Search results for: estimations of probability distributions

Authors: A. G. Akhundov

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Issues of obtaining unbiased data on the status of pipeline systems of oil- and oil product transportation become especially important when laying and operating pipelines under severe nature and climatic conditions. The essential attention is paid here to researching exogenous processes and their impact on linear facilities of the pipeline system. Reliable operation of pipelines under severe nature and climatic conditions, timely planning and implementation of compensating measures are only possible if operation conditions of pipeline systems are regularly monitored, and changes of permafrost soil and hydrological operation conditions are accounted for. One of the main reasons for emergency situations to appear is the geodynamic factor. Emergency situations are proved by the experience to occur within areas characterized by certain conditions of the environment and to develop according to similar scenarios depending on active processes. The analysis of natural and technical systems of main pipelines at different stages of monitoring gives a possibility of making a forecast of the change dynamics. The integration of GIS technologies, traditional means of geotechnical monitoring (in-line inspection, geodetic methods, field observations), and remote methods (aero-visual inspection, aero photo shooting, air and ground laser scanning) provides the most efficient solution of the problem. The united environment of geo information system (GIS) is a comfortable way to implement the monitoring system on the main pipelines since it provides means to describe a complex natural and technical system and every element thereof with any set of parameters. Such GIS enables a comfortable simulation of main pipelines (both in 2D and 3D), the analysis of situations and selection of recommendations to prevent negative natural or man-made processes and to mitigate their consequences. The specifics of such systems include: a multi-dimensions simulation of facilities in the pipeline system, math modelling of the processes to be observed, and the use of efficient numeric algorithms and software packets for forecasting and analyzing. We see one of the most interesting possibilities of using the monitoring results as generating of up-to-date 3D models of a facility and the surrounding area on the basis of aero laser scanning, data of aerophotoshooting, and data of in-line inspection and instrument measurements. The resulting 3D model shall be the basis of the information system providing means to store and process data of geotechnical observations with references to the facilities of the main pipeline; to plan compensating measures, and to control their implementation. The use of GISs for geotechnical monitoring of pipeline systems is aimed at improving the reliability of their operation, reducing the probability of negative events (accidents and disasters), and at mitigation of consequences thereof if they still are to occur.

Keywords: databases, 3D GIS, geotechnical monitoring, pipelines, laser scaning

Procedia PDF Downloads 165

Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Mohamed Hendawy Mousa, Warda Youssef Mohamed Morsy

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Background: Sepsis is a major cause of mortality and morbidity in trauma patients. Body mass index as an indicator of nutritional status was reported as a predictor of injury pattern and complications among critically ill injured patients. Aim: The aim of this study is to investigate the relationship between body mass index and the development of sepsis, systemic inflammatory response syndrome among adult trauma patients at emergency hospital - Cairo University. Research design: Descriptive correlational research design was utilized in the current study. Research questions: Q1. What is the body mass index profile of adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, Q2. What is the frequency of systemic inflammatory response syndrome and sepsis among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, and Q3. What is the relationship between the development of sepsis, systemic inflammatory response syndrome and body mass index among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?. Sample: A purposive sample of 52 adult male and female trauma patients with revised trauma score 10 to 12. Setting: The Emergency Hospital affiliated to Cairo University. Tools: Four tools were utilized to collect data pertinent to the study: Socio demographic and medical data tool, Systemic inflammatory response syndrome assessment tool, Revised Trauma Score tool, and Sequential organ failure assessment tool. Results: The current study revealed that, (61.5 %) of the studied subjects had normal body mass index, (25 %) were overweight, and (13.5 %) were underweight. 84.6% of the studied subjects had systemic inflammatory response syndrome and 92.3% were suffering from mild sepsis. No significant statistical relationship was found between body mass index and occurrence of Systemic inflammatory response syndrome (2= 2.89 & P = 0.23). However, Sequential organ failure assessment scores were affected significantly by body mass index was found mean of initial and last Sequential organ failure assessment score for underweight, normal and obese where t= 7.24 at p = 0.000, t= 16.49 at p = 0.000 and t= 9.80 at p = 0.000 respectively. Conclusion: Underweight trauma patients showed significantly higher rate of developing sepsis as compared to patients with normal body weight and obese. Recommendations: based on finding of this study the following are recommended: replication of the study on a larger probability sample from different geographical locations in Egypt; Carrying out of further studies in order to assess the other risk factors influencing trauma outcome and incidence of its complications; Establishment of standardized guidelines for managing underweight traumatized patients with sepsis.

Keywords: body mass index, sepsis, systemic inflammatory response syndrome, adult trauma

Procedia PDF Downloads 228

Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Parichehr Sharifi, Konrad Reschke, Hans-Liudger Dienel

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Psychological intervention generally targets changes in attitudes and behavior. Working with DUIs is part of traffic psychologists’ work. The primary goal of this field is to reduce the probability of re-conspicuous of the delinquent driver. One of these measurements in Germany is IFT courses for DUI s. The IFT course was designed by the Institute for Therapy Research. Participants are drivers who have fallen several times or once with a blood alcohol concentration of 1.6 per mill and who have completed a medical-psychological assessment (MPU) with the result of the course recommendation. The course covers four sessions of 3.5 hours each (1 hour / 60 m) and in a period of 3 to 4 weeks in the group discussion. This work analyzes interventions for the rehabilitation of DUI (Drunk Drivers offenders) offenders in groups under the aspect of activating psychological resources. From the aspect of sustainability, they should also have long-term consequences for the maintenance of unproblematic driving behavior in terms of the activation of resources. It is also addressing a selected consistency-theory-based intervention effect, activating psychological resources. So far, this has only been considered in the psychotherapeutic field but never in the field of traffic psychology. The methodology of this survey is one qualitative and three quantitative. In four sub-studies, it will be examined which measurements can determine the resources and how traffic psychological interventions can strengthen resources. The results of the studies have the following implications for traffic psychology research and practice: (1) In the field of traffic psychology intervention for the restoration of driving fitness, it can be stated that aspects of resource activation in this work have been investigated for the first time by qualitative and quantitative methods. (2) The resource activation could be confirmed based on the determined results as an effective factor of traffic psychological intervention. (3) Two sub-studies show a range of resources and resource activation options that must be given greater emphasis in traffic psychology interventions: - Social resource activation - improvement of the life skills of participants - Reactivation of existing social support options - Re-experiencing self-esteem, self-assurance, and acceptance of traffic-related behaviors. (4) In revising the IFT-§70 course, as well as other courses on recreating aptitude for DUI, new traffic-specific resource-enabling interventions against alcohol abuse should be developed to further enhance the courses through motivational, cognitive, and behavioral effects of resource activation, Resource-activating interventions can not only be integrated into behavioral group interventions but can also be applied in psychodynamic, psychodynamic (individual psychological) and other contexts of individual traffic psychology. The results are indicative but clearly show that personal resources can be strengthened through traffic psychology interventions. In the research, practice, training, and further education of traffic psychology, the aspect of primary resource activation (Grawe, 1999), therefore, always deserves the greatest attention for the rehabilitation of DUIs and Traffic safety.

