Search results for: converting models

Authors: Weiping Liu

Abstract:

This paper presents an equation to calculate stock prices of different growth model. This equation is mathematically derived by using discounted cash flow method. It has the advantages of being very easy to use and very accurate. It can still be used even when the first stage is lengthy. This equation is more generalized because it can be used for all the three popular stock price models. It can be programmed into financial calculator or electronic spreadsheets. In addition, it can be extended to a multistage model. It is more versatile and efficient than the traditional methods.

Keywords: stock price, multistage model, different growth model, discounted cash flow method

Procedia PDF Downloads 404

Authors: Abderrahim Siam, Ramdane Maamri, Zaidi Sahnoun

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The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines. The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques, and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets

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Authors: Alok Agrawal, Alok Satapathy

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In this paper, an attempt to determine the effective thermal conductivity (keff) of particulate filled polymer composites using finite element method (FEM) a powerful computational technique is made. A commercially available finite element package ANSYS is used for this numerical analysis. Three-dimensional spheres-in-cube lattice array models are constructed to simulate the microstructures of micro-sized particulate filled polymer composites with filler content ranging from 2.35 to 26.8 vol %. Based on the temperature profiles across the composite body, the keff of each composition is estimated theoretically by FEM. Composites with similar filler contents are than fabricated using compression molding technique by reinforcing micro-sized aluminium oxide (Al2O3) in polypropylene (PP) resin. Thermal conductivities of these composite samples are measured according to the ASTM standard E-1530 by using the Unitherm™ Model 2022 tester, which operates on the double guarded heat flow principle. The experimentally measured conductivity values are compared with the numerical values and also with those obtained from existing empirical models. This comparison reveals that the FEM simulated values are found to be in reasonable good agreement with the experimental data. Values obtained from the theoretical model proposed by the authors are also found to be in even closer approximation with the measured values within percolation limit. Further, this study shows that there is gradual enhancement in the conductivity of PP resin with increase in filler percentage and thereby its heat conduction capability is improved. It is noticed that with addition of 26.8 vol % of filler, the keff of composite increases to around 6.3 times that of neat PP. This study validates the proposed model for PP-Al2O3 composite system and proves that finite element analysis can be an excellent methodology for such investigations. With such improved heat conduction ability, these composites can find potential applications in micro-electronics, printed circuit boards, encapsulations etc.

Keywords: analytical modelling, effective thermal conductivity, finite element method, polymer matrix composite

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Authors: Floriane Shala, Evangeline Wagner, Yichun Zhao

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Background: Proper educational training and support are proven to be major components of EHR (Electronic Health Record) implementation and use. However, the majority of health providers are not sufficiently trained in EHR use, leading to adverse events, errors, and decreased quality of care. In response to this, students studying Health Information Science, Public Health, Nursing, and Medicine should all gain a thorough understanding of EHR use at different levels for different purposes. The design of a usable and safe EHR system that accommodates the needs and workflows of different users, user groups, and disciplines is required for EHR learning to be efficient and effective. Objectives: This project builds several artifacts which seek to address both the educational and usability aspects of an educational EHR. The artifacts proposed are models for and examples of such an EHR with a configurable UI to be learned by students who need a background in EHR use during their degrees. Methods: Review literature and gather professional opinions from domain experts on usability, the use of workflow patterns, UI configurability and design, and the educational aspect of EHR use. Conduct interviews in a semi-casual virtual setting with open discussion in order to gain a deeper understanding of the principal aspects of EHR use in educational settings. Select a specific task and user group to illustrate how the proposed solution will function based on the current research. Develop three artifacts based on the available research, professional opinions, and prior knowledge of the topic. The artifacts capture the user task and user’s interactions with the EHR for learning. The first generic model provides a general understanding of the EHR system process. The second model is a specific example of performing the task of MRI ordering with a configurable UI. The third artifact includes UI mock-ups showcasing the models in a practical and visual way. Significance: Due to the lack of educational EHRs, medical professionals do not receive sufficient EHR training. Implementing an educational EHR with a usable and configurable interface to suit the needs of different user groups and disciplines will help facilitate EHR learning and training and ultimately improve the quality of patient care.

Keywords: education, EHR, usability, configurable

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Authors: Mohamed Moustafa Mahmoud Sedky

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The double-fed induction generator wind turbine has recently received a great attention. The steady state performance and response of double fed induction generator (DFIG) based wind turbine are now well understood. This paper presents the analysis of stator and rotor flux linkage dq models operation of DFIG under different faults and at different locations.

