Search results for: Pattern similarity score (PaSS)

Authors: Noraini Ahmad, Seripah Awang Kechil, Norma Mohd Basir

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The steady coupled dissipative layers, called Marangoni mixed convection boundary layers, in the presence of a magnetic field and solute concentration that are formed along the surface of two immiscible fluids with uniform suction or injection effects is examined. The similarity boundary layer equations are solved numerically using the Runge-Kutta Fehlberg with shooting technique. The Marangoni, buoyancy and external pressure gradient effects that are generated in mixed convection boundary layer flow are assessed. The velocity, temperature and concentration boundary layers thickness decrease with the increase of the magnetic field strength and the injection to suction. For buoyancy-opposed flow, the Marangoni mixed convection parameter enhances the velocity boundary layer but decreases the temperature and concentration boundary layers. However, for the buoyancy-assisted flow, the Marangoni mixed convection parameter decelerates the velocity but increases the temperature and concentration boundary layers.

Keywords: Magnetic field, mixed Marangoni convection, similarity boundary layers, solute concentration.

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Authors: Luciano Nieddu, Giuseppe Manfredi

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In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

Keywords: K-means, Industrial ores classification, Invariant Features, Supervised Classification.

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: Genetic data, Pinzgau cattle, supervised learning.

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Authors: U. Kairov, T. Karpenyuk, E. Ramanculov, A. Zinovyev

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The most common result of analysis of highthroughput data in molecular biology represents a global list of genes, ranked accordingly to a certain score. The score can be a measure of differential expression. Recent work proposed a new method for selecting a number of genes in a ranked gene list from microarray gene expression data such that this set forms the Optimally Functionally Enriched Network (OFTEN), formed by known physical interactions between genes or their products. Here we present calculation results of relative connectivity of genes from META-OFTEN network and tentative biological interpretation of the most reproducible signal. The relative connectivity and inbetweenness values of genes from META-OFTEN network were estimated.

Keywords: Microarray, META-OFTEN, gene network.

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Authors: Ahmad Attiq Al-Ogaibi, Ahmad Sharieh, Moh’d Belal Al-Zoubi, R. Bremananth

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In pattern clustering, nearest neighborhood point computation is a challenging issue for many applications in the area of research such as Remote Sensing, Computer Vision, Pattern Recognition and Statistical Imaging. Nearest neighborhood computation is an essential computation for providing sufficient classification among the volume of pixels (voxels) in order to localize the active-region-of-interests (AROI). Furthermore, it is needed to compute spatial metric relationships of diverse area of imaging based on the applications of pattern recognition. In this paper, we propose a new methodology for finding the nearest neighbor point, depending on making a virtually grid of a hexagon cells, then locate every point beneath them. An algorithm is suggested for minimizing the computation and increasing the turnaround time of the process. The nearest neighbor query points Φ are fetched by seeking fashion of hexagon holistic. Seeking will be repeated until an AROI Φ is to be expected. If any point Υ is located then searching starts in the nearest hexagons in a circular way. The First hexagon is considered be level 0 (L0) and the surrounded hexagons is level 1 (L1). If Υ is located in L1, then search starts in the next level (L2) to ensure that Υ is the nearest neighbor for Φ. Based on the result and experimental results, we found that the proposed method has an advantage over the traditional methods in terms of minimizing the time complexity required for searching the neighbors, in turn, efficiency of classification will be improved sufficiently.

Keywords: Hexagon cells, k-nearest neighbors, Nearest Neighbor, Pattern recognition, Query pattern, Virtually grid

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Authors: Collins C. Chiemeke

