Search results for: 3D shape decomposition representation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1634

Search results for: 3D shape decomposition representation

1394 Wear and Friction Analysis of Sintered Metal Powder Self Lubricating Bush Bearing

Authors: J. K. Khare, Abhay Kumar Sharma, Ajay Tiwari, Amol A. Talankar

Abstract:

Powder metallurgy (P/M) is the only economic way to produce porous parts/products. P/M can produce near net shape parts hence reduces wastage of raw material and energy, avoids various machining operations. The most vital use of P/M is in production of metallic filters and self lubricating bush bearings and siding surfaces. The porosity of the part can be controlled by varying compaction pressure, sintering temperature and composition of metal powder mix. The present work is aimed for experimental analysis of friction and wear properties of self lubricating copper and tin bush bearing. Experimental results confirm that wear rate of sintered component is lesser for components having 10% tin by weight percentage. Wear rate increases for high tin percentage (experimented for 20% tin and 30% tin) at same sintering temperature. Experimental results also confirms that wear rate of sintered component is also dependent on sintering temperature, soaking period, composition of the preform, compacting pressure, powder particle shape and size. Interfacial friction between die and punch, between inter powder particles, between die face and powder particle depends on compaction pressure, powder particle size and shape, size and shape of component which decides size & shape of die & punch, material of die & punch and material of powder particles.

Keywords: Interfacial friction, porous bronze bearing, sintering temperature, wear rate.

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1393 Fermentative Production and Characterization of Carboxymethyl Bacterial Cellulose Using Date Syrup

Authors: Marzieh Moosavi-Nasab, Ali R. Yousefi, Hamed Askari, Maryam Bakhtiyari

Abstract:

In this study, static batch fermentation was used for bacterial cellulose production in date syrup solution (Bx. 10%) at 28°C using Gluconacetobacter. xylinus (PTCC 1734). The physicochemical properties of standard Sigma CMC and the produced carboxymethyl bacterial cellulose (CMBC) were studied using FT-IR spectroscopy, X-ray diffractometry (XRD) and Scanning Electron Microscopy (SEM). According to the FT-IR spectra the bands at 1664 and 1431 cm-1 indicate that carboxylic acid groups and carboxylate groups exist on the surface. The SEM imaging of CMBC and CMC carried out in magnification of 1K. Comparing the SEM imaging obviously showed that the ribbon shape in CMC remained but the length of ribbons became shorter while that shape changed to flake shape for CMBC. Determination of the area under XRD patterns demonstrated that the crystallinity amount of CMC was more than that for CMBC (51.08% and 81.84% for CMBC and CMC, respectively).

Keywords: Carboxymethyl bacterial cellulose, Fourier Transform Infrared spectroscopy, Scanning Electron Microscopy, X-ray diffractometry.

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1392 Hit-or-Miss Transform as a Tool for Similar Shape Detection

Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

Abstract:

This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: Hit-or/and-Miss Operator/Transform, HMT, binary morphological operation, shape detection, binary images processing.

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1391 Erosion in Abrasive Jet Nozzles: A Comprehensive Study

Authors: D. V. Sreekanth, M. Sreenivasa Rao

Abstract:

Abrasive jet machining is one of the promising non-traditional machining processes which uses mechanical energy (pressure and velocity) for machining various materials. The process parameters that influence the metal removal rate are kerfs, surface finish, depth of cut, air pressure, and distance between nozzle and work piece, nozzle diameter, abrasive type, abrasive shape, and mass flow rate of abrasive particles. The abrasive particles coming out with high pressure not only hits work surface but also passes through the nozzle resulting in erosion. This paper focuses mainly on the effect of different parameters on the erosion of nozzle in Abrasive jet machining. Three different types of nozzles made of sapphire, tungsten carbide, and high carbon high chromium steel (HCHCS) are used for machining glass and the erosion of these nozzles are calculated. The results are shown in tabular form and graphical representation.

Keywords: AJM, nozzle, sapphire, tungsten carbide, chrome steel.

