Search results for: working time model

Authors: Gülcan Taşkıran, Ülkü Tatar Baykal

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Aim: To identify nurses’ perceived competencies for disaster preparedness. Background: Recently, the number of disasters has increased worldwide. Since disasters often strike without warning, healthcare providers, especially nurses must be prepared with appropriate competencies for disaster procedures. Nurses’ perceptions of their own competencies for disaster preparedness need to be evaluated to aid in the creation of effective national plans and educational programs. Design: This study was conducted with a descriptive and cross-sectional design. Methods: Nurses’ perceptions were assessed using the 13-item Demographic Profile Questionnaire that is based on previous literature and the 45-item Nurses’ Perception of Core Competencies for Disaster Preparedness Scale (NPCDPS). Data were collected from June to September 2014 from 406 (79.9% return rate) Turkish nurses working in the western region of Turkey. Results: At the end of the study, it was found that out of the nurses whose mean age was 31.27 ± 5.86 and mean of working time was 8.07 ± 6.60 by the time vast majority of the nurses were women (85.7%), married (59.4%), bachelor’s degree holder (88.2%) and service nurses (56.2%). The most potential disaster that nurses think is an earthquake (70.9%) by the time majority of nurses consider having a role as a nurse at every stage of disasters. The mean total point score of nurses’ perception of disaster preparedness was 4.62. The mean total point score of the nurses from the Nurses’ Perception of Core Competencies for Disaster Preparedness Scale was 133.96. When the subscales’ mean scores are examined, the highest average of the mean score is for Technical Skills (44.52), and the lowest is for Critical Thinking Skills (10.47). When the subscales of Nurses’ Perception of Core Competencies for Disaster Preparedness Scale compared with sex, marital status and education level out of independent variable of nurses there is no significant difference (p > 0.05); compared with age group, working years, duty and being with a disaster out of independent variable of nurses there is a significant difference (p ≤ 0.05). Conclusion: Nurses generally perceive themselves as sufficient at a ‘medium level’ in terms of meeting the core competencies that are required for disaster preparedness. Nurses are not adequately prepared for disasters, but they are aware of the need for such preparation and disaster education. Disaster management training should be given to all nurses in their basic education.

Keywords: disaster competencies, disaster management, disaster nursing, disaster preparedness, nursing, nursing administration, Turkish nurses

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Deepak Raj Bhat, Ryuichi Yatabe

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In this study, a residual-state creep failure model was developed based on the residual-state creep test results of clayey soils. To develop the proposed model, the regression analyses were done by using the R. The model results of the failure time (tf) and critical displacement (δc) were compared with experimental results and found in close agreements to each others. It is expected that the proposed regression model for residual-state creep failure will be more useful for the prediction of displacement of different clayey soils in the future.

Keywords: regression model, residual-state creep failure, displacement prediction, clayey soils

Procedia PDF Downloads 377

Authors: Paula Verdugo-Hernandez, Patricio Cumsille

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We analyze a first-class on the convergence of real number sequences, named hereafter sequences, to foster exploration and discovery of concepts through graphical representations before engaging students in proving. The main goal was to differentiate between sequences and continuous functions-of-a-real-variable and better understand concepts at an initial stage. We applied the analytic frame of mathematical working spaces, which we expect to contribute to extending to sequences since, as far as we know, it has only developed for other objects, and which is relevant to analyze how mathematical work is built systematically by connecting the epistemological and cognitive perspectives, and involving the semiotic, instrumental, and discursive dimensions.

Keywords: convergence, graphical representations, mathematical working spaces, paradigms of real analysis, real number sequences

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Authors: S. Channgam, A. Sae-Tang, T. Termsaithong

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In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.

Keywords: Bak-Tang-Wiesenfeld sandpile model, cross-correlation, avalanches, prediction method

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Authors: Mansour Al Qubeissi, Sergei S. Sazhin, Cyril Crua, Morgan R. Heikal

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This paper presents the application of the Discrete Component Model for heating and evaporation to multi-component biodiesel fuel droplets in direct injection internal combustion engines. This model takes into account the effects of temperature gradient, recirculation and species diffusion inside droplets. A distinctive feature of the model used in the analysis is that it is based on the analytical solutions to the temperature and species diffusion equations inside the droplets. Nineteen types of biodiesel fuels are considered. It is shown that a simplistic model, based on the approximation of biodiesel fuel by a single component or ignoring the diffusion of components of biodiesel fuel, leads to noticeable errors in predicted droplet evaporation time and time evolution of droplet surface temperature and radius.

