Search results for: hetero-occurrences species distribution model
18826 The Charge Exchange and Mixture Formation Model in the ASz-62IR Radial Aircraft Engine
Authors: Pawel Magryta, Tytus Tulwin, Paweł Karpiński
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The ASz62IR engine is a radial aircraft engine with 9 cylinders. This object is produced by the Polish company WSK "PZL-KALISZ" S.A. This is engine is currently being developed by the above company and Lublin University of Technology. In order to provide an effective work of the technological development of this unit it was decided to made the simulation model. The model of ASz-62IR was developed with AVL BOOST software which is a tool dedicated to the one-dimensional modeling of internal combustion engines. This model can be used to calculate parameters of an air and fuel flow in an intake system including charging devices as well as combustion and exhaust flow to the environment. The main purpose of this model is the analysis of the charge exchange and mixture formation in this engine. For this purpose, the model consists of elements such: as air inlet, throttle system, compressor connector, charging compressor, inlet pipes and injectors, outlet pipes, fuel injection and model of fuel mixing and evaporation. The model of charge exchange and mixture formation was based on the model of mass flow rate in intake and exhaust pipes, and also on the calculation of gas properties values like gas constant or thermal capacity. This model was based on the equations to describe isentropic flow. The energy equation to describe flow under steady conditions was transformed into the mass flow equation. In the model the flow coefficient μσ was used, that varies with the stroke/valve opening and was determined in a steady flow state. The geometry of the inlet channels and other key components was mapped with reference to the technical documentation of the engine and empirical measurements of the structure elements. The volume of elements on the charge flow path between the air inlet and the exhaust outlet was measured by the CAD mapping of the structure. Taken from the technical documentation, the original characteristics of the compressor engine was entered into the model. Additionally, the model uses a general model for the transport of chemical compounds of the mixture. There are 7 compounds used, i.e. fuel, O2, N2, CO2, H2O, CO, H2. A gasoline fuel of a calorific value of 43.5 MJ/kg and an air mass fraction for stoichiometric mixture of 14.5 were used. Indirect injection into the intake manifold is used in this model. The model assumes the following simplifications: the mixture is homogenous at the beginning of combustion, accordingly, mixture stoichiometric coefficient A/F remains constant during combustion, combusted and non-combusted charges show identical pressures and temperatures although their compositions change. As a result of the simulation studies based on the model described above, the basic parameters of combustion process, charge exchange, mixture formation in cylinders were obtained. The AVL Boost software is very useful for the piston engine performance simulations. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.Keywords: aviation propulsion, AVL Boost, engine model, charge exchange, mixture formation
Procedia PDF Downloads 34618825 Signs-Only Compressed Row Storage Format for Exact Diagonalization Study of Quantum Fermionic Models
Authors: Michael Danilov, Sergei Iskakov, Vladimir Mazurenko
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The present paper describes a high-performance parallel realization of an exact diagonalization solver for quantum-electron models in a shared memory computing system. The proposed algorithm contains a storage format for efficient computing eigenvalues and eigenvectors of a quantum electron Hamiltonian matrix. The results of the test calculations carried out for 15 sites Hubbard model demonstrate reduction in the required memory and good multiprocessor scalability, while maintaining performance of the same order as compressed row storage.Keywords: sparse matrix, compressed format, Hubbard model, Anderson model
Procedia PDF Downloads 40818824 Continual Learning Using Data Generation for Hyperspectral Remote Sensing Scene Classification
Authors: Samiah Alammari, Nassim Ammour
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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation
Procedia PDF Downloads 27218823 Handling Complexity of a Complex System Design: Paradigm, Formalism and Transformations
Authors: Hycham Aboutaleb, Bruno Monsuez
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Current systems' complexity has reached a degree that requires addressing conception and design issues while taking into account environmental, operational, social, legal, and financial aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponentially growing effort, cost, and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework, and an environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and suggests a graph-based formalism for modeling complex systems. Finally, a set of transformations are defined to handle the model complexity.Keywords: higraph-based, formalism, system engineering paradigm, modeling requirements, graph-based transformations
