Junction trees constructions in Bayesian networks

© Published under licence by IOP Publishing Ltd. Junction trees are used as graphical structures over which propagation will be carried out through a very important property called the ruining intersection property. This paper examines an alternative method for constructing junction trees that are essential for the efficient computations of probabilities in Bayesian networks. The new proposed method converts a sequence of subsets of a Bayesian network into a junction tree, in other words, into a set of cliques that has the running intersection property. The obtained set of cliques and separators coincide with the junction trees obtained by the moralization and triangulation process, but it has the advantage of adapting to any computational task by adding links to the Bayesian network graph

Human Capital and Health Education Among Menopausal Emirati Women in Dubai: Implications and Recommendations

Health is a kind of human capital as well as an input to producing other forms of human capital. Being unhealthy depresses the ability to work productively and/or the ability and incentives to invest in human capital. Consequently, health education is a major key that is designed to help women and communities, in general, improve their health, by increasing their knowledge or influencing their attitudes. A community-based study of a random sample of 497 Emirati women aged 30–64 years attending primary health-care centers in the Emirate of Dubai was conducted. The proposed study investigated the Emirati women\u27s knowledge about and attitudes toward menopause and menopause Hormone Replacement Theory (HRT). This study added more information about Emirati menopausal women to the limited menopause research in the Arab world and specifically in the UAE. This will enable the delivery of better health education based on increased awareness of health issues which enables health-care policymakers to create and formulate a health-care policy that further increases awareness and has the potential to enhance menopausal women’s quality of life and therefore reach their full potential at work

Convergence analysis of a highly accurate Nyström scheme for Fredholm integral equations

© 2019 IMACS A stable and convergent Nyström scheme is proposed to solve Fredholm integral equations (FIEs). Our approximation is based on the barycentric rational interpolants. By introducing barycentric quadratures to the integral operator that appears in the FIE and modifying the standard Nyström scheme, we demonstrate that the new Nyström scheme is a viable option for the numerical solution of FIEs. Convergence rates of the method are proved taking into account the effect of grading the domain. The final convergence result shows clearly that one can choose an optimal domain grading. Numerical examples and comparisons with competitive methods of tunable accuracy are provided to support the theoretical analysis and illustrate the efficiency of the proposed numerical scheme

Relationships between teamwork and suicidal behavior in Juvenile detention facilities using Bayesian networks

© 2019, © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. This study examines the importance of teamwork among correctional officers within juvenile detention facilities and its relation to preventing suicides among youth. The analysis is done using Probabilistic Structural Equations Models implemented within Bayesian Network (PSEM) conducted using BayesiaLab software. PSEM are used to find possible relationships among the different variables involved in this study and to learn more about the importance of teamwork and how it can help prevent suicides. Youth who are incarcerated are more likely to contemplate suicide due to isolation within the facilities, which could lead to changes in negative behavior. This behavior needs to be monitored and communicated among correctional officers in order to save lives. The results indicated that teamwork and communication are important deterrents to suicide prevention. Results show that the strongest the communication and teamwork among correctional officers, the less youth suicidal behavior

Factorization of computations in Bayesian networks: Interpretation of factors

© Springer International Publishing Switzerland 2017. Given a Bayesian network (BN) relative to a set I of discrete random variables, we are interested in computing the probability distribution PS, where the target S is a subset of I. The general idea is to express PS in the form of a product of factors whereby each factor is easily computed and can be interpreted in terms of conditional probabilities. In this paper, a condition statingwhen PS can be written as a product of conditional probability distributions is called a non-pathology condition. This paper also considers an interpretation of the factors involved in computing marginal probabilities in BNs and a representation of the probability target as a Bayesian network of level two. Establishing such a factorization and interpretations is indeed interesting and relevant in the case of large BNs

Forecasting with deep learning: S&P 500 index

Stock price prediction has been the focus of a large amount of research but an acceptable solution has so far escaped academics. Recent advances in deep learning have motivated researchers to apply neural networks to stock prediction. In this paper, we propose a convolution-based neural network model for predicting the future value of the S&P 500 index. The proposed model is capable of predicting the next-day direction of the index based on the previous values of the index. Experiments show that our model outperforms a number of benchmarks achieving an accuracy rate of over 55%

Uniqueness of the Level Two Bayesian Network Representing a Probability Distribution

