Search results for: Mobile Ad Hoc Network
2591 Intelligent Earthquake Prediction System Based On Neural Network
Authors: Emad Amar, Tawfik Khattab, Fatma Zada
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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information about Earthquake Existed throughout history & the Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of the object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.
Keywords: BP neural network, Prediction, RBF neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32092590 Factors Influencing B2c eCommerce Diffusion
Authors: R. Mangiaracina, A. Perego, F. Campari
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Despite the fact that B2c eCommerce has become important in numerous economies, its adoption varies from country to country. This paper aims to identify the factors affecting (enabling or inhibiting) B2c eCommerce and to determine their quantitative impact on the diffusion of online sales across countries. A dynamic panel model analyzing the relationship between 13 factors (Macroeconomic, Demographic, Socio-Cultural, Infrastructural and Offer related) stemming from a complete literature analysis and the B2c eCommerce value in 45 countries over 9 years has been developed. Having a positive correlation coefficient, GDP, mobile penetration, Internet user penetration and credit card penetration resulted as enabling drivers of the B2c eCommerce value across countries, whereas, having a negative correlation coefficient,equal distribution of income and the development of traditional retailing network act as inhibiting factors.Keywords: B2c eCommerce diffusion, influencing factors, dynamic panel model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35482589 Applications of Artificial Neural Network to Building Statistical Models for Qualifying and Indexing Radiation Treatment Plans
Authors: Pei-Ju Chao, Tsair-Fwu Lee, Wei-Luen Huang, Long-Chang Chen, Te-Jen Su, Wen-Ping Chen
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The main goal in this paper is to quantify the quality of different techniques for radiation treatment plans, a back-propagation artificial neural network (ANN) combined with biomedicine theory was used to model thirteen dosimetric parameters and to calculate two dosimetric indices. The correlations between dosimetric indices and quality of life were extracted as the features and used in the ANN model to make decisions in the clinic. The simulation results show that a trained multilayer back-propagation neural network model can help a doctor accept or reject a plan efficiently. In addition, the models are flexible and whenever a new treatment technique enters the market, the feature variables simply need to be imported and the model re-trained for it to be ready for use.Keywords: neural network, dosimetric index, radiation treatment, tumor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16762588 High Gain Mobile Base Station Antenna Using Curved Woodpile EBG Technique
Authors: P. Kamphikul, P. Krachodnok, R. Wongsan
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This paper presents the gain improvement of a sector antenna for mobile phone base station by using the new technique to enhance its gain for microstrip antenna (MSA) array without construction enlargement. The curved woodpile Electromagnetic Band Gap (EBG) has been utilized to improve the gain instead. The advantages of this proposed antenna are reducing the length of MSAs array but providing the higher gain and easy fabrication and installation. Moreover, it provides a fan-shaped radiation pattern, wide in the horizontal direction and relatively narrow in the vertical direction, which appropriate for mobile phone base station. The paper also presents the design procedures of a 1x8 MSAs array associated with U-shaped reflector for decreasing their back and side lobes. The fabricated curved woodpile EBG exhibits bandgap characteristics at 2.1 GHz and is utilized for realizing a resonant cavity of MSAs array. This idea has been verified by both the Computer Simulation Technology (CST) software and experimental results. As the results, the fabricated proposed antenna achieves a high gain of 20.3 dB and the half-power beam widths in the E- and H-plane of 36.8 and 8.7 degrees, respectively. Good qualitative agreement between measured and simulated results of the proposed antenna was obtained.
