Search results for: Canny edge algorithm

Authors: Ramnath Narhete, Saket Pandey, Puran Gour

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This paper presents of dual-band planner antenna with a compact radiator for 2.4/5.2/5.8 proposed by optimizing its resonant frequency, Bandwidth of operation and radiation frequency using the genetic algorithm. The antenna consists L-shaped and E-shaped radiating element to generate two resonant modes for dual band operation. The above techniques have been successfully used in many applications. Dual band antenna with the compact radiator for 2.4/5.2/5.8 GHz WLAN application design and radiator size only width 8mm and a length is 11.3 mm. The antenna can we used for various application in the field of communication. Genetic algorithm will be used to design the antenna and impedance matching network.

Keywords: genetic algorithm, dual-band E, dual-band L, WLAN, compact radiator

Procedia PDF Downloads 558

Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

Procedia PDF Downloads 381

Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

Procedia PDF Downloads 119

Authors: Seyed Abdol Mohammad Rezavand, Mohammad Nikbakhsh

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Withdrawal resistance of screws driven into HDPE/Sugarcane Bagasse injection molded parts was investigated. After chemical treatment and drying, SCB was pre-mixed with HDPE using twin extruder. The resulting granules are used in producing samples in injection molding machine. SCB with the quantity of %10, %20, and %30 was used. By using a suitable fixture, screw heads can take with tensile test machine grips. Parts with screws in the center and edge were fasten together. Then, withdrawal resistance was measured with tensile test machine. Injection gate is at the one edge of the part. The results show that by increasing SCB content in composite, the withdrawal resistance is decreased. Furthermore, the withdrawal resistance at the edges (near injection gate and the end of the filling path of mold cavity) is more than that of the center.

Keywords: polyethylene, sugarcane bagasse, wood plastic, screw, withdrawal resistance

Procedia PDF Downloads 558

Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

Procedia PDF Downloads 265

Authors: Allan F. F. Alves, Fernando A. Bacchim Neto, Guilherme Giacomini, Marcela de Oliveira, Ana L. M. Pavan, Maria E. D. Rosa, Diana R. Pina

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Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke.

Keywords: ischemic stroke, image processing, CT scans, Fuzzy C-means

Procedia PDF Downloads 344

Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

Procedia PDF Downloads 367

Authors: T. R. Sharika, Ashwini Kumar, Kamal Bijlani

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Encryption is the process of converting crucial information’s unreadable to unauthorized persons. Image security is an important type of encryption that secures all type of images from cryptanalysis. A stream cipher is a fast symmetric key algorithm which is used to convert plaintext to cipher text. In this paper we are proposing an image encryption algorithm with Discrete Cosine Transform and Stream Ciphers that can improve compression of images and enhanced security. The paper also explains the use of a shuffling algorithm for enhancing securing.

Keywords: decryption, DCT, encryption, RC4 cipher, stream cipher

Procedia PDF Downloads 340

Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

Procedia PDF Downloads 523

Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

Procedia PDF Downloads 311

Authors: Alireza Alesaadi

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Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Hoda Abugharsa

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In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit.

Keywords: insert sorting algorithm, ASM chart, sorter circuit, state machine, control unit

Procedia PDF Downloads 428

Authors: Ghazala Anjum, Farooq Hussain Bhat, Ravi Kumar

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Multiferroic materials are vital for new application and memory devices, not only because of the presence of multiple types of domains but also as a result of cross correlation between coexisting forms of magnetic and electrical orders. In spite of wide studies done on multiferroic bulk ceramic materials their realization in thin film form is yet limited due to some crucial problems. During the last few years, special attention has been devoted to synthesis of thin films like of BiFeO₃. As they allow direct integration of the material into the device technology. Therefore owing to the process of exploration of new multiferroic thin films, preparation, and characterization of La₀.₈Bi₀.₂Fe₀.₇Mn₀.₃O₃ (LBFMO3) thin film on LaAlO₃ (LAO) substrate with LaNiO₃ (LNO) being the buffer layer has been done. The fact that all the electrical and magnetic properties are closely related to the electronic structure makes it inevitable to study the electronic structure of system under study. Without the knowledge of this, one may never be sure about the mechanism responsible for different properties exhibited by the thin film. Literature review reveals that studies on change in atomic and the hybridization state in multiferroic samples are still insufficient except few. The technique of x-ray absorption (XAS) has made great strides towards the goal of providing such information. It turns out to be a unique signature to a given material. In this milieu, it is time honoured to have the electronic structure study of the elements present in the LBFMO₃ multiferroic thin film on LAO substrate with buffer layer of LNO synthesized by RF sputtering technique. We report the electronic structure studies of well characterized LBFMO3 multiferroic thin film on LAO substrate with LNO as buffer layer using near-edge X-ray absorption fine structure (NEXAFS). Present exploration has been performed to find out the valence state and crystal field symmetry of ions present in the system. NEXAFS data of O K- edge spectra reveals a slight shift in peak position along with growth in intensities of low energy feature. Studies of Mn L₃,₂- edge spectra indicates the presence of Mn³⁺/Mn⁴⁺ network apart from very small contribution from Mn²⁺ ions in the system that substantiates the magnetic properties exhibited by the thin film. Fe L₃,₂- edge spectra along with spectra of reference compound reveals that Fe ions are present in +3 state. Electronic structure and valence state are found to be in accordance with the magnetic properties exhibited by LBFMO/LNO/LAO thin film.

