Search results for: technological pedagogical model
16343 An Improved GA to Address Integrated Formulation of Project Scheduling and Material Ordering with Discount Options
Authors: Babak H. Tabrizi, Seyed Farid Ghaderi
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Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.Keywords: genetic algorithm, material ordering, project management, project scheduling
Procedia PDF Downloads 28716342 Application of ANN and Fuzzy Logic Algorithms for Runoff and Sediment Yield Modelling of Kal River, India
Authors: Mahesh Kothari, K. D. Gharde
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The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river.Keywords: transferred function, sigmoid, backpropagation, membership function, defuzzification
Procedia PDF Downloads 54816341 Estimating PM2.5 Concentrations Based on Landsat 8 Imagery and Historical Field Data over the Metropolitan Area of Mexico City
Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa
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High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing
Procedia PDF Downloads 17016340 Model Reference Adaptive Control and LQR Control for Quadrotor with Parametric Uncertainties
Authors: Alia Abdul Ghaffar, Tom Richardson
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A model reference adaptive control and a fixed gain LQR control were implemented in the height controller of a quadrotor that has parametric uncertainties due to the act of picking up an object of unknown dimension and mass. It is shown that an adaptive control, unlike a fixed gain control, is capable of ensuring a stable tracking performance under such condition, although adaptive control suffers from several limitations. The combination of both adaptive and fixed gain control in the controller architecture results in an enhanced tracking performance in the presence of parametric uncertainties.Keywords: UAV, quadrotor, robotic arm augmentation, model reference adaptive control, LQR control
Procedia PDF Downloads 44916339 Revised Technology Acceptance Model Framework for M-Commerce Adoption
Authors: Manish Gupta
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Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use
Procedia PDF Downloads 29716338 Elevating Healthcare Social Work: Implementing and Evaluating the (Introduction, Subjective, Objective, Assessment, Plan, Summary) Documentation Model
Authors: Shir Daphna-Tekoah, Nurit Eitan-Gutman, Uri Balla
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Background: Systemic documentation is essential in social work practice. Collaboration between an institution of higher education and social work health care services enabled adaptation of the medical documentation model of SOAP in the field of social work, by creating the ISOAPS model (Introduction, Subjective, Objective, Assessment, Plan, Summary) model. Aims: The article describes the ISOAPS model and its implementation in the field of social work, as a tool for standardization of documentation and the enhancement of multidisciplinary collaboration. Methods: We examined the changes in standardization using a mixed methods study, both before and after implementation of the model. A review of social workers’ documentation was carried out by medical staff and social workers in the Clalit Healthcare Services, the largest provider of public and semi-private health services in Israel. After implementation of the model, semi-structured qualitative interviews were undertaken. Main findings: The percentage of reviewers who evaluated their documentation as correct increased from 46%, prior to implementation, to 61% after implementation. After implementation, 81% of the social workers noted that their documentation had become standardized. The training process prepared them for the change in documentation and most of them (83%) started using the model on a regular basis. The qualitative data indicate that the use of the ISOAPS model creates uniform documentation, improves standards and is important to teach social work students. Conclusions: The ISOAPS model standardizes documentation and promotes communication between social workers and medical staffs. Implications for practice: In the intricate realm of healthcare, efficient documentation systems are pivotal to ensuring coherent interdisciplinary communication and patient care. The ISOAPS model emerges as a quintessential instrument, meticulously tailored to the nuances of social work documentation. While it extends its utility across the broad spectrum of social work, its specificity is most pronounced in the medical domain. This model not only exemplifies rigorous academic and professional standards but also serves as a testament to the potential of contextualized documentation systems in elevating the overall stature of social work within healthcare. Such a strategic documentation tool can not only streamline the intricate processes inherent in medical social work but also underscore the indispensable role that social workers play in the broader healthcare ecosystem.Keywords: ISOAPS, professional documentation, medial social-work, social work
Procedia PDF Downloads 5616337 Comparison of Multivariate Adaptive Regression Splines and Random Forest Regression in Predicting Forced Expiratory Volume in One Second
Authors: P. V. Pramila , V. Mahesh
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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest
Procedia PDF Downloads 29116336 Sustainable Maintenance Model for Infrastructure in Egypt
Authors: S. Hasan, I. Beshara