Keywords: Gain Improvement, Microstrip Antenna Array, Electromagnetic Band Gap, Base Station.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29702587 A Novel Low-Profile Coupled-Fed Printed Twelve-Band Mobile Phone Antenna with Slotted Ground Plane for LTE/GSM/UMTS/WIMAX/WLAN Operations
Authors: Omar A. Saraereh, M. A. Smadi, A. K. S. Al-Bayati, Jasim A. Ghaeb, Qais H. Alsafasfeh
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A low profile planar antenna for twelve-band operation in the mobile phone is presented. The proposed antenna radiating elements occupy an area equals 17 × 50 mm2 are mounted on the compact no-ground portion of the system circuit board to achieve a simple low profile structure. In order to overcome the shortcoming of narrow bandwidth for conventional planar printed antenna, a novel bandwidth enhancement approach for multiband handset antennas is proposed here. The technique used in this study shows that by using a coupled-fed mechanism and a slotted ground structure, a multiband operation with wideband characteristic can be achieved. The influences of the modifications introduced into the ground plane improved significantly the bandwidths of the designed antenna. The slotted ground plane structure with the coupled-fed elements contributes their lowest, middle and higher-order resonant modes to form four operating modes. The generated modes are able to cover LTE 700/2300/2500, GSM 850/900/1800/1900, UMTS, WiMAX 3500, WLAN 2400/5200/5800 operations. Parametric studies via simulation are provided and discussed. Proposed antenna’s gain, efficiency and radiation pattern characteristics over the desired operating bands are obtained and discussed. The reasonable results observed can meet the requirements of practical mobile phones.
Keywords: Antenna, handset, LTE, Mobile, Multiband, Slotted ground, specific absorption rate (SAR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30372586 Concepts for Designing Low Power Wireless Sensor Network
Authors: Bahareh Gholamzadeh, Hooman Nabovati
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Wireless sensor networks have been used in wide areas of application and become an attractive area for researchers in recent years. Because of the limited energy storage capability of sensor nodes, Energy consumption is one of the most challenging aspects of these networks and different strategies and protocols deals with this area. This paper presents general methods for designing low power wireless sensor network. Different sources of energy consumptions in these networks are discussed here and techniques for alleviating the consumption of energy are presented.Keywords: Energy consumption, MAC protocol, Routing protocol, Sensor node, Topology control, Wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21412585 A Methodology for Definition of Road Networks in Rural Areas of Nepal
Authors: J. K. Shrestha, A. Benta, R. B. Lopes, N. Lopes
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This work provides a practical method for the development of rural road networks in rural areas of developing countries. The proposed methodology enables to determine obligatory points in the rural road network maximizing the number of settlements that have access to basic services within a given maximum distance. The proposed methodology is simple and practical, hence, highly applicable to real-world scenarios, as demonstrated in the definition of the road network for the rural areas of Nepal.Keywords: Minimum spanning tree, nodal points, rural road network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28672584 Hypergraph Models of Metabolism
Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova
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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterise a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.
Keywords: Complexity, hypergraphs, reciprocity, metabolism.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24372583 Performance Evaluation of Neural Network Prediction for Data Prefetching in Embedded Applications
Authors: Sofien Chtourou, Mohamed Chtourou, Omar Hammami
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Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.Keywords: Address, data set, memory, prediction, recurrentneural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16672582 A Video Watermarking Algorithm Based on Chaotic and Wavelet Neural Network
Authors: Jiadong Liang
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This paper presented a video watermarking algorithm based on wavelet chaotic neural network. First, to enhance binary image’s security, the algorithm encrypted it with double chaotic based on Arnold and Logistic map, Then, the host video was divided into some equal frames and distilled the key frame through chaotic sequence which generated by Logistic. Meanwhile, we distilled the low frequency coefficients of luminance component and self-adaptively embedded the processed image watermark into the low frequency coefficients of the wavelet transformed luminance component with the wavelet neural network. The experimental result suggested that the presented algorithm has better invisibility and robustness against noise, Gaussian filter, rotation, frame loss and other attacks.
