Scholarly

Evaluation of Stent Performances using FEA considering a Realistic Balloon Expansion

Year: 2008 Volume: 2 Issue: 1 48 - 53 Pages

Abstract: A number of previous studies were rarely considered the effects of transient non-uniform balloon expansion on evaluation of the properties and behaviors of stents during stent expansion, nor did they determine parameters to maximize the performances driven by mechanical characteristics. Therefore, in order to fully understand the mechanical characteristics and behaviors of stent, it is necessary to consider a realistic modeling of transient non-uniform balloon-stent expansion. The aim of the study is to propose design parameters capable of improving the ability of vascular stent through a comparative study of seven commercial stents using finite element analyses of a realistic transient non-uniform balloon-stent expansion process. In this study, seven representative commercialized stents were evaluated by finite element (FE) analysis in terms of the criteria based on the itemized list of Food and Drug Administration (FDA) and European Standards (prEN). The results indicate that using stents composed of opened unit cells connected by bend-shaped link structures and controlling the geometrical and morphological features of the unit cell strut or the link structure at the distal ends of stent may improve mechanical characteristics of stent. This study provides a better method at the realistic transient non-uniform balloon-stent expansion by investigating the characteristics, behaviors, and parameters capable of improving the ability of vascular stent.

MTSSM - A Framework for Multi-Track Segmentation of Symbolic Music

Year: 2010 Volume: 4 Issue: 1 142 - 148 Pages

Abstract: Music segmentation is a key issue in music information retrieval (MIR) as it provides an insight into the internal structure of a composition. Structural information about a composition can improve several tasks related to MIR such as searching and browsing large music collections, visualizing musical structure, lyric alignment, and music summarization. The authors of this paper present the MTSSM framework, a twolayer framework for the multi-track segmentation of symbolic music. The strength of this framework lies in the combination of existing methods for local track segmentation and the application of global structure information spanning via multiple tracks. The first layer of the MTSSM uses various string matching techniques to detect the best candidate segmentations for each track of a multi-track composition independently. The second layer combines all single track results and determines the best segmentation for each track in respect to the global structure of the composition.

Fast Extraction of Edge Histogram in DCT Domain based on MPEG7

Year: 2007 Volume: 1 Issue: 9 1380 - 1383 Pages

Abstract: In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Keywords:
DCT
Descriptor
EHD
MPEG7.

An Improved Model for Prediction of the Effective Thermal Conductivity of Nanofluids

Year: 2011 Volume: 5 Issue: 10 2061 - 2064 Pages

Abstract: Thermal conductivity is an important characteristic of a nanofluid in laminar flow heat transfer. This paper presents an improved model for the prediction of the effective thermal conductivity of nanofluids based on dimensionless groups. The model expresses the thermal conductivity of a nanofluid as a function of the thermal conductivity of the solid and liquid, their volume fractions and particle size. The proposed model includes a parameter which accounts for the interfacial shell, brownian motion, and aggregation of particle. The validation of the model is verified by applying the results obtained by the experiments of Tio2-water and Al2o3-water nanofluids.

Measuring Pressure Wave Velocity in a Hydraulic System

Year: 2009 Volume: 3 Issue: 1 109 - 115 Pages

Abstract: Pressure wave velocity in a hydraulic system was determined using piezo pressure sensors without removing fluid from the system. The measurements were carried out in a low pressure range (0.2 – 6 bar) and the results were compared with the results of other studies. This method is not as accurate as measurement with separate measurement equipment, but the fluid is in the actual machine the whole time and the effect of air is taken into consideration if air is present in the system. The amount of air is estimated by calculations and comparisons between other studies. This measurement equipment can also be installed in an existing machine and it can be programmed so that it measures in real time. Thus, it could be used e.g. to control dampers.

Creation of a New Software used for Palletizing Process

Year: 2012 Volume: 6 Issue: 5 988 - 995 Pages

Abstract: This article gives a short preview of the new software created especially for palletizing process in automated production systems. Each chapter of this article is about problem solving in development of modules in Java programming language. First part describes structure of the software, its modules and data flow between them. Second part describes all deployment methods, which are implemented in the software. Next chapter is about twodimensional editor created for manipulation with objects in each layer of the load and gives calculations for collision control. Module of virtual reality used for three-dimensional preview and creation of the load is described in the fifth chapter. The last part of this article describes communication and data flow between control system of the robot, vision system and software.