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1390 CAD Model of Cole Cole Representation for Analyzing Performance of Microstrip Moisture Sensing Applications

Authors: Settapong Malisuwan, Jesada Sivaraks, Wasan Jaiwong, Veerapat Sanpanich

Abstract:

In the past decade, the development of microstrip sensor application has evolved tremendously. Although cut and trial method was adopted to develop microstrip sensing applications in the past, Computer-Aided-Design (CAD) is a more effective as it ensures less time is consumed and cost saving is achieved in developing microstrip sensing applications. Therefore microstrip sensing applications has gained popularity as an effective tool adopted in continuous sensing of moisture content particularly in products that is administered mainly by liquid content. In this research, the Cole-Cole representation of reactive relaxation is applied to assess the performance of the microstrip sensor devices. The microstrip sensor application is an effective tool suitable for sensing the moisture content of dielectric material. Analogous to dielectric relaxation consideration of Cole-Cole diagrams as applied to dielectric materials, a “reactive relaxation concept” concept is introduced to represent the frequency-dependent and moisture content characteristics of microstrip sensor devices.

Keywords: Microstrip, Sensor, Cole-Cole Representation, Moisture content.

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1389 Video Shot Detection and Key Frame Extraction Using Faber Shauder DWT and SVD

Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

Abstract:

Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: Key Frame Extraction, Shot detection, FSDWT, Singular Value Decomposition.

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1388 Global Security Using Human Face Understanding under Vision Ubiquitous Architecture System

Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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1387 Floating-Point Scaling for BSS Gain Control

Authors: Abdelmalek Fermas, Adel Belouchrani, Otmane Ait Mohamed

Abstract:

In Blind Source Separation (BSS) processing, taking advantage of scaling factor indetermination and based on the floatingpoint representation, we propose a scaling technique applied to the separation matrix, to avoid the saturation or the weakness in the recovered source signals. This technique performs an Automatic Gain Control (AGC) in an on-line BSS environment. We demonstrate the effectiveness of this technique by using the implementation of a division free BSS algorithm with two input, two output. This technique is computationally cheaper and efficient for a hardware implementation.

Keywords: Automatic Gain Control, Blind Source Separation, Floating-Point Representation, FPGA Implementation.

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1386 An Ontology for Knowledge Representation and Applications

Authors: Nhon Do

Abstract:

Ontology is a terminology which is used in artificial intelligence with different meanings. Ontology researching has an important role in computer science and practical applications, especially distributed knowledge systems. In this paper we present an ontology which is called Computational Object Knowledge Base Ontology. It has been used in designing some knowledge base systems for solving problems such as the system that supports studying knowledge and solving analytic geometry problems, the program for studying and solving problems in Plane Geometry, the knowledge system in linear algebra.

Keywords: Artificial intelligence, knowledge representation, knowledge base system, ontology.

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1385 A Robust Redundant Residue Representation in Residue Number System with Moduli Set(rn-2,rn-1,rn)

Authors: Hossein Khademolhosseini, Mehdi Hosseinzadeh

Abstract:

The residue number system (RNS), due to its properties, is used in applications in which high performance computation is needed. The carry free nature, which makes the arithmetic, carry bounded as well as the paralleling facility is the reason of its capability of high speed rendering. Since carry is not propagated between the moduli in this system, the performance is only restricted by the speed of the operations in each modulus. In this paper a novel method of number representation by use of redundancy is suggested in which {rn- 2,rn-1,rn} is the reference moduli set where r=2k+1 and k =1, 2,3,.. This method achieves fast computations and conversions and makes the circuits of them much simpler.

Keywords: Binary to RNS converter, Carry save adder, Computer arithmetic, Residue number system.

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1384 Study on Performance of Wigner Ville Distribution for Linear FM and Transient Signal Analysis

Authors: Azeemsha Thacham Poyil, Nasimudeen KM

Abstract:

This research paper presents some methods to assess the performance of Wigner Ville Distribution for Time-Frequency representation of non-stationary signals, in comparison with the other representations like STFT, Spectrogram etc. The simultaneous timefrequency resolution of WVD is one of the important properties which makes it preferable for analysis and detection of linear FM and transient signals. There are two algorithms proposed here to assess the resolution and to compare the performance of signal detection. First method is based on the measurement of area under timefrequency plot; in case of a linear FM signal analysis. A second method is based on the instantaneous power calculation and is used in case of transient, non-stationary signals. The implementation is explained briefly for both methods with suitable diagrams. The accuracy of the measurements is validated to show the better performance of WVD representation in comparison with STFT and Spectrograms.

