Search results for: similarity theory and Hilbert Huang Transform.

Authors: Yi-Zhong Weng, Chien-Kang Huang, Yu-Feng Huang, Chi-Yuan Yu, Darby Tien-Hao Chang

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Search for a tertiary substructure that geometrically matches the 3D pattern of the binding site of a well-studied protein provides a solution to predict protein functions. In our previous work, a web server has been built to predict protein-ligand binding sites based on automatically extracted templates. However, a drawback of such templates is that the web server was prone to resulting in many false positive matches. In this study, we present a sequence-order constraint to reduce the false positive matches of using automatically extracted templates to predict protein-ligand binding sites. The binding site predictor comprises i) an automatically constructed template library and ii) a local structure alignment algorithm for querying the library. The sequence-order constraint is employed to identify the inconsistency between the local regions of the query protein and the templates. Experimental results reveal that the sequence-order constraint can largely reduce the false positive matches and is effective for template-based binding site prediction.

Keywords: Protein structure, binding site, functional prediction

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Authors: Wen-Shan Lin, Shu-Lu Hsu

Abstract:

Environmental concern and consumer rights have entailed e-tailers to adopt better strategies to facilitate product returns from customers. As the demand for reverse logistics (RL) continues to grow, little is known about what motivates e-tailers to enhance their RL capabilities and about the role RL capabilities plays in enabling e-tailers to achieve better customer satisfaction and economic performance. Based on resource-based theory and institutional theory, this article proposes that the following factors play a critical role in influencing the RL capability of e-tailers: (a) Financial resource commitment to RL, (b) managerial resource commitment to RL, and (c) institutional pressure to implement RL. Based on the role of these factors, the study provides a framework and propositions that serve to guide future research addressing the link among resources, institutional pressure, and RL capability.

Keywords: Reverse logistics, e-tailing, resource-based theory, institutional theory.

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Authors: Nasiri Ahmadullah, Shimozato Tetsuhiro, Masayuki Tai

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This paper presents the step-by-step procedure for using Elastic Theory to calculate the internal stresses in composite bridge girders prestressed by the Preflexing Technology, called Prebeam in Japan and Preflex beam worldwide. Elastic Theory approaches preflex beams the same way as it does the conventional composite girders. Since preflex beam undergoes different stages of construction, calculations are made using different sectional and material properties. Stresses are calculated in every stage using the properties of the specific section. Stress accumulation gives the available stress in a section of interest. Concrete presence in the section implies prestress loss due to creep and shrinkage, however; more work is required to be done in this field. In addition to the graphical presentation of this application, this paper further discusses important notes of graphical comparison between the results of an experimental-only research carried out on a preflex beam, with the results of simulation based on the elastic theory approach, for an identical beam using Finite Element Modeling (FEM) by the author.

Keywords: Composite girder, elastic theory, preflex beam, prestressing.

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Authors: Ghulam Ahmad

Abstract:

In this paper comparison of Reflector Antenna analyzing techniques based on wave and ray nature of optics is presented for an offset reflector antenna using GRASP (General Reflector antenna Analysis Software Package) software. The results obtained using PO (Physical Optics), PTD (Physical theory of Diffraction), and GTD (Geometrical Theory of Diffraction) are compared. The validity of PO and GTD techniques in regions around the antenna, caustic behavior of GTD in main beam, and deviation of GTD in case of near-in sidelobes of radiation pattern are discussed. The comparison for far-out sidelobes predicted by PO, PO + PTD and GTD is described. The effect of Direct Radiations from feed which results in feed selection for the system is addressed.

Keywords: Geometrical optics & geometrical theory of diffraction, offset reflector antenna, physical optics & physical theory of diffraction, PO & GO comaprison.

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Authors: Young-Seok Choi

Abstract:

This paper provides a quantitative measure of the time-varying multiunit neuronal spiking activity using an entropy based approach. To verify the status embedded in the neuronal activity of a population of neurons, the discrete wavelet transform (DWT) is used to isolate the inherent spiking activity of MUA. Due to the de-correlating property of DWT, the spiking activity would be preserved while reducing the non-spiking component. By evaluating the entropy of the wavelet coefficients of the de-noised MUA, a multiresolution Shannon entropy (MRSE) of the MUA signal is developed. The proposed entropy was tested in the analysis of both simulated noisy MUA and actual MUA recorded from cortex in rodent model. Simulation and experimental results demonstrate that the dynamics of a population can be quantified by using the proposed entropy.

Keywords: Discrete wavelet transform, Entropy, Multiresolution, Multiunit activity.

