Search results for: instrumental variable estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4136

Search results for: instrumental variable estimation

3986 Brain Age Prediction Based on Brain Magnetic Resonance Imaging by 3D Convolutional Neural Network

Authors: Leila Keshavarz Afshar, Hedieh Sajedi

Abstract:

Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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3985 The Linear Combination of Kernels in the Estimation of the Cumulative Distribution Functions

Authors: Abdel-Razzaq Mugdadi, Ruqayyah Sani

Abstract:

The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data.

Keywords: estimation, bandwidth, mean square error, cumulative distribution function

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3984 Estimation and Comparison of Delay at Signalized Intersections Based on Existing Methods

Authors: Arpita Saha, Satish Chandra, Indrajit Ghosh

Abstract:

Delay implicates the time loss of a traveler while crossing an intersection. Efficiency of traffic operation at signalized intersections is assessed in terms of delay caused to an individual vehicle. Highway Capacity Manual (HCM) method and Webster’s method are the most widely used in India for delay estimation purpose. However, in India, traffic is highly heterogeneous in nature with extremely poor lane discipline. Therefore, to explore best delay estimation technique for Indian condition, a comparison was made. In this study, seven signalized intersections from three different cities where chosen. Data was collected for both during morning and evening peak hours. Only under saturated cycles were considered for this study. Delay was estimated based on the field data. With the help of Simpson’s 1/3 rd rule, delay of under saturated cycles was estimated by measuring the area under the curve of queue length and cycle time. Moreover, the field observed delay was compared with the delay estimated using HCM, Webster, Probabilistic, Taylor’s expansion and Regression methods. The drawbacks of the existing delay estimation methods to be use in Indian heterogeneous traffic conditions were figured out, and best method was proposed. It was observed that direct estimation of delay using field measured data is more accurate than existing conventional and modified methods.

Keywords: delay estimation technique, field delay, heterogeneous traffic, signalised intersection

Procedia PDF Downloads 270
3983 Multivariate Control Chart to Determine Efficiency Measurements in Industrial Processes

Authors: J. J. Vargas, N. Prieto, L. A. Toro

Abstract:

Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

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3982 Variable-Fidelity Surrogate Modelling with Kriging

Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

Abstract:

Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

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3981 Study of Harmonics Estimation on Analog kWh Meter Using Fast Fourier Transform Method

Authors: Amien Rahardjo, Faiz Husnayain, Iwa Garniwa

Abstract:

PLN used the kWh meter to determine the amount of energy consumed by the household customers. High precision of kWh meter is needed in order to give accuracy results as the accuracy can be decreased due to the presence of harmonic. In this study, an estimation of active power consumed was developed. Based on the first year study results, the largest deviation due to harmonics can reach up to 9.8% in 2200VA and 12.29% in 3500VA with kWh meter analog. In the second year of study, deviation of digital customer meter reaches 2.01% and analog meter up to 9.45% for 3500VA household customers. The aim of this research is to produce an estimation system to calculate the total energy consumed by household customer using analog meter so the losses due to irregularities PLN recording of energy consumption based on the measurement used Analog kWh-meter installed is avoided.

Keywords: harmonics estimation, harmonic distortion, kWh meters analog and digital, THD, household customers

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3980 Digital Transformation, Financing Microstructures, and Impact on Well-Being and Income Inequality

Authors: Koffi Sodokin

Abstract:

Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.

Keywords: financing microstructure, microinsurance, microfinance, digital finance, well-being, income inequality

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3979 Parametric Estimation of U-Turn Vehicles

Authors: Yonas Masresha Aymeku

Abstract:

The purpose of capacity modelling at U-turns is to develop a relationship between capacity and its geometric characteristics. In fact, the few models available for the estimation of capacity at different transportation facilities do not provide specific guidelines for median openings. For this reason, an effort is made to estimate the capacity by collecting the data sets from median openings at different lane roads in Hyderabad City, India. Wide difference (43% -59%) among the capacity values estimated by the existing models shows the limitation to consider for mixed traffic situations. Thus, a distinct model is proposed for the estimation of the capacity of U-turn vehicles at median openings considering mixed traffic conditions, which would further prompt to investigate the effect of different factors that might affect the capacity.

