Search results for: tree matching

Authors: Ágnes Vathy-Fogarassy, Balázs Feil, János Abonyi

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Most of fuzzy clustering algorithms have some discrepancies, e.g. they are not able to detect clusters with convex shapes, the number of the clusters should be a priori known, they suffer from numerical problems, like sensitiveness to the initialization, etc. This paper studies the synergistic combination of the hierarchical and graph theoretic minimal spanning tree based clustering algorithm with the partitional Gath-Geva fuzzy clustering algorithm. The aim of this hybridization is to increase the robustness and consistency of the clustering results and to decrease the number of the heuristically defined parameters of these algorithms to decrease the influence of the user on the clustering results. For the analysis of the resulted fuzzy clusters a new fuzzy similarity measure based tool has been presented. The calculated similarities of the clusters can be used for the hierarchical clustering of the resulted fuzzy clusters, which information is useful for cluster merging and for the visualization of the clustering results. As the examples used for the illustration of the operation of the new algorithm will show, the proposed algorithm can detect clusters from data with arbitrary shape and does not suffer from the numerical problems of the classical Gath-Geva fuzzy clustering algorithm.

Keywords: Clustering, fuzzy clustering, minimal spanning tree, cluster validity, fuzzy similarity.

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: Pollen recognition, logistic model tree, expectation-maximization, local binary pattern.

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Authors: F. S. Eguakun, P. O. Adesoye

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One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV Oxide (CO2) to the atmosphere. Carbon IV Oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest lands are major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine) and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influences the carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density species could be relevant for management strategy to increase carbon storage.

Keywords: Adaptation, carbon sequestration, climate change, growth variables, wood density.

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Authors: Se-Jin Ko, Deok-Min Kim, Seok-Yoon Kim

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The trend of growing density on chips has increases not only the temperature in chips but also the gradient of the temperature depending on locations. In this paper, we propose the balanced skew tree generation technique for minimizing the clock skew that is affected by the temperature gradients on chips. We calculate the interconnect delay using Elmore delay equation, and find out the optimal balanced clock tree by modifying the clock trees generated through the Deferred Merge Embedding(DME) algorithm. The experimental results show that the distance variance of clock insertion points with and without considering the temperature gradient can be lowered below 54% and we confirm that the skew is remarkably decreased after applying the proposed technique.

Keywords: clock, clock-skew, temperature, thermal.

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Authors: Kitti Koonsanit, Chuleerat Jaruskulchai, Poonsak Miphokasap, Apisit Eiumnoh

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In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.

Keywords: Plant varieties selection system, decision tree, expert recommendation.

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Authors: V. S. K. Reddy, S. Sengupta, Y. M. Latha

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This paper presents an efficient VLSI architecture design to achieve real time video processing using Full-Search Block Matching (FSBM) algorithm. The design employs parallel bank architecture with minimum latency, maximum throughput, and full hardware utilization. We use nine parallel processors in our architecture and each controlled by a state machine. State machine control implementation makes the design very simple and cost effective. The design is implemented using VHDL and the programming techniques we incorporated makes the design completely programmable in the sense that the search ranges and the block sizes can be varied to suit any given requirements. The design can operate at frequencies up to 36 MHz and it can function in QCIF and CIF video resolution at 1.46 MHz and 5.86 MHz, respectively.

Keywords: Video Coding, Motion Estimation, Full-Search, Block-Matching, VLSI Architecture.

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Authors: S. Chumkiew, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

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This work investigated the phenology of Parah tree (Elateriospermum tapos) using the General Purpose Atmosphere Plant Soil Simulator (GAPS model) to determine the amount of Plant Available Water (PAW) in the soil. We found the correlation between PAW and the timing of budburst and flower burst at Khao Nan National Park, Nakhon Si Thammarat, Thailand. PAW from the GAPS model can be used as an indicator of soil water stress. The low amount of PAW may lead to leaf shedding in Parah trees.

Keywords: Basic GAPS, Parah (Elateriospermum tapos), Phenology, Climate, Nakhon Si Thammarat, Thailand.

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Authors: First G.M. Karthik, Second Ramachandra.V.Pujeri, Dr.

