Search results for: Operational matrix
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1455

Search results for: Operational matrix

1005 The Association of Matrix Metalloproteinase-3 Gene -1612 5A/6A Polymorphism with Susceptibility to Coronary Artery Stenosis in an Iranian Population

Authors: M. Seifi, S. Fallah, M. Firoozrai

Abstract:

Matrix metalloproteinase-3 (MMP3) is key member of the MMP family, and is known to be present in coronary atherosclerotic. Several studies have demonstrated that MMP-3 5A/6A polymorphism modify each transcriptional activity in allele specific manner. We hypothesized that this polymorphism may play a role as risk factor for development of coronary stenosis. The aim of our study was to estimate MMP-3 (5A/6A) gene polymorphism on interindividual variability in risk for coronary stenosis in an Iranian population.DNA was extracted from white blood cells and genotypes were obtained from coronary stenosis cases (n=95) and controls (n=100) by PCR (polymerase chain reaction) and restriction fragment length polymorphism techniques. Significant differences between cases and controls were observed for MMP3 genotype frequencies (X2=199.305, p< 0.001); the 6A allele was less frequently seen in the control group, compared to the disease group (85.79 vs. 78%, 6A/6A+5A/6A vs. 5A/5A, P≤0.001). These data imply the involvement of -1612 5A/6A polymorphism in coronary stenosis, and suggest that probably the 6A/6A MMP-3 genotype is a genetic susceptibility factor for coronary stenosis.

Keywords: Coronary artery stenosis, matrixmetalloproteinase-3, polymorphism, polymerase chain reaction.

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1004 Mechanical Characterization of Mango Peel Flour and Biopolypropylene Composites Compatibilized with PP-g-IA

Authors: J. Gomez-Caturla, L. Quiles-Carrillo, J. Ivorra-Martinez, D. Garcia-Garcia, R. Balart

Abstract:

The present work reports on the development of wood plastic composites based on biopolypropylene (BioPP) and mango peel flour (MPF) by extrusion and injection molding processes. PP-g-IA and dicumyl peroxide (DCP) have been used as a compatibilizer and as a free radical initiator for reactive extrusion, respectively. Mechanical and morphological properties have been characterized in order to study the compatibility of the blends. The obtained results showed that DCP and PP-g-IA improved the stiffness of BioPP in terms of elastic modulus. Moreover, they positively increased the tensile strength and elongation at break of the blends in comparison with the sample that only had BioPP and MPF on its composition, improving the affinity between both compounds. DCP and PP-g-IA even seem to have certain synergy, which was corroborated through Field Emission Scanning Electron Microscopy (FESEM) analysis. Images showed that the MPF particles had greater adhesion to the polymer matrix when PP-g-IA and DCP were added. This effect was more intense when both elements were added, observing an almost inexistent gap between MPF particles and the BioPP matrix.

Keywords: Biopolypropylene, compatibilization, mango peel flour, wood plastic composite.

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1003 N-Grams: A Tool for Repairing Word Order Errors in Ill-formed Texts

Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou, Konstantinos Mamouras

Abstract:

This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. A possible way for reordering the words is to use all the permutations. The problem is that for a sentence with length N words the number of all permutations is N!. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The confusion matrix technique has been designed in order to reduce the search space among permuted sentences. The limitation of search space is succeeded using the statistical inference of N-grams. The results of this technique are very interesting and prove that the number of permuted sentences can be reduced by 98,16%. For experimental purposes a test set of TOEFL sentences was used and the results show that more than 95% can be repaired using the proposed method.

Keywords: Permutations filtering, Statistical language model N-grams, Word order errors, TOEFL

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1002 Optimal Transmission Network Usage and Loss Allocation Using Matrices Methodology and Cooperative Game Theory

Authors: Baseem Khan, Ganga Agnihotri

Abstract:

Restructuring of Electricity supply industry introduced many issues such as transmission pricing, transmission loss allocation and congestion management. Many methodologies and algorithms were proposed for addressing these issues. In this paper a power flow tracing based method is proposed which involves Matrices methodology for the transmission usage and loss allocation for generators and demands. This method provides loss allocation in a direct way because all the computation is previously done for usage allocation. The proposed method is simple and easy to implement in a large power system. Further it is less computational because it requires matrix inversion only a single time. After usage and loss allocation cooperative game theory is applied to results for finding efficient economic signals. Nucleolus and Shapely value approach is used for optimal allocation of results. Results are shown for the IEEE 6 bus system and IEEE 14 bus system.