Bayesian Networks are graphic probabilistic models through which we can acquire, capitalize on, and exploit knowledge. they are becoming an important tool for research and applications in artificial intelligence and many other fields in the last decade. This paper presents Bayesian networks and discusses the inference problem in such models. It proposes a statement of the problem and the proposed method to compute probability distributions. It also uses D-separation for simplifying the computation of probabilities in Bayesian networks. Given a Bayesian network over a family of random variables, this paper presents a result on the computation of the probability distribution of a subset of using separately a computation algorithm and D-separation properties. It also shows the uniqueness of the obtained result

Psychological climacteric symptoms and attitudes toward menopause among Emirati women

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Menopause is an inevitable developmental event that women encounter at an age of 42–54 years. The drop of estrogen levels that accompanies cessation of menstruation is associated with multiple vasomotor, physical, neuropsychological, and sexual symptoms, which may hamper quality of life. This study aimed to examine the severity of psychological symptoms and their correlates among peri-and postmenopausal Emirati women (N = 60, mean age = 54.88 ± 6 years). Participants were interviewed using the Menopause-Specific Quality of Life (MENQOL) and attitudes toward menopause scale (ATMS). In four path analysis models, vasomotor symptoms, weight gain, and fatigue had significant direct effects on symptoms of anxiety, depression (only weight gain and fatigue), and psychological distress. Fatigue significantly mediated the effects of vasomotor symptoms and weight gain on symptoms of anxiety, depression (only vasomotor symptoms), psychological distress, and memory problems. These models explained 47.6%, 44.5%, 56.6%, and 29.1% of the variances in anxiety, depression, psychological distress, and memory problems, respectively. Participants with more severe menopausal symptoms expressed more negative attitudes toward menopause though regression analysis revealed that only vasomotor symptoms could significantly contribute to ATMS scores. In conclusion, psychological distress is widespread among menopausal women, and it is associated with vasomotor symptoms, fatigue, and change of body composition (obesity). Psychological symptoms, along with vasomotor symptoms, express a key link to negative attitudes toward menopause. Therefore, interventional strategies that target psychological distress may promote coping with midlife transition and improve mental health among menopausal women

Emirati women’s knowledge about the menopause and menopausal hormone therapy

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The aim of this study was to investigate the knowledge of Emirati women aged 30–64 about menopause, menopausal hormone therapy (MHT), and their associated health risks, and additionally, to determine the relationships between Emirati women’s knowledge about menopause and their sociodemographic and reproductive characteristics. A community-based cross-sectional study was conducted of 497 Emirati women visiting five primary healthcare centers in Dubai. Data were collected using a questionnaire composed of sociodemographic and reproductive characteristics, menopause knowledge scale (MKS), and menopause symptoms knowledge and MHT practice. The mean menopause symptoms knowledge percentage was 41%, with a standard deviation of 21%. There were significant differences in the mean knowledge percentage among categories of education level (p \u3c 0.001) and employment (p = 0.003). No significant differences in the knowledge percentages were found among categories of menopausal status. “Pregnancy cannot occur after menopause” was the statement with the highest knowledge percentage (83.3%), while the lowest knowledge percentages were “risk of cardiovascular diseases increases with menopause” (23.1%), “MHT increases risk of breast cancer” (22.1%), and “MHT decreases risk of colon cancer” (13.9%). The knowledge of Emirati women about menopause, MHT, and related heart diseases was very low; therefore, an education campaign about menopause and MHT risks is needed to improve their knowledge for better coping with the symptoms

Intelligent Green Communication Network for Internet of Things

The text covers the advanced and innovative concept of green communication networks using the Internet of Things in different fields including cloud technology, agriculture, the automobile sector, and robotics. It will also help readers in learning the efficient use of sensors and devices in the Internet of Things networks. The text covers 5G communication and its application for intelligent and green network-enabled Internet of Things. This book • Discusses intelligent and green networking-enabled Internet of Things • Covers architectures and models for intelligent and green communication networks-enabled Internet of Things • Discusses designing Internet of Things devices that help in reducing the emissions of CO2 in the environment and energy consumption • Highlights green computing approach and green communication network designs and implementations for Internet of Things ecosystem • Includes studies on energy-aware systems, technologies, and green communication This book comprehensively discusses recent advances and applications in the area of green Internet of Things communication in a single volume. It will serve as an ideal reference text for senior undergraduate and graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology