Search results for: reliable facility location model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20146

Search results for: reliable facility location model

16846 Development and Psychometric Validation of the Hospitalised Older Adults Dignity Scale for Measuring Dignity during Acute Hospital Admissions

Authors: Abdul-Ganiyu Fuseini, Bernice Redley, Helen Rawson, Lenore Lay, Debra Kerr

Abstract:

Aim: The study aimed to develop and validate a culturally appropriate patient-reported outcome measure for measuring dignity for older adults during acute hospital admissions. Design: A three-phased mixed-method sequential exploratory design was used. Methods: Concept elicitation and generation of items for the scale was informed by older adults’ perspectives about dignity during acute hospitalization and a literature review. Content validity evaluation and pre-testing were undertaken using standard instrument development techniques. A cross-sectional survey design was conducted involving 270 hospitalized older adults for evaluation of construct and convergent validity, internal consistency reliability, and test–retest reliability of the scale. Analysis was performed using Statistical Package for the Social Sciences, version 25. Reporting of the study was guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. Results: We established the 15-item Hospitalized Older Adults’ Dignity Scale that has a 5-factor structure: Shared Decision-Making (3 items); Healthcare Professional-Patient Communication (3 items); Patient Autonomy (4 items); Patient Privacy (2 items); and Respectful Care (3 items). Excellent content validity, adequate construct and convergent validity, acceptable internal consistency reliability, and good test-retest reliability were demonstrated. Conclusion: We established the Hospitalized Older Adults Dignity Scale as a valid and reliable scale to measure dignity for older adults during acute hospital admissions. Future studies using confirmatory factor analysis are needed to corroborate the dimensionality of the factor structure and external validity of the scale. Routine use of the scale may provide information that informs the development of strategies to improve dignity-related care in the future. Impact: The development and validation of the Hospitalized Older Adults Dignity Scale will provide healthcare professionals with a feasible and reliable scale for measuring older adults’ dignity during acute hospitalization. Routine use of the scale may enable the capturing and incorporation of older patients’ perspectives about their healthcare experience and provide information that informs the development of strategies to improve dignity-related care in the future.

Keywords: dignity, older adults, hospitalisation, scale, patients, dignified care, acute care

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16845 Release Management with Continuous Delivery: A Case Study

Authors: A. Maruf Aytekin

Abstract:

We present our approach on using continuous delivery pattern for release management. One of the key practices of agile and lean teams is the continuous delivery of new features to stakeholders. The main benefits of this approach lie in the ability to release new applications rapidly which has real strategic impact on the competitive advantage of an organization. Organizations that successfully implement Continuous Delivery have the ability to evolve rapidly to support innovation, provide stable and reliable software in more efficient ways, decrease the amount of resources need for maintenance, and lower the software delivery time and costs. One of the objectives of this paper is to elaborate a case study where IT division of Central Securities Depository Institution (MKK) of Turkey apply Continuous Delivery pattern to improve release management process.

Keywords: automation, continuous delivery, deployment, release management

Procedia PDF Downloads 249
16844 A Stochastic Diffusion Process Based on the Two-Parameters Weibull Density Function

Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

Abstract:

Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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16843 Advanced Exergetic Analysis: Decomposition Method Applied to a Membrane-Based Hard Coal Oxyfuel Power Plant

Authors: Renzo Castillo, George Tsatsaronis

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High-temperature ceramic membranes for air separation represents an important option to reduce the significant efficiency drops incurred in state-of-the-art cryogenic air separation for high tonnage oxygen production required in oxyfuel power stations. This study is focused on the thermodynamic analysis of two power plant model designs: the state-of-the-art supercritical 600ᵒC hard coal plant (reference power plant Nordrhein-Westfalen) and the membrane-based oxyfuel concept implemented in this reference plant. In the latter case, the oxygen is separated through a mixed-conducting hollow fiber perovskite membrane unit in the three-end operation mode, which has been simulated under vacuum conditions on the permeate side and at high-pressure conditions on the feed side. The thermodynamic performance of each plant concept is assessed by conventional exergetic analysis, which determines location, magnitude and sources of efficiency losses, and advanced exergetic analysis, where endogenous/exogenous and avoidable/unavoidable parts of exergy destruction are calculated at the component and full process level. These calculations identify thermodynamic interdependencies among components and reveal the real potential for efficiency improvements. The endogenous and exogenous exergy destruction portions are calculated by the decomposition method, a recently developed straightforward methodology, which is suitable for complex power stations with a large number of process components. Lastly, an improvement priority ranking for relevant components, as well as suggested changes in process layouts are presented for both power stations.

