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In this research, a new acceptance sampling plan for a truncated life test is presented, assuming that the quality characteristic follows the power Lomax distribution. The operating characteristic function values are calculated for the proposed sampling plan, jointly with the optimal sample size and the producer’s risk for a selection of distribution parameters. Furthermore, a comparative study with other sampling plans is introduced to demonstrate the advantages of the proposed plan. Finally, a real-life example illustrating the applicability of the proposed sampling plan in a manufacturing company is discussed.

Motivated mainly by lifetime issues, a new lifetime distribution coined ``Discrete Poisson-Gold distribution'' is introduced in this paper. Different structural properties of the new distribution are derived including moment generating function and the $r^{th}$ moment and others are presented. In addition, we discussed various important mathematical properties of the new distribution including estimation procedures for estimating the distribution parameters using the maximum likelihood and method of moments. The usefulness and credibility of the distribution are illustrated by means of two real-data applications to show its superior performance over some other well-known lifetime distributions and to prove its versatility in practical applications.

In this paper, data concerning MILANO EXPO2015 is collected from the official twitter page of the event before and after its opening. In order to extract a semi-supervised ontology and to evaluate the global sentiment around the event, a variety of language processing techniques has been applied on the collected “tweets”: Latent Semantic Analysis, sentiment polarity tracking, along with gap analysis has allowed the semantic evaluation of users’ opinions. Moreover, the generalized cross entropy approach has been applied for the first time on web data, adding prior information on the effect of semantic classes on the global sentiment, improving accuracy and adding detail to the analysis.

The present paper offers a new extension to the Ishita distribution called Size-Biased Ishia distribution (SBID). Various structural statistical properties of this distribution are derived such as the jth moment, moment generating function, the coefficients of variation, skewness and kurtosis. Also, the distribution of order statistics, harmonic mean, mode, reliability analysis, maximum likelihood estimation are provided, as well as the Fisher’s information, generalized and Renyi entropies are derived. The main advantage of using sized-based distributions appears when the sample are recorded with unequal probabilities. Accordingly, the superiority of the SBI distribution is illustrated to ball bearings data. It is shown that the SBID is the most appropriate model for this data set as compared to Rama distribution, Ishita distribution and Marshall–Olkin Esscher Transformed Laplace distribution. We believe that the SBID is an alternative distribution to lifetime data analysis.

Purpose Lifetime data are used in many different applied sciences, like biomedicine, engineering, insurance and finance and others. The purpose of this paper is to develop a new acceptance sampling plans for Rama distribution when the mean lifetime test is truncated at a pre-determined time. The minimum sample sizes required to assert the specified life mean is obtained for a given customer’s risk. The operating characteristic function values of the sampling plans and producer’s risk are calculated. Design/methodology/approach The results are illustrated using numerical examples and a real data set is considered to illustrate the performance of the suggested acceptance sampling plans and how it can be used for the industry applications. Findings This paper shows a new acceptance sampling plans based on Rama distribution in the particular case when the mean life time test is truncated. Originality/value The results calculated in this paper demonstrate the differences between OC values for different distributions taken into account. In particular, OC values of Rama distribution are found to be less than the proposed distribution counterparts.

Currently we are witnessing the revaluation of huge data recourses that should be analyzed carefully to draw the right decisions about the world problems. Such big data are statistically risky since we know that the data are combination of (useful) signals and (useless) noise, which considered as unorganized facts that need to be filtered and processed. Using the signals only and discarding the noise means that the data restructured and reorganized to be useful and it is called information. So for any data set, we need only the information. In context of information theory, the entropy is used as a statistical measure to quantify the maximum amount of information in a random event.

