to form one seamless chain that allows smooth flow of raw materials, information and products throughout the entire network that help in minimizing all related efforts and costs. The main objective of this paper is to develop a model that can accept a specified number of spare-parts within the supply chain, simulating its inventory operations throughout all stages in order to minimize the inventory holding costs, base-stock, safety-stock, and to find the optimum quantity of inventory levels, thereby suggesting a way forward to adapt some factors of Just-In-Time to minimizing the inventory costs throughout the entire supply chain. The model has been developed using Micro- Soft Excel & Visual Basic in order to study inventory allocations in any network of the supply chain. The application and reproducibility of this model were tested by comparing the actual system that was implemented in the case study with the results of the developed model. The findings showed that the total inventory costs of the developed model are about 50% less than the actual costs of the inventory items within the case study.Keywords: Holding Costs, Inventory, JIT, Modeling, SCM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34795837 Efficiency of Membrane Distillation to Produce Fresh Water
Authors: Sabri Mrayed, David Maccioni, Greg Leslie
Abstract:
Seawater desalination has been accepted as one of the most effective solutions to the growing problem of a diminishing clean drinking water supply. Currently two desalination technologies dominate the market – the thermally driven multi-stage flash distillation (MSF) and the membrane based reverse osmosis (RO). However, in recent years membrane distillation (MD) has emerged as a potential alternative to the established means of desalination. This research project intended to determine the viability of MD as an alternative process to MSF and RO for seawater desalination. Specifically the project involves conducting thermodynamic analysis of the process based on the second law of thermodynamics to determine the efficiency of the MD. Data was obtained from experiments carried out on a laboratory rig. To determine exergy values required for the exergy analysis, two separate models were built in Engineering Equation Solver – the ’Minimum Separation Work Model’ and the ‘Stream Exergy Model’. The efficiency of MD process was found to be 17.3 % and the energy consumption was determined to be 4.5 kWh to produce one cubic meter of fresh water. The results indicate MD has potential as a technique for seawater desalination compared to RO and MSF. However it was shown that this was only the case if an alternate energy source such as green or waste energy was available to provide the thermal energy input to the process. If the process was required to power itself, it was shown to be highly inefficient and in no way thermodynamically viable as a commercial desalination process.
Keywords: Desalination, Exergy, Membrane distillation, Second law efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23305836 A Bi-Objective Stochastic Mathematical Model for Agricultural Supply Chain Network
Authors: Mohammad Mahdi Paydar, Armin Cheraghalipour, Mostafa Hajiaghaei-Keshteli
Abstract:
Nowadays, in advanced countries, agriculture as one of the most significant sectors of the economy, plays an important role in its political and economic independence. Due to farmers' lack of information about products' demand and lack of proper planning for harvest time, annually the considerable amount of products is corrupted. Besides, in this paper, we attempt to improve these unfavorable conditions via designing an effective supply chain network that tries to minimize total costs of agricultural products along with minimizing shortage in demand points. To validate the proposed model, a stochastic optimization approach by using a branch and bound solver of the LINGO software is utilized. Furthermore, to accumulate the data of parameters, a case study in Mazandaran province placed in the north of Iran has been applied. Finally, using ɛ-constraint approach, a Pareto front is obtained and one of its Pareto solutions as best solution is selected. Then, related results of this solution are explained. Finally, conclusions and suggestions for the future research are presented.Keywords: Perishable products, stochastic optimization, agricultural supply chain, ɛ-constraint.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10045835 Determination of the Economic Planning Depth for Assembly Process Planning
Authors: A. Kampker, P. Burggräf, Y. Bäumers
Abstract:
In order to be competitive, companies have to reduce their production costs while meeting increasing quality requirements. Therefore, companies try to plan their assembly processes as detailed as possible. However, increasing product individualization leading to a higher number of variants, smaller batch sizes and shorter product life cycles raise the question to what extent the effort of detailed planning is still justified. An important approach in this field of research is the concept of determining the economic planning depth for assembly process planning based on production specific influencing factors. In this paper first solution hypotheses as well as a first draft of the resulting method will be presented.Keywords: Assembly process planning, economic planning depth, planning benefit, planning effort.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21225834 Optimising Data Transmission in Heterogeneous Sensor Networks
Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read
Abstract:
The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.
