New Publications are available for Combinatorial mathematics
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New Publications are available now online for this publication.
Please follow the links to view the publication.Simultaneus placement of conventional and renewable distributed generation using fuzzy multiobjective optimization
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0753
This paper proposes fuzzy multi objective optimization to determine the optimal size and location of conventional and renewable distributed generation in distribution network. In this paper the random generation of renewable DG is represented with a probabilistic-fuzzy approach. Operating constraints in DG placement are considered and the amount of ENS and current/voltage constraints evaluated using by fuzzy load flow. Objective function consists of ENS, economical advantage of DG's and also environmental benefits of renewable based DGs. (4 pages)Real time voltage control in distribution network considering renewable energy sources
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0793
Nowadays, fossil fuels reduction, environmental impacts, transmission line and substation construction costs, economic and technical efficiency, are leading to increase distributed generation such as renewable energy sources (RES). RES are connected to distribution networks (DN), so we don't need to transmission equipment. But the reverse power flow from RES causes to change operation method. As we know weather condition have influence on output power in RES. Conventional control methods are not useful for operation and bus voltage variation damage equipment of network and customer. So we see voltage control is important in DN with RES. So developing in communicating, smart sensors and distribution network automation is made possible for real time control. In this paper we propose a real time voltage and reactive power control in distribution network considering RES. Also fuzzy sets theory is combined with partial swarm optimization algorithm to solve the multiobjective voltage control problem. (4 pages)Transformer fault diagnosis based on IAFSA and rough set
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0664
With For a large number of incomplete fault data, the traditional artificial intelligence methods based cannot effectively and timely analysis or can not be accurately diagnosed or misdiagnosed because of the ill-conditioned problem caused by inefficient discretization approaches. A method based on rough set theory integrated with improved artificial fish-swarm algorithm (IAFSA) was presented in this paper for fault diagnosis of transformer. Firstly, the values of dissolved gas-in-oil analysis (DGA) were taken as conditional attributes and the type faults were taken as decision attributes. Various relations between fault and symptom were connected and decision table was established. the improved artificial fish-swarm algorithm is used to discrete continuous attribute; then, using the rough set theory to reduce the decision table. The simplified decision rules were got, which greatly simplifies the difficulty of diagnosis The experimental results indicate that the method has increased the diagnosis accuracy compared with traditional algorithm.Optimal operation of distribution network considering renewable energy sources by binary particle swarm optimization and fuzzy theory
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0787
Today, the development of telecommunications infrastructure has led to rapid exchange of data between the distribution network components and the control center. On the other hand, renewable energy sources (RES) are increasing due to deregulation and restructuring in power systems, global warming and reduction of fossil fuels .These sources are connected to the distribution network therefore behavior of these networks will change. One of the most important problems is the optimal operation of the distribution network including renewable energy sources. Optimal operation of distribution network is a mixed integer, nonlinear and multi-objective problem. Therefore in this paper, binary particle swarm optimization and fuzzy set theory are used for solved the problem. Finally, a practical distribution test system is used to investigate the feasibility and effectiveness of the proposed method. (4 pages)Investment optimization in distribution network based on fuzzy outage parameters
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0848
This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer nonlinear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network. (4 pages)Illumination robust face representation based on intrinsic geometrical information
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0437
The ability to recognize people is a key element for improving naturalistic human-robot and human-computer interaction systems. In this paper, we propose a binary non-subsampled contourlet transform (B-NSCT) based illumination robust face representation. Faces are transformed into multi-scale and multi-directional contour information where the intrinsic geometrical structures are used for characterising facial texture. Experiments on the Yale B and CMU PIE databases illustrate that B-NSCT is highly insensitive to illumination variation. (6 pages)Multi-frame super resolution using edge directed interpolation and complex wavelet transform
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0447
In this paper, a multi frame super resolution technique is proposed which uses edge directional interpolation (EDI) and dual-tree complex wavelet transform (DT-CWT). In the proposed technique a super resolution process is applied for each frame to generate the low frequency component. On the other hand, high frequency components are generated by DTCWT decomposition followed by EDI. Finally, the composition of the generated subbands using inverse DTCWT (IDT-CWT) reconstructs the super resolved output frame. Experimental results on a number of benchmark video sequences with respect to their PSNR measures confirm the superiority of the suggested method over the state of the art video resolution enhancement methods. (5 pages)Box-particle intensity filter