Keywords: double fed induction motor, wind energy, flux linkage, short circuit

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Authors: Hisham Mortada

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Transition in the urban configuration of Arab cities has never been as radical and visible as it has been since the turn of the last century. The emergence of new cities near historical settlements of Arabia has spawned a series of developments in and around the old city precincts. New developments are based on advanced technology and conform to globally prevalent standards of city planning, superseding the vernacular arrangements based on traditional norms that guided so-called ‘city planning’. Evidence to this fact are the extant Arab buildings present at the urban core of modern cities, which inform us about intricate spatial organization. Organization that subscribed to multiple norms such as, satisfying gender segregation and socialization, economic sustainability, and ensuring security and environmental coherence etc., within settlement compounds. Several participating factors achieved harmony in such an inclusive city—an organization that was challenged and apparently replaced by the new planning order in the face of growing needs of globalized, economy-centric and high-tech models of development. Communities found it difficult to acclimatize with the new western planning models that were implemented at a very large scale throughout the Kingdom, which later experienced spatial re-structuring to suit users’ needs. A closer look the ancient city of Yanbu, now flanked with such new developments, allows us to differentiate and track the beginnings of this unprecedented transition in settlement formations. This paper aims to elaborate the Arabian context offered to both the ‘traditional’ and ‘modern’ planning approaches, in order to understand challenges and solutions offered by both at different times. In the process it will also establish the inconsistencies and conflicts that arose with the shift in planning paradigm, from traditional-'cultural norms’, to modern-'physical planning', in the Arabian context. Thus, by distinguishing the two divergent planning philosophies, their impact of the Arabian morphology, relevance to lifestyle and suitability to the biophysical environment, it concludes with a perspective on sustainability particularly for in case of Yanbu.

Keywords: Yanbu, traditional architecture, Hijaz, coral building, Saudi Arabia

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Authors: Mokhlisur Rahman

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Consumers have developed a sense of responsibility in the past decade, reflecting on their purchasing behavior after viewing an advertisement. Consumers tend to buy ideal products that enable them to be judged by their close network in the opinion world. In such value considerations, any information that feeds consumers' desire for social status helps, which becomes capital for educating consumers on the importance of purchasing green products for manufacturing companies. Companies' effort in manufacturing green products to get high conversion demands a good deal of promotion with quality information and engaging representation. Additionally, converting people from traditional to eco-friendly products requires innovative alternatives to replace the existing product. Considering consumers' understanding of products and their purchasing behavior, it becomes essential for the brands to know the extent to which consumers' level of awareness of the ecosystem is to make them more responsive to green products. Another is brand image plays a vital role in consumers' perception regarding the credibility of the claim regarding the product. Brand image is a significant positive influence on the younger generation, and younger generations tend to engage more in pro-environmental behavior, including purchasing sustainable products. For example, Adidas senses the necessity of satisfying consumers with something that brings more profits and serves the planet. Several of their eco-friendly products are already in the market, and one is UltraBOOST DNA parley, made from 3D-printed recycled ocean waste. As a big brand image, Adidas has leveraged an interest among the younger generation by incorporating sustainability into its advertising. Therefore, influential brands' effort in the sustainable revolution through engaging advertisement makes it more prominent by educating consumers about the reason behind launching the product. This study investigates younger consumers' attitudes toward sustainability, brand recognition, exposure to green advertising, willingness to receive more green advertising, purchasing green products, and motivation. The study conducts a market experiment by creating two video advertisements: a sustainable product video advertisement and a non-sustainable product video advertisement. Both the videos have similar content design and the same length of 2 minutes, but the messages are different based on the identical product type college bags. The first video advertisement promotes eco-friendly college bags made from biodegradable raw materials, and the second promotes non-sustainable college bags made from plastics. After viewing the videos, consumers make purchasing decisions and complete an online survey to collect their attitudes toward sustainable products. The study finds the importance of a sense of responsibility to the consumers for climate change issues. Also, it empowers people to take a step, even small, and increases environmental awareness. This study provides companies with the knowledge to participate in sustainable product launches by collecting consumers' perceptions and attitudes toward green products. Also, it shows how important it is to build a brand's image for the younger generation.

Keywords: brand-image, environment, green-advertising, sustainability, younger-consumer

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Authors: Mohammed Eltayeb Salih Elamin

