Search results for: statistical machine translation

Authors: Adeniyi G. Adeogun, Bolaji F. Sule, Adebayo W. Salami, Michael O. Daramola

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Estimation of water yield and water balance in a river catchment is critical to the sustainable management of water resources at watershed level in any country. Therefore, in the present study, Soil and Water Assessment Tool (SWAT) interfaced with Geographical Information System (GIS) was applied as a tool to predict water balance and water yield of a catchment area in Nigeria. The catchment area, which was 12,992km2, is located upstream Jebba hydropower dam in North central part of Nigeria. In this study, data on the observed flow were collected and compared with simulated flow using SWAT. The correlation between the two data sets was evaluated using statistical measures, such as, Nasch-Sucliffe Efficiency (NSE) and coefficient of determination (R2). The model output shows a good agreement between the observed flow and simulated flow as indicated by NSE and R2, which were greater than 0.7 for both calibration and validation period. A total of 42,733 mm of water was predicted by the calibrated model as the water yield potential of the basin for a simulation period 1985 to 2010. This interesting performance obtained with SWAT model suggests that SWAT model could be a promising tool to predict water balance and water yield in sustainable management of water resources. In addition, SWAT could be applied to other water resources in other basins in Nigeria as a decision support tool for sustainable water management in Nigeria.

Keywords: GIS, modeling, sensitivity analysis, SWAT, water yield, watershed level

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Authors: Mohammad A. Khasawneh

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Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure. The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab. Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.

Keywords: friction, image analysis, polishing, statistical analysis, texture

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Authors: Gurukiran Veerapur, Nytik Birudavolu, Seetharam U. N., Chandravva Hebbi, R. Praneeth Reddy

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This work presents a robust approach for the recognition of characters in Telugu and Kannada, two South Indian scripts with structural similarities in characters. To recognize the characters exhaustive datasets are required, but there are only a few publicly available datasets. As a result, we decided to create a dataset for one language (source language),train the model with it, and then test it with the target language.Telugu is the target language in this work, whereas Kannada is the source language. The suggested method makes use of Canny edge features to increase character identification accuracy on pictures with noise and different lighting. A dataset of 45,150 images containing printed Kannada characters was created. The Nudi software was used to automatically generate printed Kannada characters with different writing styles and variations. Manual labelling was employed to ensure the accuracy of the character labels. The deep learning models like CNN (Convolutional Neural Network) and Visual Attention neural network (VAN) are used to experiment with the dataset. A Visual Attention neural network (VAN) architecture was adopted, incorporating additional channels for Canny edge features as the results obtained were good with this approach. The model's accuracy on the combined Telugu and Kannada test dataset was an outstanding 97.3%. Performance was better with Canny edge characteristics applied than with a model that solely used the original grayscale images. The accuracy of the model was found to be 80.11% for Telugu characters and 98.01% for Kannada words when it was tested with these languages. This model, which makes use of cutting-edge machine learning techniques, shows excellent accuracy when identifying and categorizing characters from these scripts.

Keywords: base characters, modifiers, guninthalu, aksharas, vattakshara, VAN

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Authors: Mahlet Nigussie Worku

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The main purpose of this study was to examine the effects of different leadership styles on employee engagement in Ethiopian Airlines head quarter located in Addis Ababa. Specific objectives of the study were stated to examine the effects of five leadership styles namely transformational, transactional, democratic, lassies fair and autocratic leadership styles on employees’ engagement. The study was conducted on 288 sample size and a simple random sampling technique was employed. The quantitative findings were presented and analyzed by table, ANOVA, bivariate correlation and regression model through SPSS software version 23. Out of 288 total distributed questionnaires 280 were returned and 8 of the returned were rejected due to missing data while the remaining 280 responses were used for data analysis. Data was analyzed using the Statistical Package for Social Sciences (SPSS). The study employed both descriptive and explanatory research design. Correlation and regression were used to analyze the relationship and its effect between leadership Style and employee’s engagement. The regression results showed that transformational, transactional and democratic leadership Styles have significant contribution for employee’s engagement. Similarly transformational, transactional land democratic leadership style had a positive and strong correlation with employee’s engagement. However lassies-fair and autocratic leadership style showed negative and insignificant effect on employee engagement. Finally, based on the findings, workable recommendations and implications for further studies were forwarded

Keywords: leadership, leadership style, employee engagement, autocratic leadership styles

