Search results for: Statistical Pattern Recognition.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2643

Search results for: Statistical Pattern Recognition.

1923 Ontology Population via NLP Techniques in Risk Management

Authors: Jawad Makki, Anne-Marie Alquier, Violaine Prince

Abstract:

In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA1 project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency2. The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.

Keywords: Information Extraction, Instance Recognition Rules, Ontology Population, Risk Management, Semantic analysis.

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1922 Strengthening of RC Beams with Large Openings in Shear by CFRP Laminates: 2D Nonlinear FE Analysis

Authors: S.C. Chin, N. Shafiq, M.F. Nuruddin

Abstract:

To date, theoretical studies concerning the Carbon Fiber Reinforced Polymer (CFRP) strengthening of RC beams with openings have been rather limited. In addition, various numerical analyses presented so far have effectively simulated the behaviour of solid beam strengthened by FRP material. In this paper, a two dimensional nonlinear finite element analysis is presented to validate against the laboratory test results of six RC beams. All beams had the same rectangular cross-section geometry and were loaded under four point bending. The crack pattern results of the finite element model show good agreement with the crack pattern of the experimental beams. The load midspan deflection curves of the finite element models exhibited a stiffer result compared to the experimental beams. The possible reason may be due to the perfect bond assumption used between the concrete and steel reinforcement.

Keywords: CFRP, large opening, RC beam, strengthening

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1921 Skew Detection Technique for Binary Document Images based on Hough Transform

Authors: Manjunath Aradhya V N, Hemantha Kumar G, Shivakumara P

Abstract:

Document image processing has become an increasingly important technology in the automation of office documentation tasks. During document scanning, skew is inevitably introduced into the incoming document image. Since the algorithm for layout analysis and character recognition are generally very sensitive to the page skew. Hence, skew detection and correction in document images are the critical steps before layout analysis. In this paper, a novel skew detection method is presented for binary document images. The method considered the some selected characters of the text which may be subjected to thinning and Hough transform to estimate skew angle accurately. Several experiments have been conducted on various types of documents such as documents containing English Documents, Journals, Text-Book, Different Languages and Document with different fonts, Documents with different resolutions, to reveal the robustness of the proposed method. The experimental results revealed that the proposed method is accurate compared to the results of well-known existing methods.

Keywords: Optical Character Recognition, Skew angle, Thinning, Hough transform, Document processing

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1920 Effect of Highly Pressurized Dispersion Arc Nozzle on Breakup of Oil Leakage in Offshore

Authors: N. M. M. Ammar, S. M. Mustaqim, N. M. Nadzir

Abstract:

The most important problem occurs on oil spills in sea water is to reduce the oil spills size. This study deals with the development of high pressurized nozzle using dispersion method for oil leakage in offshore. 3D numerical simulation results were obtained using ANSYS Fluent 13.0 code and correlate with the experimental data for validation. This paper studies the contribution of the process on flow speed and pressure of the flow from two different geometrical designs of nozzles and to generate a spray pattern suitable for dispersant application. Factor of size distribution of droplets generated by the nozzle is calculated using pressures ranging from 2 to 6 bars. Results obtain from both analyses shows a significant spray pattern and flow distribution as well as distance. Results also show a significant contribution on the effect of oil leakage in terms of the diameter of the oil spills break up.

Keywords: Arc Nozzle, CFD simulation, Droplets, Oil Spills.

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1919 Enhanced Planar Pattern Tracking for an Outdoor Augmented Reality System

Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

Abstract:

In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: Augmented reality framework, server-client model, vision-based tracking, image search.

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1918 Statistical Assessment of Models for Determination of Soil – Water Characteristic Curves of Sand Soils

Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

Abstract:

Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and timeconsuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: Soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil.

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1917 Dual-Polarized Multi-Antenna System for Massive MIMO Cellular Communications

Authors: Naser Ojaroudi Parchin, Haleh Jahanbakhsh Basherlou, Raed A. Abd-Alhameed, Peter S. Excell

Abstract:

In this paper, a multiple-input/multiple-output (MIMO) antenna design with polarization and radiation pattern diversity is presented for future smartphones. The configuration of the design consists of four double-fed circular-ring antenna elements located at different edges of the printed circuit board (PCB) with an FR-4 substrate and overall dimension of 75×150 mm2. The antenna elements are fed by 50-Ohm microstrip-lines and provide polarization and radiation pattern diversity function due to the orthogonal placement of their feed lines. A good impedance bandwidth (S11 ≤ -10 dB) of 3.4-3.8 GHz has been obtained for the smartphone antenna array. However, for S11 ≤ -6 dB, this value is 3.25-3.95 GHz. More than 3 dB realized gain and 80% total efficiency are achieved for the single-element radiator. The presented design not only provides the required radiation coverage but also generates the polarization diversity characteristic.