Keywords: geometric, guiddelines, median, vehicles

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3978 Political Connections, Business Strategy and Tax Aggressiveness: Evidence from China

Authors: Liqiang Chen

Abstract:

This study investigates the effects of political connections on the association between firms’ business strategy and their tax aggressiveness in an emerging economy such as China. By studying all public Chinese firms in the period from 2011 to 2017, we find that firms adopting innovative business strategy are more tax aggressive overall, but innovative firms with political connections are less tax aggressive compared to those without political connections. Moreover, we document several channels through which political connections affect the association between innovative business strategy and tax aggressiveness. In particular, we show that the mitigation effect of political connections on tax aggressiveness is stronger for innovative firms located in areas with a lower marketization index and for innovative firms with a lower leverage level or with less earnings management. Our results are robust to an instrumental variable approach to account for possible endogenous bias. Our study contributes to the understanding of firms’ tax behaviors in an emerging economy setting and suggests that there are costs associated with political connections, such as foregone tax saving opportunities, which are understudied in the prior literature.

Keywords: tax aggressiveness, business strategy, political connections, emerging economy

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3977 Solution to Riemann Hypothesis Critical Strip Zone Using Non-Linear Complex Variable Functions

Authors: Manojkumar Sabanayagam

Abstract:

The Riemann hypothesis is an unsolved millennium problem and the search for a solution to the Riemann hypothesis is to study the pattern of prime number distribution. The scope of this paper is to identify the solution for the critical strip and the critical line axis, which has the non-trivial zero solutions using complex plane functions. The Riemann graphical plot is constructed using a linear complex variable function (X+iY) and is applicable only when X>1. But the investigation shows that complex variable behavior has two zones. The first zone is the transformation zone, where the definition of the complex plane should be a non-linear variable which is the critical strip zone in the graph (X=0 to 1). The second zone is the transformed zone (X>1) defined using linear variables conventionally. This paper deals with the Non-linear function in the transformation zone derived using cosine and sinusoidal time lag w.r.t imaginary number ‘i’. The alternate complex variable (Cosθ+i Sinθ) is used to understand the variables in the critical strip zone. It is concluded that the non-trivial zeros present in the Real part 0.5 are because the linear function is not the correct approach in the critical strip. This paper provides the solution to Reimann's hypothesis.

Keywords: Reimann hypothesis, critical strip, complex plane, transformation zone

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3976 The Estimation Method of Stress Distribution for Beam Structures Using the Terrestrial Laser Scanning

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

Abstract:

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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3975 Channel Estimation for Orthogonal Frequency Division Multiplexing Systems over Doubly Selective Channels Base on DCS-DCSOMP Algorithm

Authors: Linyu Wang, Furui Huo, Jianhong Xiang

Abstract:

The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low SNR stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

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3974 Mobile Platform’s Attitude Determination Based on Smoothed GPS Code Data and Carrier-Phase Measurements

Authors: Mohamed Ramdani, Hassen Abdellaoui, Abdenour Boudrassen

Abstract:

Mobile platform’s attitude estimation approaches mainly based on combined positioning techniques and developed algorithms; which aim to reach a fast and accurate solution. In this work, we describe the design and the implementation of an attitude determination (AD) process, using only measurements from GPS sensors. The major issue is based on smoothed GPS code data using Hatch filter and raw carrier-phase measurements integrated into attitude algorithm based on vectors measurement using least squares (LSQ) estimation method. GPS dataset from a static experiment is used to investigate the effectiveness of the presented approach and consequently to check the accuracy of the attitude estimation algorithm. Attitude results from GPS multi-antenna over short baselines are introduced and analyzed. The 3D accuracy of estimated attitude parameters using smoothed measurements is over 0.27°.

Keywords: attitude determination, GPS code data smoothing, hatch filter, carrier-phase measurements, least-squares attitude estimation

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3973 Estimation of Chronic Kidney Disease Using Artificial Neural Network

Authors: Ilker Ali Ozkan

Abstract:

In this study, an artificial neural network model has been developed to estimate chronic kidney failure which is a common disease. The patients’ age, their blood and biochemical values, and 24 input data which consists of various chronic diseases are used for the estimation process. The input data have been subjected to preprocessing because they contain both missing values and nominal values. 147 patient data which was obtained from the preprocessing have been divided into as 70% training and 30% testing data. As a result of the study, artificial neural network model with 25 neurons in the hidden layer has been found as the model with the lowest error value. Chronic kidney failure disease has been able to be estimated accurately at the rate of 99.3% using this artificial neural network model. The developed artificial neural network has been found successful for the estimation of chronic kidney failure disease using clinical data.