Procedia PDF Downloads 40418822 Impacts of Climate Change on Water Resources of Greater Zab and Lesser Zab Basins, Iraq, Using Soil and Water Assessment Tool Model
Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari
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The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.Keywords: Tigris River, climate change, water resources, SWAT
Procedia PDF Downloads 20718821 Statistical Model of Water Quality in Estero El Macho, Machala-El Oro
Authors: Rafael Zhindon Almeida
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Surface water quality is an important concern for the evaluation and prediction of water quality conditions. The objective of this study is to develop a statistical model that can accurately predict the water quality of the El Macho estuary in the city of Machala, El Oro province. The methodology employed in this study is of a basic type that involves a thorough search for theoretical foundations to improve the understanding of statistical modeling for water quality analysis. The research design is correlational, using a multivariate statistical model involving multiple linear regression and principal component analysis. The results indicate that water quality parameters such as fecal coliforms, biochemical oxygen demand, chemical oxygen demand, iron and dissolved oxygen exceed the allowable limits. The water of the El Macho estuary is determined to be below the required water quality criteria. The multiple linear regression model, based on chemical oxygen demand and total dissolved solids, explains 99.9% of the variance of the dependent variable. In addition, principal component analysis shows that the model has an explanatory power of 86.242%. The study successfully developed a statistical model to evaluate the water quality of the El Macho estuary. The estuary did not meet the water quality criteria, with several parameters exceeding the allowable limits. The multiple linear regression model and principal component analysis provide valuable information on the relationship between the various water quality parameters. The findings of the study emphasize the need for immediate action to improve the water quality of the El Macho estuary to ensure the preservation and protection of this valuable natural resource.Keywords: statistical modeling, water quality, multiple linear regression, principal components, statistical models
Procedia PDF Downloads 10618820 Development of Management Model for Promoting Sustainable Tourism of Rajabhat Universities in Thailand
Authors: Weera Weerasophon
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This research paper is to study the development of a management model for promoting sustainable tourism of Rajabhat universities in Thailand. Mixed Method Research is applied under the said topic. The researcher has developed a management model to promote sustainable tourism. The objectives of the research are 1) to study the readiness in management sustainable tourism of Rajabhat universities in Thailand 2) to develop a management model for promoting sustainable tourism of those universities. The process of this research is organized in two steps according to the objectives. The results of the research are as in the following: 1. Rajabhat universities have the readiness in management for promoting sustainable tourism. The universities can be developed to be sustainable tourist attraction under the admistrators who have vision and realize the importance of tourism, eager to promote sustainable tourism of the universities by specifying obvious policy plans and management. 2. The management model for promoting sustainable tourism of Rajabhat universities is consisted of the main following factors : 2.1 Master plan and policy, 2.2 Rajabhat universities organization management and personnel administration, 2.3 Assignment and authority, leadership, 2.4 Join network, 2.5 Assurance of quality and controlling, 2.6 Budget management, 2.7 Human Resources management, 2.8 Alliance and co-ordination, 2.9 Tool of marketing. There are also other communal factors for promoting sustainable tourism. They are: local communities, local communities, tourism activities, government and private sectors, communicative technology system, history, tourist attractive, art and culture, internal and external environment including local wisdom heritage. The management model for promoting sustainable tourism can be concluded from these main and communal factors mentioned above.Keywords: tourism, sustainable tourism, management, Rajabhat University
Procedia PDF Downloads 41918819 Exploring Tree Growth Variables Influencing Carbon Sequestration in the Face of Climate Change
Authors: Funmilayo Sarah Eguakun, Peter Oluremi Adesoye
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One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV oxide (CO2) to the atmosphere. Carbon IV oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest landsare major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine)and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influencesthe carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density speciescould be relevant for management strategy to increase carbon storage.Keywords: adaptation, carbon sequestration, climate change, growth variables, wood density