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Authors: Adebola Ajayi, Francis B. Aiyeleye, Olakunke M. Makanjuola, Olalekan J. Adebowale

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Cocoyam, a generic term for both xanthoma and colocasia, is a traditional staple root crop in many developing countries in Africa, Asia and the Pacific. It is mostly cultivated as food crop which is very rich in vitamin B6, magnesium and also in dietary fiber. The cocoyam starch is easily digested and often used for baby food. Drying food is a method of food preservation that removes enough moisture from the food so bacteria, yeast and molds cannot grow. It is a one of the oldest methods of preserving food. The effect of drying methods on the proximate composition and functional properties of extracted cocoyam starch flour were studied. Freshly harvested cocoyam cultivars at matured level were washed with portable water, peeled, washed and grated. The starch in the grated cocoyam was extracted, dried using sun drying, oven and cabinet dryers. The extracted starch flour was milled into flour using Apex mill and packed and sealed in low-density polyethylene film (LDPE) 75 micron thickness with Nylon sealing machine QN5-3200HI and kept for three months under ambient temperature before analysis. The result showed that the moisture content, ash, crude fiber, fat, protein and carbohydrate ranged from 6.28% to 12.8% 2.32% to 3.2%, 0.89% to 2.24%%, 1.89% to 2.91%, 7.30% to 10.2% and 69% to 83% respectively. The functional properties of the cocoyam starch flour ranged from 2.65ml/g to 4.84ml/g water absorption capacity, 1.95ml/g to 3.12ml/g oil absorption capacity, 0.66ml/g to 7.82ml/g bulk density and 3.82% to 5.30ml/g swelling capacity. Significant difference (P≥0.5) was not obtained across the various drying methods used. The drying methods provide extension to the shelf-life of the extracted cocoyam starch flour.

Keywords: cocoyam, extraction, oven dryer, cabinet dryer

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Authors: Abhijit Trailokya, Kamlesh Patel

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Background: Hypertension is a common disease seen in clinical practice and is associated with high morbidity and mortality. Many patients require combination therapy for the management of hypertension. Objective: To evaluate co-morbidities, risk factors and management practices of hypertension in Indian population. Material and methods: A total of 1596 hypertensive adult patients received anti-hypertensive medications were studied in a cross-sectional, multi-centric, non-interventional, observational registry. Statistical analysis: Categories or nominal data was expressed as numbers with percentages. Continuous variables were analyzed by descriptive statistics using mean, SD, and range Chi square test was used for in between group comparison. Results: The study included 73.50% males and 26.50% females. Overweight (50.50%) and obesity (30.01%) was common in the hypertensive patients (n=903). A total of 54.76% patients had history of smoking. Alcohol use (33.08%), sedentary life style (32.96%) and history of tobacco chewing (17.92%) were the other lifestyle habits of hypertensive patients. Diabetes (36.03%) and dyslipidemia (39.79%) history was common in these patients. Family history of hypertension and diabetes was seen in 82.21% and 45.99% patients respectively. Most (89.16%) patients were treated with combination of antihypertensive agents. ARBs were the by far most commonly used agents (91.98%) followed by calcium channel blockers (68.23%) and diuretics (60.21%). ARB was the most (80.35%) preferred agent as monotherapy. ARB was also the most common agent as a component of dual therapy, four drug and five drug combinations. Conclusion: Most of the hypertensive patients need combination treatment with antihypertensive agents. ARBs are the most preferred agents as monotherapy for the management of hypertension. ARBs are also very commonly used as a component of combination therapy during hypertension management.

Keywords: antihypertensive, hypertension, management, ARB

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Authors: Bonnie R. Brammall, Rhonda M. Garad, Helena J. Teede, Cheryce L. Harrison

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Introduction: Reproductive aged women are at high-risk for accelerated weight gain and obesity development, with pregnancy recognised as a critical contributory life phase. Healthy lifestyle interventions during the preconception and antenatal period improve maternal and infant health outcomes. Yet, interventions from preconception through to postpartum and translation and implementation into real-world healthcare settings remain limited. OptimalMe is a randomised, hybrid implementation effectiveness study of evidence-based healthy lifestyle intervention. Here, we report engagement, acceptability of the intervention during preconception, and self-reported behaviour change outcomes as a result of the preconception phase of the intervention. Methods: Reproductive aged women who upgraded their private health insurance to include pregnancy and birth cover, signalling a pregnancy intention, were invited to participate. Women received access to an online portal with preconception health and lifestyle modules, goal-setting and behaviour change tools, monthly SMS messages, and two coaching sessions (randomised to video or phone) prior to pregnancy. Results: Overall n=527 expressed interest in participating. Of these, n=33 did not meet inclusion criteria, n=8 were not contactable for eligibility screening, and n=177 failed to engage after the screening, leaving n=309 who were enrolled in OptimalMe and randomised to intervention delivery method. Engagement with coaching sessions dropped by 25% for session two, with no difference between intervention groups. Women had a mean (SD) age of 31.7 (4.3) years and, at baseline, a self-reported mean BMI of 25.7 (6.1) kg/m², with 55.8% (n=172) of a healthy BMI. Behaviour was sub-optimal with infrequent self-weighing (38.1%), alcohol consumption prevalent (57.1%), sub-optimal pre-pregnancy supplementation (61.5%), and incomplete medical screening. Post-intervention 73.2% of women reported engagement with a GP for preconception care and improved lifestyle behaviour (85.5%), since starting OptimalMe. Direct pre-and-post comparison of individual participant data showed that of 322 points of potential change (up-to-date cervical screening, elimination of high-risk behaviours [alcohol, drugs, smoking], uptake of preconception supplements and improved weighing habits) 158 (49.1%) points of change were achieved. Health coaching sessions were found to improve accountability and confidence, yet further personalisation and support were desired. Engagement with video and phone sessions was comparable, having similar impacts on behaviour change, and both methods were well accepted and increased women's accountability. Conclusion: A low-intensity digital health and lifestyle program with embedded health coaching can improve the uptake of preconception care and lead to self-reported behaviour change. This is the first program of its kind to reach an otherwise healthy population of women planning a pregnancy. Women who were otherwise healthy showed divergence from preconception health and lifestyle objectives and benefited from the intervention. OptimalMe shows promising results for population-based behaviour change interventions that can improve preconception lifestyle habits and increase engagement with clinical health care for pregnancy preparation.

Keywords: preconception, pregnancy, preventative health, weight gain prevention, self-management, behaviour change, digital health, telehealth, intervention, women's health

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Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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Authors: Claudia Patricia Beltran Miranda, Mónica López Anaya, Mónica Navarro Meza, Maria Leonor Valderrama Chairez

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Background: Mexico occupies the second world-wide place of morbid obese people (10- 12 million). Factors that predispose the development of MO are genetic, environmental, physiological, psycho-social and behavioral (nourishing habits). Objective: Associate Gln223Arg polymorphism of gene LEPR, levels of leptina and nourishing habits with the presence of morbid obesity in adolescents of the south of Jalisco (México). Methods: In 41 adolescents (18 normal weight and 23 morbid obesity) of 12 to 19 years of age, both sexes that were measure size and weight with tanita scale and stadimeter to determine IMC. Morbid obesity was determined by tables of the WHO and was established with a standard deviation >3. The Gln223Arg polymorphism have been identify by PCR and leptina levels by ELISA. Nourishing habits were evaluate by the questionnaire the Adolescent Food Habits Checklist. The statistical analysis was performed to compare mean scores obtained from the questionnaire when we compare morbid obesity vs. normal weight adolescents with p=0.03 and a significance of 95%. Results: frequencies alellics and genics were not stadistics significatives p= 0,011 and p=0,279 respectly when were compared between normal weight adolescents and morbib obesity Leptin levels and nourishing habits were associated with morbid obesity. The polymorphism not shown significance with morbid obesity. Conclusions: Dietary habits and leptin levels in adolescents are important factor that predisposes the development of obesity in adolescents. The presence of the polymorphism are not associated with morbid obesity in these subjects.

Keywords: leptin, nourishing habits, morbid obesity, polymorphism

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Authors: Venuste Kayinamura, V. Iyamuremye, A. Ngirabakunzi

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Anti-retroviral therapy (ART) for HIV patient can cause a deficiency in glucose metabolism by promoting insulin resistance, glucose intolerance, and diabetes, diabetes mellitus keep increasing among HIV-infected patients worldwide but there is limited data on levels of blood glucose and its relationship with antiretroviral drugs (ARVs) and HIV-infection worldwide, particularly in Rwanda. A convenient sampling strategy was used in this study and it involved 323 HIV patients (n=323). Patients who are HIV positive under ARVs were involved in this study. The patient’s blood glucose was analyzed using an automated machine or glucometer (COBAS C 311). Data were analyzed using Microsoft Excel and SPSS V. 20.0 and presented in percentages. The highest diabetes mellitus prevalence was 93.33 % in people aged >40 years while the lowest diabetes mellitus prevalence was 6.67% in people aged between 21-and 40 years. The P-value was (0.021). Thus, there is a significant association between age and diabetes occurrence. The highest diabetes mellitus prevalence was 28.2% in patients under ART treatment for more than 10 years, 16.7% were <5years while 20% of patients were on ART treatment between 5-10 years. The P-value here is (0.03), thus the incidence of diabetes is associated with long-term ART use in HIV-infected patients. This study assessed the prevalence of diabetes among HIV-infected patients under ARVs attending the University Teaching Hospital of Butare (CHUB), it shows that the prevalence of diabetes is high in HIV-infected patients under ARTs. This study found no significant relationship between gender and diabetes mellitus growth. Therefore, regular assessment of diabetes mellitus especially among HIV-infected patients under ARVs is highly recommended to control other health issues caused by diabetes mellitus.

Keywords: anti-retroviral, diabetes mellitus, antiretroviral therapy, human immune deficiency virus

Procedia PDF Downloads 113

Authors: Rajesh Kumar G

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A challenging aspect of any clinical trial is to carefully plan the study design to meet the study objective in optimum way and to validate the assumptions made during protocol designing. And when it is a pediatric study, there is the added challenge of stringent guidelines and difficulty in recruiting the necessary subjects. Unlike adult trials, there is not much historical data available for pediatrics, which is required to validate assumptions for planning pediatric trials. Typically, pediatric studies are initiated as soon as approval is obtained for a drug to be marketed for adults, so with the adult study historical information and with the available pediatric pilot study data or simulated pediatric data, the pediatric study can be well planned. Generalizing the historical adult study for new pediatric study is a tedious task; however, it is possible by integrating various statistical techniques and utilizing the advantage of hybrid study design, which will help to achieve the study objective in a smoother way even with the presence of many constraints. This research paper will explain how well the hybrid study design can be planned along with integrated technique (SEV) to plan the pediatric study; In brief the SEV technique (Simulation, Estimation (using borrowed adult data and applying Bayesian methods)) incorporates the use of simulating the planned study data and getting the desired estimates to Validate the assumptions.This method of validation can be used to improve the accuracy of data analysis, ensuring that results are as valid and reliable as possible, which allow us to make informed decisions well ahead of study initiation. With professional precision, this technique based on the collected data allows to gain insight into best practices when using data from historical study and simulated data alike.

Keywords: adaptive design, simulation, borrowing data, bayesian model

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Authors: Dinamarie Fonzone

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Employer-sponsored health insurance (ESI) strategic decision-making processes rely on financial analysis to guide leadership in choosing plans that will produce optimal organizational spending outcomes. These financial decision-making methods have not abated ESI costs. Previously unrecognized external social determinants, the impact on ESI plan spending, and other organizational strategies are emerging and are important considerations for organizational decision-makers and change management practitioners. The purpose of thisstudy is to examine the relationship between the social determinants of health (SDoH), employer-sponsored health insurance (ESI) plans, andthe unintended consequence of health inequity. A quantitative research design using selectemployee records from an existing employer human capital management database will be analyzed. Statistical regressionmethods will be used to study the relationships between certainSDoH (employee income, neighborhood geographic living area, and health care access) and health plan utilization, cost, and chronic disease prevalence. The discussion will include an application of the social gradient of health theory to the study findings, organizational transformation through changes in ESI decision-making mental models, and the connection of ESI health inequity to organizational development and changediversity, equity, and inclusion strategies.

Keywords: employer-sponsored health insurance, social determinants of health, health inequity, mental models, organizational development, organizational change, social gradient of health theory

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Authors: Ma. Doreen E. Candelaria, Ma. Louise Margaret A. Ramos, Dr. Jaime Y. Hernandez, Jr

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Bamboo has been introduced as a possible alternative to some construction materials nowadays. Its potential use in the field of engineering, however, is still not widely practiced due to insufficient engineering knowledge on the material’s properties and characteristics. Although there are researches and studies proving its advantages, it is still not enough to say that bamboo can sustain and provide the strength and capacity required of common structures. In line with this, a more detailed analysis was made to observe the layered structure of the bamboo, particularly the species of Kawayan Tinik. It is the main intent of this research to provide the necessary experiments to determine the tensile strength of dried bamboo samples. The test includes tensile strength parallel to fibers with samples taken at internodes only. Throughout the experiment, methods suggested by the International Organization for Standardization (ISO) were followed. The specimens were tested using 3366 INSTRON Universal Testing Machine, with a rate of loading set to 0.6 mm/min. It was then observed from the results of these experiments that dried bamboo samples recorded high layered tensile strengths, as high as 600 MPa. Likewise, along the culm’s length and across its cross section, higher tensile strength were observed at the top part and at its outer layers. Overall, the top part recorded the highest tensile strength per layer, with its outer layers having tensile strength as high as 600 MPa. The recorded tensile strength of its middle and inner layers, on the other hand, were approximately 450 MPa and 180 MPa, respectively. From this variation in tensile strength across the cross section, it may be concluded that an increase in tensile strength may be observed towards the outer periphery of the bamboo. With these preliminary investigations on the layered tensile strength of bamboo, it is highly recommended to conduct experimental investigations on the layered compressive strength properties as well. It is also suggested to conduct investigations evaluating perpendicular layered tensile strength of the material.

Keywords: bamboo strength, layered strength tests, strength test, tensile test

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Authors: Thipsupar Pureprasert, Niwat Anuwongnukroh, Surachai Dechkunakorn, Surapich Loykulanant, Chaveewan Kongkaew, Wassana Wichai

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Objective: Orthodontic elastic bands made from natural rubber continue to be commonly used due to their favorable characteristics. However, there are concerns associated cytotoxicity due to harmful components released during conventional vulcanization (sulfur-based method). With the co-operation of The National Metal and Materials Technology Center (MTEC) and Faculty of Dentistry Mahidol University, a method was introduced to reduce toxic components by leaching the orthodontic elastic bands with NaOH solution. Objectives: To evaluate the mechanical properties of Thai and commercial orthodontic elastic brands (Ormco and W&H) leached with NaOH solution. Material and methods: Three elastic brands (N =30, size ¼ inch, 4.5 oz.) were tested for mechanical properties in terms of initial extension force, residual force, force loss, breaking strength and maximum displacement using a Universal Testing Machine. Results : Force loss significantly decreased in Thai-LEACH and W&H-LEACH, whereas the values increased in Ormco-LEACH (P < 0.05). The data exhibited a significantly decrease in breaking strength with Thai-LEACH and Ormco-LEACH, whereas all 3 brands revealed a significantly decrease in maximum displacement with the leaching process (P < 0.05). Conclusion: Leaching with NaOH solution is a new method, which can remove toxic components from orthodontic latex elastic bands. However, this process can affect their mechanical properties. Leached elastic bands from Thai had comparable properties with Ormco and have potential to be developed as a promising product.

Keywords: leaching, orthodontic elastics, natural rubber latex, orthodontic

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Authors: Odunjo Oluronke Omolola, Okanlawon Simon Ayorinde

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This study examines the relationship between house characteristics and socio-economic characteristics of developers in Ibadan, southwest, Nigeria. The research is borne out of the fact that social housing has not done much as a result of finance and housing poverty is on the increase in the country. Multistage random sampling was used in selecting 2,646 respondents in the area. The questionnaire forms the basic instrument for data collection and was administered to heads of households to collect information on socio-economic and demographic characteristics as well as characteristics of development. Both descriptive and inferential statistical analyses were employed in the presentation of the findings; MANOVA was used to analyse the relationship between house characteristics measured by wall materials (Y1-Yn) and socio-economic characteristics of developers measured by gender (X1), religion (X2), educational background (X3) and employment status (X4).The study found out that the bulk of the respondents (65.7%) were male, while 51.7% practiced Christianity. Also, 35.9% had HND/1st/Postgraduate degree, while 43.9% were self employed; Most households however, had membership size of 5 (26.9%). The significant wall material in the area was sandcrete block (71.2%) as opposed to mud (19.1%) and brick (0.6%). Multiple Analysis of Variance shows that there is a significant relationship between sandcrete block and each of gender (X1) and employment status (X3). The factor adduced to this is accessibility to cooperative societies which serve as the gravitational force of attraction for housing finance. The study suggests among others that, there should be re-invigoration of existing cooperative societies, while more should be established for the provision of housing finance.