Keywords: estimation, artificial neural network, chronic kidney failure disease, disease diagnosis

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3972 On the Cluster of the Families of Hybrid Polynomial Kernels in Kernel Density Estimation

Authors: Benson Ade Eniola Afere

Abstract:

Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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3971 Anisotropic Approach for Discontinuity Preserving in Optical Flow Estimation

Authors: Pushpendra Kumar, Sanjeev Kumar, R. Balasubramanian

Abstract:

Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving.

Keywords: optical flow, variational methods, computer vision, anisotropic operator

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3970 Functional Decomposition Based Effort Estimation Model for Software-Intensive Systems

Authors: Nermin Sökmen

Abstract:

An effort estimation model is needed for software-intensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

Keywords: functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis

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3969 Optical Flow Direction Determination for Railway Crossing Occupancy Monitoring

Authors: Zdenek Silar, Martin Dobrovolny

Abstract:

This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.

Keywords: background estimation, direction of optical flow, K-means clustering, objects detection, railway crossing monitoring, velocity vectors

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3968 The Long-Run Effects of In-Utero Exposure to Malaria: Evidence from the Brazilian Eradication Campaign

Authors: Henrique Veras De Paiva Fonseca

Abstract:

This paper investigates the long-term relationship between early life exposure to malaria and adult socioeconomic outcomes in Brazil. The identification strategy relies on exogenous variation in the risk of malaria outbreaks in different states and seasons of the year to identify early life exposure according to the timing and location of birth. Furthermore, Brazil has undergone a successful campaign of malaria eradication during the late 1950s, which allows for comparing outcomes of birth cohorts born just prior to and just after eradication to identify the extent of in utero exposure. Instrumental variables estimates find consistent negative treatment effects of in utero exposure to malaria on socioeconomic outcomes, such as educational attainment and health status. The effects are stronger for exposure during the first trimester of pregnancy than during other periods of gestation. Additionally, consistent with previous findings, men are more likely to exhibit larger long-term effects.

Keywords: malaria, exposure, eradication, instrumental variables, education, health

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3967 Neuronal Networks for the Study of the Effects of Cosmic Rays on Climate Variations

Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

Abstract:

The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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3966 Evaluation of Earthquake Induced Cost for Mid-Rise Buildings

Authors: Gulsah Olgun, Ozgur Bozdag, Yildirim Ertutar

Abstract:

This paper mainly focuses on performance assessment of buildings by associating the damage level with the damage cost. For this purpose a methodology is explained and applied to the representative mid-rise concrete building residing in Izmir. In order to consider uncertainties in occurrence of earthquakes, the structural analyses are conducted for all possible earthquakes in the region through the hazard curve. By means of the analyses, probability of the structural response being in different limit states are obtained and used to calculate expected damage cost. The expected damage cost comprises diverse cost components related to earthquake such as cost of casualties, replacement or repair cost of building etc. In this study, inter-story drift is used as an effective response variable to associate expected damage cost with different damage levels. The structural analysis methods performed to obtain inter story drifts are response spectrum method as a linear one, accurate push-over and time history methods to demonstrate the nonlinear effects on loss estimation. Comparison of the results indicates that each method provides similar values of expected damage cost. To sum up, this paper explains an approach which enables to minimize the expected damage cost of buildings and relate performance level to damage cost.

Keywords: expected damage cost, limit states, loss estimation, performance based design

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3965 Stagnation Point Flow Over a Stretching Cylinder with Variable Thermal Conductivity and Slip Conditions

Authors: M. Y. Malik, Farzana Khan

Abstract:

In this article, we discuss the behavior of viscous fluid near stagnation point over a stretching cylinder with variable thermal conductivity. The effects of slip conditions are also encountered. Thermal conductivity is considered as a linear function of temperature. By using homotopy analysis method and Fehlberg method we compare the graphical results for both momentum and energy equations. The effect of different parameters on velocity and temperature fields are shown graphically.

