Search results for: health belief model.

Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi

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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.

Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance

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Authors: Livhuwani Muthelo

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The health and safety of the miners in the South African mining industry are guided by the regulations and standards which are anticipated to promote a healthy work environment and fatalities. It is of utmost importance for the miners to comply with these regulations/standards to protect themselves from potential occupational health and safety risks, accidents, and fatalities. The purpose of this study was to develop and validate strategies to enhance compliance with the Health and safety standards within the mining industries of Limpopo province in South Africa. A mixed-method exploratory sequential research design was adopted. The population consisted of 5350 miners. Purposive sampling was used to select the participants in the qualitative strand and stratified random sampling in the quantitative strand. Semi-structured interviews were conducted among the occupational health nurse practitioners and the health and safety team. Thematic analysis was used to generate an understanding of the interviews. In the quantitative strand, a survey was conducted using a self-administered questionnaire. Data were analysed using SPSS version 26.0. A descriptive statistical test was used in the analysis of data including frequencies, means, and standard deviation. Cronbach's alpha test was used to measure internal consistency. The integrated results revealed that there are diverse experiences related to health and safety standards compliance among the mineworkers. The main findings were challenges related to leadership compliance and also related to the cost of maintaining safety, Miner's behavior-related challenges; the impact of non-compliance on the overall health of the miners was also described, the conflict between production and safety. Health and safety compliance is not just mere compliance with regulations and standards but a culture that warrants the miners and organization to take responsibility for their behavior and actions towards health and safety. Thus taking responsibility for your well-being and other miners.

Keywords: perceptions, compliance, health and safety, legislation, standards, miners

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Kannapha Amaruchkul

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We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

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Authors: C. Sridawruang

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Young people today has sexual activities differing from those of earlier generations, in that teenagers are likely to have multiple partners, and are frequently in short-term relationships or with partners that are not well known to them. The proportion of teenage mothers in Thailand has increased. Young people were not specifically addressed during the overall very successful HIV-prevention campaigns. Because of this missed opportunity, they are still unaware of the risk of unsafe sexual behavior. Aims: To describe the reproductive health care services in perspectives of rural Thai teenagers Methods: This survey was one part of a mixed method approach taken using survey and focus groups with 439 teenagers aged 12-18 years in 5 villages, Udon Thani, Thailand. The standard questionnaire survey had been used for collecting data. The numeric data was checked and analyzed by using descriptive statistics. Results: Most teenager respondents stated that they do not know where sexual reproductive health services provided for them. Most teenagers felt difficult to access and talk with health staff about sexual related issues. They stated that discussing, or consulting with health providers might not be safe. Teenagers might lose opportunities to access and get advice from health care services. The mean knowledge score of contraception and condom reproductive was 6.34 from a total score 11. Most teenagers especially girls expressed a need for counseling services and reported a need for telephone services. Conclusions: The need of appropriate information focusing on sexual relationships and contraception should be designed to help young people make wise decisions and there should be set health care services for Thai teenagers to make sure that teenagers could access easily. Health care providers need to be trained to improve their knowledge, attitudes and skills in reproductive health care practices for Thai teenagers.

Keywords: youth friendly health services, rural, Thai, teenagers

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Authors: Moustafa Osman Mohammed

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This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.

Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change

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Authors: Sabita Karki

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Occupational health hazards are recognized as global problems for health care workers, it is quiet high in developing countries. It is increasing day by day due to change in science and technology. This study aimed to assess the knowledge and practice of occupational health hazards among the nurses. A descriptive, cross sectional study was carried out among 339 nurses working in three different teaching hospitals of the Kathmandu from February 28, 2016 to March 28, 2016. A self-administered questionnaire was used to collect the data. The study findings revealed that out of 339 samples of all 80.5% were below 30 years; 51.6% were married; 57.5% were graduates and above; 91.4% respondents were working as staff nurse; 56.9% were working in general ward; 56.9% have work experience of 1 to 5 years; 79.1% respondents were immunized against HBV; only 8.6% have received training/ in-service education related to OHH and 35.4% respondents have experienced health hazards. The mean knowledge score was 26.7 (SD=7.3). The level of knowledge of occupational health hazards among the nurses was 68.1% (adequate knowledge). The knowledge was statistically significant with education OR = 0.288, CI: 0.17-0.46 and p value 0.00 and immunization against HBV OR= 1.762, CI: 0.97-0.17 and p value 0.05. The mean practice score was 7.6 (SD= 3.1). The level of practice on prevention of OHH was 74.6% (poor practice). The practice was statistically significant with age having OR=0.47, CI: 0.26-0.83 and p value 0.01; designation OR= 0.32, CI: 0.14-0.70 and p value 0.004; working department OR=0.61, CI: 0.36-1.02 and p value 0.05; work experience OR=0.562, CI: 0.33-0.94 and p value 0.02; previous in-service education/ training OR=2.25; CI: 1.02-4.92 and p value 0.04. There was no association between knowledge and practice on prevention of occupational health hazards which is not statistically significant. Overall, nurses working in various teaching hospitals of Kathmandu had adequate knowledge and poor practice of occupational health hazards. Training and in-service education and availability of adequate personal protective equipments for nurses are needed to encourage them adhere to practice.

Keywords: occupational health hazard, nurses, knowledge, preventive practice

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Jadon Matthiasa, Cindy Donga, Ali Al Jibouria, Hsin Kuo

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The environmental impact of emissions from the Covanta Waste-to-Energy facility in Burnaby, BC, was comprehensively evaluated, focusing on the dispersion of air pollutants and the subsequent assessment of heavy metal contamination in surrounding soils. A Gaussian Plume Model, implemented in MATLAB, was utilized to simulate the dispersion of key pollutants to understand their atmospheric behaviour and potential deposition patterns. The MATLAB code developed for this study enhanced the accuracy of pollutant concentration predictions and provided capabilities for visualizing pollutant dispersion in 3D plots. Furthermore, the code could predict the maximum concentration of pollutants at ground level, eliminating the need to use the Ranchoux model for predictions. Complementing the modelling approach, empirical soil sampling and analysis were conducted to evaluate heavy metal concentrations in the vicinity of the facility. This integrated methodology underscored the importance of computational modelling in air pollution assessment and highlighted the necessity of soil analysis to obtain a holistic understanding of environmental impacts. The findings emphasized the effectiveness of current emissions controls while advocating for ongoing monitoring to safeguard public health and environmental integrity.

Keywords: air emissions, Gaussian Plume Model, MATLAB, soil contamination, air pollution monitoring, waste-to-energy, pollutant dispersion visualization, heavy metal analysis, environmental impact assessment, emission control effectiveness

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Authors: Ahasanul Haque, Noor Hazilah Abd Manaf, Zohurul Anis, Tarekol Islam

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Sustainable community health (SCH) is an example of a new healthcare concept formed from applying the Maqasid al-Shariah principle to hospital management and delivery services. Because the idea is novel, it needs comprehensive and ongoing investigation to be improved. However, there is a lack of research on the necessity of developing sustainable community health (SCH), particularly its organizational structure. Furthermore, there is a misconception about the order of components in Maqasid al-Shariah, particularly in a hospital setting. Furthermore, the use of medicines and treatment by conventional recommendations to carry out the treatment by the Maqasid al Shariah. As such, this study focuses on the essential prerequisite for establishing a sustainable community health system based on Maqasid al-Shariah. This study discusses the use of Maqasid al-Shariah in administration and treatment. In this qualitative research approach, a literature search and interviews with specialists are conducted. The gathered data is examined using content analysis, emphasizing inductive and deductive reasoning. The research reveals that the Shariah Advisory Council and Shariah Critical Point are necessary for sustainable community health. In conclusion, by discussing the causes for each instance, this research adds to the creation of methods for determining the level of Maasid al-Shariah in-hospital care.

Keywords: empowering, sustainability, community health, maqasid al shariah, hospital and malaysia

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Authors: Luo Lan, Huang Jingjing, Li Huafang

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Hypoactive sexual desire disorder (HSDD) was common in China, and Chinese women's sexual health-seeking behaviors were found to be mainly impeded by their psychological barriers. However, underlying mechanisms for such unhealthy sexual health attitudes and symptoms of HSDD were unknown. Many studies suggested the correlation between women's psychological barriers, HSDD and attachment style but had limitations, so this study further explored their relationship. Chinese women of childbearing age were recruited from May 2020 to December 2022 in Shanghai, China. The Revised Adult Attachment Scale (RAAS), the Female Sexual Function Index (FSFI), the Female Sexual Distress Scale-Desire/Arousal/Orgasm (FSDS-DAO), a sexual health attitude questionnaire, and a psychiatric interview were administered. The analytic sample contained 279 women, of which 107 women were HSDD patients. Women with a fearful attachment style were found to be more likely to be unwilling to communicate sexual health (aOR 2.55, 95%CI 1.05-6.28) and feel ashamed of sexual health-related disorders (aOR 2.66, 95%CI 1.14-6.13). They are also linked with a higher risk of HSDD (aOR 3.25, 95%CI 1.35-8.12). Therefore, fearful attachment style should be given enough attention in the whole process of the diagnosis and treatment of HSDD and should be one of the focuses that guide sexual education.

Keywords: attachment style, hypoactive sexual desire disorder, attitude to health, sexual desire, sexual distress

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Jatuphum Ketchatturat

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Value-added assessment has been used for developing the model of monitoring and evaluation of student's learning achievement. The steps of model development consist of 1) study and analyisis of the school and the district report system of student achievement and progress, 2) collecting the data of student achievement to develop the value added indicator, 3) developing the system of value-added assessment by participatory action research approach, 4) putting the system of value-added assessment into the educational district of secondary school, 5) determining the quality of the developed system of value-added assessment. The components of the developed model consist of 1) the database of value-added assessment of student's learning achievement, 2) the process of monitoring and evaluation the student's learning achievement, and 3) the reporting system of value-added assessment of student's learning achievement.

Keywords: learning achievement, monitoring and evaluation, value-added assessment

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Aline Giardin

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Introduction: This review addresses the relationship between physical education and mental health and its main objective is to discuss the meanings that circulate in Psychiatric Hospitalization Units and Psychosocial Care Centers (CAPS) about the presence of physical education teachers and the practices developed by Them within these services. Material and methods: It is based on the theoretical contribution of the Psychiatric Reform and is methodologically inspired by the Bibliographic Review. Objectives: The objective of this review was to identify the main scientific evidence on the effects of physical activity on the main psychological aspects associated with mental health during the hospitalization process. Results: It was observed that physical activity has beneficial effects in the psychological, social and cognitive aspects, being thus a fundamental aspect of the lifestyle in promoting a healthy and successful treatment. In studies evaluating the effects of physical activity on mental health, the most frequently evaluated outcomes include anxiety, depression, and health-related quality of life (eg, self-esteem and self-efficacy). Evidence from epistemological studies indicates that the level of physical activity is positively associated with good mental health, when mental health is defined as good mood, general well-being and decreased symptoms. Conclusion: It is necessary to intervene and a greater interest of the professionals of physical education in the treatment with the people with mental disorders so that the negative symptoms are modified, through the aid of the physical activity, by better quality of life, physical condition, nutritional state and A healthy emotional appearance.

Keywords: health mental, physical activity, benefits, treatment

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: E. Benga, T. Tengen, A. Alugongo

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Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.

Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant

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Authors: Duplan Yves Jamont Junior

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The Diamond-Mortensen-Pissarides model widely used in labor economics is tailored to fishery. By this way, a fishing function is defined to depict the fishing technology, and Bellman equations are established to describe the behaviors of fishermen and conservationists. On this basis, a negotiation takes place as a Nash-bargaining over the upper limit of the fishing pressure between both political representative groups of fishermen and conservationists. The existence and uniqueness conditions of the Nash-bargained fishing pressure are established. Given the biomass evolution equation, the dynamics of the model variables (fishing pressure, biomass, fish need) is studied.

Keywords: conservation, fishery, fishing, Nash bargaining

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Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi

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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.

Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model

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Authors: Farokh Alipour, Ali Falavand, Neda Beit Saeid

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The calculation of the effect of accidental releases of flammable materials such as LNG requires the use of a suitable consequence model. This study is due to providing a planning advice for developments in the vicinity of LNG sites and other sites handling flammable materials. In this paper, an applicable algorithm that is able to model pool fires on water is presented and applied to estimate pool fire damage zone. This procedure can be used to model pool fires on land and could be helpful in consequence modeling and domino effect zone measurements of flammable materials which is needed in site selection and plant layout.

Keywords: LNG, pool fire, spill, radiation

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Authors: Fredrick Etyang

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This paper presents a Rapid Industrialization Model (RIM) designed to support existing industrialization policies, strategies and industrial development plans at National, Regional and Constituent level in Africa. The model will reinforce efforts to attainment of inclusive and sustainable industrialization of Africa by state and non-state actors. The overall objective of this model is to serve as a framework for rapid industrialization in developing economies and the specific objectives range from supporting rapid industrialization development to promoting a structural change in the economy, a balanced regional industrial growth, achievement of local, regional and international competitiveness in areas of clear comparative advantage in industrial exports and ultimately, the RIM will serve as a step-by-step guideline for the industrialization of African Economies. This model is a product of a scientific research process underpinned by desk research through the review of African countries development plans, strategies, datasets, industrialization efforts and consultation with key informants. The rigorous research process unearthed multi-directional and renewed efforts towards industrialization of Africa premised on collective commitment of individual states, regional economic communities and the African union commission among other strategic stakeholders. It was further, established that the inputs into industrialization of Africa outshine the levels of industrial development on the continent. The RIM comes in handy to serve as step-by-step framework for African countries to follow in their industrial development efforts of transforming inputs into tangible outputs and outcomes in the short, intermediate and long-run. This model postulates three stages of industrialization and three phases toward rapid industrialization of African economies, the model is simple to understand, easily implementable and contextualizable with high return on investment for each unit invested into industrialization supported by the model. Therefore, effective implementation of the model will result into inclusive and sustainable rapid industrialization of Africa.

Keywords: economic development, industrialization, economic efficiency, exports and imports

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Authors: Samindi Samarakoon, Ørjan Sletbakk Vie, Remi Kleiven Fjelldal

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White concrete facade elements are widely used in construction industry. It is challenging to achieve the desired workability in casting of white concrete elements. Particle Matrix model was used for proportioning the self-compacting white concrete (SCWC) to control segregation and bleeding and to improve workability. The paper presents how to reach the target slump flow while controlling bleeding and segregation in SCWC. The amount of aggregates, binders and mixing water, as well as type and dosage of superplasticizer (SP) to be used are the major factors influencing the properties of SCWC. Slump flow and compressive strength tests were carried out to examine the performance of SCWC, and the results indicate that the particle matrix model could produce successfully SCWC controlling segregation and bleeding.

Keywords: white concrete, particle matrix model, mix design, construction industry

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Authors: M. Khalid, W. Rashmi, L. L. Kwan

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This work provides an overview on the experimental and numerical simulations of various nanofluids and their flow and heat transfer behavior. It was further extended to study the effect of nanoparticle concentration, fluid flow rates and thermo-physical properties on the heat transfer enhancement of Al2O3/water nanofluid in a turbulent flow circular conduit using ANSYS FLUENT™ 14.0. Single-phase approximation (homogeneous model) and two-phase (mixture and Eulerian) models were used to simulate the nanofluid flow behavior in the 3-D horizontal pipe. The numerical results were further validated with experimental correlations reported in the literature. It was found that heat transfer of nanofluids increases with increasing particle volume concentration and Reynolds number, respectively. Results showed good agreement (~9% deviation) with the experimental correlations, especially for a single-phase model with constant properties. Among two-phase models, mixture model (~14% deviation) showed better prediction compared to Eulerian-dispersed model (~18% deviation) when temperature independent properties were used. Non-drag forces were also employed in the Eulerian two-phase model. However, the two-phase mixture model with temperature dependent nanofluid properties gave slightly closer agreement (~12% deviation).

Keywords: nanofluid, CFD, heat transfer, forced convection, circular conduit

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Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

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Authors: Ghassen Kharroubi, Ines Cherif, Leila Bouabid, Adel Gharbi, Aicha Boukthir, Margaret McCarron, Nissaf Ben Alaya, Afif Ben Salah, Jihene Bettaieb

Abstract:

Influenza vaccination (IV) is recommended for elderly persons, especially those with underlying conditions. In countries where IV rates in the elderly remain unsatisfactory, exploring attitudes of older persons toward the flu vaccine could be useful to identify barriers and facilitators to IV. The aim of this study was to determine the reasons for IV acceptance or decline in the Tunisian elderly. A national cross-sectional study was conducted in 2019, among persons aged 60 years and over with chronic disease. Data were collected using a standard administered questionnaire. Of the 1191 older persons included, 19.4% received the influenza vaccine in the 2018-2019 flu season. The two main reasons that may lead to refusal of vaccination were concerns that the vaccine could cause side effects (71.5%) and a belief that the vaccine was ineffective (33.9%). The main reason that may lead to accepting vaccination was a doctor’s recommendation (41.1%). Doctors were by far the most trusted source for information regarding influenza vaccine (91.5%) followed by pharmacists (17.6%). Our results highlighted the important role that doctors could play in promoting IV among the Tunisian elderly. Physicians should correct misconceptions about adverse events and the efficiency of the vaccine. In fact, influenza vaccines are generally effective and safe among older persons.

Keywords: attitudes, influenza vaccination, older persons, Tunisia

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Authors: Katalin Bodor, Zsolt Bodor, Robert Szep

Abstract:

The particulate matter (PM) smaller than 2.5 μm are less studied due to the limited availability of PM₂.₅, and less information is available on the health effects attributable to PM₁₀ in Central-Eastern Europe. The objective of the current study was to assess the human health risk and characterize the spatial and temporal variation of PM₂.₅ and PM₁₀ in eight Romanian regions between the 2009-2018 and. The PM concentrations showed high variability over time and spatial distribution. The highest concentration was detected in the Bucharest region in the winter period, and the lowest was detected in West. The relative risk caused by the PM₁₀ for all-cause mortality varied between 1.017 (B) and 1.025 (W), with an average 1.020. The results demonstrate a positive relative risk of cardiopulmonary and lung cancer disease due to exposure to PM₂.₅ on the national average 1.26 ( ± 0.023) and 1.42 ( ± 0.037), respectively.

Keywords: PM₂.₅, PM₁₀, relative risk, health effect

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Authors: Fatemeh Abdollahi, Mehran Zarghami, Jamshid Yazdani Jarati, Mun-Sunn Lye

Abstract:

Fathers may be at risk of depression during the postpartum period. Some studies have been reported maternal depression is the key predictor of paternal postpartum depression (PPD). This study aimed to explore this association. Using a cross-sectional study design, 591 couples referring to primary health centers at 2-8 weeks postpartum (during 2017) were recruited. Couples screened for depression using Edinburgh Postnatal Depression Scale (EPDS). Data on socio-demographic characteristics and psychosocial factors was also gathered. Paternal PPD was analyzed in relation to maternal PPD and other related factors using multiple regressions. The prevalence of Paternal and maternal postpartum depression was 15.7% (93) and 31.8% (188), respectively. The regression model showed that there was increased risk of PPD in fathers whose wives experienced PPD [OR=1.15, (95%CI: 1.04-1.27)], who had a lower state of general health [OR=1.21, (95%CI: 1.11-1.33)], who experienced increased number of life events [OR=1.42, (95%CI: 1.01-1.2.00)], and who were at older age [OR=1.20, (95%CI: 1.05- 1.36)]. Also, there was a decreased risk of depression in fathers with more children compared with those with fewer children [OR=0.20, (95%CI: 0.07-0.53)]. Maternal PPD and psychosocial risk factors were the strong predictors of parental PPD. Being grown up in a family with two depressed parents are an important issue for children and needs futher research and attention.

Keywords: Father, Mother, Postpartum depression, Risk factors

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Authors: Noora Al-Shanfari, M. Mazharul Islam

Abstract:

The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

Procedia PDF Downloads 104