Search results for: insurance estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2231

Search results for: insurance estimation

2111 Defects Estimation of Embedded Systems Components by a Bond Graph Approach

Authors: I. Gahlouz, A. Chellil

Abstract:

The paper concerns the estimation of system components faults by using an unknown inputs observer. To reach this goal, we used the Bond Graph approach to physical modelling. We showed that this graphical tool is allowing the representation of system components faults as unknown inputs within the state representation of the considered physical system. The study of the causal and structural features of the system (controllability, observability, finite structure, and infinite structure) based on the Bond Graph approach was hence fulfilled in order to design an unknown inputs observer which is used for the system component fault estimation.

Keywords: estimation, bond graph, controllability, observability

Procedia PDF Downloads 413
2110 Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model

Authors: Navid Daryasafar, Nima Farshidfar

Abstract:

In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

Procedia PDF Downloads 539
2109 Localization of Near Field Radio Controlled Unintended Emitting Sources

Authors: Nurbanu Guzey, S. Jagannathan

Abstract:

Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

Procedia PDF Downloads 526
2108 An Enhanced Floor Estimation Algorithm for Indoor Wireless Localization Systems Using Confidence Interval Approach

Authors: Kriangkrai Maneerat, Chutima Prommak

Abstract:

Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN). We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

Procedia PDF Downloads 418
2107 Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

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2106 A Novel Stator Resistance Estimation Method and Control Design of Speed-Sensorless Induction Motor Drives

Authors: N. Ben Si Ali, N. Benalia, N. Zarzouri

Abstract:

Speed sensorless systems are intensively studied during recent years; this is mainly due to their economical benefit and fragility of mechanical sensors and also the difficulty of installing this type of sensor in many applications. These systems suffer from instability problems and sensitivity to parameter mismatch at low speed operation. In this paper an analysis of adaptive observer stability with stator resistance estimation is given.

Keywords: motor drive, sensorless control, adaptive observer, stator resistance estimation

Procedia PDF Downloads 375
2105 Advocacy for Increasing Health Care Budget in Parepare City with DALY Approach: Case Study on Improving Public Health Insurance Budget

Authors: Kasman, Darmawansyah, Alimin Maidin, Amran Razak

Abstract:

Background: In decentralization, advocacy is needed to increase the health budget in Parepare District. One of the advocacy methods recommended by the World Bank is the economic loss approach. Methods: This research is observational in the field of health economics that contributes directly to the magnitude of the economic loss of the community and the government and provides advocacy to the executive and legislative to see the harm it causes. Results: The research results show the amount of direct cost, which consists of household expenditure for transport Rp.295,865,500. Indirect Cost of YLD of Rp.14.688.000, and YLL of Rp.28.986.336.00, so the amount of DALY is Rp.43.674.336.000. The total economic loss of Rp.43.970.201.500. These huge economic losses can be prevented by increasing the allocation of health budgets for promotive and preventive efforts and expanding the coverage of health insurance for the community. Conclusion: There is a need to advocate the executive and legislative about the importance of guarantee on public health financing by conducting studies in terms of economic losses so that all strategic alliances believe that health is an investment.

Keywords: advocacy, economic lost, health insurance, economic losses

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2104 Unintended Health Inequity: Using the Relationship Between the Social Determinants of Health and Employer-Sponsored Health Insurance as a Catalyst for Organizational Development and Change

Authors: Dinamarie Fonzone

Abstract:

Employer-sponsored health insurance (ESI) strategic decision-making processes rely on financial analysis to guide leadership in choosing plans that will produce optimal organizational spending outcomes. These financial decision-making methods have not abated ESI costs. Previously unrecognized external social determinants, the impact on ESI plan spending, and other organizational strategies are emerging and are important considerations for organizational decision-makers and change management practitioners. The purpose of thisstudy is to examine the relationship between the social determinants of health (SDoH), employer-sponsored health insurance (ESI) plans, andthe unintended consequence of health inequity. A quantitative research design using selectemployee records from an existing employer human capital management database will be analyzed. Statistical regressionmethods will be used to study the relationships between certainSDoH (employee income, neighborhood geographic living area, and health care access) and health plan utilization, cost, and chronic disease prevalence. The discussion will include an application of the social gradient of health theory to the study findings, organizational transformation through changes in ESI decision-making mental models, and the connection of ESI health inequity to organizational development and changediversity, equity, and inclusion strategies.