Keywords: Cellular communications, MIMO systems, mobile-phone antenna, polarization diversity.

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1916 Second Order Statistics of Dynamic Response of Structures Using Gamma Distributed Damping Parameters

Authors: B. Chemali, B. Tiliouine

Abstract:

This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: Correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response.

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1915 An Optimal Unsupervised Satellite image Segmentation Approach Based on Pearson System and k-Means Clustering Algorithm Initialization

Authors: Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida, Mohamed Benjelloun

Abstract:

This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.

Keywords: Unsupervised classification, Pearson system, Satellite image, Segmentation.

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1914 Effects of Water Content on Dielectric Properties of Mineral Transformer Oil

Authors: Suwarno, M. Helmi Prakoso

Abstract:

Mineral oil is commonly used for high voltage transformer insulation. The insulation quality of mineral oil is affecting the operation process of high voltage transformer. There are many contaminations which could decrease the insulation quality of mineral oil. One of them is water. This research talks about the effect of water content on dielectric properties, physic properties, and partial discharge pattern on mineral oil. Samples were varied with 10 varieties of water content value. And then all samples would be tested to measure the dielectric properties, physic properties, and partial discharge pattern. The result of this research showed that an increment of water content value would decrease the insulation quality of mineral oil.

Keywords: Dielectric properties, high voltage transformer, mineral oil, water content.

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1913 Wavelet-Based Classification of Myocardial Ischemia, Arrhythmia, Congestive Heart Failure and Sleep Apnea

Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

Abstract:

This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.

Keywords: Arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea.

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1912 An Efficient Algorithm for Motion Detection Based Facial Expression Recognition using Optical Flow

Authors: Ahmad R. Naghsh-Nilchi, Mohammad Roshanzamir

Abstract:

One of the popular methods for recognition of facial expressions such as happiness, sadness and surprise is based on deformation of facial features. Motion vectors which show these deformations can be specified by the optical flow. In this method, for detecting emotions, the resulted set of motion vectors are compared with standard deformation template that caused by facial expressions. In this paper, a new method is introduced to compute the quantity of likeness in order to make decision based on the importance of obtained vectors from an optical flow approach. For finding the vectors, one of the efficient optical flow method developed by Gautama and VanHulle[17] is used. The suggested method has been examined over Cohn-Kanade AU-Coded Facial Expression Database, one of the most comprehensive collections of test images available. The experimental results show that our method could correctly recognize the facial expressions in 94% of case studies. The results also show that only a few number of image frames (three frames) are sufficient to detect facial expressions with rate of success of about 83.3%. This is a significant improvement over the available methods.

Keywords: Facial expression, Facial features, Optical flow, Motion vectors.

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1911 Magnetic Properties Govern the Processes of DNA Replication and the Shortening of the Telomere

Authors: Adnan Y. Rojeab

Abstract:

This hypothesis shows that the induction and the remanent of magnetic properties govern the mechanism processes of DNA replication and the shortening of the telomere. The solenoid–like formation of each parental DNA strand, which exists at the initial stage of the replication process, enables an electric charge transformation through the strand to produce a magnetic field. The magnetic field, in turn, induces the surrounding medium to form a new (replicated) strand by a remanent magnetisation. Through the remanent [residual] magnetisation process, the replicated strand possesses a similar information pattern to that of the parental strand. In the same process, the remanent amount of magnetisation forms the medium in which it has less of both repetitive and pattern magnetisation than that of the parental strand, therefore the replicated strand shows a shortening in the length of its telomeres.

Keywords: DNA replication, magnetic properties, residual magnetisation, shortening of the telomere.