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Authors: Celso A. G. Santos, Paula K. M. M. Freire

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The urban centers within northeastern Brazil are mainly influenced by the intense rainfalls, which can occur after long periods of drought, when flood events can be observed during such events. Thus, this paper aims to study the rainfall frequencies in such region through the wavelet transform. An application of wavelet analysis is done with long time series of the total monthly rainfall amount at the capital cities of northeastern Brazil. The main frequency components in the time series are studied by the global wavelet spectrum and the modulation in separated periodicity bands were done in order to extract additional information, e.g., the 8 and 16 months band was examined by an average of all scales, giving a measure of the average annual variance versus time, where the periods with low or high variance could be identified. The important increases were identified in the average variance for some periods, e.g. 1947 to 1952 at Teresina city, which can be considered as high wet periods. Although, the precipitation in those sites showed similar global wavelet spectra, the wavelet spectra revealed particular features. This study can be considered an important tool for time series analysis, which can help the studies concerning flood control, mainly when they are applied together with rainfall-runoff simulations.

Keywords: rainfall data, urban center, wavelet transform.

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Authors: Raniya Alsharif

Abstract:

The color theory of good and evil is the association of colors to the omnipresent concept of good and evil, where human behavior and perception can be highly influenced by seeing black and white, making these connotations almost dangerously distinctive where they can be very hard to distinguish. This theory is a human construct that dates back to ancient Egypt and has been used since then in almost all forms of communication and expression, such as art, fashion, literature, and religious manuscripts, helping the implantation of preconceived ideas that influence behavior and society. This is a mixed-methods research that uses both surveys to collect quantitative data related to the theory and a vignette to collect qualitative data by using a scenario where participants aged between 18-25 will style two characters of good and bad characteristics with color contrasting clothes, both yielding results about the nature of the preconceived perceptions associated with ‘black and white’ and ‘good and evil’, illustrating the important role of media and communications in human behavior and subconscious, and also uncover how far this theory goes in the age of social media enlightenment.

Keywords: Color perception, interpretivism, thematic analysis, vignettes.

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Authors: Lianglin Xiong, Yun Zhao, Tao Jiang

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In this paper, we study the stability of n-dimensional linear fractional neutral differential equation with time delays. By using the Laplace transform, we introduce a characteristic equation for the above system with multiple time delays. We discover that if all roots of the characteristic equation have negative parts, then the equilibrium of the above linear system with fractional order is Lyapunov globally asymptotical stable if the equilibrium exist that is almost the same as that of classical differential equations. An example is provided to show the effectiveness of the approach presented in this paper.

Keywords: Fractional neutral differential equation, Laplace transform, characteristic equation.

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Authors: Xueqin Shan, Wenhua Hou, Xiaosu Ye, Chuanming Wu

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Any decision-making is based on certain theory. Taking the public rental housing in Chongqing municipality as an example, this essay states that the stakeholder theory can provide innovative criteria and evaluation methods for Public Private Partnership (PPP) projects. It gives an analysis of how to choose decision-making criteria for different stakeholders in the PPP model and what measures to take to meet the criteria to form “symbiotic" decision-making mode through contracts and to boost the application of PPP model in large-scale public programs in China.

Keywords: PPP, Stakeholder Theory, Stakeholders, Decision- making Criteria

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Authors: Mohammad Ali Molaei

Abstract:

New Growth Theory helps us make sense of the ongoing shift from a resource-based economy to a knowledge-based economy. It underscores the point that the economic processes which create and diffuse new knowledge are critical to shaping the growth of nations, communities and individual firms. In all too many contributions to New (Endogenous) Growth Theory – though not in all – central reference is made to 'a stock of knowledge', a 'stock of ideas', etc., this variable featuring centre-stage in the analysis. Yet it is immediately apparent that this is far from being a crystal clear concept. The difficulty and uncertainty of being able to capture the value associated with knowledge is a real problem. The intent of this paper is introducing new thinking and theorizing about the knowledge and its measurability in new growth theory. Moreover the study aims to synthesize various strain of the literature with a practical bearing on knowledge concept. By contribution of institution framework which is found within NGT, we can indirectly measure the knowledge concept. Institutions matter because they shape the environment for production and employment of new knowledge

Keywords: Institution Framework, Knowledge, New GrowthTheory (NGT)

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Authors: Julian Pigott

Abstract:

This paper presents the Language Learning as a Means of Drive Engagement (LLMDE) theory, derived from a grounded theory analysis of interviews with Japanese university students. According to LLMDE theory, language learning can be understood as a means of engaging one or more of four self-fulfillment drives: the drive to expand one’s horizons (perspective drive); the drive to make a success of oneself (status drive); the drive to engage in interaction with others (communication drive); and the drive to obtain intellectual and affective stimulation (entertainment drive). While many theories of learner psychology focus on conscious agency, LLMDE theory addresses the role of the unconscious. In addition, supplementary thematic analysis of the data revealed the role of context in mediating drive engagement. Unexpected memorable events, for example, play a key role in instigating and, indirectly, in regulating learning, as do institutional and cultural contexts. Given the apparent importance of such factors beyond the immediate control of the learner, and given the pervasive role of habit and drives, it is argued that the concept of motivation merits theoretical reappraisal. Rather than an underlying force determining language learning success or failure, it can be understood to emerge sporadically in consciousness to promote behavioral change, or to protect habitual behavior from disruption.

Keywords: Drives, grounded theory, motivation, significant events.

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Authors: Veni.S , K.A.Narayanankutty

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For about two decades scientists have been developing techniques for enhancing the quality of medical images using Fourier transform, DWT (Discrete wavelet transform),PDE model etc., Gabor wavelet on hexagonal sampled grid of the images is proposed in this work. This method has optimal approximation theoretic performances, for a good quality image. The computational cost is considerably low when compared to similar processing in the rectangular domain. As X-ray images contain light scattered pixels, instead of unique sigma, the parameter sigma of 0.5 to 3 is found to satisfy most of the image interpolation requirements in terms of high Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error (MSE) and better image quality by adopting windowing technique.

Keywords: Hexagonal lattices, Gabor filter, Interpolation, imageprocessing.

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Authors: Min Wang , Shuyuan Yang

Abstract:

The paper presents a method of designing ultrawide band (UWB) pulse array beamformer in the case of nearfield. Firstly the principle of space-time processing of UWB pulse array is discussed. The radical beampattern transform based on spherical coordinates is employed to solve the nearfield beamforming of UWB pulse array. The frequency invariant technology is considered for the frequency dependent beampattern of UWB pulse array. We use a multirate bank scheme of to implement the FI beamformer of UWB pulse array. By using multirate filters in each element channel, it can make the response of the UWB array to avoid distortion in the whole band. The simulation resultes are given to prove the efficiency and feasibility of this method.

Keywords: UWB pulse array, frequency invariant, multiratebank, nearfield beamformer, radical transform

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Authors: John N. Ellinas

Abstract:

In this paper, a robust watermarking algorithm using the wavelet transform and edge detection is presented. The efficiency of an image watermarking technique depends on the preservation of visually significant information. This is attained by embedding the watermark transparently with the maximum possible strength. The watermark embedding process is carried over the subband coefficients that lie on edges, where distortions are less noticeable, with a subband level dependent strength. Also, the watermark is embedded to selected coefficients around edges, using a different scale factor for watermark strength, that are captured by a morphological dilation operation. The experimental evaluation of the proposed method shows very good results in terms of robustness and transparency to various attacks such as median filtering, Gaussian noise, JPEG compression and geometrical transformations.

Keywords: Watermarking, wavelet transform, edge detection.

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

Abstract:

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

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

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

Abstract:

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: Abdulnasir Hossen, Ulrich Heute

Abstract:

In 1990 [1] the subband-DFT (SB-DFT) technique was proposed. This technique used the Hadamard filters in the decomposition step to split the input sequence into low- and highpass sequences. In the next step, either two DFTs are needed on both bands to compute the full-band DFT or one DFT on one of the two bands to compute an approximate DFT. A combination network with correction factors was to be applied after the DFTs. Another approach was proposed in 1997 [2] for using a special discrete wavelet transform (DWT) to compute the discrete Fourier transform (DFT). In the first step of the algorithm, the input sequence is decomposed in a similar manner to the SB-DFT into two sequences using wavelet decomposition with Haar filters. The second step is to perform DFTs on both bands to obtain the full-band DFT or to obtain a fast approximate DFT by implementing pruning at both input and output sides. In this paper, the wavelet-based DFT (W-DFT) with Haar filters is interpreted as SB-DFT with Hadamard filters. The only difference is in a constant factor in the combination network. This result is very important to complete the analysis of the W-DFT, since all the results concerning the accuracy and approximation errors in the SB-DFT are applicable. An application example in spectral analysis is given for both SB-DFT and W-DFT (with different filters). The adaptive capability of the SB-DFT is included in the W-DFT algorithm to select the band of most energy as the band to be computed. Finally, the W-DFT is extended to the two-dimensional case. An application in image transformation is given using two different types of wavelet filters.

Keywords: Image Transform, Spectral Analysis, Sub-Band DFT, Wavelet DFT.

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Authors: Weifeng Pan

Abstract:

Complex networks have been intensively studied across many fields, especially in Internet technology, biological engineering, and nonlinear science. Software is built up out of many interacting components at various levels of granularity, such as functions, classes, and packages, representing another important class of complex networks. It can also be studied using complex network theory. Over the last decade, many papers on the interdisciplinary research between software engineering and complex networks have been published. It provides a different dimension to our understanding of software and also is very useful for the design and development of software systems. This paper will explore how to use the complex network theory to analyze software structure, and briefly review the main advances in corresponding aspects.

Keywords: Metrics, measurement, complex networks, software.

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Authors: Salem El-t. Ashoor, Ibtisam M. Ediab

Abstract:

Zirconium diamine and triamine complexes can possess biological activities. These complexes were synthesised via the reaction of equimolar quantities of 1,10-phenanthroline {NC₃H₃(C₆H₂)NC₃H₃} (L1) or 4-4-amino phenazone {ONC₆H₅(NH)CH(NH₂} (L2) or diphenyl carbizon {HNNCO(NH)₂(C₆H₅)} (L3) with a Zirconium Salt {ZrOCl₂} in a 1:1 ratio to form complexes [{NC₃H₃(C₆H₂)NC₃H₃}ZrOCl₂}] [ZrOCl₂L₁], [{(O₂NC₆H₄(NH)(NH₂)}ZrOCl₂] [ZrOCl₂L₂] and [{HNNCO(NH)₂(C₆H₅)ZrOCl₂}] [ZrOCl₂L₃] respectively. They were characterised using Fourier Transform Infrared (FT-IR) and UV-Visible spectroscopy. Also a variable temperature study of these complexes was completed, using UV-Visible spectroscopy to observe electronic transitions under temperature control. Also a DFT study was done on these complexes via the information from FT-IR and UV-Visible spectroscopy.

These complexes were found to show different inhibition to the growth of bacterial strains of Bacillus spp. & Klebsiella spp. & E. coli & Proteus spp. & Pseudomona spp. at different concentrations (0.001, 0.2 and 1M). For better understanding these complexes were examined by using a Density Functional Theory (DFT) calculation.

Keywords: (1:10-phenanthroline) (L1), 4-4-amino phenazone (L2), diphenyl carbizon (L3), DFT study, antibacterial.

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Authors: T. Sakamoto, N. Hori

Abstract:

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: J. Prakash, K. Rajesh

Abstract:

In this paper we present a new method for coin identification. The proposed method adopts a hybrid scheme using Eigenvalues of covariance matrix, Circular Hough Transform (CHT) and Bresenham-s circle algorithm. The statistical and geometrical properties of the small and large Eigenvalues of the covariance matrix of a set of edge pixels over a connected region of support are explored for the purpose of circular object detection. Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain only a small number of non-zero elements, they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of the circumference pixels is identified using Raster scan algorithm which uses geometrical symmetry property. After finding circular objects, the proposed method uses the texture on the surface of the coins called texton, which are unique properties of coins, refers to the fundamental micro structure in generic natural images. This method has been tested on several real world images including coin and non-coin images. The performance is also evaluated based on the noise withstanding capability.

Keywords: Circular Hough Transform, Coin detection, Covariance matrix, Eigenvalues, Raster scan Algorithm, Texton.

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Authors: O. J. Olaniran, P. E. D. Love, D. J. Edwards, O. Olatunji, J. Matthews

Abstract:

Cost overruns are a persistent problem in oil and gas megaprojects. Whilst the extant literature is filled with studies on incidents and causes of cost overruns, underlying theories to explain their emergence in oil and gas megaprojects are few. Yet, a way to contain the syndrome of cost overruns is to understand the bases of ‘how and why’ they occur. Such knowledge will also help to develop pragmatic techniques for better overall management of oil and gas megaprojects. The aim of this paper is to explain the development of cost overruns in hydrocarbon megaprojects through the perspective of chaos theory. The underlying principles of chaos theory and its implications for cost overruns are examined and practical recommendations proposed. In addition, directions for future research in this fertile area provided.

Keywords: Chaos theory, oil and gas, cost overruns, megaprojects.

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Authors: Soon Fook Fong, Aldalalah, M. Osamah

Abstract:

The purpose of this study was to investigate effects of modality and redundancy principles on music theory learning among pupils of different anxiety levels. The lesson of music theory was developed in three different modes, audio and image (AI), text with image (TI) and audio with image and text (AIT). The independent variables were the three modes of courseware. The moderator variable was the anxiety level, while the dependent variable was the post test score. The study sample consisted of 405 third-grade pupils. Descriptive and inferential statistics were conducted to analyze the collected data. Analyses of covariance (ANCOVA) and Post hoc were carried out to examine the main effects as well as the interaction effects of the independent variables on the dependent variable. The findings of this study showed that medium anxiety pupils performed significantly better than low and high anxiety pupils in all the three treatment modes. The AI mode was found to help pupils with high anxiety significantly more than the TI and AIT modes.

Keywords: Modality, Redundancy, Music theory, Cognitivetheory of multimedia learning, Cognitive load theory, Anxiety.

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

Abstract:

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

Abstract:

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: Shimal Das, Dibyendu Ghoshal

Abstract:

Fractal based digital image compression is a specific technique in the field of color image. The method is best suited for irregular shape of image like snow bobs, clouds, flame of fire; tree leaves images, depending on the fact that parts of an image often resemble with other parts of the same image. This technique has drawn much attention in recent years because of very high compression ratio that can be achieved. Hybrid scheme incorporating fractal compression and speedup techniques have achieved high compression ratio compared to pure fractal compression. Fractal image compression is a lossy compression method in which selfsimilarity nature of an image is used. This technique provides high compression ratio, less encoding time and fart decoding process. In this paper, fractal compression with quad tree and DCT is proposed to compress the color image. The proposed hybrid schemes require four phases to compress the color image. First: the image is segmented and Discrete Cosine Transform is applied to each block of the segmented image. Second: the block values are scanned in a zigzag manner to prevent zero co-efficient. Third: the resulting image is partitioned as fractals by quadtree approach. Fourth: the image is compressed using Run length encoding technique.

Keywords: Fractal coding, Discrete Cosine Transform, Iterated Function System (IFS), Affine Transformation, Run length encoding.

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Authors: Rozilawati Binti Dollah, Masaki Aono

Abstract:

Classifying biomedical literature is a difficult and challenging task, especially when a large number of biomedical articles should be organized into a hierarchical structure. In this paper, we present an approach for classifying a collection of biomedical text abstracts downloaded from Medline database with the help of ontology alignment. To accomplish our goal, we construct two types of hierarchies, the OHSUMED disease hierarchy and the Medline abstract disease hierarchies from the OHSUMED dataset and the Medline abstracts, respectively. Then, we enrich the OHSUMED disease hierarchy before adapting it to ontology alignment process for finding probable concepts or categories. Subsequently, we compute the cosine similarity between the vector in probable concepts (in the “enriched" OHSUMED disease hierarchy) and the vector in Medline abstract disease hierarchies. Finally, we assign category to the new Medline abstracts based on the similarity score. The results obtained from the experiments show the performance of our proposed approach for hierarchical classification is slightly better than the performance of the multi-class flat classification.

Keywords: Biomedical literature, hierarchical text classification, ontology alignment, text mining.

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Authors: Liming Zhang

Abstract:

In this paper, a new adaptive Fourier decomposition (AFD) based time-frequency speech analysis approach is proposed. Given the fact that the fundamental frequency of speech signals often undergo fluctuation, the classical short-time Fourier transform (STFT) based spectrogram analysis suffers from the difficulty of window size selection. AFD is a newly developed signal decomposition theory. It is designed to deal with time-varying non-stationary signals. Its outstanding characteristic is to provide instantaneous frequency for each decomposed component, so the time-frequency analysis becomes easier. Experiments are conducted based on the sample sentence in TIMIT Acoustic-Phonetic Continuous Speech Corpus. The results show that the AFD based time-frequency distribution outperforms the STFT based one.

Keywords: Adaptive fourier decomposition, instantaneous frequency, speech analysis, time-frequency distribution.

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Authors: S. Avdakovic, A. Lukac, A. Nuhanovic, M. Music

Abstract:

Renewable energy systems are becoming a topic of great interest and investment in the world. In recent years wind power generation has experienced a very fast development in the whole world. For planning and successful implementations of good wind power plant projects, wind potential measurements are required. In these projects, of great importance is the effective choice of the micro location for wind potential measurements, installation of the measurement station with the appropriate measuring equipment, its maintenance and analysis of the gained data on wind potential characteristics. In this paper, a wavelet transform has been applied to analyze the wind speed data in the context of insight in the characteristics of the wind and the selection of suitable locations that could be the subject of a wind farm construction. This approach shows that it can be a useful tool in investigation of wind potential.

Keywords: Wind potential, Wind speed data, Wavelettransform.

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