In this article, a new fuzzy entropy measure of order α is proposed. The fuzzy entropy axiomatic requirements are discussed for the new measure, and an empirical comparison are made with several entropy measures including Shannon, Rényi and Kapur. It turns out, the proposed measure satisfies all axiomatic and outperform the other entropy measures in terms of the fuzziness degree.Â

We develop a ranked acceptance sampling plan by attribute for exponential distribution assuming that the life test is truncated at a pre-assigned time. Two main requirements are essential for the proposed ranked sampling plans; namely; the life times of the test units are assumed to follow the exponential distribution; and the data are selected by using a free cost sampling method, the median ranked set sampling scheme from a large lot. The main advantage of using the median rank set sampling is to reduce producer’s risk, and it is one of the ranked scheme that produces a judgment order statistics that are mutually independent and identically distributed random variables to meet the binomial theory assumptions. The distribution function characterization under the median ranked set sampling scheme is derived assuming that the set size is known; then the minimum sample size necessary to ensure the specified average life are obtained and the operating characteristic values of the sampling plans based on the ranked samples and producer’s risk are presented. A comparisons with sampling plan based on simple random sampling and an illustrative example are given.

This article aims to estimate the population ratio using a multistage median ranked set sampling method. The mean squared errors and bias equations of the suggested estimators are obtained. The new estimators are compared with their counterparts using simple random sampling, ranked set sampling, and median ranked set sampling methods. A real data set is used for illustration. The results revealed that the multistage median ranked set sampling estimators are approximately unbiased in terms of the population ratio and their efficiencies increase in the number of stages for specific value of the sample size. Also, it is found that the multistage median ranked set sampling estimators are more efficient than their counterparts based on simple random sampling, ranked set sampling, and median ranked set sampling.

Khawar Ahmad started his poetic career in 1970’s and has published four books based on his poetic works So far. Like many poets, the basic theme of his poetry is ‘love’ and emotions related to it. Khawar’s uniqueness however, is that he discusses new aspects of a commonplace theme like ‘love’. In this article, it has been tried to bring new aspects of love as discussed by Khawar in his first poetic work.

A double acceptance sampling plan (DASP) based on truncated life tests is suggested in this paper when the lifetime of a product follows the exponentiated generalized inverse Rayleigh distribution (EGIR). For a fixed value of the consumer’s confidence level, the minimum sample sizes of the first and second samples needed to ensure the specified mean life are obtained. The operating characteristic values according to the different quality levels are obtained and the minimum ratios of the mean life to the specified life are calculated. The important tables based on the suggested DASP are calculated and illustrated.

This paper examines how bank efficiency and stability are affected by the market power in Africa. Our results show that the higher degree of market power is associated with high level of efficiency and profitability. The banks with more market power operating are able to be in command of the price and hence improve their profit. The market power has a benefit in both stability and risk. Hence, gain in market will increase the stability and reduce the risk for banking system. Our findings do not support the argument that competition should not be based on a “quiet life hypothesis”.

PurposeThe purpose of this study is to analytically extend the understanding of leadership styles and organisational coaching and their influence on organisational outcomes and workplace counterproductive behaviours within a non-Western context, i.e. the United Arab Emirates (UAE).Design/methodology/approachIn this study, a sample size of 656 participants from 14 different business sectors in the Emirates was used. The meta-analysis concept of latent variables and non-linear principal components analysis, along with the corresponding methodology of structural equation modelling, were implemented.FindingsThe study finds that organisational coaching has a significant positive effect on transactional leadership and has a significant influence on job alienation. Interestingly, coaching has a significant effect on commitment and counterproductive workplace behaviours. The detailed data analysis usingFtests and independentt-tests, when applicable, indicated that there was a tendency for older employees to have more favourable attitudes towards transformational leadership or commitment but not towards coaching.Originality/valueDespite the popularity of the presented topic in today's organisations, research in a Middle East context has not kept pace with its counterpart in Western areas of the world. The present study attempts to bridge the gap between Western theories in developed countries and under-researched Eastern countries, namely, the UAE, and to test the impact of leadership styles and organisational coaching and their influence on employee commitment and trust mediated by job bullying and job alienation.