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1910 Recursive Filter for Coastal Displacement Estimation

Authors: Efstratios Doukakis, Nikolaos Petrelis

Abstract:

All climate models agree that the temperature in Greece will increase in the range of 1° to 2°C by the year 2030 and mean sea level in Mediterranean is expected to rise at the rate of 5 cm/decade. The aim of the present paper is the estimation of the coastline displacement driven by the climate change and sea level rise. In order to achieve that, all known statistical and non-statistical computational methods are employed on some Greek coastal areas. Furthermore, Kalman filtering techniques are for the first time introduced, formulated and tested. Based on all the above, shoreline change signals and noises are computed and an inter-comparison between the different methods can be deduced to help evaluating which method is most promising as far as the retrieve of shoreline change rate is concerned.

Keywords: Climate Change, Coastal Displacement, KalmanFilter

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1909 Three-dimensional Simulation of Flow Pattern at the Lateral Intake in Straight Path, using Finite-Volume Method

Authors: R.Goudarzizadeh, N.Hedayat, S.H.Mousavi Jahromi

Abstract:

Channel junctions can be analyzed in two ways of division (lateral intake) and combined flows (confluence). The present paper investigates 3D flow pattern at lateral intake using Navier-Stokes equation and κ -ε (RNG) turbulent model. The equations are solved by Finite-Volume Method (FVM) and results are compared with the experimental data of (Barkdoll, B.D., 1997) to test the validity of the findings. Comparison of the results with the experimental data indicated a close proximity between the two sets of data which suggest a very close simulation. Results further indicated an inverse relation between the effects of discharge ratio ( r Q ) on the length and width of the separation zone. In other words, as the discharge ration increases, the length and width of separation zone decreases.

Keywords: 900 junction, flow division, turbulent flow, numerical modeling, flow separation zone.

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1908 The Statistical Properties of Filtered Signals

Authors: Ephraim Gower, Thato Tsalaile, Monageng Kgwadi, Malcolm Hawksford.

Abstract:

In this paper, the statistical properties of filtered or convolved signals are considered by deriving the resulting density functions as well as the exact mean and variance expressions given a prior knowledge about the statistics of the individual signals in the filtering or convolution process. It is shown that the density function after linear convolution is a mixture density, where the number of density components is equal to the number of observations of the shortest signal. For circular convolution, the observed samples are characterized by a single density function, which is a sum of products.

Keywords: Circular Convolution, linear Convolution, mixture density function.

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1907 Irrigation Water Quality Evaluation Based on Multivariate Statistical Analysis: A Case Study of Jiaokou Irrigation District

Authors: Panpan Xu, Qiying Zhang, Hui Qian

Abstract:

Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K+, Na+, Mg2+, Ca2+, SO42-, Cl-, HCO3-, and CO32-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl-, Na+, Mg2+, and SO42-, and the HCO3- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.

Keywords: Irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process.

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1906 WPRiMA Tool: Managing Risks in Web Projects

Authors: Thamer Al-Rousan, Shahida Sulaiman, Rosalina Abdul Salam

Abstract:

Risk management is an essential fraction of project management, which plays a significant role in project success. Many failures associated with Web projects are the consequences of poor awareness of the risks involved and lack of process models that can serve as a guideline for the development of Web based applications. To circumvent this problem, contemporary process models have been devised for the development of conventional software. This paper introduces the WPRiMA (Web Project Risk Management Assessment) as the tool, which is used to implement RIAP, the risk identification architecture pattern model, which focuses upon the data from the proprietor-s and vendor-s perspectives. The paper also illustrates how WPRiMA tool works and how it can be used to calculate the risk level for a given Web project, to generate recommendations in order to facilitate risk avoidance in a project, and to improve the prospects of early risk management.

Keywords: Architecture pattern model, risk factors, risk identification, web project, web project risk management assessment.

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1905 Noninvasive Disease Diagnosis through Breath Analysis Using DNA-Functionalized SWNT Sensor Array

Authors: Wenjun Zhang, Yunqing Du, Ming L. Wang

Abstract:

Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancements in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless, and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-functionalized single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Seven DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, and diabetes. Our test results indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, and repeatability; and different molecules can be distinguished through pattern recognition enabled by this sensor array. Furthermore, the experimental sensing results are consistent with the Molecular Dynamics simulated ssDNAmolecular target interaction rankings. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or biomolecular detection for the noninvasive diagnostics of diseases and personal health monitoring.