Keywords: employer-sponsored health insurance, social determinants of health, health inequity, mental models, organizational development, organizational change, social gradient of health theory

Procedia PDF Downloads 107
2103 Contrasting The Water Consumption Estimation Methods

Authors: Etienne Alain Feukeu, L. W. Snyman

Abstract:

Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.

Keywords: water scarcity, water estimation, water prediction, water forecast.

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2102 Variogram Fitting Based on the Wilcoxon Norm

Authors: Hazem Al-Mofleh, John Daniels, Joseph McKean

Abstract:

Within geostatistics research, effective estimation of the variogram points has been examined, particularly in developing robust alternatives. The parametric fit of these variogram points which eventually defines the kriging weights, however, has not received the same attention from a robust perspective. This paper proposes the use of the non-linear Wilcoxon norm over weighted non-linear least squares as a robust variogram fitting alternative. First, we introduce the concept of variogram estimation and fitting. Then, as an alternative to non-linear weighted least squares, we discuss the non-linear Wilcoxon estimator. Next, the robustness properties of the non-linear Wilcoxon are demonstrated using a contaminated spatial data set. Finally, under simulated conditions, increasing levels of contaminated spatial processes have their variograms points estimated and fit. In the fitting of these variogram points, both non-linear Weighted Least Squares and non-linear Wilcoxon fits are examined for efficiency. At all levels of contamination (including 0%), using a robust estimation and robust fitting procedure, the non-weighted Wilcoxon outperforms weighted Least Squares.

Keywords: non-linear wilcoxon, robust estimation, variogram estimation, wilcoxon norm

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2101 Impacts of Public Insurance on Health Access and Outcomes: Evidence from India

Authors: Titir Bhattacharya, Tanika Chakraborty, Prabal K. De

Abstract:

Maternal and child health continue to be a significant policy focus in developing countries, including India. An emerging model in health care is the creation of public and private partnerships. Since the construction of physical infrastructure is costly, governments at various levels have tried to implement social health insurance schemes where a trust calculates insurance premiums and medical payments. Typically, qualifying families get full subsidization of the premium and get access to private hospitals, in addition to low cost public hospitals, for their tertiary care needs. We analyze one such pioneering social insurance scheme in the Indian state of Andhra Pradesh (AP). The Rajiv Aarogyasri program (RA) was introduced by the Government of AP on a pilot basis in 2007 and implemented in 2008. In this paper, we first examine the extent to which access to reproductive health care changed. For example, the RA scheme reimburses hospital deliveries leading us to expect an increase in institutional deliveries, particularly in private hospitals. Second, we expect an increase in institutional deliveries to also improve child health outcomes. Hence, we estimate if the program improved infant and child mortality. We use District Level Health Survey data to create annual birth cohorts from 2000-2015. Since AP was the only state in which such a state insurance program was implemented, the neighboring states constituted a plausible control group. Combined with the policy timing, and the year of birth, we employ a difference-indifference strategy to identify the effects of RA on the residents of AP. We perform several checks against threats to identification, including testing for pre-treatment trends between the treatment and control states. We find that the policy significantly lowered infant and child mortality in AP. We also find that deliveries in private hospitals increased, and government hospitals decreased, showing a substitution effect of the relative price change. Finally, as expected, out-of-pocket costs declined for the treatment group. However, we do not find any significant effects for usual preventive care such as vaccination, showing that benefits of insurance schemes targeted at the tertiary level may not trickle down to the primary care level.

Keywords: public health insurance, maternal and child health, public-private choice

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2100 Combined Localization, Beamforming, and Interference Threshold Estimation in Underlay Cognitive System

Authors: Omar Nasr, Yasser Naguib, Mohamed Hafez

Abstract:

This paper aims at providing an innovative solution for blind interference threshold estimation in an underlay cognitive network to be used in adaptive beamforming by secondary user Transmitter and Receiver. For the task of threshold estimation, blind detection of modulation and SNR are used. For the sake of beamforming several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as LCMV (Linear Constraint Minimum Variance) and MVDR (Minimum Variance Distortion less) are also proposed and compared. The idea of just nulling the primary user after knowledge of its location is discussed against the idea of working under interference threshold.

