Search results for: logit estimation

Authors: Mostafa Aminzadeh, Min Deng

Abstract:

Modeling loss data is an important part of actuarial science. Actuaries use models to predict future losses and manage financial risk, which can be beneficial for marketing purposes. In the insurance industry, small claims happen frequently while large claims are rare. Traditional distributions such as Normal, Exponential, and inverse-Gaussian are not suitable for describing insurance data, which often show skewness and fat tails. Several authors have studied classical and Bayesian inference for parameters of composite distributions, such as Exponential-Pareto, Weibull-Pareto, and Inverse Gamma-Pareto. These models separate small to moderate losses from large losses using a threshold parameter. This research introduces a computational approach using a nonlinear regression model for loss data that relies on multiple predictors. Simulation studies were conducted to assess the accuracy of the proposed estimation method. The simulations confirmed that the proposed method provides precise estimates for regression parameters. It's important to note that this approach can be applied to datasets if goodness-of-fit tests confirm that the composite distribution under study fits the data well. To demonstrate the computations, a real data set from the insurance industry is analyzed. A Mathematica code uses the Fisher information algorithm as an iteration method to obtain the maximum likelihood estimation (MLE) of regression parameters.

Keywords: maximum likelihood estimation, fisher scoring method, non-linear regression models, composite distributions

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Andrey V. Timofeev

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This paper introduces an original method for guaranteed estimation of the accuracy of an ensemble of Lipschitz classifiers. The solution was obtained as a finite closed set of alternative hypotheses, which contains an object of classification with a probability of not less than the specified value. Thus, the classification is represented by a set of hypothetical classes. In this case, the smaller the cardinality of the discrete set of hypothetical classes is, the higher is the classification accuracy. Experiments have shown that if the cardinality of the classifiers ensemble is increased then the cardinality of this set of hypothetical classes is reduced. The problem of the guaranteed estimation of the accuracy of an ensemble of Lipschitz classifiers is relevant in the multichannel classification of target events in C-OTDR monitoring systems. Results of suggested approach practical usage to accuracy control in C-OTDR monitoring systems are present.

Keywords: Lipschitz classifiers, confidence set, C-OTDR monitoring, classifiers accuracy, classifiers ensemble

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Authors: Suzana Ramli, Wardah Tahir

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Estimation of surface runoff depth is a vital part in any rainfall-runoff modeling. It leads to stream flow calculation and later predicts flood occurrences. GIS (Geographic Information System) is an advanced and opposite tool used in simulating hydrological model due to its realistic application on topography. The paper discusses on calculation of surface runoff depth for two selected events by using GIS with Curve Number method for Upper Klang River basin. GIS enables maps intersection between soil type and land use that later produces curve number map. The results show good correlation between simulated and observed values with more than 0.7 of R2. Acceptable performance of statistical measurements namely mean error, absolute mean error, RMSE, and bias are also deduced in the paper.

Keywords: surface runoff, geographic information system, curve number method, environment

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Authors: Chad Brown

Abstract:

This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Yeongyu Choi, Ju H. Park, S. M. Lee, Ho-Youl Jung

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In this paper, an improved method for estimating fundamental matrix is proposed. The method is applied effectively to monocular camera based moving object detection. The method consists of corner points detection, moving object’s motion estimation and fundamental matrix calculation. The corner points are obtained by using Harris corner detector, motions of moving objects is calculated from pyramidal Lucas-Kanade optical flow algorithm. Through epipolar geometry analysis using RANSAC, the fundamental matrix is calculated. In this method, we have improved the performances of moving object detection by using two threshold values that determine inlier or outlier. Through the simulations, we compare the performances with varying the two threshold values.

Keywords: corner detection, optical flow, epipolar geometry, RANSAC

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Authors: Mohammad Ridzwan Bin Abd Rahim, Siegfried Schmauder, Yupiter HP Manurung, Peter Binkele, Meor Iqram B. Meor Ahmad, Kiarash Dogahe

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This paper deals with the short crack initiation of the material P91 under cyclic loading at two different temperatures, concluded with the estimation of the short crack initiation Wöhler (S/N) curve. An artificial but representative model microstructure was generated using Voronoi tessellation and the Finite Element Method, and the non-uniform stress distribution was calculated accordingly afterward. The number of cycles needed for crack initiation is estimated on the basis of the stress distribution in the model by applying the physically-based Tanaka-Mura model. Initial results show that the number of cycles to generate crack initiation is strongly correlated with temperature.