Procedia PDF Downloads 38318818 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 8218817 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 52018816 Experimental Studies of the Response of Single Piles Under Torsional and Vertical Combined Loads in Contaminated Sand
Authors: Ahmed Mohamed Nasr, Waseim Ragab Azzam, Nada Osama Ramadan
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Contaminated soil can weaken the stability of buildings and infrastructure, posing serious risks to their structural integrity. Therefore, this study aims to understand how oil contamination affects the torsion behavior of model steel piles at different soil densities. This research is crucial for evaluating the structural integrity and stability of piles in oil-contaminated environments. Clean sand samples and heavy motor oil were mixed in amounts ranging from 0 to 6% of the soil's dry weight. The mixture was thoroughly mixed to ensure uniform distribution of the oil throughout the sandy soil for simulating the field conditions. In these investigations, the relative densities (Dr), pile slenderness ratio (Lp/Dp), oil content (O.C%), and contaminated sand layer thickness (LC) were all different. Also, the paper presents an analysis of piles that are loaded both vertically and torsionally. The findings demonstrated that the pre-applied torsion load led to a decrease in the vertical bearing ability of the pile. Also, at Dr = 80%, the ultimate vertical load under combined load at constant torsional load T = (1/3Tu, 2/3Tu, and Tu) in the cases of (Lc/Lp) = 0.5 and (Lp/Dp) =13.3 was found to be reduced by (1.48, 2.78, and 4.15%) less than piles under independent vertical load, respectively so it is crucial to consider the torsion load during pile design.Keywords: torsion-vertical load, oil-contaminated sand, twist angle, steel pile
Procedia PDF Downloads 7718815 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 43718814 Single and Combined Effects of Diclofenac and Ibuprofen on Daphnia Magna and Some Phytoplankton Species
Authors: Ramatu I. Sha’aba, Mathias A. Chia, Abdullahi B. Alhassan, Yisa A. Gana, Ibrahim M. Gadzama
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Globally, Diclofenac (DLC) and Ibuprofen (IBU) are the most prescribed drugs due to their antipyretic and analgesic properties. They are, however, highly toxic at elevated doses, with the involvement of an already described oxidative stress pathway. As a result, there is rising concern about the ecological fate of analgesics on non-target organisms such as Daphnia magna and Phytoplankton species. Phytoplankton is a crucial component of the aquatic ecosystem that serves as the primary producer at the base of the food chain. However, the increasing presence and levels of micropollutants such as these analgesics can disrupt their community structure, dynamics, and ecosystem functions. This study presents a comprehensive series of the physiology, antioxidant response, immobilization, and risk assessment of Diclofenac and Ibuprofen’s effects on Daphnia magna and the Phytoplankton community using a laboratory approach. The effect of DLC and IBU at 27.16 µg/L and 20.89 µg/L, respectively, for a single exposure and 22.39 µg/L for combined exposure of DLC and IBU for the experimental setup. The antioxidant response increased with increasing levels of stress. The highest stressor to the organism was 1000 µg/L of DLC and 10,000 µg/L of IBU. Peroxidase and glutathione -S-transferase activity was higher for Diclofenac + Ibuprofen. The study showed 60% and 70% immobilization of the organism at 1000 g L-1 of DLC and IBU. The two drugs and their combinations adversely impacted Phytoplankton biomass with increased exposure time. However, combining the drugs resulted in more significant adverse effects on physiological and pigment content parameters. The risk assessment calculation for the risk quotient and toxic unit of the analgesic reveals from this study was RQ Diclofenac = 8.41, TU Diclofenac = 3.68, and RQ Ibuprofen = 718.05 and TU Ibuprofen = 487.70. Hence, these findings demonstrate that the current exposure concentrations of Diclofenac and Ibuprofen can immobilize D. magna. This study shows the dangers of multiple drugs in the aquatic environment because their combinations could have additive effects on the structure and functions of Phytoplankton and are capable of immobilizing D. magna.Keywords: algae, analgesic drug, daphnia magna, toxicity
Procedia PDF Downloads 8318813 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 29818812 ZBTB17 Gene rs10927875 Polymorphism in Slovak Patients with Dilated Cardiomyopathy
Authors: I. Boroňová, J. Bernasovská, J. Kmec, E. Petrejčíková
