Search results for: TensorFlow probability

Authors: D. De-León-Escobedo, D. J. Delgado-Hernández, S. Pérez

Abstract:

A probabilistic formulation to assess the slopes safety under the hazard of strong storms is presented and illustrated through a slope in Mexico. The formulation is based on the classical safety factor (SF) used in practice to appraise the slope stability, but it is introduced the treatment of uncertainties, and the slope failure probability is calculated as the probability that SF<1. As the main hazard is the rainfall on the area, statistics of rainfall intensity and duration are considered and modeled with an exponential distribution. The expected life-cycle cost is assessed by considering a monetary value on the slope failure consequences. Alternative mitigation measures are simulated, and the formulation is used to get the measures driving to the optimal one (minimum life-cycle costs). For the example, the optimal mitigation measure is the reduction on the slope inclination angle.

Keywords: expected life-cycle cost, failure probability, slopes failure, storms

Procedia PDF Downloads 161

Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

Abstract:

Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: cathode spot, vacuum arc discharge, transverse magnetic field, random walk

Procedia PDF Downloads 434

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

Procedia PDF Downloads 274

Authors: Augustine Okolie, Johannes Müller, Mirjam Kretzchmar

Abstract:

We adopt a maximum-likelihood framework to estimate parameters of a stochastic susceptible-infected-recovered (SIR) model with contact tracing on a rooted random tree. Given the number of detectees per index case, our estimator allows to determine the degree distribution of the random tree as well as the tracing probability. Since we do not discover all infectees via contact tracing, this estimation is non-trivial. To keep things simple and stable, we develop an approximation suited for realistic situations (contract tracing probability small, or the probability for the detection of index cases small). In this approximation, the only epidemiological parameter entering the estimator is the basic reproduction number R0. The estimator is tested in a simulation study and applied to covid-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical covid-19 data, we are able to compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution meet the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency on the reproduction number.

Keywords: stochastic SIR model on graph, contact tracing, branching process, parameter inference

Procedia PDF Downloads 79

Authors: Lokesh Varshney, R. K. Saket

Abstract:

This paper presents reliability indices evaluation of the rotor core magnetization of the induction motor operated as a self-excited induction generator by using probability distribution approach and Monte Carlo simulation. Parallel capacitors with calculated minimum capacitive value across the terminals of the induction motor operating as a SEIG with unregulated shaft speed have been connected during the experimental study. A three phase, 4 poles, 50Hz, 5.5 hp, 12.3A, 230V induction motor coupled with DC Shunt Motor was tested in the electrical machine laboratory with variable reactive loads. Based on this experimental study, it is possible to choose a reliable induction machine operating as a SEIG for unregulated renewable energy application in remote area or where grid is not available. Failure density function, cumulative failure distribution function, survivor function, hazard model, probability of success and probability of failure for reliability evaluation of the three phase induction motor operating as a SEIG have been presented graphically in this paper.

Keywords: residual magnetism, magnetization curve, induction motor, self excited induction generator, probability distribution, Monte Carlo simulation

Procedia PDF Downloads 559

Authors: Ali Razmi, Saeed Golian

Abstract:

Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.

Keywords: climate change, climate variables, copula, joint probability

Procedia PDF Downloads 361

Authors: Ali S. Gargoum

Abstract:

Graphical modeling plays an important role in providing efficient probability calculations in high dimensional problems (computational efficiency). In this paper, we address one of such problems where we discuss fragmenting puff models and some distributional assumptions concerning models for the instantaneous, emission readings and for the fragmenting process. A graphical representation in terms of a junction tree of the conditional probability breakdown of puffs and puff fragments is proposed.

Keywords: graphical models, influence diagrams, junction trees, Bayesian nets

Procedia PDF Downloads 396

Authors: Bohli Afef

Abstract:

The fifth-generation (5G) wireless systems is featured by extreme densities of cell stations to overcome the higher future demand. Hence, interference management is a crucial challenge in 5G ultra-dense cellular networks. In contrast to the classical inter-cell interference coordination approach, which is no longer fit for the high density of cell-tiers, this paper proposes a novel virtual coordination based on the dynamic common cognitive monitor channel protocol to deal with the inter-cell interference issue. A tractable and flexible model for the coverage probability of a typical user is developed through the use of the stochastic geometry model. The analyses of the performance of the suggested protocol are illustrated both analytically and numerically in terms of coverage probability.

