Search results for: profile likelihood

Authors: T. Sattarpour, D. Nazarpour

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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

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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: 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: J. R. Lee, E. V. Lau

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Ionic wind is developed when high voltage is supplied to an anode and a grounded cathode in a gaseous medium. This paper studies the ionic wind profile with different anode configurations, the relationship between electrode gap against the voltage supplied and finally a comparison of the heat transfer coefficient of ionic wind over a horizontal flat plate against a conventional fan experimentally. It is observed that increase in the distance between electrodes decreases at a rate of 1-e-0.0206x as the voltage supply is increased until a distance of 3.1536cm. It is also observed that the wind speed produced by ionic wind is stronger, 2.7ms-1 at 2W compared to conventional fan, 2.5ms-1 at 2W but the wind produced decays at a fast exponential rate and is more localized as compared to conventional fan wind that decays at a slower exponential rate and is less localized. Next, it is found out that the ionic wind profile is the same regardless of the position of the anode relative to the cathode. Lastly, it is discovered that ionic wind produced a heat transfer coefficient that is almost 1.6 times higher compared to a conventional fan with Nusselt number reaching 164 compared to 102 for conventional fan.

Keywords: conventional fan, heat transfer, ionic wind, wind profile

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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: Shahana Sharmin

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In the present study, the effect of cellulose polymers Ethyl Cellulose and Hydroxy Propyl Methyl Cellulose was evaluated on the release profile of drug from sustained release pellet. Diltiazem Hydrochloride, an antihypertensive, cardio-protective agent and slow channel blocker were used as a model drug to evaluate its release characteristics from different pellets formulations. Diltiazem Hydrochloride sustained release pellets were prepared by drug loading (drug binder suspension) on neutral pellets followed by different percentages of spraying, i.e. 2%,4%, 6%, 8% and 10% coating suspension using ethyl cellulose and hydroxy-propyl methyl cellulose polymer in a fixed 85:15 ratios respectively. The in vitro dissolution studies of Diltiazem Hydrochloride from these sustained release pellets were carried out in pH 7.2 phosphate buffer for 1, 2, 3, 4, 5, 6, 7, and 8 hrs using USP-I method. Statistically, significant differences were found among the drug release profile from different formulations. Polymer content with the highest concentration of Ethyl cellulose on the pellets shows the highest release retarding rate of the drug. The retarding capacity decreases with the decreased concentration of ethyl cellulose. The release mechanism was explored and explained with zero order, first order, Higuchi and Korsmeyer’s equations. Finally, the study showed that the profile and kinetics of drug release were functions of polymer type, polymer concentration & the physico-chemical properties of the drug.

Keywords: diltiazem hydrochloride, ethyl cellulose, hydroxy propyl methyl cellulose, release kinetics, sustained release pellets

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Authors: Beghdadi Lotfi

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In the present work a numerical method is proposed in order to optimize the thermal performance of finned surfaces. The bidimensional temperature distribution on the longitudinal section of the fin is calculated by restoring to the finite volumes method. The heat flux dissipated by a generic profile fin is compared with the heat flux removed by the rectangular profile fin with the same length and volume. In this study, it is shown that a finite volume method for quadrilaterals unstructured mesh is developed to predict the two dimensional steady-state solutions of conduction equation, in order to determine the sinusoidal parameter values which optimize the fin effectiveness. In this scheme, based on the integration around the polygonal control volume, the derivatives of conduction equation must be converted into closed line integrals using same formulation of the Stokes theorem. The numerical results show good agreement with analytical results. To demonstrate the accuracy of the method, the absolute and root-mean square errors versus the grid size are examined quantitatively.

Keywords: Stokes theorem, unstructured grid, heat transfer, complex geometry, effectiveness

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Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

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Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Umang H. Gajjar, K. M. Khambholja, R. K. Patel

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Semecarpus anacardium shows the presence of bioflavonoids, phenolic compounds, bhilawanols, minerals, vitamins and amino acids. Detoxified S. anacardium and its oils are considered to have anti-inflammatory properties and used in nervous debility, neuritis, rheumatism and leprous modules. S. anacardium if used without purification causes toxic skin inflammation problem because it contains toxic phenolic oil. During this Shodhana Process - An ayurvedic purification method, toxic phenolic oil was removed, have marked effect on the concentration of the phytoconstituent & antioxidant activity of S. anacardium. Total phenolic content decreased up to 70 % (from 28.9 %w/w to 8.94 %w/w), while there is a negligible effect on the concentration of total flavonoid (7.51 %w/w to 7.43 %w/w) and total carbohydrate (0.907 %w/w to 0.853 % w/w) content. IC50& EC50 value of extract of S. anacardium before and after purification are 171.7 & 314.3 while EC50values are 280.μg/ml & 304. μg/ml, shows that antioxidant activity of S. anacardium is decreased but the safety profile of the drug is increased as the toxic phenolic oil was removed during Shodhana - An ayurvedic purification method.