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The need to evaluate and understand the natural drainage pattern in a flood prone, and fast developing environment is of paramount importance. This information will go a long way to help the town planners to determine the drainage pattern, road networks and areas where prominent structures are to be located. This research work was carried out with the aim of studying the Bayelsa landscape topography using digitized topographic information, and to model the natural drainage flow pattern that will aid the understanding and constructions of workable drainages. To achieve this, digitize information of elevation and coordinate points were extracted from a global imagery map. The extracted information was modeled into 3D surfaces. The result revealed that the average elevation for Bayelsa State is 12 m above sea level. The highest elevation is 28 m, and the lowest elevation 0 m, along the coastline. In Yenagoa the capital city of Bayelsa were a detail survey was carried out showed that average elevation is 15 m, the highest elevation is 25 m and lowest is 3 m above the mean sea level. The regional elevation in Bayelsa, showed a gradation decrease from the North Eastern zone to the South Western Zone. Yenagoa showed an observed elevation lineament, were low depression is flanked by high elevation that runs from the North East to the South west. Hence, future drainages in Yenagoa should be directed from the high elevation, from South East toward the North West and from the North West toward South East, to the point of convergence which is at the center that flows from South East toward the North West. Bayelsa when considered on a regional Scale, the flow pattern is from the North East to the South West, and also North South. It is recommended that in the event of any large drainage construction at municipal scale, it should be directed from North East to the South West or from North to South. Secondly, detail survey should be carried out to ascertain the local topography and the drainage pattern before the design and construction of any drainage system in any part of Bayelsa.

Keywords: Bayelsa, Digitized Topographic Information, Drainage, Flood.

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Authors: T. Sakamoto, N. Hori

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A multi-rate discrete-time model, whose response agrees exactly with that of a continuous-time original at all sampling instants for any sampling periods, is developed for a linear system, which is assumed to have multiple real eigenvalues. The sampling rates can be chosen arbitrarily and individually, so that their ratios can even be irrational. The state space model is obtained as a combination of a linear diagonal state equation and a nonlinear output equation. Unlike the usual lifted model, the order of the proposed model is the same as the number of sampling rates, which is less than or equal to the order of the original continuous-time system. The method is based on a nonlinear variable transformation, which can be considered as a generalization of linear similarity transformation, which cannot be applied to systems with multiple eigenvalues in general. An example and its simulation result show that the proposed multi-rate model gives exact responses at all sampling instants.

Keywords: Multi-rate discretization, linear systems, triangularization, similarity transformation, diagonalization, exponential transformation, multiple eigenvalues

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Authors: Pitaktiratham J., Sinlan T., Anuntavoranich P., Sinthupinyo S.

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The Kansei engineering is a technology which converts human feelings into quantitative terms and helps designers develop new products that meet customers- expectation. Standard Kansei engineering procedure involves finding relationships between human feelings and design elements of which many researchers have found forward and backward relationship through various soft computing techniques. In this paper, we proposed the framework of Kansei engineering linking relationship not only between human feelings and design elements, but also the whole part of product, by constructing association rules. In this experiment, we obtain input from emotion score that subjects rate when they see the whole part of the product by applying semantic differentials. Then, association rules are constructed to discover the combination of design element which affects the human feeling. The results of our experiment suggest the pattern of relationship of design elements according to human feelings which can be derived from the whole part of product.

Keywords: Association Rules Mining, Kansei Engineering, Product Design, Semantic Differentials

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Authors: Yin-Ching Keung, Kit-Lun Yick

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The issue of bra fitting has persisted throughout history despite advancements in molded bra cups. To gain a deeper understanding of the interaction between the breast and bra pattern, this study combines the art of traditional bra patternmaking with 3D body scanning technology. By employing a 2D bra pattern drafting method and analyzing the effect of body shape on the desired bra cup shape, the study focuses on the differentiation of the lower cup among bras designed for flat and round body-shaped breasts. The results shed light on the impact of body shape on bra fit and provide valuable insights for further research and improvements in bra design, pattern drafting, and fit. The integration of 3D body scanning technology enhances the accuracy and precision of measurements, allowing for a more comprehensive analysis of the unique contours and dimensions of the breast and body. Ultimately, the study aims to provide individuals with different body shapes a more comfortable and well-fitted bra-wearing experience, contributing to the ongoing efforts to alleviate the longstanding problem of bra fitting.

Keywords: Breast shapes, bra fitting, 3D body scanning, bra patternmaking.

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Authors: M. V. Sudhamani, C. R. Venugopal

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Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.

Keywords: Content-based, indexing, cluster, region.

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Authors: Roslinda Nazar, Amin Noor, Khamisah Jafar, Ioan Pop

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In this paper, the steady laminar three-dimensional boundary layer flow and heat transfer of a copper (Cu)-water nanofluid in the vicinity of a permeable shrinking flat surface in an otherwise quiescent fluid is studied. The nanofluid mathematical model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Dual solutions (upper and lower branch solutions) are found for the similarity boundary layer equations for a certain range of the suction parameter. A stability analysis has been performed to show which branch solutions are stable and physically realizable. The numerical results for the skin friction coefficient and the local Nusselt number as well as the velocity and temperature profiles are obtained, presented and discussed in detail for a range of various governing parameters.

Keywords: Heat Transfer, Nanofluid, Shrinking Surface, Stability Analysis, Three-Dimensional Flow.

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Authors: S. Sarumathi, P. Ranjetha, C. Saraswathy, M. Vaishnavi, S. Geetha

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Clustering is an unsupervised learning technique for aggregating data objects into meaningful classes so that intra cluster similarity is maximized and inter cluster similarity is minimized in data mining. However, no single clustering algorithm proves to be the most effective in producing the best result. As a result, a new challenging technique known as the cluster ensemble approach has blossomed in order to determine the solution to this problem. For the cluster analysis issue, this new technique is a successful approach. The cluster ensemble's main goal is to combine similar clustering solutions in a way that achieves the precision while also improving the quality of individual data clustering. Because of the massive and rapid creation of new approaches in the field of data mining, the ongoing interest in inventing novel algorithms necessitates a thorough examination of current techniques and future innovation. This paper presents a comparative analysis of various cluster ensemble approaches, including their methodologies, formal working process, and standard accuracy and error rates. As a result, the society of clustering practitioners will benefit from this exploratory and clear research, which will aid in determining the most appropriate solution to the problem at hand.

Keywords: Clustering, cluster ensemble methods, consensus function, data mining, unsupervised learning.

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Authors: Makram Ben Jeddou

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ABC classification is widely used by managers for inventory control. The classical ABC classification is based on Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to consider other important criteria. From these models, we will consider a specific model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score, based on a normalized average between a good and a bad optimized index, can affect the ABC-item classification. We will focus on items differently assigned to classes and then propose a classification compromise.

Keywords: ABC classification, Multi criteria inventory classification models, ZF-model.

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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Authors: Tran Trong Thang, Nguyen Phan Kien, Trinh Quang Duc

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The phased-array ultrasound transducer types are utilities for medical ultrasonography as well as optical imaging. However, their discontinuity characteristic limits the applications due to the artifacts contaminated into the reconstructed images. Because of the effects of the ultrasound pressure field pattern to the echo ultrasonic waves as well as the optical modulated signal, the side lobes of the focused ultrasound beam induced by discontinuity of the phased-array ultrasound transducer might the reason of the artifacts. In this paper, a simple method in approach of numerical simulation was used to investigate the limitation of discontinuity of the elements in phased-array ultrasound transducer and their effects to the ultrasound pressure field. Take into account the change of ultrasound pressure field patterns in the conditions of variation of the pitches between elements of the phased-array ultrasound transducer, the appropriated parameters for phased-array ultrasound transducer design were asserted quantitatively.

Keywords: Phased-array ultrasound transducer, sound pressure pattern, discontinuous sound field, numerical visualization.

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Authors: Cosmin Rablou

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In this paper we present a way of controlling the concurrent access to data in a distributed application using the Pessimistic Offline Lock design pattern. In our case, the application processes a complex entity, which contains in a hierarchical structure different other entities (objects). It will be shown how the complex entity and the contained entities must be locked in order to control the concurrent access to data.

Keywords: Object-oriented programming, Pessimistic Lock, Design pattern, Concurrent access to data, Processing complex entities

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Authors: Mohammad J. Almalkawi

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In this communication, a low-cost circularly polarized wire antenna exhibiting improved gain performance for Dedicated Short Range Communications (DSRC), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications is presented. The proposed antenna comprises a Y-shaped quarterwavelength monopole antenna surrounded by two iterations of eight conductive arched walls acting as parasitic elements to enhance the overall antenna gain and to shape the radiation pattern in the H-plane. A hemispherical radome shell is added to protect the antenna structure and its effect on the antenna performance is discussed. The designed antenna demonstrates antenna gain of 8.2 dB with omnidirectional far-field radiation pattern in the H-plane. The gain of the proposed antenna is also compared with the characteristic of the stand-alone Y-shaped monopole to highlight the advantages of the proposed approach.

Keywords: Circularly polarized, dedicated short-range communication, omnidirectional pattern, vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), Y-shaped wire monopole antenna.

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Authors: C. Ardil

Abstract:

This article presents a multiple criteria evaluation approach to uncertainty, vagueness, and imprecision analysis for ranking alternatives with fuzzy data for decision making using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The fighter aircraft evaluation and selection decision making problem is modeled in a fuzzy environment with triangular fuzzy numbers. The fuzzy decision information related to the fighter aircraft selection problem is taken into account in ordering the alternatives and selecting the best candidate. The basic fuzzy TOPSIS procedure steps transform fuzzy decision matrices into matrices of alternatives evaluated according to all decision criteria. A practical numerical example illustrates the proposed approach to the fighter aircraft selection problem.

Keywords: triangular fuzzy number (TFN), multiple criteria decision making analysis, decision making, aircraft selection, MCDMA, fuzzy TOPSIS

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Authors: M. R. AlRashidi, K. M. El-Naggar, M. F. AlHajri

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A new technique based on Pattern search optimization is proposed for estimating different solar cell parameters in this paper. The estimated parameters are the generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor. The proposed approach is tested and validated using double diode model to show its potential. Performance of the developed approach is quite interesting which signifies its potential as a promising estimation tool.

Keywords: Solar Cell, Parameter Estimation, Pattern Search.

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Authors: Kayun Chantarasathaporn, Chonawat Srisa-an

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Design Patterns have gained more and more acceptances since their emerging in software development world last decade and become another de facto standard of essential knowledge for Object-Oriented Programming developers nowadays. Their target usage, from the beginning, was for regular computers, so, minimizing power consumption had never been a concern. However, in this decade, demands of more complicated software for running on mobile devices has grown rapidly as the much higher performance portable gadgets have been supplied to the market continuously. To get along with time to market that is business reason, the section of software development for power conscious, battery, devices has shifted itself from using specific low-level languages to higher level ones. Currently, complicated software running on mobile devices are often developed by high level languages those support OOP concepts. These cause the trend of embracing Design Patterns to mobile world. However, using Design Patterns directly in software development for power conscious systems is not recommended because they were not originally designed for such environment. This paper demonstrates the adapted Design Pattern for power limitation system. Because there are numerous original design patterns, it is not possible to mention the whole at once. So, this paper focuses only in creating Energy Conscious version of existing regular "Builder Pattern" to be appropriated for developing low power consumption software.

Keywords: Design Patterns, Builder Pattern, Low Power Consumption, Object Oriented Programming, Power Conscious System, Software.

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Authors: Maleika Heenaye- Mamode Khan , Naushad Mamode Khan, Raja K.Subramanian

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Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.

Keywords: Dorsal hand vein pattern, PCA, Cholesky decomposition, Lanczos algorithm.

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Authors: Diego Ordonez, Carlos Dafonte, Minia Manteiga, Bernardino Arcayy

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This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with different resolutions depending on the region to analyze. The benefits and performance of the algorithm are discussed in application to the Iris dataset, a classical example for pattern recognition.

Keywords: Neural networks, Self-organizing feature maps, Hierarchicalsystems, Pattern clustering methods.

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Authors: N. Charoenpokaraj, P. Chitman

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This research aims to study species, abundance, status of birds, the similarities and activity characteristics of birds which reap benefits from the research area in boat touring routes in Tha Ka sub-district, Amphawa District, Samut Songkram Province, Thailand. from October 2012 – September 2013. The data was analyzed to find the abundance, and similarity index of the birds. The results from the survey of birds on all three routes found that there are 33 families and 63 species. Route 3 (traditional coconut sugar making kiln – resort) had the most species; 56 species. There were 18 species of commonly found birds with an abundance level of 5, which calculates to 28.57% of all bird species. In August, 46 species are found, being the greatest number of bird species benefiting from this route. As for the status of the birds, there are 51 resident birds, 7 resident and migratory birds, and 5 migratory birds. On Route 2 and Route 3, the similarity index value is equal to 0.881. The birds are classified by their activity characteristics i.e. insectivore, piscivore, granivore, nectrivore and aquatic invertebrate feeder birds. Some birds also use the area for nesting.

