Search results for: cumulative exposure model
16572 Personal Exposure to Respirable Particles and Other Selected Gases among Cyclists near and Away from Busy Roads of Perth Metropolitan Area
Authors: Anu Shrestha, Krassi Rumchev, Ben Mullins, Yun Zhao, Linda Selvey
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Cycling is often promoted as a means of reducing vehicular congestion, noise and greenhouse gas and air pollutant emissions in urban areas. It is also indorsed as a healthy means of transportation in terms of reducing the risk of developing a range of physical and psychological conditions. However, people who cycle regularly may not be aware that they can become exposed to high levels of Vehicular Air Pollutants (VAP) emitted by nearby traffics and therefore experience adverse health effects as a result. The study will highlight the present scenario of ambient air pollution level in different cycling routes in Perth and also highlight significant contribution to the understanding of health risks that cyclist may face from exposure to particulate air pollution. Methodology: This research was conducted in Perth, Western Austral and consisted of two groups of cyclists cycling near high (2 routes) and low (two routes) vehicular traffic roads, at high and low levels of exertion, during the cold and warm seasons. A sample size of 123 regular cyclists who cycled at least 80 km/week, aged 20-55, and non-smoker were selected for this study. There were altogether 100 male and 23 female who were asked to choose one or more routes among four different routes, and each participant cycled the route for warm or cold or both seasons. Cyclist who reported cardiovascular and other chronic health conditions (excluding asthma) were not invited into the study. Exposures to selected air pollutants were assessed by undertaking background and personal measurements alone with the measurement of heart and breathe rate of each participant. Finding: According to the preliminary study findings, the cyclists who used cycling route close to high traffic route were exposed to higher levels of measured air pollutants Nitrogen Oxide (NO₂) =0.12 ppm, sulfur dioxide (SO₂)=0.06 ppm and carbon monoxide (CO)=0.25 PPM compared to those who cycled away from busy roads. However, we measured high concentrations of particulate air pollution near one of the low traffic route which we associate with the close proximity to ferry station. Concluding Statement: As a conclusion, we recommend that cycling routes should be selected away from high traffic routes. If possible, we should also consider that if the cycling route is surrounded by the dense populated infrastructures, it can trap the pollutants and always facilitate in increasing inhalation of particle count among the cyclists.Keywords: air pollution, carbon monoxide, cyclists' health, nitrogen dioxide, nitrogen oxide, respirable particulate matters
Procedia PDF Downloads 26316571 Enhancing Security and Privacy Protocols in Telehealth: A Comprehensive Approach across IoT/Fog/Cloud Environments
Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo
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This paper introduces an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.Keywords: cloud, enhancing security, fog, IoT, telehealth
Procedia PDF Downloads 7816570 Increases in Serum Erythropoietin Hormone in Recreational Breath-Hold Divers Following a Series of Repeated Apnoeas: Apnoea beyond Freediving
Authors: Antonis Elia, Theo Loizou, Gladys Onambele-Pearson, Matthew Barlow, Georgina Stebbings
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Hypoxic conditions have been reported to enhance red blood cell production in both acclimatised low-landers and altitude adapted populations. This process is mediated by the erythropoietin hormone, which is released predominantly by the hypoxic kidney. A higher haemoglobin concentration was previously reported in elite breath-hold divers when compared to elite-skiers and untrained individuals. Therefore, the present study aimed to investigate whether apnoea induced hypoxia could induce a significant increase in serum erythropoietin concentration in recreational breath-hold divers which would provide an explanation to the higher haemoglobin levels observed in elite breath-hold divers. Identifying whether apnoea induced hypoxia induces a significant increase in serum erythropoietin might suggest that apnoea can be used as an alternative acclimatisation method to high altitude exposure. Seven healthy, recreational male breath-hold divers performed two sets of five 180 second breath-holds with a ten-minute supine rest between each set and a two-minute seated rest between each apnoea. During each breath-hold, participant’s heart rate and peripheral oxygen saturation levels were recorded every subsequent 10 seconds until the end of the 180 second breath-hold. After each 180 second breath-hold a capillary blood sample was collected from the finger to identify circulating haemoglobin levels. Following completion of the apnoeic protocol, three blood samples were collected at 30, 90 and 180 minutes to measure circulating erythropoietin levels. A significant interaction between erythropoietin and time was observed (F(3,18)= 4.72, p < 0.001), with significant increases in erythropoietin evident at 30 (t(6)= -5.035, p < 0.0590 (t(6)= -6.162, p < 0.05) and 180 (t(6)= - 7.232, p < 0.001) minutes post the last apnoea when compared to baseline. Corresponding average increases when compared to baseline were 16% at 30, 23% at 90 and 40% at 180 minutes post the last apnoea. A significant interaction between haemoglobin and time was observed (F(78,84)= 20.814, p < 0.001), with significant increases in haemoglobin evident at the fifth (t(29)= -1.124, p < 0.001), ninth (t(29)= -1.357, p < 0.001) and tenth (t(29)= -1.211, p < 0.05) apnoeas when compared to baseline. A significant interaction between peripheral oxygen saturation and time was observed (F(10,60)= 408.23, p < 0.001). The present study demonstrates that a series of ten 180 second breath-holds is sufficient to induce a significant increase in the circulating erythropoietin concentration of recreational breath hold divers. These observations may suggest that apnoea induced hypoxia may be used as an alternative acclimatisation method to high altitude exposure.Keywords: apnoea, breath-holding, diving reflex, erythropoietin, haemoglobin
Procedia PDF Downloads 18016569 Prenatal Use of Serotonin Reuptake Inhibitors (SRIs) and Congenital Heart Anomalies (CHA): An Exploratory Pharmacogenetics Study
Authors: Aizati N. A. Daud, Jorieke E. H. Bergman, Wilhelmina S. Kerstjens-Frederikse, Pieter Van Der Vlies, Eelko Hak, Rolf M. F. Berger, Henk Groen, Bob Wilffert
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Prenatal use of SRIs was previously associated with Congenital Heart Anomalies (CHA). The aim of the study is to explore whether pharmacogenetics plays a role in this teratogenicity using a gene-environment interaction study. A total of 33 case-mother dyads and 2 mother-only (children deceased) registered in EUROCAT Northern Netherlands were included in a case-only study. Five case-mother dyads and two mothers-only were exposed to SRIs (paroxetine=3, fluoxetine=2, venlafaxine=1, paroxetine and venlafaxine=1) in the first trimester of pregnancy. The remaining 28 case-mother dyads were not exposed to SRIs. Ten genes that encode the enzymes or proteins important in determining fetal exposure to SRIs or its mechanism of action were selected: CYPs (CYP1A2, CYP2C9, CYP2C19, CYP2D6), ABCB1 (placental P-glycoprotein), SLC6A4 (serotonin transporter) and serotonin receptor genes (HTR1A, HTR1B, HTR2A, and HTR3B). All included subjects were genotyped for 58 genetic variations in these ten genes. Logistic regression analyses were performed to determine the interaction odds ratio (OR) between genetic variations and SRIs exposure on the risk of CHA. Due to low phenotype frequencies of CYP450 poor metabolizers among exposed cases, the OR cannot be calculated. For ABCB1, there was no indication of changes in the risk of CHA with any of the ABCB1 SNPs in the children and their mothers. Several genetic variations of the serotonin transporter and receptors (SLC6A4 5-HTTLPR and 5-HTTVNTR, HTR1A rs1364043, HTR1B rs6296 & rs6298, HTR3B rs1176744) were associated with an increased risk of CHA, but with too limited sample size to reach statistical significance. For SLC6A4 genetic variations, the mean genetic scores of the exposed case-mothers tended to be higher than the unexposed mothers (2.5 ± 0.8 and 1.88 ± 0.7, respectively; p=0.061). For SNPs of the serotonin receptors, the mean genetic score for exposed cases (children) tended to be higher than the unexposed cases (3.4 ± 2.2, and 1.9 ± 1.6, respectively; p=0.065). This study might be among the first to explore the potential gene-environment interaction between pharmacogenetic determinants and SRIs use on the risk of CHA. With small sample sizes, it was not possible to find a significant interaction. However, there were indications for a role of serotonin receptor polymorphisms in fetuses exposed to SRIs on fetal risk of CHA which warrants further investigation.Keywords: gene-environment interaction, heart defects, pharmacogenetics, serotonin reuptake inhibitors, teratogenicity
Procedia PDF Downloads 21916568 Resource Allocation Modeling and Simulation in Border Security Application
Authors: Kai Jin, Hua Li, Qing Song
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Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.Keywords: resource optimization, simulation, modeling, border security
Procedia PDF Downloads 51716567 Customer Data Analysis Model Using Business Intelligence Tools in Telecommunication Companies
Authors: Monica Lia
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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes
Procedia PDF Downloads 43016566 Time Series Regression with Meta-Clusters
Authors: Monika Chuchro
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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.Keywords: clustering, data analysis, data mining, predictive models
Procedia PDF Downloads 46616565 QSAR Study and Haptotropic Rearrangement in Estradiol Derivatives
Authors: Mohamed Abd Esselem Dems, Souhila Laib, Nadjia Latelli, Nadia Ouddai