Keywords: Modified Kirchhoff Matrix, Power flow tracing, Transmission Pricing, Transmission Loss Allocation.

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1001 Sediment Fixation of Arsenic in the Ash Lagoon of a Coal-Fired Power Plant, Philippines

Authors: Joselito P. Duyanen, Aries Milay

Abstract:

Arsenic in the sediments of the ash lagoons of the coal-fired power plant in Pagbilao, Quezon Province in the Philippines was sequentially extracted to determine its potential for leaching to the groundwater and the adjacent marine environment. Results show that 89% of the As is bound to the quasi-crystalline Fe/Mn oxides and hydroxide matrix in the sediments, whereas, the adsorbed and exchangeable As hosted by the clay minerals, representing those that are easiest to release from the sediment matrix, is below 10% of the acid leachable As. These As in these sediment matrices represent the possible maximum amount of As that can be released and supplied to the groundwater and the adjacent marine environment. Of the 89% reducible As, up to 4% is associated with the easily reducible variety, whereas, the rest is more strongly bonded by the moderately reducible variety. Based on the long-term As content of the lagoon water, the average desorption rate of As is calculated to be very low -- 0.3-0.5% on the average and 0.6% on the maximum. This indicates that As is well-fixed by its sediment matrices in the ash lagoon, attenuating the influx of As into the adjacent groundwater and marine environments.

Keywords: Arsenic, natural attenuation, coal-fired power plant, Philippines.

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1000 H∞ Fuzzy Integral Power Control for DFIG Wind Energy System

Authors: N. Chayaopas, W. Assawinchaichote

Abstract:

In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.

Keywords: H∞ fuzzy integral control, linear matrix inequality, wind energy system, doubly fed induction generator (DFIG).

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999 Physico-Mechanical Properties of Chemically Modified Sisal Fibre Reinforced Unsaturated Polyester Composites

Authors: A. A. Salisu, M. Y. Yakasai, K. M. Aujara

Abstract:

Sisal leaves were subjected to enzymatic retting method to extract the sisal fibre. A portion of the fibre was pretreated with alkali (NaOH), and further treated with benzoyl chloride and silane treatment reagents. Both the treated and untreated Sisal fibre composites were used to fabricate the composite by hand lay-up technique using unsaturated polyester resin. Tensile, flexural, water absorption, density, thickness swelling and chemical resistant tests were conducted and evaluated on the composites. Results obtained for all the parameters showed an increase in the treated fibre compared to untreated fibre. FT-IR spectra results ascertained the inclusion of benzoyl and silane groups on the fibre surface. Scanning electron microscopy (SEM) result obtained showed variation in the morphology of the treated and untreated fibre. Chemical modification was found to improve adhesion of the fibre to the matrix, as well as physico-mechanical properties of the composites.

Keywords: Chemical resistance, density test, Sisal fibre, polymer matrix, thickness swelling.

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998 Phosphine Mortality Estimation for Simulation of Controlling Pest of Stored Grain: Lesser Grain Borer (Rhyzopertha dominica)

Authors: Mingren Shi, Michael Renton

Abstract:

There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.

Keywords: mortality estimation, probit models, logistic model, generalized inverse matrix approach, pest control simulation

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997 Finite-Horizon Tracking Control for Repetitive Systems with Uncertain Initial Conditions

Authors: Sung Wook Yun, Yun Jong Choi, Kyong-min Lee, Poogyeon Park*

Abstract:

Repetitive systems stand for a kind of systems that perform a simple task on a fixed pattern repetitively, which are widely spread in industrial fields. Hence, many researchers have been interested in those systems, especially in the field of iterative learning control (ILC). In this paper, we propose a finite-horizon tracking control scheme for linear time-varying repetitive systems with uncertain initial conditions. The scheme is derived both analytically and numerically for state-feedback systems and only numerically for output-feedback systems. Then, it is extended to stable systems with input constraints. All numerical schemes are developed in the forms of linear matrix inequalities (LMIs). A distinguished feature of the proposed scheme from the existing iterative learning control is that the scheme guarantees the tracking performance exactly even under uncertain initial conditions. The simulation results demonstrate the good performance of the proposed scheme.