Keywords: exergy, carbon capture and storage, ceramic membranes, perovskite, oxyfuel combustion

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16842 Owner/Managers’ External Financing Used and Preference towards Islamic Banking

Authors: Khalid Hassan Abdesamed, Kalsom Abd Wahab

Abstract:

Economic development and growth are significantly linked to the consistent and sustainable sector of small and medium enterprises (SMEs). Banks are the frontrunners in financing and advising SMEs. The main objective of the study is to assess the tendency of SMEs to use the Islamic bank. Model was developed using quantitative method with a hypothetical-deductive testing approach. Model (N = 364) used primary data on the tendency of SMEs to use Islamic banks gathered from questionnaire. It is found by Mann-Whitney test that the tendency to use Islamic bank varies between those firms which consider formal financing with the ones relying on informal financing with the latter tends more to use Islamic bank. This study can serve academic researchers, policy makers, and developing countries as a model of SMEs’ desirability to Islamic banking.

Keywords: formal financing, informal financing, Islamic bank, SMEs

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16841 The Outcome of Using Machine Learning in Medical Imaging

Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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16840 Data Integration with Geographic Information System Tools for Rural Environmental Monitoring

Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

Abstract:

The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

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16839 Site Selection of CNG Station by Using FUZZY-AHP Model (Case Study: Gas Zone 4, Tehran City Iran)

Authors: Hamidrza Joodaki

Abstract:

The most complex issue in urban land use planning is site selection that needs to assess the verity of elements and factors. Multi Criteria Decision Making (MCDM) methods are the best approach to deal with complex problems. In this paper, combination of the analytical hierarchy process (AHP) model and FUZZY logic was used as MCDM methods to select the best site for gas station in the 4th gas zone of Tehran. The first and the most important step in FUZZY-AHP model is selection of criteria and sub-criteria. Population, accessibility, proximity and natural disasters were considered as the main criteria in this study. After choosing the criteria, they were weighted based on AHP by EXPERT CHOICE software, and FUZZY logic was used to enhance accuracy and to approach the reality. After these steps, criteria layers were produced and weighted based on FUZZY-AHP model in GIS. Finally, through ARC GIS software, the layers were integrated and the 4th gas zone in TEHRAN was selected as the best site to locate gas station.

Keywords: multiple criteria decision making (MCDM), analytic hierarchy process (AHP), FUZZY logic, geographic information system (GIS)

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16838 Meat Qualities and Death on Arrival (DOA) of Broiler Chickens Transported in a Brazilian Tropical Conditions

Authors: Arlan S. Freitas, Leila M. Carvalho, Adriana L. Soares, Arnoud Neto, Marta S. Madruga, Elza I. Ida, Massami Shimokomaki

Abstract:

The objective of this work was to evaluate the influence of microclimatic profile of broiler transport trucks under commercial conditions over the breast meat quality and DOA (Death On Arrival) in a tropical Brazilian regions as the North East where routinely the season is divided into dry and wet seasons. The temperature remains fairly constant and obviously the relative humidity changes accordingly. Three loads of 4,100 forty seven days old broiler were monitored from farm to slaughterhouse in a distance of 4.3 km, morning period of October 2015 rainy days. The profile of the environmental variables inside the container truck throughout the journey was obtained by the installation of thermo anemometers in 6 different locations by monitoring the heat index (HI), air velocity (AV), temperature (T), and relative humidity (RH). Meat qualities were evaluated by determining the occurrence of PSE (pale, soft, exudative) meat and DFD (dark, firm dry) meat. The percentage of birds DOA per loaded truck was determined by counting the dead broiler during the hanging step at the slaughtering plant. The analysis of variance was performed using statistical software (Statistica 8 for windows, Statsoft 2007, Tulsa, OK, USA). The Tukey significance test (P<0.05) was applied to compare means from microenvironmental data, PSE, DFD and DOA. Fillet samples were collected at 24h post mortem for pH e color (L*, a* e b*) determination through the CIELAB system. Results showed the occurrence of 2.98% of PSE and 0.66% de DFD and only 0.016% of DOA and overall the most uncomfortable container location was at the truck frontal inferior presenting 6.25% of PSE. DFD of 2.0% were obtained from birds located at central and inferior rear locations. These values were unexpected in comparison to other results obtained in our laboratories in previous experiments carried out within the country south state. The results reported herein were lower in every aspect. Reasonable explanation would be the shorter distance, wet conditions throughout around 15-20 min journeys and lower T and RH values as observed in samples taken from the rear location as higher DFD values were obtained. These facts mean the animals were not under heat stressful condition but in fact under cold stress conditions as the result of DFD suggested in association to the lower number of DOA.

Keywords: cold stress, DFD, microclimatic profile, PSE

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16837 Predictive Value of Coagulopathy in Patients with Isolated Blunt Traumatic Brain Injury: A Cohort of Pakistani Population

Authors: Muhammad Waqas, Shahan Waheed, Mohsin Qadeer, Ehsan Bari, Salman Ahmed, Iqra Patoli

Abstract:

Objective: To determine the value of aPTT, platelets and INR as the predictor of unfavorable outcomes in patients with blunt isolated traumatic brain injury. Methods: This was an observational cohort study conducted in a tertiary care facility from 1st January 2008 to 31st December 2012. All the patients with isolated traumatic brain injury presenting within 24 hours of injury were included in the study. Coagulation parameters at presentation were recorded and Glasgow Outcome Scale calculated on last follow up. Outcomes were dichotomized into favorable and unfavorable outcomes. Relationship of coagulopathy with GOS and unfavorable outcomes was calculated using Spearman`s correlation and area under curve ROC analysis. Results: 121 patients were included in the study. The incidence of coagulopathy was found to be 6 %. aPTT was found to a significantly associated with unfavorable outcomes with an AUC = 0.702 (95%CI = 0.602-0.802). Predictive value of platelets and INR was not found to be significant. Conclusion: Incidence of coagulopathy was found to be low in current population compared to data from the West. aPTT was found to be a good predictor of unfavorable outcomes compared with other parameters of coagulation.

Keywords: aPTT, coagulopathy, unfavorable outcomes, parameters

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16836 Presenting a Model Of Empowering New Knowledge-based Companies In Iran Insurance Industry

Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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16835 Generation of Waste Streams in Small Model Reactors

Authors: Sara Mostofian

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The nuclear industry is a technology that can fulfill future energy needs but requires special attention to ensure safety and reliability while minimizing any environmental impact. To meet these expectations, the nuclear industry is exploring different reactor technologies for power production. Several designs are under development and the technical viability of these new designs is the subject of many ongoing studies. One of these studies considers the radioactive emissions and radioactive waste generated during the life of a nuclear power production plant to allow a successful license process. For all the modern technologies, a good understanding of the radioactivity generated in the process systems of the plant is essential. Some of that understanding may be gleaned from the performance of some prototype reactors of similar design that operated decades ago. This paper presents how, with that understanding, a model can be developed to estimate the emissions as well as the radioactive waste during the normal operation of a nuclear power plant. The model would predict the radioactive material concentrations in different waste streams. Using this information, the radioactive emission and waste generated during the life of these new technologies can be estimated during the early stages of the design of the plant.