Keywords: Video watermark, double chaotic encryption, wavelet neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10462581 Single-Camera EKF-vSLAM
Authors: ML. Benmessaoud, A. Lamrani, K. Nemra, AK. Souici
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This paper presents an Extended Kaman Filter implementation of a single-camera Visual Simultaneous Localization and Mapping algorithm, a novel algorithm for simultaneous localization and mapping problem widely studied in mobile robotics field. The algorithm is vision and odometry-based, The odometry data is incremental, and therefore it will accumulate error over time, since the robot may slip or may be lifted, consequently if the odometry is used alone we can not accurately estimate the robot position, in this paper we show that a combination of odometry and visual landmark via the extended Kalman filter can improve the robot position estimate. We use a Pioneer II robot and motorized pan tilt camera models to implement the algorithm.Keywords: Mobile Robot, Navigation, vSLAM, EKF, monocular.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16752580 Application of the Neural Network to the Synthesis of Vertical Dipole Antenna over Imperfect Ground
Authors: Kais Hafsaoui
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In this paper, we propose to study the synthesis of the vertical dipole antenna over imperfect ground. The synthesis implementation-s method for this type of antenna permits to approach the appropriated radiance-s diagram. The used approach is based on neural network. Our main contribution in this paper is the extension of a synthesis model of this vertical dipole antenna over imperfect ground.Keywords: Vertical dipole antenna, imperfect ground, neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11942579 Persian Printed Numeral Characters Recognition Using Geometrical Central Moments and Fuzzy Min-Max Neural Network
Authors: Hamid Reza Boveiri
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In this paper, a new proposed system for Persian printed numeral characters recognition with emphasis on representation and recognition stages is introduced. For the first time, in Persian optical character recognition, geometrical central moments as character image descriptor and fuzzy min-max neural network for Persian numeral character recognition has been used. Set of different experiments on binary images of regular, translated, rotated and scaled Persian numeral characters has been done and variety of results has been presented. The best result was 99.16% correct recognition demonstrating geometrical central moments and fuzzy min-max neural network are adequate for Persian printed numeral character recognition.Keywords: Fuzzy min-max neural network, geometrical centralmoments, optical character recognition, Persian digits recognition, Persian printed numeral characters recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17132578 Face Recognition using Radial Basis Function Network based on LDA
Authors: Byung-Joo Oh
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This paper describes a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers. The face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). LDA features of the face image are taken as the input of the Radial Basis Function Network (RBFN). The proposed approach has been tested on the ORL database. The experimental results show that the LDA+RBFN algorithm has achieved a recognition rate of 93.5%
Keywords: Face recognition, linear discriminant analysis, radial basis function network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21092577 Internet Bandwidth Network Quality Management: The Case Study of Telecom Organization of Thailand
Authors: Sriaroonnirun Sittha, Rotchanakitumnuai Siriluck
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This paper addresses a current problem that occurs among Thai internet service providers with regard to bandwidth network quality management. The IPSTAR department of Telecom Organization of Thailand public company (TOT); the largest internet service provider in Thailand, is the case study to analyze the problem that exists. The Internet bandwidth network quality management (iBWQM) framework is mainly applied to the problem that has been found. Bandwidth management policy (BMP) and quality of service (QoS) are two antecedents of iBWQM. This paper investigates internet user behavior, marketing demand and network operation views in order to determine bandwidth management policy (e.g. quota management, scheduling and malicious management). The congestion of bandwidth is also analyzed to enhance quality of service (QoS). Moreover, the iBWQM framework is able to improve the quality of service and increase bandwidth utilization, minimize complaint rate concerns to slow speed, and provide network planning guidelines through Thai Internet services providers.
Keywords: Internet bandwidth management, Internet serviceprovider, Internet usage behavior, Quality of Service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26372576 Real-Time Recognition of Dynamic Hand Postures on a Neuromorphic System
Authors: Qian Liu, Steve Furber
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To explore how the brain may recognise objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor (DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network (SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modelled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study’s largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognise the postures with an accuracy of around 86.4% - only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much improved cost to performance trade-off in its approach.
Keywords: Spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20422575 M-Learning Curriculum Design for Secondary School: A Needs Analysis
Authors: Muhammad Ridhuan Tony Lim Abdullah, Saedah Siraj
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The learning society has currently transformed from 'wired society' to become 'mobile society' which is facilitated by wireless network. To suit to this new paradigm, m-learning was given birth and rapidly building its prospect to be included in the future curriculum. Research and studies on m-learning spruced up in numerous aspects but there is still scarcity in studies on curriculum design of m-learning. This study is a part of an ongoing bigger study probing into the m-learning curriculum for secondary schools. The paper reports on the first phase of the study which aims to probe into the needs of curriculum design for m-learning at the secondary school level and the researcher adopted the needs analysis method. Data accrued from responses on survey questionnaires based on Lickert-point scale were analyzed statistically. The findings from this preliminary study serve as a basis for m-learning curriculum development for secondary schools.
