Search results for: quasi-maximum likelihood estimate

Authors: Mesut BALIBEY, Serpil TÜRKYILMAZ

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A popular topic in the econometrics and time series area is the cointegrating relationships among the components of a nonstationary time series. Engle and Granger’s least squares method and Johansen’s conditional maximum likelihood method are the most widely-used methods to determine the relationships among variables. Furthermore, a method proposed to test a unit root based on the periodogram ordinates has certain advantages over conventional tests. Periodograms can be calculated without any model specification and the exact distribution under the assumption of a unit root is obtained. For higher order processes the distribution remains the same asymptotically. In this study, in order to indicate advantages over conventional test of periodograms, we are going to examine a possible relationship between tourism and economic growth during the period 1999:01-2010:12 for Turkey by using periodogram method, Johansen’s conditional maximum likelihood method, Engle and Granger’s ordinary least square method.

Keywords: cointegration, economic growth, periodogram ordinate, tourism

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Augustine Okolie, Johannes Müller, Mirjam Kretzchmar

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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

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Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

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Authors: Ankita Shukla

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The promotion and support of breastfeeding is a global priority with benefits for maternal and infant health, especially in low income and middle-income countries where the probability of child survival is still very low. In India too it has been well established that breastfeeding increases the survival of the child. However, the breastfeeding levels are quite low in the country. Examining the socio-economic inequality in breastfeeding pattern can help to the causal pathways responsible for early breastfeeding termination. This paper tries to understand the socio-economic differential in breastfeeding patterns among Indian women. Data is used from nationally representative National Family Health Survey-3. Using Cox regression modelling techniques, the analysis found that the likelihood of having small breastfeeding duration increased with increasing household wealth status similarly education also has negative effect on breastfeeding duration. The considerable gender difference is also visible in India, likelihood of stopping breastfeeding was significantly higher among female children compared with male children. To understand the cultural factors or norms responsible for the early termination of breastfeeding more in depth/qualitative studies are needed.

Keywords: breastfeeding, India, socio-economic inequality, women education

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Benedictus Asriparusa

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Solar radiation is a green renewable energy which has the potential to answer the needs of energy problems on the period. Knowing how to estimate the strength of the solar radiation force may be one solution of sustainable energy development in an integrated manner. Unfortunately, a fairly extensive area of Indonesia is still very low availability of solar radiation data. Therefore, we need a method to estimate the exact strength of solar radiation. In this study, author used a model Reference Evaluation of Solar Transmittance, 2 Bands (REST 2). Validation of REST 2 model has been performed in Spain, India, Colorado, Saudi Arabia, and several other areas. But it is not widely used in Indonesia. Indonesian region study area is represented by the area of Semarang, Central Java. Solar radiation values estimated using REST 2 model was then verified by field data and gives average RMSE value of 6.53%. Based on the value, it can be concluded that the model REST 2 can be used to estimate the value of solar radiation in clear sky conditions in parts of Indonesia.

Keywords: estimation, solar radiation power, REST 2, solar transmittance

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Authors: Binjuan Xu, Qian Zhao, Ping Jiang, Bo Guo, Zhijun Cheng, Xiaoyue Wu

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Astronautical valves are key units in engine systems of astronautical products; their reliability will influence results of rocket or missile launching, even lead to damage to staff and devices on the ground. Besides failure in engine system may influence the hitting accuracy and flight shot of missiles. Therefore high reliability is quite essential to astronautical products. There are quite a few literature doing research based on few failure test data to estimate valves’ reliability, thus this paper proposed a new method to estimate valves’ reliability, according to the corresponding tests of different failure modes, this paper takes advantage of tests data which acquired from temperature, vibration, and action tests to estimate reliability in every failure modes, then this paper has regarded these three kinds of tests as three stages in products’ process to integrate these results to acquire valves’ reliability. Through the comparison of results achieving from tests data and simulated data, the results have illustrated how to obtain valves’ reliability based on the few failure data with failure modes and prove that the results are effective and rational.

Keywords: censored data, temperature tests, valves, vibration tests

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Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

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This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

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Authors: Md. Rashidul Hasan, Atikur Rahman Baizid

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The Bayesian estimation approach is a non-classical estimation technique in statistical inference and is very useful in real world situation. The aim of this paper is to study the Bayes estimators of the parameter of exponential distribution under different loss functions and then compared among them as well as with the classical estimator named maximum likelihood estimator (MLE). In our real life, we always try to minimize the loss and we also want to gather some prior information (distribution) about the problem to solve it accurately. Here the gamma prior is used as the prior distribution of exponential distribution for finding the Bayes estimator. In our study, we also used different symmetric and asymmetric loss functions such as squared error loss function, quadratic loss function, modified linear exponential (MLINEX) loss function and non-linear exponential (NLINEX) loss function. Finally, mean square error (MSE) of the estimators are obtained and then presented graphically.

Keywords: Bayes estimator, maximum likelihood estimator (MLE), modified linear exponential (MLINEX) loss function, Squared Error (SE) loss function, non-linear exponential (NLINEX) loss function

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Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

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Authors: Fathima M. A., Milu Maria Anto

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Aim: The current study aims to explore the understanding about Mental Health and the likelihood to seek help for mental health problems among adolescents in the state of Kerala (India). Method: A cross sectional exploratory design was used. Samples were selected using convenience sampling. Ninety nine high school and higher secondary school students who had enrolled in the program “Responsible Adolescents (READ)” organized by MKMS Education from Kerala participated in this study. The data for the present study was collected using google forms prior to the commencement of the READ programme. Open-ended questions were used to explore the understanding of participants about mental health, mental health problems, causes of mental health problems and the role of mental health professionals. The likelihood to seek help (from friends, parents, teachers and mental health professionals) for mental health problems was assessed using a visual analogue scale. Further open-ended questions were used to identify what changes in teachers and parents will make them feel more comfortable to approach them when they need help. Content analysis was used to identify themes and coded data was further analyzed using correlation. Results: The results show that students have a fair idea about what Mental Health is. Even though the majority is familiar with the names of mental health disorders, relatively fewer students identify it as irregularity in mental functions such as thoughts, emotions and behaviors. The students tend to attribute symptoms of mental health problems as the cause of mental health problems. Very few students have the understanding that biological variations and adverse childhood experiences are primary causes for the development of mental health problems. Less than half of the students were aware of the role of psychiatrists and psychologists in mental health treatment. The students were more likely to seek help from parents and friends during distress. They had a medium inclination to seek help from mental health professionals and showed even lower likelihood to seek help from teachers. The majority of the students responded that they would be more comfortable approaching teachers if they were more open-minded and approachable as well as non-judgmental and non-dismissive. Conclusion: Findings show that there is inadequate awareness among adolescents about mental health problems and their causes. There is a lack of understanding about the roles of two main mental health professionals which can pose a big hurdle in accessing adequate help from the appropriate professional at the right time. The low likelihood to seek help from teachers for mental health problems is very concerning. The major barriers reported by the students in seeking help from teachers were the judgmental and dismissive approach. The findings throw light on the current level of awareness about mental health and mental health help-seeking, which can be utilized in framing mental health awareness programs for students as well as teachers.

Keywords: Mental Health Awareness, Adolescent Mental Health, Help Seeking Behavior, School Mental Health

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Authors: John Farr Rothrock

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Although migraine traditionally has been assumed to convey a relative decrease in libido, sexual activity and sexual performance, recent data have suggested that the female migraine population is far from homogenous in this regard. We sought to determine the levels of libido, sexual activity and sexual performance in the female migraine patient population both generally and according to clinical phenotype. In this single-blind study, a consecutive series of sexually active new female patients ages 25-55 initially presenting to a university-based headache clinic and having a >1 year history of migraine were asked to complete anonymously a survey assessing their sexual histories generally and as they related to their headache disorder and the 19-item Female Sexual Function Index (FSFI). To serve as 2 separate control groups, 100 sexually active females with no history of migraine and 100 female migraineurs from the general (non-clinic) population but matched for age, marital status, educational background and socioeconomic status completed a similar survey. Over a period of 3 months, 188 consecutive migraine patients were invited to participate. Twenty declined, and 28 of the remaining 160 potential subjects failed to meet the inclusion criterion utilized for “sexually active” (ie, heterosexual intercourse at a frequency of > once per month in each of the preceding 6 months). In all groups younger age (p<.005), higher educational level attained (p<.05) and higher socioeconomic status (p<.025) correlated with a higher monthly frequency of intercourse and a higher likelihood of intercourse resulting in orgasm. Relative to the 100 control subjects with no history of migraine, the two migraine groups (total n=232) reported a lower monthly frequency of intercourse and recorded a lower FSFI score (both p<.025), but the contribution to this difference came primarily from the chronic migraine (CM) subgroup (n=92). Patients with low frequency episodic migraine (LFEM) and mid frequency episodic migraine (MFEM) reported a higher FSFI score, higher monthly frequency of intercourse, higher likelihood of intercourse resulting in orgasm and higher likelihood of multiple active sex partners than controls. All migraine subgroups reported a decreased likelihood of engaging in intercourse during an active migraine attack, but relative to the CM subgroup (8/92=9%), a higher proportion of patients in the LFEM (12/49=25%), MFEM (14/67=21%) and high frequency episodic migraine (HFEM: 6/14=43%) subgroups reported utilizing intercourse - and orgasm specifically - as a means of potentially terminating a migraine attack. In the clinic vs no-clinic groups there were no significant differences in the dependent variables assessed. Research subjects with LFEM and MFEM may report a level of libido, frequency of intercourse and likelihood of orgasm-associated intercourse that exceeds what is reported by age-matched controls free of migraine. Many patients with LFEM, MFEM and HFEM appear to utilize intercourse/orgasm as a means to potentially terminate an acute migraine attack.

Keywords: migraine, female, libido, sexual activity, phenotype

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Authors: A. Y. Mukhtar, J. B. Munyakazi, R. Ouifki

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Over the past few decades, the unprecedented increase in mobility has raised considerable concern about the relationship between mobility and vector-borne diseases and malaria in particular. Thus, one can claim that human mobility is one of the contributing factors to the resurgence of malaria. To assess human mobility on malaria burden among hosts, we formulate a movement-based model on a network of patches. We then extend human multi-group SEIAR deterministic epidemic models into a system of stochastic differential equations (SDEs). Our quantitative stochastic model which is expressed in terms of average rates of movement between compartments is fitted to time-series data (weekly malaria data of 2011 for each patch) using the maximum likelihood approach. Using the metapopulation (multi-group) model, we compute and analyze the basic reproduction number. The result shows that human movement is sufficient to preserve malaria disease firmness in the patches with the low transmission. With these results, we concluded that the sensitivity of malaria to the human mobility is turning to be greatly important over the implications of future malaria control in South Sudan.

Keywords: basic reproduction number, malaria, maximum likelihood, movement, stochastic model

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Authors: Ashraf M. Ward, Ruban S. Yu

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Data consisting of 2757 records from tow Holstein herds made between 2000 and 2010 were used to examine environmental factors affecting age at first calving (AFC) and calving intervals (CI) and consequently estimate genetic and phenotypic parameters and trends. The overall means and standard errors for AFC and CI were 39.4 ± 7.2 months and 487.5 ± 151.6 days respectively. The respective heritability estimates were 0.091 ± 0.05 and 0.044 ± 0.032, while the repeatability estimate for CI was 0.096 ± 0.001. The genetic trends for CI and AFC were -0.6 d/yr and -0.01 mo/yr respectively and were both significant (P < 0.001), indicating a decrease in mean breeding value over the study period. Phenotypic trends were -0.31 mo/yr and -0.35 d/yr for AFC and CI respectively though non-significant (P > 0.05). The low heritability for CI and AFC indicated that temporary environmental influences were much greater than genetic influences or permanent environmental influences on these traits.

Keywords: Holstein, reproductive, genetic parameters, heritability

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Authors: Daniel Nigusse Tollosa, Erica James, Alexis Hurre, Meredith Tavener

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Introduction: Lifestyle behaviours such as healthy diet, regular physical activity and maintaining a healthy weight are essential for cancer survivors to improve the quality of life and longevity. However, there is no study that synthesis cancer survivor’s adherence to healthy lifestyle recommendations. The purpose of this review was to collate existing data on the prevalence of adherence to healthy behaviours and produce the pooled estimate among adult cancer survivors. Method: Multiple databases (Embase, Medline, Scopus, Web of Science and Google Scholar) were searched for relevant articles published since 2007, reporting cancer survivors adherence to more than two lifestyle behaviours based on the WCRF/AICR recommendations. The pooled prevalence of adherence to single and multiple behaviours (operationalized as adherence to more than 75% (3/4) of health behaviours included in a particular study) was calculated using a random effects model. Subgroup analysis adherence to multiple behaviours was undertaken corresponding to the mean survival years and year of publication. Results: A total of 3322 articles were generated through our search strategies. Of these, 51 studies matched our inclusion criteria, which presenting data from 2,620,586 adult cancer survivors. The highest prevalence of adherence was observed for smoking (pooled estimate: 87%, 95% CI: 85%, 88%) and alcohol intake (pooled estimate 83%, 95% CI: 81%, 86%), and the lowest was for fiber intake (pooled estimate: 31%, 95% CI: 21%, 40%). Thirteen studies were reported the proportion of cancer survivors (all used a simple summative index method) to multiple healthy behaviours, whereby the prevalence of adherence was ranged from 7% to 40% (pooled estimate 23%, 95% CI: 17% to 30%). Subgroup analysis suggest that short-term survivors ( < 5 years survival time) had relatively a better adherence to multiple behaviours (pooled estimate: 31%, 95% CI: 27%, 35%) than long-term ( > 5 years survival time) cancer survivors (pooled estimate: 25%, 95% CI: 14%, 36%). Pooling of estimates according to the year of publication (since 2007) also suggests an increasing trend of adherence to multiple behaviours over time. Conclusion: Overall, the adherence to multiple lifestyle behaviors was poor (not satisfactory), and relatively, it is a major concern for long-term than the short-term cancer survivor. Cancer survivors need to obey with healthy lifestyle recommendations related to physical activity, fruit and vegetable, fiber, red/processed meat and sodium intake.

Keywords: adherence, lifestyle behaviours, cancer survivors, WCRF/AICR

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Authors: Sai Chand, Ashish Dhamaniya, Satish Chandra

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Curbside bus stops are provided on urban roads when sufficient land is not available to construct bus bays. The present study demonstrates the effect of curbside bus stops on midblock capacity of an urban arterial road. Data were collected on seven sections of 6-lane urban arterial roads in New Delhi. Three sections were selected without any side friction to estimate the base value of capacity. Remaining four sections were with curbside bus stop. Speed and volume data were collected in field and these data were used to estimate the capacity of a section. The average base midblock capacity of a 6–lane divided urban road was found to be 6314 PCU/hr which was further referred as base capacity. Effect of curbside bus stop on midblock capacity of urban road was evaluated by comparing the capacity of a section with curbside bus stop with that of the base capacity. Finally, a mathematical relation has been developed between bus frequency and capacity loss. Also a relation has been suggested between dwell time and capacity loss. The developed relations would be very useful for practising engineers to estimate capacity loss due to bus stop.

Keywords: bus frequency, bus stops, capacity loss, urban arterial

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Authors: Y. Chiang, W. Y. Li, J. R. Wang, S. W. Chen, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT code was used to estimate the concentration under the CO₂ and H₂SO₄ storage burst conditions for Kuosheng nuclear power plant (NPP). The Final Safety Analysis Report (FSAR) and reports were used in this research. In addition, to evaluate the control room habitability for these cases, the HABIT analysis results were compared with the R.G. 1.78 failure criteria. The comparison results show that the HABIT results are below the criteria. Additionally, some sensitivity studies (stability classification, wind speed and control room intake rate) were performed in this study.

Keywords: BWR, HABIT, habitability, Kuosheng

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Authors: Fatemah A. Alqallaf, Debasis Kundu

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The aim of this paper is to introduce a bivariate inverse generalized exponential distribution which has a singular component. The proposed bivariate distribution can be used when the marginals have heavy-tailed distributions, and they have non-monotone hazard functions. Due to the presence of the singular component, it can be used quite effectively when there are ties in the data. Since it has four parameters, it is a very flexible bivariate distribution, and it can be used quite effectively for analyzing various bivariate data sets. Several dependency properties and dependency measures have been obtained. The maximum likelihood estimators cannot be obtained in closed form, and it involves solving a four-dimensional optimization problem. To avoid that, we have proposed to use an EM algorithm, and it involves solving only one non-linear equation at each `E'-step. Hence, the implementation of the proposed EM algorithm is very straight forward in practice. Extensive simulation experiments and the analysis of one data set have been performed. We have observed that the proposed bivariate inverse generalized exponential distribution can be used for modeling dependent competing risks data. One data set has been analyzed to show the effectiveness of the proposed model.