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This study discusses the concept of the artificial heart using engineering concepts, of the fluid mechanics and the characteristics of the non-Newtonian fluid. For the purpose to serve heart patients and improve aspects of their lives and since the Statistics review according to world health organization (WHO) says that heart disease and blood vessels are the first cause of death in the world. Statistics shows that 30% of the death cases in the world by the heart disease, so simply we can consider it as the number one leading cause of death in the entire world is heart failure. And since the heart implantation become a very difficult and not always available, the idea of the artificial heart become very essential. So it’s important that we participate in the developing this idea by searching and finding the weakness point in the earlier designs and hoping for improving it for the best of humanity. In this study a pump was designed in order to pump blood to the human body and taking into account all the factors that allows it to replace the human heart, in order to work at the same characteristics and the efficiency of the human heart. The pump was designed on the idea of the diaphragm pump. Three models of blood obtained from the blood real characteristics and all of these models were simulated in order to study the effect of the pumping work on the fluid. After that, we study the properties of this pump by using Ansys15 software to simulate blood flow inside the pump and the amount of stress that it will go under. The 3D geometries modeling was done using SOLID WORKS and the geometries then imported to Ansys design modeler which is used during the pre-processing procedure. The solver used throughout the study is Ansys FLUENT. This is a tool used to analysis the fluid flow troubles and the general well-known term used for this branch of science is known as Computational Fluid Dynamics (CFD). Basically, Design Modeler used during the pre-processing procedure which is a crucial step before the start of the fluid flow problem. Some of the key operations are the geometry creations which specify the domain of the fluid flow problem. Next is mesh generation which means discretization of the domain to solve governing equations at each cell and later, specify the boundary zones to apply boundary conditions for the problem. Finally, the pre–processed work will be saved at the Ansys workbench for future work continuation.

Keywords: Artificial heart, computational fluid dynamic heart chamber, design, pump

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Authors: Domenico Carmelo Mongelli

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The context of this research is that of the Italian reality, which, in order to adapt to the EU Directives that prohibit the production of internal combustion engines in favor of electric mobility from 2035, is extremely concerned about the significant loss of jobs resulting from the difficulty of the automotive industry in converting in such a short time and due to the reticence of potential buyers in the face of such an epochal change. The aim of the research is to evaluate for Italy the potential of the most valid alternative to this transition to electric: leaving the current production of diesel engines unchanged, no longer powered by gasoil, imported and responsible for greenhouse gas emissions, but powered entirely by a nationally produced and eco-sustainable fuel such as biodiesel. Today in Italy, the percentage of biodiesel mixed with gasoil for diesel engines is too low (around 10%); for this reason, this research aims to evaluate the functioning of current diesel engines powered 100% by biodiesel and the ability of the Italian production system to cope to this hypothesis. The research geographically identifies those abandoned lands in Italy, now out of the food market, which is best suited to an energy crop for the final production of biodiesel. The cultivation of oilseeds is identified, which for the Italian agro-industrial reality allows maximizing the agricultural and industrial yields of the transformation of the agricultural product into a final energy product and minimizing the production costs of the entire agro-industrial chain. To achieve this objective, specific databases are used, and energy and economic balances are prepared for the different agricultural product alternatives. Solutions are proposed and tested that allow the optimization of all production phases in both the agronomic and industrial phases. The biodiesel obtained from the most feasible of the alternatives examined is analyzed, and its compatibility with current diesel engines is identified, and from the evaluation of its thermo-fluid-dynamic properties, the engineering measures that allow the perfect functioning of current internal combustion engines are examined. The results deriving from experimental tests on the engine bench are evaluated to evaluate the performance of different engines fueled with biodiesel alone in terms of power, torque, specific consumption and useful thermal efficiency and compared with the performance of engines fueled with the current mixture of fuel on the market. The results deriving from experimental tests on the engine bench are evaluated to evaluate the polluting emissions of engines powered only by biodiesel and compared with current emissions. At this point, we proceed with the simulation of the total replacement of gasoil with biodiesel as a fuel for the current fleet of diesel vehicles in Italy, drawing the necessary conclusions in technological, energy, economic, and environmental terms and in terms of social and employment implications. The results allow us to evaluate the potential advantage of a total replacement of diesel fuel with biodiesel for powering road vehicles with diesel cycle internal combustion engines without significant changes to the current vehicle fleet and without requiring future changes to the automotive industry.

Keywords: biodiesel, economy, engines, environment

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

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Authors: Bharath Anantharamaiah, Tomas Bouda, Elke Deckers, Stijn Jonckheere, Wim Desmet, Juan J. Garcia