Keywords: magnetic, multiferroic, NEXAFS, x-ray absorption fine structure, XMCD, x-ray magnetic circular dichroism

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Authors: Giorgi Methodishvili, Iuliia Methodishvili

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In this paper product development algorithm is used to determine the optimal management of financial resources in company. Aspects of financial management considered include put initial investment, examine all possible ways to solve the problem and the optimal rotation length of profit. The software of given problems is based using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Abdelkhalek Bakkari

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Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.

Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image

Procedia PDF Downloads 449

Authors: Dong-Keun Jeong, Jong-Hyun Kim, Woon-Ha Yoon, Hee-Je Kim

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In order to automatically operate the ultrasonic transducer drive system for sonicating aluminum, this paper proposes the ultrasonic transducer sensorless control algorithm. The resonance frequency shift and electrical impedance change is a common phenomenon in the state of the ultrasonic transducer. The proposed control algorithm make use of the impedance change of ultrasonic transducer according to the environment between air state and aluminum alloy state, it controls the ultrasonic transducer drive system autonomous without a sensor. The proposed sensorless autonomous ultrasonic transducer control algorithm was experimentally verified using a 3kW prototype ultrasonic transducer drive system.

Keywords: ultrasonic transducer drive system, impedance change, sensorless, autonomous control algorithm

Procedia PDF Downloads 336

Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

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Authors: Ahad Salimi, Hassan Masoumi

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Prostate cancer is one of the most common recognized cancers in men, and, is one of the most important mortality factors of cancer in this group. Determining of prostate’s boundary in TRUS (Transrectal Ultra Sound) images is very necessary for prostate cancer treatments. The weakness edges and speckle noise make the ultrasound images inherently to segment. In this paper a new automatic algorithm for prostate segmentation in TRUS images proposed that include three main stages. At first morphological smoothing and sticks filtering are used for noise removing. In second step, for finding a point in prostate region, SOFM algorithm is enlisted and in the last step, the boundary of prostate extracting accompanying active contour is employed. For validation of proposed method, a number of experiments are conducted. The results obtained by our algorithm show the promise of the proposed algorithm.

Keywords: SOFM, preprocessing, GVF contour, segmentation

Procedia PDF Downloads 305

Authors: Francesco Rizzuto, Matthew Stickland, Stephan Hannot

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The simulation of a positive displacement pump system with commercial software for Computer Fluid Dynamics (CFD), will result in an enormous computational effort due to the complexity of the pump system. This drawback restricts the use of it to a specific part of the pump in one simulation. This research focuses on developing an algorithm that provides a suitable result in agreement with experiment data, without that computational effort. The compressible equations are solved with an explicit algorithm. A comparison is presented between the FV method with Monotonic Upwind scheme for Conservative Laws (MUSCL) with slope limiter and experimental results. The source term for cavitation and friction is introduced into the algorithm with a slipping strategy and solved with a 4th order Runge-Kutta scheme (RK4). Different pumps are modeled and analyzed to evaluate the flexibility of the code. The simulation required minimal computation time and resources without compromising the accuracy of the simulation results. Therefore, this algorithm highlights the feasibility of pressure pulsation simulation as a design tool for an industrial purpose.

Keywords: cavitation, diaphragm, DVCM, finite volume, MUSCL, positive displacement pump

Procedia PDF Downloads 128

Authors: Ping Bo, Meng Yunshan

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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

Procedia PDF Downloads 295

Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi

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Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.

Keywords: digital image, image processing, edge detection, grayscale, castella beams

Procedia PDF Downloads 116

Authors: Anju Bala, Inderveer Chana

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Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.

Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation

Procedia PDF Downloads 491

Authors: Ahmed Tarek, Ahmed Alveed

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Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.

Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem

Procedia PDF Downloads 122

Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

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The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

Procedia PDF Downloads 443

Authors: Rejab Hajlaoui, Tarek Moulahi, Hervé Guyennet

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In a highway scenario, the vehicle speed can exceed 120 kmph. Therefore, any vehicle can enter or leave the network within a very short time. This mobility adversely affects the network connectivity and decreases the life time of all established links. To ensure an effective stability in vehicular ad hoc networks with minimum broadcasting storm, we have developed a weighted algorithm based on the k-medoids clustering algorithm (WKCA). Indeed, the number of clusters and the initial cluster heads will not be selected randomly as usual, but considering the available transmission range and the environment size. Then, to ensure optimal assignment of nodes to clusters in both k-medoids phases, the combined weight of any node will be computed according to additional metrics including direction, relative speed and proximity. Empirical results prove that in addition to the convergence speed that characterizes the k-medoids algorithm, our proposed model performs well both AODV-Clustering and OLSR-Clustering protocols under different densities and velocities in term of end-to-end delay, packet delivery ratio, and throughput.

Keywords: communication, clustering algorithm, k-medoids, sensor, vehicular ad hoc network

Procedia PDF Downloads 212

Authors: Dmitry A. Koptelov, Leonid M. Mestetskiy

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Voronoi Diagram (VD) of finite set of disjoint simple polygons, called sites, is a partition of plane into loci (for each site at the locus) – regions, consisting of points that are closer to a given site than to all other. Set of polygons is a universal model for many applications in engineering, geoinformatics, design, computer vision, and graphics. VD of polygons construction usually done with a reduction to task of constructing VD of segments, for which there are effective O(n log n) algorithms for n segments. Preprocessing – constructing segments from polygons’ sides, and postprocessing – polygon’s loci construction by merging the loci of the sides of each polygon are also included in reduction. This approach doesn’t take into account two specific properties of the resulting segment sites. Firstly, all this segments are connected in pairs in the vertices of the polygons. Secondly, on the one side of each segment lies the interior of the polygon. The polygon is obviously included in its locus. Using this properties in the algorithm for VD construction is a resource to reduce computations. The article proposes an algorithm for the direct construction of VD of polygonal sites. Algorithm is based on sweepline paradigm, allowing to effectively take into account these properties. The solution is performed based on reduction. Preprocessing is the constructing of set of sites from vertices and edges of polygons. Each site has an orientation such that the interior of the polygon lies to the left of it. Proposed algorithm constructs VD for set of oriented sites with sweepline paradigm. Postprocessing is a selecting of edges of this VD formed by the centers of empty circles touching different polygons. Improving the efficiency of the proposed sweepline algorithm in comparison with the general Fortune algorithm is achieved due to the following fundamental solutions: 1. Algorithm constructs only such VD edges, which are on the outside of polygons. Concept of oriented sites allowed to avoid construction of VD edges located inside the polygons. 2. The list of events in sweepline algorithm has a special property: the majority of events are connected with “medium” polygon vertices, where one incident polygon side lies behind the sweepline and the other in front of it. The proposed algorithm processes such events in constant time and not in logarithmic time, as in the general Fortune algorithm. The proposed algorithm is fully implemented and tested on a large number of examples. The high reliability and efficiency of the algorithm is also confirmed by computational experiments with complex sets of several thousand polygons. It should be noted that, despite the considerable time that has passed since the publication of Fortune's algorithm in 1986, a full-scale implementation of this algorithm for an arbitrary set of segment sites has not been made. The proposed algorithm fills this gap for an important special case - a set of sites formed by polygons.

Keywords: voronoi diagram, sweepline, polygon sites, fortunes' algorithm, segment sites

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Authors: Alluru Gopala Krishna, Thella Babu Rao

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In machining, there is always a problem with heat generation and friction produced during the process as they consequently affect tool wear and surface finish. An instant heat transfer mechanism could protect the cutting tool edge and enhance the tool life by cooling the cutting edge of the tool. In the present work, carbon nanotube (CNT) based nano-cutting fluid is proposed for machining a hard-to-cut material. Tool wear and surface roughness are considered for the evaluation of the nano-cutting fluid in turning process. The performance of nanocoolant is assessed against the conventional coolant and dry machining conditions and it is observed that the proposed nanocoolant has produced better performance than the conventional coolant.

Keywords: CNT based nano cutting fluid, tool wear, turning, surface roughness

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: Toshanlal Meenpal, Ankita Meenpal

Abstract:

A very important technique in reversible data hiding field is Difference expansion. Secret message as well as the cover image may be completely recovered without any distortion after data extraction process due to reversibility feature. In general, in any difference expansion scheme embedding is performed by integer transform in the difference image acquired by grouping two neighboring pixel values. This paper proposes an improved reversible difference expansion embedding scheme. We mainly consider edge direction for embedding by modifying the difference of two neighboring pixels values. In general, the larger difference tends to bring a degraded stego image quality than the smaller difference. Image quality in the range of 0.5 to 3.7 dB in average is achieved by the proposed scheme, which is shown through the experimental results. However payload wise it achieves almost similar capacity in comparisons with previous method.

Keywords: information hiding, wedge direction, difference expansion, integer transform

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Authors: Murat Yazici

Abstract:

Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

Procedia PDF Downloads 27