Keywords: Finite time horizon, linear matrix inequality (LMI), repetitive system, uncertain initial condition.

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996 Development and Characterization of a Polymer Composite Electrolyte to Be Used in Proton Exchange Membranes Fuel Cells

Authors: B. A. Berns, V. Romanovicz, M. M. de Camargo Forte, D. E. O. S. Carpenter

Abstract:

The Proton Exchange Membranes (PEM) are largely studied because they operate at low temperatures and they are suitable for mobile applications. However, there are some deficiencies in their operation, mainly those that use ethanol as a hydrogen source, that require a certain attention. Therefore, this research aimed to develop Nafion® composite membranes, mixing clay minerals, kaolin and halloysite to the polymer matrix in order to improve the ethanol molecule retentions and, at the same time, to keep the system’s protonic conductivity. The modified Nafion/Kaolin, Nafion/Halloysite composite membranes were prepared in weight proportion of 0.5, 1.0 and 1.5. The membranes obtained were characterized as to their ethanol permeability, protonic conductivity and water absorption. The composite morphology and structure are characterized by SEM and EDX and the thermal behavior is determined by TGA and DSC. The analysis of the results shows ethanol permeability reduction from 48% to 63%. However, the protonic conductivity results are lower in relation to pure Nafion®. As to the thermal behavior, the Nafion® composite membranes were stable up to a temperature of 325ºC.

Keywords: Polymer-matrix composites (PMCs), Thermal properties, Nanoclay, Differential scanning calorimetry.

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995 Micromechanics of Stress Transfer across the Interface Fiber-Matrix Bonding

Authors: Fatiha Teklal, Bachir Kacimi, Arezki Djebbar

Abstract:

The study and application of composite materials are a truly interdisciplinary endeavor that has been enriched by contributions from chemistry, physics, materials science, mechanics and manufacturing engineering. The understanding of the interface (or interphase) in composites is the central point of this interdisciplinary effort. From the early development of composite materials of various nature, the optimization of the interface has been of major importance. Even more important, the ideas linking the properties of composites to the interface structure are still emerging. In our study, we need a direct characterization of the interface; the micromechanical tests we are addressing seem to meet this objective and we chose to use two complementary tests simultaneously. The microindentation test that can be applied to real composites and the drop test, preferred to the pull-out because of the theoretical possibility of studying systems with high adhesion (which is a priori the case with our systems). These two tests are complementary because of the principle of the model specimen used for both the first "compression indentation" and the second whose fiber is subjected to tensile stress called the drop test. Comparing the results obtained by the two methods can therefore be rewarding.

Keywords: Interface, micromechanics, pull-out, composite, fiber, matrix.

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994 Pragati Node Popularity (PNP) Approach to Identify Congestion Hot Spots in MPLS

Authors: E. Ramaraj, A. Padmapriya

Abstract:

In large Internet backbones, Service Providers typically have to explicitly manage the traffic flows in order to optimize the use of network resources. This process is often referred to as Traffic Engineering (TE). Common objectives of traffic engineering include balance traffic distribution across the network and avoiding congestion hot spots. Raj P H and SVK Raja designed the Bayesian network approach to identify congestion hors pots in MPLS. In this approach for every node in the network the Conditional Probability Distribution (CPD) is specified. Based on the CPD the congestion hot spots are identified. Then the traffic can be distributed so that no link in the network is either over utilized or under utilized. Although the Bayesian network approach has been implemented in operational networks, it has a number of well known scaling issues. This paper proposes a new approach, which we call the Pragati (means Progress) Node Popularity (PNP) approach to identify the congestion hot spots with the network topology alone. In the new Pragati Node Popularity approach, IP routing runs natively over the physical topology rather than depending on the CPD of each node as in Bayesian network. We first illustrate our approach with a simple network, then present a formal analysis of the Pragati Node Popularity approach. Our PNP approach shows that for any given network of Bayesian approach, it exactly identifies the same result with minimum efforts. We further extend the result to a more generic one: for any network topology and even though the network is loopy. A theoretical insight of our result is that the optimal routing is always shortest path routing with respect to some considerations of hot spots in the networks.

Keywords: Conditional Probability Distribution, Congestion hotspots, Operational Networks, Traffic Engineering.

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993 Adaptive Kernel Principal Analysis for Online Feature Extraction

Authors: Mingtao Ding, Zheng Tian, Haixia Xu

Abstract:

The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.

Keywords: adaptive method, kernel principal component analysis, online extraction, recursive algorithm

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992 Machine Learning Approach for Identifying Dementia from MRI Images

Authors: S. K. Aruna, S. Chitra

Abstract:

This research paper presents a framework for classifying Magnetic Resonance Imaging (MRI) images for Dementia. Dementia, an age-related cognitive decline is indicated by degeneration of cortical and sub-cortical structures. Characterizing morphological changes helps understand disease development and contributes to early prediction and prevention of the disease. Modelling, that captures the brain’s structural variability and which is valid in disease classification and interpretation is very challenging. Features are extracted using Gabor filter with 0, 30, 60, 90 orientations and Gray Level Co-occurrence Matrix (GLCM). It is proposed to normalize and fuse the features. Independent Component Analysis (ICA) selects features. Support Vector Machine (SVM) classifier with different kernels is evaluated, for efficiency to classify dementia. This study evaluates the presented framework using MRI images from OASIS dataset for identifying dementia. Results showed that the proposed feature fusion classifier achieves higher classification accuracy.

Keywords: Magnetic resonance imaging, dementia, Gabor filter, gray level co-occurrence matrix, support vector machine.

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991 Comparative Study on Recent Integer DCTs

Authors: Sakol Udomsiri, Masahiro Iwahashi

Abstract:

This paper presents comparative study on recent integer DCTs and a new method to construct a low sensitive structure of integer DCT for colored input signals. The method refers to sensitivity of multiplier coefficients to finite word length as an indicator of how word length truncation effects on quality of output signal. The sensitivity is also theoretically evaluated as a function of auto-correlation and covariance matrix of input signal. The structure of integer DCT algorithm is optimized by combination of lower sensitive lifting structure types of IRT. It is evaluated by the sensitivity of multiplier coefficients to finite word length expression in a function of covariance matrix of input signal. Effectiveness of the optimum combination of IRT in integer DCT algorithm is confirmed by quality improvement comparing with existing case. As a result, the optimum combination of IRT in each integer DCT algorithm evidently improves output signal quality and it is still compatible with the existing one.

Keywords: DCT, sensitivity, lossless, wordlength.

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990 Promising Immobilization of Cadmium and Lead inside Ca-rich Glass-ceramics

Authors: A. Karnis, L. Gautron

Abstract:

Considering toxicity of heavy metals and their accumulation in domestic wastes, immobilization of lead and cadmium is envisaged inside glass-ceramics. We particularly focused this work on calcium-rich phases embedded in a glassy matrix. Glass-ceramics were synthesized from glasses doped with 12 wt% and 16 wt% of PbO or CdO. They were observed and analyzed by Electron MicroProbe Analysis (EMPA) and Analytical Scanning Electron Microscopy (ASEM). Structural characterization of the samples was performed by powder XRay Diffraction. Diopside crystals of CaMgSi2O6 composition are shown to incorporate significant amounts of cadmium (up to 9 wt% of CdO). Two new crystalline phases are observed with very high Cd or Pb contents: about 40 wt% CdO for the cadmiumrich phase and near 60 wt% PbO for the lead-rich phase. We present complete chemical and structural characterization of these phases. They represent a promising way for the immobilization of toxic elements like Cd or Pb since glass ceramics are known to propose a “double barrier" protection (metal-rich crystals embedded in a glass matrix) against metal release in the environment.

Keywords: Cadmium, Calcium-rich phases, Diopside, Domesticwastes, Fly ashes, Glass-ceramics, Lead, Municipal Solid WasteIncineration.

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989 Performance Comparison of Particle Swarm Optimization with Traditional Clustering Algorithms used in Self-Organizing Map

Authors: Anurag Sharma, Christian W. Omlin

Abstract:

Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of an adaptive heuristic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOM. The application of our method to several standard data sets demonstrates its feasibility. PSO algorithm utilizes a so-called U-matrix of SOM to determine cluster boundaries; the results of this novel automatic method compare very favorably to boundary detection through traditional algorithms namely k-means and hierarchical based approach which are normally used to interpret the output of SOM.