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Generalized Center String (GCS) problem are generalized from Common Approximate Substring problem and Common substring problems. GCS are known to be NP-hard allowing the problems lies in the explosion of potential candidates. Finding longest center string without concerning the sequence that may not contain any motifs is not known in advance in any particular biological gene process. GCS solved by frequent pattern-mining techniques and known to be fixed parameter tractable based on the fixed input sequence length and symbol set size. Efficient method known as Bpriori algorithms can solve GCS with reasonable time/space complexities. Bpriori 2 and Bpriori 3-2 algorithm are been proposed of any length and any positions of all their instances in input sequences. In this paper, we reduced the time/space complexity of Bpriori algorithm by Constrained Based Frequent Pattern mining (CBFP) technique which integrates the idea of Constraint Based Mining and FP-tree mining. CBFP mining technique solves the GCS problem works for all center string of any length, but also for the positions of all their mutated copies of input sequence. CBFP mining technique construct TRIE like with FP tree to represent the mutated copies of center string of any length, along with constraints to restraint growth of the consensus tree. The complexity analysis for Constrained Based FP mining technique and Bpriori algorithm is done based on the worst case and average case approach. Algorithm's correctness compared with the Bpriori algorithm using artificial data is shown.

Keywords: Constraint Based Mining, FP tree, Data mining, GCS problem, CBFP mining technique.

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Authors: Mahdi Shaneh, Azizollah Taheri

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The goal of this project is to design a system to recognition voice commands. Most of voice recognition systems contain two main modules as follow “feature extraction" and “feature matching". In this project, MFCC algorithm is used to simulate feature extraction module. Using this algorithm, the cepstral coefficients are calculated on mel frequency scale. VQ (vector quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithms, the accuracy of this voice command system is high. Using these algorithms, by at least 5 times repetition for each command, in a single training session, and then twice in each testing session zero error rate in recognition of commands is achieved.

Keywords: MFCC, Vector quantization, Vocal tract, Voicecommand.

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Authors: Rahma Al Maawali, Hameed Sulaiman

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Air pollution both from point and non-point sources is difficult to control once released in to the atmosphere. There is no engineering method known available to ameliorate the dispersed pollutants. The only suitable approach is the ecological method of constructing green belts in and around the pollution sources. Air pollution in Muscat, Oman is a serious concern due to ever increasing vehicles on roads. Identifying the air pollution tolerance levels of species is important for implementing pollution control strategies in the urban areas of Muscat. Hence, in the present study, Air Pollution Tolerance Index (APTI) for ten avenue tree species was evaluated by analyzing four bio-chemical parameters, plus their Anticipated Performance Index (API) in field conditions. Based on the two indices, Ficus benghalensis was the most suitable one with the highest performance score. Conocarpus erectuse, Phoenix dactylifera, and Pithcellobium dulce were found to be good performers and are recommended for extensive planting. Azadirachta indica which is preferred for its dense canopy is qualified in the moderate category. The rest of the tree species expressed lower API score of less than 51, hence cannot be considered as suitable species for pollution mitigation plantation projects.

Keywords: Air pollution tolerance index, avenue tree species, bio-chemical parameters, Muscat.

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Authors: Xing Li, Chengqing Zong

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This paper presents an effective framework for Chinesesyntactic parsing, which includes two parts. The first one is a parsing framework, which is based on an improved bottom-up chart parsingalgorithm, and integrates the idea of the beam search strategy of N bestalgorithm and heuristic function of A* algorithm for pruning, then get multiple parsing trees. The second is a novel evaluation model, which integrates contextual and partial lexical information into traditional PCFG model and defines a new score function. Using this model, the tree with the highest score is found out as the best parsing tree. Finally,the contrasting experiment results are given. Keywords?syntactic parsing, PCFG, pruning, evaluation model.

Keywords: syntactic parsing, PCFG, pruning, evaluation model.