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Automotive tyres are gaining importance recently in terms of their noise emission, not only with respect to reduction in noise, but also their perception and detection. Tyres exhibit a mechanical noise generation mechanism up to 1 kHz. However, owing to the fact that tyre is a composite of several materials, it has been difficult to model it using finite elements to predict noise at high frequencies. The currently available FE models have a reliability of about 500 Hz, the limit which, however, is not enough to perceive the roughness or sharpness of noise from tyre. These noise components are important in order to alert pedestrians on the street about passing by slow, especially electric vehicles. In order to model tyre noise behaviour up to 1 kHz, its dynamic behaviour must be accurately developed up to a 1 kHz limit using finite elements. Materials play a vital role in modelling the dynamic tyre behaviour precisely. Since tyre is a composition of several components, their precise definition in finite element simulations is necessary. However, during the tyre manufacturing process, these components are subjected to various pressures and temperatures, due to which these properties could change. Hence, material definitions are better described based on the tyre responses. In this work, the hyperelasticity of tyre component rubbers is calibrated, using the design of experiments technique from the tyre characteristic responses that are measured on a stiffness measurement machine. The viscoelasticity of rubbers are defined by the Prony series for rubbers, which are determined from the loss factor relationship between the loss and storage moduli, assuming that the rubbers are excited within the linear viscoelasticity ranges. These values of loss factor are measured and theoretically expressed as a function of rubber shore hardness or hyperelasticities. From the results of the work, there exists a good correlation between test and simulation vibrational transfer function up to 1 kHz. The model also allows flexibility, i.e., the frequency limit can also be extended, if required, by calibrating the Prony parameters of rubbers corresponding to the frequency of interest. As future work, these tyre models are used for noise generation at high frequencies and thus for tyre noise perception.

Keywords: tyre dynamics, rubber materials, prony series, hyperelasticity

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Authors: Sharein El-Tourky, Sharon Smith, Gary Hitchcock

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Effective fisheries management is necessarily dependent on the accuracy of fisheries models, which can be limited if they omit critical elements. One critical element in the formulation of these models is the trophic interactions at the larval stage of fish development. At this stage, fish mortality rates are at their peak and survival is often determined by resource limitation. Thus it is crucial to identify and quantify essential prey resources and determine how they vary in abundance and availability. The main resources larval fish consume are mesozooplankton. In the Straits of Florida, little is known about temporal and spatial variability of the mesozooplankton community despite its importance as a spawning ground for fish such as the Blue Marlin. To investigate mesozooplankton distribution patterns in the Straits of Florida, a transect of 16 stations from Miami to the Bahamas was sampled once a month in 2003 and 2004 at four depths. We found marked temporal and spatial variability in mesozooplankton biomass, diversity, and depth distribution. Mesozooplankton biomass peaked on the western boundary of the SOF and decreased gradually across the straits to a minimum at eastern stations. Midcurrent stations appeared to be a region of enhanced year-round variability, but limited seasonality. Examination of dominant zooplankton groups revealed groups could be parsed into 6 clusters based on abundance. Of these zooplankton groups, copepods were the most abundant zooplankton group, with the 20 most abundant species making up 86% of the copepod community. Copepod diversity was lowest at midcurrent stations and highest in the Eastern SOF. Interestingly, one copepods species, previously identified to compose up to 90% of larval blue marlin and sailfish diets in the SOF, had a mean abundance of less than 7%. However, the unique spatial and vertical distribution patterns of this copepod coincide with peak larval fish spawning periods and larval distribution, suggesting an important relationship requiring further investigation.

Keywords: mesozooplankton biodiversity, larval fish diet, food web, Straits of Florida, vertical distribution, spatiotemporal variability, cross-current comparisons, Gulf Stream

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Olga I. Moskalenko, Maksim O. Zhuravlev, Alexey A. Koronovskii, Alexander E. Hramov

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Intermittent behavior near the boundary of phase synchronization in the presence of noise is studied. In certain range of the coupling parameter and noise intensity the intermittency of eyelet and ring intermittencies is shown to take place. Main results are illustrated using the example of two unidirectionally coupled Rössler systems. Similar behavior is shown to take place in two hydrodynamical models of Pierce diode coupled unidirectionally.

Keywords: chaotic oscillators, phase synchronization, noise, intermittency of intermittencies

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Authors: Monika Jurkeviciute, Amia Enam, Johanna Torres Bonilla, Henrik Eriksson

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Introduction: Many evaluations of eHealth interventions conclude that the evidence for improved clinical outcomes is limited, especially when the intervention is short, such as one year. Often, evaluation design does not address the feasibility of achieving clinical outcomes. Evaluations are designed to reflect upon clinical goals of intervention without utilizing the opportunity to illuminate effects on organizations and cost. A comprehensive design of evaluation can better support decision-making regarding the effectiveness and potential transferability of eHealth. Hence, the purpose of this paper is to present a feasible and comprehensive design of evaluation for eHealth intervention, including the design process in different contexts. Methodology: The situation of limited feasibility of clinical outcomes was foreseen in the European Union funded project called “DECI” (“Digital Environment for Cognitive Inclusion”) that is run under the “Horizon 2020” program with an aim to define and test a digital environment platform within corresponding care models that help elderly people live independently. A complex intervention of eHealth implementation into elaborate care models in four different countries was planned for one year. To design the evaluation, a participative approach was undertaken using Pettigrew’s lens of change and transformations, including context, process, and content. Through a series of workshops, observations, interviews, and document analysis, as well as a review of scientific literature, a comprehensive design of evaluation was created. Findings: The findings indicate that in order to get evidence on clinical outcomes, eHealth interventions should last longer than one year. The content of the comprehensive evaluation design includes a collection of qualitative and quantitative methods for data gathering which illuminates non-medical aspects. Furthermore, it contains communication arrangements to discuss the results and continuously improve the evaluation design, as well as procedures for monitoring and improving the data collection during the intervention. The process of the comprehensive evaluation design consists of four stages: (1) analysis of a current state in different contexts, including measurement systems, expectations and profiles of stakeholders, organizational ambitions to change due to eHealth integration, and the organizational capacity to collect data for evaluation; (2) workshop with project partners to discuss the as-is situation in relation to the project goals; (3) development of general and customized sets of relevant performance measures, questionnaires and interview questions; (4) setting up procedures and monitoring systems for the interventions. Lastly, strategies are presented on how challenges can be handled during the design process of evaluation in four different countries. The evaluation design needs to consider contextual factors such as project limitations, and differences between pilot sites in terms of eHealth solutions, patient groups, care models, national and organizational cultures and settings. This implies a need for the flexible approach to evaluation design to enable judgment over the effectiveness and potential for adoption and transferability of eHealth. In summary, this paper provides learning opportunities for future evaluation designs of eHealth interventions in different national and organizational settings.

Keywords: ehealth, elderly, evaluation, intervention, multi-cultural

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Authors: V. Markogianni, D. Kalivas, G. Petropoulos, E. Dimitriou

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Lake water quality monitoring in combination with the use of earth observation products constitutes a major component in many water quality monitoring programs. Landsat 8 images of Trichonis Lake (Greece) acquired on 30/10/2013 and 30/08/2014 were used in order to explore the possibility of Landsat 8 to estimate water quality parameters and particularly CDOM absorption at specific wavelengths, chlorophyll-a and nutrient concentrations in this oligotrophic freshwater body, characterized by inexistent quantitative, temporal and spatial variability. Water samples have been collected at 22 different stations, on late August of 2014 and the satellite image of the same date was used to statistically correlate the in-situ measurements with various combinations of Landsat 8 bands in order to develop algorithms that best describe those relationships and calculate accurately the aforementioned water quality components. Optimal models were applied to the image of late October of 2013 and the validation of the results was conducted through their comparison with the respective available in-situ data of 2013. Initial results indicated the limited ability of the Landsat 8 sensor to accurately estimate water quality components in an oligotrophic waterbody. As resulted by the validation process, ammonium concentrations were proved to be the most accurately estimated component (R = 0.7), followed by chl-a concentration (R = 0.5) and the CDOM absorption at 420 nm (R = 0.3). In-situ nitrate, nitrite, phosphate and total nitrogen concentrations of 2014 were measured as lower than the detection limit of the instrument used, hence no statistical elaboration was conducted. On the other hand, multiple linear regression among reflectance measures and total phosphorus concentrations resulted in low and statistical insignificant correlations. Our results were concurrent with other studies in international literature, indicating that estimations for eutrophic and mesotrophic lakes are more accurate than oligotrophic, owing to the lack of suspended particles that are detectable by satellite sensors. Nevertheless, although those predictive models, developed and applied to Trichonis oligotrophic lake are less accurate, may still be useful indicators of its water quality deterioration.

Keywords: landsat 8, oligotrophic lake, remote sensing, water quality

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Authors: Priyanka Agrawal, Janou Koskamp, Amir Raoof, Mariette Wolthers

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Calcite is the main mineral found in carbonate rocks, which form significant hydrocarbon reservoirs and subsurface repositories for CO2 sequestration. The injected CO2 mixes with the reservoir fluid and disturbs the geochemical equilibrium, triggering calcite dissolution. Different combinations of fluid chemistry and injection rate may therefore result in different evolution of porosity, permeability and dissolution patterns. To model the changes in porosity and permeability Kozeny-Carman equation K∝〖(∅)〗^n is used, where K is permeability and ∅ is porosity. The value of n is mostly based on experimental data or pore network models. In pore network models, this derivation is based on accuracy of relation used for conductivity and pore volume change. In fact, at a single pore scale, this relationship is the result of the pore shape development due to dissolution. We have prepared a new reactive transport model for a single pore which simulates the complex chemical reaction of carbonic-acid induced calcite dissolution and subsequent pore-geometry evolution at a single pore scale. We use COMSOL Multiphysics package 5.3 for the simulation. COMSOL utilizes the arbitary-Lagrangian Eulerian (ALE) method for the free-moving domain boundary. We examined the effect of flow rate on the evolution of single pore shape profiles due to calcite dissolution. We used three flow rates to cover diffusion dominated and advection-dominated transport regimes. The fluid in diffusion dominated flow (Pe number 0.037 and 0.37) becomes less reactive along the pore length and thus produced non-uniform pore shapes. However, for the advection-dominated flow (Pe number 3.75), the fast velocity of the fluid keeps the fluid relatively more reactive towards the end of the pore length, thus yielding uniform pore shape. Different pore shapes in terms of inlet opening vs overall pore opening will have an impact on the relation between changing volumes and conductivity. We have related the shape of pore with the Pe number which controls the transport regimes. For every Pe number, we have derived the relation between conductivity and porosity. These relations will be used in the pore network model to get the porosity and permeability variation.