Keywords: cluster boundaries, clustering, code vectors, data mining, particle swarm optimization, self-organizing maps, U-matrix.

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988 Reasons for the Slow Uptake of Embodied Carbon Estimation in the Sri Lankan Building Sector

Authors: Amalka Nawarathna, Nirodha Fernando, Zaid Alwan

Abstract:

Global carbon reduction is not merely a responsibility of environmentally advanced developed countries, but also a responsibility of developing countries regardless of their less impact on global carbon emissions. In recognition of that, Sri Lanka as a developing country has initiated promoting green building construction as one reduction strategy. However, notwithstanding the increasing attention on Embodied Carbon (EC) reduction in the global building sector, they still mostly focus on Operational Carbon (OC) reduction (through improving operational energy). An adequate attention has not yet been given on EC estimation and reduction. Therefore, this study aims to identify the reasons for the slow uptake of EC estimation in the Sri Lankan building sector. To achieve this aim, 16 numbers of global barriers to estimate EC were identified through existing literature. They were then subjected to a pilot survey to identify the significant reasons for the slow uptake of EC estimation in the Sri Lankan building sector. A questionnaire with a three-point Likert scale was used to this end. The collected data were analysed using descriptive statistics. The findings revealed that 11 out of 16 challenges/ barriers are highly relevant as reasons for the slow uptake in estimating EC in buildings in Sri Lanka while the other five challenges/ barriers remain as moderately relevant reasons. Further, the findings revealed that there are no low relevant reasons. Eventually, the paper concluded that all the known reasons are significant to the Sri Lankan building sector and it is necessary to address them in order to upturn the attention on EC reduction.

Keywords: Embodied carbon emissions, embodied carbon estimation, global carbon reduction, Sri Lankan building sector.

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987 Hydrogen-Fueled Micro-Thermophotovoltaic Power Generator: Flame Regimes and Flame Stability

Authors: Hosein Faramarzpour

Abstract:

This work presents the optimum operational conditions for a hydrogen-based micro-scale power source, using a verified mathematical model including fluid dynamics and reaction kinetics. Thereafter, the stable operational flame regime is pursued as a key factor in optimizing the design of micro-combustors. The results show that with increasing velocities, four H2 flame regimes develop in the micro-combustor, namely: 1) periodic ignition-extinction regime, 2) steady symmetric regime, 3) pulsating asymmetric regime, and 4) steady asymmetric regime. The first regime that appears in 0.8 m/s inlet velocity is a periodic ignition-extinction regime which is characterized by counter flows and tulip-shape flames. For flow velocity above 0.2 m/s, the flame shifts downstream, and the combustion regime switches to a steady symmetric flame where temperature increases considerably due to the increased rate of incoming energy. Further elevation in flow velocity up to 1 m/s leads to the pulsating asymmetric flame formation, which is associated with pulses in various flame properties such as temperature and species concentration. Further elevation in flow velocity up to 1 m/s leads to the pulsating asymmetric flame formation, which is associated with pulses in various flame properties such as temperature and species concentration. Ultimately, when the inlet velocity reached 1.2 m/s, the last regime was observed, and a steady asymmetric regime appeared.

Keywords: Thermophotovoltaic generator, micro combustor, micro power generator, combustion regimes, flame dynamic.

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986 Quick Sequential Search Algorithm Used to Decode High-Frequency Matrices

Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

Abstract:

This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: Matrix Minimization Algorithm, Decoding Sequential Search Algorithm, image compression, Discrete Cosine Transform, Discrete Wavelet Transform.

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985 Blind Channel Estimation for Frequency Hopping System Using Subspace Based Method

Authors: M. M. Qasaymeh, M. A. Khodeir

Abstract:

Subspace channel estimation methods have been studied widely, where the subspace of the covariance matrix is decomposed to separate the signal subspace from noise subspace. The decomposition is normally done by using either the eigenvalue decomposition (EVD) or the singular value decomposition (SVD) of the auto-correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. This paper considers the estimation of the multipath slow frequency hopping (FH) channel using noise space based method. In particular, an efficient method is proposed to estimate the multipath time delays by applying multiple signal classification (MUSIC) algorithm which is based on the null space extracted by the rank revealing LU (RRLU) factorization. As a result, precise information is provided by the RRLU about the numerical null space and the rank, (i.e., important tool in linear algebra). The simulation results demonstrate the effectiveness of the proposed novel method by approximately decreasing the computational complexity to the half as compared with RRQR methods keeping the same performance.