Keywords: curriculum design, e-learning, future curriculum, m-learning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26332574 MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network
Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade
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The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22742573 A Taxonomy of Routing Protocols in Wireless Sensor Networks
Authors: A. Kardi, R. Zagrouba, M. Alqahtani
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The Internet of Everything (IoE) presents today a very attractive and motivating field of research. It is basically based on Wireless Sensor Networks (WSNs) in which the routing task is the major analysis topic. In fact, it directly affects the effectiveness and the lifetime of the network. This paper, developed from recent works and based on extensive researches, proposes a taxonomy of routing protocols in WSNs. Our main contribution is that we propose a classification model based on nine classes namely application type, delivery mode, initiator of communication, network architecture, path establishment (route discovery), network topology (structure), protocol operation, next hop selection and latency-awareness and energy-efficient routing protocols. In order to provide a total classification pattern to serve as reference for network designers, each class is subdivided into possible subclasses, presented, and discussed using different parameters such as purposes and characteristics.
Keywords: WSNs, sensor, routing protocols, survey.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10262572 Content-based Indoor/Outdoor Video Classification System for a Mobile Platform
Authors: Mitko Veta, Tomislav Kartalov, Zoran Ivanovski
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Organization of video databases is becoming difficult task as the amount of video content increases. Video classification based on the content of videos can significantly increase the speed of tasks such as browsing and searching for a particular video in a database. In this paper, a content-based videos classification system for the classes indoor and outdoor is presented. The system is intended to be used on a mobile platform with modest resources. The algorithm makes use of the temporal redundancy in videos, which allows using an uncomplicated classification model while still achieving reasonable accuracy. The training and evaluation was done on a video database of 443 videos downloaded from a video sharing service. A total accuracy of 87.36% was achieved.Keywords: Indoor/outdoor, video classification, imageclassification
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15112571 Evaluation of Classification Algorithms for Road Environment Detection
Authors: T. Anbu, K. Aravind Kumar
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The road environment information is needed accurately for applications such as road maintenance and virtual 3D city modeling. Mobile laser scanning (MLS) produces dense point clouds from huge areas efficiently from which the road and its environment can be modeled in detail. Objects such as buildings, cars and trees are an important part of road environments. Different methods have been developed for detection of above such objects, but still there is a lack of accuracy due to the problems of illumination, environmental changes, and multiple objects with same features. In this work the comparison between different classifiers such as Multiclass SVM, kNN and Multiclass LDA for the road environment detection is analyzed. Finally the classification accuracy for kNN with LBP feature improved the classification accuracy as 93.3% than the other classifiers.Keywords: Classifiers, feature extraction, mobile-based laser scanning, object location estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7672570 Artificial Neural Network Models of the Ruminal pH in Holstein Steers
Authors: Alireza Vakili, Mohsen Danesh Mesgaran, Majid Abdollazade
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In this study four Holstein steers with rumen fistula fed 7 kg of dry matter (DM) of diets differing in concentrate to alfalfa hay ratios as 60:40, 70:30, 80:20, and 90:10 in a 4 × 4 latin square design. The pH of the ruminal fluid was measured before the morning feeding (0.0 h) to 8 h post feeding. In this study, a two-layered feed-forward neural network trained by the Levenberg-Marquardt algorithm was used for modelling of ruminal pH. The input variables of the network were time, concentrate to alfalfa hay ratios (C/F), non fiber carbohydrate (NFC) and neutral detergent fiber (NDF). The output variable was the ruminal pH. The modeling results showed that there was excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 >0.96). Therefore, we suggest using these model-derived biological values to summarize continuously recorded pH data.Keywords: Ruminal pH, Artificial Neural Network (ANN), Non Fiber Carbohydrate, Neutral Detergent Fiber.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15162569 Pattern Classification of Back-Propagation Algorithm Using Exclusive Connecting Network