Keywords: ultra dense heterogeneous networks, dynamic common channel protocol, cognitive radio, stochastic geometry, coverage probability

Procedia PDF Downloads 326

Authors: Yaping Zhao

Abstract:

In the present study, the exact solutions for the steady response of quasi-linear systems under non-white wide-band random excitation are considered by means of the stochastic averaging method. The non linearity of the systems contains the power-law damping and the cross-product term of the power-law damping and displacement. The drift and diffusion coefficients of the Fokker-Planck-Kolmogorov (FPK) equation after averaging are obtained by a succinct approach. After solving the averaged FPK equation, the joint probability density function and the marginal probability density function in steady state are attained. In the process of resolving, the eigenvalue problem of ordinary differential equation is handled by integral equation method. Some new results are acquired and the novel method to deal with the problems in nonlinear random vibration is proposed.

Keywords: random vibration, stochastic averaging method, FPK equation, transition probability density

Procedia PDF Downloads 506

Authors: Viriyavudh Sim, Woo Young Jung

Abstract:

The failure of roof cladding mostly occurs due to the failing of the connection between claddings and purlins, which is the pull-out of the screw connecting the two parts when the pull-out load, i.e. typhoon, is higher than the resistance of the connection screw. As typhoon disasters in Korea are constantly on the rise, probability risk assessment (PRA) has become a vital tool to evaluate the performance of civil structures. In this study, we attempted to determine the fragility of roof cladding with the screw connection. Experimental study was performed to evaluate the pull-out resistance of screw joints between honeycomb panels and back frames. Subsequently, by means of Monte Carlo Simulation method, probability of failure for these types of roof cladding was determined. The results that the failure of roof cladding was depends on their location on the roof, for example, the edge most panel has the highest probability of failure.

Keywords: Monte Carlo Simulation, roof cladding, screw pull-out strength, wind fragility

Procedia PDF Downloads 253

Authors: Selvavinayagan Babiharan

Abstract:

This research aims to develop a deep learning platform to enhance mathematics education for secondary students in Sri Lanka. The platform will be designed to incorporate interactive and user-friendly features to engage students in active learning and promote their mathematical skills. The proposed platform will be developed using TensorFlow and Keras, two widely used deep learning frameworks. The system will be trained on a large dataset of math problems, which will be collected from Sri Lankan school curricula. The results of this research will contribute to the improvement of mathematics education in Sri Lanka and provide a valuable tool for teachers to enhance the learning experience of their students.

Keywords: information technology, education, machine learning, mathematics

Procedia PDF Downloads 84

Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

Abstract:

This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

Procedia PDF Downloads 335

Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

Abstract:

A packet loss probability (PLP) estimation filter with finite memory structure is proposed to estimate the packet rate mean and variance of the input traffic process in real-time while removing undesired system and measurement noises. The proposed PLP estimation filter is developed under a weighted least square criterion using only the finite traffic measurements on the most recent window. The proposed PLP estimation filter is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. A guideline for choosing appropriate window length is described since it can affect significantly the estimation performance. Using computer simulations, the proposed PLP estimation filter is shown to be superior to the Kalman filter for the temporarily uncertain system. One possible explanation for this is that the proposed PLP estimation filter can have greater convergence time of a filtered estimate as the window length M decreases.

Keywords: packet loss probability estimation, finite memory filter, infinite memory filter, Kalman filter

Procedia PDF Downloads 674

Authors: Bawadi M. A., Abbad J. A., Baras E. A.

Abstract:

This study was conducted to assess wind energy resources in the area of Al-Adwas Ras-Huwirah Hadhramout Governorate, Yemen, through using statistical calculations, the Weibull model and SPSS program were used in the monthly and the annual to analyze the wind energy resource; the convergence of wind energy; turbine efficiency in the selected area. Wind speed data was obtained from NASA over a period of ten years (2010-2019) and at heights of 50 m above ground level. Probability distributions derived from wind data and their distribution parameters are determined. The density probability function is fitted to the measured probability distributions on an annual basis. This study also involves locating preliminary sites for wind farms using Geographic Information System (GIS) technology. This further leads to maximizing the output energy from the most suitable wind turbines in the proposed site.

Keywords: wind speed analysis, Yemen wind energy, wind power density, Weibull distribution model

Procedia PDF Downloads 84

Authors: Tolulope Aremu

Abstract:

This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

Procedia PDF Downloads 34

Authors: Weichao Yu, Kai Wen, Weihe Huang, Yang Yang, Jing Gong

Abstract:

Metal-loss corrosion is a major threat to the safety and integrity of gas pipelines as it may result in the burst failures which can cause severe consequences that may include enormous economic losses as well as the personnel casualties. Therefore, it is important to ensure the corroding pipeline integrity and efficiency, considering the value of wall thickness, which plays an important role in the failure probability of corroding pipeline. Actually, the wall thickness is controlled during pipe purchase stage. For example, the API_SPEC_5L standard regulates the allowable tolerance of the wall thickness from the specified value during the pipe purchase. The allowable wall thickness tolerance will be used to determine the wall thickness distribution characteristic such as the mean value, standard deviation and distribution. Taking the uncertainties of the input variables in the burst limit-state function into account, the reliability approach rather than the deterministic approach will be used to evaluate the failure probability. Moreover, the cost of pipe purchase will be influenced by the allowable wall thickness tolerance. More strict control of the wall thickness usually corresponds to a higher pipe purchase cost. Therefore changing the wall thickness tolerance will vary both the probability of a burst failure and the cost of the pipe. This paper describes an approach to optimize the wall thickness tolerance considering both the safety and economy of corroding pipelines. In this paper, the corrosion burst limit-state function in Annex O of CSAZ662-7 is employed to evaluate the failure probability using the Monte Carlo simulation technique. By changing the allowable wall thickness tolerance, the parameters of the wall thickness distribution in the limit-state function will be changed. Using the reliability approach, the corresponding variations in the burst failure probability will be shown. On the other hand, changing the wall thickness tolerance will lead to a change in cost in pipe purchase. Using the variation of the failure probability and pipe cost caused by changing wall thickness tolerance specification, the optimal allowable tolerance can be obtained, and used to define pipe purchase specifications.

Keywords: allowable tolerance, corroding pipeline segment, operation cost, production cost, reliability approach

Procedia PDF Downloads 396

Authors: Seon Soon Choi

Abstract:

The principal purpose of this paper is to find the influence of maximum fatigue load on the probabilistic aspect of fatigue crack propagation life at a specified grown crack in magnesium alloys. The experiments of fatigue crack propagation are carried out in laboratory air under different conditions of the maximum fatigue loads to obtain the fatigue crack propagation data for the statistical analysis. In order to analyze the probabilistic aspect of fatigue crack propagation life, the goodness-of fit test for probability distribution of the fatigue crack propagation life at a specified grown crack is implemented through Anderson-Darling test. The good probability distribution of the fatigue crack propagation life is also verified under the conditions of the maximum fatigue loads.

Keywords: fatigue crack propagation life, magnesium alloys, maximum fatigue load, probability

Procedia PDF Downloads 391

Authors: M. A. Tayfun, M. A. Alkhalidi

Abstract:

The exact theoretical expression describing the probability distribution of nonlinear sea-surface elevations derived from the second-order narrowband model has a cumbersome form that requires numerical computations, not well-disposed to theoretical or practical applications. Here, the same narrowband model is re-examined to develop a simpler closed-form approximation suitable for theoretical and practical applications. The salient features of the approximate form are explored, and its relative validity is verified with comparisons to other readily available approximations, and oceanic data.

Keywords: ocean waves, probability distributions, second-order nonlinearities, skewness coefficient, wave steepness

Procedia PDF Downloads 432

Authors: Yoshiaki Shikata

Abstract:

A prioritized processor-sharing (PS) system with a maximum permissible sojourn time (MPST) is proposed. In this PS system, a higher-priority request is allocated a larger service ratio than a lower-priority request. Moreover, each request receiving service is guaranteed the maximum permissible sojourn time determined by each priority class, regardless of its service time. Arriving requests that cannot receive service due to this guarantee are rejected. We further propose a guarantee method for implementing such a system, and discuss performance evaluation procedures for the resulting system. Practical performance measures, such as the relationships between the loss probability or mean sojourn time of each class request and the maximum permissible sojourn time are evaluated via simulation. At the arrival of each class request, its acceptance or rejection is judged using extended sojourn times of all requests receiving service in the server. As the MPST increases, the mean sojourn time increases almost linearly. However, the logarithm of the loss probability decreases almost linearly. Moreover with an MPST, the difference in the mean sojourn time for different MPSTs increases with the traffic rate. Conversely, the difference in the loss probability for different MPSTs decreases as the traffic rate increases.