Keywords: short crack initiation, P91, Wöhler curve, Voronoi tessellation, Tanaka-Mura model

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Authors: Xiang Jia, Zhijun Cheng

Abstract:

The residual lifetime of a product is the operation time between the current time and the time point when the failure happens. The residual lifetime estimation is rather important in reliability analysis. To predict the residual lifetime, it is necessary to assume or verify a particular distribution that the lifetime of the product follows. And the two-parameter Weibull distribution is frequently adopted to describe the lifetime in reliability engineering. Due to the time constraint and cost reduction, a life testing experiment is usually terminated before all the units have failed. Then the censored data is usually collected. In addition, other information could also be obtained for reliability analysis. The expert judgements are considered as it is common that the experts could present some useful information concerning the reliability. Therefore, the residual lifetime is estimated for Weibull distribution by fusing the censored data and expert judgements in this paper. First, the closed-forms concerning the point estimate and confidence interval for the residual lifetime under the Weibull distribution are both presented. Next, the expert judgements are regarded as the prior information and how to determine the prior distribution of Weibull parameters is developed. For completeness, the cases that there is only one, and there are more than two expert judgements are both focused on. Further, the posterior distribution of Weibull parameters is derived. Considering that it is difficult to derive the posterior distribution of residual lifetime, a sample-based method is proposed to generate the posterior samples of Weibull parameters based on the Monte Carlo Markov Chain (MCMC) method. And these samples are used to obtain the Bayes estimation and credible interval for the residual lifetime. Finally, an illustrative example is discussed to show the application. It demonstrates that the proposed method is rather simple, satisfactory, and robust.

Keywords: expert judgements, information fusion, residual lifetime, Weibull distribution

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Authors: S. Gharbi, S. Labidi, M. Mars, M. Chelli, F. Ladeb

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The purpose of this study is to reduce radiation dose for chest CT examination by including Tube Current Modulation (TCM) to a standard CT protocol. A scan of an anthropomorphic male Alderson phantom was performed on a 128-slice scanner. The estimation of effective dose (ED) in both scans with and without mAs modulation was done via multiplication of Dose Length Product (DLP) to a conversion factor. Results were compared to those measured with a CT-Expo software. The size specific dose estimation (SSDE) values were obtained by multiplication of the volume CT dose index (CTDIvol) with a conversion size factor related to the phantom’s effective diameter. Objective assessment of image quality was performed with Signal to Noise Ratio (SNR) measurements in phantom. SPSS software was used for data analysis. Results showed including CARE Dose 4D; ED was lowered by 48.35% and 51.51% using DLP and CT-expo, respectively. In addition, ED ranges between 7.01 mSv and 6.6 mSv in case of standard protocol, while it ranges between 3.62 mSv and 3.2 mSv with TCM. Similar results are found for SSDE; dose was higher without TCM of 16.25 mGy and was lower by 48.8% including TCM. The SNR values calculated were significantly different (p=0.03<0.05). The highest one is measured on images acquired with TCM and reconstructed with Filtered back projection (FBP). In conclusion, this study proves the potential of TCM technique in SSDE and ED reduction and in conserving image quality with high diagnostic reference level for thoracic CT examinations.

Keywords: anthropomorphic phantom, computed tomography, CT-expo, radiation dose

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Authors: Navneet Kalia, Lalit Mohan Verma, Vinay Guleria