Keywords: Block and Basu bivariate distributions, competing risks, EM algorithm, Marshall-Olkin bivariate exponential distribution, maximum likelihood estimators

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Authors: Olivier Mesly

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This article examines the likelihood of deception on the part of borrowers wishing to obtain credit from institutional or private lenders. In our first study, we identify five explanatory variables that account for nearly forty percent of the propensity to act deceitfully: a poor credit history, debt, risky behavior, and to a much lesser degree, irrational behavior and disconnection from the bundle of needs, goals, and preferences. For the second study, we remodeled the initial questionnaire to adapt it to the needs of institutional bankers and borrowers, especially those that engage in money on-line peer-to-peer lending, a growing business fueled by the COVID pandemic. We find that the three key psychological variables that help to indirectly predict the likelihood of deceitful behaviors and possible default on loan reimbursement, i.e., risky behaviors, ir-rationality, and dis-connection, interact with each other to form a loop. This study presents two benefits: first, we provide evidence that it is to some degree possible to tighten control over lending practices. Second, we offer a pragmatic tool: a questionnaire, that lenders can use or adapt to gauge potential borrowers’ deceit, notably by combining their results with standard hard-data measures of risk.

Keywords: bundle of needs, default, debt, deception, risk, peer-to-peer lending

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Authors: Godwin Chigozie Okpara

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This paper using standard GARCH, EGARCH, and TARCH models on day of the week return series (of 246 days) from the Nigerian Stock market estimated the model variants’ VaR. An asymmetric return distribution and fat-tail phenomenon in financial time series were considered by estimating the models with normal, student t and generalized error distributions. The analysis based on Akaike Information Criterion suggests that the EGARCH model with student t innovation distribution can furnish more accurate estimate of VaR. In the light of this, we apply the likelihood ratio tests of proportional failure rates to VaR derived from EGARCH model in order to determine the short and long positions VaR performances. The result shows that as alpha ranges from 0.05 to 0.005 for short positions, the failure rate significantly exceeds the prescribed quintiles while it however shows no significant difference between the failure rate and the prescribed quantiles for long positions. This suggests that investors and portfolio managers in the Nigeria stock market have long trading position or can buy assets with concern on when the asset prices will fall. Precisely, the VaR estimates for the long position range from -4.7% for 95 percent confidence level to -10.3% for 99.5 percent confidence level.

Keywords: downside risk, value-at-risk, failure rate, kupiec LR tests, GARCH models

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Authors: Maria Sciammarella, Uttam M. Shrestha, Youngho Seo, Grant T. Gullberg, Elias H. Botvinick

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Background: Myocardial perfusion imaging (MPI) is typically performed with static imaging protocols and visually assessed for perfusion defects based on the relative intensity distribution. Dynamic cardiac SPECT, on the other hand, is a new imaging technique that is based on time varying information of radiotracer distribution, which permits quantification of myocardial blood flow (MBF). In this abstract, we report a progress and current status of dynamic cardiac SPECT using conventional gamma camera (Infinia Hawkeye 4, GE Healthcare) for estimation of myocardial blood flow and coronary flow reserve. Methods: A group of patients who had high risk of coronary artery disease was enrolled to evaluate our methodology. A low-dose/high-dose rest/pharmacologic-induced-stress protocol was implemented. A standard rest and a standard stress radionuclide dose of ⁹⁹ᵐTc-tetrofosmin (140 keV) was administered. The dynamic SPECT data for each patient were reconstructed using the standard 4-dimensional maximum likelihood expectation maximization (ML-EM) algorithm. Acquired data were used to estimate the myocardial blood flow (MBF). The correspondence between flow values in the main coronary vasculature with myocardial segments defined by the standardized myocardial segmentation and nomenclature were derived. The coronary flow reserve, CFR, was defined as the ratio of stress to rest MBF values. CFR values estimated with SPECT were also validated with dynamic PET. Results: The range of territorial MBF in LAD, RCA, and LCX was 0.44 ml/min/g to 3.81 ml/min/g. The MBF between estimated with PET and SPECT in the group of independent cohort of 7 patients showed statistically significant correlation, r = 0.71 (p < 0.001). But the corresponding CFR correlation was moderate r = 0.39 yet statistically significant (p = 0.037). The mean stress MBF value was significantly lower for angiographically abnormal than that for the normal (Normal Mean MBF = 2.49 ± 0.61, Abnormal Mean MBF = 1.43 ± 0. 0.62, P < .001). Conclusions: The visually assessed image findings in clinical SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion. The MBF and CFR measured with dynamic SPECT are fully objective and available only with the data generated from the dynamic SPECT method. A quantitative approach such as measuring CFR using dynamic SPECT imaging is a better mode of diagnosing CAD than visual assessment of stress and rest images from static SPECT images Coronary Flow Reserve.

