Search results for: Series/Parallel network

Authors: P. O. Umenne, Odhiambo Marcel O.

Abstract:

A simple network model is developed in OPNET to study the performance of the Wi-Fi protocol. The model is simulated in OPNET and performance factors such as load, throughput and delay are analysed from the model. Four applications such as oracle, http, ftp and voice are applied over the Wireless LAN network to determine the throughput. The voice application utilises a considerable amount of bandwidth of up to 5Mbps, as a result the 802.11g standard of the Wi-Fi protocol was chosen which can support a data rate of up to 54Mbps. Results indicate that when the load in the Wi-Fi network is increased the queuing delay on the point-to-point links in the Wi-Fi network significantly reduces until it is comparable to that of WiMAX. In conclusion, the queuing delay of the Wi-Fi protocol for the network model simulated was about 0.00001secs comparable to WiMAX network values.

Keywords: WLAN-Wireless Local Area Network, MIMO-Multiple Input Multiple Output, Queuing delay, Throughput, AP-Access Point, IP-Internet protocol, TOS-Type of Service.

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Authors: Yi-Pin Hsu, Shin-Yu Lin

Abstract:

An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.

Keywords: Parallel-computing, FFT, low-memory reference, TIDSP.

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Authors: Ding Guo-hao, Li Hua, Wang Wen-long

Abstract:

A parallel computational fluid dynamics code has been developed for the study of aerodynamic heating problem in hypersonic flows. The code employs the 3D Navier-Stokes equations as the basic governing equations to simulate the laminar hypersonic flow. The cell centered finite volume method based on structured grid is applied for spatial discretization. The AUSMPW+ scheme is used for the inviscid fluxes, and the MUSCL approach is used for higher order spatial accuracy. The implicit LU-SGS scheme is applied for time integration to accelerate the convergence of computations in steady flows. A parallel programming method based on MPI is employed to shorten the computing time. The validity of the code is demonstrated by comparing the numerical calculation result with the experimental data of a hypersonic flow field around a blunt body.

Keywords: Aerodynamic Heating, AUSMPW+, MPI, ParallelComputation

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Authors: Cauvery N. K., K. V. Viswanatha

Abstract:

Mobile Ad hoc network consists of a set of mobile nodes. It is a dynamic network which does not have fixed topology. This network does not have any infrastructure or central administration, hence it is called infrastructure-less network. The change in topology makes the route from source to destination as dynamic fixed and changes with respect to time. The nature of network requires the algorithm to perform route discovery, maintain route and detect failure along the path between two nodes [1]. This paper presents the enhancements of ARA [2] to improve the performance of routing algorithm. ARA [2] finds route between nodes in mobile ad-hoc network. The algorithm is on-demand source initiated routing algorithm. This is based on the principles of swarm intelligence. The algorithm is adaptive, scalable and favors load balancing. The improvements suggested in this paper are handling of loss ants and resource reservation.

Keywords: Ad hoc networks, On-demand routing, Swarmintelligence.

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Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: Personal information, deep learning, auto fill, NLP, document analysis.

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Authors: Ying-Wen Bai, Ju-Maw Chen

Abstract:

To successfully provide a fast FIR filter with FTT algorithms, overlapped-save algorithms can be used to lower the computational complexity and achieve the desired real-time processing. As the length of the input block increases in order to improve the efficiency, a larger volume of zero padding will greatly increase the computation length of the FFT. In this paper, we use the overlapped block digital filtering to construct a parallel structure. As long as the down-sampling (or up-sampling) factor is an exact multiple lengths of the impulse response of a FIR filter, we can process the input block by using a parallel structure and thus achieve a low-complex fast FIR filter with overlapped-save algorithms. With a long filter length, the performance and the throughput of the digital filtering system will also be greatly enhanced.

Keywords: FIR Filter, Overlapped-save Algorithm, ParallelStructure

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Authors: S. Janpong, K-L. Areerak, K-N. Areerak

Abstract:

This paper aims to present the reviews of the application of neural network in shunt active power filter (SAPF). From the review, three out of four components of SAPF structure, which are harmonic detection component, compensating current control, and DC bus voltage control, have been adopted some of neural network architecture as part of its component or even substitution. The objectives of most papers in using neural network in SAPF are to increase the efficiency, stability, accuracy, robustness, tracking ability of the systems of each component. Moreover, minimizing unneeded signal due to the distortion is the ultimate goal in applying neural network to the SAPF. The most famous architecture of neural network in SAPF applications are ADALINE and Backpropagation (BP).