Authors: Insung Jung, Gi-Nam Wang
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The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern generation or training the network. However, this model is using exclusive connection in between hidden layer nodes and output nodes. The advantage of this model is less number of iteration and better performance compare with standard back-propagation model. We simulated some cases of classification data and different setting of network factors (e.g. hidden layer number and nodes, number of classification and iteration). During our simulation, we found that most of simulations cases were satisfied by BP based using exclusive connection network model compared to standard BP. We expect that this algorithm can be available to identification of user face, analysis of data, mapping data in between environment data and information.Keywords: Neural network, Back-propagation, classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16452568 On Simulation based WSN Multi-Parametric Performance Analysis
Authors: Ch. Antonopoulos, Th. Kapourniotis, V. Triantafillou
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Optimum communication and performance in Wireless Sensor Networks, constitute multi-facet challenges due to the specific networking characteristics as well as the scarce resource availability. Furthermore, it is becoming increasingly apparent that isolated layer based approaches often do not meet the demands posed by WSNs applications due to omission of critical inter-layer interactions and dependencies. As a counterpart, cross-layer is receiving high interest aiming to exploit these interactions and increase network performance. However, in order to clearly identify existing dependencies, comprehensive performance studies are required evaluating the effect of different critical network parameters on system level performance and behavior.This paper-s main objective is to address the need for multi-parametric performance evaluations considering critical network parameters using a well known network simulator, offering useful and practical conclusions and guidelines. The results reveal strong dependencies among considered parameters which can be utilized by and drive future research efforts, towards designing and implementing highly efficient protocols and architectures.Keywords: Wireless sensor network, Communication Systems, cross-layer architectures, simulation based performance evaluation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15162567 Control Chart Pattern Recognition Using Wavelet Based Neural Networks
Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim
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Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.
Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24662566 A Novel Approach to Allocate Channels Dynamically in Wireless Mesh Networks
Authors: Y. Harold Robinson, M. Rajaram
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Wireless mesh networking is rapidly gaining in popularity with a variety of users: from municipalities to enterprises, from telecom service providers to public safety and military organizations. This increasing popularity is based on two basic facts: ease of deployment and increase in network capacity expressed in bandwidth per footage; WMNs do not rely on any fixed infrastructure. Many efforts have been used to maximizing throughput of the network in a multi-channel multi-radio wireless mesh network. Current approaches are purely based on either static or dynamic channel allocation approaches. In this paper, we use a hybrid multichannel multi radio wireless mesh networking architecture, where static and dynamic interfaces are built in the nodes. Dynamic Adaptive Channel Allocation protocol (DACA), it considers optimization for both throughput and delay in the channel allocation. The assignment of the channel has been allocated to be codependent with the routing problem in the wireless mesh network and that should be based on passage flow on every link. Temporal and spatial relationship rises to re compute the channel assignment every time when the pattern changes in mesh network, channel assignment algorithms assign channels in network. In this paper a computing path which captures the available path bandwidth is the proposed information and the proficient routing protocol based on the new path which provides both static and dynamic links. The consistency property guarantees that each node makes an appropriate packet forwarding decision and balancing the control usage of the network, so that a data packet will traverse through the right path.
Keywords: Wireless mesh network, spatial time division multiple access, hybrid topology, timeslot allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18312565 The Optimal Placement of Capacitor in Order to Reduce Losses and the Profile of Distribution Network Voltage with GA, SA
Authors: Limouzade E., Joorabian M.