Keywords: Bird diversity, boat touring routes, Samut Songkram.

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Authors: Wanli Ma, Dat Tran, Dharmendra Sharma

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The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.

Keywords: Artificial Immune Systems, ComputationalIntelligence, Negative Selection, Pattern Discovery.

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Authors: Abiodun M. Aibinu, Athaur Rahman Najeeb, Momoh J. E. Salami, Amir A. Shafie

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An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. This method is suitable for problems in which the image can be modeled by explicit known source functions with a few adjustable parameters. Despite the success reported in the use of modeling technique as an alternative MRI reconstruction technique, two important problems constitutes challenges to the applicability of this method, these are estimation of Model order and model coefficient determination. In this paper, five of the suggested method of evaluating the model order have been evaluated, these are: The Final Prediction Error (FPE), Akaike Information Criterion (AIC), Residual Variance (RV), Minimum Description Length (MDL) and Hannan and Quinn (HNQ) criterion. These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). The result for each criterion is compared to result obtained by the use of a fixed order technique and three measures of similarity were evaluated. Result obtained shows that the use of MDL gives the highest measure of similarity to that use by a fixed order technique.

Keywords: Autoregressive Moving Average (ARMA), MagneticResonance Imaging (MRI), Parametric modeling, Transient Error.

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Authors: Krishnaiah Arkanti, Ramulu Malothu

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The experiments have been conducted to study the mechanical properties of commercially pure copper processing at room temperature by severe plastic deformation using equal channel angular extrusion (ECAE) through a die of 90^oangle up to 3 passes by route B_C i.e. rotating the sample in the same direction by 90^o after each pass. ECAE is used to produce from existing coarse grains to ultra-fine, equiaxed grains structure with high angle grain boundaries in submicron level by introducing a large amount of shear strain in the presence of hydrostatic pressure into the material without changing billet shape or dimension. Mechanical testing plays an important role in evaluating fundamental properties of engineering materials as well as in developing new materials and in controlling the quality of materials for use in design and construction. Yield stress, ultimate tensile stress and ductility are structure sensitive properties and vary with the structure of the material. Microhardness and tensile tests were carried out to evaluate the hardness, strength and ductility of the ECAE processed materials. The results reveal that the strength and hardness of commercially pure copper samples improved significantly without losing much ductility after each pass.

Keywords: Equal Channel Angular Extrusion, Severe Plastic Deformation, Copper, Mechanical Properties.

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and roughsets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: Rough-sets, Classification, Feature Selection, Entropy, Outliers, Frequent itemset mining.

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Authors: Stefan Wagenpfeil, Felix Engel, Paul McKevitt, Matthias Hemmje

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Multimedia Indexing and Retrieval is generally de-signed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, espe-cially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelisation. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Keywords: indexing, retrieval, multimedia, graph code, graph algorithm

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.

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Authors: M. M. Hossain, M. Z. Hasan, M. Alauddin, S. Akhter

Abstract:

Climate change has become a major concern across the world as the intensity along with quantity of the rainfall, mean surface temperature and other climatic parameters have been changed not only in Bangladesh but also in the entire globe. Bangladesh has already experienced many natural hazards. Among them changing of rainfall pattern, erratic and heavy rainfalls are very common. But changes of rainfall pattern and its amount is still in question to some extent. This study aimed to unfold how the historical rainfalls varied over time and how would be their future trends. In this context, historical rainfall data (1975-2014) were collected from Bangladesh Metrological Department (BMD) and then a time series model was developed using Box-Jenkins algorithm in IBM SPSS to forecast the future rainfall. From the historical data analysis, this study revealed that the amount of rainfall decreased over the time and shifted to the post monsoons. Forecasted rainfall shows that the pre-monsoon and early monsoon will get drier in future whereas late monsoon and post monsoon will show huge fluctuations in rainfall magnitudes with temporal variations which means Bangladesh will get comparatively drier seasons in future which may be a serious problem for the country as it depends on agriculture.

Keywords: Monsoon, Pre-monsoon, rainfall, pattern, variations, IBM-SPSS.

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