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0405
This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Further more, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables this approach to be used for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes the methods from the field of interval analysis. Our studies suggest that the box-iFilter reaches an accuracy similar to a sequential Monte Carlo (SMC) iFilter but with much less computational costs. (6 pages)Lifetime enhancement in wireless sensor networks using fuzzy approach and A-star algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0611
Wireless Sensor Networks (WSNs) are used in many applications to gather sensitive information which is then forwarded to an analysis centre. Resource limitations have to be taken into account when designing a WSN infrastructure. Unbalanced energy consumption is an inherent problem in WSNs characterized by multi-hop routing and many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. This paper proposes a new routing method for WSNs to extend the network lifetime using a combination of Fuzzy approach and A-star algorithm. The proposal is to determine the optimal routing path from the source to the destination by favouring the highest remaining battery power, minimum number of hops, as well as minimum traffic loads. To demonstrate the effectiveness of the proposed method in terms of balancing energy consumption and maximization of network lifetime, we compare our approach with A-star search algorithm and Fuzzy approach using the same routing criteria. Simulation results demonstrate that the network lifetime is significantly increased by employing the proposed routing method. (6 pages)Normalized cuts and watersheds for image segmentation
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0440
In this paper problem of image segmentation is considered. Specifically, normalized graph cut algorithm is regarded. In its source version the Ncut approach is computationally complex and time consuming, what decreases possibilities of its application in practical applications of machine vision. The segmentation approach proposed in this paper overcomes these limitations by incorporating watershed transform and normalized cuts. Results of the proposed method are presented, compared with results of the original normalized cut method and discussed. (6 pages)MRI mammogram image classification using ID3 algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0464
Breast cancer is one of the most common forms of cancer in women. In order to reduce the death rate , early detection of cancerous regions in mammogram images is needed. The existing system is not so accurate and it is time consuming. The Proposed system is mainly used for automatic segmentation of the mammogram images and classify them as benign,malignant or normal based on the decision tree ID3 algorithm. A hybrid method of data mining technique is used to predict the texture features which play a vital role in classification. The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm accounts to 93.45% , 99.95%,94% and 98.5% which rates very high when compared to the existing algorithms. The size and the stages of the tumor is detected using the ellipsoid volume formula which is calculated over the segmented region. (5 pages)Learning based objective evaluation of image segmentation algorithms
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0444
Image segmentation plays an important role in a broad range of applications and many image segmentation methods have been proposed, therefore it is necessary to be able to evaluate the performance of image segmentation algorithms objectively. In this paper we present a new fuzzy metric to evaluate the accuracy of image segmentation algorithms, based on the features of each segments using neural networks. The neural network after training can distinguish the similarity or dissimilarity of each pairs of segments and finally the segmentation algorithms accuracy have been computed by novel presented metric quantitatively. Our proposed method does not require a manually-segmented reference image for comparison therefore can be used for real-time evaluation and is sensitive to both oversegmentation and under-segmentation. Experimental results were obtained for a selection of images from Berkeley segmentation data set and demonstrated that it's a proper measure for comparing image segmentation algorithms. (6 pages)Retinal vessel segmentation using ensemble classifier of bagged decision trees
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0458
This paper presents a new supervised method for segmentation of blood vessels in retinal images. This method uses an ensemble system of boot strapped decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological linear transformation, line strength measures and Gabor filter responses. The feature vector encodes information to handle the healthy as well as the pathological retinal image. The method is evaluated on the publicly available DRIVE and STARE databases. Method performance on both sets of test images is better than the 2<sup xmlns="http://pub2web.metastore.ingenta.com/ns/">nd</sup> human observer and other existing methodologies available in the literature. The incurred accuracy, speed, robustness and simplicity make the algorithm a suitable tool for automated retinal image analysis. (6 pages)Robust watermarking for scalable image coding-based content adaptation
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0436