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In this work, we have developed QSAR model for Relative Binding Affinity (RBA) of a large diverse set of estradiol among these derivatives, the organometallic derivatives. By dividing the dataset into a training set of 24 compounds and a test set of 6 compounds. The DFT method was used to calculate quantum chemical descriptors and physicochemical descriptors (MR and MLOGP) were performed using E-Dragon. All the validations indicated that the QSAR model built was robust and satisfactory (R2 = 90.12, Q2LOO = 86.61, RMSE = 0.272, F = 60.6473, Q2ext =86.07). We have therefore apply this model to predict the RBA, for two isomers β and α wherein Mn(CO)3 complex with the aromatic ring of estradiol, and the two isomers show little appreciation for the estrogenic receptor (RBAβ = 1.812 and RBAα = 1.741).Keywords: DFT, estradiol, haptotropic rearrangement, QSAR, relative binding affinity
Procedia PDF Downloads 29516564 Digital Marketing Maturity Models: Overview and Comparison
Authors: Elina Bakhtieva
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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis
Procedia PDF Downloads 34516563 Numerical Simulation of Punching Shear of Flat Plates with Low Reinforcement
Authors: Fatema-Tuz-Zahura, Raquib Ahsan
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Punching shear failure is usually the governing failure mode of flat plate structures. Punching failure is brittle in nature which induces more vulnerability to this type of structure. In the present study, a 3D finite element model of a flat plate with low reinforcement ratio and without any transverse reinforcement has been developed. Punching shear stress and the deflection data were obtained on the surface of the flat plate as well as through the thickness of the model from numerical simulations. The obtained data were compared with the experimental results. Variation of punching stress with respect to deflection as obtained from numerical results is found to be in good agreement with the experimental results; the range of variation of punching stress is within 5%. The numerical simulation shows an early and gradual onset of nonlinearity, whereas the same is late and abrupt as observed in the experimental results. The range of variation of punching stress for different slab thicknesses between experimental and numerical results is less than 15%. The developed numerical model is useful to complement available punching test series performed in the past. The results obtained from the numerical model will be helpful for designing retrofitting schemes of flat plates.Keywords: flat plate, finite element model, punching shear, reinforcement ratio
Procedia PDF Downloads 25716562 Detection of Chaos in General Parametric Model of Infectious Disease
Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari
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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test
Procedia PDF Downloads 32516561 Recovery of Fried Soybean Oil Using Bentonite as an Adsorbent: Optimization, Isotherm and Kinetics Studies
Authors: Prakash Kumar Nayak, Avinash Kumar, Uma Dash, Kalpana Rayaguru
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Soybean oil is one of the most widely consumed cooking oils, worldwide. Deep-fat frying of foods at higher temperatures adds unique flavour, golden brown colour and crispy texture to foods. But it brings in various changes like hydrolysis, oxidation, hydrogenation and thermal alteration to oil. The presence of Peroxide value (PV) is one of the most important factors affecting the quality of the deep-fat fried oil. Using bentonite as an adsorbent, the PV can be reduced, thereby improving the quality of the soybean oil. In this study, operating parameters like heating time of oil (10, 15, 20, 25 & 30 h), contact time ( 5, 10, 15, 20, 25 h) and concentration of adsorbent (0.25, 0.5, 0.75, 1.0 and 1.25 g/ 100 ml of oil) have been optimized by response surface methodology (RSM) considering percentage reduction of PV as a response. Adsorption data were analysed by fitting with Langmuir and Freundlich isotherm model. The results show that the Langmuir model shows the best fit compared to the Freundlich model. The adsorption process was also found to follow a pseudo-second-order kinetic model.Keywords: bentonite, Langmuir isotherm, peroxide value, RSM, soybean oil
Procedia PDF Downloads 37516560 Development of Geo-computational Model for Analysis of Lassa Fever Dynamics and Lassa Fever Outbreak Prediction
Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin
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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria
Procedia PDF Downloads 9416559 Development of a One-Window Services Model for Accessing Cancer Immunotherapies
Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat
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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.Keywords: cancer immunotherapy, one-window services model, accessibility, competence
Procedia PDF Downloads 7616558 Optimization of Element Type for FE Model and Verification of Analyses with Physical Tests
Authors: Mustafa Tufekci, Caner Guven
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In Automotive Industry, sliding door systems that are also used as body closures, are safety members. Extreme product tests are realized to prevent failures in a design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for the design process. These analyses are used before production of a prototype for validation of design according to customer requirement. In result of this, the substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. The cheaper model can be created by the selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then the optimum combination was achieved.Keywords: finite element analysis, sliding door mechanism, element type, structural analysis
Procedia PDF Downloads 32916557 'It Is a Sin to Be in Love with a Disabled Woman': Stigma, Rejection and Intersections of Womanhood and Violence among Physically Disabled Women Living in South Africa
Authors: Ingrid Van Der Heijden, Naeemah Abrahams, Jane Harries
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Background: Commonly, womanhood is defined as the qualities considered to be natural to or characteristic of a woman. However, womanhood is not a static concept; it is contextual and negotiable. For women with disabilities, gender roles or ‘qualities’ of womanhood are often overstated or contradicted because of assumptions of weakness, passivity, asexuality and infertility. Currently, little is known about how disability stigma intersects with notions of womanhood to make women with disabilities vulnerable to violence, or how women navigate this intersection to prevent or protect themselves from violence. Objective: To describe how the stigmatized constructions of womanhood and disability promote women with physical disabilities’ exposure to or protection from violence. Methods: Qualitative data for this paper comes from a doctoral study involving women with disabilities living in Cape Town, South Africa. It presents data from repeat in-depth interviews with 30 women with a range of physical impairments. Women attending protective workshops, rehabilitative centers and residential care facilities for people living with disabilities were invited to participate. Consent procedures and interviews were conducted by the first author (who is herself a woman living with a physical disability), and a female research assistant/translator who is a qualified occupational therapist. Reasonable accommodation is central to the methodology and the study as a whole. Findings: Descriptive and thematic analyses reveal how stigma and local constructions around womanhood, as well as women’s self-image and physical limitations, promotes women’s exposure to psychological, physical and sexual violence. It reveals how disabled women feel they are presumed incapable of living up to expectations of a ‘proper’ woman. This plays out as psychological violence, with women reporting that they feel ‘devalued,' ‘rejected’ and deprived of lasting intimate relationships. Furthermore, forms of psychological violence perpetuate physical and sexual violence. Women also discuss using strategies to prevent violence; by refusing to date, avoiding certain places or avoiding isolation, creating awareness, hiding their physical impairments, and exaggerating their ‘femininity.' Implications: Service providers need to be made aware of women’s violence experiences, and provide a range of accessible psychological and mental health services to women living with disabilities, as well as raising awareness around disability, and violence prevention, among caregivers, men, and women. Violence awareness and prevention interventions need to involve disability experts, researchers and people with disabilities.Keywords: disability, gender, stigma, violence awareness and prevention interventions
Procedia PDF Downloads 35216556 Motivating Factors to Use Electric Vehicles Based on Behavioral Intention Model in South Korea
Authors: Seyedsamad Tahani, Samira Ghorbanpour
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The global warming crisis forced humans to consider their place in the world and the earth's future. In this regard, Electric Vehicles (EVs) are a significant step toward protecting the environment. By identifying factors that influence people's behavior intentions toward using Electric Vehicles (EV), we proposed a theoretical model by extending the Technology Acceptance Model (TAM), including three more concepts, Subjective Norm (SN), Self-Efficacy (SE), and Perceived Behavior Control (PBC). The study was conducted in South Korea, and a random sample was taken at a specific time. In order to collect data, a questionnaire was created in a Google Form and sent via Kakao Talk, a popular social media application used in Korea. There were about 220 participants in this survey. However, 201 surveys were completely done. The findings revealed that all factors in the TAM model and the other added concepts such as subjective norms, self-efficacy and perceived behavior control significantly affect the behavioral intention of using EVs.Keywords: electric vehicles, behavioral intention, perceived trust, perceived enjoyment, self-efficacy
Procedia PDF Downloads 13416555 An Adaptive Controller Method Based on Full-State Linear Model of Variable Cycle Engine