Keywords: Time Delay Estimation, RRLU, RRQR, MUSIC, LS-ESPRIT, LS-ESPRIT, Frequency Hopping.

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984 Managing Uncertainty in Unmanned Aircraft System Safety Performance Requirements Compliance Process

Authors: Achim Washington, Reece Clothier, Jose Silva

Abstract:

System Safety Regulations (SSR) are a central component to the airworthiness certification of Unmanned Aircraft Systems (UAS). There is significant debate on the setting of appropriate SSR for UAS. Putting this debate aside, the challenge lies in how to apply the system safety process to UAS, which lacks the data and operational heritage of conventionally piloted aircraft. The limited knowledge and lack of operational data result in uncertainty in the system safety assessment of UAS. This uncertainty can lead to incorrect compliance findings and the potential certification and operation of UAS that do not meet minimum safety performance requirements. The existing system safety assessment and compliance processes, as used for conventional piloted aviation, do not adequately account for the uncertainty, limiting the suitability of its application to UAS. This paper discusses the challenges of undertaking system safety assessments for UAS and presents current and envisaged research towards addressing these challenges. It aims to highlight the main advantages associated with adopting a risk based framework to the System Safety Performance Requirement (SSPR) compliance process that is capable of taking the uncertainty associated with each of the outputs of the system safety assessment process into consideration. Based on this study, it is made clear that developing a framework tailored to UAS, would allow for a more rational, transparent and systematic approach to decision making. This would reduce the need for conservative assumptions and take the risk posed by each UAS into consideration while determining its state of compliance to the SSR.

Keywords: Part 1309 regulations, unmanned aircraft systems, system safety, uncertainty.

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983 Interference Reduction Technique in Multistage Multiuser Detector for DS-CDMA System

Authors: Lokesh Tharani, R.P.Yadav

Abstract:

This paper presents the results related to the interference reduction technique in multistage multiuser detector for asynchronous DS-CDMA system. To meet the real-time requirements for asynchronous multiuser detection, a bit streaming, cascade architecture is used. An asynchronous multiuser detection involves block-based computations and matrix inversions. The paper covers iterative-based suboptimal schemes that have been studied to decrease the computational complexity, eliminate the need for matrix inversions, decreases the execution time, reduces the memory requirements and uses joint estimation and detection process that gives better performance than the independent parameter estimation method. The stages of the iteration use cascaded and bits processed in a streaming fashion. The simulation has been carried out for asynchronous DS-CDMA system by varying one parameter, i.e., number of users. The simulation result exhibits that system gives optimum bit error rate (BER) at 3rd stage for 15-users.

Keywords: Multi-user detection (MUD), multiple accessinterference (MAI), near-far effect, decision feedback detector, successive interference cancellation detector (SIC) and parallelinterference cancellation (PIC) detector.

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982 An Improved Adaptive Dot-Shape Beamforming Algorithm Research on Frequency Diverse Array

Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

Abstract:

Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: Multi-carrier frequency diverse array, adaptive beamforming, correction index, limited snapshot, robust.

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981 Ownership, Management Responsibility and Corporate Performance of the Listed Firms in Kazakhstan

Authors: Gulnara Moldasheva

Abstract:

The research explores the relationship between management responsibility and corporate governance of listed companies in Kazakhstan. This research employs firm level data of selected listed non-financial firms and firm level data “operational” financial sector, consisted from banking sector, insurance companies and accumulated pension funds using multivariate regression analysis under fixed effect model approach. Ownership structure includes institutional ownership, managerial ownership and private investor’s ownership. Management responsibility of the firm is expressed by the decision of the firm on amount of leverage. Results of the cross sectional panel study for non-financial firms showed that only institutional shareholding is significantly negatively correlated with debt to equity ratio. Findings from “operational” financial sector show that leverage is significantly affected only by the CEO/Chair duality and the size of financial institutions, and insignificantly affected by ownership structure. Also, the findings show, that there is a significant negative relationship between profitability and the debt to equity ratio for non-financial firms, which is consistent with pecking order theory. Generally, the found results suggest that corporate governance and a management responsibility play important role in corporate performance of listed firms in Kazakhstan.