Keywords: single pore, reactive transport, calcite system, moving boundary

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Authors: Yael Deutsch, Arieh Gavious

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The threat of aviation terrorism and its potential damage became significant after the 9/11 terror attacks. These attacks have led authorities and leaders to suggest that security personnel should overcome politically correct scruples about profiling and use it openly. However, there is a lack of knowledge about the smart usage of profiling and its advantages. We analyze game models that are suitable to specific real-world scenarios, focusing on profiling as a tool to detect potential violators, such as terrorists and smugglers. We provide analytical and clear answers to difficult questions, and by that help fighting against harmful violation acts.

Keywords: game theory, profiling, security, nash equilibrium

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Authors: Mikhail O. Eremin

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Present work is devoted to experimental study and numerical modelling of failure of rocks typical for Kuzbass coal basin (Russia). The main goal was to define strength and deformation characteristics of rocks on the base of uniaxial compression and three-point bending loadings and then to build a mathematical model of failure process for both types of loading. Depending on particular physical-mechanical characteristics typical rocks of Kuzbass coal basin (sandstones, siltstones, mudstones, etc. of different series – Kolchuginsk, Tarbagansk, Balohonsk) manifest brittle and quasi-brittle character of failure. The strength characteristics for both tension and compression are found. Other characteristics are also found from the experiment or taken from literature reviews. On the base of obtained characteristics and structure (obtained from microscopy) the mathematical and structural models are built and numerical modelling of failure under different types of loading is carried out. Effective characteristics obtained from modelling and character of failure correspond to experiment and thus, the mathematical model was verified. An Instron 1185 machine was used to carry out the experiments. Mathematical model includes fundamental conservation laws of solid mechanics – mass, impulse, energy. Each rock has a sufficiently anisotropic structure, however, each crystallite might be considered as isotropic and then a whole rock model has a quasi-isotropic structure. This idea gives an opportunity to use the Hooke’s law inside of each crystallite and thus explicitly accounting for the anisotropy of rocks and the stress-strain state at loading. Inelastic behavior is described in frameworks of two different models: von Mises yield criterion and modified Drucker-Prager yield criterion. The damage accumulation theory is also implemented in order to describe a failure process. Obtained effective characteristics of rocks are used then for modelling of rock mass evolution when mining is carried out both by an open-pit or underground opening.

Keywords: damage accumulation, Drucker-Prager yield criterion, failure, mathematical modelling, three-point bending, uniaxial compression

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

Procedia PDF Downloads 448

Authors: Satoshi Nishimura

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Although much information has been garnered from the genomes of humans and mice, it remains difficult to extend that information to explain physiological and pathological phenomena. This is because the processes underlying life are by nature stochastic and fluctuate with time. Thus, we developed novel "in vivo molecular imaging" method based on single and two-photon microscopy. We visualized and analyzed many life phenomena, including common adult diseases. We integrated the knowledge obtained, and established new models that will serve as the basis for new minimally invasive therapeutic approaches.