Authors: Jia Li, Huacong Li, Xiaobao Han
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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio
Procedia PDF Downloads 31816554 Damage Identification Using Experimental Modal Analysis
Authors: Niladri Sekhar Barma, Satish Dhandole
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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification
Procedia PDF Downloads 11616553 Unsupervised Feature Learning by Pre-Route Simulation of Auto-Encoder Behavior Model
Authors: Youngjae Jin, Daeshik Kim
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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning
Procedia PDF Downloads 44616552 mKDNAD: A Network Flow Anomaly Detection Method Based On Multi-teacher Knowledge Distillation
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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning
Procedia PDF Downloads 12216551 Numerical Simulation of Transient 3D Temperature and Kerf Formation in Laser Fusion Cutting
Authors: Karim Kheloufi, El Hachemi Amara
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In the present study, a three-dimensional transient numerical model was developed to study the temperature field and cutting kerf shape during laser fusion cutting. The finite volume model has been constructed, based on the Navier–Stokes equations and energy conservation equation for the description of momentum and heat transport phenomena, and the Volume of Fluid (VOF) method for free surface tracking. The Fresnel absorption model is used to handle the absorption of the incident wave by the surface of the liquid metal and the enthalpy-porosity technique is employed to account for the latent heat during melting and solidification of the material. To model the physical phenomena occurring at the liquid film/gas interface, including momentum/heat transfer, a new approach is proposed which consists of treating friction force, pressure force applied by the gas jet and the heat absorbed by the cutting front surface as source terms incorporated into the governing equations. All these physics are coupled and solved simultaneously in Fluent CFD®. The main objective of using a transient phase change model in the current case is to simulate the dynamics and geometry of a growing laser-cutting generated kerf until it becomes fully developed. The model is used to investigate the effect of some process parameters on temperature fields and the formed kerf geometry.Keywords: laser cutting, numerical simulation, heat transfer, fluid flow
Procedia PDF Downloads 33916550 Deep Learning Prediction of Residential Radon Health Risk in Canada and Sweden to Prevent Lung Cancer Among Non-Smokers
Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist
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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden
Procedia PDF Downloads 11216549 The Delone and McLean Model: A Review and Reconceptualisation for Explaining Organisational IS Success
Authors: Probir Kumar Banerjee
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Though the revised DeLone and McLean (DM) model of IS success is found to be effective at the individual level of analysis, there is lack of consensus in regard to its effectiveness at the organisational level. This research reviews the DM model in the light of business/IT alignment theory and supporting literature, and suggests its reconceptualization. Specifically, arguments are made for augmenting it with business process quality. Business process quality, it is argued, captures the effect of intent to use, use and user satisfaction interactions, thus eliminating the need to capture their interaction effects in explaining organisational IS success. It is also argued that ‘operational performance’ driven by systems and business process quality, and higher order measures of organisational performance tied to operational performance are appropriate measures of ‘net benefit’. Suggestions are made for reconceptualisation of the other constructs and an adapted model of organisational IS success is proposed.Keywords: organisational IS success, business/IT alignment, systems quality, business process quality, operational performance, market performance
Procedia PDF Downloads 39516548 Evaluation of Simulated Noise Levels through the Analysis of Temperature and Rainfall: A Case Study of Nairobi Central Business District
Authors: Emmanuel Yussuf, John Muthama, John Ng'ang'A