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Introduction: Design Flood studies are essential for effective planning and functioning of water resource projects. Design flood estimation for Sunni Dam Hydro Electric Project located in State of Himachal Pradesh, India, on the river Satluj, was a big challenge in view of the river flowing in the Himalayan region from Tibet to India, having a large catchment area of varying topography, climate, and vegetation. No Discharge data was available for the part of the river in Tibet, whereas, for India, it was available only at Khab, Rampur, and Luhri. The estimation of Design Flood using standard methods was not possible. This challenge was met using two different approaches for upper (snow-fed) and lower (rainfed) catchment using Flood Frequency Approach and Hydro-metrological approach. i) For catchment up to Khab Gauging site (Sub-Catchment, C1), Flood Frequency approach was used. Around 90% of the catchment area (46300 sqkm) up to Khab is snow-fed which lies above 4200m. In view of the predominant area being snow-fed area, 1 in 10000 years return period flood estimated using Flood Frequency analysis at Khab was considered as Probable Maximum Flood (PMF). The flood peaks were taken from daily observed discharges at Khab, which were increased by 10% to make them instantaneous. Design Flood of 4184 cumec thus obtained was considered as PMF at Khab. ii) For catchment between Khab and Sunni Dam (Sub-Catchment, C2), Hydro-metrological approach was used. This method is based upon the catchment response to the rainfall pattern observed (Probable Maximum Precipitation - PMP) in a particular catchment area. The design flood computation mainly involves the estimation of a design storm hyetograph and derivation of the catchment response function. A unit hydrograph is assumed to represent the response of the entire catchment area to a unit rainfall. The main advantage of the hydro-metrological approach is that it gives a complete flood hydrograph which allows us to make a realistic determination of its moderation effect while passing through a reservoir or a river reach. These studies were carried out to derive PMF for the catchment area between Khab and Sunni Dam site using a 1-day and 2-day PMP values of 232 and 416 cm respectively. The PMF so obtained was 12920.60 cumec. Final Result: As the Catchment area up to Sunni Dam has been divided into 2 sub-catchments, the Flood Hydrograph for the Catchment C1 has been routed through the connecting channel reach (River Satluj) using Muskingum method and accordingly, the Design Flood was computed after adding the routed flood ordinates with flood ordinates of catchment C2. The total Design Flood (i.e. 2-Day PMF) with a peak of 15473 cumec was obtained. Conclusion: Even though, several factors are relevant while deciding the method to be used for design flood estimation, data availability and the purpose of study are the most important factors. Since, generally, we cannot wait for the hydrological data of adequate quality and quantity to be available, flood estimation has to be done using whatever data is available. Depending upon the type of data available for a particular catchment, the method to be used is to be selected.

Keywords: design flood, design storm, flood frequency, PMF, PMP, unit hydrograph

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Authors: Albert Kwabena Osei Konadu

Abstract:

One of the endemic forest species of the savannah transition zones enlisted by the Convention of International Treaty for Endangered Species (CITES) in Appendix II is the Rosewood, also known as Pterocarpus erinaceus or Krayie. Its economic viability has made it increasingly popular and in high demand. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. The study was limited by the usage of regulators assigned volume as benchmark and also fraught with potential volume measurement error in the stacked billet scenario due to the existence of spaces within packed billets. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: cubic volume formula, smallian volume formula, pterocarpus erinaceus, tree information form, forest transition and savannah zones, harvested tree volume

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Authors: Asaad Y. Shamseldin

Abstract:

Analytical probabilistic approach is an innovative approach for urban stormwater modeling. It can provide information about the long-term performance of a stormwater management facility without being computationally very demanding. This paper explores the application of the analytical probabilistic approach in New Zealand. The paper presents the results of a case study aimed at development of an objective way of identifying what constitutes a rainfall storm event and the estimation of the corresponding statistical properties of storms using two selected automatic rainfall stations located in the Auckland region in New Zealand. The storm identification and the estimation of the storm statistical properties are regarded as the first step in the development of the analytical probabilistic models. The paper provides a recommendation about the definition of the storm inter-event time to be used in conjunction with the analytical probabilistic approach.

Keywords: hydrology, rainfall storm, storm inter-event time, New Zealand, stormwater management

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Authors: Rita SahaRay, Ganesh Dutta

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In this article, experimental situations are considered where a main effects plan is to be used to study m two-level factors using n runs which are partitioned into b blocks, not necessarily of same size. Assuming the block sizes to be even for all blocks, for the case n ≡ 2 (mod 4), optimal designs are obtained with respect to type 1 and type 2 optimality criteria in the class of designs providing estimation of all main effects orthogonal to the block effects. In practice, such orthogonal estimation of main effects is often a desirable condition. In the wider class of all available m two level even sized blocked main effects plans, where the factors do not occur at high and low levels equally often in each block, E-optimal designs are also characterized. Simple construction methods based on Hadamard matrices and Kronecker product for these optimal designs are presented.