Keywords: traffic safety, psychological resources, activating of resources, intervention programs for alcohol offenders, empowerment

Procedia PDF Downloads 52

Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

Procedia PDF Downloads 102

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

Procedia PDF Downloads 146

Authors: Fong-Zuo Lee, Jihn-Sung Lai, Yung-Bin Lin, Xiaoqin Liu, Kuo-Chun Chang, Zhi-Xian Yang, Wen-Dar Guo, Jian-Hao Hong

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In recent years, climate change is a major factor to increase rainfall intensity and extreme rainfall frequency. The increased rainfall intensity and extreme rainfall frequency will increase the probability of flash flood with abundant sediment transport in a river basin. The floods caused by heavy rainfall may cause damages to the bridge, embankment, hydraulic works, and the other disasters. Therefore, the foundation scouring of bridge pier, embankment and spur dike caused by floods has been a severe problem in the worldwide. This severe problem has happened in many East Asian countries such as Taiwan and Japan because of these areas are suffered in typhoons, earthquakes, and flood events every year. Results from the complex interaction between fluid flow patterns caused by hydraulic works and the sediment transportation leading to the formation of river morphology, it is extremely difficult to develop a reliable and durable sensor to measure river bed degradation and bridge pier scouring. Therefore, an innovative scour monitoring sensor using vibration-based Micro-Electro Mechanical Systems (MEMS) was developed. This vibration-based MEMS sensor was packaged inside a stainless sphere with the proper protection of the full-filled resin, which can measure free vibration signals to detect scouring/deposition processes at the bridge pier. In addition, a friendly operational system includes rainfall runoff model, one-dimensional and two-dimensional numerical model, and the applicability of sediment transport equation and local scour formulas of bridge pier are included in this research. The friendly operational system carries out the simulation results of flood events that includes the elevation changes of river bed erosion near the specified bridge pier and the erosion depth around bridge piers. In addition, the system is developed with easy operation and integrated interface, the system can supplies users to calibrate and verify numerical model and display simulation results through the interface comparing to the scour monitoring sensors. To achieve the forecast of the erosion depth of river bed and main bridge pier in the study area, the system also connects the rainfall forecast data from Taiwan Typhoon and Flood Research Institute. The results can be provided available information for the management unit of river and bridge engineering in advance.

Keywords: flash flood, river bed degradation, bridge pier scouring, a friendly operational system

Procedia PDF Downloads 167

Authors: Shotiros Protong

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The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

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Authors: Sayyed Mostafa Ahmadi, Neda Raeesi

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Background and Objectives: Cervical spondylosis is a common problem that affects the adult spine and is the most common cause of radiculopathy and myelopathy in older patients. Anterior discectomy and fusion is a well-known technique in degenerative cervical disc disease. However, one of the late undesirable complications is adjacent disc degeneration, which affects about 91% of patients in ten years. Many factors can be effective in causing this complication, but some are still debatable. Discovering these risk factors and eliminating them can improve the quality of life. Methods: This is a retrospective cohort study. All patients who underwent anterior discectomy and fusion surgery in the neurosurgery ward of Imam Khomeini Hospital between 2013 and 2016 were evaluated. Their demographic information was collected. All patients were visited and examined for radiculopathy, myelopathy, and muscular force. At the same visit, all patients were asked to have a facelift, and neck profile, as well as a neck MRI(General Tesla 3). Preoperative graphs were used to measure the diameter of the cervical canal(Pavlov ratio) and to evaluate sagittal alignment(Cobb Angle). Preoperative MRI of patients was reviewed for anterior and posterior longitudinal ligament calcification. Result: In this study, 57 patients were studied. The mean age of patients was 50.63 years, and 49.1% were male. Only 3.5% of patients had anterior and posterior longitudinal ligament calcification. Symptomatic ASD was observed in 26.6%. The X-rays and MRIs showed evidence of 80.7% radiological ASD. Among patients who underwent one-level surgery, 20% had symptomatic ASD, but among patients who underwent two-level surgery, the rate of ASD was 50%.In other words, the higher the number of surfaces that are operated and fused, the higher the probability of symptomatic ASD(P-value <0.05). The X-rays and MRIs showed 80.7% of radiological ASD. Among patients who underwent surgery at one level, 78% had radiological ASD, and this number was 92% among patients who underwent two-level surgery(P-value> 0.05). Demographic variables such as age, sex, height, weight, and BMI did not have a significant effect on the incidence of radiological ASD(P-value> 0.05), but sex and height were two influential factors on symptomatic ASD(P-value <0.05). Other related variables such as family history, smoking and exercise also have no significant effect(P-value> 0.05). Radiographic variables such as Pavlov ratio and sagittal alignment were also unaffected by the incidence of radiological and symptomatic ASD(P-value> 0.05). The number of surgical surfaces and the incidence of anterior and posterior longitudinal ligament calcification before surgery also had no statistically significant effect(P-value> 0.05). In the study of the ability of the neck to move in different directions, none of these variables are statistically significant in the two groups with radiological and symptomatic ASD and the non-affected group(P-value> 0.05). Conclusion: According to the findings of this study, this disease is considered to be a multifactorial disease. The incidence of radiological ASD is much higher than symptomatic ASD (80.7% vs. 26.3%) and sex, height and number of fused surfaces are the only factors influencing the incidence of symptomatic ASD and no variable influences radiological ASD.

Keywords: risk factors, anterior neck disectomy and fusion, adjucent segment degeneration, complication

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Authors: Ivelise M. Strozberg, Lucas O. Vale, Maria V. V. Morais

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Expansive soils are characterized by their significant volumetric variations, tending to suffer an increase of this volume when added water in their voids and a decrease of volume when this water is removed. The parameters of resistance (especially the angle of friction, cohesion and specific weight) of expansive or non-expansive soils of the same field present differences, as found in laboratory tests. What is expected is that, through this research, demonstrate that this variation directly affects the results of the calculation of factors of safety for slope stability. The expansibility due to specific clay minerals such as montmorillonites and vermiculites is the most common form of expansion of soils or rocks, causing expansion pressures. These pressures can become an aggravating problem in regions across the globe that, when not previously studied, may present high risks to the enterprise, such as cracks, fissures, movements in structures, breaking of retaining walls, drilling of wells, among others. The study provides results based on analyzes carried out in the Slide 2018 software belonging to the Rocsience group, where the software is a two-dimensional equilibrium slope stability program that calculates the factor of safety or probability of failure of certain surfaces composed of soils or rocks (or both, depending on the situation), - through the methods of: Bishop simplified, Fellenius and Janbu corrected. This research compares the factors of safety of a homogeneous earthfill dam geometry, analysed for operation and end-of-construction situations, having a height of approximately 35 meters, with a slope of 1.5: 1 in the slope downstream and 2: 1 on the upstream slope. As the water level is 32.73m high and the water table is drawn automatically by the Slide program using the finite element method for the operating situation, considering two hypotheses for the use of materials - the first with soils with characteristics of expansion and the second with soils without expansibility. For this purpose, soil samples were collected from the region of São Bento do Una - Pernambuco, Brazil and taken to the soil mechanics laboratory to characterize and determine the percentage of expansibility. There were found 2 types of soils in that area: 1 site of expansive soils (8%) and another with non- expansive ones. Based on the results found, the analysis of the values of factors of safety indicated, both upstream and downstream slopes, the highest values were obtained in the case where there is no presence of materials with expansibility resulting, for one of the situations, values of 1.353 (Fellenius), 1,295 (Janbu corrected) and 1,409 (Bishop simplified). There is a considerable drop in safety factors in cases where soils are potentially expansive, resulting in values for the same situation of 0.859 (Fellenius), 0.809 (Janbu corrected) and 0.842 (Bishop simplified), in the case of higher expansibility (8 %). This shows that the expansibility is a determinant factor in the fall of resistance of soil, determined by the factors of cohesion and angle of friction.

Keywords: dam. slope. software. swelling soil

Procedia PDF Downloads 93

Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Students’ emotional experiences have been a widely discussed theme among researchers, proving a central role on students’ outcomes. Yet, up to now, far too little attention has been paid to teaching practices that negatively relate with students’ negative emotions in the higher education. The present work aims to examine the relationship between teachers’ teaching practices (i.e., students’ evaluations of teaching and autonomy support), the students’ feelings of boredom and agentic engagement and motivation in the higher education context. To do so, the present study incorporates one of the most popular tools in natural processing language to address students’ evaluations of teaching: sentiment analysis. Whereas most research has focused on the creation of SA models and assessing students’ satisfaction regarding teachers and courses to the author’s best knowledge, no research before has included results from SA into an explanatory model. A total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) participated in the study. Students were enrolled in degree and masters’ studies at the faculty of Education of a public university of Spain. Data was collected using an online questionnaire students could access through a QR code they completed during a teaching period where the assessed teacher was not present. To assess students’ sentiments towards their teachers’ teaching, we asked them the following open-ended question: “If you had to explain a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?”. Sentiment analysis was performed with Microsoft's pre-trained model. For this study, we relied on the probability of the students answer belonging to the negative category. To assess the reliability of the measure, inter-rater agreement between this NLP tool and one of the researchers, who independently coded all answers, was examined. The average pairwise percent agreement and the Cohen’s kappa were calculated with ReCal2. The agreement reached was of 90.8% and Cohen’s kappa .68, both considered satisfactory. To test the hypothesis relations a structural equation model (SEM) was estimated. Results showed that the model fit indices displayed a good fit to the data; χ² (134) = 351.129, p < .001, RMSEA = .07, SRMR = .09, TLI = .91, CFI = .92. Specifically, results show that boredom was negatively predicted by autonomy support practices (β = -.47[-.61, -.33]), whereas for the negative sentiment extracted from SET, this relation was positive (β = .23[.16, .30]). In other words, when students’ opinion towards their instructors’ teaching practices was negative, it was more likely for them to feel bored. Regarding the relations among boredom and student outcomes, results showed a negative predictive value of boredom on students’ motivation to study (β = -.46[-.63, -.29]) and agentic engagement (β = -.24[-.33, -.15]). Altogether, results show a promising future for sentiment analysis techniques in the field of education as they proved the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, boredom, motivation, agentic engagement

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Authors: Ye Zhang, Chuanjun Liu

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In-service aircraft is exposed to different types of threaten, e.g. bird strike, ground vehicle impact, and run-way debris, or even lightning strike, etc. To satisfy the aircraft damage tolerance design requirements, the designer has to understand the threatening level for different types of the aircraft structures, either metallic or composite. Exposing to low-velocity impacts may produce very serious internal damages such as delaminations and matrix cracks without leaving visible mark onto the impacted surfaces for composite structures. This internal damage can cause significant reduction in the load carrying capacity of structures. The semi-probabilistic method provides a practical and proper approximation to establish the impact-threat based energy cut-off level for the damage tolerance evaluation of the aircraft components. Thus, the probabilistic distribution of impact threat and the realistic impact energy level cut-offs are the essential establishments required for the certification of aircraft composite structures. A new survey of impact threat to civil aircraft in-service has recently been carried out based on field records concerning around 500 civil aircrafts (mainly single aisles) and more than 4.8 million flight hours. In total 1,006 damages caused by low-velocity impact events had been screened out from more than 8,000 records including impact dents, scratches, corrosions, delaminations, cracks etc. The impact threat dependency on the location of the aircraft structures and structural configuration was analyzed. Although the survey was mainly focusing on the metallic structures, the resulting low-energy impact data are believed likely representative to general civil aircraft, since the service environments and the maintenance operations are independent of the materials of the structures. The probability of impact damage occurrence (Po) and impact energy exceedance (Pe) are the two key parameters for describing the statistic distribution of impact threat. With the impact damage events from the survey, Po can be estimated as 2.1x10-4 per flight hour. Concerning the calculation of Pe, a numerical model was developed using the commercial FEA software ABAQUS to backward estimate the impact energy based on the visible damage characteristics. The relationship between the visible dent depth and impact energy was established and validated by drop-weight impact experiments. Based on survey results, Pe was calculated and assumed having a log-linear relationship versus the impact energy. As the product of two aforementioned probabilities, Po and Pe, it is reasonable and conservative to assume Pa=PoxPe=10-5, which indicates that the low-velocity impact events are similarly likely as the Limit Load events. Combing Pa with two probabilities Po and Pe obtained based on the field survey, the cutoff level of realistic impact energy was estimated and valued as 34 J. In summary, a new survey was recently done on field records of civil aircraft to investigate the probabilistic distribution of impact threat. Based on the data, two probabilities, Po and Pe, were obtained. Considering a conservative assumption of Pa, the cutoff energy level for the realistic impact energy has been determined, which provides potential applicability in damage tolerance certification of future civil aircraft.

Keywords: composite structure, damage tolerance, impact threat, probabilistic

Procedia PDF Downloads 284

Authors: Bailey Houghtaling, Elena Serrano, Vivica Kraak, Samantha Harden, George Davis, Sarah Misyak

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United States (U.S.) Department of Agriculture Supplemental Nutrition Assistance Program (SNAP) participants are low-income Americans receiving federal dollars for supplemental food and beverage purchases. Participants use a variety of (traditional/non-traditional) SNAP-authorized stores for household dietary purchases - also representing food access points for all Americans. Importantly consumers' food and beverage purchases from non-traditional store formats tend to be higher in saturated fats, added sugars, and sodium when compared to purchases from traditional (e.g., grocery/supermarket) formats. Overconsumption of energy-dense and low-nutrient food and beverage products contribute to high obesity rates and adverse health outcomes that differ in severity among urban/rural U.S. locations and high/low-income populations. Little is known about the SNAP-authorized food store format landscape nationally, regionally, or by urban-rural status, as traditional formats are currently used as the gold standard in food access research. This research utilized publicly available U.S. databases to fill this large literature gap and to provide insight into modes of food access for vulnerable U.S. populations: (1) SNAP Retailer Locator which provides a list of all authorized food stores in the U.S., and; (2) Rural-Urban Continuum Codes (RUCC) that categorize U.S. counties as urban (RUCC 1-3) or rural (RUCC 4-9). Frequencies were determined for the highest occurring food store formats nationally and within two regionally diverse U.S. states – Virginia in the east and California in the west. Store format codes were assigned (e.g., grocery, drug, convenience, mass merchandiser, supercenter, dollar, club, or other). RUCC was applied to investigate state-level differences in urbanity-rurality regarding prevalent food store formats and Chi Square test of independence was used to determine if food store format distributions significantly (p < 0.05) differed by region or rurality. The resulting research sample that represented highly prevalent SNAP-authorized food stores nationally included 41.25% of all SNAP stores in the U.S. (N=257,839), comprised primarily of convenience formats (31.94%) followed by dollar (25.58%), drug (19.24%), traditional (10.87%), supercenter (6.85%), mass merchandiser (1.62%), non-food store or restaurant (1.81%), and club formats (1.09%). Results also indicated that the distribution of prevalent SNAP-authorized formats significantly differed by state. California had a lower proportion of traditional (9.96%) and a higher proportion of drug (28.92%) formats than Virginia- 11.55% and 19.97%, respectively (p < 0.001). Virginia also had a higher proportion of dollar formats (26.11%) when compared to California (10.64%) (p < 0.001). Significant differences were also observed for rurality variables (p < 0.001). Prominently, rural Virginia had a significantly higher proportion of dollar formats (41.71%) when compared to urban Virginia (21.78%) and rural California (21.21%). Non-traditional SNAP-authorized formats are highly prevalent and significantly differ in distribution by U.S. region and rurality. The largest proportional difference was observed for dollar formats where the least nutritious consumer purchases are documented in the literature. Researchers/practitioners should investigate non-traditional food stores at the local level using these research findings and similar applied methodologies to determine how access to various store formats impact obesity prevalence. For example, dollar stores may be prime targets for interventions to enhance nutritious consumer purchases in rural Virginia while targeting drug formats in California may be more appropriate.

Keywords: food access, food store format, nutrition interventions, SNAP consumers

Procedia PDF Downloads 112

Authors: Danny Barash

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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

Procedia PDF Downloads 210

Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

Procedia PDF Downloads 258

Authors: Muhammad Younas, Sidra Sawati, M. Razzaq Athar

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Organizational development history reveals that it has ever been a challenge to identify and fathom the role of talent management, career development and compensation management towards employees’ retention and organizational performance. Organizations strive hard to measure the impact of all those factors which affect employee retention and organizational performance. Researchers have worked in great deal in order to know the relationship of independent variables i.e. Talent Management, Career Development and Compensation Management on dependent variables i.e. Employee Retention and Organizational Performance. Employees adorned with latest skills with long lasting loyalty play a significant role towards successful achievement of short term as well as long term goals of the organizations. Retention of valuable and resourceful employees for a longer time is equally essential for meeting the set goals. The organizations which spend reasonable chunk of their resources for taking such measures that help to retain their employees through talent management and satisfactory career development always enjoy a competitive edge over their competitors. Human resource is regarded as one of the most precious and difficult resource to management. It has its own needs and requirement. It becomes an easy prey to monotony when lacks career development. Wants and aspirations of this resource are seldom met completely but can be managed through career development and compensation management. In this era of competition, organizations have to take viable steps to management their resources especially human resource. Top management and Managers keep on working for an amenable solution in order to address the challenges relating career development and compensation management as their ultimate goal is to ensure the organizational performance on optimum level. The current study was conducted to examine the impact of Talent Management, Career Development and Compensation Management towards Employees Retention and Organizational Performance with mediating effect of Employees Motivation in Service Sector of Pakistan. The current study is based on Resource Based View (RBV) and Ability Motivation Opportunity (AMO) theories. It explains that by increasing internal resources we can manage employee talent, career development through compensation management and employee motivation more effectively. It will result in effective execution of HRM practices for employee retention enabling an organization to achieve and sustain competitive advantage through optimal performance. Data collection was made through a structured questionnaire which was based upon adopted instruments after testing reliability and validity. A total 300 employees of 30 firms in service sector of Pakistan were sampled through non-probability sampling technique. Regression analysis revealed that talent management, career development and compensation management have significant positive impact on employee retention and perceived organizational performance. The results further showed that employee motivation have a significant mediating effect on employee retention and organizational performance. The interpretation of the findings and limitations, theoretical and managerial implications are also discussed.

Keywords: career development, compensation management, employee retention, organizational performance, talent management

Procedia PDF Downloads 292

Authors: Jeremie Coullon, Robert J. Webber

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We introduce a Markov chain Monte Carlo (MCMC) sam-pler for infinite-dimensional inverse problems. Our sam-pler is based on the affine invariant ensemble sampler, which uses interacting walkers to adapt to the covariance structure of the target distribution. We extend this ensem-ble sampler for the first time to infinite-dimensional func-tion spaces, yielding a highly efficient gradient-free MCMC algorithm. Because our ensemble sampler does not require gradients or posterior covariance estimates, it is simple to implement and broadly applicable. In many Bayes-ian inverse problems, Markov chain Monte Carlo (MCMC) meth-ods are needed to approximate distributions on infinite-dimensional function spaces, for example, in groundwater flow, medical imaging, and traffic flow. Yet designing efficient MCMC methods for function spaces has proved challenging. Recent gradi-ent-based MCMC methods preconditioned MCMC methods, and SMC methods have improved the computational efficiency of functional random walk. However, these samplers require gradi-ents or posterior covariance estimates that may be challenging to obtain. Calculating gradients is difficult or impossible in many high-dimensional inverse problems involving a numerical integra-tor with a black-box code base. Additionally, accurately estimating posterior covariances can require a lengthy pilot run or adaptation period. These concerns raise the question: is there a functional sampler that outperforms functional random walk without requir-ing gradients or posterior covariance estimates? To address this question, we consider a gradient-free sampler that avoids explicit covariance estimation yet adapts naturally to the covariance struc-ture of the sampled distribution. This sampler works by consider-ing an ensemble of walkers and interpolating and extrapolating between walkers to make a proposal. This is called the affine in-variant ensemble sampler (AIES), which is easy to tune, easy to parallelize, and efficient at sampling spaces of moderate dimen-sionality (less than 20). The main contribution of this work is to propose a functional ensemble sampler (FES) that combines func-tional random walk and AIES. To apply this sampler, we first cal-culate the Karhunen–Loeve (KL) expansion for the Bayesian prior distribution, assumed to be Gaussian and trace-class. Then, we use AIES to sample the posterior distribution on the low-wavenumber KL components and use the functional random walk to sample the posterior distribution on the high-wavenumber KL components. Alternating between AIES and functional random walk updates, we obtain our functional ensemble sampler that is efficient and easy to use without requiring detailed knowledge of the target dis-tribution. In past work, several authors have proposed splitting the Bayesian posterior into low-wavenumber and high-wavenumber components and then applying enhanced sampling to the low-wavenumber components. Yet compared to these other samplers, FES is unique in its simplicity and broad applicability. FES does not require any derivatives, and the need for derivative-free sam-plers has previously been emphasized. FES also eliminates the requirement for posterior covariance estimates. Lastly, FES is more efficient than other gradient-free samplers in our tests. In two nu-merical examples, we apply FES to challenging inverse problems that involve estimating a functional parameter and one or more scalar parameters. We compare the performance of functional random walk, FES, and an alternative derivative-free sampler that explicitly estimates the posterior covariance matrix. We conclude that FES is the fastest available gradient-free sampler for these challenging and multimodal test problems.