Keywords: prioritized processor sharing, priority ratio, permissible sojourn time, loss probability, mean sojourn time, simulation

Procedia PDF Downloads 193

Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina

Procedia PDF Downloads 137

Authors: Francis Mugabi, Kevin Duffy, Joseph J. Y. T Mugisha, Obiora Collins

Abstract:

Bluetongue virus (BTV) has 27 serotypes, with some of them coexisting in patchy (different) environments, which make its control difficult. Wind-aided midge movement is a known mechanism in the spread of BTV. However, its effects on the probability of coexistence of multiple BTV serotypes are not clear. Deterministic and stochastic models for r BTV serotypes in n discrete patches connected by midge and/or cattle movement are formulated and analyzed. For the deterministic model without midge and cattle movement, using the comparison principle, it is shown that if the patch reproduction number R0 < 1, i=1,2,...,n, j=1,2,...,r, all serotypes go extinct. If R^j_i0>1, competitive exclusion takes place. Using numerical simulations, it is shown that when the n patches are connected by midge movement, coexistence takes place. To account for demographic and movement variability, the deterministic model is transformed into a continuous-time Markov chain stochastic model. Utilizing a multitype branching process, it is shown that the midge movement can have a large effect on the probability of coexistence of multiple BTV serotypes. The probability of coexistence can be brought to zero when the control interventions that directly kill the adult midges are applied. These results indicate the significance of wind-aided midge movement and vector control interventions on the coexistence and control of multiple BTV serotypes in patchy environments.

Keywords: bluetongue virus, coexistence, multiple serotypes, midge movement, branching process

Procedia PDF Downloads 152

Authors: Petr Gurný

Abstract:

One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the credit-scoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: credit-scoring models, multidimensional subordinated Lévy model, probability of default

Procedia PDF Downloads 456

Authors: Mohammad Noor Hisham Osman, Ahmed Razman Abdul Latiff, Zaidi Mat Daud, Zulkarnain Muhamad Sori

Abstract:

The problem that Malaysian auditors do not issue going concern opinion (GC opinion) to seriously financially distressed companies is still a pressing issue. Policy makers, particularly the Financial Statement Review Committee (FSRC) of Malaysian Institute of Accountant, have raised this issue as early as in 2009. Similar problem happened in the US, UK, and many developing countries. It is important for auditors to issue GC opinion properly because such opinion is one signal about the viability of a company much needed by stakeholders. There are at least two unanswered questions or research gaps in the literature on determinants of GC opinion. Firstly, is client’s probability of failure associated with GC opinion issuance? Secondly, to what extent influential owners (management, family, and institution) moderate the association between client probability of failure and GC opinion issuance. The objective of this study is, therefore, twofold; (1) To examine the extent of the relationship between the probability of client failure and the issuance of GC opinion and (2) To examine the level of management, family, and institutional ownerships moderate the association between client probability of failure and the issuance of GC opinion. This study is quantitative in nature, and the sources of data are secondary (mainly company’s annual reports). A total of four hypotheses have been developed and tested on data accumulated from annual reports of seriously financially distressed Malaysian public listed companies. Data from 2006 to 2012 on a sample of 644 observations have been analyzed using panel logistic regression. It is found that certainty (rather than probability) of client failure affects the issuance of GC opinion. In addition, it is found that only the level of family ownership does positively moderate the relationship between client probability of failure and GC opinion issuance. This study is a contribution to auditing literature as its findings can enhance our understanding about audit quality; particularly on the variables that are associated with the issuance of GC opinion. The findings of this study shed light on the roles family owners in GC opinion issuance process, and this would open ways for the researcher to suggest measures that can be used to tackle the problem of auditors do not want to issue GC opinion to financially distressed clients. The measures to be suggested can be useful to policy makers in formulating future promulgations.

Keywords: audit quality, auditing, auditor characteristics, going concern opinion, Malaysia

Procedia PDF Downloads 261

Authors: Md Fazlul Kader, Soo Young Shin

Abstract:

In this paper, we consider a cognitive relay network (CRN) in which the primary receiver (PR) is protected by peak transmit power $\bar{P}_{ST}$ and/or peak interference power Q constraints. In addition, the interference effect from the primary transmitter (PT) is considered to show its impact on the performance of the CRN. We investigate the outage probability (OP) and outage capacity (OC) of the CRN by deriving closed-form expressions over Rayleigh fading channel. Results show that both the OP and OC improve by increasing the cooperative relay nodes as well as when the PT is far away from the SR.