Keywords: SMRs, activity transport, model, radioactive waste

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16834 Imperfect Production Inventory Model with Inspection Errors and Fuzzy Demand and Deterioration Rates

Authors: Chayanika Rout, Debjani Chakraborty, Adrijit Goswami

Abstract:

Our work presents an inventory model which illustrates imperfect production and imperfect inspection processes for deteriorating items. A cost-minimizing model is studied considering two types of inspection errors, namely, Type I error of falsely screening out a proportion of non-defects, thereby passing them on for rework and Type II error of falsely not screening out a proportion of defects, thus selling those to customers which incurs a penalty cost. The screened items are reworked; however, no returns are entertained due to deteriorating nature of the items. In more practical situations, certain parameters such as the demand rate and the deterioration rate of inventory cannot be accurately determined, and therefore, they are assumed to be triangular fuzzy numbers in our model. We calculate the optimal lot size that must be produced in order to minimize the total inventory cost for both the crisp and the fuzzy models. A numerical example is also considered to exemplify the procedure which is followed by the analysis of sensitivity of various parameters on the decision variable and the objective function.

Keywords: deteriorating items, EPQ, imperfect quality, rework, type I and type II inspection errors

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16833 A Mathematical Model of Blood Perfusion Dependent Temperature Distribution in Transient Case in Human Dermal Region

Authors: Yogesh Shukla

Abstract:

Many attempts have been made to study temperature distribution problem in human tissues under normal environmental and physiological conditions at constant arterial blood temperature. But very few attempts have been made to investigate temperature distribution in human tissues under different arterial blood temperature. In view of above, a finite element model has been developed to unsteady temperature distribution in dermal region in human body. The model has been developed for one dimension unsteady state case. The variation in parameters like thermal conductivity, blood mass flow and metabolic activity with respect to position and time has been incorporated in the model. Appropriate boundary conditions have been framed. The central difference approach has been used in space variable and trapezoidal rule has been employed a long time variable. Numerical results have been obtained to study relationship among temperature and time.

Keywords: rate of metabolism, blood mass flow rate, thermal conductivity, heat generation, finite element method

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16832 A Deep Learning Approach to Detect Complete Safety Equipment for Construction Workers Based on YOLOv7

Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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16831 Demographic Factors Influencing Employees’ Salary Expectations and Labor Turnover

Authors: M. Osipova

Abstract:

Thanks to informational technologies development every sphere of economics is becoming more and more data-centralized as people are generating huge datasets containing information on any aspect of their life. Applying research of such data to human resources management allows getting scarce statistics on labor market state including salary expectations and potential employees’ typical career behavior, and this information can become a reliable basis for management decisions. The following article presents results of career behavior research based on freely accessible resume data. Information used for study is much wider than one usually uses in human resources surveys. That is why there is enough data for statistically significant results even for subgroups analysis.

Keywords: human resources management, salary expectations, statistics, turnover

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16830 Modeling Driving Distraction Considering Psychological-Physical Constraints

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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16829 Particle Swarm Optimisation of a Terminal Synergetic Controllers for a DC-DC Converter

Authors: H. Abderrezek, M. N. Harmas

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DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DC-DC converters control mostly with asymptotic convergence. Synergetic control (SC) is a proven robust control approach and will be used here in a so-called terminal scheme to achieve finite time convergence. Lyapunov synthesis is adopted to assure controlled system stability. Furthermore particle swarm optimization (PSO) algorithm, based on an integral time absolute of error (ITAE) criterion will be used to optimize controller parameters. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to classic synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed control method.

Keywords: DC-DC converter, PSO, finite time, terminal, synergetic control

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16828 A Hybrid Method for Determination of Effective Poles Using Clustering Dominant Pole Algorithm

Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

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16827 Physical Education Effect on Sports Science Analysis Technology

Authors: Peter Adly Hamdy Fahmy

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The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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16826 Experimentally Validated Analytical Model for Thermal Analysis of Multi-Stage Depressed Collector

Authors: Vishant Gahlaut, A Mercy Latha, Sanjay Kumar Ghosh

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Multi-stage depressed collectors (MDC) are used as an efficiency enhancement technique in traveling wave tubes the high-energy electron beam, after its interaction with the RF signal, gets velocity sorted and collected at various depressed electrodes of the MDC. The ultimate goal is to identify an optimum thermal management scheme (cooling mechanism) that could extract the heat efficiently from the electrodes. Careful thermal analysis, incorporating the cooling mechanism is required to ensure that the maximum temperature does not exceed the safe limits. A simple analytical model for quick prediction of the thermal has been developed. The model has been developed for the worst-case un-modulated DC condition, where all the thermal power is dissipated in the last electrode (typically, fourth electrode in the case of the four-stage depressed collector). It considers the thermal contact resistances at various braze joints accounting for the practical non-uniformities. Analytical results obtained from the model have been validated with simulated and experimental results.