Keywords: WVD: Wigner Ville Distribution, STFT: Short Time Fourier Transform, FT: Fourier Transform, TFR: Time-Frequency Representation, FM: Frequency Modulation, LFM Signal: Linear FM Signal, JTFA: Joint time frequency analysis.

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1383 Mathematical Models of Flow Shop and Job Shop Scheduling Problems

Authors: Miloš Šeda

Abstract:

In this paper, mathematical models for permutation flow shop scheduling and job shop scheduling problems are proposed. The first problem is based on a mixed integer programming model. As the problem is NP-complete, this model can only be used for smaller instances where an optimal solution can be computed. For large instances, another model is proposed which is suitable for solving the problem by stochastic heuristic methods. For the job shop scheduling problem, a mathematical model and its main representation schemes are presented.

Keywords: Flow shop, job shop, mixed integer model, representation scheme.

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1382 1-D Modeling of Hydrate Decomposition in Porous Media

Authors: F. Esmaeilzadeh, M. E. Zeighami, J. Fathi

Abstract:

This paper describes a one-dimensional numerical model for natural gas production from the dissociation of methane hydrate in hydrate-capped gas reservoir under depressurization and thermal stimulation. Some of the hydrate reservoirs discovered are overlying a free-gas layer, known as hydrate-capped gas reservoirs. These reservoirs are thought to be easiest and probably the first type of hydrate reservoirs to be produced. The mathematical equations that can be described this type of reservoir include mass balance, heat balance and kinetics of hydrate decomposition. These non-linear partial differential equations are solved using finite-difference fully implicit scheme. In the model, the effect of convection and conduction heat transfer, variation change of formation porosity, the effect of using different equations of state such as PR and ER and steam or hot water injection are considered. In addition distributions of pressure, temperature, saturation of gas, hydrate and water in the reservoir are evaluated. It is shown that the gas production rate is a sensitive function of well pressure.

Keywords: Hydrate reservoir, numerical modeling, depressurization, thermal stimulation, gas generation.

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1381 Classification of Non Stationary Signals Using Ben Wavelet and Artificial Neural Networks

Authors: Mohammed Benbrahim, Khalid Benjelloun, Aomar Ibenbrahim, Adil Daoudi

Abstract:

The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Keywords: Seismic signals, Ben Wavelet, Dimensionality reduction, Artificial neural networks, Classification.

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1380 Speech Intelligibility Improvement Using Variable Level Decomposition DWT

Authors: Samba Raju, Chiluveru, Manoj Tripathy

Abstract:

Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods

Keywords: Discrete Wavelet Transform, speech intelligibility, STOI, standard deviation.

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1379 Model for Knowledge Representation using Sample Problems and Designing a Program for Automatically Solving Algebraic Problems

Authors: Nhon Do, Hien Nguyen

Abstract:

Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: educational software, artificial intelligence, knowledge base system, knowledge representation.

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1378 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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1377 A Robust and Efficient Segmentation Method Applied for Cardiac Left Ventricle with Abnormal Shapes

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

Abstract:

Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is widely used for LV segmentation, but it suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is improved to achieve a fast and efficient LV segmentation. First, a robust and efficient detection based on Hough forest localizes cardiac feature points. Such feature points are used to predict the initial fitting of the LV shape model. Second, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. With the robust initialization, ASM is able to achieve more accurate segmentation. The performance of the proposed method is evaluated on a dataset of 810 cardiac ultrasound images that are mostly abnormal shapes. This proposed method is compared with several combinations of ASM and existing initialization methods. Our experiment results demonstrate that accuracy of the proposed method for feature point detection for initialization was 40% higher than the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops and thus speeds up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: Hough forest, active shape model, segmentation, cardiac left ventricle.