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Infrastructure maintenance is a great challenge facing sustainable development of infrastructure assets due to the high cost of passive implementation of a sustainable maintenance plan. An assessment model of sustainable maintenance for highway infrastructure projects in Egypt is developed in this paper. It helps in improving the implementation of sustainable maintenance criteria. Thus, this paper has applied the analytical hierarchy processes (AHP) to rank and explore the weight of 26 assessment indicators using three hierarchy levels containing the main sustainable categories and subcategories with related indicators. Overall combined weight of each indicator for sustainable maintenance evaluation has been calculated to sum up to a sustainable maintenance performance index (SMI). The results show that the factor "Preventive maintenance cost" has the highest relative contribution factor among others (13.5%), while two factors of environmental performance have the least weights (0.7%). The developed model aims to provide decision makers with information about current maintenance performance and support them in the decision-making process regarding future directions of maintenance activities. It can be used as an assessment performance tool during the operation and maintenance stage. The developed indicators can be considered during designing the maintenance plan. Practices for successful implementation of the model are also presented.Keywords: analytical hierarchy process, assessment performance Model, KPIs for sustainable maintenance, sustainable maintenance index
Procedia PDF Downloads 12116335 Artificial Neural Network Reconstruction of Proton Exchange Membrane Fuel Cell Output Profile under Transient Operation
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Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient
Procedia PDF Downloads 15216334 Unsteady Natural Convection in a Square Cavity Partially Filled with Porous Media Using a Thermal Non-Equilibrium Model
Authors: Ammar Alsabery, Habibis Saleh, Norazam Arbin, Ishak Hashim
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Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal non-equilibrium model is studied in this paper. The left vertical wall is maintained at a constant hot temperature and the right vertical wall is maintained at a constant cold temperature, while the horizontal walls are adiabatic. The governing equations are obtained by applying the Darcy model and Boussinesq approximation. COMSOL's finite element method is used to solve the non-dimensional governing equations together with specified boundary conditions. The governing parameters of this study are the Rayleigh number, the modified thermal conductivity ratio, the inter-phase heat transfer coefficien and the time independent. The results presented for values of the governing parameters in terms of streamlines in both fluid/porous layer, isotherms of fluid and solid porous layer, isotherms of fluid layer, and average Nusselt number.Keywords: unsteady natural convection, thermal non-equilibrium model, Darcy model
Procedia PDF Downloads 36316333 Dissocial Personality in Adolescents
Authors: Tsirekidze M., Aprasidze T.
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Introduction: The problem of dissocial behavior is at the heart of the social sciences and psychiatry; however, it should be noted that its psychiatric aspect is little studied, and some issues of the problem are still controversial. This is complicated by the diversity of terminological concepts in defining “dissocial behavior”, “behavioral disorder”, “abnormal behavior”, “deviant behavior”, “delinquent behavior”, etc. In literature, there is no comprehensive definition of the essence of dissociative behavior. Numerous attempts to systematize dissociative disorders should also be considered unsatisfactory, which is primarily related to the lack of solid criteria for defining this group of disorders. According to the clinical classification, dissocial behavior is divided into psychotic and non-psychotic forms. Such differentiation is conditional in nature since it is not always possible to draw precise, clear distinctions between these forms, and in addition, there is a transition of a behavior disorder or so-called intermediate forms. One group of authors distinguishes two main forms of deviant behavior in terms of both theoretical and practical significance - non-pathological and pathological. In recent years, especially, the non-pathological form of behavior disorder has become topical. It refers to a large group of forms of deviant behavior, the emergence of which is associated with psychologically full-fledged reactions of children and adolescents to stressful situations and extreme conditions. According to the authors, its concept is understandable-it is difficult to draw a line between psychologically understandable reactions and psychogenically induced reactive states. In addition, the concept of "normal" child and adolescent is, to some extent, a vague concept, as in medicine, any definition of the norm. From a practical (more precisely, pragmatic) point of view, the term "abnormal behavioral disorder" undoubtedly makes sense, especially for the purpose of forensic psychiatric examination. Non-pathological deviation mainly includes transient situational reactions, microsocial-pedagogical backwardness, and character accentuation.Deviant behavior was predominantly manifested in a non-pathological form, which, in our opinion, is due to the difficult socio-economic situation of the country, moral-ethical deprivation, and expressed frustration. By itself, society is an indicator of deviation. Add to this situation complicated factors such as micro-social-pedagogical leave, unfavorable family environment, and parenting defects. Consideration is also given to the connection of acceptable deviation with the personal structural features of the adolescent. Aim: The topic of our discussion is the dissocial behavior of the non-psychotic register. Methods: We surveyed 120 adolescents with deviant behaviors. 