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Most of the losses in a power system relate to the distribution sector which always has been considered. From the important factors which contribute to increase losses in the distribution system is the existence of radioactive flows. The most common way to compensate the radioactive power in the system is the power to use parallel capacitors. In addition to reducing the losses, the advantages of capacitor placement are the reduction of the losses in the release peak of network capacity and improving the voltage profile. The point which should be considered in capacitor placement is the optimal placement and specification of the amount of the capacitor in order to maximize the advantages of capacitor placement. In this paper, a new technique has been offered for the placement and the specification of the amount of the constant capacitors in the radius distribution network on the basis of Genetic Algorithm (GA). The existing optimal methods for capacitor placement are mostly including those which reduce the losses and voltage profile simultaneously. But the retaliation cost and load changes have not been considered as influential UN the target function .In this article, a holistic approach has been considered for the optimal response to this problem which includes all the parameters in the distribution network: The price of the phase voltage and load changes. So, a vast inquiry is required for all the possible responses. So, in this article, we use Genetic Algorithm (GA) as the most powerful method for optimal inquiry.Keywords: Genetic Algorithm (GA), capacitor placement, voltage profile, network losses, Simulating Annealing (SA), distribution network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15232564 System for Monitoring Marine Turtles Using Unstructured Supplementary Service Data
Authors: Luís Pina
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The conservation of marine biodiversity keeps ecosystems in balance and ensures the sustainable use of resources. In this context, technological resources have been used for monitoring marine species to allow biologists to obtain data in real-time. There are different mobile applications developed for data collection for monitoring purposes, but these systems are designed to be utilized only on third-generation (3G) phones or smartphones with Internet access and in rural parts of the developing countries, Internet services and smartphones are scarce. Thus, the objective of this work is to develop a system to monitor marine turtles using Unstructured Supplementary Service Data (USSD), which users can access through basic mobile phones. The system aims to improve the data collection mechanism and enhance the effectiveness of current systems in monitoring sea turtles using any type of mobile device without Internet access. The system will be able to report information related to the biological activities of marine turtles. Also, it will be used as a platform to assist marine conservation entities to receive reports of illegal sales of sea turtles. The system can also be utilized as an educational tool for communities, providing knowledge and allowing the inclusion of communities in the process of monitoring marine turtles. Therefore, this work may contribute with information to decision-making and implementation of contingency plans for marine conservation programs.
Keywords: GSM, marine biology, marine turtles, USSD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9182563 Traffic Load based Performance Analysis of DSR and STAR Routing Protocol
Authors: Rani Astya, S.C. Sharma
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The wireless adhoc network is comprised of wireless node which can move freely and are connected among themselves without central infrastructure. Due to the limited transmission range of wireless interfaces, in most cases communication has to be relayed over intermediate nodes. Thus, in such multihop network each node (also called router) is independent, self-reliant and capable to route the messages over the dynamic network topology. Various protocols are reported in this field and it is very difficult to decide the best one. A key issue in deciding which type of routing protocol is best for adhoc networks is the communication overhead incurred by the protocol. In this paper STAR a table driven and DSR on demand protocols based on IEEE 802.11 are analyzed for their performance on different performance measuring metrics versus varying traffic CBR load using QualNet 5.0.2 network simulator.Keywords: Adhoc networks, wireless networks, CBR, routingprotocols, route discovery, simulation, performance evaluation, MAC, IEEE 802.11, STAR, DSR
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18782562 Split-Pipe Design of Water Distribution Network Using Simulated Annealing
Authors: J. Tospornsampan, I. Kita, M. Ishii, Y. Kitamura
Abstract:
In this paper a procedure for the split-pipe design of looped water distribution network based on the use of simulated annealing is proposed. Simulated annealing is a heuristic-based search algorithm, motivated by an analogy of physical annealing in solids. It is capable for solving the combinatorial optimization problem. In contrast to the split-pipe design that is derived from a continuous diameter design that has been implemented in conventional optimization techniques, the split-pipe design proposed in this paper is derived from a discrete diameter design where a set of pipe diameters is chosen directly from a specified set of commercial pipes. The optimality and feasibility of the solutions are found to be guaranteed by using the proposed method. The performance of the proposed procedure is demonstrated through solving the three well-known problems of water distribution network taken from the literature. Simulated annealing provides very promising solutions and the lowest-cost solutions are found for all of these test problems. The results obtained from these applications show that simulated annealing is able to handle a combinatorial optimization problem of the least cost design of water distribution network. The technique can be considered as an alternative tool for similar areas of research. Further applications and improvements of the technique are expected as well.Keywords: Combinatorial problem, Heuristics, Least-cost design, Looped network, Pipe network, Optimization
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