Keywords: Breath analysis, DNA-SWNT sensor array, diagnosis, noninvasive.

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1904 Strategic Investment in Infrastructure Development to Facilitate Economic Growth in the United States

Authors: Arkaprabha Bhattacharyya, Makarand Hastak

Abstract:

The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: Economic growth, infrastructure development, infrastructure projects, strategic investment.

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1903 Statistical Properties and Performance of Ecological Indices Based On Relative Abundances

Authors: Gebriel M. Shamia

Abstract:

The Improved Generalized Diversity Index (IGDI) has been proposed as a tool that can be used to identify areas that have high conservation value and measure the ecological condition of an area. IGDI is based on the species relative abundances. This paper is concerned with particular attention is given to comparisons involving the MacArthur model of species abundances. The properties and performance of various species indices were assessed. Both IGDI and species richness increased with sampling area according to a power function. IGDI were also found to be acceptable ecological indicators of conditions and consistently outperformed coefficient of conservatism indices.

Keywords: Statistical ecology, MacArthur model, Functional Diversity.

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1902 Statistical Analysis and Impact Forecasting of Connected and Autonomous Vehicles on the Environment: Case Study in the State of Maryland

Authors: Alireza Ansariyar, Safieh Laaly

Abstract:

Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates Connected and Autonomous Vehicles (CAVs) fuel consumption and air pollutants including Carbon Monoxide (CO), Particulate Matter (PM), and Nitrogen Oxides (NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: Connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models.

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1901 Effect of Non-Newtonian Behavior of Oil Phase on Oil-Water Stratified Flow in a Horizontal Channel

Authors: Satish Kumar Dewangan, Santosh Kumar Senapati

Abstract:

The present work focuses on the investigation of the effect of non-Newtonian behavior on the oil-water stratified flow in a horizontal channel using ANSYS Fluent. Coupled level set and volume of fluid (CLSVOF) has been used to capture the evolving interface assuming unsteady, coaxial flow with constant fluid properties. The diametric variation of oil volume fraction, mixture velocity, total pressure and pressure gradient has been studied. Non-Newtonian behavior of oil has been represented by the power law model in order to investigate the effect of flow behavior index. Stratified flow pattern tends to assume dispersed flow pattern with the change in the behavior of oil to non-Newtonian. The pressure gradient is found to be very much sensitive to the flow behavior index. The findings could be useful in designing the transportation pipe line in petroleum industries.

Keywords: Oil-water stratified flow, horizontal channel, CLSVOF, non–Newtonian behavior.

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1900 Statistical Distributions of the Lapped Transform Coefficients for Images

Authors: Vijay Kumar Nath, Deepika Hazarika, Anil Mahanta,

Abstract:

Discrete Cosine Transform (DCT) based transform coding is very popular in image, video and speech compression due to its good energy compaction and decorrelating properties. However, at low bit rates, the reconstructed images generally suffer from visually annoying blocking artifacts as a result of coarse quantization. Lapped transform was proposed as an alternative to the DCT with reduced blocking artifacts and increased coding gain. Lapped transforms are popular for their good performance, robustness against oversmoothing and availability of fast implementation algorithms. However, there is no proper study reported in the literature regarding the statistical distributions of block Lapped Orthogonal Transform (LOT) and Lapped Biorthogonal Transform (LBT) coefficients. This study performs two goodness-of-fit tests, the Kolmogorov-Smirnov (KS) test and the 2- test, to determine the distribution that best fits the LOT and LBT coefficients. The experimental results show that the distribution of a majority of the significant AC coefficients can be modeled by the Generalized Gaussian distribution. The knowledge of the statistical distribution of transform coefficients greatly helps in the design of optimal quantizers that may lead to minimum distortion and hence achieve optimal coding efficiency.

Keywords: Lapped orthogonal transform, Lapped biorthogonal transform, Image compression, KS test,

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1899 A Heuristic Statistical Model for Lifetime Distribution Analysis of Complicated Systems in the Reliability Centered Maintenance

Authors: Mojtaba Mahdavi, Mohamad Mahdavi, Maryam Yazdani

Abstract:

A heuristic conceptual model for to develop the Reliability Centered Maintenance (RCM), especially in preventive strategy, has been explored during this paper. In most real cases which complicity of system obligates high degree of reliability, this model proposes a more appropriate reliability function between life time distribution based and another which is based on relevant Extreme Value (EV) distribution. A statistical and mathematical approach is used to estimate and verify these two distribution functions. Then best one is chosen just among them, whichever is more reliable. A numeric Industrial case study will be reviewed to represent the concepts of this paper, more clearly.