Keywords: heat/mass transfer, biodiesel, multi-component fuel, droplet

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Authors: A. S. Zgalei, B. T. Al-Mabrouk

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With a particularly significant growth rate observed in the Libyan commercial and residential buildings coupled with a growth in energy demand, solar desiccant evaporative cooling offers energy savings and promises a good sharing for sustainable buildings where the availability of solar radiation matches with the cooling load demand. The paper presents a short introduction for the desiccant systems. A mathematical model of a selected system has been developed and a simulation has been performed in order to investigate the system performance at different working conditions and an optimum design of the system structure is established. The results showed a technical feasibility of the system working under the Libyan climatic conditions with a reasonable COP at temperatures that can be obtained through the solar reactivation system. Discussion of the results and the recommendations for future work are proposed.

Keywords: computer program, solar desiccant wheel cooling, system modelling, simulation, technical feasibility

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Authors: Solmaz Jahed Shiran, Elizabeth Taylor, John Hearne

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Over the past decade a growing body of research, known as mobility biography approach has emerged that focuses on changes in travel behaviour over the life course of individuals. Mobility biographies suggest that changes in travel behaviour have a certain relation to important key events in life courses such as residential relocation, workplace changes, marriage and the birth of children. Taking this approach as the theoretical background, this study uses data from the Household, Income and Labor Dynamics Survey in Australia (HILDA) to model a set of life course events and their interaction with the commute time. By analysing longitudinal data, it is possible to assign different key events during the life course to change a person’s travel behaviour. Changes in the journey-to-work travel time is used as an indication of travel behaviour change in this study. Results of a linear regression model for change in commute time show a significant influence from socio-demographic factors like income and age, the previous home-to-work commute time and remoteness of the residence. Residential relocation and job change have significant influences on commute time. Other life events such as birth of a child, marriage and divorce or separation have also a strong impact on commute time change. Overall, the research confirms previous studies of links between life course events and travel behaviour.

Keywords: life course events, residential mobility, travel behaviour, commute time, job change

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Authors: Lokesh Harshe

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The building construction sector is using 36% of global energy consumption with 39% of CO₂ emission. Professionals in the Built Environment Sector have long been aware of the industry’s contribution towards CO₂ emissions and are now moving towards more sustainable practices. As a result of this, many organizations have introduced rating systems to address the issue of global warming in the construction sector by ranking construction projects based on sustainability parameters. The pre-construction phase of any building project is the most essential time to make decisions for addressing the sustainability aspects. Traditionally, it is very difficult to collect data from different stakeholders and bring it together to form a decision based on factual data to perform sustainability analyses in the pre-construction phase. Building Information Modelling (BIM) is the solution where one single model is the result of the collaborative approach of BIM processes where all the information is shared, extracted, communicated, and stored on a single platform that everyone can access and make decisions based on real-time data. The focus of this research is on the Indian Green Rating System IGBC® with the objective of understanding IGBC® requirements and developing a framework to create the relationship between the rating processes and BIM. A Hypothetical (Architectural) model of a hostel building is developed using AutoCAD 2019 & Revit Arch. 2019, where the framework is applied to generate results on sustainability analysis using Green Building Studio (GBS) and Revit Add-ins. The results of any sustainability analysis are generated within a fraction of a minute, which is very quick in comparison with traditional sustainability analysis. This may save a considerable amount of time as well as cost. The future scope is to integrate Architectural, Structural, and MEP Models to perform accurate sustainability analyses with inputs from industry professionals working on real-life Green BIM projects.

Keywords: sustainability analyses, BIM, green rating systems, IGBC®, LEED

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Authors: Mingyu Xie, Mietek Brdys

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The paper develops a non-linear model predictive control (NMPC) of water quality in drinking water distribution systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.