Keywords: two photon microscope, intravital visualization, thrombus, artery

Procedia PDF Downloads 371

Authors: Nivedita T. Patil, M. T. Patil, M. S. Shashidhar, R. G. Gonnade

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Cyclitols are cycloalkane polyols which have raise attention since they have numerous biological and pharmaceutical properties. Among these, inositols are important cyclitols, which constitute a group of naturally occurring polyhydric alcohols. Myo, scyllo, allo, neo, D-chiro- are naturally occurring structural isomer of inositol while other four isomers (L-chiro, allo, epi-, and cis-inositol) are derived from myo-inositol by chemical synthesis. Myo-inositol, most abundant isomer, plays an important role in signal transduction process and for the treatment of type 2 diabetes, bacterial infections, stimulation of menstruation, ovulation in polycystic ovary syndrome, improvement of osteogenesis, and in treatment of neurological disorders. Considering the vast application of the derivatives, it becomes important to supply these compounds for further studies in quantitative amounts, but the synthesis of suitably protected chiral inositol derivatives is the key intermediates in most of the synthesis which is difficult. Chiral inositol derivatives could also be of interest to synthetic organic chemists as they could serve as potential starting materials for the synthesis of several natural products and their analogs. Thus, obtaining chiral myo-inositol derivatives in a more eco-friendly way is need for current inositol chemistry. Thus, the resolution of nonracemates by preferential crystallization of enantiomers has not been reported as a method for inositol derivatives. We are optimistic that this work might lead to the development of the two tosylate enantiomers as synthetic chiral pool molecules for organic synthesis. Resolution of racemic 4-O-benzyl 6-O-tosyl myo-inositol 1, 3, 5 orthoformate was successfully achieved on multigram scale by preferential crystallization, which is more scalable, eco-friendly method of separation than other reported methods. The separation of the conglomeric mixture of tosylate was achieved by suspending the mixture in ethyl acetate till the level of saturation is obtained. To this saturated clear solution was added seed crystal of the desired enantiomers. The filtration of the precipitated seed was carried out at its filtration window to get enantiomerically enriched tosylate, and the process was repeated alternatively. These enantiomerically enriched samples were recrystallized to get tosylate as pure enantiomers. The configuration of the resolved enantiomers was determined by converting it to previously reported dibenzyl ether myo-inositol, which is an important precursor for mono- and tetraphosphates. We have also developed a convenient and practical method for the preparation of enantiomeric 4-O and 6-O-allyl myo-inositol orthoesters by resolution of diastereomeric allyl dicamphante orthoesters on multigram scale. These allyl ethers can be converted to other chiral protected myo-inositol derivatives using routine synthetic transformations. The chiral allyl ethers can be obtained in gram quantities, and the methods are amenable to further scale-up due to the simple procedures involved. We believe that the work described enhances the pace of research to understand the intricacies of the myo-inositol cycle as the methods described provide efficient access to enantiomeric phosphoinositols, cyclitols, and their derivatives from the abundantly available myo-inositol as a starting material.

Keywords: cyclitols, diastereomers, enantiomers, myo-inositol, preferential crystallization, signal transduction

Procedia PDF Downloads 136

Authors: Saurabh Sharma

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Introduction: The case study deals with the ground stabilisation of Nabi Karim Metro Station in Delhi, India, wherein an extremely complex geology was encountered while excavating the tunnelling shaft for launching Tunnel Boring Machine. The borelog investigation and the Seismic Refraction Technique (SRT) indicated towards the presence of an extremely hard rocky mass from a depth of 3-4 m itself, and accordingly, the Geotechnical Interpretation Report (GIR) concluded the presence of Grade-IV rock from 3m onwards and presence of Grade-III and better rock from 5-6m onwards. Accordingly, it was planned to retain the ground by providing secant piles all around the launching shaft and then excavating the shaft vertically after leaving a berm of 1.5m to prevent secant piles from getting exposed. To retain the side slopes, rock bolting with shotcreting and wire meshing were proposed, which is a normal practice in such strata. However, with the increase in depth of excavation, the rock quality kept on decreasing at an unexpected and surprising pace, with the Grade-III rock mass at 5-6 m converting to conglomerate formation at the depth of 15m. This worsening of geology from high grade rock to slushy conglomerate formation can never be predicted and came as a surprise to even the best geotechnical engineers. Since the excavation had already been cut down vertically to manage the shaft size, the execution was continued with enhanced cautions to stabilise the side slopes. But, when the shaft work was about to finish, a collapse was encountered on one side of the excavation shaft. This collapse was unexpected and surprising since all measures to stabilise the side slopes had been taken after face mapping, and the grid size, diameter, and depth of the rockbolts had already been readjusted to accommodate rock fractures. The above scenario was baffling even to the best geologists and geotechnical engineers, and it was decided that any further slope stabilisation scheme shall have to be designed in such a way to ensure safe completion of works. Accordingly, following revisions to excavation scheme were made: The excavation would be carried while maintaining a slope based on type of soil/rock. The rock bolt type was changed from SN rockbolts to Self Drilling type anchor. The grid size of the bolts changed on real time assessment. the excavation carried out by implementing a ‘Bench Release Approach’. Aggressive Real Time Instrumentation Scheme. Discussion: The above case Study again asserts vitality of correct interpretation of the geological strata and the need of real time revisions of the construction schemes based on the actual site data. The excavation is successfully being done with the above revised scheme, and further details of the Revised Slope Stabilisation Scheme, Instrumentation Schemes, Monitoring results, along with the actual site photographs, shall form the part of the final Paper.