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Authors: Zhihan Li

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Nowadays, most universities use the course enrollment system considering students’ registration orders. However, the students’ preference level to certain courses is also one important factor to consider. In this research, the possibility of applying a preference-first system has been discussed and analyzed compared to the order-first system. A bipartite graph is applied to resemble the relationship between students and courses they tend to register. With the graph set up, we apply Ford-Fulkerson (F.F.) Algorithm to maximize parings between two sets of nodes, in our case, students and courses. Two models are proposed in this paper: the one considered students’ order first, and the one considered students’ preference first. By comparing and contrasting the two models, we highlight the usability of models which potentially leads to better designs for school course registration systems.

Keywords: Bipartite graph, Ford-Fulkerson Algorithm, graph theory, maximum matching.

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Authors: Padmanabhan Balasubramanian, C. Ardil

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An effective approach for realizing the binary tree structure, representing a combinational logic functionality with enhanced throughput, is discussed in this paper. The optimization in maximum operating frequency was achieved through delay minimization, which in turn was possible by means of reducing the depth of the binary network. The proposed synthesis methodology has been validated by experimentation with FPGA as the target technology. Though our proposal is technology independent, yet the heuristic enables better optimization in throughput even after technology mapping for such Boolean functionality; whose reduced CNF form is associated with a lesser literal cost than its reduced DNF form at the Boolean equation level. For cases otherwise, our method converges to similar results as that of [12]. The practical results obtained for a variety of case studies demonstrate an improvement in the maximum throughput rate for Spartan IIE (XC2S50E-7FT256) and Spartan 3 (XC3S50-4PQ144) FPGA logic families by 10.49% and 13.68% respectively. With respect to the LUTs and IOBUFs required for physical implementation of the requisite non-regenerative logic functionality, the proposed method enabled savings to the tune of 44.35% and 44.67% respectively, over the existing efficient method available in literature [12].

Keywords: Binary logic tree, FPGA based design, Boolean function, Throughput rate, CNF, DNF.

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original dataset. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 dataset is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: Distributed intrusion detection system, mobile agent, feature selection, Bees Algorithm, decision tree.

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Authors: Girish Kumar Singh, Sonajharia Minz

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Granular computing deals with representation of information in the form of some aggregates and related methods for transformation and analysis for problem solving. A granulation scheme based on clustering and Rough Set Theory is presented with focus on structured conceptualization of information has been presented in this paper. Experiments for the proposed method on four labeled data exhibit good result with reference to classification problem. The proposed granulation technique is semi-supervised imbibing global as well as local information granulation. To represent the results of the attribute oriented granulation a tree structure is proposed in this paper.

Keywords: Granular computing, clustering, Rough sets, datamining.

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Authors: Min Yao, Kota Aoki, Hiroshi Nagahashi

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In this paper, a novel system recognition of human faces without using face different color photographs is proposed. It mainly in face detection, normalization and recognition. Foot method of combination of Haar-like face determined segmentation and region-based histogram stretchi (RHST) is proposed to achieve more accurate perf using Haar. Apart from an effective angle norm side-face (pose) normalization, which is almost a might be important and beneficial for the prepr introduced. Then histogram-based and photom normalization methods are investigated and ada retinex (ASR) is selected for its satisfactory illumin Finally, weighted multi-block local binary pattern with 3 distance measures is applied for pair-mat Experimental results show its advantageous perfo with PCA and multi-block LBP, based on a principle.

Keywords: Face detection, pair-matching rec normalization, skin color segmentation.

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Authors: Athanasios Theoharidis, Thomas Kamalakis, Ioannis Neokosmidis, Thomas Sphicopoulos

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In this paper, the application of the Mode Matching (MM) method in the case of photonic crystal waveguide discontinuities is presented. The structure under consideration is divided into a number of cells, which supports a number of guided and evanescent modes. These modes can be calculated numerically by an alternative formulation of the plane wave expansion method for each frequency. A matrix equation is then formed relating the modal amplitudes at the beginning and at the end of the structure. The theory is highly efficient and accurate and can be applied to study the transmission sensitivity of photonic crystal devices due to fabrication tolerances. The accuracy of the MM method is compared to the Finite Difference Frequency Domain (FDFD) and the Adjoint Variable Method (AVM) and good agreement is observed.

Keywords: Optical Communications, Integrated Optics, Photonic Crystals, Optical Waveguide Discontinuities.