Keywords: Active power filter, neural network, harmonic distortion, harmonic detection and compensation, non-linear load.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

Abstract:

A synchronous network-on-chip using wormhole packet switching and supporting guaranteed-completion best-effort with low-priority (LP) and high-priority (HP) wormhole packet delivery service is presented in this paper. Both our proposed LP and HP message services deliver a good quality of service in term of lossless packet completion and in-order message data delivery. However, the LP message service does not guarantee minimal completion bound. The HP packets will absolutely use 100% bandwidth of their reserved links if the HP packets are injected from the source node with maximum injection. Hence, the service are suitable for small size messages (less than hundred bytes). Otherwise the other HP and LP messages, which require also the links, will experience relatively high latency depending on the size of the HP message. The LP packets are routed using a minimal adaptive routing, while the HP packets are routed using a non-minimal adaptive routing algorithm. Therefore, an additional 3-bit field, identifying the packet type, is introduced in their packet headers to classify and to determine the type of service committed to the packet. Our NoC prototypes have been also synthesized using a 180-nm CMOS standard-cell technology to evaluate the cost of implementing the combination of both services.

Keywords: Network-on-Chip, Parallel Pipeline Router Architecture, Wormhole Switching, Two-Level Priority Service.

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Authors: Amir Rashid, M. Saleem Khan, Freeha Zafar

Abstract:

This work presents a new approach of securing a wireless network. The configuration is focused on securing & Protecting wireless network traffic for a small network such as a home or dorm room. The security Mechanism provided both authentication, allowing only known authorized users access to the wireless network, and encryption, preventing anyone from reading the wireless traffic. The mentioned solution utilizes the open source free S/WAN software which implements the Internet Protocol Security –IPSEC. In addition to wireless components, wireless NIC in PC and wireless access point needs a machine running Linux to act as security gateway. While the current configuration assumes that the wireless PC clients are running Linux, Windows XP/VISTA/7 based machines equipped with VPN software which will allow to interface with this configuration.

Keywords: Wireless network security, security network, authentication, encryption and internet protocol security.

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Authors: Panagiotis H. Tsarouhas

Abstract:

the reliability analysis of the medical equipments can help to increase the availability and the efficiency of the systems. In this manuscript we present a simple method of decomposition that could be easily applied on the complex medical systems. Using this method we can easily calculate the effect of the subsystems or components on the reliability of the overall system. Furthermore, to investigate the effect of subsystems or components on system performance, we perform a numerical study varying every time the worst reliability of subsystem or component with another which has higher reliability. It can also be useful to engineers and designers of medical equipment, who wishes to optimize the complex systems.

Keywords: Reliability, Availability, Series-parallel System, medical equipment.

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Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

Abstract:

This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1^st January, 1997 to 28^th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: Detrended fluctuation analysis, generalized Hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis.

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Authors: H. Shayeghi, M. Mahdavi, A. Kazemi

Abstract:

Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, transmission expansion planning considering network adequacy restriction has not been investigated. Thus, in this paper, STNEP problem is being studied considering network adequacy restriction using discrete particle swarm optimization (DPSO) algorithm. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network and compared with the decimal codification genetic algorithm (DCGA). The results show that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is more than DCGA approach.

Keywords: DPSO algorithm, Adequacy restriction, STNEP.

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Authors: Christian H. Sanabria-Montaña, Rodrigo Huerta-Quintanilla

Abstract:

A lattice network is a special type of network in which all nodes have the same number of links, and its boundary conditions are periodic. The most basic lattice network is the ring, a one-dimensional network with periodic border conditions. In contrast, the Cartesian product of d rings forms a d-dimensional lattice network. An analytical expression currently exists for the clustering coefficient in this type of network, but the theoretical value is valid only up to certain connectivity value; in other words, the analytical expression is incomplete. Here we obtain analytically the clustering coefficient expression in d-dimensional lattice networks for any link density. Our analytical results show that the clustering coefficient for a lattice network with density of links that tend to 1, leads to the value of the clustering coefficient of a fully connected network. We developed a model on criminology in which the generalized clustering coefficient expression is applied. The model states that delinquents learn the know-how of crime business by sharing knowledge, directly or indirectly, with their friends of the gang. This generalization shed light on the network properties, which is important to develop new models in different fields where network structure plays an important role in the system dynamic, such as criminology, evolutionary game theory, econophysics, among others.