Keywords: dynamic SPECT, clinical SPECT/CT, selective coronary angiograph, ⁹⁹ᵐTc-Tetrofosmin

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Authors: Maoxin Ye

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This study examines the relationship between social network sites (SNS) usage and social capital. Because SNS usage can expand the users’ networks, and people who are connected in this networks may become resources to SNS users and lead them to advantage in some situation, it is important to estimate the relationship between SNS usage and ‘who’ is connected or what resources the SNS users can get. Additionally, ‘who’ can be divided in two aspects – people who possess high position and people who are different, hence, it is important to estimate the relationship between SNS usage and high position people and different people. This study adapts Lin’s definition of social capital and the measurement of position generator which tells us who was connected, and can be divided into the same two aspects as well. A national data of America (N = 2,255) collected by Pew Research Center is utilized to do a general regression analysis about SNS usage and social capital. The results indicate that SNS usage is negatively associated with each factor of social capital, and it suggests that, in fact, comparing with non-users, although SNS users can get more connections, the variety and resources of these connections are fewer. For this reason, we could lose benefits through SNS usage.

Keywords: social network sites, social capital, position generator, general regression

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Authors: Oyuntsetseg Sandag, Lkhagvadorj Khosbayar, Naidansuren Tsendeekhuu, Densenbal Dansran, Bandi Solongo

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Introduction: Obstructive sleep apnea (OSA) is a common disorder affecting at least 2% to 4% of the adult population. It is estimated that nearly 80% of men and 93% of women with moderate to severe sleep apnea are undiagnosed. A number of screening questionnaires and clinical screening models have been developed to help identify patients with OSA, also it’s indeed to clinical practice. Purpose of study: Determine dependence of obstructive sleep apnea between for severe risk and risk factor. Material and Methods: A cross-sectional study included 114 patients presenting from theCentral state 3th hospital and Central state 1th hospital. Patients who had obstructive sleep apnea (OSA)selected in this study. Standard StopBang questionnaire was obtained from all patients.According to the patients’ response to the StopBang questionnaire was divided into low risk, intermediate risk, and high risk.Descriptive statistics were presented mean ± standard deviation (SD). Each questionnaire was compared on the likelihood ratio for a positive result, the likelihood ratio for a negative test result of regression. Statistical analyses were performed utilizing SPSS 16. Results: 114 patients were obtained (mean age 48 ± 16, male 57)that divided to low risk 54 (47.4%), intermediate risk 33 (28.9%), high risk 27 (23.7%). Result of risk factor showed significantly increasing that mean age (38 ± 13vs. 54 ± 14 vs. 59 ± 10, p<0.05), blood pressure (115 ± 18vs. 133 ± 19vs. 142 ± 21, p<0.05), BMI(24 IQR 22; 26 vs. 24 IQR 22; 29 vs. 28 IQR 25; 34, p<0.001), neck circumference (35 ± 3.4 vs. 38 ± 4.7 vs. 41 ± 4.4, p<0.05)were increased. Results from multiple logistic regressions showed that age is significantly independently factor for OSA (odds ratio 1.07, 95% CI 1.02-1.23, p<0.01). Predictive value of age was significantly higher factor for OSA (AUC=0.833, 95% CI 0.758-0.909, p<0.001). Our study showing that risk of OSA is beginning 47 years old (sensitivity 78.3%, specifity74.1%). Conclusions: According to most of all patients’ response had intermediate risk and high risk. Also, age, blood pressure, neck circumference and BMI were increased such as risk factor was increased for OSA. Especially age is independently factor and highest significance for OSA. Patients’ age one year is increased likelihood risk factor 1.1 times is increased.