Keywords: Corporate governance, corporate performance, debt to equity ratio, ownership.

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980 Operational Representation of Certain Hypergeometric Functions by Means of Fractional Derivatives and Integrals

Authors: Manoj Singh, Mumtaz Ahmad Khan, Abdul Hakim Khan

Abstract:

The investigation in the present paper is to obtain certain types of relations for the well known hypergeometric functions by employing the technique of fractional derivative and integral.

Keywords: Fractional Derivatives and Integrals, Hypergeometric functions.

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979 Detecting HCC Tumor in Three Phasic CT Liver Images with Optimization of Neural Network

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each region of interest (ROI), 6 distinct sets of texture features are extracted such as: first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. When analyzing more phases, we show that the injection of liquid cause changes to the high relevant features in each region. Our results demonstrate that for detecting HCC tumor phase 3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between pathology and healthy classes, according to our method, relates to first order histogram parameters with accuracy of 85% in phase 1, 95% in phase 2, and 95% in phase 3.

Keywords: Feature selection, Multi-phasic liver images, Neural network, Texture analysis.

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978 The Significance of Embodied Energy in Certified Passive Houses

Authors: Robert H. Crawford, André Stephan

Abstract:

Certifications such as the Passive House Standard aim to reduce the final space heating energy demand of residential buildings. Space conditioning, notably heating, is responsible for nearly 70% of final residential energy consumption in Europe. There is therefore significant scope for the reduction of energy consumption through improvements to the energy efficiency of residential buildings. However, these certifications totally overlook the energy embodied in the building materials used to achieve this greater operational energy efficiency. The large amount of insulation and the triple-glazed high efficiency windows require a significant amount of energy to manufacture. While some previous studies have assessed the life cycle energy demand of passive houses, including their embodied energy, these rely on incomplete assessment techniques which greatly underestimate embodied energy and can lead to misleading conclusions. This paper analyses the embodied and operational energy demands of a case study passive house using a comprehensive hybrid analysis technique to quantify embodied energy. Results show that the embodied energy is much more significant than previously thought. Also, compared to a standard house with the same geometry, structure, finishes and number of people, a passive house can use more energy over 80 years, mainly due to the additional materials required. Current building energy efficiency certifications should widen their system boundaries to include embodied energy in order to reduce the life cycle energy demand of residential buildings.

Keywords: Embodied energy, Hybrid analysis, Life cycle energy analysis, Passive house.

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977 The Effects of Alkalization to the Mechanical Properties of the Ijuk Fiber Reinforced PLA Biocomposites

Authors: Mochamad Chalid, Imam Prabowo

Abstract:

Today, the pollution due to non-degradable material such as plastics, has led to studies about the development of environmental-friendly material. Because of biodegradability obtained from natural sources, polylactid acid (PLA) and ijuk fiber are interesting to modify into a composite. This material is also expected to reduce the impact of environmental pollution. Surface modification of ijuk fiber through alkalinization with 0.25 M NaOH solution for 30 minutes was aimed to enhance its compatibility to PLA, in order to improve properties of the composite such as the mechanical properties. Alkalinization of the ijuk fibers annihilates some surface components such as lignin, wax and hemicelloluse, so the pore on the surface clearly appeared, decreasing of the density and diameter of the ijuk fibers. The change of the ijuk fiber properties leads to increase the mechanical properties of PLA composites reinforced the ijuk fibers through strengthening of the mechanical interlocking with the PLA matrix. An addition to enhance the distribution of the fibers in the PLA matrix, the stirring during DCM solvent evaporation from the mixture of the ijuk fibers and the dissolved-PLA can reduce amount of the trapped-voids and fibers pull-out phenomena, which can decrease the mechanical properties of the composite.

Keywords: Polylactic acid, Arenga pinnata, alkalinization, compatibility, adhesion, morphology, mechanical properties, volume fraction, distributiom.

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976 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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