Keywords: Clustering coefficient, criminology, generalized, regular network d-dimensional.

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Authors: Rade M. Ciric, Nikola Lj.Rajakovic

Abstract:

Since the 80s huge efforts have been made to utilize renewable energy sources to generate electric power. This paper reports some aspects of integration of the distributed generators into the low voltage distribution networks. An assessment of impact of the distributed generators on the reliability indices of low voltage network is performed. Results obtained from case study using low voltage network, are presented and discussed.

Keywords: low voltage network, distributed generation, reliability indices

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Authors: F. A. Gdhaidh, K. Hussain, H. S. Qi

Abstract:

A numerical study of natural convection heat transfer in water filled cavity has been examined in 3-Dfor single phase liquid cooling system by using an array of parallel plate fins mounted to one wall of a cavity. The heat generated by a heat source represents a computer CPU with dimensions of 37.5∗37.5mm mounted on substrate. A cold plate is used as a heat sink installed on the opposite vertical end of the enclosure. The air flow inside the computer case is created by an exhaust fan. A turbulent air flow is assumed and k-ε model is applied. The fins are installed on the substrate to enhance the heat transfer. The applied power energy range used is between 15 - 40W. In order to determine the thermal behaviour of the cooling system, the effect of the heat input and the number of the parallel plate fins are investigated. The results illustrate that as the fin number increases the maximum heat source temperature decreases. However, when the fin number increases to critical value the temperature start to increase due to the fins are too closely spaced and that cause the obstruction of water flow. The introduction of parallel plate fins reduces the maximum heat source temperature by 10% compared to the case without fins. The cooling system maintains the maximum chip temperature at 64.68°C when the heat input was at 40W that is much lower than the recommended computer chips limit temperature of no more than 85°C and hence the performance of the CPU is enhanced.

Keywords: Chips limit temperature, closed enclosure, natural convection, parallel plate, single phase liquid.

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Authors: M. Kollar, A. Zieba

Abstract:

In this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The two eNBs are cooperating in so-called inter eNB CA (Carrier Aggregation) case and connected via asymmetrical IP network. We solve the problem by using broadcasting signals generated in E-UTRAN as synchronization signals. The results show that the time synchronization with the proposed method is possible with the error significantly less than 1 ms which is sufficient considering the time transmission interval is 1 ms in E-UTRAN. This makes this method (with low complexity) more suitable than Network Time Protocol (NTP) in the mobile applications with generated broadcasting signals where time synchronization in asymmetrical network is required.

Keywords: E-UTRAN, IP scheduled throughput, initial burst delay, synchronization, NTP, delay, asymmetric network.

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Authors: Rampal Singh, S. Balasundaram

Abstract:

In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction.

Keywords: Chaotic time series, Extreme learning machine, Generalization performance.

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Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat

Abstract:

The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge- Kutta solution using 38 time steps.

Keywords: Impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision.

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Authors: Y. Shpungin

Abstract:

Estimating the reliability of a computer network has been a subject of great interest. It is a well known fact that this problem is NP-hard. In this paper we present a very efficient combinatorial approach for Monte Carlo reliability estimation of a network with unreliable nodes and unreliable edges. Its core is the computation of some network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of network reliability. As a specific case of this approach we obtain tight lower and upper bounds for distributed network reliability (the so called residual connectedness reliability). We also present some simulation results.

Keywords: Combinatorial invariants, Monte Carlo simulation, reliability, unreliable nodes and unreliable edges.

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Authors: S. Chebbi, A. Meddeb

Abstract:

The distribution networks are often exposed to harmful incidents which can halt the electricity supply of the customer. In this context, we studied a real case of a critical zone of the Tunisian network which is currently characterized by the dysfunction of its plan of protection. In this paper, we were interested in the harmonization of the protection plan settings in order to ensure a perfect selectivity and a better continuity of service on the whole of the network.