Keywords: design matrix, Hadamard matrix, Kronecker product, type 1 criteria, type 2 criteria

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Authors: A. M. Abd-Elfattah, M. H. Abu-Moussa

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In this paper, the estimation of stress-strength parameter R = P(Y < X) is considered when X; Y the strength and stress respectively are two independent random variables of Burr Type XII distribution. The samples taken for X and Y are progressively censoring of type II. The maximum likelihood estimator (MLE) of R is obtained when the common parameter is unknown. But when the common parameter is known the MLE, uniformly minimum variance unbiased estimator (UMVUE) and the Bayes estimator of R = P(Y < X) are obtained. The exact condence interval of R based on MLE is obtained. The performance of the proposed estimators is compared using the computer simulation.

Keywords: Burr Type XII distribution, progressive type-II censoring, stress-strength model, unbiased estimator, maximum-likelihood estimator, uniformly minimum variance unbiased estimator, confidence intervals, Bayes estimator

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Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: control, identification, robot, co-manipulation, sensor-less

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Authors: K. Zhumadilov, P. Kazymbet, A. Ivannikov, M. Bakhtin, A. Akylbekov, K. Kadyrzhanov, A. Morzabayev, M. Hoshi

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The aim of the study is to evaluate the possible excess of dose received by uranium processing plant workers. The possible excess of dose of workers was evaluated with comparison with population pool (Stepnogorsk) and control pool (Astana city). The measured teeth samples were extracted according to medical indications. In total, twenty-seven tooth enamel samples were analyzed from the residents of Stepnogorsk city (180 km from Astana city, Kazakhstan). About 6 tooth samples were collected from the workers of uranium processing plant. The results of tooth enamel dose estimation show us small influence of working conditions to workers, the maximum excess dose is less than 100 mGy. This is pilot study of EPR dose estimation and for a final conclusion additional sample is required.

Keywords: EPR dose, workers, uranium mines, tooth samples

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Authors: T. C. Bera, A. Bansal, D. Nema

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During performing turning operation, cutting force plays a significant role in metal cutting process affecting tool-work piece deflection, vibration and eventually part quality. The present research work aims to develop a mechanistic cutting force model and to study the mechanistic constants used in the force model in case of turning operation. The proposed model can be used for the reliable and accurate estimation of the cutting forces establishing relationship of various force components (cutting force and feed force) with uncut chip thickness. The accurate estimation of cutting force is required to improve thin-walled part accuracy by controlling the tool-work piece deflection induced surface errors and tool-work piece vibration.

Keywords: turning, cutting forces, cutting constants, uncut chip thickness

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Authors: Mohammad Amjad Sabir, Ishtiaq Khan, Shahid Ali, Umar Shabbir, Aneel Ahmad

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Creep, being the main silt contributor to the rivers, is a slow, downhill flow of soils. The creep velocity is measured in millimeters to a couple of centimeters per year and is determined with the help of tilt caused by creep in the vertical objects and needs at least ten years to get a reliable creep velocity. This project was devised to calculate creep velocity using dendrochronology and looking for the difference of creep velocity registered by different trees on the same slope. It was concluded that dendrochronology provides a very reliable procedure of creep velocity estimation if ‘J’ shaped trees are studied for their horizontal movement and age. The age of these trees was measured using tree coring, and the horizontal movement was measured with a conventional tape. Using this procedure it does not require decades and additionally the data reveals the creep velocity for up to 150 years and even more instead of just a decade. It was also concluded that the creep velocity does not only depend on bulk density of soil hence no pronounced effect of bulk density was detected.

Keywords: creep velocity, Galiyat, Pakistan, dendrochronology, Nagri Bala

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Authors: Saba Riaz, Syed A. Hussain

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This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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Authors: Afia Naheed, Manmohan Singh, David Lucy

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This work is based on a mathematical as well as statistical study of an SEIJTR deterministic model for the interpretation of transmission of severe acute respiratory syndrome (SARS). Based on the SARS epidemic in 2003, the parameters are estimated using Runge-Kutta (Dormand-Prince pairs) and least squares methods. Possible graphical and numerical techniques are used to validate the estimates. Then effect of the model parameters on the dynamics of the disease is examined using sensitivity and uncertainty analysis. Sensitivity and uncertainty analytical techniques are used in order to analyze the affect of the uncertainty in the obtained parameter estimates and to determine which parameters have the largest impact on controlling the disease dynamics.