Keywords: Semecarpus anacardium, Shodhana process, safety profile, improvement

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Authors: Choki, Supatchai Boonpratham, Suwannee Luppanapornlarp

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The objective of this study was to find a correlation between cephalometric measurements and visual perception of facial profile in skeletal type II patients. In this study, 250 lateral cephalograms of female patients from age, 20 to 22 years were analyzed. The profile outlines of all the samples were hand traced and transformed into silhouettes by the principal investigator. Profile ratings were done by 9 orthodontists on Visual Analogue Scale from score one to ten (increasing level of convexity). 37 hard issue and soft tissue cephalometric measurements were analyzed by the principal investigator. All the measurements were repeated after 2 weeks interval for error assessment. At last, the rankings of visual perceptions were correlated with cephalometric measurements using Spearman correlation coefficient (P < 0.05). The results show that the increase in facial convexity was correlated with higher values of ANB (A point, nasion and B point), AF-BF (distance from A point to B point in mm), L1-NB (distance from lower incisor to NB line in mm), anterior maxillary alveolar height, posterior maxillary alveolar height, overjet, H angle hard tissue, H angle soft tissue and lower lip to E plane (absolute correlation values from 0.277 to 0.711). In contrast, the increase in facial convexity was correlated with lower values of Pg. to N perpendicular and Pg. to NB (mm) (absolute correlation value -0.302 and -0.294 respectively). From the soft tissue measurements, H angles had a higher correlation with visual perception than facial contour angle, nasolabial angle, and lower lip to E plane. In conclusion, the findings of this study indicated that the correlation of cephalometric measurements with visual perception was less than expected. Only 29% of cephalometric measurements had a significant correlation with visual perception. Therefore, diagnosis based solely on cephalometric analysis can result in failure to meet the patient’s esthetic expectation.

Keywords: cephalometric measurements, facial profile, skeletal type II, visual perception

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Authors: Bahaa Eldin Kornah

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The organism profile for peri-prosthetic joint infection caused by hematogenous seeding or direct inoculations is changing. The organisms that cause prosthetic joint infections range from normal skin colonizers to highly virulent pathogens. The pathogens continue to evolve. While Staphylococcus aureus continues to be the leading organism, gram-negative bacilli account for approximately 7% of cases and that incidence is increasing. Methicillin-resistant S. aureus(MRSA) accounts for approximately 10% of all infections occurring in the community setting and 20% of those in the health care setting. The list of organisms causing PJI has expanded in recent years. It is important to have an understanding of which organisms may be causing a periprosthetic joint infection based on where the patient contracted it and their recent medical history. Also, recent technology has expanded rapidly and new methods to detect the pathogen and why we failed in detecting it. There are a number of explanations for the latter finding, perhaps the most important reason being the liberal use of antibiotics that interferes with the isolation of the infective organism.

Keywords: infection, periprosthetic, hip, organism profile, joint infection, joint infection

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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: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

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To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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Authors: Helen Frialde-Dupale

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Critical thinking Index (CTI) of 150 third year college students from five State Colleges and Universities (SUCs) in Region I were determined. Only students with Grade Point Average (GPA) of at least 2.0 from four general classification of degree courses, namely: Education, Arts and Sciences, Engineering and Agriculture were included. Specific problem No.1 dealt with the profile variables, namely: age, sex, degree course, monthly family income, number of siblings, high school graduated from, grade point average, personality type, highest educational attainment of parents, and occupation of parents. Problem No. 2 determined the critical thinking index among the respondents. Problem No. 3 investigated whether or not there are significant differences in the critical thinking index among the respondents across the profile variables. While problem No.4 determined whether or not there are significant relationship between the critical thinking index and selected profile variables, namely: age, monthly family income, number of siblings, and grade point average of the respondents. Finally, on problem No. 5, the critical thinking instrument which obtained the lowest rates, were used as basis for outlining an intervention program for enhancing critical thinking index (CTI) of students. The following null hypotheses were tested at 0.05 level of significance: there are no significant differences in the critical thinking index of the third college students across the profile variables; there are no significant relationships between the critical thinking index of the respondents and selected variables, namely: age, monthly family income, number of siblings, and grade point average.

