Search results for: elliptic curve digital signature algorithm

Authors: Kavita Burse, Manish Manoria, Vishnu P. S. Kirar

Abstract:

The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Keywords: Three term back propagation, multiplicative neuralnetwork, proportional factor, local minima.

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Authors: Chen Sun, Nemai Chandra Karmakar

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A novel direction-of-arrival (DOA) estimation technique, which uses a conventional multiple signal classification (MUSIC) algorithm with periodic signals, is applied to a single RF-port parasitic array antenna for direction finding. Simulation results show that the proposed method gives high resolution (1 degree) DOA estimation in an uncorrelated signal environment. The novelty lies in that the MUSIC algorithm is applied to a simplified antenna configuration. Only one RF port and one analogue-to-digital converter (ADC) are used in this antenna, which features low DC power consumption, low cost, and ease of fabrication. Modifications to the conventional MUSIC algorithm do not bring much additional complexity. The proposed technique is also free from the negative influence by the mutual coupling between elements. Therefore, the technique has great potential to be implemented into the existing wireless mobile communications systems, especially at the power consumption limited mobile terminals, to provide additional position location (PL) services.

Keywords: Direction-of-arrival (DOA) estimation, electronically steerable parasitic array radiator (ESPAR), multiple single classifications (MUSIC), position location.

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Authors: Roza Dastres, Mohsen Soori

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Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.

Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.

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Authors: Parisut Jitpakdee, Pakinee Aimmanee, Bunyarit Uyyanonvara

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Color Image quantization (CQ) is an important problem in computer graphics, image and processing. The aim of quantization is to reduce colors in an image with minimum distortion. Clustering is a widely used technique for color quantization; all colors in an image are grouped to small clusters. In this paper, we proposed a new hybrid approach for color quantization using firefly algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased algorithm that can be used for solving optimization problems. The proposed method can overcome the drawbacks of both algorithms such as the local optima converge problem in K-means and the early converge of firefly algorithm. Experiments on three commonly used images and the comparison results shows that the proposed algorithm surpasses both the base-line technique k-means clustering and original firefly algorithm.

Keywords: Clustering, Color quantization, Firefly algorithm, Kmeans.

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Authors: Jianwei Wu

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Based on the one-bit-matching principle and by turning the de-mixing matrix into an orthogonal matrix via certain normalization, Ma et al proposed a one-bit-matching learning algorithm on the Stiefel manifold for independent component analysis [8]. But this algorithm is not adaptive. In this paper, an algorithm which can extract kurtosis and its sign of each independent source component directly from observation data is firstly introduced.With the algorithm , the one-bit-matching learning algorithm is revised, so that it can make the blind separation on the Stiefel manifold implemented completely in the adaptive mode in the framework of natural gradient.

Keywords: Independent component analysis, kurtosis, Stiefel manifold, super-gaussians or sub-gaussians.

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Authors: Aber S. Aboalgasm, Rupert Ward

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This study investigated some results of the use of digital art tools by junior school children in order to discover if these tools could promote artistic ability and creativity. The study considers the ease of use and usefulness of the tools as well as how to assess artwork produced by digital means. As the use of these tools is a relatively new development in Art education, this study may help educators in their choice of which tools to use and when to use them. The study also aims to present a model for the assessment of students’ artistic development and creativity by studying their artistic activity. This model can help in determining differences in students’ creative ability and could be useful both for teachers, as a means of assessing digital artwork, and for students, by providing the motivation to use the tools to their fullest extent. Sixteen students aged nine to ten years old were observed and recorded while they used the digital drawing tools. The study found that, according to the students’ own statements, it was not the ease of use but the successful effects the tools provided which motivated the children to use them.

Keywords: Artistic ability, creativity, drawing digital tool, TAM model, psychomotor domain.

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Authors: Robert F. Kenny

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Because today-s media centric students have adopted digital as their native form of communication, teachers are having increasingly difficult time motivating reluctant readers to read and write. Our research has shown these text-averse individuals can learn to understand the importance of reading and writing if the instruction is based on digital narratives. While these students are naturally attracted to story, they are better at consuming them than creating them. Therefore, any intervention that utilizes story as its basis needs to include instruction on the elements of story making. This paper presents a series of digitally-based tools to identify potential weaknesses of visually impaired visual learners and to help motivate these and other media-centric students to select and complete books that are assigned to them

Keywords: Cognitive tempo, digital narratives, digital Booktalk

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.