Effects of Catalyst Tubes Characteristics on a Steam Reforming Process in Ammonia

Year: 2010 Volume: 4 Issue: 11 723 - 728 Pages

Authors:
M.Boumaza

Abstract: The tubes in an Ammonia primary reformer furnace operate close to the limits of materials technology in terms of the stress induced as a result of very high temperatures, combined with large differential pressures across the tube wall. Operation at tube wall temperatures significantly above design can result in a rapid increase in the number of tube failures, since tube life is very sensitive to the absolute operating temperature of the tube. Clearly it is important to measure tube wall temperatures accurately in order to prevent premature tube failure by overheating.. In the present study, the catalyst tubes in an Ammonia primary reformer has been modeled taking into consideration heat, mass and momentum transfer as well as reformer characteristics.. The investigations concern the effects of tube characteristics and superficial tube wall temperatures on of the percentage of heat flux, unconverted methane and production of Hydrogen for various values of steam to carbon ratios. The results show the impact of catalyst tubes length and diameters on the performance of operating parameters in ammonia primary reformers.

Fatigue Properties and Strength Degradation of Carbon Fibber Reinforced Composites

Year: 2013 Volume: 7 Issue: 1 116 - 119 Pages

Abstract: A two-parameter fatigue model explicitly accounting for the cyclic as well as the mean stress was used to fit static and fatigue data available in literature concerning carbon fiber reinforced composite laminates subjected tension-tension fatigue. The model confirms the strength–life equal rank assumption and predicts reasonably the probability of failure under cyclic loading. The model parameters were found by best fitting procedures and required a minimum of experimental tests.

Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process

Year: 2011 Volume: 5 Issue: 2 465 - 468 Pages

Abstract: In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Cross Layer Optimization for Fairness Balancing Based on Adaptively Weighted Utility Functions in OFDMA Systems

Year: 2007 Volume: 1 Issue: 6 902 - 907 Pages

Abstract: Cross layer optimization based on utility functions has been recently studied extensively, meanwhile, numerous types of utility functions have been examined in the corresponding literature. However, a major drawback is that most utility functions take a fixed mathematical form or are based on simple combining, which can not fully exploit available information. In this paper, we formulate a framework of cross layer optimization based on Adaptively Weighted Utility Functions (AWUF) for fairness balancing in OFDMA networks. Under this framework, a two-step allocation algorithm is provided as a sub-optimal solution, whose control parameters can be updated in real-time to accommodate instantaneous QoS constrains. The simulation results show that the proposed algorithm achieves high throughput while balancing the fairness among multiple users.

Keywords:
OFDMA
Fairness
AWUF
QoS.

Dimensionality Reduction of PSSM Matrix and its Influence on Secondary Structure and Relative Solvent Accessibility Predictions

Year: 2009 Volume: 3 Issue: 10 855 - 861 Pages

Authors:
Rafał Adamczak

Abstract: State-of-the-art methods for secondary structure (Porter, Psi-PRED, SAM-T99sec, Sable) and solvent accessibility (Sable, ACCpro) predictions use evolutionary profiles represented by the position specific scoring matrix (PSSM). It has been demonstrated that evolutionary profiles are the most important features in the feature space for these predictions. Unfortunately applying PSSM matrix leads to high dimensional feature spaces that may create problems with parameter optimization and generalization. Several recently published suggested that applying feature extraction for the PSSM matrix may result in improvements in secondary structure predictions. However, none of the top performing methods considered here utilizes dimensionality reduction to improve generalization. In the present study, we used simple and fast methods for features selection (t-statistics, information gain) that allow us to decrease the dimensionality of PSSM matrix by 75% and improve generalization in the case of secondary structure prediction compared to the Sable server.

On Optimum Stratification

Year: 2014 Volume: 8 Issue: 3 494 - 498 Pages

Abstract: In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique.

Comparative Analysis of Vibration between Laminated Composite Plates with and without Holes under Compressive Loads

Year: 2013 Volume: 7 Issue: 6 502 - 506 Pages

Abstract: In this study, a vibration analysis was carried out of symmetric angle-ply laminated composite plates with and without square hole when subjected to compressive loads, numerically. A buckling analysis is also performed to determine the buckling load of laminated plates. For each fibre orientation, the compression load is taken equal to 50% of the corresponding buckling load. In the analysis, finite element method (FEM) was applied to perform parametric studies, the effects of degree of orthotropy and stacking sequence upon the fundamental frequencies and buckling loads are discussed. The results show that the presence of a constant compressive load tends to reduce uniformly the natural frequencies for materials which have a low degree of orthotropy. However, this reduction becomes non-uniform for materials with a higher degree of orthotropy.

A General Regression Test Selection Technique

Year: 2010 Volume: 4 Issue: 2 297 - 301 Pages

Abstract: This paper presents a new methodology to select test cases from regression test suites. The selection strategy is based on analyzing the dynamic behavior of the applications that written in any programming language. Methods based on dynamic analysis are more safe and efficient. We design a technique that combine the code based technique and model based technique, to allow comparing the object oriented of an application that written in any programming language. We have developed a prototype tool that detect changes and select test cases from test suite.