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Authors: Guruprasad Khataniar, Hitesh Tahbildar, Prakriti Prava Das

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There are various overlay structures that provide efficient and scalable solutions for point and range query in a peer-topeer network. Overlay structure based on m-Binary Search Tree (BST) is one such popular technique. It deals with the division of the tree into different key intervals and then assigning the key intervals to a BST. The popularity of the BST makes this overlay structure vulnerable to different kinds of attacks. Here we present four such possible attacks namely index poisoning attack, eclipse attack, pollution attack and syn flooding attack. The functionality of BST is affected by these attacks. We also provide different security techniques that can be applied against these attacks.

Keywords: BST, eclipse attack, index poisoning attack, pollution attack, syn flooding attack.

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Authors: W. Devapriya, C. Nelson Kennedy Babu, T. Srihari

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Automatic License plate recognition (ALPR) is a technology which recognizes the registration plate or number plate or License plate of a vehicle. In this paper, an Indian vehicle number plate is mined and the characters are predicted in efficient manner. ALPR involves four major technique i) Pre-processing ii) License Plate Location Identification iii) Individual Character Segmentation iv) Character Recognition. The opening phase, named pre-processing helps to remove noises and enhances the quality of the image using the conception of Morphological Operation and Image subtraction. The second phase, the most puzzling stage ascertain the location of license plate using the protocol Canny Edge detection, dilation and erosion. In the third phase, each characters characterized by Connected Component Approach (CCA) and in the ending phase, each segmented characters are conceptualized using cross correlation template matching- a scheme specifically appropriate for fixed format. Major application of ALPR is Tolling collection, Border Control, Parking, Stolen cars, Enforcement, Access Control, Traffic control. The database consists of 500 car images taken under dissimilar lighting condition is used. The efficiency of the system is 97%. Our future focus is Indian Vehicle License Plate Validation (Whether License plate of a vehicle is as per Road transport and highway standard).

Keywords: Automatic License plate recognition, Character recognition, Number plate Recognition, Template matching, morphological operation, canny edge detection.

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Authors: M. Kaya, M. Eris

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Internet use, intelligent communication tools, and social media have all become an integral part of our daily life as a result of rapid developments in information technology. However, this widespread use increases crimes committed in the digital environment. Therefore, digital forensics, dealing with various crimes committed in digital environment, has become an important research topic. It is in the research scope of digital forensics to investigate digital evidences such as computer, cell phone, hard disk, DVD, etc. and to report whether it contains any crime related elements. There are many software and hardware tools developed for use in the digital evidence acquisition process. Today, the most widely used digital evidence investigation tools are based on the principle of finding all the data taken place in digital evidence that is matched with specified criteria and presenting it to the investigator (e.g. text files, files starting with letter A, etc.). Then, digital forensics experts carry out data analysis to figure out whether these data are related to a potential crime. Examination of a 1 TB hard disk may take hours or even days, depending on the expertise and experience of the examiner. In addition, it depends on examiner’s experience, and may change overall result involving in different cases overlooked. In this study, a hash-based matching and digital evidence evaluation method is proposed, and it is aimed to automatically classify the evidence containing criminal elements, thereby shortening the time of the digital evidence examination process and preventing human errors.

Keywords: Block matching, digital evidence, hash list.

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Authors: Y. H. Tsai, Y. W. Chen

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Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.

Keywords: Facial feature extraction, AdaBoost, Active shapemodel, Hausdorff distance

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Authors: N. Muthukumaran, R. Ravi

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The Quad Tree Decomposition based performance analysis of compressed image data communication for lossy and lossless through wireless sensor network is presented. Images have considerably higher storage requirement than text. While transmitting a multimedia content there is chance of the packets being dropped due to noise and interference. At the receiver end the packets that carry valuable information might be damaged or lost due to noise, interference and congestion. In order to avoid the valuable information from being dropped various retransmission schemes have been proposed. In this proposed scheme QTD is used. QTD is an image segmentation method that divides the image into homogeneous areas. In this proposed scheme involves analysis of parameters such as compression ratio, peak signal to noise ratio, mean square error, bits per pixel in compressed image and analysis of difficulties during data packet communication in Wireless Sensor Networks. By considering the above, this paper is to use the QTD to improve the compression ratio as well as visual quality and the algorithm in MATLAB 7.1 and NS2 Simulator software tool.