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Authors: Wang Tong, He Pi-lian

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This paper sets forth the possibility and importance about applying Data Mining in Web logs mining and shows some problems in the conventional searching engines. Then it offers an improved algorithm based on the original AprioriAll algorithm which has been used in Web logs mining widely. The new algorithm adds the property of the User ID during the every step of producing the candidate set and every step of scanning the database by which to decide whether an item in the candidate set should be put into the large set which will be used to produce next candidate set. At the meantime, in order to reduce the number of the database scanning, the new algorithm, by using the property of the Apriori algorithm, limits the size of the candidate set in time whenever it is produced. Test results show the improved algorithm has a more lower complexity of time and space, better restrain noise and fit the capacity of memory.

Keywords: Candidate Sets Pruning, Data Mining, ImprovedAlgorithm, Noise Restrain, Web Log

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Authors: Vahid Salmani, Saman Taghavi Zargar, Mahmoud Naghibzadeh

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This paper presents a modified version of the maximum urgency first scheduling algorithm. The maximum urgency algorithm combines the advantages of fixed and dynamic scheduling to provide the dynamically changing systems with flexible scheduling. This algorithm, however, has a major shortcoming due to its scheduling mechanism which may cause a critical task to fail. The modified maximum urgency first scheduling algorithm resolves the mentioned problem. In this paper, we propose two possible implementations for this algorithm by using either earliest deadline first or modified least laxity first algorithms for calculating the dynamic priorities. These two approaches are compared together by simulating the two algorithms. The earliest deadline first algorithm as the preferred implementation is then recommended. Afterwards, we make a comparison between our proposed algorithm and maximum urgency first algorithm using simulation and results are presented. It is shown that modified maximum urgency first is superior to maximum urgency first, since it usually has less task preemption and hence, less related overhead. It also leads to less failed non-critical tasks in overloaded situations.

Keywords: Modified maximum urgency first, maximum urgency first, real-time systems, scheduling.

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Authors: O. Kadri, M. D. Mouss, L.H. Mouss, F. Merah

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This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.

Keywords: Binary Ant Colony algorithm, Support VectorMachine, feature selection, classification.

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Authors: Ezequiel Herruzo, Juan José Cruz, José Ignacio Benavides, Oscar Plata

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This paper describes a new algorithm of arrangement in parallel, based on Odd-Even Mergesort, called division and concurrent mixes. The main idea of the algorithm is to achieve that each processor uses a sequential algorithm for ordering a part of the vector, and after that, for making the processors work in pairs in order to mix two of these sections ordered in a greater one, also ordered; after several iterations, the vector will be completely ordered. The paper describes the implementation of the new algorithm on a Message Passing environment (such as MPI). Besides, it compares the obtained experimental results with the quicksort sequential algorithm and with the parallel implementations (also on MPI) of the algorithms quicksort and bitonic sort. The comparison has been realized in an 8 processors cluster under GNU/Linux which is running on a unique PC processor.

Keywords: Parallel algorithm, arrangement, MPI, sorting, parallel program.

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Authors: Mehdi Ghayoumi

Abstract:

We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.

Keywords: lda, adaptive, svm, face recognition.

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Authors: Yasunori Sugita, Toshinori Yoshikawa, Naoyuki Aikawa

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Variable digital filters are useful for various signal processing and communication applications where the frequency characteristics, such as fractional delays and cutoff frequencies, can be varied. In this paper, we propose a design method of variable FIR digital filters with an approximate linear phase characteristic in the passband. The proposed variable FIR filters have some large attenuation in stopband and their large attenuation can be varied by spectrum parameters. In the proposed design method, a quasi-equiripple characteristic can be obtained by using an iterative weighted least square method. The usefulness of the proposed design method is verified through some examples.

Keywords: Weighted Least Squares Approximation, Variable FIR Filters, Low-Delay, Quasi-Equiripple

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Authors: Maros Barabas, Michal Drozd, Petr Hanacek

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A novel behavioral detection framework is proposed to detect zero day buffer overflow vulnerabilities (based on network behavioral signatures) using zero-day exploits, instead of the signature-based or anomaly-based detection solutions currently available for IDPS techniques. At first we present the detection model that uses shadow honeypot. Our system is used for the online processing of network attacks and generating a behavior detection profile. The detection profile represents the dataset of 112 types of metrics describing the exact behavior of malware in the network. In this paper we present the examples of generating behavioral signatures for two attacks – a buffer overflow exploit on FTP server and well known Conficker worm. We demonstrated the visualization of important aspects by showing the differences between valid behavior and the attacks. Based on these metrics we can detect attacks with a very high probability of success, the process of detection is however very expensive.