Keywords: Bayesian inverse problems, Markov chain Monte Carlo, infinite-dimensional inverse problems, dimensionality reduction

Procedia PDF Downloads 129

Authors: Lee Yan Nian

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Safety investigation is different from an administrative investigation in that the former is conducted by an independent agency and the purpose of such investigation is to prevent accidents in the future and not to apportion blame or determine liability. Before October 2018, Taiwan railway occurrences were investigated by local supervisory authority. Characteristics of this kind of investigation are that enforcement actions, such as administrative penalty, are usually imposed on those persons or units involved in occurrence. On October 21, 2018, due to a Taiwan Railway accident, which caused 18 fatalities and injured another 267, establishing an agency to independently investigate this catastrophic railway accident was quickly decided. The Taiwan Transportation Safety Board (TTSB) was then established on August 1, 2019 to take charge of investigating major aviation, marine, railway and highway occurrences. The objective of this study is to assess the effectiveness of safety investigations conducted by the TTSB. In this study, the major railway occurrence investigation reports published by the TTSB are used for modeling and analysis. According to the classification of railway occurrences investigated by the TTSB, accident types of Taiwan railway occurrences can be categorized into: derailment, fire, Signal Passed at Danger and others. A Causal Factor Analysis System (CFAS) developed by the TTSB is used to identify the influencing causal factors and their causal relationships in the investigation reports. All terminologies used in the CFAS are equivalent to the Human Factors Analysis and Classification System (HFACS) terminologies, except for “Technical Events” which was added to classify causal factors resulting from mechanical failure. Accordingly, the Bayesian network structure of each occurrence category is established based on the identified causal factors in the CFAS. In the Bayesian networks, the prior probabilities of identified causal factors are obtained from the number of times in the investigation reports. Conditional Probability Table of each parent node is determined from domain experts’ experience and judgement. The resulting networks are quantitatively assessed under different scenarios to evaluate their forward predictions and backward diagnostic capabilities. Finally, the established Bayesian network of derailment is assessed using investigation reports of the same accident which was investigated by the TTSB and the local supervisory authority respectively. Based on the assessment results, findings of the administrative investigation is more closely tied to errors of front line personnel than to organizational related factors. Safety investigation can identify not only unsafe acts of individual but also in-depth causal factors of organizational influences. The results show that the proposed methodology can identify differences between safety investigation and administrative investigation. Therefore, effective intervention strategies in associated areas can be better addressed for safety improvement and future accident prevention through safety investigation.

Keywords: administrative investigation, bayesian network, causal factor analysis system, safety investigation

Procedia PDF Downloads 90

Authors: Maria Evnevich

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In modern conditions, in most markets, price competition is becoming less effective. On the one hand, there is a gradual decrease in the level of marginality in main traditional sectors of the economy, so further price reduction becomes too ‘expensive’ for the company. On the other hand, the effect of price reduction is leveled, and the reason for this phenomenon is likely to be informational. As a result, it turns out that even if the company reduces prices, making its products more accessible to the buyer, there is a high probability that this will not lead to increase in sales unless additional large-scale advertising and information campaigns are conducted. Similarly, a large-scale information and advertising campaign have a much greater effect itself than price reductions. At the same time, the cost of mass informing is growing every year, especially when using the main information channels. The article presents generalization, systematization and development of theoretical approaches and best practices in the field of customer focus approach to business management and in the field of relationship marketing in the modern digital economy. The research methodology is based on the synthesis and content-analysis of sociological and marketing research and on the study of the systems of working with consumer appeals and loyalty programs in the 50 largest client-oriented companies in Russia. Also, the analysis of internal documentation on customers’ purchases in one of the largest retail companies in Russia allowed to identify if buyers prefer to buy goods for complex purchases in one retail store with the best price image for them. The cost of attracting a new client is now quite high and continues to grow, so it becomes more important to keep him and increase the involvement through marketing tools. A huge role is played by modern digital technologies used both in advertising (e-mailing, SEO, contextual advertising, banner advertising, SMM, etc.) and in service. To implement the above-described client-oriented omnichannel service, it is necessary to identify the client and work with personal data provided when filling in the loyalty program application form. The analysis of loyalty programs of 50 companies identified the following types of cards: discount cards, bonus cards, mixed cards, coalition loyalty cards, bank loyalty programs, aviation loyalty programs, hybrid loyalty cards, situational loyalty cards. The use of loyalty cards allows not only to stimulate the customer to purchase ‘untargeted’, but also to provide individualized offers, as well as to produce more targeted information. The development of digital technologies and modern means of communication has significantly changed not only the sphere of marketing and promotion, but also the economic landscape as a whole. Factors of competitiveness are the digital opportunities of companies in the field of customer orientation: personalization of service, customization of advertising offers, optimization of marketing activity and improvement of logistics.