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Dilated cardiomyopathy (DCM) is a severe cardiovascular disorder characterized by progressive systolic dysfunction due to cardiac chamber dilatation and inefficient myocardial contractility often leading to chronic heart failure. Recently, a genome-wide association studies (GWASs) on DCM indicate that the ZBTB17 gene rs10927875 single nucleotide polymorphism is associated with DCM. The aim of the study was to identify the distribution of ZBTB17 gene rs10927875 polymorphism in 50 Slovak patients with DCM and 80 healthy control subjects using the Custom Taqman®SNP Genotyping assays. Risk factors detected at baseline in each group included age, sex, body mass index, smoking status, diabetes and blood pressure. The mean age of patients with DCM was 52.9±6.3 years; the mean age of individuals in control group was 50.3±8.9 years. The distribution of investigated genotypes of rs10927875 polymorphism within ZBTB17 gene in the cohort of Slovak patients with DCM was as follows: CC (38.8%), CT (55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT (5.0%). The risk allele T was more common among the patients with dilated cardiomyopathy than in normal controls (33.7% versus 30.6%). The differences in genotype or allele frequencies of ZBTB17 gene rs10927875 polymorphism were not statistically significant (p=0.6908; p=0.6098). The results of this study suggest that ZBTB17 gene rs10927875 polymorphism may be a risk factor for susceptibility to DCM in Slovak patients with DCM. Studies of numerous files and additional functional investigations are needed to fully understand the roles of genetic associations.Keywords: ZBTB17 gene, rs10927875 polymorphism, dilated cardiomyopathy, cardiovascular disorder
Procedia PDF Downloads 40918811 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 34918810 Adaptive Process Monitoring for Time-Varying Situations Using Statistical Learning Algorithms
Authors: Seulki Lee, Seoung Bum Kim
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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process
Procedia PDF Downloads 30318809 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 25818808 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 32818807 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 37918806 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 9918805 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 8218804 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 33218803 Distribution System Modelling: A Holistic Approach for Harmonic Studies
Authors: Stanislav Babaev, Vladimir Cuk, Sjef Cobben, Jan Desmet
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The procedures for performing harmonic studies for medium-voltage distribution feeders have become relatively mature topics since the early 1980s. The efforts of various electric power engineers and researchers were mainly focused on handling large harmonic non-linear loads connected scarcely at several buses of medium-voltage feeders. In order to assess the impact of these loads on the voltage quality of the distribution system, specific modeling and simulation strategies were proposed. These methodologies could deliver a reasonable estimation accuracy given the requirements of least computational efforts and reduced complexity. To uphold these requirements, certain analysis assumptions have been made, which became de facto standards for establishing guidelines for harmonic analysis. Among others, typical assumptions include balanced conditions of the study and the negligible impact of impedance frequency characteristics of various power system components. In latter, skin and proximity effects are usually omitted, and resistance and reactance values are modeled based on the theoretical equations. Further, the simplifications of the modelling routine have led to the commonly accepted practice of neglecting phase angle diversity effects. This is mainly associated with developed load models, which only in a handful of cases are representing the complete harmonic behavior of a certain device as well as accounting on the harmonic interaction between grid harmonic voltages and harmonic currents. While these modelling practices were proven to be reasonably effective for medium-voltage levels, similar approaches have been adopted for low-voltage distribution systems. Given modern conditions and massive increase in usage of residential electronic devices, recent and ongoing boom of electric vehicles, and large-scale installing of distributed solar power, the harmonics in current low-voltage grids are characterized by high degree of variability and demonstrate sufficient diversity leading to a certain level of cancellation effects. It is obvious, that new modelling algorithms overcoming previously made assumptions have to be accepted. In this work, a simulation approach aimed to deal with some of the typical assumptions is proposed. A practical low-voltage feeder is modeled in PowerFactory. In order to demonstrate the importance of diversity effect and harmonic interaction, previously developed measurement-based models of photovoltaic inverter and battery charger are used as loads. The Python-based script aiming to supply varying voltage background distortion profile and the associated current harmonic response of loads is used as the core of unbalanced simulation. Furthermore, the impact of uncertainty of feeder frequency-impedance characteristics on total harmonic distortion levels is shown along with scenarios involving linear resistive loads, which further alter the impedance of the system. The comparative analysis demonstrates sufficient differences with cases when all the assumptions are in place, and results indicate that new modelling and simulation procedures need to be adopted for low-voltage distribution systems with high penetration of non-linear loads and renewable generation.Keywords: electric power system, harmonic distortion, power quality, public low-voltage network, harmonic modelling