Keywords: relationship, house development, developers, sandcrete block, cooperative societies

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: Mehdi Destani, Asghar Heydari

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Objective: The present study aimed to investigate the association between pathological personality dimensions and emotion dysregulation through the mediating role of Cyberchondria behaviors among users of virtual networks. Materials and methods: A descriptive–correlational research method was used in this study, and the statistical population consisted of all people active on social network sites in 2020. The sample size was 300 people who were selected through Convenience Sampling. Data collection was carried out in a survey method using online questionnaires, including the "Difficulties in Emotion Regulation Scale" (DERS), Personality Inventory for DSM-5 Brief Form (PID-5-BF), and Cyberchondria Severity Scale Brief Form (CSS-12). Data analysis was conducted using Pearson's Correlation Coefficient and Structural Equation Modeling (SEM). Findings: Findings suggested that pathological personality dimensions and Cyberchondria behaviors have a positive and significant association with emotion dysregulation (p<0.001). The presented model had a good fit with the data. The variable “pathological personality dimensions” with an overall effect (p<0.001, β=0.658), a direct effect (p<0.001, β=0.528), and an indirect mediating effect through Cyberchondria Behaviors (p<.001), β=0.130), accounted for emotion dysregulation among virtual network users. Conclusion: The research findings showed a necessity to pay attention to the pathological personality dimensions as a determining variable and Cyberchondria behaviors as a mediator in the vulnerability of users of social network sites to emotion dysregulation.

Keywords: cyberchondria, emotion dysregulation, pathological personality dimensions, social networks

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Wasfi Al Salamat, Shaker Al-Kharouf

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This study aims to examine the determinants of financial stability for 13 commercial banks listed on the Amman stock exchange (ASE) over the period (2007-2016) after controlling for the independent variables: return on equity (ROE), return on assets (ROA), earnings per share (EPS), growth in gross domestic product (GDP), inflation rate and debt ratio to measure the financial stability by three main variables: capital adequacy, non-performing loans and the number of returned checks. The balanced panel data statistical approach has been used for data analysis. Results are estimated by using multiple regression models. The empirical results suggested that there is statistically significant negative effect of inflation rate and debt ratio on the capital adequacy while there is statistically significant positive effect of growth in gross domestic product on capital adequacy. In contrast, there is statistically significant negative effect of return on equity and growth in gross domestic product on the non-performing loans while there is statistically significant positive effect of inflation rate on non-performing loans. Finally, there is statistically significant negative effect of growth in gross domestic product on the number of returned checks while there is statistically significant positive effect of inflation rate on the number of returned checks.

Keywords: capital adequacy, financial stability, non-performing loans, number of returned checks, ASE

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: Sahar Oudeh, Abbas Javaheri Vayeghan, Mahmood Ahmadi-Hamedani

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This study aimed to investigate the effect of diabetic duration on platelet and platelet indices in streptozotocin-induced diabetic male and female rats. Thirty-two healthy adult Wistar rats (16 females and 16 males) were randomly divided into 4 groups of eight, including 1) control group (4 females and 4 males who did not undergo any treatment until the end of 28 days), 2) 7-day diabetic group (4 females and 4 males who were diabetic for 7 days and were euthanized after 7 days), 3) 14-day diabetic group (4 females and 4 males who were diabetic for 14 days and were euthanized after 14 days), and 28-day diabetic group (4 females and 4 males who were diabetic for 28 days and were euthanized after 28 days). Diabetes was induced by intraperitoneal injection of streptozotocin (65 mg/kg). After induction of diabetes in the groups, blood samples were taken from their hearts after anesthesia, and platelet counts (PLT) and platelet indices were measured by an automatic blood cell counter (Nihon Kohden, Celltac Alpha VET MEK-6550, Japan). Statistical differences among groups were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple tests. The results of this study showed that PLT and mean platelet volume (MPV) significantly increased in 7 and 14-day diabetic groups compared to the control group, whereas plateletcrit (PCT) and platelet distribution rate (PDW) significantly increased in 14 and 28-day diabetic groups, respectively. Significant differences were observed between female and male rats in PCT and PLT in the 14-day diabetic group and PDW in the 28-day diabetic group. According to the results of this study, measurement and analysis of platelet indices can be used as a method for the early diagnosis of diabetes and its complications.

Keywords: diabetic duration, streptozotocin, female and male rats, platelet indices

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

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Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: M. J. Pourvaghar, M. E. Bahram, M. Sayyah, Sh. Khoshemehry

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Adiponectin is a cytokine secreted by the adipose tissue that functions as an anti-inflammatory, antiathrogenic and anti-diabetic substance. Its density is inversely correlated with body mass index. The purpose of this research was to examine the effect of 12 weeks of high intensity interval training (HIIT) with the level of serum adiponectin and some selected adiposity markers in overweight and fat college students. This was a clinical research in which 24 students with BMI between 25 kg/m² to 30 kg/m². The sample was purposefully selected and then randomly assigned into two groups of experimental (age =22.7±1.5 yr.; weight = 85.8±3.18 kg and height =178.7±3.29 cm) and control (age =23.1±1.1 yr.; weight = 79.1±2.4 kg and height =181.3±4.6 cm), respectively. The experimental group participated in an aerobic exercise program for 12 weeks, three sessions per weeks at a high intensity between 85% to 95% of maximum heart rate (considering the over load principle). Prior and after the termination of exercise protocol, the level of serum adiponectin, BMI, waist to hip ratio, and body fat percentages were calculated. The data were analyzed by using SPSS: PC 16.0 and statistical procedure such as ANCOVA, was used. The results indicated that 12 weeks of intensive interval training led to the increase of serum adiponectin level and decrease of body weight, body fat percent, body mass index and waist to hip ratio (P < 0.05). Based on the results of this research, it may be concluded that participation in intensive interval training for 12 weeks is a non-invasive treatment to increase the adiponectin level while decreasing some of the anthropometric indices associated with obesity or being overweight.

Keywords: adiponectin, cardiovascular, interval, overweight, training

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Authors: Mohsen Yaghmor, Sima Radmanesh

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Rapid environmental changes have been threatening the life of many organizations. Enabling and productivity of human resource should be considered as the most important issue in order to increase performance and ensure survival of the organizations. In this research, the effectiveness of management factory in productivity and inability of human resource have been identified and reviewed at glance. Afterwards, answers were sought to questions "What are the factors effecting productivity and enabling of human resource?" and "What are the priority order based on effective management of human resource in Fars Poultry Complex?". A specified questionnaire has been designed regarding the priorities and effectiveness of the identified factors. Six factors were specified consisting of: individual characteristics, teaching, motivation, partnership management, authority or power submission and job development that have most effect on organization. Then a questionnaire was specified for priority and effect measurement of specified factors that were reached after collecting information and using statistical tests of Keronchbakh alpha coefficient r = 0.792, so that we can say the questionnaire has sufficient reliability. After information analysis of specified six factors by Friedman test their effects were categorized. Measurement on organization respectively consists of individual characteristics, job development or enrichment, authority submission, partnership management, teaching and motivation. Lastly, approaches has been introduced to increase productivity of manpower.

Keywords: productivity, empowerment, enrichment, authority submission, partnership management, teaching, motivation

Procedia PDF Downloads 265

Authors: Christian H. Girsang, M. Razi B. Mansoor, Noorizal N. Huang

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An offshore platform was installed in 1977 at about 260km offshore West Malaysia at the water depth of 73.6m. Twelve (12) piles were installed with four (4) are skirt piles. The piles have 1.219m outside diameter and wall thickness of 31mm and were driven to 109m below seabed. Deterministic analyses of the pile capacity under axial loading were conducted using the current API (American Petroleum Institute) method and the four (4) CPT-based methods: the ICP (Imperial College Pile)-method, the NGI (Norwegian Geotechnical Institute)-Method, the UWA (University of Western Australia)-method and the Fugro-method. A statistical analysis of the model uncertainty associated with each pile capacity method was performed. There were two (2) piles analysed: Pile 1 and piles other than Pile 1, where Pile 1 is the pile that was most affected by shallow gas problems. Using the mean estimate of soil properties, the five (5) methods used for deterministic estimation of axial pile capacity in compression predict an axial capacity from 28 to 42MN for Pile 1 and 32 to 49MN for piles other than Pile 1. These values refer to the static capacity shortly after pile installation. They do not include the effects of cyclic loading during the design storm or time after installation on the axial pile capacity. On average, the axial pile capacity is expected to have increased by about 40% because of ageing since the installation of the platform in 1977. On the other hand, the cyclic loading effects during the design storm may reduce the axial capacity of the piles by around 25%. The study concluded that all piles have sufficient safety factor when the pile aging and cyclic loading effect are considered, as all safety factors are above 2.0 for maximum operating and storm loads.