61% of them were diagnosed with various neuropsychiatric disorders. Results: Abnormal forms of deviant behavior were observed in 13%, and non-pathological forms in -69%. A combination of non-pathological and pathological forms was present in 10% of cases. In the case of non-pathological deviation, microsocial-pedagogical acceptance was revealed in 62%, character accentuation in 22%; during the pathological forms, pathological reactions were observed in 21%, and abnormal formation of the person -21%. Conclusion: It should be emphasized that in case of any of the above defects, if the so-called family psychosis, and medical and pedagogical habilitation measures for the adolescent, it is quite possible to prevent the abnormal development of the child's personality, correct his character, regulate behavior and develop positive labor-social relations.Keywords: dissocial personality, deviant behavior, dissocial, delinquent behavior
Procedia PDF Downloads 20016332 Micro-Meso 3D FE Damage Modelling of Woven Carbon Fibre Reinforced Plastic Composite under Quasi-Static Bending
Authors: Aamir Mubashar, Ibrahim Fiaz
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This research presents a three-dimensional finite element modelling strategy to simulate damage in a quasi-static three-point bending analysis of woven twill 2/2 type carbon fibre reinforced plastic (CFRP) composite on a micro-meso level using cohesive zone modelling technique. A meso scale finite element model comprised of a number of plies was developed in the commercial finite element code Abaqus/explicit. The interfaces between the plies were explicitly modelled using cohesive zone elements to allow for debonding by crack initiation and propagation. Load-deflection response of the CRFP within the quasi-static range was obtained and compared with the data existing in the literature. This provided validation of the model at the global scale. The outputs resulting from the global model were then used to develop a simulation model capturing the micro-meso scale material features. The sub-model consisted of a refined mesh representative volume element (RVE) modelled in texgen software, which was later embedded with cohesive elements in the finite element software environment. The results obtained from the developed strategy were successful in predicting the overall load-deflection response and the damage in global and sub-model at the flexure limit of the specimen. Detailed analysis of the effects of the micro-scale features was carried out.Keywords: woven composites, multi-scale modelling, cohesive zone, finite element model
Procedia PDF Downloads 12016331 Artificial Neural Network Modeling of a Closed Loop Pulsating Heat Pipe
Authors: Vipul M. Patel, Hemantkumar B. Mehta
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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant
Procedia PDF Downloads 27316330 Determination of the Bearing Capacity of Granular Pumice Soils by Laboratory Tests
Authors: Mustafa Yildiz, Ali Sinan Soganci
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Pumice soils are countered in many projects such as transportation roads, channels and residential units throughout the World. The pumice deposits are characterized by the vesicular nature of their particles. When the pumice soils are evaluated considering the geotechnical viewpoint, they differ from silica sands in terms of physical and engineering characteristics. These differences are low grain strength, high friction angle, void ratio and compressibility. At stresses greater than a few hundred kPa, the stress-strain-strength behaviour of these soils is determined by particle crushing. Particle crushing leads to changes in the density and reduction in the components of shear stress due to expansion. In this study, the bearing capacity and behaviour of granular pumice soils compared to sand-gravels were investigated by laboratory model tests. Firstly the geotechnical properties of granular pumice soils were determined; then, the behaviour of pumice soils with an equivalent diameter of sand and gravel soils were investigated by model rectangular and circular foundation types and were compared with each other. For this purpose, basic types of model footing (15*15 cm, 20*20 cm, Φ=15 cm and Φ=20 cm) have been selected. When the experimental results of model bearing capacity are analyzed, the values of sand and gravel bearing capacity tests were found to be 1.0-1.5 times higher than the bearing capacity of pumice the same size. This fact has shown that sand and gravel have a higher bearing capacity than pumice of the similar particle sizes.Keywords: pumice soils, laboratory model tests, bearing capacity, laboratory model tests, Nevşehir
Procedia PDF Downloads 19516329 Modeling Default Probabilities of the Chosen Czech Banks in the Time of the Financial Crisis
Authors: Petr Gurný
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One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the credit-scoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.Keywords: credit-scoring models, multidimensional subordinated Lévy model, probability of default
Procedia PDF Downloads 43816328 Fuzzy Inference Based Modelling of Perception Reaction Time of Drivers
Authors: U. Chattaraj, K. Dhusiya, M. Raviteja
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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.Keywords: driver, fuzzy logic, perception reaction time, premise variable
Procedia PDF Downloads 28016327 Development of a Mathematical Model to Characterize the Oil Production in the Federal Republic of Nigeria Environment