In scalable image coding-based content adaptation, such as, JPEG 2000, the quality scaling is performed by a quantization process that follows a bit plane discarding model. In this paper we propose a robust blind image watermarking algorithm by incorporating the bit plane discarding model. The new wavelet based binary tree guided rules-based watermarking algorithm is capable to retain the watermarking information for a given number of bit plane being discarded. The experimental simulations confirm the scheme's robustness against JPEG 2000 quality scalability. (6 pages)Improved maximum power extraction strategy for PMSG based wind energy conversion system
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0325
Even though hill climbing search (HCS) control is the simplest MPPT algorithm that does not require any prior knowledge of the system, it has the disadvantage of being slow in its response. This slowness in the response is due to the number of perturbations involved in climbing the hill and the settling time of the each perturbation. This paper proposes an improved HCS control, in which the nature of the input perturbation is changed, so as to improve the control algorithm's response speed in tracking the maximum power point of a wind turbine. (6 pages)A six-phase multilevel space vector PWM algorithm for a dual-inverter supplied drive
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0245
Multilevel drive supply can be realised in two different ways, by using either a conventional multilevel single-sided supply configuration or with a dual-inverter supply topology. The second structure is simpler for practical realisation, since the problem of capacitor voltage balancing does not arise. This paper develops a space vector PWM (SVPWM) algorithm for the dual-inverter six-phase supply, based on two two-level six-phase voltage source inverters (VSIs), feeding a symmetrical six-phase load. In the algorithm, each inverter is controlled using SVPWM technique that was previously developed for a single-sided supply configuration. A multilevel output voltage is produced for a certain range of modulation index. The performance of the algorithm is verified through simulations and experiments. (5 pages)Power system fault diagnosis based on power grid
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0140
This paper proposed a new power grid fault diagnosis model combining Petri nets and grid computing. It includes the power grid computing system's structure, software service and algorithm. The model can use the high performance computing method and distributed environment of grid computing. At the same time, Data grid system can offer table, efficient and unified information resources for the power grid fault diagnosis. When a fault happens, the component connecting topology trees were used for creating the Petri Nets model of possible fault components. Finally according Petri Nets model the true fault primary devices were identified, and the false tripping or operating information were picked out. This fault diagnosis model standardized the fault information and can share fault diagnosis results with other systems, realized real-time online fault diagnosis of power systems. (4 pages)Superiority of decision tree classifier on complicated cases for power system protection
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0054
Diagnosis of power system faults requires identification and classification of voltage disturbances in power systems and smart grids. The objective of this approach is to develop state of art signal classification algorithms for classifying different types of power quality disturbances (faults) based on latest improvements in signal processing and pattern recognition techniques. This paper proposes a new solution for power system monitoring against all possible power quality issues. S-transform is used for analyzing distorted power signal. As a classifier, decision tree algorithm is used and its performance is compared to other classifiers. The proposed hybrid power system monitoring system is able to detect common power system disturbances such as voltage sag/swell/, flicker, DC component, electro-magnetic interference, harmonics, transients and blackouts. (6 pages)Iterative QR decomposition-based detection algorithms with multiple feedback and dynamic tree search for LDPC-coded MIMO systems
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0170
In this paper, we present two innovative LDPC- coded QR decomposition-based soft-output detection techniques, both of which are able to achieve a near-ML performance with significant reduced complexity compare to other optimal detection solutions, such as MAP or list SD algorithms. The first detector (MF-QRD) employs a multi-feedback technique to select appropriate candidates when the symbols are unreliable. Another detection strategy called variable-M QRD (VM-QRD) detector is developed which dynamically adapts the number of detection candidates according to the channel variations in each detection layer. The irregular PEG LDPC code is employed as the outer channel code which provides efficient redundancy for mitigating remaining co-channel interference and additive noise. And simulation results show that the proposed algorithms have excellent performances. (5 pages)Real-time active visual tracking with level sets
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0122
This paper presents a new real-time active visual tracker which improves standard mean shift tracking by using level sets to extract contours from the target. We use colour and the disparity map computed from a stereo camera pair which prove to be powerful features for tracking in an indoor surveillance scenario. To combine the features in the level sets process, we enhance Chen's et al appearance model of [5] by using a probabilistic model determined via Expectation-Maximization (EM) clustering. The level set result is used as the weighting kernel which improves the accuracy of the similarity measurement in the mean shift method. Finally a Kalman filter deals with complete occlusions. (6 pages)Extended visual cryptography scheme with an artificial cocktail party effect