Keywords: cognitive radio, underlay, beamforming, MUSIC, MVDR, LCMV, threshold estimation

Procedia PDF Downloads 582
2099 Simulation and Experimental Study on Tensile Force Measurement of PS Tendons Using an Embedded EM Sensor

Authors: ByoungJoon Yu, Junkyeong Kim, Seunghee Park

Abstract:

The tensile force estimation PS tendons is in great demand on monitoring the structural health condition of PSC girder bridges. Measuring the tensile force of the PS tendons inside the PSC girder using conventional methods is hard due to its location. In this paper, an embedded EM sensor based tensile force estimation of PS tendon was carried out by measuring the permeability of the PS tendons in PSC girder. The permeability is changed due to the induced tensile force by the magneto-elastic effect and the effect then lead to the gradient change of the B-H curve. An experiment was performed to obtain the signals from the EM sensor using three down-scaled PSC girder models. The permeability of PS tendons was proportionally decreased according to the increase of the tensile forces. To verify the experiment results, a simulation of tensile force estimation will be conducted in further study. Consequently, it is expected that both the experiment results and the simulation results increase the accuracy of the tensile force estimation, and then it could be one of the solutions for evaluating the performance of PSC girder.

Keywords: tensile force estimation, embedded EM sensor, PSC girder, EM sensor simulation, cross section loss

Procedia PDF Downloads 479
2098 Introduction of Robust Multivariate Process Capability Indices

Authors: Behrooz Khalilloo, Hamid Shahriari, Emad Roghanian

Abstract:

Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices.

Keywords: multivariate process capability indices, robust M-estimator, outlier, multivariate quality control, statistical quality control

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2097 The Digital Transformation of Life Insurance Sales in Iran With the Emergence of Personal Financial Planning Robots; Opportunities and Challenges

Authors: Pedram Saadati, Zahra Nazari

Abstract:

Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

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2096 Exploring Affordable Care Practs in Nigeria’s Health Insurance Discourse

Authors: Emmanuel Chinaguh, Kehinde Adeosun

Abstract:

Nigerians die untimely, with 55.75 years of life expectancy, which is 17.45 below the world average of 73.2 (Worldometer, 2020). This is due, among other factors, to the country's limited access to high-quality healthcare. To increase access to good and affordable healthcare services, the National Health Insurance Authority (NHIA) Bill 2022 – which repealed the National Health Insurance Scheme Act 2004 – was passed into law. Applying Jacob Mey’s (2001) pragmatics act (pract) theory, this study explores how NHIA seeks to actualise these healthcare goals by characterising the general situational prototype or pragmemes and pragmatic acts in institutional communications. Data was sourced from the NHIA operational guidelines, which has 147 pages and four sections, and shared posters on NHIA Nigeria Twitter Handle with 14,200 followers. Digital humanities tools, like AntConc and Voyant, were engaged in the data analysis for text encoding and data visualisation. This study identifies these discourse tokens in the data: advertisement and programmes, standards and accreditation, records and information, and offences and penalties. Advertisement and programmes pract facilitating, propagating, prospecting, advising and informing; standards and accreditation, and records and information pract stating, informing and instructing; and offences and penalties pract stating and sanctioning. These practs combined to advance the goals of affordable care and universal accessibility to quality healthcare services. The pragmatic acts were marked by these pragmatic tools: shared situational knowledge (SSK), relevance (REL), reference (REF) and inference (INF). This paper adds to the understanding of health insurance discourse in Nigeria as a mediated social practice that promotes the health of Nigerians.

Keywords: affordable care, NHIA, Nigeria’s health insurance discourse, pragmatic acts.

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2095 Channel Estimation Using Deep Learning for Reconfigurable Intelligent Surfaces-Assisted Millimeter Wave Systems

Authors: Ting Gao, Mingyue He

Abstract:

Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

Procedia PDF Downloads 150
2094 A New Criterion Using Pose and Shape of Objects for Collision Risk Estimation

Authors: DoHyeung Kim, DaeHee Seo, ByungDoo Kim, ByungGil Lee

Abstract:

As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.

Keywords: collision risk, pose, shape, fuzzy logic

Procedia PDF Downloads 529
2093 Classic Training of a Neural Observer for Estimation Purposes

Authors: R. Loukil, M. Chtourou, T. Damak

Abstract:

This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

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2092 Evidence on the Nature and Extent of Fall in Oil Prices on the Financial Performance of Listed Companies: A Ratio Analysis Case Study of the Insurance Sector in the UAE

Authors: Pallavi Kishore, Mariam Aslam

Abstract:

The sharp decline in oil prices that started in 2014 affected most economies in the world either positively or negatively. In some economies, particularly the oil exporting countries, the effects were felt immediately. The Gulf Cooperation Council’s (GCC henceforth) countries are oil and gas-dependent with the largest oil reserves in the world. UAE (United Arab Emirates) has been striving to diversify away from oil and expects higher non-oil growth in 2018. These two factors, falling oil prices and the economy strategizing away from oil dependence, make a compelling case to study the financial performance of various sectors in the economy. Among other sectors, the insurance sector is widely recognized as an important indicator of the health of the economy. An expanding population, surge in construction and infrastructure, increased life expectancy, greater expenditure on automobiles and other luxury goods translate to a booming insurance sector. A slow-down of the insurance sector, on the other hand, may indicate a general slow-down in the economy. Therefore, a study on the insurance sector will help understand the general nature of the current economy. This study involves calculations and comparisons of ratios pre and post the fall in oil prices in the insurance sector in the UAE. A sample of 33 companies listed on the official stock exchanges of UAE-Dubai Financial Market and Abu Dhabi Stock Exchange were collected and empirical analysis employed to study the financial performance pre and post fall in oil prices. Ratios were calculated in 5 categories: Profitability, Liquidity, Leverage, Efficiency, and Investment. The means pre- and post-fall are compared to conclude that the profitability ratios including ROSF (Return on Shareholder Funds), ROCE (Return on Capital Employed) and NPM (Net Profit Margin) have all taken a hit. Parametric tests, including paired t-test, concludes that while the fall in profitability ratios is statistically significant, the other ratios have been quite stable in the period. The efficiency, liquidity, gearing and investment ratios have not been severely affected by the fall in oil prices. This may be due to the implementation of stronger regulatory policies and is a testimony to the diversification into the non-oil economy. The regulatory authorities can use the findings of this study to ensure transparency in revealing financial information to the public and employ policies that will help further the health of the economy. The study will also help understand which areas within the sector could benefit from more regulations.

Keywords: UAE, insurance sector, ratio analysis, oil price, profitability, liquidity, gearing, investment, efficiency

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2091 Off-Line Parameter Estimation for the Induction Motor Drive System

Authors: Han-Woong Ahn, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

Abstract:

It is important to accurately identify machine parameters for direct vector control. To obtain the parameter values, traditional methods can be used such as no-load and rotor locked tests. However, there are many differences between values obtained from the traditional tests and actual values. In addition, there are drawbacks that additional equipment and cost are required for the experiment. Therefore, it is hard to temporary operation to estimate induction motor parameters. Therefore, this paper deals with the estimation algorithm of induction motor parameters without a motor operation and the measurement from additional equipment such as sensors and dynamometer. The validity and usefulness of the estimation algorithm considering inverter nonlinearity is verified by comparing the conventional method with the proposed method.

Keywords: induction motor, parameter, off-line estimation, inverter nonlinearity

Procedia PDF Downloads 529
2090 Deep Learning-Based Channel Estimation for RIS-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System

Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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2089 Signal Estimation and Closed Loop System Performance in Atrial Fibrillation Monitoring with Communication Channels

Authors: Mohammad Obeidat, Ayman Mansour

Abstract:

In this paper a unique issue rising from feedback control of Atrial Fibrillation monitoring system with embedded communication channels has been investigated. One of the important factors to measure the performance of the feedback control closed loop system is disturbance and noise attenuation factor. It is important that the feedback system can attenuate such disturbances on the atrial fibrillation heart rate signals. Communication channels depend on network traffic conditions and deliver different throughput, implying that the sampling intervals may change. Since signal estimation is updated on the arrival of new data, its dynamics actually change with the sampling interval. Consequently, interaction among sampling, signal estimation, and the controller will introduce new issues in remotely controlled Atrial Fibrillation system. This paper treats a remotely controlled atrial fibrillation system with one communication channel which connects between the heart rate and rhythm measurements to the remote controller. Typical and optimal signal estimation schemes is represented by a signal averaging filter with its time constant derived from the step size of the signal estimation algorithm.

Keywords: atrial fibrillation, communication channels, closed loop, estimation

Procedia PDF Downloads 378
2088 Effects of Work Stress and Chinese Indigenous Ren-Qing Shi-Ku Social Wisdom on Emotional Exhaustion, Work Satisfaction and Well-Being of Insurance Workers

Authors: Wang Chung-Kwei, Lo Kuo Ying

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This study is aimed to examine main and moderation effect of Chinese traditional social wisdom ‘Ren-qing Shi-kuo’ on the adjustment of insurance workers. Rationale: Ren-qing Shi-ku as a social wisdom has been emphasized and practiced by collective-oriented Chinese for thousand years. The concept of‘Ren-qing Shi-ku’includes values, beliefs and behavior rituals, which helps Chinese to cope with interpersonal conflicts in a sophisticated and closely tied collective society. Based on interview and literature review, we found out Chinese still emphasized the importance of ‘Ren-qing Shi-ku’. The concepts contains five factors, including ‘proper emotion display’, ‘social ritual abiding’, ‘ make empathetic concession’, ‘harmonious and proper behavior’ and ‘tolerance for the interest of the whole’. We developed an indigenous ‘Ren-qing Shi-ku’scale based on interview data and a survey on social worker students. Research methods: We conduct a dyad survey between 294 insurance worker and their supervisors. Insurance workers’ response on ‘Ren-qing Shi-ku,emotion labor, emotional exhaustion, work stress and load, work satisfaction and well-being were collected. We also ask their supervisors to rate these workers ‘empathy, social rule abiding, work performance, and Ren-qing Shi-ku performance. Results: Students’self-ratings on Ren-qing Shi-ku scale are positively correlated with rating from their supervisors on all above indexes. Workers who have higher Ren-qing Shi-ku score also have lower work stress and emotion exhaustion, higher work satisfaction and well-being, more emotion deep acting. They also have higher work performance, social rule abiding, and Ren-qing Shi-ku performance rating from their supervisor. The finding of this study suggested Ren-qing Shi-ku is an effective indicator on insurance workers ‘adjustment. Since Ren-qing Shi-ku is trainable, we suggested that Ren-qing Shi-ku training might be beneficial to service industry in a collective-oriented culture.

Keywords: work stress, Ren-qing Shi-ku, emotional exhaustion, work satisfaction, well-being

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2087 Mathematics Model Approaching: Parameter Estimation of Transmission Dynamics of HIV and AIDS in Indonesia

Authors: Endrik Mifta Shaiful, Firman Riyudha

Abstract:

Acquired Immunodeficiency Syndrome (AIDS) is one of the world's deadliest diseases caused by the Human Immunodeficiency Virus (HIV) that infects white blood cells and cause a decline in the immune system. AIDS quickly became a world epidemic disease that affects almost all countries. Therefore, mathematical modeling approach to the spread of HIV and AIDS is needed to anticipate the spread of HIV and AIDS which are widespread. The purpose of this study is to determine the parameter estimation on mathematical models of HIV transmission and AIDS using cumulative data of people with HIV and AIDS each year in Indonesia. In this model, there are parameters of r ∈ [0,1) which is the effectiveness of the treatment in patients with HIV. If the value of r is close to 1, the number of people with HIV and AIDS will decline toward zero. The estimation results indicate when the value of r is close to unity, there will be a significant decline in HIV patients, whereas in AIDS patients constantly decreases towards zero.

Keywords: HIV, AIDS, parameter estimation, mathematical models

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2086 Blind Super-Resolution Reconstruction Based on PSF Estimation

Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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2085 Parameter Estimation via Metamodeling

Authors: Sergio Haram Sarmiento, Arcady Ponosov

Abstract:

Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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2084 Density-based Denoising of Point Cloud

Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

Abstract:

Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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2083 Overhead Reduction by Channel Estimation Using Linear Interpolation for Single Carrier Frequency Domain Equalization Transmission

Authors: Min-Su Song, Haeng-Bok Kil, Eui-Rim Jeong

Abstract:

This paper proposes a new method to reduce the overhead by pilots for single carrier frequency domain equalization (SC-FDE) transmission. In the conventional SC-FDE transmission structure, the overhead by transmitting pilot is heavy because the pilot are transmitted at every SC-FDE block. The proposed SC-FDE structure has fewer pilots and many SC-FCE blocks are transmitted between pilots. The channel estimation and equalization is performed at the pilot period and the channels between pilots are estimated through linear interpolation. This reduces the pilot overhead by reducing the pilot transmission compared with the conventional structure, and enables reliable channel estimation and equalization.

Keywords: channel estimation, linear interpolation, pilot overhead, SC-FDE

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2082 Approximation of the Time Series by Fractal Brownian Motion

Authors: Valeria Bondarenko

Abstract:

In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates.

Keywords: fractional Brownian motion, Gausssian processes, approximation, time series, estimation of properties of the model

Procedia PDF Downloads 376