In this chapter, the design of the Shewhart control chart based on ranked repetitive sampling is presented. The structure of the proposed control chart is given for the quality characteristic and follows the normal distribution. The necessary measures of this chart are given to assess its performance. The performance of the chart is evaluated using the average run length over the existing control chart. The application of the chart is given through simulation and a real example.

This is a study surrounding the interplay between Human Resource Management (HRM) and knowledge transfer within an emerging institutional petro-state. It seeks to link HRM and knowledge transfer through individual-level mechanisms in response to the recent calls for more research on micro-foundations. Our findings provide empirical evidence for the HRM-related factors influencing knowledge exchange in a sample of 815 employees in the national context of the UAE. We found that individual-level perceptions and extrinsic motivation have a positive impact on knowledge exchange; however, we found evidence to suggest only an indirect effect of individual perceptions of organisational commitment to knowledge exchange, via individual intrinsic motivation and social interaction. Unlike some existing accounts from the Western world, individual perceptions of organisational commitment to knowledge sharing had no direct positive impact on knowledge exchange – an issue that may be ascribed to the distinct institutional setting of the UAE. This paper adds to the existing literature on HRM and knowledge exchange by bringing to bear new evidence from a Middle Eastern emerging market setting – an area thus far relatively neglected in the literature.

Purpose – The purpose of this study is to establish both the validity of Western theories within the Middle East, namely, the United Arab Emirates (UAE), and to further improve and extend our understanding of the effect of organisational coaching on counterproductive behaviours, such as bullying and alienation. Design/methodology/approach – A sample size of 656 participants from 29 organisations and 14 different industries was employed. A research model was proposed, refined and tested through a quantitative paradigm using one dimension nonlinear principal components analysis, linear structural equation modelling (SEM) and MANOVA. Findings – The correlation analysis results show non-significant negative correlations between coaching and all of the organisational counterproductive behaviour dimensions but not certainty. It was found that a significant weak relationship exists between most of the mediator dimensions, while a strong relationship exists between job alienation and workplace bullying. Results of the linear SEM provide support that coaching is related to certainty. Furthermore, the results reveal that certainty mediates a significant link between coaching and organisational counterproductive work behaviours (job alienation and bullying). Originality/value – The study is considered the first in the UAE to investigate organisational counterproductive work behaviours (bullying and job alienation). The main contribution of this study is to quantify the relationship between organisational coaching and bullying and job alienation mediated by organisational climate dimensions.

Background: Viral cause of sporadic breast cancer (SBC) has been suggested based on the experimental murine model of mammary tumor caused by mouse mammary tumor virus (MMTV), Epstein-Barr virus (EBV), and human papillomavirus (HPV). While some studies have demonstrated the presence of viral sequences of MMTV, HPV, and EBV in breast cancer cells, others failed. These contradictions may be attributed to the geographical distribution of breast cancer incidence and/or technical variations. In the current study, we aimed to investigate the correlation of MMTV, HPV, and EBV infections with the development of breast cancer in Jordanian patients. Methods: One hundred SBC tissue samples were subjected to laser capture microdissection for the selection of tumor cells populations. Fluorescence polymerase chain reaction (PCR) was used to detect the presence of the MMTV env-like sequences. Real-time PCR was used for HPV and EBV detection, and EBV was further confirmed by chromogen in situ hybridization (CISH). Results: Mouse mammary tumor virus, HPV, and EBV were detected in SBC in 11%, 21%, and 23%, respectively. Only 3 of 52 (5.7%) positive cases demonstrated multiple virus infections. However, 49 of 52 (94%) of the positive cases revealed the presence of 1 type of viral sequences. Consequently, 52% of the studied breast cancer cases were infected with at least 1 type of the aforementioned viruses. Conclusions: The current cohort suggests that MMTV, HPV, and EBV have a potential role in the development of breast cancer and adding more reasons to proceed with the quest of a possible viral origin of breast cancer.

This article proposes using an information theoretic procedure in order to obtain an unbiased weighted mean estimator for the population mean when the data collection structure is truncated-based ranked set sampling. The performance of the proposed estimator is discussed along with its properties, and the optimal weights are computed by maximizing Shannon’s entropy. It is found that the weighted truncated-based ranked set sampling estimator is more accurate and more efficient than its unweighted counterpart or the simple random sampling-based estimators.

This paper presents a procedure utilizing the generalized maximum entropy (GME) estimation method in two steps to quantify the uncertainty of the simple linear structural measurement error model parameters exactly. The first step estimates the unknowns from the horizontal line, and then the estimates were used in a second step to estimate the unknowns from the vertical line. The proposed estimation procedure has the ability to minimize the number of unknown parameters in formulating the GME system within each step, and hence reduce variability of the estimates. Analytical and illustrative Monte Carlo simulation comparison experiments with the maximum likelihood estimators and a one-step GME estimation procedure were presented. Simulation experiments demonstrated that the two steps estimation procedure produced parameter estimates that are more accurate and more efficient than the classical estimation methods. An application of the proposed method is illustrated using a data set gathered from the Centre fo...

There is a growing concern that reduction in hospital length of stay (LOS) may raise the rate of hospital readmission. This study aims to identify the rate of avoidable 30-day readmission and find out the association between LOS and readmission.All consecutive patient admissions to the internal medicine services (n = 5,273) at King Abdullah University Hospital in Jordan between 1 December 2012 and 31 December 2013 were analyzed. To identify avoidable readmissions, a validated computerized algorithm called SQLape was used. The multinomial logistic regression was firstly employed. Then, detailed analysis was performed using the Decision Trees (DTs) model, one of the most widely used data mining algorithms in Clinical Decision Support Systems (CDSS).The potentially avoidable 30-day readmission rate was 44%, and patients with longer LOS were more likely to be readmitted avoidably. However, LOS had a significant negative effect on unavoidable readmissions.The avoidable readmission rate is still highly unacceptable. Because LOS potentially increases the likelihood of avoidable readmission, it is still possible to achieve a shorter LOS without increasing the readmission rate. Moreover, the way the DT model classified patient subgroups of readmissions based on patient characteristics and LOS is applicable in real clinical decisions.

In this paper, exponentiated Frechet distribution is considered as a model for a life time random variable when the life test is truncated at a pre-assigned time. The operating characteristic functions values of the suggested sampling plans and the corresponding producer's risk are obtained.

This paper implements the generalized maximum entropy (GME) method in longitudinal data setup to investigate the regression para meters and correlation among the repeated measurements. We derive the GME system using Shannon classical entropy as well as some higher-order entropies assuming an autoregressive correlation structure. This method is illustrated using two simulated examples to study the effect of changing the support range and compare the performance of the GME approach with the classical estimation methods.

Cichorium Pumilum (chicory) is could be a promising cancer treatment in which a photosensitizing drug concentrates in benign tumor cells and activated by quanta at certain wavelength. Such activated extracts could lead to cell death and tumor ablation. Previous studies have shown that Cichorium Pumilum (chicory) contains photosensitive compounds such as cichoriin, anthocyanins, lactucin, and Lactucopicrin. In the present study, the protective effect of sun light-activated Cichorium against the dimethylbenz[a]anthracene (DMBA) induced benign breast tumors to female Sprague-Dawley rats was investigated. Chicory's extract has significantly increase P.carbonyl (PC) and malondialdehyde (MDA) and decreases the hepatic levels of total antioxidant capacity (TAC) and superoxide dismutase (SOD) in benign breast tumors-induced group compared to control. It also significantly decrease the number of estrogen receptors ER-positive cells in tumor masses. These results suggest that chicory extracts could be used as herbal photosensitizing agent in treating benign breast tumor in rats.