Procedia PDF Downloads 16418802 Pathogenic Candida Biofilms Producers Involved in Healthcare Associated Infections
Authors: Ouassila Bekkal Brikci Benhabib, Zahia Boucherit Otmani, Kebir Boucherit, A. Seghir
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The establishment of intravenous catheters in hospitalized patient is an act common in many clinical situations. These therapeutic tools, from their insertion in the body, represent gateways including fungal germs prone. The latter can generate the growth of biofilms, which can be the cause of fungal infection. Faced with this problem, we conducted a study at the University Hospital of Tlemcen in the neurosurgery unit and aims to isolate and identify Candida yeasts from intravenous catheters. Then test their ability to form biofilms. Materials and methods: 256 patient hospitalized in surgery of the hospital in west Algeria were submitted to this study. All samples were taken from peripheral venous catheters implanted for 72 hours or more days. A total of 31 isolates of Candida species were isolated. MIC and SMIC are determined at 80% inhibition by the test XTT tetrazolium measured at 490 nm. The final concentrations of antifungal agent being between 0.03 and 16 mg / ml for amphotericin B and from 0.015 to 8 mg / mL caspofungin. Results: 31 Candida species isolates from catheters including 14 Candida albicans and 17 Candida non albicans . 21 strains of all the isolates were able to form biofilms. In their form of Planktonic cells, all isolates are 100% susceptible to antifungal agents tested. However, in their state of biofilms, more isolates have become tolerant to the tested antifungals. Conclusion: Candida yeasts isolated from intravascular catheters are considered an important virulence factor in the pathogenesis of infections. Their involvement in catheter-related infections can be disastrous for their potential to generate biofilms. They survive high concentrations of antifungal where treatment failure. Pending the development of a therapeutic approach antibiofilm related to catheters, their mastery is going through: -The risk of infection prevention based on the training and awareness of medical staff, -Strict hygiene and maximum asepsis, and -The choice of material limiting microbial colonization.Keywords: candida, biofilm, hospital, infection, amphotericin B, caspofungin
Procedia PDF Downloads 32618801 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 14018800 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 31918799 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 12018798 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 45018797 A Review: Role of Chromium in Broiler
Authors: Naveed Zahra, Zahid Kamran, Shakeel Ahmad
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Heat stress is one of the most important environmental stressors challenging poultry production worldwide. The detrimental effect of heat stress results in reduction in the productive performance of poultry with high incidences of mortality. Researchers have made efforts to prevent such damage to poultry production through dietary manipulation. Supplementation with Chromium (Cr) might have some positive effects on some aspect of blood parameters and broilers performance. Chromium (Cr) the element whose trivalent Cr (III) organic state is present in trace amounts in animal feed and water is found to be a key element in evading heat stress and thus cutting down the heavy expenditure on air conditioning in broiler sheds. Chromium, along with other essential minerals is lost due to increased excretion during heat stress and thus its inclusion in broiler diet is kind of mandatory in areas of hot climate. Chromium picolinate in broiler diet has shown a hike in growth rate including muscle gain with body fat reduction under environmental stress. Fat reduction is probably linked to the ability of chromium to increase the sensitivity of the insulin receptors on tissues and thus the uptake of sugar from blood increases which decreases the amount of glucose to be converted to amino acids and stored in adipose tissue as triglycerides. Organic chromium has also shown to increase lymphocyte proliferation rate and antioxidant levels. So, the immune competency, muscle gain and fat reduction along with evasion of heat stress are good enough signs that indicate the fruitful inclusion of dietary chromium for broiler. This promising element may bring the much needed break in the local poultry industry. The task is now to set the exact dose of the element in the diet that would be useful enough and still not toxic to broiler. In conclusion there is a growing body of evidence which suggest that chromium may be an essential trace element for livestock and poultry. The nutritional requirement for chromium may vary with different species and physiological state within a species.Keywords: broiler, chromium, heat stress, performance
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