Keywords: model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives

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Authors: Aboulkacem El Mehdi

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We develop a theoretical model at the crossroads of labour and urban economics, used for explaining the mechanism through which the duration of home-workplace trips and their monetary costs impact the labour demand and supply in a spatially scattered labour market and how they are impacted by a change in passenger transport infrastructures and services. The spatial disconnection between home and job opportunities is referred to as the spatial mismatch hypothesis (SMH). Its harmful impact on employment has been subject to numerous theoretical propositions. However, all the theoretical models proposed so far are patterned around the American context, which is particular as it is marked by racial discrimination against blacks in the housing and the labour markets. Therefore, it is only natural that most of these models are developed in order to reproduce a steady state characterized by agents carrying out their economic activities in a mono-centric city in which most unskilled jobs being created in the suburbs, far from the Blacks who dwell in the city-centre, generating a high unemployment rates for blacks, while the White population resides in the suburbs and has a low unemployment rate. Our model doesn't rely on any racial discrimination and doesn't aim at reproducing a steady state in which these stylized facts are replicated; it takes the main principle of the SMH -the spatial disconnection between homes and workplaces- as a starting point. One of the innovative aspects of the model consists in dealing with a SMH related issue at an aggregate level. We link the parameters of the passengers transport system to employment in the whole area of a city. We consider here a city that consists of four areas: two of them are residential areas with unemployed workers, the other two host firms looking for labour force. The workers compare the indirect utility of working in each area with the utility of unemployment and choose between submitting an application for the job that generate the highest indirect utility or not submitting. This arbitration takes account of the monetary and the time expenditures generated by the trips between the residency areas and the working areas. Each of these expenditures is clearly and explicitly formulated so that the impact of each of them can be studied separately than the impact of the other. The first findings show that the unemployed workers living in an area benefiting from good transport infrastructures and services have a better chance to prefer activity to unemployment and are more likely to supply a higher 'quantity' of labour than those who live in an area where the transport infrastructures and services are poorer. We also show that the firms located in the most accessible area receive much more applications and are more likely to hire the workers who provide the highest quantity of labour than the firms located in the less accessible area. Currently, we are working on the matching process between firms and job seekers and on how the equilibrium between the labour demand and supply occurs.

Keywords: labour market, passenger transport infrastructure, spatial mismatch hypothesis, urban economics

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker

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Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.

Keywords: air pollution, time series modeling, public health, road transport

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Authors: Nidhi Bansal, Upasna Agarwal

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Innovation is a key driver for economic growth and well-being of developed as well as emerging economies like India. Very few studies examined the relationship between IWB and work-family enrichment. Therefore, the present study examines the relationship between work-family enrichment (WFE) and innovative workplace behavior (IWB) and whether it is mediated by positive emotions. Social exchange theory and broaden and build theory explain the proposed relationships. Data were collected from 250 full time dual working parents in different Indian organizations through a survey questionnaire. Snowball technique was used for approaching respondents. Mediation analysis was assessed through PROCESS macro (Hayes, 2012) in SPSS. With correlational analysis, it was explored that all three variables were significantly and positively related. Analysis suggests that work-family enrichment is significantly related to innovative workplace behavior and this relationship is partially mediated by positive emotions. A cross-sectional design, use of self-reported questions and data collected only from dual working parents are few limitations of the study. This is one of the few studies to examine the innovative workplace behavior in response to work-family enrichment and first attempt to examine the mediation effect of emotions between these two variables.

Keywords: dual working parents, emotions, innovative workplace behavior, work-family enrichment

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Changgil Lee, Seunghee Park

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Although vehicle driving test for the development of BWIM system is necessary, but it needs much cost and time in addition application of various driving condition. Thus, we need the numerical-simulation method resolving the cost and time problems of vehicle driving test and the way of measuring response of bridge according to the various driving condition. Using the precision analysis model reflecting the dynamic characteristic is contributed to increase accuracy in numerical simulation. In this paper, we conduct a numerical simulation to apply precision analysis model, which reflects the dynamic characteristic of bridge using Bridge Weigh-in-Motion technique and suggest overload vehicle enforcement technology using precision analysis model.