The aim of this paper was to develop a national customer satisfaction index (CSI) in Jordan and to derive its theory using generalized maximum entropy. During the course of this research, we conducted two different surveys to complete the framework of this CSI. The first one is a pilot study conducted based on a CSI basket in order to select the main factors that comprise the Jordanian customer satisfaction index (JCSI). Based on two different analyses, namely nonlinear principal component analysis and factor analysis, the explained variances in the first and second dimensions were 50.32 and 16.99% respectively. Also, Cronbach coefficients α in the first and second dimensions were 0.923 and 0.521, respectively. The results of this survey suggests the inclusion of loyalty, complaint, expectation, image and service quality as the main CS factors of our proposed model. The second study is a practical implementation conducted on the Vocational Training Corporation in order to evaluate the proposed JCSI. The r...

PurposeThe purpose of this paper is to provide a robust statistical procedure for evaluating and measuring the relative efficiency of multiple decision‐making units. This robust approach is based on the generalized maximum entropy principle.Design/methodology/approachInformation‐theoretic estimation approach is employed in this paper and a comparison is made with the classical relative efficiency (CCR) by using a non‐parametric bootstrap simulation. A real data application on the research performance of faculty members at Yarmouk University is presented.FindingsResults indicate that the relative efficiency based on the generalized maximum entropy estimation approach is more accurate, costs less and is more efficient than the CCR relative efficiency.Research limitations/implicationsOwing to use of Shannon's entropy formulation, it is still critical whether the results also hold with cross entropy or a higher order entropy formulation for modeling additive, multiplicative or partial relative efficiency.Originality/valueA super data envelopment analysis has been introduced for finding superior decision‐making units (DMU) by solving only one nonlinear programming system, which could be considered as a flexible tool for modeling multiple input‐output DMU.

The activity of the methylenetetrahydrofolate reductase (MTHFR) enzyme is regulated by the two polymorphisms C677T and A1298C, which reduce enzyme activity and result in hypomethylation of chromosomes that increase the risk of nondisjunction. These polymorphisms are suggested to be risk factors for Down syndrome (DS) in some populations.The aim of this study was to test if C677T and A1298C polymorphisms are correlated to maternal risk of DS in Jordan.The proportions of C677T and A1298C polymorphisms were examined in 53 case mothers who delivered DS children and 29 controls. The median age of case mothers was 35 years when delivering their affected children. Polymerase chain reaction-restriction fragment length polymorphism was used for genotyping.The frequency of MTHFR C677T allele in all DS mothers was 3.2-fold higher than in the controls (odds ratio [OR] = 3.12, 95% confidence interval [CI]: 1.303-7.677). Also, the proportion of 677T in the older case mothers was different from the controls, but was significantly higher in younger case mothers than in the controls (OR = 4.2, 95% CI: 1.61-10.97, p = 0.003). The proportions of 677CT and 677TT genotypes in younger cases are, respectively, 10- and 9-fold higher than in the controls. The proportions of MTHFR A1298C are significantly different among all case groups and the controls (χ(2) = 4.27, p = 0.127), but there was a significant difference between young case mothers and both older case mothers group and the controls (OR = 1.25, 95% CI: 0.405-3.85, p = 0.698).There is strong association between MTHFRC677T and maternal risk of DS in Jordanian mothers younger than 35 years old and the MTHFR1298C allele has a lesser but additive risk effect in MTHFR677T/1298C compound heterozygotes.

Objectives The aim was to evaluate the awareness and implementation of the Smoking Cessation Clinical Practice (SCCP) guidelines. Methods A self-reported questionnaire based on the updated version of the SCCP guidelines was completed by 422 healthcare providers (HCPs) including physicians, dentists, dental hygienists and pharmacists recruited from both public and private sectors in Jordan. Key findings The majority of HCPs reported good smoking-cessation practices. However, their awareness about the SCCP guidelines was inadequate. Approximately 68% of HCPs lacked knowledge of the 5As; about 74% lacked knowledge of the 5Rs of the clinical guidelines for smoking cessation, which are the principal guidelines for smoking intervention and motivation to quit smoking. Fortunately, about 70% of participants from all groups examined and applied most of the steps in the guideline spontaneously without previous knowledge of the guideline. This spontaneous practice could be due to their vast practical experience, and the use of logic and/or basic knowledge about smoking cessation. Compared to physicians, pharmacists and dental hygienists showed significantly more frequent practice of most steps with patients willing to quit smoking. Conclusions Jordanian HCPs showed good, spontaneous smoking-cessation practice. However, this practice could have been better if HCPs had adequate awareness of the SCCP guidelines.