How to Integrate Sustainability in Technological Degrees: Robotics at UPC

Year: 2014 Volume: 8 Issue: 9 2939 - 2944 Pages

Abstract: Embedding Sustainability in technological curricula has become a crucial factor for educating engineers with competences in sustainability. The Technical University of Catalonia UPC, in 2008, designed the Sustainable Technology Excellence Program STEP 2015 in order to assure a successful Sustainability Embedding. This Program takes advantage of the opportunity that the redesign of all Bachelor and Master Degrees in Spain by 2010 under the European Higher Education Area framework offered. The STEP program goals are: to design compulsory courses in each degree; to develop the conceptual base and identify reference models in sustainability for all specialties at UPC; to create an internal interdisciplinary network of faculty from all the schools; to initiate new transdisciplinary research activities in technology-sustainability-education; to spread the know/how attained; to achieve international scientific excellence in technology-sustainability-education and to graduate the first engineers/architects of the new EHEA bachelors with sustainability as a generic competence. Specifically, in this paper authors explain their experience in leading the STEP program, and two examples are presented: Industrial Robotics subject and the curriculum for the School of Architecture.

Model Discovery and Validation for the Qsar Problem using Association Rule Mining

Year: 2007 Volume: 1 Issue: 11 560 - 564 Pages

Abstract: There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (QSAR) problem. These approaches are based either on statistical methods or on predictive data mining. Among the statistical methods, one should consider regression analysis, pattern recognition (such as cluster analysis, factor analysis and principal components analysis) or partial least squares. Predictive data mining techniques use either neural networks, or genetic programming, or neuro-fuzzy knowledge. These approaches have a low explanatory capability or non at all. This paper attempts to establish a new approach in solving QSAR problems using descriptive data mining. This way, the relationship between the chemical properties and the activity of a substance would be comprehensibly modeled.

Keywords:
association rules
classification
data mining
Quantitative Structure - Activity Relationship.

ISC–Intelligent Subspace Clustering, A Density Based Clustering Approach for High Dimensional Dataset

Year: 2009 Volume: 3 Issue: 7 1835 - 1839 Pages

Abstract: Many real-world data sets consist of a very high dimensional feature space. Most clustering techniques use the distance or similarity between objects as a measure to build clusters. But in high dimensional spaces, distances between points become relatively uniform. In such cases, density based approaches may give better results. Subspace Clustering algorithms automatically identify lower dimensional subspaces of the higher dimensional feature space in which clusters exist. In this paper, we propose a new clustering algorithm, ISC – Intelligent Subspace Clustering, which tries to overcome three major limitations of the existing state-of-art techniques. ISC determines the input parameter such as є – distance at various levels of Subspace Clustering which helps in finding meaningful clusters. The uniform parameters approach is not suitable for different kind of databases. ISC implements dynamic and adaptive determination of Meaningful clustering parameters based on hierarchical filtering approach. Third and most important feature of ISC is the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.

Modeling and Simulation of a Serial Production Line with Constant Work-In-Process

Year: 2009 Volume: 3 Issue: 5 629 - 637 Pages

Authors:
Mehmet Savsar

Abstract: This paper presents a model for an unreliable production line, which is operated according to demand with constant work-in-process (CONWIP). A simulation model is developed based on the discrete model and several case problems are analyzed using the model. The model is utilized to optimize storage space capacities at intermediate stages and the number of kanbans at the last stage, which is used to trigger the production at the first stage. Furthermore, effects of several line parameters on production rate are analyzed using design of experiments.

Identification of PIP Aquaporin Genes from Wheat

Year: 2011 Volume: 5 Issue: 11 810 - 814 Pages

Abstract: There is strong evidence that water channel proteins 'aquaporins (AQPs)' are central components in plant-water relations as well as a number of other physiological parameters. We had previously reported the isolation of 24 plasma membrane intrinsic protein (PIP) type AQPs. However, the gene numbers in rice and the polyploid nature of bread wheat indicated a high probability of further genes in the latter. The present work focused on identification of further AQP isoforms in bread wheat. With the use of altered primer design, we identified five genes homologous, designated PIP1;5b, PIP2;9b, TaPIP2;2, TaPIP2;2a, TaPIP2;2b. Sequence alignments indicate PIP1;5b, PIP2;9b are likely to be homeologues of two previously reported genes while the other three are new genes and could be homeologs of each other. The results indicate further AQP diversity in wheat and the sequence data will enable physical mapping of these genes to identify their genomes as well as genetic to determine their association with any quantitative trait loci (QTLs) associated with plant-water relation such as salinity or drought tolerance.

Security Engine Management of Router based on Security Policy

Year: 2007 Volume: 1 Issue: 10 1531 - 1534 Pages

Abstract: Security management has changed from the management of security equipments and useful interface to manager. It analyzes the whole security conditions of network and preserves the network services from attacks. Secure router technology has security functions, such as intrusion detection, IPsec(IP Security) and access control, are applied to legacy router for secure networking. It controls an unauthorized router access and detects an illegal network intrusion. This paper relates to a security engine management of router based on a security policy, which is the definition of security function against a network intrusion. This paper explains the security policy and designs the structure of security engine management framework.

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