Keywords: bridge weigh-in-motion(BWIM) system, precision analysis model, dynamic characteristic of bridge, numerical simulation

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Authors: A. Rahim Baharudin, Nor Arinee binti Mat Saaud, Muhammad Afiq Azman, Farah Adiba A. Sani

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Objectives: This paper shares the case study on the engineering analysis, data analysis, and real-time data comparison for qualifying the stand wires' minimum breaking load and safe working load upon loadout operation for a new project and, at the same time, eliminate the risk due to discrepancies and unalignment of COMPANY Technical Standards to Industry Standards and Practices. This paper demonstrates “Lean Construction” for COMPANY’s Project by sustaining fit-for-purpose Technical Requirements of Loadout Strand Wire Factor of Safety (F.S). The case study utilizes historical engineering data from a few loadout operations by skidding methods from different projects. It is also demonstrating and qualifying the skidding wires' minimum breaking load and safe working load used for loadout operation for substructure and other facilities for the future. Methods: Engineering analysis and comparison of data were taken as referred to the international standard and internal COMPANY standard requirements. Data was taken from nine (9) previous projects for both topsides and jacket facilities executed at the several local fabrication yards where load out was conducted by three (3) different service providers with emphasis on four (4) basic elements: i) Industry Standards for Loadout Engineering and Operation Reference: COMPANY internal standard was referred to superseded documents of DNV-OS-H201 and DNV/GL 0013/ND. DNV/GL 0013/ND and DNVGL-ST-N001 do not mention any requirements of Strand Wire F.S of 4.0 for Skidding / Pulling Operations. ii) Reference to past Loadout Engineering and Execution Package: Reference was made to projects delivered by three (3) major offshore facilities operators. Strand Wire F.S observed ranges from 2.0 MBL (Min) to 2.5 MBL (Max). No Loadout Operation using the requirements of 4.0 MBL was sighted from the reference. iii) Strand Jack Equipment Manufacturer Datasheet Reference: Referring to Strand Jack Equipment Manufactured Datasheet by different loadout service providers, it is shown that the Designed F.S for the equipment is also ranging between 2.0 ~ 2.5. Eight (8) Strand Jack Datasheet Model was referred to, ranging from 15 Mt to 850 Mt Capacity; however, there are NO observations of designed F.S 4.0 sighted. iv) Site Monitoring on Actual Loadout Data and Parameter: Max Load on Strand Wire was captured during 2nd Breakout, which is during Static Condition of 12.9 MT / Strand Wire (67.9% Utilization). Max Load on Strand Wire for Dynamic Conditions during Step 8 and Step 12 is 9.4 Mt / Strand Wire (49.5% Utilization). Conclusion: This analysis and study demonstrated the adequacy of strand wires supplied by the service provider were technically sufficient in terms of strength, and via engineering analysis conducted, the minimum breaking load and safe working load utilized and calculated for the projects were satisfied and operated safely for the projects. It is recommended from this study that COMPANY’s technical requirements are to be revised for future projects’ utilization.

Keywords: construction, load out, minimum breaking load, safe working load, strand jacking, skidding

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Authors: Hossein Shokouhmand, Masoomeh Shadab, Rohallah Torabi

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Turbulent flow inside the seal chamber of a pump operating at nearly high Reynolds number is investigated. A comparison of a 3-D computational model for flow and thermal analysis of a mechanical seal with experimental thermal results is presented. The computational model adequately predicts the flow field in the seal chamber and thermal characteristics with the rotating and stationary rings and the twister flow around the seal parts by solving N-S and energy equations in ANSYS-CFX software. The Reynolds stress model (RSM) is applied as a turbulence model for this purpose. Experimental work is discussed which quantifies the temperature of five different points of the working fluid in chamber, mass flow at inlet and the fluid pressure at inlet and outlet. Experimental measurements are combined with computational modeling to obtain local and average heat transfer characteristics. Numerical results of three cases including different flush rates are reported.