Keywords: infectious disease, severe acute respiratory syndrome (SARS), parameter estimation, sensitivity analysis, uncertainty analysis, Runge-Kutta methods, Levenberg-Marquardt method

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Authors: Aarati Susan Mathew, Radhika Narendra Patel, Jiji Mathew

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A retrospective study conducted at Christian Medical College (CMC) Teaching Hospital, Vellore, India on 14th August 2014 to assess the accuracy of clinically estimated foetal weight upon labour admission. Estimating foetal weight is a crucial factor in assessing maternal and foetal complications during and after labour. Medical notes of ninety-eight postnatal women who fulfilled the inclusion criteria were studied to evaluate the correlation between their recorded Estimated Foetal Weight (EFW) on admission and actual birth weight (ABW) of the newborn after delivery. Data concerning maternal and foetal demographics was also noted. Accuracy was determined by absolute percentage error and proportion of estimates within 10% of ABW. Actual birth weights ranged from 950-4080g. A strong positive correlation between EFW and ABW (r=0.904) was noted. Term deliveries (≥40 weeks) in the normal weight range (2500-4000g) had a 59.5% estimation accuracy (n=74) compared to pre-term (<40 weeks) with an estimation accuracy of 0% (n=2). Out of the term deliveries, macrosomic babies (>4000g) were underestimated by 25% (n=3) and low birthweight (LBW) babies were overestimated by 12.7% (n=9). Registrars who estimated foetal weight were accurate in babies within normal weight ranges. However, there needs to be an improvement in predicting weight of macrosomic and LBW foetuses. We have suggested the use of an amended version of the Johnson’s formula for the Indian population for improvement and a need to re-audit once implemented.

Keywords: clinical palpation, estimated foetal weight, pregnancy, India, Johnson’s formula

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Authors: Giriraj Achari, Malay Bhattacharyya

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In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

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Authors: Sang Wook Park, Jun Su Park, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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This study suggests the estimation method of stress distribution for the beam structures based on TLS (Terrestrial Laser Scanning). The main components of method are the creation of the lattices of raw data from TLS to satisfy the suitable condition and application of CSSI (Cubic Smoothing Spline Interpolation) for estimating stress distribution. Estimation of stress distribution for the structural member or the whole structure is one of the important factors for safety evaluation of the structure. Existing sensors which include ESG (Electric strain gauge) and LVDT (Linear Variable Differential Transformer) can be categorized as contact type sensor which should be installed on the structural members and also there are various limitations such as the need of separate space where the network cables are installed and the difficulty of access for sensor installation in real buildings. To overcome these problems inherent in the contact type sensors, TLS system of LiDAR (light detection and ranging), which can measure the displacement of a target in a long range without the influence of surrounding environment and also get the whole shape of the structure, has been applied to the field of structural health monitoring. The important characteristic of TLS measuring is a formation of point clouds which has many points including the local coordinate. Point clouds is not linear distribution but dispersed shape. Thus, to analyze point clouds, the interpolation is needed vitally. Through formation of averaged lattices and CSSI for the raw data, the method which can estimate the displacement of simple beam was developed. Also, the developed method can be extended to calculate the strain and finally applicable to estimate a stress distribution of a structural member. To verify the validity of the method, the loading test on a simple beam was conducted and TLS measured it. Through a comparison of the estimated stress and reference stress, the validity of the method is confirmed.