Keywords: behavioral signatures, metrics, network, security design

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Authors: Pi-Chung Hsu

Abstract:

Super-quadrics can represent a set of implicit surfaces, which can be used furthermore as primitive surfaces to construct a complex object via Boolean set operations in implicit surface modeling. In fact, super-quadrics were developed to create a parametric surface by performing spherical product on two parametric curves and some of the resulting parametric surfaces were also represented as implicit surfaces. However, because not every parametric curve can be redefined implicitly, this causes only implicit super-elliptic and super-hyperbolic curves are applied to perform spherical product and so only implicit super-ellipsoids and hyperboloids are developed in super-quadrics. To create implicit surfaces with more diverse shapes than super-quadrics, this paper proposes an implicit representation of spherical product, which performs spherical product on two implicit curves like super-quadrics do. By means of the implicit representation, many new implicit curves such as polygonal, star-shaped and rose-shaped curves can be used to develop new implicit surfaces with a greater variety of shapes than super-quadrics, such as polyhedrons, hyper-ellipsoids, superhyperboloids and hyper-toroids containing star-shaped and roseshaped major and minor circles. Besides, the newly developed implicit surfaces can also be used to define new primitive implicit surfaces for constructing a more complex implicit surface in implicit surface modeling.

Keywords: Implicit surfaces, Soft objects, Super-quadrics.

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

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This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms.

Keywords: Cuttlefish Algorithm, bio-inspired algorithms, optimization.

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Authors: W. Maddison

Abstract:

This paper describes an Action Research project which was undertaken to inform professional practice in order to develop a newly created Centre for Student Success in the specific context of transnational medical and nursing education in the Middle East. The objectives were to enhance the academic performance, persistence, integration and personal and professional development of a multinational study body, in particular in relation to pre-clinical medical students, and to establish a comfortable, friendly and student-driven environment within an Irish medical university recently established in Bahrain. The outcomes of the project resulted in the development of a specific student success ‘signature’ for this particular transnational higher education context.

Keywords: Global-Local, pre-clinical medical students, student success, transnational higher education, Middle East.

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Authors: Juan Li, Chunfu Shao, Chunjiao Dong, Dan Zhao, Yinhong Liu

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Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is proposed for mixed-traffic data collection at intersections using surveillance cameras. The algorithm is derived from Gaussian Mixture Model (GMM), and uses a mergence time adjustment scheme to improve the traditional algorithm. Real-world video data were selected to test the algorithm. The results show that the proposed algorithm has the faster processing speed and more accuracy than the traditional algorithm. This indicates that the improved algorithm can be applied to detect mixed-traffic at signalized intersection, even when conflicts occur.

Keywords: detection, intersection, mixed traffic, moving objects.

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Authors: Anon Yantarasri, Yachai Limpiyakorn

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Decisions are regularly made during a project or daily life. Some decisions are critical and have a direct impact on project or human success. Formal evaluation is thus required, especially for crucial decisions, to arrive at the optimal solution among alternatives to address issues. According to microeconomic theory, all people-s decisions can be modeled as indifference curves. The proposed approach supports formal analysis and decision by constructing indifference curve model from the previous experts- decision criteria. These knowledge embedded in the system can be reused or help naïve users select alternative solution of the similar problem. Moreover, the method is flexible to cope with unlimited number of factors influencing the decision-making. The preliminary experimental results of the alternative selection are accurately matched with the expert-s decisions.

Keywords: Decision Analysis and Resolution, Indifference Curve, Multi-criteria Decision Making.

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Authors: Yi Zhang, Quan Zhou, Jun Li, Yanlang Hu

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Scheduling algorithm is a key technology in satellite switching system with input-buffer. In this paper, a new scheduling algorithm and its realization are proposed. Based on Crossbar switching fabric, the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduce the scheduling delay and cell loss rate. The analysis and simulation results by OPNET show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity. On the basis of these results, the hardware realization and simulation based on FPGA are completed, which validate the feasibility of the new scheduling algorithm.

Keywords: Scheduling algorithm, input-buffer, serial scheduling, hardware design.

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Authors: Mehmet Yörükoğlu, Serhat Aydın

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Since the discovery of the manuscript, mechanical methods for storing, transferring and using the information have evolved into digital methods over the time. In this process, libraries that are the center of the information have also become digitized and become accessible from anywhere and at any time in the world by taking on a structure that has no physical boundaries. In this context, some criteria for information obtained from digital libraries have become more important for users. This paper evaluates the user criteria from different perspectives that make a digital library more useful. The Step-Wise Weight Assessment Ratio Analysis-Weighted Aggregated Sum Product Assessment (SWARA-WASPAS) method is used with flexibility and easy calculation steps for the evaluation of digital library criteria. Three different digital libraries are evaluated by information technology experts according to five conflicting main criteria, ‘interface design’, ‘effects on users’, ‘services’, ‘user engagement’ and ‘context’. Finally, alternatives are ranked in descending order.

Keywords: Digital library, multi criteria decision making, SWARA-WASPAS method.