In this paper, a robust extreme ranked set sampling (RERSS) procedure for estimating the population mean is introduced. It is shown that the proposed method gives an unbiased estimator with smaller variance, provided the underlying distribution is symmetric. However, for asymmetric distributions a weighted mean is given, where the optimal weights are computed by using Shannon's entropy. The performance of the population mean estimator is discussed along with its properties. Monte Carlo simulations are used to demonstrate the performance of the RERSS estimator relative to the simple random sample (SRS), ranked set sampling (RSS) and extreme ranked set sampling (ERSS) estimators. The results indicate that the proposed estimator is more efficient than the estimators based on the traditional sampling methods.

The correlations between the presence of MTHFR 677 (C>T) and MTHFR 1298 (A>C) mutations in human lymphocytes and the sensitivity of lymphocytes to methotrexate (MTX) were examined in cultures derived from 82 unrelated women, genotyped for these mutations by polymerase chain reaction–restriction fragment length polymorphism. Lymphocytes heterozygous for the mutant allele, MTHFR 677T, were significantly more sensitive to methotrexate than those carrying the homozygous wild-type allele, MTHFR677C, and those carrying either the mutant or the wild-type alleles in the polymorphic MTHFR 1298 site. In addition, the lymphocyte cultures carrying the mutant MTHFR 1298C allele were not different in their sensitivity to MTX from those cultures carrying the wild-type allele, MTHFR 1298A. This demonstrated that the polymorphic site MTHFR C677, but not MTHFR1298, could be considered as a useful pharmacogenetic determinant in planning and designing the effective personal MTX chemotherapeutic doses and regimes.

In this work, we investigate a double acceptance sampling plan (DASP) based on truncated life tests when the lifetime of a product follows the half normal distribution. By fixing the consumer’s confidence level, the minimum sample sizes of the first and second samples needful to assert the specified mean life are calculated. The operating characteristic values and the minimum ratios of the mean life to the specified life are also analyzed. Several important tables are provided and a numerical example is given to illustrate the results.

In this article, a robust ranked set sampling (LRSS) scheme for estimating population mean is introduced. The proposed method is a generalization for many types of ranked set sampling that introduced in the literature for estimating the population mean. It is shown that the LRSS method gives unbiased estimator for the population mean with minimum variance providing that the underlying distribution is symmetric. However, for skewed distributions a weighted mean is given, where the optimal weights is computed by using Shannon's entropy. The performance of the population mean estimator is discussed along with its properties. Monte Carlo comparisons for detecting outliers are made with the traditional simple random sample and the ranked set sampling for some distributions. The results indicate that the LRSS estimator is superior alternative to the existing methods.

Interval estimation of the scale parameter of the gamma distribution using grouped data is considered in this article. Exact intervals do not exist and approximate intervals are needed Recently, Chen and Mi (2001) proposed alternative approximate intervals. In this article, some bootstrap and jackknife type intervals are proposed. The performance of these intervals is investigated and compared. The results show that some of the suggested intervals have a satisfactory statistical performance in situations where the sample size is small with heavy proportion of censoring.

In this article, an estimation procedure to simple linear regression in the presence of outliers is proposed. The performance of the proposed estimator, the AM estimator, is compared with other traditional estimators: least squares, Theil type repeated median, and geometric mean. A numerical example is given to illustrate the proposed estimator. Simulation results indicate that the proposed estimator is accurate and has a high precision in the presence of outliers.