Keywords: Wireless sensor networks, remote method invocation, transmission time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20385833 Mobile Multicast Support using Old Foreign Agent (MMOFA)
Authors: Hamed Rajabi, Naser Nematbakhsh, Naser Movahediniya
Abstract:
IP multicasting is a key technology for many existing and emerging applications on the Internet. Furthermore, with increasing popularity of wireless devices and mobile equipment, it is necessary to determine the best way to provide this service in a wireless environment. IETF Mobile IP, that provides mobility for hosts in IP networks, proposes two approaches for mobile multicasting, namely, remote subscription (MIP-RS) and bi-directional tunneling (MIP-BT). In MIP-RS, a mobile host re-subscribes to the multicast groups each time it moves to a new foreign network. MIP-RS suffers from serious packet losses while mobile host handoff occurs. In MIP-BT, mobile hosts send and receive multicast packets by way of their home agents (HAs), using Mobile IP tunnels. Therefore, it suffers from inefficient routing and wastage of system resources. In this paper, we propose a protocol called Mobile Multicast support using Old Foreign Agent (MMOFA) for Mobile Hosts. MMOFA is derived from MIP-RS and with the assistance of Mobile host's Old foreign agent, routes the missing datagrams due to handoff in adjacent network via tunneling. Also, we studied the performance of the proposed protocol by simulation under ns-2.27. The results demonstrate that MMOFA has optimal routing efficiency and low delivery cost, as compared to other approaches.Keywords: Mobile Multicast, Mobile IP, MMOFA, NS-2. 27.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14695832 A Subjectively Influenced Router for Vehicles in a Four-Junction Traffic System
Authors: Anilkumar Kothalil Gopalakrishnan
Abstract:
A subjectively influenced router for vehicles in a fourjunction traffic system is presented. The router is based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy routing procedure. The BPNN detects priorities of vehicles based on the subjective criteria. The subjective criteria and the routing procedure depend on the routing plan towards vehicles depending on the user. The routing procedure selects vehicles from their junctions based on their priorities and route them concurrently to the traffic system. That is, when the router is provided with a desired vehicles selection criteria and routing procedure, it routes vehicles with a reasonable junction clearing time. The cost evaluation of the router determines its efficiency. In the case of a routing conflict, the router will route the vehicles in a consecutive order and quarantine faulty vehicles. The simulations presented indicate that the presented approach is an effective strategy of structuring a subjective vehicle router.Keywords: Backpropagation Neural Network, Backpropagationalgorithm, Greedy routing procedure, Subjective criteria, Vehiclepriority, Cost evaluation, Route generation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13925831 Identifying and Adopting Latter Instruments Determining the Sustainable Company Competitiveness
Authors: Andrej Miklošík, Petra Horváthová, Štefan Žák
Abstract:
Nowadays companies in all sectors are looking for the sources of competitive advantages. Holistic marketing approach searches for their emergence based on the integration of all components and elements across the organization. Modern marketing sees the sources of competitive advantage in implementing the latest managerial practices, motivation, intelligent project management, knowledge management, collaborative marketing, CSR and, in the recent years, also in the business process optimization. With the use of modern tools including business process management and business process modelling the company can markedly increase its internal efficiency which can lead not only to lowering the costs but to creating the environment for optimal customer care, positive corporate culture and for origination of innovations as well. In the article the authors analyze the recent trend in this area and introduce suggestions to companies to identify and optimize the key processes that have a significant impact of the company´s competitiveness.Keywords: business process optimization, competitive advantage, corporate social responsibility, knowledge management
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17375830 Realization of Design Features for Linear Flow Splitting in NX 6
Authors: Anselm L. Schüle, Thomas Rollmann, Reiner Anderl
Abstract:
Within the collaborative research center 666 a new product development approach and the innovative manufacturing method of linear flow splitting are being developed. So far the design process is supported by 3D-CAD models utilizing User Defined Features in standard CAD-Systems. This paper now presents new functions for generating 3D-models of integral sheet metal products with bifurcations using Siemens PLM NX 6. The emphasis is placed on design and semi-automated insertion of User Defined Features. Therefore User Defined Features for both, linear flow splitting and its derivative linear bend splitting, were developed. In order to facilitate the modeling process, an application was developed that guides through the insertion process. Its usability and dialog layout adapt known standard features. The work presented here has significant implications on the quality, accurateness and efficiency of the product generation process of sheet metal products with higher order bifurcations.Keywords: Linear Flow Splitting, CRC 666, User Defined Features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24815829 WebAppShield: An Approach Exploiting Machine Learning to Detect SQLi Attacks in an Application Layer in Run-Time
Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl
Abstract:
In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.
Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4445828 A Study on the Impacts of Computer Aided Design on the Architectural Design Process
Authors: Halleh Nejadriahi, Kamyar Arab
Abstract:
Computer-aided design (CAD) tools have been extensively used by the architects for the several decades. It has evolved from being a simple drafting tool to being an intelligent architectural software and a powerful means of communication for architects. CAD plays an essential role in the profession of architecture and is a basic tool for any architectural firm. It is not possible for an architectural firm to compete without taking the advantage of computer software, due to the high demand and competition in the architectural industry. The aim of this study is to evaluate the impacts of CAD on the architectural design process from conceptual level to final product, particularly in architectural practice. It examines the range of benefits of integrating CAD into the industry and discusses the possible defects limiting the architects. Method of this study is qualitatively based on data collected from the professionals’ perspective. The identified benefits and limitations of CAD on the architectural design process will raise the awareness of professionals on the potentials of CAD and proper utilization of that in the industry, which would result in a higher productivity along with a better quality in the architectural offices.
Keywords: Architecture, architectural practice, computer aided design, CAD, design process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19195827 Optimizing Operation of Photovoltaic System Using Neural Network and Fuzzy Logic
Authors: N. Drir, L. Barazane, M. Loudini
Abstract:
It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.
Keywords: Maximum power point tracking, neural networks, photovoltaic, P&O.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19555826 Design Process of the Fixing Pipes in the Guide Pipe Anchor System for Cable-Stayed Bridges
Authors: Jinwoong Choi, Sun-Kyu Park, Sungnam Hong
Abstract:
For the efficient and safe use of the cable-stayed bridge, a design based on the detailed local analysis of the cable anchor system is required. Also, a theoretical design process for the anchor system should be prepared and reviewed. Generally, the size of the fixing pipe in the anchor system is decided according to the specifications prepared by cable-manufacturing companies, and accordingly, there is difficulty determining the initial inner diameters of the fixing pipes. As such, there is no choice but to use the products with the existing sizes. In this study, the existing design process of the fixing pipe, is a type of guide pipe anchor in the cable anchor system, is reviewed, a formula determining the thickness of the fixing pipe is proposed, and the convenience and validity of the suggested equation is compared with the results of the existing designs to verify its convenience and validity.Keywords: Cable-stayed bridge; Guide pipe anchor system; Fixing pipe; Theoretical design process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33115825 Human Action Recognition Using Variational Bayesian HMM with Dirichlet Process Mixture of Gaussian Wishart Emission Model
Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park
Abstract:
In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.