Keywords: customer focus, digital economy, loyalty program, relationship marketing

Procedia PDF Downloads 141

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

Procedia PDF Downloads 124

Authors: K. M. S. Weerasinghe, A. H. K. Balasooriya, S. L. Ransingha, G. D. Krishantha, R. S. Brhakamanagae, L. C. Wijethilke

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Tomato (Lycopersicon esculentum Mill.) is a major horticultural crop with an estimated global production of over 120 million metric tons and ranks first as a processing crop. The average tomato productivity in Sri Lanka (11 metric tons/ha) is much lower than the world average (24 metric tons/ha).To meet the tomato demand for the increasing population the productivity has to be intensified through the agronomic-techniques. Nutrition is one of the main factors which govern the growth and yield of tomato and the main nutrient source soil affect the plant growth and quality of the produce. Continuous cropping, improper fertilizer usage etc., cause widespread nutrient deficiencies. Therefore synthetic fertilizers and organic manures were introduced to enhance plant growth and maximize the crop yields. In this study, effects of macro and micronutrient supplementations on improvement of growth and yield of tomato were investigated. Selected tomato variety is Maheshi and plants were grown in Regional Agricultural and Research Centre Makadura under the Department of Agriculture recommended (DOA) macro nutrients and various combination of Ontario recommended dosages of secondary and micro fertilizer supplementations. There were six treatments in this experiment and each treatment was replicated in three times and each replicate consisted of six plants. Other than the DOA recommendation, five combinations of Ontario recommended dosage of secondary and micronutrients for tomato were also used as treatments. The treatments were arranged in a Randomized Complete Block Design. All cultural practices were carried out according to the DOA recommendations. The mean data was subjected to the statistical analysis using SAS package and mean separation (Duncan’s Multiple Range test at 5% probability level) procedures. Secondary and micronutrients containing treatments significantly increased most of the growth parameters. Plant height, plant girth, number of leaves, leaf area index etc. Fruits harvested from pots amended with macro, secondary and micronutrients performed best in terms of total yield; yield quality; to pots amended with DOA recommended dosage of fertilizer for tomato. It could be due to the application of all essential macro and micro nutrients that rise in photosynthetic activity, efficient translocation and utilization of photosynthates causing rapid cell elongation and cell division in actively growing region of the plant leading to stimulation of growth and yield were caused. The experiment revealed and highlighted the requirements of essential macro, secondary and micro nutrient fertilizer supplementations for tomato farming. The study indicated that, macro and micro nutrient supplementation practices can influence growth and yield performances of tomato fruits and it is a promising approach to get potential tomato yields.

Keywords: macro and micronutrients, tomato, SAS package, photosynthates

Procedia PDF Downloads 424

Authors: Ružica Tomičić, Zorica Tomičić, Peter Raspor

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An abundant growth of unwanted yeasts in food processing plants can lead to problems in quality and safety with significant financial losses. Candida and Pichia are the genera mainly involved in spoilage of products in the food and beverage industry. These contaminating microorganisms can form biofilms on food contact surfaces, being difficult to eradicate, increasing the probability of microbial survival and further dissemination during food processing. It is well known that biofilms are more resistant to antimicrobial agents compared to planktonic cells and this makes them difficult to eliminate. Among the strategies used to overcome resistance to antifungal drugs and preservatives, the use of natural substances such as plant extracts has shown particular promise, and many natural substances have been found to exhibit antifungal properties. This study aimed to investigated the impact of growth medium (Malt Extract broth (MEB) or Yeast Peptone Dextrose (YPD) broth) and temperatures (7°C, 37°C, 43°C for Candida strains and 7°C, 27°C, 32°C for Pichia strains) on the adhesion of Candida spp. and Pichia spp. to stainless steel (AISI 304) discs with different degrees of surface roughness (Ra = 25.20 – 961.9 nm), a material commonly used in the food industry. We also evaluated the antifungal and antiadhesion activity of plant extracts such as Humulus lupulus, Alpinia katsumadai and Evodia rutaecarpa against C. albicans, C glabrata and P. membranifaciens and investigated whether these plant extracts can interfere with biofilm formation. The adhesion was assessed by the crystal violet staining method, while the broth microdilution method CLSI M27-A3 was used to determine the minimum inhibitory concentration (MIC) of plant extracts. Our results indicated that the nutrient content of the medium significantly influenced the amount of adhered cells of the tested yeasts. The growth medium which resulted in a higher adhesion of C. albicans and C. glabrata was MEB, while for C. parapsilosis and C. krusei was YPD. In the case of P. pijperi and P. membranifaciens, YPD broth was more effective in promoting adhesion than MEB. Regarding the effect of temperature, C. albicans strain adhered to stainless steel surfaces in significantly higher level at a temperature of 43°C, while on the other hand C. glabrata, C. parapsilosis and C. krusei showed a different behavior with significantly higher adhesion at 37°C than at 7°C and 43°C. Further, the adherence ability of Pichia strains was highest at 27°C. Based on the MIC values, all plant extracts exerted significant antifungal effects with MIC values ranged from 100 to 400 μg/mL. It was observed that biofilm of C. glabrata were more resistance to plant extracts as compared to C. albicans. However, extracts of A. katsumadai and E. rutaecarpa promoted the growth and development of the preformed biofilm of P. membranifaciens. Thus, the knowledge of how these microorganisms adhere and which factors affect this phenomenon is of great importance in order to avoid their colonization on food contact surfaces.

Keywords: adhesion, Candida spp., Pichia spp., plant extracts

Procedia PDF Downloads 176

Authors: Obinna Benedict Duru

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This study focuses on the elderly and the challenges that confront them. The elderly are that particular segment of our population who by virtue of the aging process have attained the stage in most cases where they are confronted with the challenges of economic dependency and social marginality. These challenges are as a result of the physical and biological decline occasioned by social myths and realities which portray the elderly as a dependent population whose members could not and should not work and who need social assistance that the younger population is obliged to provide. From the moment of birth to the moment of death, our bodies are constantly changing. We are all enmeshed in the process of growing old, a transition from youthfulness to elderliness. In youth-oriented modern societies like ours, we tend to attach positive importance and significance to the biological changes that occur early in life and define later physical changes in negative terms. Children growing up and young adults receive more attention, greater responsibilities and more legal rights to reward them on their way. But few people are congratulated on getting old. We commiserate with people who are getting old and make jokes about their supposedly physical, mental and biological decline. Wrinkles, loss of weight and vitality are all parts of the aging process. In almost all parts of the world, earlier researches have shown that about fifty percent of the elderly who suffer from stroke, arthritis, senility and other age related diseases are the disengaged and neglected elderly. Rapid technological changes render the knowledge and skills of the elderly obsolete; education is geared toward the young and the generational competition for jobs leads to pressures on the elderly to retire. Control of initial resources are shifted to the middle-aged and older workers are pushed into positions of economic dependency. This study therefore, among other things tend to discover how some government policies have affected the elderly particularly in Africa. To discover the prospects and possibilities of the elderly for a better living. To make a comparison of the advances in healthcare giving made in the advanced western societies to the practice in Sub Saharan Africa etc. The hypotheses of this study include: that the elderly in Sub Saharan Africa are more vulnerable than their counterparts in Europe and America. The elderly are more prone to social isolation, and that the elderly are mostly affected by age-related sickness etc. With a survey method as the research design, and sample size of about 500 respondents,probability sampling technique was used. Data which were analyzed using chi-square and tables were collected through primary and secondary sources. The findings made include: that the elderly suffer pains of old age especially when disengaged from work or social activity. That loss of income condemn the elderly to a life of vegetable existence, and that those who do not have other means of re-integration usually see old age with regret and despair. It is therefore, recommended among other things that social welfare scheme and the process of re-integration at old age be introduced for the non pensionable elderly in Africa.