Keywords: multi-stage depressed collector, TWTs, thermal contact resistance, thermal management

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16825 Investigation of Enhanced Geothermal System with CO2 as Working Fluid

Authors: Ruina Xu, Peixue Jiang, Feng Luo

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The novel concept of enhanced geothermal system with CO2 instead of water as working fluid (CO2-EGS) has attracted wide attention due to additional benefit of CO2 geological storage during the power generation process. In this research, numerical investigation on a doublet CO2-EGS system is performed, focusing on the influence of the injection/production well perforation location in the targeted geothermal reservoir. Three different reservoir inlet and outlet boundary conditions are used in simulations since the well constrains are different in reality. The results show that CO2-EGS system performance of power generation and power cost vary greatly among cases of different wells perforation locations, and the optimum options under different boundary conditions are also different.

Keywords: Enhanced Geothermal System, supercritical CO2, heat transfer, CO2-EGS

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16824 An Analytic Cross-Sectional Study on the Association between Social Determinants of Health, Maternal and Child Health-Related Knowledge and Attitudes, and Utilization of Maternal, Newborn, Child Health and Nutrition Strategy-Prescribed Services for M

Authors: Rafael Carlos C. Aniceto, Bryce Abraham M. Anos, Don Christian A. Cornel, Marjerie Brianna S. Go, Samantha Nicole U. Roque, Earl Christian C. Te

Abstract:

Indigenous peoples (IPs) in the Philippines are a vulnerable, marginalized group in terms of health and overall well-being due to social inequities and cultural differences. National standards regarding maternal healthcare are geared towards facility-based delivery with modern medicine, health services, and skilled birth attendants. Standards and procedures of care for pregnant mothers do not take into account cultural differences between indigenous people and the majority of the population. There do exist, however, numerous other factors that cause relatively poorer health outcomes among indigenous peoples (IPs). This analytic cross-sectional study sought to determine the association between social determinants of health (SDH), focusing on status as indigenous peoples, and maternal health-related knowledge and attitudes (KA), and health behavior of the Dumagat-Agta indigenous people of Barangay Catablingan and Barangay San Marcelino, General Nakar, Quezon Province, and their utilization of health facilities for antenatal care, facility-based delivery and postpartum care, which would affect their health outcomes (that were not within the scope of this study). To quantitatively measure the primary/secondary exposures and outcomes, a total of 90 face-to-face interviews with IP and non-IP mothers were done. For qualitative information, participant observation among 6 communities (5 IP and 1 non-IP), 11 key informant interviews (traditional and modern health providers) and 4 focused group discussions among IP mothers were conducted. Primary quantitative analyses included chi-squared, T-test and binary logistic regression, while secondary qualitative analyses involved thematic analysis and triangulation. The researchers spent a total of 15 days in the community to learn the culture and participate in the practices of the Dumagat-Agta more intensively and deeply. Overall, utilization of all MNCHN services measured in the study was lower for IP mothers compared to their non-IP counterparts. After controlling for confounders measured in the study, IP status (primary exposure) was found to be significantly correlated with utilization of and adherence to two MNCHN-prescribed services: number of antenatal care check-ups and place of delivery (secondary outcomes). Findings show that being an indigenous mother leads to unfavorable social determinants of health, and if compounded by a difference in knowledge and attitudes, would then lead to poor levels of utilization of MNCHN-prescribed services. Key themes from qualitative analyses show that factors that affected utilization were: culture, land alienation, social discrimination, socioeconomic status, and relations between IPs and non-IPs, specifically with non-IP healthcare providers. The findings of this study aim to be used to help and guide in policy-making, to provide healthcare that is not only adequate and of quality, but more importantly, that addresses inequities stemming from various social determinants, and which is socio-culturally acceptable to indigenous communities. To address the root causes of health problems of IPs, there must be full recognition and exercise of their collective rights to communal assets, specifically land, and self-determination. This would improve maternal and child health outcomes to one of the most vulnerable and neglected sectors in society today.