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Authors: V.K.Ananthashayana, Geetha.K.S

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In this paper, a recursive algorithm for the computation of 2-D DCT using Ramanujan Numbers is proposed. With this algorithm, the floating-point multiplication is completely eliminated and hence the multiplierless algorithm can be implemented using shifts and additions only. The orthogonality of the recursive kernel is well maintained through matrix factorization to reduce the computational complexity. The inherent parallel structure yields simpler programming and hardware implementation and provides log 1 2 3 2 N N-N+ additions and N N 2 log 2 shifts which is very much less complex when compared to other recent multiplierless algorithms.

Keywords: DCT, Multilplerless, Ramanujan Number, Recursive.

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Authors: R. Khadim, M. Erritali, A. Maaden

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Localization of nodes is one of the key issues of Wireless Sensor Network (WSN) that gained a wide attention in recent years. The existing localization techniques can be generally categorized into two types: range-based and range-free. Compared with rang-based schemes, the range-free schemes are more costeffective, because no additional ranging devices are needed. As a result, we focus our research on the range-free schemes. In this paper we study three types of range-free location algorithms to compare the localization error and energy consumption of each one. Centroid algorithm requires a normal node has at least three neighbor anchors, while DV-hop algorithm doesn’t have this requirement. The third studied algorithm is the amorphous algorithm similar to DV-Hop algorithm, and the idea is to calculate the hop distance between two nodes instead of the linear distance between them. The simulation results show that the localization accuracy of the amorphous algorithm is higher than that of other algorithms and the energy consumption does not increase too much.

Keywords: Wireless Sensor Networks, Node Localization, Centroid Algorithm, DV–Hop Algorithm, Amorphous Algorithm.

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Authors: Noboru Abe, Yoshinori Amai, Toshinori Nakatake, Sumio Masuda, Kazuaki Yamaguchi

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We consider the problem of placing labels of the points on a plane. For each point, its position, the size of its label and a priority are given. Moreover, several candidates of its label positions are prespecified, and each of such label positions is assigned a priority. The objective of our problem is to maximize the total sum of priorities of placed labels and their points. By refining a labeling algorithm that can use these priorities, we propose a new heuristic algorithm which is more suitable for treating the assigned priorities.

Keywords: Map labeling, greedy algorithm, heuristic algorithm, priority.

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Authors: ChangWoo Lee, Young Kow Lee, Sung Jun Ban, SungHoo Choi, Sang Woo Kim

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This paper suggests a new Affine Projection (AP) algorithm with variable data-reuse factor using the condition number as a decision factor. To reduce computational burden, we adopt a recently reported technique which estimates the condition number of an input data matrix. Several simulations show that the new algorithm has better performance than that of the conventional AP algorithm.

Keywords: Affine projection algorithm, variable data-reuse factor, condition number, convergence rate, misalignment.

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Authors: Hao Wu, Jonathan L. Shapiro

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The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.

Keywords: Bayesian optimization algorithm, greedy search, KL divergence, stochastic search.

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts.

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Authors: Jesús A. Pérez, Sam Coppieters, Dimitri Debruyne

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In the past decade, the use of digital image correlation (DIC) techniques has increased significantly in the area of experimental mechanics, especially for materials behavior characterization. This non-contact tool enables full field displacement and strain measurements over a complete region of interest. The DIC algorithm requires a random contrast pattern on the surface of the specimen in order to perform properly. To create this pattern, the specimen is usually first coated using a white matt paint. Next, a black random speckle pattern is applied using any suitable method. If the applied paint coating is too thick, its top surface may not be able to exactly follow the deformation of the specimen, and consequently, the strain measurement might be underestimated. In the present article, a study of the influence of the paint thickness on the strain underestimation is performed for different strain levels. The results are then compared to typical paint coating thicknesses applied by experienced DIC users. A slight strain underestimation was observed for paint coatings thicker than about 30μm. On the other hand, this value was found to be uncommonly high compared to coating thicknesses applied by DIC users.

Keywords: Digital Image Correlation, paint coating thickness, strain.

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Authors: N. Webb, A. Buchanan

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Digital and virtual heritage is often associated with the recreation of lost artefacts and architecture; however, we can also investigate works that were not completed, using digital tools and techniques. Here we explore physical evidence of a fourteenth-century Gothic vault located in the north transept of St Mary’s church in Nantwich, Cheshire, using existing springer stones that are built into the walls as a starting point. Digital surveying tools are used to document the architecture, followed by an analysis process to hypothesise and simulate possible design solutions, had the vault been completed. A number of options, both two-dimensionally and three-dimensionally, are discussed based on comparison with examples of other contemporary vaults, thus adding another specimen to the corpus of vault designs. Dissemination methods such as digital models and 3D prints are also explored as possible resources for demonstrating what the finished vault might have looked like for heritage interpretation and other purposes.

Keywords: Digital simulation, heritage interpretation, medieval vaults, virtual heritage, 3D scanning.

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