Keywords: structural healthcare monitoring, terrestrial laser scanning, estimation of stress distribution, coordinate transformation, cubic smoothing spline interpolation

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Authors: Fatma Mohamed Magdy Badr El Dine, Amr Mohamed Abd Allah

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Introduction: Age estimation of individuals is one of the crucial steps in forensic practice. Different traditional methods rely on the length of the diaphysis of long bones of limbs, epiphyseal-diaphyseal union, fusion of the primary ossification centers as well as dental eruption. However, there is a growing need for the development of precise and reliable methods to estimate age, especially in cases where dismembered corpses, burnt bodies, purified or fragmented parts are recovered. Teeth are the hardest and indestructible structure in the human body. In recent years, assessment of pulp/tooth area ratio, as an indirect quantification of secondary dentine deposition has received a considerable attention. However, scanty work has been done in Egypt in terms of applicability of pulp/tooth ratio for age estimation. Aim of the Work: The present work was designed to assess the Cameriere’s method for age estimation from pulp/tooth ratio of maxillary canines, central and lateral incisors among a sample from Egyptian population. In addition, to formulate regression equations to be used as population-based standards for age determination. Material and Methods: The present study was conducted on 270 peri-apical X-rays of maxillary canines, central and lateral incisors (collected from 131 males and 139 females aged between 19 and 52 years). The pulp and tooth areas were measured using the Adobe Photoshop software program and the pulp/tooth area ratio was computed. Linear regression equations were determined separately for canines, central and lateral incisors. Results: A significant correlation was recorded between the pulp/tooth area ratio and the chronological age. The linear regression analysis revealed a coefficient of determination (R² = 0.824 for canine, 0.588 for central incisor and 0.737 for lateral incisor teeth). Three regression equations were derived. Conclusion: As a conclusion, the pulp/tooth ratio is a useful technique for estimating age among Egyptians. Additionally, the regression equation derived from canines gave better result than the incisors.

Keywords: age determination, canines, central incisors, Egypt, lateral incisors, pulp/tooth ratio

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Authors: Swarnadip Ghosh

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Sentiment Analysis is the process of detecting the contextual polarity of text. In other words, it determines whether a piece of writing is positive, negative or neutral.Sentiment analysis of documents holds great importance in today's world, when numerous information is stored in databases and in the world wide web. An efficient algorithm to illicit such information, would be beneficial for social, economic as well as medical purposes. In this project, we have developed an algorithm to classify a document into positive or negative. Using our algorithm, we obtained a feature set from the data, and classified the documents based on this feature set. It is important to note that, in the classification, we have not used the independence assumption, which is considered by many procedures like the Naive Bayes. This makes the algorithm more general in scope. Moreover, because of the sparsity and high dimensionality of such data, we did not use empirical distribution for estimation, but developed a method by finding degree of close clustering of the data points. We have applied our algorithm on a movie review data set obtained from IMDb and obtained satisfactory results.

Keywords: sentiment, Run's Test, cross validation, higher dimensional pmf estimation

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Chiang Wei, Hui-Chung Yeh, Yen-Chang Chen

Abstract:

The objective of this study is to estimate the rainfall using the new generation Himawari-8 meteorological satellite with multi-band, high-bit format, and high spatiotemporal resolution, ground rainfall data at the Chen-Yu-Lan watershed of Joushuei River Basin (443.6 square kilometers) in Central Taiwan. Accurate and fine-scale rainfall information is essential for rugged terrain with high local variation for early warning of flood, landslide, and debris flow disasters. 10-minute and 2 km pixel-based rainfall of Typhoon Megi of 2016 and meiyu on June 1-4 of 2017 were tested to demonstrate the new generation Himawari-8 meteorological satellite can capture rainfall variation in the rugged mountainous area both at fine-scale and watershed scale. The results provide the valuable rainfall information for early warning of future disasters.

Keywords: estimation, Himawari-8, rainfall, satellite imagery

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Authors: Animut Meseret Simachew

Abstract:

Parallel Code Phase Search Acquisition (PCSA) Algorithm has been considered as a promising method in GPS software receivers for detection and estimation of the accurate correlation peak between the received Global Positioning System (GPS) signal and locally generated replicas. GPS signal acquisition in highly dense multipath environments is the main research challenge. In this work, we proposed a robust variable step-size (RVSS) PCSA algorithm based on fast frequency transform (FFT) filtering technique to mitigate short time delay multipath signals. Simulation results reveal the effectiveness of the proposed algorithm over the conventional PCSA algorithm. The proposed RVSS-PCSA algorithm equalizes the received carrier wiped-off signal with locally generated C/A code.

Keywords: adaptive PCSA, detection and estimation, GPS signal acquisition, GPS software receiver

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

Abstract:

In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

Procedia PDF Downloads 82