Keywords: elderly, social isolation, dependency, re-integration

Procedia PDF Downloads 306

Authors: A. T. Al-Isawi, P. E. F. Collins

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The behaviour of structures exposed to fire after an earthquake is not a new area of engineering research, but there remain a number of areas where further work is required. Such areas relate to the way in which seismic excitation is applied to a structure, taking into account the effect of soil-structure interaction (SSI) and the method of analysis, in addition to identifying the excitation load properties. The selection of earthquake data input for use in nonlinear analysis and the method of analysis are still challenging issues. Thus, realistic artificial ground motion input data must be developed to certify that site properties parameters adequately describe the effects of the nonlinear inelastic behaviour of the system and that the characteristics of these parameters are coherent with the characteristics of the target parameters. Conversely, ignoring the significance of some attributes, such as frequency content, soil site properties and earthquake parameters may lead to misleading results, due to the misinterpretation of required input data and the incorrect synthesise of analysis hypothesis. This paper presents a study of the post-earthquake fire (PEF) performance of a multi-storey steel-framed building resting on soft clay, taking into account the effects of the nonlinear inelastic behaviour of the structure and soil, and the soil-structure interaction (SSI). Structures subjected to an earthquake may experience various levels of damage; the geometrical damage, which indicates the change in the initial structure’s geometry due to the residual deformation as a result of plastic behaviour, and the mechanical damage which identifies the degradation of the mechanical properties of the structural elements involved in the plastic range of deformation. Consequently, the structure presumably experiences partial structural damage but is then exposed to fire under its new residual material properties, which may result in building failure caused by a decrease in fire resistance. This scenario would be more complicated if SSI was also considered. Indeed, most earthquake design codes ignore the probability of PEF as well as the effect that SSI has on the behaviour of structures, in order to simplify the analysis procedure. Therefore, the design of structures based on existing codes which neglect the importance of PEF and SSI can create a significant risk of structural failure. In order to examine the criteria for the behaviour of a structure under PEF conditions, a two-dimensional nonlinear elasto-plastic model is developed using ABAQUS software; the effects of SSI are included. Both geometrical and mechanical damages have been taken into account after the earthquake analysis step. For comparison, an identical model is also created, which does not include the effects of soil-structure interaction. It is shown that damage to structural elements is underestimated if SSI is not included in the analysis, and the maximum percentage reduction in fire resistance is detected in the case when SSI is included in the scenario. The results are validated using the literature.

Keywords: Abaqus Software, Finite Element Analysis, post-earthquake fire, seismic analysis, soil-structure interaction

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Authors: Adu-Ampomah Yaw Junior

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Local procurement has become one of the latest trends in the discourse of sustainable tourism due to the economic benefits it generates for tourist destinations in developing countries. Local procurement helps in creating jobs which consequently helps in alleviating poverty. However, there have been limited studies on local procurement patterns in developing countries. Research on hotel procurement practices has mainly emphasized the challenges that hoteliers face when procuring locally, leaving questions regarding their motivations to engage in local procurement unanswered. The institutional theory provides a suitable framework to better understand these motivations as it underlines the importance of individual cognitive perceptions on issues in shaping organizational response strategies. More specifically, the extent to which an issue is perceived to belong to the organization’s responsibility. Also the organizational actors’ belief of losses or gains resultant from acting or not acting on an issue (degree of importance). Furthermore the organizational actors’ belief of the probability of resolving an issue (degree of feasibility). These factors influence how an organization will act on this issue. Hence, this paper adopts an institutional perspective to examine local procurement patterns of food by hoteliers in Ghana. Qualitative interviews with 20 procurement managers about their procurement practices and motivations, as well as interviews with different stakeholders for data triangulation purposes, indicated that most hotels sourced their food from middlemen who imported most of their products. However, direct importation was more prevalent foreign owned hotels as opposed to locally owned ones. Notwithstanding, the importation and the usage of foreign foods as opposed to local ones can be explained by the lack of pressure from NGOs and trade associations on hotels to act responsibly. Though guests’ menu preferences were perceived as important to hoteliers business operations, western tourists demand foreign food primarily with the foreign owned hotels make it less important to procure local produce. Lastly hoteliers, particularly those in foreign owned ones, perceive local procurement to be less feasible, raising concerns about quality and variety of local produce. The paper outlines strategies to improve the perception and degree of local Firstly, there is the need for stakeholder engagement in order to make hoteliers feel responsible for acting on the issue.Again it is crucial for Ghana government to promote and encourage hotels to buy local produce. Also, the government has to also make funds and storage facilities available for farmers to impact on the quality and quantity of local produce. Moreover, Sites need to be secured for farmers to engage in sustained farming.Furthermore, there is the need for collaborations between various stakeholders to organize training programs for farmers. Notwithstanding hotels need to market local produce to their guests. Finally, the Ghana hotels association has to encourage hotels to indulge in local procurement.

Keywords: sustainable tourism, feasible, important, local procurement

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, Sevan Komshian, Ruby Wang, Jun Tang

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Background: Monitoring the anti-nociceptive drug effect is useful because a sudden and strong nociceptive stimulus may result in untoward autonomic responses and muscular reflex movements. Monitoring the anti-nociceptive effects of perioperative medications has long been desiredas a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively.To this end, electroencephalogram (EEG) based tools includingBIS and qCON were designed to provide information about the depth of sedation whileqNOXwas produced to informon the degree of antinociception.The goal of this study was to compare the reliability of qCON/qNOX to BIS asspecific indicators of response to nociceptive stimulation. Methods: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board(IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed o62n all patientsprior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. Results: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from74±13 mm Hg at baseline to 84± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76±12 BPM at baseline to 80±13BPM during noxious stimuli[p=0.078] respectively). Conclusion: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices.