Keywords: obstructive sleep apnea, Stop-Bang, BMI (Body Mass Index), blood pressure

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Authors: Jozef Mindas, Jana Skvareninova

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Wetlands are a main natural source of methane emissions, but they also represent the important biodiversity reservoirs in the landscape. There are about 26 thousands hectares of wetlands in Slovakia identified via the wetlands monitoring program. Created database of wetlands in Slovakia allows to analyze several ecological processes including also the methane emissions estimate. Based on the information from the database, the first estimate of the methane emissions from wetlands in Slovakia has been done. The IPCC methodology (Tier 1 approach) has been used with proposed emission factors for the ice-free period derived from the climatic data. The highest methane emissions of nearly 550 Gg are associated with the category of fens. Almost 11 Gg of methane is emitted from bogs, and emissions from flooded lands represent less than 8 Gg.

Keywords: bogs, methane emissions, Slovakia, wetlands

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Authors: Serge B. Provost

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Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

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Authors: Bhavatharani S., Boopathy V., Kavin S., Naveethkumar R.

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Context: Resistance training with blood flow restriction (BFR) has increased in clinical rehabilitation due to the substantial benefits observed in augmenting muscle mass and strength using low loads. However, there is a great variability of training pressures for clinical populations as well as methods to estimate it. The aim of this study was to estimate the percentage of maximal BFR that could result by applying different methodologies based on arbitrary or individual occlusion levels using a cuff width between 9 and 13 cm. Design: A secondary analysis was performed on the combined databases of 2 previous larger studies using BFR training. Methods: To estimate these percentages, the occlusion values needed to reach complete BFR (100% limb occlusion pressure [LOP]) were estimated by Doppler ultrasound. Seventy-five participants (age 24.32 [4.86] y; weight: 78.51 [14.74] kg; height: 1.77 [0.09] m) were enrolled in the laboratory study for measuring LOP in the thigh, arm, or calf. Results: When arbitrary values of restriction are applied, a supra-occlusive LOP between 120% and 190% LOP may result. Furthermore, the application of 130% resting brachial systolic blood pressure creates a similar occlusive stimulus as 100% LOP. Conclusions: Methods using 100 mm Hg and the resting brachial systolic blood pressure could represent the safest application prescriptions as they resulted in applied pressures between 60% and 80% LOP. One hundred thirty percent of the resting brachial systolic blood pressure could be used to indirectly estimate 100% LOP at cuff widths between 9 and 13 cm. Finally, methodologies that use standard values of 200 and, 300 mm Hg far exceed LOP and may carry additional risk during BFR exercise.

Keywords: lower limb rehabilitation, ESP32, pneumatics for medical, programmed rehabilitation

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Mahmut Yildirim

Abstract:

This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: A. A. Ahmadi, A. R. Pishevar, M. Nili

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As the test gas in a gun tunnel is non-isentropically compressed and heated by a light weight piston. Here, first consideration is the optimum piston weight. Although various aspects of the influence of piston weight on gun tunnel performance have been studied, it is not possible to decide from the existing literature what piston weight is required for optimum performance in various conditions. The technique whereby the piston is rapidly brought to rest at the end of the gun tunnel barrel, and the resulted peak pressure is equal in magnitude to the final equilibrium pressure, is called the equilibrium piston technique. The equilibrium piston technique was developed to estimate the equilibrium piston mass; but this technique cannot give an appropriate estimate for the optimum piston weight. In the present work, a gun tunnel with diameter of 3 in. is described and its performance is investigated numerically to obtain the effect of piston and its weight. Numerical results in the present work are in very good agreement with experimental results. Significant influence of the existence of a piston is shown by comparing the gun tunnel results with results of a conventional shock tunnel in the same dimension and same initial condition. In gun tunnel, an increase of around 250% in running time is gained relative to shock tunnel. Also, Numerical results show that equilibrium piston technique is not a good way to estimate suitable piston weight and there will be a lighter piston which can increase running time of the gun tunnel around 60%.

Keywords: gun tunnel, hypersonic flow, piston, shock tunnel

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