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1376 Challenging Hegemonic Masculinity in Nigerian Hip Hop: An Evaluation of Gender Representation in Falz the Bahd Guy’s Moral Instruction Album

Authors: Adelaja O. Oriade

Abstract:

The Nigerian hip-hop music genre, like the African American scene where it was adopted from, is riddled with musical lyrics that amplify and normalize hypermasculinity, homophobia, sexism, and objectification of women. Several factors are responsible for this anomaly; however, the greatest factor is the urge of hip-hop musicians to achieve the commercial success that is dependent on selling records and appealing to the established societal accepted norm for hip-hop music. Consequently, this paper presents a counter-narrative of this gender representation within the Nigerian hip-hop industry. This study analyzed the musical lyrics of the ‘Hypocrisy’ track on the 2019 album of famous Nigerian rapper, Falz the Bahd Guy; and argued that Falz in this album challenged the predominant ideas of hegemonic masculinity by singing in favor of LGBT people and women. Also, based on the success of this album, this paper argues that a hip-hop album can achieve commercial success without aligning with predominant hip-hop parameters of gender representation. The study recommends that future studies should evaluate the reactions of Nigerians to these gender presentations by Falz the Bahd guy.

Keywords: Hegemonic Masculinity, hypermasculinity, LGBT, misogyny, sexism.

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1375 Parametric Transition as a Spiral Curve and Its Application in Spur Gear Tooth with FEA

Authors: S. H. Yahaya, J. M. Ali, T.A. Abdullah

Abstract:

The exploration of this paper will focus on the Cshaped transition curve. This curve is designed by using the concept of circle to circle where one circle lies inside other. The degree of smoothness employed is curvature continuity. The function used in designing the C-curve is Bézier-like cubic function. This function has a low degree, flexible for the interactive design of curves and surfaces and has a shape parameter. The shape parameter is used to control the C-shape curve. Once the C-shaped curve design is completed, this curve will be applied to design spur gear tooth. After the tooth design procedure is finished, the design will be analyzed by using Finite Element Analysis (FEA). This analysis is used to find out the applicability of the tooth design and the gear material that chosen. In this research, Cast Iron 4.5 % Carbon, ASTM A-48 is selected as a gear material.

Keywords: Bézier-like cubic function, Curvature continuity, Cshapedtransition curve, Spur gear tooth.

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1374 Image Retrieval Using Fused Features

Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

Abstract:

The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.

Keywords: Color Histogram, Haar Wavelet Transform, Fuzzy C-means, Co-occurrence matrix; Similarity measure.

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1373 A Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor

Authors: Wenji Zhu, Yigang He

Abstract:

This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.

Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.

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1372 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

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1371 Orthogonal Polynomial Density Estimates: Alternative Representation and Degree Selection

Authors: Serge B. Provost, Min Jiang

Abstract:

The density estimates considered in this paper comprise a base density and an adjustment component consisting of a linear combination of orthogonal polynomials. It is shown that, in the context of density approximation, the coefficients of the linear combination can be determined either from a moment-matching technique or a weighted least-squares approach. A kernel representation of the corresponding density estimates is obtained. Additionally, two refinements of the Kronmal-Tarter stopping criterion are proposed for determining the degree of the polynomial adjustment. By way of illustration, the density estimation methodology advocated herein is applied to two data sets.

Keywords: kernel density estimation, orthogonal polynomials, moment-based methodologies, density approximation.

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1370 Restrictedly-Regular Map Representation of n-Dimensional Abstract Polytopes

Authors: Antonio Breda d’Azevedo

Abstract:

Regularity has often been present in the form of regular polyhedra or tessellations; classical examples are the nine regular polyhedra consisting of the five Platonic solids (regular convex polyhedra) and the four Kleper-Poinsot polyhedra. These polytopes can be seen as regular maps. Maps are cellular embeddings of graphs (with possibly multiple edges, loops or dangling edges) on compact connected (closed) surfaces with or without boundary. The n-dimensional abstract polytopes, particularly the regular ones, have gained popularity over recent years. The main focus of research has been their symmetries and regularity. Planification of polyhedra helps its spatial construction, yet it destroys its symmetries. To our knowledge there is no “planification” for n-dimensional polytopes. However we show that it is possible to make a “surfacification” of the n-dimensional polytope, that is, it is possible to construct a restrictedly-marked map representation of the abstract polytope on some surface that describes its combinatorial structures as well as all of its symmetries. We also show that there are infinitely many ways to do this; yet there is one that is more natural that describes reflections on the sides ((n−1)-faces) of n-simplices with reflections on the sides of n-polygons. We illustrate this construction with the 4-tetrahedron (a regular 4-polytope with automorphism group of size 120) and the 4-cube (a regular 4-polytope with automorphism group of size 384).