We analyze a batch arrival queue with a single server providing two kinds of general heterogeneous service. Just before his service starts, a customer may choose one of the services and as soon as a service (of any kind) gets completed, the server may take a vacation or may continue staying in the system. The vacation times are assumed to be general and the server vacations are based on Bernoulli schedules under a single vacation policy. We obtain explicit queue size distribution at a random epoch as well as at a departure epoch and also the mean busy period of the server under the steady state. In addition, some important performance measures such as the expected queue size and the expected waiting time of a customer are obtained. Further, some interesting particular cases are also discussed.

The application of some bootstrap type intervals for the scale parameter of the Burr type X distribution with grouped data is proposed. The general asymptotic confidence interval procedure (Chen & Mi, 2001) is studied. The performance of these intervals is investigated and compared. Some of the bootstrap intervals give better performance for situations of small sample size and heavy censoring.

This article deals with multiple linear functional relationships models. Two robust estimations procedure are proposed to estimate the model, based on Generalized Maximum Entropy and Partial Least Square. They are distribution free and do not rely (so much) on classical assumptions. The experiments showed that the GME approach outperforms the PLS in terms of mean squares of errors (MSE). Empirical examples are studied.

We study a single server queue with batch arrivals and two types of heterogeneous service with different general (arbitrary) service time distributions. The server provides either type of service to customers, one by one, on a first come, first served basis. Just before a service starts, a customer has the option to choose either type of service after completion of which the customer may leave the system or may opt for re-service of the service taken by him. We obtain steady-state results in explicit and closed form in terms of the probability generating functions for the number of customers in the queue and the system, the average number of customers and the average waiting time in the queue as well as the system. Some special cases of interest are discussed and some known results have been derived. A numerical illustration is provided.

In this article a new single sampling plan based on ranked data scheme is proposed. Two main requirements are considered for the new plan: the lifetime of the test units is assumed to follow the generalized exponential distribution; and the data are selected by using the median ranked set sampling scheme from a large lot. The distribution function characterization under the median ranked set sampling scheme is derived assuming that the set size is known; the minimum number of set cycle and consequently the minimum sample size necessary to ensure the specified average life are obtained and the operating characteristic values of the ranked sampling plans as well as the producer’s risk are presented. An illustrative examples based on the results obtained are given.

This paper examines the influence of financial and non-financial performance measures on perceived Islamic banks’ service quality in the United Arab Emirates. External customers and internal customers of Islamic banks were considered in the study. External customers represent individuals dealing with the banks and their sample consisted of 230 customers. Internal bank customers represent banks’ employees with a sample size of 174 participants from five main Islamic banks in UAE. Data were collected mainly through a questionnaire and analyzed and tested through two proposed models using structural equation modeling techniques. The results indicate strong positive relationship between service quality and banks’ performance and that banks internal operations mediate the relationship for the external customers group.

Socio-demographic Characteristics as Risk Factors for Hepatitis C Virus Infection among Pregnant Women in Iraq Hepatitis C virus (HCV) infection is a major public health, affecting approximately 180 million persons worldwide. It was documented that HCV are accounting for 70%-90% of hepatocellular carcinoma (HCC) cases worldwide. Interestingly, Ly et al. predicted that by year 2020, the annual death rate due to liver cirrhosis or HCC is expected to be around 18,000 persons. HCV infection considered as a significant major public health burden in both industrialized and developing countries. However, region specific variation in prevalence of HCV infection was detected with the highest prevalence were (15-20%) in Egypt.

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

In this paper, the robust extreme ranked set sampling (RERSS) scheme is considered for estimating the population median. The RERSS is compared with the simple random sampling (SRS), ranked set sampling (RSS) and extreme ranked set sampling (ERSS) schemes. A Monte Carlo simulation study is used to study the performance of the median estimator. It is found that RERSS estimators are unbiased of the population median when the underlying distribution is symmetric. Also, in terms of the efficiency criterion; the median estimator based on RERSS is more efficient than the median estimators based on SRS, ERSS, and RSS for symmetric and asymmetric distributions considered in this study. For asymmetric distributions, the RERSS estimators have a smaller bias.