Keywords: Lifetime distribution, Reliability, Estimation, Extreme value, Improving model, Series, Parallel.

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1898 High Speed Bitwise Search for Digital Forensic System

Authors: Hyungkeun Jee, Jooyoung Lee, Dowon Hong

Abstract:

The most common forensic activity is searching a hard disk for string of data. Nowadays, investigators and analysts are increasingly experiencing large, even terabyte sized data sets when conducting digital investigations. Therefore consecutive searching can take weeks to complete successfully. There are two primary search methods: index-based search and bitwise search. Index-based searching is very fast after the initial indexing but initial indexing takes a long time. In this paper, we discuss a high speed bitwise search model for large-scale digital forensic investigations. We used pattern matching board, which is generally used for network security, to search for string and complex regular expressions. Our results indicate that in many cases, the use of pattern matching board can substantially increase the performance of digital forensic search tools.

Keywords: Digital forensics, search, regular expression.

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1897 Novel Adaptive Channel Equalization Algorithms by Statistical Sampling

Authors: János Levendovszky, András Oláh

Abstract:

In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Keywords: Cellular Neural Network, channel equalization, communication over fading channels, multiuser communication, spectral efficiency, statistical sampling.

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1896 Neural Network Optimal Power Flow(NN-OPF) based on IPSO with Developed Load Cluster Method

Authors: Mat Syai'in, Adi Soeprijanto

Abstract:

An Optimal Power Flow based on Improved Particle Swarm Optimization (OPF-IPSO) with Generator Capability Curve Constraint is used by NN-OPF as a reference to get pattern of generator scheduling. There are three stages in Designing NN-OPF. The first stage is design of OPF-IPSO with generator capability curve constraint. The second stage is clustering load to specific range and calculating its index. The third stage is training NN-OPF using constructive back propagation method. In training process total load and load index used as input, and pattern of generator scheduling used as output. Data used in this paper is power system of Java-Bali. Software used in this simulation is MATLAB.

Keywords: Optimal Power Flow, Generator Capability Curve, Improved Particle Swarm Optimization, Neural Network

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1895 Microstrip Slot Antenna for Triple Band Application in Wireless Communication

Authors: Biplab Bag

Abstract:

In this paper, the design of a coaxial feed single layer rectangular microstrip patch antenna for three different wireless communication band applications is presented. The proposed antenna is designed by using substrate Roger RT/duroid 5880 having permittivity of about 2.2 and tangent loss of 0.0009. The characteristics of the substrate are designed and to evaluate the performance of modeled antenna using HFSS v.11 EM simulator, from Ansoft. The proposed antenna has small in size and operates at 2.25GHz, 3.76GHz and 5.23GHz suitable for mobile satellite service (MSS) network, WiMAX and WLAN applications. The dimension of the patch and slots are optimized to obtain these desired functional frequency ranges. The simulation results with frequency response, radiation pattern and return loss, VSWR, Input Impedance are presented with appropriate table and graph.

Keywords: Microstrip, Tangent Loss, MSS, WiMAX, WLAN, Radiation Pattern, Return Loss, VSWR.

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1894 Evaluation of the Burden of Taxation Received by Households in Lithuania

Authors: V. Boguslauskas, G. Jakstonyte, L. Giriunas

Abstract:

Many foreign and Lithuanian scientists, analyzing the evaluation of the tax system in respect of the burden of taxation, agree that the latter, in principle, depends on how many individuals and what units of the residents constitute a household. Therefore, the aim of scientific research is to substantiate or to deny the significance of a household, but not a resident, as a statistical unit, during the evaluation of tax system, to be precise, determination of the value of the burden of taxation. A performed scientific research revealed that evaluation of the tax system in respect of a household, but not a resident, as a statistical unit, allows not only to evaluate the efficiency of the tax system more objectively, but also to forecast practicably existing poverty line, burden of taxation, and to capacitate the initiation of efficient decisions in social and tax fields creating the environment of existence.

Keywords: burden of taxation, household, tax systemevaluation.

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