Authors: Paul C. Njoku, Archana Swati Njoku
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The study deals with the development of a mathematical model to characterize the oil production in Nigeria. This is calculated by initiating the dynamics of oil production in million barrels revenue plan cost of oil production in million nairas and unit cost of production from 1974-1982 in the contest of the federal Republic of Nigeria. This country export oil to other countries as well as importing specialized crude. The transport network from origin/destination tij to pairs is taking into account simulation runs, optimization have been considered in this study.Keywords: mathematical oil model development dynamics, Nigeria, characterization barrels, dynamics of oil production
Procedia PDF Downloads 36716326 The Factors Influencing Consumer Intentions to Use Internet Banking and Apps: A Case of Banks in Cambodia
Authors: Tithdanin Chav, Phichhang Ou
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The study is about the e-banking consumer behavior of five major banks in Cambodia. This work aims to examine the relationships among job relevance, trust, mobility, perceived ease of use, perceived usefulness, attitude toward using, and intention to use of internet banking and apps. Also, the research develops and tests a conceptual model of intention to use internet banking by integrating the Technology Acceptance Model (TAM) and job relevance, trust, and mobility which were supported by Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). The proposed model was tested using Structural Equation Modeling (SEM), which was processed by using SPSS and AMOS with a sample size of 250 e-banking users. The results showed that there is a significant positive relationship among variables and attitudes toward using internet banking, and apps are the most factor influencing consumers’ intention to use internet banking and apps with the importance level in SEM 0.82 accounted by 82%. Significantly, all six hypotheses were accepted.Keywords: bank apps, consumer intention, internet banking, technology acceptance model, TAM
Procedia PDF Downloads 12516325 Resonant Fluorescence in a Two-Level Atom and the Terahertz Gap
Authors: Nikolai N. Bogolubov, Andrey V. Soldatov
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Terahertz radiation occupies a range of frequencies somewhere from 100 GHz to approximately 10 THz, just between microwaves and infrared waves. This range of frequencies holds promise for many useful applications in experimental applied physics and technology. At the same time, reliable, simple techniques for generation, amplification, and modulation of electromagnetic radiation in this range are far from been developed enough to meet the requirements of its practical usage, especially in comparison to the level of technological abilities already achieved for other domains of the electromagnetic spectrum. This situation of relative underdevelopment of this potentially very important range of electromagnetic spectrum is known under the name of the 'terahertz gap.' Among other things, technological progress in the terahertz area has been impeded by the lack of compact, low energy consumption, easily controlled and continuously radiating terahertz radiation sources. Therefore, development of new techniques serving this purpose as well as various devices based on them is of obvious necessity. No doubt, it would be highly advantageous to employ the simplest of suitable physical systems as major critical components in these techniques and devices. The purpose of the present research was to show by means of conventional methods of non-equilibrium statistical mechanics and the theory of open quantum systems, that a thoroughly studied two-level quantum system, also known as an one-electron two-level 'atom', being driven by external classical monochromatic high-frequency (e.g. laser) field, can radiate continuously at much lower (e.g. terahertz) frequency in the fluorescent regime if the transition dipole moment operator of this 'atom' possesses permanent non-equal diagonal matrix elements. This assumption contradicts conventional assumption routinely made in quantum optics that only the non-diagonal matrix elements persist. The conventional assumption is pertinent to natural atoms and molecules and stems from the property of spatial inversion symmetry of their eigenstates. At the same time, such an assumption is justified no more in regard to artificially manufactured quantum systems of reduced dimensionality, such as, for example, quantum dots, which are often nicknamed 'artificial atoms' due to striking similarity of their optical properties to those ones of the real atoms. Possible ways to experimental observation and practical implementation of the predicted effect are discussed too.Keywords: terahertz gap, two-level atom, resonant fluorescence, quantum dot, resonant fluorescence, two-level atom
Procedia PDF Downloads 25216324 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 38316323 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 23016322 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 38716321 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 18716320 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 7316319 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 39516318 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 5216317 Resource Allocation Modeling and Simulation in Border Security Application
Authors: Kai Jin, Hua Li, Qing Song
Abstract:
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 49816316 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 41316315 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 45016314 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 275