Keywords: child health, indigenous people, knowledge-attitudes-practices, maternal health, social determinants of health

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16823 Hydro-Mechanical Forming of AZ31 Sheet

Authors: Yong-Nam Kwon

Abstract:

In the present study, we have designed the hydro-mechanical forming in which AZ31 sheet was drawn to a kind of preform step following gas blow forming for accurate geometry. In order to judge a formability enhancement of AZ31 sheet, model geometry came from a practical automotive part which had quite depth with complicated curvatures, which was proven that a single sheet forming could not gave a successful part. Experimentally, we succeeded to make the model part with accurate dimension. The optimum forming conditions for respective forming steps were considered most important technical features of this hydro-mechanical and would be discussed in details. Also, the effort to avoid detrimental abnormal grain growth was given and discussed for a practical application.

Keywords: hydro-mechanical forming, AZ31, abnormal grain growth, model geometry

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16822 Online Learning for Modern Business Models: Theoretical Considerations and Algorithms

Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

Abstract:

This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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16821 Dynamics of the Coupled Fitzhugh-Rinzel Neurons

Authors: Sanjeev Kumar Sharma, Arnab Mondal, Ranjit Kumar Upadhyay

Abstract:

Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization.

Keywords: excitable neuron model, spiking-bursting, stability and bifurcation, synchronization networks

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16820 The Role of Women in Climate Change Impact in Kupang-Indonesia

Authors: Rolland Epafras Fanggidae

Abstract:

The impact of climate change such as natural disasters, crop failures, increasing crop pests, bad gisi on children and other impacts, will indirectly affect education, health, food safety, as well as the economy. The impact of climate change has put a man in a situation of vulnerability, which was powerless to meet the minimum requirements, it is in close contact with poverty. When talking about poverty, the most plausible is female. The role of women in Indonesia, particularly in East Nusa Tenggara in Domestic aktifity very central and dominant. This makes Indonesian woman can say "outstanding actor in the face of climate change mitigation and adaptation and applying local knowledge", but still ignored when women based on gender division of work entrusted role in domestic activities. Similarly, in public activity is an extension of the Domestic example, trading activity in the market lele / mama. Although men are also affected by climate change, but most feel is female. From the above problems, it can be said that Indonesia's commitment has not been followed by optimal empowerment of women's role in addressing climate change, it is necessary to learn to know how the role of women in the face of climate change impacts that hit on her role as a woman, a housewife or head of the family and will be input in order to determine how women find a solution to tackle the problem of climate change. This study focuses on the efforts made by women cope with the impacts of climate change, efforts by the government, empowerment model used in Playing the impact of climate change. The container with the formulation of the title "The Role of Women in Climate Change Impact in Kupang district". Where the assessment in use types Research mix Methods combination of quantitative research and qualitative research. While the location of the research conducted in Kupang regency, East Nusa Tenggara, namely: District of East Kupang is a district granary in Kupang district. Subdistrict West Kupang, especially Tablolong Village is the center of seaweed cultivation in Kupang district.

Keywords: climate change, women, women's roles, gender, family

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16819 Chromatography Study of Fundamental Properties of Medical Radioisotope Astatine-211

Authors: Evgeny E. Tereshatov

Abstract:

Astatine-211 is considered one of the most promising radionuclides for Targeted Alpha Therapy. In order to develop reliable procedures to label biomolecules and utilize efficient delivery vehicle principles, one should understand the main chemical characteristics of astatine. The short half-life of 211At (~7.2 h) and absence of any stable isotopes of this element are limiting factors towards studying the behavior of astatine. Our team has developed a procedure for rapid and efficient isolation of astatine from irradiated bismuth material in nitric acid media based on 3-octanone and 1-octanol extraction chromatography resins. This process has been automated and it takes 20 min from the beginning of the target dissolution to the At-211 fraction elution. Our next step is to consider commercially available chromatography resins and their applicability in astatine purification in the same media. Results obtained along with the corresponding sorption mechanisms will be discussed.