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0114
Visual cryptography schemes have been introduced in 1994 by Naor and Shamir [9]. These kind of schemes have been also well described by C. Blundo, A. De Santis and D.R. Stinson in [3]. In this case, a secret image I may be encoded into n shadow images called the shares, and to give exactly one such shadow image to each member of a group P of n persons. Certain qualified subsets of participants can visually recover I, but other, forbidden sets of participants have no information on I. A visual recovery for a set X consists of photocopying the shares given to the participants and then stacking them. Shortly afterwards the discovery of visual cryptography schemes Droste gave a generalization of such schemes, and Ateniese et al, formalized the idea of Naor and Shamir of an extension of the model which conceals the very existence of the secret image. Ateniese et al have called this formalization, Extended Visual Cryptography [5, 7,10]. In order to encode and hide a given set I<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">1</sub>, I<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sub>, . . . , I<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">k</sub> of gray-level images, in this paper, we propose an Extended Visual Cryptography Scheme for which the decoding process simulates a cocktail party effect. (10 pages)Object classification based on behaviour patterns
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0112
With the recent explosion of surveillance videos, media management has gained n increasing popularity. Addressing this challenge, in this paper, we propose a Surveillance Media Management framework for object detection and classification based on behaviour patterns. The objectives of the paper are: (i) demostrating the discriminative power of behaviour features for object recognition and classification, (ii) proposing a behavioural fuzzy classifier which progressively discriminate objects by including different degrees of uncertainty in the classification process and (iii) presenting a Surveillance Media Management system to extract semantic media information and provide unsupervised object classification from raw surveillance videos. The performance of the proposed system has been thoroughly evaluated on AVSS 2007 surveillance dataset and as the results indicate the proposed technique enhances object classification performance. (6 pages)Clustering performance analysis of FCM algorithm on iterative relaxed median filtered medical images
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0069
Noise removal is a major concern in image processing particularly in medical imaging. In this paper, a novel noise removal technique called Iterative relaxed median filter (IRMF) has been proposed and the effect of noise removal, by means of median filtering, on Fuzzy C-Means Clustering (FCM) has been analysed. Noise removal is carried out by various median filtering methods such as standard median filter (SMF), adaptive median filter (AMF), hybrid median filter (HMF) & relaxed median filter (RMF) and the performance of these methods is compared with the proposed method.A new technique to solve minimum spanning tree (MST) problem using modified shuffled frog-leaping algorithm (MSFLA) with GA cross-over
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0046
A minimum spanning tree (MST) of a connected, weighted (non-negative), undirected graph G = (V,E) is such that vertices of the graph G is connected by edges which have minimum weight and it forms a tree. Finding the MST from a graph is a NP-hard problem. In this paper a new technique is proposed to solve MST problem using Modified Shuffled Frog- Leaping Algorithm (MSFLA) with Genetic Algorithm (GA) cross-over. SFLA is a meta-heuristic search method inspired by natural memetics. It combines the benefits of both meme-based Memetic Algorithm (MA) and social behaviour based Particle Swarm Optimization (PSO). In this paper some modification of SFLA is done and applied it to MST problem. Extensive experimental results show that the algorithm performs very well compare to other algorithms and gives accurate results with minimum no of iterations.Research and realization on the ant colony optimization algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0894
This is where the abstract should be placed. It should consist of one paragraph and a concise summary of the material discussed in the article below. It is preferable not to use footnotes in the abstract or the title. The acknowledgement for funding organisations etc. is placed in a separate section at the end of the text. We wish you success with the preparation of your manuscript. The ant colony algorithm (ACA ) is a simulated evolutionary algorithm , which is inspired by real ants foraging in natural world. In this paper, it has effectively solved the problem of precocity and halting of the ant colony algorithm, taking use of the global and rapidity of the PSO. Meanwhile, it can also judge the standard of the route by use of the eliminating- cross. Through classic experiments about Traveling Salesman Problem, the optimization algorithm has the better astringency, robustness and efficiency.Finding a crack in a material and determining of depth
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0097
The purpose of this paper is to find geometry of a crack (length and depth) in a conductive plate, on the basis of non-destructive testing with eddy currents. The position of a crack can be determined by taking into consideration the change in the magnetic density between the measured points. The depth is determined with the use of FEM model. The calculated test case points to an accurate determination.Adaptive multiple level mobility anchor point selection scheme in HMIPv6