Keywords: Human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, Prior distribution and approximate posterior distribution, KTH dataset.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10065824 On the Development of a Homogenized Earthquake Catalogue for Northern Algeria
Authors: I. Grigoratos, R. Monteiro
Abstract:
Regions with a significant percentage of non-seismically designed buildings and reduced urban planning are particularly vulnerable to natural hazards. In this context, the project ‘Improved Tools for Disaster Risk Mitigation in Algeria’ (ITERATE) aims at seismic risk mitigation in Algeria. Past earthquakes in North Algeria caused extensive damages, e.g. the El Asnam 1980 moment magnitude (Mw) 7.1 and Boumerdes 2003 Mw 6.8 earthquakes. This paper will address a number of proposed developments and considerations made towards a further improvement of the component of seismic hazard. In specific, an updated earthquake catalog (until year 2018) is compiled, and new conversion equations to moment magnitude are introduced. Furthermore, a network-based method for the estimation of the spatial and temporal distribution of the minimum magnitude of completeness is applied. We found relatively large values for Mc, due to the sparse network, and a nonlinear trend between Mw and body wave (mb) or local magnitude (ML), which are the most common scales reported in the region. Lastly, the resulting b-value of the Gutenberg-Richter distribution is sensitive to the declustering method.
Keywords: Conversion equation, magnitude of completeness, seismic events, seismic hazard.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8165823 Design and Implementation of Secure Electronic Payment System (Client)
Authors: Pyae Pyae Hun
Abstract:
Secure electronic payment system is presented in this paper. This electronic payment system is to be secure for clients such as customers and shop owners. The security architecture of the system is designed by RC5 encryption / decryption algorithm. This eliminates the fraud that occurs today with stolen credit card numbers. The symmetric key cryptosystem RC5 can protect conventional transaction data such as account numbers, amount and other information. This process can be done electronically using RC5 encryption / decryption program written by Microsoft Visual Basic 6.0. There is no danger of any data sent within the system being intercepted, and replaced. The alternative is to use the existing network, and to encrypt all data transmissions. The system with encryption is acceptably secure, but that the level of encryption has to be stepped up, as computing power increases. Results In order to be secure the system the communication between modules is encrypted using symmetric key cryptosystem RC5. The system will use simple user name, password, user ID, user type and cipher authentication mechanism for identification, when the user first enters the system. It is the most common method of authentication in most computer system.Keywords: A 128-bit block cipher, Microsoft visual basic 6.0, RC5 encryption /decryption algorithm and TCP/IP protocol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23715822 A Novel Prostate Segmentation Algorithm in TRUS Images
Authors: Ali Rafiee, Ahad Salimi, Ali Reza Roosta
Abstract:
Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.
Keywords: Prostate segmentation, stick filter, neural network, active contour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19695821 Performances Comparison of Neural Architectures for On-Line Speed Estimation in Sensorless IM Drives
Authors: K.Sedhuraman, S.Himavathi, A.Muthuramalingam
Abstract:
The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.Keywords: Sensorless IM drives, rotor speed estimators, artificial neural network, feed- forward architecture, single neuron cascaded architecture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14585820 Innovation, e-Learning and Higher Education: An Example of a University- LMS Adoption Process
Authors: Ana Mafalda Gonçalves, Neuza Pedro
Abstract:
The evolution of ICT has changed all sections of society and these changes have been creating an irreversible impact on higher education institutions, which are expected to adopt innovative technologies in their teaching practices. As theorical framework this study select Rogers theory of innovation diffusion which is widely used to illustrate how technologies move from a localized invented to a widespread evolution on organizational practices. Based on descriptive statistical data collected in a European higher education institution three years longitudinal study was conducted for analyzing and discussion the different stages of a LMS adoption process. Results show that ICT integration in higher education is not progressively successful and a linear process and multiple aspects must be taken into account.
Keywords: e-learning, higher education, LMS, innovation, technologies
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24695819 MIMO-OFDM Channel Tracking Using a Dynamic ANN Topology
Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma
Abstract:
All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Keywords: MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23725818 A Web-Based Self-Learning Grammar for Spoken Language Understanding
Authors: S. M. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno
Abstract:
One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.
Keywords: Spoken Dialog System, Spoken Language Understanding, Web Semantic, Name Entity Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1776