Keywords: mechanical seal, CFD_CFX, reynolds stress model, flow field, heat transfer analysis, stream line, heat transfer coefficient, heat flux, nusselt

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Authors: S. K. Ashiquer Rahman

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Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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Authors: Uwe C. Fischer

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Mental health and well-being for employees working in the human service system are getting more and more important given the increasing rate of absenteeism at work. Besides individual capacities, social and community factors seem to be important in the working setting. Starting from a demand resource framework including the classical demand control aspects, social support systems, specific demands and resources of the client work, and work-family conflict were considered in the present study. We state hypothetically, that these factors have a meaningful association with the mental quality of life of employees working in the field of social, educational and health sectors. 1140 employees, working in human service organizations (education, youth care, nursing etc.) were asked for strains and resources at work (selected scales from Salutogenetic Subjective Work Assessment SALSA and own new scales for client work), work-family conflict, and mental quality of life from the German Short Form Health Survey. Considering the complex influences of the variables, we conducted a multiple hierarchical regression analysis. One third of the whole variance of the mental quality of life can be declared by the different variables of the model. When the variables concerning social influences were included in the hierarchical regression, the influence of work related control resource decreased. Excessive workload, work-family conflict, social support by supervisors, co-workers and other persons outside work, as well as strains and resources associated with client work had significant regression coefficients. Conclusions: Social support systems are crucial in the social, educational and health related service sector, regarding the influence on mental well-being. Especially the work-family conflict focuses on the importance of the work-life balance. Also the specific strains and resources of the client work, measured with new constructed scales, showed great impact on mental health. Therefore occupational health promotion should focus more on the social factors within and outside the working place.

Keywords: client interaction, human service system, mental health, social support, work-family conflict

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Ashwini V. Chavan, Sukhanand S. Bhosale

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Challenges of weak soil subgrade are often resolved either by stabilization or reinforcing it. However, it is also practiced to reinforce the granular fill to improve the load-settlement behavior of over weak soil strata. The inclusion of reinforcement in the engineered granular fill provided a new impetus for the development of enhanced Soil-Structure Interaction (SSI) models, also known as mechanical foundation models or lumped parameter models. Several researchers have been working in this direction to understand the mechanism of granular fill-reinforcement interaction and the response of weak soil under the application of load. These models have been developed by extending available SSI models such as the Winkler Model, Pasternak Model, Hetenyi Model, Kerr Model etc., and are helpful to visualize the load-settlement behavior of a physical system through 1-D and 2-D analysis considering beam and plate resting on the foundation respectively. Based on the literature survey, these models are categorized as ‘Reinforced Pasternak Model,’ ‘Double Beam Model,’ ‘Reinforced Timoshenko Beam Model,’ and ‘Reinforced Kerr Model.’ The present work reviews the past 30+ years of research in the field of SSI models for reinforced foundation systems, presenting the conceptual development of these models systematically and discussing their limitations. Special efforts are taken to tabulate the parameters and their significance in the load-settlement analysis, which may be helpful in future studies for the comparison and enhancement of results and findings of physical models.

Keywords: geosynthetics, mathematical modeling, reinforced foundation, soil-structure interaction, ground improvement, soft soil

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Hiroshi Ikeda

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In this research, a questionnaire survey was conducted to measure nap, drowsiness and fatigue of drivers who work long shifts, to discuss about the work environment and health conditions for taxi and bus drivers who work at night time. The questionnaire sheet used for this research was organized into the following categories: tension/tiredness, drowsiness while driving, and the nap situation during night-time work. The number of taxi drivers was 127 and the number of bus drivers was 40. Concerning the results of a comparison of nap hours of taxi and bus drivers, the taxi drivers’ nap hours are overwhelmingly shorter, and also the frequency of drivers who feel drowsiness is higher. The burden on bus drivers does not change because of the system of a two-driver rotation shift. In particular, the working environment of the taxi driver may lead to greater fatigue accumulation than the bus driver’s environment.

Keywords: bus and taxi, drowsiness, fatigue, nap

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Authors: Sabita Karki

Abstract:

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

Procedia PDF Downloads 323

Authors: L. Korpinen, R. Pääkkönen, F. Gobba

Abstract:

Accidents and close call situations involving cell phones are nowadays possible. The objective of this study was to investigate the accidents and close call situations due to cell phone use while moving, driving, and working among Finns aged between 18 and 65. This work is part of a large cross-sectional study that was carried out on 15,000 working-age Finns. About 26% of people who had an accident, and about half of the people including close call situation with the mobile phone, answered that use of the phone influenced. In the future, it is important to take into account that the use of a mobile phone can be distracting while driving.

Keywords: blue-collar workers, accident, cell phone, close call situation

Procedia PDF Downloads 289

Authors: Entisar A. Elgmati

Abstract:

Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

Procedia PDF Downloads 609

Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

Procedia PDF Downloads 102