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0945
Hierarchical Mobile IPv6 (HMIPv6) introduces a mobility anchor point (MAP) that localizes the signaling traffic and hence reduces the handoff latency. In addition to processing binding update messages from mobile nodes (MNs) on behalf of MNs' home agents (HAs), the MAP performs data traffic tunneling destined to or originated from MNs, both of which will burden the MAP substantially as the network size grow s. To provide scalable and robust mobile Internet services to a large number of visiting MNs, multiple MAPs will be deployed. In such an environment, how to select an appropriate MAP has a vital effect on the overall network performance. In this paper, we propose the adaptive multiple level MAP selection scheme in the form of binary tree structure. Then, we give the optimal threshold value calculation formula based on the total communication cost, which is used to select the MAP for MN. We compare its performance quantitatively in terms of signaling overhead. It can be shown that the adaptive multiple level MAP selection scheme is better than the furthest and the nearest MAP selection schemes in some area, since this scheme can be used to select the serving MAP depending on the MN's mobility and session activity. In addition, this MAP selection scheme is insensitive to the lower threshold value offseting.Analysis of time invariant state equation using blend function
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0447
"The Blend Function" is a combination of Sample-and-Hold (SHF) function set and Right Hand Side Triangular Function (RHTF) set. It is a new set of Piece-wise Constant Basis Function (PCBF). Any square integrable function can be approximated in this domain. Here, the blend function set is used to find response of a linear time invariant system described by a linear state equation and the result is compared with block pulse function domain analysis (the most fundamental component of PCBF family).The fine structures of three idempotent Latin squares with small orders
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1024
Latin squares have wide application in communication and cipher. Denote by IdFin(v) the set of all integer pairs (t, s) for which there exist three idempotent Latin squares of order r on the same set having fine structure (t, s). We obtain that (6, 17), (4, 18)∈IdFin(7), which gives some new examples (6, 17), (4, 18)∈Fin(7). We prove that (t, 16)∉IdFin(v) with 0t3 for order v with 8 v 11, and determine the set IdFin(11).A graph approach for coordinated channel allocation in downlink multi-cell OFDMA networks
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0666
Radio resource allocation in multi-cell OFDMA (orthogonal frequency-division multiple access) networks is a challenging and practically important problem. In this work we propose a new graph-based sub-channel assignment scheme for downlink multi-cell OFDMA networks. Our scheme consists of two phases, both of which are formulated as graph problems. The first phase is location-aware interference management, including inter-cell interference coordination (IOC) as well as intra-cell interference avoidance. The second phase is channel-aware sub-channel assignment. Simulation results demonstrate that the proposed scheme significantly enhances the system throughput while maintaining user-Quality of Service (QoS) compared with existing sub-channel assignment schemes.An advanced dynamic spectrum allocation algorithm in cognitive radio based on priority of nodes
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0879
The proposal of cognitive radio can fundamentally solve the problem of the insufficiency of spectrum. Among them, the dynamic spectrum allocation is the key to decide how to use the limited spectrum efficiently. However, the existing graph colouring algorithm does not consider the priority of user nodes, leading to the delay of spectrum allocation. In this article, an advanced dynamic spectrum allocation algorithm based on the priority of user nodes will be put forward. During the spectrum allocation, the priority of channel and the priority of user nodes will be considered, using the thoughts of best-available-multiple-allocate in order to meet the requirements of the users' bit error rate and the need of delay. The simulation analysis shows that the advanced algorithm based on the priority of nodes can not only satisfy the customers' needs, providing higher allocation efficiency, but also reflect the fairness of spectrum allocation better.A method to construct elements of IdFin(2v+1) by using elements in IdFin(v)
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1026
Latin squares have wide application in communication and cipher. Denote by IdFin(r) the set of all integer pairs (t, s) for which there exist three idempotent Latin squares of order v on the same set having fine structure (t, s). A method to construct elements of IdFin(2v+1) by using elements in IdFin(v) is presented.A graph-based dynamic coordinated clustering scheme for base station cooperation
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0659
In this paper, a graph-based dynamic coordinated clustering scheme is proposed for base station cooperation (BSC) wireless systems. An interference weighted graph is constructed to assist dynamic coordinated clustering for inter-cell interference mitigating and improving the cell-user performance. The assist graph is constructed with weighted interference value among users, considering the overhead exchange constraint, only 2 bits (1 bit for diversity set judgment, 1 bit for user status) signalling exchange between base stations are needed during the graph constructing. Based on the interference weighted graph, a modified Hungarian algorithm is used for the coordinated clustering. Simulation results show that the proposed scheme can improve the performance of cell-edge users.New coupling between PEEC method and an integro-differential approach for modeling solid conductors in the presence of magnetic-conductive thin plates