Keywords: Distribution network Gabes-Tunisia, NEPLAN©DACH, protection plan settings, selectivity.

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Authors: Nicolò Vaiana, Giorgio Serino

Abstract:

In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: Base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops.

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Authors: Jiun-Wei Chen, Chih-Yang Wu, Ming-Feng Hou

Abstract:

A numerical study on the heat transfer in the thermal barrier coatings and the substrates of a parallel-plate enclosure is carried out. Some of the thermal barrier coatings, such as ceramics, are semitransparent and are of interest for high-temperature applications where radiation effects are significant. The radiative transfer equations and the energy equations are solved by using the discrete ordinates method and the finite difference method. Illustrative results are presented for temperature distributions in the coatings and the opaque walls under various heating conditions. The results show that the temperature distribution is more uniform in the interior portion of each coating away from its boundary for the case with a larger average of varying refractive index and a positive gradient of refractive index enhances radiative transfer to the substrates.

Keywords: Radiative transfer, parallel-plate enclosure, coatings, varying refractive index

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Authors: Sello Mokwena, Monyepao Thabang

Abstract:

In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis of benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: Camera network, convolutional neural network topology, person tracking, person re-identification, Siamese.

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Authors: M. A. Elghorab, A. Abou El-Azm Aly, A. S. Elwetedy, M. A. Kotb

Abstract:

Later marine propeller is the main component of ship propulsion system. For a non-series propeller, it is difficult to indicate the open water marine propeller performance without an experimental study to measure the marine propeller parameters. In the present study, the open water performance of a non-series marine propeller has been carried out experimentally. The geometrical aspects of a commercial non-series marine propeller have been measured for a propeller blade area ratio of 0.3985. The measured propeller performance parameters were the thrust and torque coefficients for different propeller rotational speed and different water channel flow velocity, then the open water performance for the propeller has been plotted. In addition, a direct comparison between the obtained experimental results and a theoretical study of a B-series marine propeller of the same blade area ratio has been carried out. A correction factor has been introduced to apply the operating conditions of the experimental results to that of the theoretical study for the studied marine propeller.

Keywords: Advance speed, marine propeller, open water performance, thrust coefficient, torque coefficient.

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Authors: S. Farzi

Abstract:

Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, we introduce GPNN (genetic polynomial neural network) to improve the performance of PNN. GPNN determines the number of input variables and the order of all neurons with GA (genetic algorithm). We use GA to search between all possible values for the number of input variables and the order of polynomial. GPNN performance is obtained by two nonlinear systems. the quadratic equation and the time series Dow Jones stock index are two case studies for obtaining the GPNN performance.

Keywords: GMDH, GPNN, GA, PNN.

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Authors: M. Mahdavi, M. Ismail, K. Jumari, Z. M. Hanapi

Abstract:

For the sensor network to operate successfully, the active nodes should maintain both sensing coverage and network connectivity. Furthermore, scheduling sleep intervals plays critical role for energy efficiency of wireless sensor networks. Traditional methods for sensor scheduling use either sensing coverage or network connectivity, but rarely both. In this paper, we use random scheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for network connectivity. Simulation results have demonstrated that the number of extra nodes that is on with upper bound of around 9%, is small compared to the total number of deployed sensor nodes. Thus energy consumption for switching on extra sensor node is small.

Keywords: Wireless sensor networks, energy efficient network, performance analysis, network coverage.

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Authors: Belassel Mohand-Tahar

Abstract:

This work is devoted to the calculation of the undulatory parameters and the study of the influence of te number parallel path of a winding on overvoltage compared to the frame and between turns (sections) in a multiturn random winding of an asynchronous motors supplied with PWM- converters.

Keywords: Asynchronous Motors, Parallel path, PWMconverters, Undulatory process, Undulatory parameters, Undulatory voltage

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Authors: Rahib Abiyev, Vasif H. Abiyev, C. Ardil

Abstract:

In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.

Keywords: Fuzzy logic, neural network, neuro-fuzzy system, neuro-fuzzy prediction.

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Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

Abstract:

In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN.

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Authors: Mohamed Othmani, Yassine Khlifi

Abstract:

This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3D object, optimization, parametrization, Polywog wavelets, reconstruction, wavelet networks.

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