Keywords: slip conditions, stretching cylinder, heat generation/absorption, stagnation point flow, variable thermal conductivity

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3964 Using Seismic and GPS Data for Hazard Estimation in Some Active Regions in Egypt

Authors: Abdel-Monem Sayed Mohamed

Abstract:

Egypt rapidly growing development is accompanied by increasing levels of standard living particular in its urban areas. However, there is a limited experience in quantifying the sources of risk management in Egypt and in designing efficient strategies to keep away serious impacts of earthquakes. From the historical point of view and recent instrumental records, there are some seismo-active regions in Egypt, where some significant earthquakes had occurred in different places. The special tectonic features in Egypt: Aswan, Greater Cairo, Red Sea and Sinai Peninsula regions are the territories of a high seismic risk, which have to be monitored by up-to date technologies. The investigations of the seismic events and interpretations led to evaluate the seismic hazard for disaster prevention and for the safety of the dense populated regions and the vital national projects as the High Dam. In addition to the monitoring of the recent crustal movements, the most powerful technique of satellite geodesy GPS are used where geodetic networks are covering such seismo-active regions. The results from the data sets are compared and combined in order to determine the main characteristics of the deformation and hazard estimation for specified regions. The final compiled output from the seismological and geodetic analysis threw lights upon the geodynamical regime of these seismo-active regions and put Aswan and Greater Cairo under the lowest class according to horizontal crustal strains classifications. This work will serve a basis for the development of so-called catastrophic models and can be further used for catastrophic risk management. Also, this work is trying to evaluate risk of large catastrophic losses within the important regions including the High Dam, strategic buildings and archeological sites. Studies on possible scenarios of earthquakes and losses are a critical issue for decision making in insurance as a part of mitigation measures.

Keywords: b-value, Gumbel distribution, seismic and GPS data, strain parameters

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3963 Indoor Temperature Estimation with FIR Filter Using R-C Network Model

Authors: Sung Hyun You, Jeong Hoon Kim, Dae Ki Kim, Choon Ki Ahn

Abstract:

In this paper, we proposed a new strategy for estimating indoor temperature based on the modified resistance capacitance (R–C) network thermal dynamic model. Using minimum variance finite impulse response (FIR) filter, accurate indoor temperature estimation can be achieved. Our study is clarified by the experimental validation of the proposed indoor temperature estimation method. This experiment scenario environment is composed of a demand response (DR) server and home energy management system (HEMS) in a test bed.

Keywords: energy consumption, resistance-capacitance network model, demand response, finite impulse response filter

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3962 Hardware Implementation and Real-time Experimental Validation of a Direction of Arrival Estimation Algorithm

Authors: Nizar Tayem, AbuMuhammad Moinuddeen, Ahmed A. Hussain, Redha M. Radaydeh

Abstract:

This research paper introduces an approach for estimating the direction of arrival (DOA) of multiple RF noncoherent sources in a uniform linear array (ULA). The proposed method utilizes a Capon-like estimation algorithm and incorporates LU decomposition to enhance the accuracy of DOA estimation while significantly reducing computational complexity compared to existing methods like the Capon method. Notably, the proposed method does not require prior knowledge of the number of sources. To validate its effectiveness, the proposed method undergoes validation through both software simulations and practical experimentation on a prototype testbed constructed using a software-defined radio (SDR) platform and GNU Radio software. The results obtained from MATLAB simulations and real-time experiments provide compelling evidence of the proposed method's efficacy.

Keywords: DOA estimation, real-time validation, software defined radio, computational complexity, Capon's method, GNU radio

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3961 Reliability and Probability Weighted Moment Estimation for Three Parameter Mukherjee-Islam Failure Model

Authors: Ariful Islam, Showkat Ahmad Lone

Abstract:

The Mukherjee-Islam Model is commonly used as a simple life time distribution to assess system reliability. The model exhibits a better fit for failure information and provides more appropriate information about hazard rate and other reliability measures as shown by various authors. It is possible to introduce a location parameter at a time (i.e., a time before which failure cannot occur) which makes it a more useful failure distribution than the existing ones. Even after shifting the location of the distribution, it represents a decreasing, constant and increasing failure rate. It has been shown to represent the appropriate lower tail of the distribution of random variables having fixed lower bound. This study presents the reliability computations and probability weighted moment estimation of three parameter model. A comparative analysis is carried out between three parameters finite range model and some existing bathtub shaped curve fitting models. Since probability weighted moment method is used, the results obtained can also be applied on small sample cases. Maximum likelihood estimation method is also applied in this study.