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0023
In order to introduce magnetic conductive thin plates in quasi-static PEEC method, a coupling with the integro differential method is proposed. This coupling enables to take the advantage of each method. The complex conductor geometry is achieved thanks to the PEEC method. The modeling of thin plates is taken into account thanks to an integro-differential one.Optimal switching operation using knowledge based colored petri net
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0480
In this paper, an attempt is made to find optimal switching operations for the service restoration and feeder load balancing of the distribution systems using Colored Petri Nets (CPN). When a power distribution system is operating under normal condition, the reconfiguration of feeders for load balancing among distribution feeders is obtained, which improve the operating performance of distribution system. Heuristic rules combined with the artificial intelligent Colored Petri net are applied to find the proper switching operation decision to solve the problem during a contingency. The Colored Petri Net approach performs very efficiently by its parallel like inference characteristics to determine the appropriate switching operations for solving the contingencies of distribution system. 33bus system is tested to demonstrate the effectiveness of this study. The results obtained are comparable to the results available in the literature.Audio classification based on fuzzy- rough nearest neighbour clustering
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0901
In the time of digital information, audio data has become an important part in many modern computer applications. Automatic classification based on audio content has been considered as an important way to cope with the problem of audio structuration. In this paper, we present an improved algorithm based on FRNNC (Fuzzy-rough nearest neighbour clustering), which derive from FRNN algorithm and have combined clustering algorithm. In our work, we extract audio features from the MDCT domain and form feature vectors by introduce the concept of feature granularity, and then apply the FRNNC algorithm in audio classification. The experimental results show that our classification method not only greatly reduces the processing time of classification, but also improves the classification accuracy.Intelligent tourist attractions recommendation system based on cases
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1490
This paper describes how to meet the tourists' demands by using web crawlers, perceptual hashing, decision tree modeling and other technologies in city tourist attractions recommendation. The system makes the intelligent suggestions by using web crawlers to capture weather conditions for the next few days, and builds a decision tree according to the data base of users' feedbacks. It analyses the result of the model and updates the algorithms. To solve the tourist picture reviews issue, we design and implement a hashing algorithm base on digital image sense technology and give out the test and analysis results.Database construction of urban land cover Information using RS and GIS
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0282
Remote sensing technology can obtain the urban land cover information quickly and accurately, and it has been widely used in the urban development. In view of the information extraction present in high resolution remote sensing image and database construction characteristics, in this paper, the Google Earth image is data source, an object-oriented method including image segmentation, feature space optimization and the fuzzy classification rules are proposed to extract the urban land-cover information. The precision of the extraction information is 94.17% and Kappa coefficient is 0.8302. The format of urban land-cover information was changed from raster to vector, then which was transferred to GIS software to construct the database. The results show that it has proved the feasibility and practicability to extract the urban land cover information from the high resolution remote sensing images and construct database in the GIS software. (7 pages)Power system restoration using reverse delete algorithm implemented in FPGA
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0392
A graph theory based algorithm called as reverse delete algorithm to find the optimal path of power flow for a given network is proposed in this paper. Whenever an outage occurs in the distribution network, the power has to be restored to the isolated area by altering the path of power flow, which is achieved by altering the switching positions of the network. The reverse delete algorithm helps in finding the path of least impedance called minimum spanning tree to supply the power to the isolated areas. Backward sweeper based load flow technique is applied to this resultant minimum spanning tree. Based on the results (voltage, current and power flow) obtained from the load flow solutions, other constraints of the restoration problem are applied. The results are tabulated for 33 bus single feeder distribution network and for 16 bus multi feeder distribution network. The hardware implementation of this algorithm is done using Verilog HDL.Numeric design engineering of a magneto-inductive foil sensor
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0078