Keywords: cognitive relay, outage, interference limited, decode-and-forward (DF)

Procedia PDF Downloads 512

Authors: Yao Fu, Xingli Zhang, Jiannong Shi

Abstract:

Visual working memory (VWM) capacity is the ability to maintain and manipulate short-term information which is not currently available. It is well known for its significance to form the basis of numerous cognitive abilities and its limitation in holding information. VWM span, the most popular measurable indicator, is found to reach the adult level (3-4 items) around 12-13 years’ old, while less is known about the precision development of the VWM capacity. By using simultaneously delayed responses paradigm, the present study investigates the development of VWM precision among 6-18-year-old children and young adults, besides its possible relationships with fluid intelligence and span. Results showed that precision and span both increased with age, and precision reached the maximum in 16-17 age-range. Moreover, when remembering 3 simultaneously presented items, the probability of remembering target item correlated with fluid intelligence and the probability of wrap errors (misbinding target and non-target items) correlated with age. When remembering more items, children had worse performance than adults due to their wrap errors. Compared to span, VWM precision was effective predictor of intelligence even after controlling for age. These results suggest that unlike VWM span, precision developed in a slow, yet longer fashion. Moreover, decreasing probability of wrap errors might be the main reason for the development of precision. Last, precision correlated more closely with intelligence than span in childhood and adolescence, which might be caused by the probability of remembering target item.

Keywords: fluid intelligence, precision, visual working memory, wrap errors

Procedia PDF Downloads 277

Authors: Mouna Zitouni, Mariem Tounsi

Abstract:

This research introduces an application of the Riesz mixture model for medical image segmentation for accurate diagnosis and treatment of brain tumors. We propose a pixel classification technique based on the Riesz distribution, derived from an extended Bartlett decomposition. To our knowledge, this is the first study addressing this approach. The Expectation-Maximization algorithm is implemented for parameter estimation. A comparative analysis, using both synthetic and real brain images, demonstrates the superiority of the Riesz model over a recent method based on the Wishart distribution.

Keywords: EM algorithm, segmentation, Riesz probability distribution, Wishart probability distribution

Procedia PDF Downloads 21

Authors: Zeyu Zhang, Guisheng Yin, Ziying Zhang, Liguo Zhang

Abstract:

This paper mainly studies the path planning method based on ant colony optimization (ACO), and proposes heuristic integration ant colony optimization (HIACO). This paper not only analyzes and optimizes the principle, but also simulates and analyzes the parameters related to the application of HIACO in path planning. Compared with the original algorithm, the improved algorithm optimizes probability formula, tabu table mechanism and updating mechanism, and introduces more reasonable heuristic factors. The optimized HIACO not only draws on the excellent ideas of the original algorithm, but also solves the problems of premature convergence, convergence to the sub optimal solution and improper exploration to some extent. HIACO can be used to achieve better simulation results and achieve the desired optimization. Combined with the probability formula and update formula, several parameters of HIACO are tested. This paper proves the principle of the HIACO and gives the best parameter range in the research of path planning.

Keywords: ant colony optimization, heuristic integration, path planning, probability formula

Procedia PDF Downloads 251

Authors: Vincenzo Russo, Rosella Giacometti

Abstract:

The paper aims to assess the insurance industry's resilience under Solvency II against adverse scenarios. Starting from the economic balance sheet available under Solvency II for insurance and reinsurance undertakings, we assume that assets and liabilities follow a bivariate geometric Brownian motion (GBM). Then, using the results available under Margrabe's formula, we establish an analytical solution to calibrate the volatility of the asset-liability ratio. In such a way, we can estimate the probability of default and the probability of breaching the undertaking's Solvency Capital Requirement (SCR). Furthermore, since estimating the volatility of the Solvency Ratio became crucial for insurers in light of the financial crises featured in the last decades, we introduce a novel measure that we call Resiliency Ratio. The Resiliency Ratio can be used, in addition to the Solvency Ratio, to evaluate the insurance industry's resilience in case of adverse scenarios. Finally, we introduce a simplified stress test tool to evaluate the economic balance sheet under stressed conditions. The model we propose is featured by analytical tractability and fast calibration procedure where only the disclosed data available under the Solvency II public reporting are needed for the calibration. Using the data published regularly by the European Insurance and Occupational Pensions Authority (EIOPA) in an aggregated form by country, an empirical analysis has been performed to calibrate the model and provide the related results at the country level.