Keywords: astatine-211, chromatography, automation, mechanism, radiopharmaceuticals

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16818 A Structural Constitutive Model for Viscoelastic Rheological Behavior of Human Saphenous Vein Using Experimental Assays

Authors: Rassoli Aisa, Abrishami Movahhed Arezu, Faturaee Nasser, Seddighi Amir Saeed, Shafigh Mohammad

Abstract:

Cardiovascular diseases are one of the most common causes of mortality in developed countries. Coronary artery abnormalities and carotid artery stenosis, also known as silent death, are among these diseases. One of the treatment methods for these diseases is to create a deviatory pathway to conduct blood into the heart through a bypass surgery. The saphenous vein is usually used in this surgery to create the deviatory pathway. Unfortunately, a re-surgery will be necessary after some years due to ignoring the disagreement of mechanical properties of graft tissue and/or applied prostheses with those of host tissue. The objective of the present study is to clarify the viscoelastic behavior of human saphenous tissue. The stress relaxation tests in circumferential and longitudinal direction were done in this vein by exerting 20% and 50% strains. Considering the stress relaxation curves obtained from stress relaxation tests and the coefficients of the standard solid model, it was demonstrated that the saphenous vein has a non-linear viscoelastic behavior. Thereafter, the fitting with Fung’s quasilinear viscoelastic (QLV) model was performed based on stress relaxation time curves. Finally, the coefficients of Fung’s QLV model, which models the behavior of saphenous tissue very well, were presented.

Keywords: Viscoelastic behavior, stress relaxation test, uniaxial tensile test, Fung’s quasilinear viscoelastic (QLV) model, strain rate

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16817 Development of a Coupled Thermal-Mechanical-Biological Model to Simulate Impacts of Temperature on Waste Stabilization at a Landfill in Quebec, Canada

Authors: Simran Kaur, Paul J. Van Geel

Abstract:

A coupled Thermal-Mechanical-Biological (TMB) model was developed for the analysis of impacts of temperatures on waste stabilization at a Municipal Solid Waste (MSW) landfill in Quebec, Canada using COMSOL Multiphysics, a finite element-based software. For waste placed in landfills in Northern climates during winter months, it can take months or even years before the waste approaches ideal temperatures for biodegradation to occur. Therefore, the proposed model links biodegradation induced strain in MSW to waste temperatures and corresponding heat generation rates as a result of anaerobic degradation. This provides a link between the thermal-biological and mechanical behavior of MSW. The thermal properties of MSW are further linked to density which is tracked and updated in the mechanical component of the model, providing a mechanical-thermal link. The settlement of MSW is modelled based on the concept of viscoelasticity. The specific viscoelastic model used is a single Kelvin – Voight viscoelastic body in which the finite element response is controlled by the elastic material parameters – Young’s Modulus and Poisson’s ratio. The numerical model was validated with 10 years of temperature and settlement data collected from a landfill in Ste. Sophie, Quebec. The coupled TMB modelling framework, which simulates placement of waste lifts as they are placed progressively in the landfill, allows for optimization of several thermal and mechanical parameters throughout the depth of the waste profile and helps in better understanding of temperature dependence of MSW stabilization. The model is able to illustrate how waste placed in the winter months can delay biodegradation-induced settlement and generation of landfill gas. A delay in waste stabilization will impact the utilization of the approved airspace prior to the placement of a final cover and impact post-closure maintenance. The model provides a valuable tool to assess different waste placement strategies in order to increase airspace utilization within landfills operating under different climates, in addition to understanding conditions for increased gas generation for recovery as a green and renewable energy source.

Keywords: coupled model, finite element modeling, landfill, municipal solid waste, waste stabilization

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