Keywords: Image compression, Compression Ratio, Quad tree decomposition, Wireless sensor networks, NS2 simulator.

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Authors: F. Majeed, D. V. Thiel, M. Shahpari

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An electrically small meander line antenna is designed for impedance matching with RF transceiver chip CC1101. The design provides the flexibility of tuning the reactance of the antenna over a wide range of values: highly capacitive to highly inductive. The antenna was printed with silver ink on FR4 substrate using the screen printing design process. The antenna impedance was perfectly matched to CC1101 at 433 MHz. The measured radiation efficiency of the antenna was 81.3% at resonance. The 3 dB and 10 dB fractional bandwidth of the antenna was 14.5% and 4.78%, respectively. The read range of the antenna was compared with a copper wire monopole antenna over a distance of five meters. The antenna, with a perfect impedance match with RF transceiver chip CC1101, shows improvement in the read range compared to a monopole antenna over the specified distance.

Keywords: Meander line antenna, RFID, Silver ink printing, Impedance matching.

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Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a paradigm designed to facilitate the way of controlling the network dynamically and with more agility. Network traffic is a set of flows, each of which contains a set of packets. In SDN, a matching process is performed on every packet coming to the network in the SDN switch. Only the headers of the new packets will be forwarded to the SDN controller. In terminology, the flow header fields are called tuples. Basically, these tuples are 5-tuple: the source and destination IP addresses, source and destination ports, and protocol number. This flow information is used to provide an overview of the network traffic. Our module is meant to extract this 5-tuple with the packets and flows numbers and show them as a list. Therefore, this list can be used as a first step in the way of detecting the DDoS attack. Thus, this module can be considered as the beginning stage of any flow-based DDoS detection method.

Keywords: Matching, OpenFlow tables, POX controller, SDN, table-miss.

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Authors: R. Arulmurugan, P. Sengottuvelan

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Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.

Keywords: Object Detection, Cross-point Searching, Wavelet Neural Network, Object Determination, Gabor Wavelet Transform, Tagged Grid Matching.

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Authors: Yi-an Cui, Lu Wang, Jian-ping Xiao

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This paper presents an automatic feature recognition method based on center-surround difference detecting and fuzzy logic that can be applied in ground-penetrating radar (GPR) image processing. Adopted center-surround difference method, the salient local image regions are extracted from the GPR images as features of detected objects. And fuzzy logic strategy is used to match the detected features and features in template database. This way, the problem of objects detecting, which is the key problem in GPR image processing, can be converted into two steps, feature extracting and matching. The contributions of these skills make the system have the ability to deal with changes in scale, antenna and noises. The results of experiments also prove that the system has higher ratio of features sensing in using GPR to image the subsurface structures.

Keywords: feature recognition, GPR image, matching strategy, salient image

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Authors: Slim Yacoub, Kosai Raoof

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The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.

Keywords: Surface EMG, Adaptive, Matching Pursuit, Powerline interference.

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Authors: Hina Kausher, Sangita Srivastava

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In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which cover the variety of figure proportions in both height and girth. 3,000 data have been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from the some states of India to produce the sizing system suitable for clothing manufacture and retailing. The data are used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from the large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: Anthropometric data, data mining, decision tree, garments manufacturing, ready-made garments, sizing systems.

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Authors: K.Somasundaram, I.Kaspar Raj

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In this paper we have proposed three and two stage still gray scale image compressor based on BTC. In our schemes, we have employed a combination of four techniques to reduce the bit rate. They are quad tree segmentation, bit plane omission, bit plane coding using 32 visual patterns and interpolative bit plane coding. The experimental results show that the proposed schemes achieve an average bit rate of 0.46 bits per pixel (bpp) for standard gray scale images with an average PSNR value of 30.25, which is better than the results from the exiting similar methods based on BTC.

Keywords: Bit plane, Block Truncation Coding, Image compression, lossy compression, quad tree segmentation

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

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Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.

Keywords: Association, frequent pattern mining, functionalprogramming, pattern matching.

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