Keywords: Maps, representation, polytopes.

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1369 A Fully Parallel Reverse Converter

Authors: Mehdi Hosseinzadeh, Amir Sabbagh Molahosseini, Keivan Navi

Abstract:

The residue number system (RNS) is popular in high performance computation applications because of its carry-free nature. The challenges of RNS systems design lie in the moduli set selection and in the reverse conversion from residue representation to weighted representation. In this paper, we proposed a fully parallel reverse conversion algorithm for the moduli set {rn - 2, rn - 1, rn}, based on simple mathematical relationships. Also an efficient hardware realization of this algorithm is presented. Our proposed converter is very faster and results to hardware savings, compared to the other reverse converters.

Keywords: Reverse converter, residue to weighted converter, residue number system, multiple-valued logic, computer arithmetic.

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1368 Granulation using Clustering and Rough Set Theory and its Tree Representation

Authors: Girish Kumar Singh, Sonajharia Minz

Abstract:

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

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

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1367 Improvement of Load Carrying Capacity of an RCC T-Beam Bridge Longitudinal Girder by Replacing Steel Bars with SMA Bars

Authors: N. K. Paul, S. Saha

Abstract:

An innovative three dimensional finite element model has beed developed and tested under two point loading system to examine the structural behavior of the longitudinal reinforced concrete Tee-beam bridge girder, reinforcing with steel and shape memory alloy bars respectively. 25% of steel bars are replaced with superelastic Shape Memory Alloy bars in this study. Finite element analysis is performed using ANSYS 11.0 program. Experimentally a model of steel reinforced girder has been casted and its load deflection responses are checked with ANSYS analysis. A comparison of load carrying capacity for the model between steel RC girder and the girder combined reinforcement with SMA and steel are also performed.

Keywords: Shape memory alloy, bridge girder, ANSYS, load-deflection.

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1366 Conversion in Chemical Reactors using Hollow Cylindrical Catalyst Pellet

Authors: Mohammad Asif

Abstract:

Heterogeneous catalysis is vital for a number of chemical, refinery and pollution control processes. The use of catalyst pellets of hollow cylindrical shape provide several distinct advantages over other common shapes, and can therefore help to enhance conversion levels in reactors. A better utilization of the catalytic material is probably most notable of these features due to the absence of the pellet core, which helps to significantly lower the effect of the internal transport resistance. This is reflected in the enhancement of the effectiveness factor. For the case of the first order irreversible kinetics, a substantial increase in the effectiveness factor can be obtained by varying shape parameters. Important shape parameters of a finite hollow cylinder are the ratio of the inside to the outside radii (κ) and the height to the diameter ratio (γ). A high value of κ the generally helps to enhance the effectiveness factor. On the other hand, lower values of the effectiveness factors are obtained when the dimension of the height and the diameter are comparable. Thus, the departure of parameter γ from the unity favors higher effectiveness factor. Since a higher effectiveness factor is a measure of a greater utilization of the catalytic material, higher conversion levels can be achieved using the hollow cylindrical pellets possessing optimized shape parameters.

Keywords: Finite hollow cylinder, Catalyst pellet, Effectiveness factor, Thiele Modulus, Conversion

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1365 The Growth of the Watermelons with Geometric Shapes and Comparing Retention between Cubic and Hexagonal Forms

Authors: M. Malekyarand, M. Shariati Ghalehno, A. Mokhber Dezfuli, H. Saebi Monfared, S. R. Ghoraishi K.

Abstract:

Shape and form of the watermelon fruits are important factors to save spaces and reducing damage during storing of the fruits. In order to save spaces and prevent fruit damage in watermelon the following experiment was carried out in the farm. The fruits were boxed when they were approximately one cm less than the box diameter. The cubic, hexagonal forms were compared in this research. To do this, different boxes were designed with different holes on the sides to holes the watermelons fruits for shaping. The shapes of the boxes were hexagonal and cubic. The boxes holes sizes were the same with 10mm diameter each. Each side of the boxes had different holes including: without holes to 75 holes. The result showed that the best shape for watermelon storing to save space and prevent fruit damage was hexagonal form. The percentages of the fruit damage were 33 to 80 respectively.

Keywords: Cubic form, fruit damage, hexagonal, watermelon shape.

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