Keywords: comparative analysis, maximum likelihood estimation, Mukherjee-Islam failure model, probability weighted moment estimation, reliability

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3960 Personality Traits of Students Effecting Entrepreneurial Intention

Authors: Muhammad Ali, Aamir Sohail, Umair Malik

Abstract:

Research in entrepreneurship has gained much attention in current academic environment. Youngsters are taking interest to start their own business in spite of risk matter. The objective of the study is to explain how various personality traits (personal attitude, locus of control, instrumental readiness and perceived behavioral control) are affecting entrepreneurial intention of students. The theory of planned behavior supports out study which explains that personal attractiveness, social norms and feasibility are the main factors that affect intentions of an individual. The sample data of 120 is collected from graduating batch of three reputed universities of Islamabad through questionnaires. Our results support the hypothesis that personality traits positively influence the entrepreneurial intention. We conclude from the study that many graduating students are willing to start a new venture, but most of them are likely to do a job in their respective fields. Risk factor also exists in their minds because in our country most people are risk-averse and they do not want to lose their money in case of loss.

Keywords: entrepreneurship, instrumental readiness, locus of control, personal attitude

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3959 Refined Procedures for Second Order Asymptotic Theory

Authors: Gubhinder Kundhi, Paul Rilstone

Abstract:

Refined procedures for higher-order asymptotic theory for non-linear models are developed. These include a new method for deriving stochastic expansions of arbitrary order, new methods for evaluating the moments of polynomials of sample averages, a new method for deriving the approximate moments of the stochastic expansions; an application of these techniques to gather improved inferences with the weak instruments problem is considered. It is well established that Instrumental Variable (IV) estimators in the presence of weak instruments can be poorly behaved, in particular, be quite biased in finite samples. In our application, finite sample approximations to the distributions of these estimators are obtained using Edgeworth and Saddlepoint expansions. Departures from normality of the distributions of these estimators are analyzed using higher order analytical corrections in these expansions. In a Monte-Carlo experiment, the performance of these expansions is compared to the first order approximation and other methods commonly used in finite samples such as the bootstrap.

Keywords: edgeworth expansions, higher order asymptotics, saddlepoint expansions, weak instruments

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3958 Interval Estimation for Rainfall Mean in Northeastern Thailand

Authors: Nitaya Buntao

Abstract:

This paper considers the problems of interval estimation for rainfall mean of the lognormal distribution and the delta-lognormal distribution in Northeastern Thailand. We present here the modified generalized pivotal approach (MGPA) compared to the modified method of variance estimates recovery (MMOVER). The performance of each method is examined in term of coverage probabilities and average lengths by Monte Carlo simulation. An extensive simulation study indicates that the MMOVER performs better than the MGPA approach in terms of the coverage probability; it results in highly accurate coverage probability.

Keywords: rainfall mean, interval estimation, lognormal distribution, delta-lognormal distribution

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3957 Consumers’ Responses to Non-Traditional Marketing Communication Strategies for Advertising Herbal Products

Authors: Chioma Ifeoma Agbasimelo, Stephen Afam Kenechukwu

Abstract:

The study examined consumers’ responses to non-traditional marketing communication strategies in advertising herbal products. The study identified the following non-traditional marketing communication strategies: (a) trado-instrumental marketing strategy, (b) trado-demonstrative marketing strategy, and (c) trado-iconographic marketing strategy. Anchored on the Black Box Theory, it adopted the survey design of three metropolises (Awka, Onitsha, and Nnewi) in Anambra State, Nigeria. Major findings indicated that among the identified strategies, the trado-instrumental marketing strategy is the most dominant strategy. Other strategies: (b) trado-demonstrative marketing strategy and (c) trado-iconographic marketing strategy are sparingly used in semi-urban cities. It also found that consumers’ preferences and adoption of non-traditional marketing communication were minimal. Based on the findings, there is a need to create a unified system of integration of both traditional and non-traditional marketing communication strategies due to technology interfaces.

Keywords: advertising, consumers’ responses, herbal products, non-traditional marketing communication strategies

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