Keywords: antinociception, bispectral index (BIS), general anesthesia, laryngeal mask airway, qCON/qNOX

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Authors: Linyi Fan, C.J. Schumaker

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Background: Biomedical efforts to treat Alzheimer’s disease (AD) have typically produced mixed to poor results, while more lifestyle-focused treatments such as exercise may fare better than existing biomedical treatments. A few promising studies have indicated that activities of daily life (ADL) may be a useful way of predicting AD. However, the existing cross-sectional studies fail to show how functional-related issues such as ADL in early years predict AD and how social factors influence health either in addition to or in interaction with individual risk factors. This study would helpbetterscreening and early treatments for the elderly population and healthcare practice. The findings have significance academically and practically in terms of creating positive social change. Methodology: The purpose of this quantitative historical, correlational study was to examine the relationship between early years’ ADL and the development of AD in later years. The studyincluded 4,526participantsderived fromRAND HRS dataset. The Health and Retirement Study (HRS) is a longitudinal household survey data set that is available forresearchof retirement and health among the elderly in the United States. The sample was selected by the completion of survey questionnaire about AD and dementia. The variablethat indicates whether the participant has been diagnosed with AD was the dependent variable. The ADL indices and changes in ADL were the independent variables. A four-step multilevel regression model approach was utilized to address the research questions. Results: Amongst 4,526 patients who completed the AD and dementia questionnaire, 144 (3.1%) were diagnosed with AD. Of the 4,526 participants, 3,465 (76.6%) have high school and upper education degrees,4,074 (90.0%) were above poverty threshold. The model evaluatedthe effect of ADL and change in ADL on onset of AD in late years while allowing the intercept of the model to vary by level of education. The results suggested that the only significant predictor of the onset of AD was changes in early years’ ADL (b = 20.253, z = 2.761, p < .05). However, the result of the sensitivity analysis (b = 7.562, z = 1.900, p =.058), which included more control variables and increased the observation period of ADL, are not supported this finding. The model also estimated whether the variances of random effect vary by Level-2 variables. The results suggested that the variances associated with random slopes were approximately zero, suggesting that the relationship between early years’ ADL were not influenced bysociodemographic factors. Conclusion: The finding indicated that an increase in changes in ADL leads to an increase in the probability of onset AD in the future. However, this finding is not support in a broad observation period model. The study also failed to reject the hypothesis that the sociodemographic factors explained significant amounts of variance in random effect. Recommendations were then made for future research and practice based on these limitations and the significance of the findings.

Keywords: alzheimer’s disease, epidemiology, moderation, multilevel modeling

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Authors: Etienne Gatera

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Many studies have been conducted on SDT. Most of them focus on developed countries because of influencing factors such as; education, health, labor force, female labor force participation, industrialization, urbanization and migration. However, this thesis project paper aims to assess the impact of the total fertility rate (TFR) on the trends of the SDR in Rwanda. We will mainly be based in Rwanda after the 1994 genocide. Rwanda is located in East Africa, with approximately 13 million inhabitants. Thus, after the 1994 Tutsi genocide. The population growth rate exploded out of control with 6.17 children per woman in 1995. However, it's declined to 4.2 in 2014-2015 and declining to 4.1% in 2019-2020. Respectively with 3.4 children per woman in urban areas and 4.3 in rural areas. According to the National Institute of Statistics of Rwanda. Rwanda's population is expected to continue to grow for the rest of the century and reach 33.35 million people in 2099, with 2.1 children per woman in 2050. However, this project document aims to demonstrate the impact of the TFR on SDT trends in Rwanda. Thus, the decline in the TFR in Rwanda began with the introduction of family planning practices, which now account for 47.5% in 2019. Childbearing with three children for rural women compared to two children in the city, the increase in Divorce and separation caused by the behavior called "Kuza n'ijoro" or "coming at night" similar to cohabitation in developed countries. The decline in remarriage is caused by single mothers behavior who prefer to raise their children rather than remarry. Therefore, the study used probability sampling with (Stratified random sampling) method with a survey questionnaire of 1067 respondents in the 5 Districts (3 in rural areas and two in urban areas), with the target group of women Age between 15-49. The study demonstrated that the age of marriage in rural areas is two years higher than in urban areas. Divorce is more common in urban is with 6.2% with 5.2% in rural areas. However, separation is more common in rural areas than in urban areas, with a lower rate of 3%, due to the higher system called "Kuza n'ijoro" or "come at night", similar to cohabitation in developed countries. The study revealed that more than 85% of divorced people prefer to remain single, which confirms the low remarriage rate. Childbearing has started to decrease, especially for young singles in urban areas, due to the economic situation, with national statistics showing that unemployment in the youth community is still 16% higher. Therefore, the study concluded by confirming the hypothesis based on the results of the TFR indicators such as marriage, remarriage, divorce, separation, divorce, Kuza n'ijoro, childbearing] and abortion. The study consists of four sections, an introduction and background, a review of the literature, a description of the data and methodology, an analysis of the data, discussion results and a conclusion.

Keywords: Kuza n'ijoro, Rwanda, second demographic transition (SDT), total fertility rate (TFR)

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Authors: Caroline M. B. De Araujo, Helenise A. Do Nascimento, Claudia J. Da S. Cavalcanti, Mauricio A. Da Motta Sobrinho, Maria F. Pimentel

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Oil production is often followed by the joint production of water and gas. During the journey up to the surface, due to severe conditions of temperature and pressure, the mixing between these three components normally occurs. Thus, the three phases separation process must be one of the first steps to be performed after crude oil extraction, where the water-oil separation is the most complex and important step, since the presence of water into the process line can increase corrosion and hydrates formation. A wide range of methods can be applied in order to proceed with oil-water separation, being more commonly used: flotation, hydrocyclones, as well as the three phase separator vessels. Facing what has been presented so far, it is the aim of this paper to study a system consisting of a three-phase separator, evaluating the influence of three variables: temperature, working pressure and separator type, for two types of oil (light and heavy), by performing two factorial design plans 23, in order to find the best operating condition. In this case, the purpose is to obtain the greatest oil flow rate in the product stream (m3/h) as well as the lowest percentage of water in the oil stream. The simulation of the three-phase separator was performed using Aspen Hysys®2006 simulation software in stationary mode, and the evaluation of the factorial experimental designs was performed using the software Statistica®. From the general analysis of the four normal probability plots of effects obtained, it was observed that interaction effects of two and three factors did not show statistical significance at 95% confidence, since all the values were very close to zero. Similarly, the main effect "separator type" did not show significant statistical influence in any situation. As in this case, it has been assumed that the volumetric flow of water, oil and gas were equal in the inlet stream, the effect separator type, in fact, may not be significant for the proposed system. Nevertheless, the main effect “temperature” was significant for both responses (oil flow rate and mass fraction of water in the oil stream), considering both light and heavy oil, so that the best operation condition occurs with the temperature at its lowest level (30oC), since the higher the temperature, the liquid oil components pass into the vapor phase, going to the gas stream. Furthermore, the higher the temperature, the higher the formation water vapor, so that ends up going into the lighter stream (oil stream), making the separation process more difficult. Regarding the “working pressure”, this effect showed to be significant only for the oil flow rate, so that the best operation condition occurs with the pressure at its highest level (9bar), since a higher operating pressure, in this case, indicated a lower pressure drop inside the vessel, generating lower level of turbulence inside the separator. In conclusion, the best-operating condition obtained for the proposed system, at the studied range, occurs for temperature is at its lowest level and the working pressure is at its highest level.

Keywords: factorial experimental design, oil production, simulation, three-phase separator

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