Keywords: attitude as critical thinker, critical thinking applied, critical thinking index, self-perception as critical thinker

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Authors: Subhamita Chakraborty, Shubhabrata Datta, Sujay Kumar Mukherjea, Partha Protim Chattopadhyay

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Manufacturing of multiphase high strength steel in hot strip mill have drawn significant attention due to the possibility of forming low temperature transformation product of austenite under continuous cooling condition. In such endeavor, reliable prediction of temperature profile of hot strip coil is essential in order to accesses the evolution of microstructure at different location of hot strip coil, on the basis of corresponding Continuous Cooling Transformation (CCT) diagram. Temperature distribution profile of the hot strip coil has been determined by using finite volume method (FVM) vis-à-vis finite difference method (FDM). It has been demonstrated that FVM offer greater computational reliability in estimation of contact pressure distribution and hence the temperature distribution for curved and irregular profiles, owing to the flexibility in selection of grid geometry and discrete point position, Moreover, use of finite volume concept allows enforcing the conservation of mass, momentum and energy, leading to enhanced accuracy of prediction.

Keywords: simulation, modeling, thermal analysis, coil cooling, contact pressure, finite volume method

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Authors: Merzougui Imene, Gherib Asma, Henchiri Cherifa

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This study has allowed to confirm the physico chemical characteristics and fatty acid composition by GC of the oil of Pistacia lentiscus extracted by traditional method and evaluate its effect on some blood lipid parameters. The results showed that the main physico chemical characteristics of Pistacia lentiscus oil are: moisture (0.84 %), a relatively high iodine value (80,44) indicating that this oil has an important degree of unsaturation. The oil is mainly composed of unsaturated fatty acids (MUFA) where oleic acid dominate with 47,01 % of total fatty acids and PUFA's represented by linoleic acid (19,26 %). Concerning the biological survey, oil, at 10% and 20% doses of diet for 15 and 30 days of two periods of treatment, resulted in beneficial effects on the lipid profile of Wistar albinos rats previously fed with animal and vegetable fats. We observed decreases in total cholesterol, triglycerides (TGA), total lipids and LDL-C, and an increase in HDL-C "good cholesterol" probably related to the presence of a large amount of (MUFA) and (PUFA).

Keywords: Pistacia lentiscus, oil, lipid profile, monounsaturated fatty acids, polyunsaturated fatty acids

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Authors: Reem Alkadeem

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This study aims at evaluating the overall satisfaction of faculty members and relating it to organizational and personal aspects in Egyptian public and private universities. These aspects are identified through an extensive study of all factors that might affect job satisfaction. The most influencing parameters selected are academics’ demographics, human resource management, organizational profile, workload, teamwork skills, recognition, autonomy, teaching activity, research activity, and motivation. A questionnaire of 94 questions was used to assess job satisfaction and the previously mentioned parameters. It was distributed among seven hundred members of different universities in Egypt. Two hundred and twenty-seven faculty members responded. This sample was gathered from twelve universities and The Supreme Council of Universities. The ANOVA showed a significant relationship (p < 0.05) between eight of the selected parameters and job satisfaction. These parameters are age, rank, human resource management, profile of organizational characteristics, workload, recognition, teaching activity, and motivation.

Keywords: job satisfaction, higher education, organizational profile, Egyptian universities

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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: M. M. Alhaji, M. Alhassan, A. M. Yahaya

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Soil engineers pay very little or no attention to variation in the mineralogical and consequently, the geotechnical properties of overburden with depth on basement complexes, a situation which can lead to sudden failure of civil engineering structures. Soil samples collected at depths ranging from 0.5m to 4.0m at 0.5m intervals, from a trial pit dogged manually to depth of 4.0m on an overburden over gneiss basement complex, was evaluated for physico-chemical, mineralogical and physical properties. This is to determine the variation of these properties with depth within the profile of the strata. Results showed that sodium amphibolite and feldspar, which are both primary minerals dominate the overall profile of the overburden. Carbon which dominates the lower profile of the strata was observed to alter to gregorite at upper section of the profile. Organic matter contents and cation exchange capacity reduces with increase in depth while lost on ignition and pH were relatively constant with depth. The index properties, as well as natural moisture contents, increases from 0.5m to between 1.0m to 1.5m depth after which the values reduced to constant values at 3.0m depth. The grain size analysis shows high composition of sand sized particles with silts of low to non-plasticity. The maximum dry density (MDD) values are generally relatively high and increases from 2.262g/cm³ at 0.5m depth to 2.410g/cm³ at 4.0m depth while the optimum moisture content (OMC) reduced from 9.8% at 0.5m depth to 6.7% at 4.0m depth.