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There has been increasing noise levels all over the world in the last decade. Many factors contribute to this increase, which is causing health related effects to humans. Developing countries are not left out of the whole picture as they are still growing and advancing their development. Motor vehicles are increasing on urban roads; there is an increase in infrastructure due to the rising population, increasing number of industries to provide goods and so many other activities. All this activities lead to the high noise levels in cities. This study was conducted in Nairobi’s Central Business District (CBD) with the main objective of simulating noise levels in order to understand the noise exposed to the people within the urban area, in relation to weather parameters namely temperature, rainfall and wind field. The study was achieved using the Neighbourhood Proximity Model and Time Series Analysis, with data obtained from proxies/remotely-sensed from satellites, in order to establish the levels of noise exposed to which people of Nairobi CBD are exposed to. The findings showed that there is an increase in temperature (0.1°C per year) and a decrease in precipitation (40 mm per year), which in comparison to the noise levels in the area, are increasing. The study also found out that noise levels exposed to people in Nairobi CBD were roughly between 61 and 63 decibels and has been increasing, a level which is high and likely to cause adverse physical and psychological effects on the human body in which air temperature, precipitation and wind contribute so much in the spread of noise. As a noise reduction measure, the use of sound proof materials in buildings close to busy roads, implementation of strict laws to most emitting sources as well as further research on the study was recommended. The data used for this study ranged from the year 2000 to 2015, rainfall being in millimeters (mm), temperature in degrees Celsius (°C) and the urban form characteristics being in meters (m).Keywords: simulation, noise exposure, weather, proxy
Procedia PDF Downloads 37916547 Monitoring of Belt-Drive Defects Using the Vibration Signals and Simulation Models
Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed
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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE. Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.Keywords: simulation model, misalignment, cogs missing, vibration analysis
Procedia PDF Downloads 28416546 External Strengthening of RC Continuous Beams Using FRP Plates: Finite Element Model
Authors: Mohammed A. Sakr, Tarek M. Khalifa, Walid N. Mansour
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Fiber reinforced polymer (FRP) installation is a very effective way to repair and strengthen structures that have become structurally weak over their life span. This technique attracted the concerning of researchers during the last two decades. This paper presents a simple uniaxial nonlinear finite element model (UNFEM) able to accurately estimate the load-carrying capacity, different failure modes and the interfacial stresses of reinforced concrete (RC) continuous beams flexurally strengthened with externally bonded FRP plates on the upper and lower fibers. Results of the proposed finite element (FE) model are verified by comparing them with experimental measurements available in the literature. The agreement between numerical and experimental results is very good. Considering fracture energy of adhesive is necessary to get a realistic load carrying capacity of continuous RC beams strengthened with FRP. This simple UNFEM is able to help design engineers to model their strengthened structures and solve their problems.Keywords: continuous beams, debonding, finite element, fibre reinforced polymer
Procedia PDF Downloads 48216545 Biomechanical Prediction of Veins and Soft Tissues beneath Compression Stockings Using Fluid-Solid Interaction Model
Authors: Chongyang Ye, Rong Liu
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Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.Keywords: elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction
Procedia PDF Downloads 11216544 Indoor Temperature Estimation with FIR Filter Using R-C Network Model
Authors: Sung Hyun You, Jeong Hoon Kim, Dae Ki Kim, Choon Ki Ahn
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In this paper, we proposed a new strategy for estimating indoor temperature based on the modified resistance capacitance (R–C) network thermal dynamic model. Using minimum variance finite impulse response (FIR) filter, accurate indoor temperature estimation can be achieved. Our study is clarified by the experimental validation of the proposed indoor temperature estimation method. This experiment scenario environment is composed of a demand response (DR) server and home energy management system (HEMS) in a test bed.Keywords: energy consumption, resistance-capacitance network model, demand response, finite impulse response filter
Procedia PDF Downloads 44816543 Design of a Compact Microstrip Patch Antenna for LTE Applications by Applying FDSC Model
Authors: Settapong Malisuwan, Jesada Sivaraks, Peerawat Promkladpanao, Nattakit Suriyakrai, Navneet Madan
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In this paper, a compact microstrip patch antenna is designed for mobile LTE applications by applying the frequency-dependent Smith-Chart (FDSC) model. The FDSC model is adopted in this research to reduce the error on the frequency-dependent characteristics. The Ansoft HFSS and various techniques is applied to meet frequency and size requirements. The proposed method within this research is suitable for use in computer-aided microstrip antenna design and RF integrated circuit (RFIC) design.Keywords: frequency-dependent, smith-chart, microstrip, antenna, LTE, CAD
Procedia PDF Downloads 374