In this paper the numeric design engineering of a magneto inductive foil sensor will be discussed. This sensor system is a position sensor which enables to measure distances with high resolution. First the approach of this project is explained and the objectives are presented. Then the build-up sequence and functional active principle of the sensor is described. Therefore appropriate models shall be used to reflect the physical effects of the device accordingly. After that we perform the numerical design engineering of the device using Finite Element Analysis (FEA). For this purpose the geometry and the complexity of the mesh will be presented. Due to the different geometric dimensions of the sensor element and the sender, represented as a permanent magnet, meshing of the whole system is very challenging. After that the comparison between simulation results and measurements are shown. We achieve quite good compliance, only about 3-5% of deviation. The conclusion and outlook, which reviews and discusses further steps, complete the paper.An orthogonal tensor rank one discriminative graph embedding method for facial expression recognition
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0998
In this paper a new tensor dimensionality reduction algorithm is proposed based on graph embedding and orthogonal tensor rank one decomposition. In the algorithm, both the intra- class local manifold structure and the inter-class margins are enhanced by projecting the original tensors onto a group of orthogonal rank-one tensors, and a novel and effective orthogonalization process is given. In the experiments the algorithm is used for the facial expression recognition and achieves accelerant results.Boundary recovery for conforming Delaunay triangulation of curved complexes
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0016
This paper presents a method to recover boundaries of Delaunay meshes conformed to curved geometries. The method uses a topological property to identify conforming simplices and to create Steiner points. A pruning algorithm is introduced to avoid unnecessary predicate tests. Its implementation is both effective and efficient.Fuzzy inference supported current differential protection for HV transmission lines
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.0278
In this paper enhanced differential current protection scheme dedicated for HV transmission lines is described. The adaptive fuzzy relay scheme is proposed that combines strengths of both current and phase comparison protection criteria. The relay stabilization characteristic is adapted online depending on the output of the fuzzy reasoning scheme supplied with information from the phase comparison unit. As a result improved performance of the scheme for cases of external faults with CT saturation is reached. The performance of presented fuzzy protection scheme has been tested with the signals generated with use of EMTP-ATP program and compared to the traditional solutions. (5 pages)Automatic optimization system for CD-phantom image quality
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.0558
This main proposed an appropriate automatic optimization system as a criterion of Contrast-detail phantom (CD-phantom) image quality. First, the test region is separated from the phantom image of Plexiglas tablet, and four corners region are located linearly. Then the geometry distorted bilinear equation model and the bilinear pixel interpolation are used to recover the image of rectangular test region. Therefore, this present method would locate the squares and cut out the holes region. Finally, the statistics of hole's Contrast, Signal to Noise Ratio (SNR) and probability density relationship (PDR) are calculated and gathered. The experimental results showed that the method can obtain accurate location and information of holes, and also provide a simple and fast way to achieve that.Service restoration in distribution systems using an evolutionary algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.0905
This study proposes an efficient and computationally feasible solution approach based on evolutionary algorithms, to the distribution system restoration problem. In recent years, the enlargement and development of electrical power systems have introduced various problems related to the continuity of load feeding. When a fault occurs in a distribution system, the faulted area should be isolated from the system and as much load as possible has to be restored to this area. This is done by transferring de-energized loads from out-of-service areas through the distribution system without violating or disturbing the existing operation constraints. The solution of this problem, which can be defined as obtaining an optimum system configuration providing minimization of deenergized areas on the system after a fault occurred, is known as service restoration in distribution networks. The main concern of this problem is to minimize the impact of the outage on the system. This is achieved by finding an optimal operation configuration via changing the status of sectionalizing switches, taking into account the objectives and the constraints of the system. This makes the distribution system restoration problem a complex combinatorial optimization problem with multiple constraints. Therefore, to solve this problem and obtain feasible solutions of good quality, with an acceptable amount of computational effort, an evolutionary algorithm approach is proposed. The proposed evolutionary algorithm is applied to a radially configured distribution system model and analysis results are presented.. (9 pages)Fuzzy generalized synchronization between non-smooth-air-gap and smooth-air-gap PMSM chaotic systems with channel delay
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.0785