Keywords: axial capacity, cyclic loading, pile ageing, shallow gas

Procedia PDF Downloads 345

Authors: Luksanaporn Krungkraipetch

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One hundred cataract patients with phacoemulsification were enrolled in the study to compare of visual acuity outcome and complication after phacoemulsification between diabetic and non-diabetic patients at Burapha University Hospital, Chonburi, Thailand. Fifty patients were diabetic (type II) group and 50 patients were non-diabetic group. All cases were operated by one doctor with the same pre-operative care, operation (phacoemulsification), and post-operative care. Visual acuity and complication after surgery were assessed after the operation for two years. There were no significant differences in demographic data between the two groups. The visual outcome values ≥ 2 lines and ≥ 20/40 had no significant differences between two groups after two years of surgery. The complication rate in diabetic group had cystoid macular edema 16%, rupture posterior capsule 8%, posterior capsule opacity 2%, uveitis 2 %, and 2% endophthalmitis. The non-diabetic group had cystoid macular edema 12%, rupture posterior capsule 8%, uveitis 2%, posterior capsule opacity 2%, and 2% wound leak. Comparison of visual acuity outcome and complication after phacoemulsification between diabetic and non-diabetic patients had no statistical significant differences between these two groups. It was found that cystoid macular edema was the most common complication in both groups and 10% of retinopathy progression was seen.

Keywords: cataract, visual acuity, cataract extraction, phacoemulsification, diabetic retinopathy

Procedia PDF Downloads 349

Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

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Semi autogenous mills are designed for grinding or primary crushed ore, and are the most widely used in concentrators globally. Any defect occurrence in semi autogenous mills can stop the production line. A Gearbox is a significant part of a rotating machine or a mill, so, the gearbox monitoring is a necessary process to prevent the unwanted defects. When a defect happens in a gearbox bearing, this defect can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. Vibration analysis is one of the most effective and common ways to detect the bearing defects in the mills. Vibration signal in a mill can be made by different parts of the mill including electromotor, pinion girth gear, different rolling bearings, and tire. When a vibration signal, made by the aforementioned parts, is added to the gearbox vibration spectrum, an accurate and on time defect detection in the gearbox will be difficult. In this paper, a new method is proposed to detect the gearbox bearing defects in the semi autogenous mill on time and accurately, using the vibration signal analysis method. In this method, if the vibration values are increased in the vibration curve, the probability of defect occurrence is investigated by comparing the equipment vibration values and the standard ones. Then, all vibration frequencies are extracted from the vibration signal and the equipment defect is detected using the vibration spectrum curve. This method is implemented on the semi autogenous mills in the Golgohar mining and industrial company in Iran. The results show that the proposed method can detect the bearing looseness on time and accurately. After defect detection, the bearing is opened before the equipment failure and the predictive maintenance actions are implemented on it.

Keywords: condition monitoring, gearbox defects, predictive maintenance, vibration analysis

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Authors: Ahsan Ullah

Abstract:

The aim of this study is to measure the relationship between sedentary behaviour and metabolic rate among adult professionals. An intervention (e-mobile) approach was used for gathered the information from the participants. A total of 40 participants (men = 30, and women = 10) with an average age of (36.53 years ± 8.85) were randomly assigned to an intervention group (n= 20) and control group (n= 20). All the participants completed the Sedentary Behaviour Questionnaire (SBQ) and The International Physical Activity Questionnaire (IPAQ) at baseline and at the end of eight weeks. The participants in the intervention group were given physical activity guidelines targeted at increasing physical activity levels during daily activities. On the other side, the control group was advised to continue with their routine daily physical activity. Statistical analyses, including descriptive statistics and inferential analysis like mean, SD, T-tests, and ANOVA, were used to analyze the data and determine relationships between variables. After analyzing the data, the results showed that significant difference in pre and post metabolic rate scores (1488.31 ± 179.13 to 1468.44 ± 128.19) (f = 10.83, p < 0.000) were noted in the experimental group after eight week. The experimental group increased their walking (863.78 METs per week to 1625.55 METs per week), moderate activity (295 METs per week to 743 METs per week) and vigorous activity (362 METs per week to 1366 METs per week) physical activity (all p<0.001). There were no significant differences observed in any outcome measured before and after eight weeks in the control group. These findings suggest that engaging in physical activity can effectively improve metabolic rate and reduce sedentary behavior among physically active adults.

Keywords: sedentary behavior, metabolic rate, adult’s professionals, physical activity

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