Keywords: Solvency II, solvency ratio, volatility of the asset-liability ratio, probability of default, probability to breach the SCR, resilience ratio, stress test

Procedia PDF Downloads 82

Authors: Rukhsana Kausar, Issam Malki

Abstract:

The integration and assimilation of ethnic minority immigrants (EMIs) and their subsequent generations remains a serious unsettled issue in most of the host countries. This study conducts the labour market gender analysis to investigate specifically whether second generation of ethnic minority immigrants in the UK is gaining access to professional and managerial employment and advantaged occupational positions on par with their native counterparts. The data used to examine the labour market achievements of EMIs is taken from Labour Force Survey (LFS) for the period 2014-2018. We apply a multivalued treatment under ignorability as proposed by Cattaneo (2010), which refers to treatment effects under the assumptions of (i) selection – on – observables and (ii) common support. We report estimates of Average Treatment Effect (ATE), Average Treatment Effect on the Treated (ATET), and Potential Outcomes Means (POM) using three estimators, including the Regression Adjustment (RA), Augmented Inverse Probability Weighting (AIPW) and Inverse Probability Weighting- Regression Adjustment (IPWRA). We consider two cases: the case with four categories where the first-generation natives are the base category, the second case combine all natives as a base group. Our findings suggest the following. Under Case 1, the estimated probabilities and differences across groups are consistently similar and highly significant. As expected, first generation natives have the highest probability for higher career attainment among both men and women. The findings also suggest that first generation immigrants perform better than the remaining two groups, including the second-generation natives and immigrants. Furthermore, second generation immigrants have higher probability to attain higher professional career, while this is lower for a managerial career. Similar conclusions are reached under Case 2. That is to say that both first – generation and second – generation immigrants have a lower probability for higher career and managerial attainment. First – generation immigrants are found to perform better than second – generation immigrants.

Keywords: immigrnats, second generation, occupational attainment, ethnicity

Procedia PDF Downloads 108

Authors: Suraj Sam Issaka, Anita Asamoah, Abass Gibrilla, Joseph Richmond Fianko

Abstract:

Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that can form in edible oils during repeated frying and accumulate in fried foods. This study assesses the chances of health risks (carcinogenic and non-carcinogenic) due to PAHs levels in popular finger foods (bean cakes, plantain chips, doughnuts) fried in edible oils (mixed vegetable, sunflower, soybean) from the Ghanaian market. Employing probabilistic health risk assessment that considers variability and uncertainty in exposure and risk estimates provides a more realistic representation of potential health risks. Monte Carlo simulations with 10,000 iterations were used to estimate carcinogenic, mutagenic, and non-carcinogenic risks for different age groups (A: 6-10 years, B: 11-20 years, C: 20-70 years), food types (bean cake, plantain chips, doughnut), oil types (soybean, mixed vegetable, sunflower), and re-usage frying oil frequencies (once, twice, thrice). Our results suggest that, for age Group A, doughnuts posed the highest probability of carcinogenic risk (91.55%) exceeding the acceptable threshold, followed by bean cakes (43.87%) and plantain chips (7.72%), as well as the highest probability of unacceptable mutagenic risk (89.2%), followed by bean cakes (40.32%). Among age Group B, doughnuts again had the highest probability of exceeding carcinogenic risk limits (51.16%) and mutagenic risk limits (44.27%). At the same time, plantain chips exhibited the highest maximum carcinogenic risk. For adults age Group C, bean cakes had the highest probability of unacceptable carcinogenic (50.88%) and mutagenic risks (46.44%), though plantain chips showed the highest maximum values for both carcinogenic and mutagenic risks in this age group. Also, on non-carcinogenic risks across different age groups, it was found that age Group A) who consumed doughnuts had a 68.16% probability of a hazard quotient (HQ) greater than 1, suggesting potential cognitive impairment and lower IQ scores due to early PAH exposure. This group also faced risks from consuming plantain chips and bean cake. For age Group B, the consumption of plantain chips was associated with a 36.98% probability of HQ greater than 1, indicating a potential risk of reduced lung function. In age Group C, the consumption of plantain chips was linked to a 35.70% probability of HQ greater than 1, suggesting a potential risk of cardiovascular diseases.

Keywords: PAHs, fried foods, carcinogenic risk, non-carcinogenic risk, Monte Carlo simulations

Procedia PDF Downloads 18