Keywords: Gneiss basement complex, mineralogical properties, North Central Nigeria, physico-chemical properties, physical properties, overburden soil

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Authors: Kayode A. Olaniyi, Tola. M. Osifeko, Adeola A. Ogunleye

Abstract:

Text line segmentation is an important step in document image processing. It represents a labeling process that assigns the same label using distance metric probability to spatially aligned units. Text line detection techniques have successfully been implemented mainly in printed documents. However, processing of the handwritten texts especially unconstrained documents has remained a key problem. This is because the unconstrained hand-written text lines are often not uniformly skewed. The spaces between text lines may not be obvious, complicated by the nature of handwriting and, overlapping ascenders and/or descenders of some characters. Hence, text lines detection and segmentation represents a leading challenge in handwritten document image processing. Text line detection methods that rely on the traditional global projection profile of the text document cannot efficiently confront with the problem of variable skew angles between different text lines. Hence, the formulation of a horizontal line as a separator is often not efficient. This paper presents a technique to segment a handwritten document into distinct lines of text. The proposed algorithm starts, by partitioning the initial text image into columns, across its width into chunks of about 5% each. At each vertical strip of 5%, the histogram of horizontal runs is projected. We have worked with the assumption that text appearing in a single strip is almost parallel to each other. The algorithm developed provides a sliding window through the first vertical strip on the left side of the page. It runs through to identify the new minimum corresponding to a valley in the projection profile. Each valley would represent the starting point of the orientation line and the ending point is the minimum point on the projection profile of the next vertical strip. The derived text-lines traverse around any obstructing handwritten vertical strips of connected component by associating it to either the line above or below. A decision of associating such connected component is made by the probability obtained from a distance metric decision. The technique outperforms the global projection profile for text line segmentation and it is robust to handle skewed documents and those with lines running into each other.

Keywords: connected-component, projection-profile, segmentation, text-line

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Authors: N. Dahbi, D. E. Arafah

Abstract:

Cd1−xZnxS thins films have been fabricated from ZnS/CdS/ZnS multilayer thin film systems, by using the vacuum deposition method; the Rutherford back-scattering (RBS) technique have been applied in order to determine the: structure, composition, depth profile, and stoichiometric of these films. The influence of the chemical and heat treatments on the produced films also have been investigated; the RBS spectra of the films showed that homogenous Cd1−xZnxS can be synthesized with x=0.45.

Keywords: Cd1−xZnxS, chemical treatment, depth profile, heat treatment, RBS, RUMP simulation, thin film, vacuum deposition, ZnS/CdS/ZnS

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Authors: S. Mawlood, L. Denanny, N. Watson, B. Pickard

Abstract:

DNA analysis has been widely accepted as providing valuable evidence concerning the identity of the source of biological traces. Our work has showed that DNA samples can survive on cartridges even after firing. The study also raised the possibility of determining other information such as the age of the donor. Such information may be invaluable in certain cases where spent cartridges from automatic weapons are left behind at the scene of a crime. In spite of the nature of touch evidence and exposure to high chamber temperatures during shooting, we were still capable to retrieve enough DNA for profile typing. In order to estimate age of contributor, DNA methylation levels were analyzed using EpiTect system for retrieved DNA. However, results were not conclusive, due to low amount of input DNA.

Keywords: DNA profile, DNA Methylation, fired cartridge, touch sample

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Authors: Luis N. Pereira, Marco P. Carrasco

Abstract:

Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Fu Jinyu, Lin Jinguan

Abstract:

This paper introduces a novel approach that unifies two types of models: one is the continuous-time jump-diffusion used to model high-frequency data, and the other is discrete-time GQARCH employed to model low-frequency financial data by embedding the discrete GQARCH structure with jumps in the instantaneous volatility process. This model is named “GQARCH-It\^{o} -Jumps mode.” We adopt the realized range-based threshold estimation for high-frequency financial data rather than the realized return-based volatility estimators, which entail the loss of intra-day information of the price movement. Meanwhile, a quasi-likelihood function for the low-frequency GQARCH structure with jumps is developed for the parametric estimate. The asymptotic theories are mainly established for the proposed estimators in the case of finite activity jumps. Moreover, simulation studies are implemented to check the finite sample performance of the proposed methodology. Specifically, it is demonstrated that how our proposed approaches can be practically used on some financial data.

Keywords: It\^{o} process, GQARCH, leverage effects, threshold, realized range-based volatility estimator, quasi-maximum likelihood estimate

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Authors: Fatemah A. Alqallaf, Debasis Kundu

Abstract:

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

Procedia PDF Downloads 115