Keywords: unconfined compressive strength (ucs), rock mass rating (rmr), rock bolts, self drilling anchors, face mapping of rock, secant pile, shotcrete

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Authors: Sinuhé Perea Puente

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In several physics systems the whole can be obtained as an exact copy of each of its parts, which facilitates the study of a complex system by looking carefully at its elements, separately. Reducionism offers simplified models which makes the problems easier, but “there’s plenty of room...at the mesoscopic scale”. Here we present a tour for two of its representants: Berry phase and skyrmions, studying some of its basic definitions and properties, and two cases in which both arise together, to finish constraining the scale for our mesoscopic system in the quest of quantum skyrmions, discovering which properties are conserved and which others may be destroyed.

Keywords: condensed mattter, quantum physics, skyrmions, topological defects

Procedia PDF Downloads 141

Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

Procedia PDF Downloads 157

Authors: Yeo Kyeong Lee, Ji Yeon Kang, Eun Mi Ryu, Hee Sun Kim, Yeong Soo Shin

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The objective of this paper is an investigation of the effects of the thickness and axial loading during a fire test on the load-bearing capacity of a fire-damaged normal-strength concrete wall. Two factors are attributed to the temperature distributions in the concrete members and are mainly obtained through numerous experiments. Toward this goal, three wall specimens of different thicknesses are heated for 2 h according to the ISO-standard heating curve, and the temperature distributions through the thicknesses are measured using thermocouples. In addition, two wall specimens are heated for 2 h while simultaneously being subjected to a constant axial loading at their top sections. The test results show that the temperature distribution during the fire test depends on wall thickness and axial load during the fire test. After the fire tests, the specimens are cured for one month, followed by the loading testing. The heated specimens are compared with three unheated specimens to investigate the residual load-bearing capacities. The fire-damaged walls show a minor difference of the load-bearing capacity regarding the axial loading, whereas a significant difference became evident regarding the wall thickness. To validate the experiment results, finite element models are generated for which the material properties that are obtained for the experiment are subject to elevated temperatures, and the analytical results show sound agreements with the experiment results. The analytical method based on validated thought experimental results is applied to generate the fire-damaged walls with 2,800 mm high considering the buckling effect: typical story height of residual buildings in Korea. The models for structural analyses generated to deformation shape after thermal analysis. The load-bearing capacity of the fire-damaged walls with pin supports at both ends does not significantly depend on the wall thickness, the reason for it is restraint of pinned ends. The difference of the load-bearing capacity of fire-damaged walls as axial load during the fire is within approximately 5 %.

Keywords: normal-strength concrete wall, wall thickness, axial-load ratio, slenderness ratio, fire test, residual strength, finite element analysis

Procedia PDF Downloads 214

Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

Procedia PDF Downloads 68

Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

Procedia PDF Downloads 281

Authors: Anthony J. Kondracki, Bonzo I. Reddick, Jennifer L. Barkin

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We sought to examine the association of maternal Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and treponema pallidum (TP) (syphilis) infections with preterm birth (PTB) (<37 weeks gestation), low birth weight (LBW) (<2500 grams) and prenatal care (PNC) attendance. This cross-sectional study was based on data drawn from the 2020 United States National Center for Health Statistics (NCHS) Natality File. We estimated the prevalence of all births, early/late PTBs, moderately/very LBW, and the distribution of sexually transmitted infections (STIs) according to maternal characteristics in the sample. In multivariable logistic regression models, we examined adjusted odds ratios (aORs) and their corresponding 95% confidence intervals (CIs) of PTB and LBW subcategories in the association with maternal/infant characteristics, PNC status, and maternal CT, NG, and TP infections. In separate logistic regression models, we assessed the risk of these newborn outcomes stratified by PNC status. Adjustments were made for race/ethnicity, age, education, marital status, health insurance, liveborn parity, previous preterm birth, gestational hypertension, gestational diabetes, PNC status, smoking, and infant sex. Additionally, in a sensitivity analysis, we assessed the association with early, full, and late term births and the potential impact of unmeasured confounding using the E-value. CT (1.8%) was most prevalent STI in pregnancy, followed by NG (0.3%), and TP (0.1%). Non-Hispanic Black women, 20-24 years old, with a high school education, and on Medicaid had the highest rate of STIs. Around 96.6% of women reported receiving PNC and about 60.0% initiated PNC early in pregnancy. PTB and LBW were strongly associated with NG infection (12.2% and 12.1%, respectively) and late initiation/no PNC (8.5% and 7.6%, respectively), and ≤10 prenatal visits received (13.1% and 10.3%, respectively). The odds of PTB and LBW were 2.5- to 3-foldhigher for each STI among women who received ≤10 prenatal visits than >10 visits. Adequate prenatal care utilization and timely screening and treatment of maternal STIs can substantially reduce the burden of adverse newborn outcomes.

Keywords: low birthweight, prenatal care, preterm birth, sexually transmitted infections

Procedia PDF Downloads 172