The generalized synchronization problem between non-smooth-air-gap and smooth-air-gap PMSM chaotic systems is studied in this paper. In addition, the channel delay is considered in the realization of the chaotic synchronization. Firstly, the nonsmooth-air-gap PMSM chaotic system and the smooth-air-gap PMSM chaotic system are represented by the T-S fuzzy models without any modeling error. Then, a simple fuzzy state feedback controller is designed based on the parallel distributed compensation technique. By virtue of the definition of lag synchronization and fuzzy control idea, the asymptotical synchronization is realized by choosing appropriate controller gain matrices. Finally, an illustrative example is presented to demonstrate the effectiveness of the proposed fuzzy synchronization method.On the double-pancyclicity of augmented cubes
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.0576
A graph G is called pancyclic if it contains a cycle of length I for each integer I from 3 to |V(G)| inclusive, where |V(G)| denotes the cardinality of the vertex set of graph G. It has been shown by Ma et al. (2007) that the augmented cube, proposed by Choudum and Sunitha (2002), is pancyclic. In this paper, we propose a more refined property, namely double-pancyclicity. Let G be a pancyclic graph with N vertices, and (u<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">1</sub>, v<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">1</sub>), (u<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sub>, v<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sub>) be any two vertex-disjoint edges in G. Moreover, let l<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">1</sub> and l<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sub> be any two integers of {3, 4,. .., N - 3} such that l<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">1</sub> + l<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sub> N. Then G is said to be double-pancyclic if it has two vertex-disjoint cycles, C<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">1</sub> and C<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sub>, such that |V(C<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">i</sub>)| = l<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">i</sub> and (u<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">i</sub>, v<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">i</sub>) ∈ E(C<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">i</sub>) for i = 1,2. Moreover, we show that the class of augmented cubes can be almost double-pancyclic.Link scheduling and data forwarding in wireless sensor networks of long chains tree topology
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.1070
Wireless sensor network (WSN) is characterized by the information transmission from multiple sensor nodes observing an environment. WSN based monitoring system with its nodes of low cost can be deployed in strict environment. According to the structure and the layout of the Monitoring objects, the long chain tree-like topology of wireless sensor network is often used. Such monitoring systems include power transmission line, oil transportation, gas transportation and road traffic monitoring. This paper firstly reviews the basic WSN theory and protocols concentrating basically on the MAC layer, try to identify the maximum throughput achievable in multi-hop long chain tree structure WSNs. A second objective of this paper is to propose a multimode hierarchical network based multi-channel assignment algorithm for data collection applications. The proposed algorithm has three components, Multimode Hierarchical Network Establishment (MHN), Channel Assignment (CA), and Data Forwarding (DF). The MHN module partitions the whole network into NL subnetworks, and each subnetwork represents a data dissemination mode. CA module assigns one unique channel to each mode. And then DF forwards each data flow only along its corresponding level. Evaluation results show that the algorithm proposed in this paper can significantly reduce data collection time, improve the network throughput.Regularized direct linear graph embedding
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.0689
Linear Graph Embedding (LGE) is the linearization of graph embedding, which could explain many of the popular dimensionality reduction algorithms such as LDA, LLE and LPP. LGE algorithms have been applied in many domains successfully; however, those algorithms need a PCA transform in advance to avoid a possible singular problem. In this paper, a regularized direct linear graph embedding algorithm is proposed by imposing Tikhonov regularizer on the objective function of LGE. Further, we extract features from the original data set directly by solving common Eigen value problem of symmetric positive semi definite matrix. Experimental results demonstrate the effectiveness and robustness of our proposed algorithm.Deployment patterns for <i xmlns="http://pub2web.metastore.ingenta.com/ns/">k</i>-coverage and <i xmlns="http://pub2web.metastore.ingenta.com/ns/">I</i>-connectivity in wireless sensor networks
http://dl-live.theiet.org/content/conferences/10.1049/cp.2010.1031
In this paper, the patterns for k-coverage (2k4) based on optimal /-connectivity (3/6) patterns are deeply discussed and a series of deployment patterns for k-coverage and I-connectivity are proposed under different ratios of sensor communication range (denoted by R<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">c</sub>) over sensing range (denoted by R<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">s</sub>) for Wireless Sensor Networks (WSNs). The patterns proposed are based on regular graphs and have precise thresholds that discriminate different k-coverage and I-connectivity when R<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">c</sub>/R<sub xmlns="http://pub2web.metastore.ingenta.com/ns/">s</sub>1. Also, the mathematical operations of MAPN (Maximum Area per Node) in all patterns are described in the paper. In the end, comparison graphs of coverage rate for each pattern are illustrated and different values of k and I in k-coverage and I-connectivity's coverage varying rates could be observed.