Search results for: concerns based adoption model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 39252

Search results for: concerns based adoption model

37542 A Sequential Approach for Random-Effects Meta-Analysis

Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

Abstract:

The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

Procedia PDF Downloads 465
37541 Analysis on Prediction Models of TBM Performance and Selection of Optimal Input Parameters

Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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37540 The Impact of the Adittapariyaya Sutta in the Meaning-making of T.S. Eliot’s The Waste Land: A critical Analysis

Authors: Ven Pothupitiye Thilakasiri

Abstract:

The Ādittapariyāya Sutta, also known as the Fire Sermon is an important Buddhist text that addresses the nature of sensual pleasures and attachment through the metaphor of fire. Eliot makes use of this in his epic poem The Waste Land. Though scholars have studied Eliot‘s long poem for traces of eastern philosophy, no scholars have touched upon the idea of how the Adittapariyaya Sutta has enabled the meaning making endeavor of the poem. The present study attempts to address this research gap by undertaking a critical analysis of the Fire Sermon of The Waste Land by undertaking an interdisciplinary study of the poem using two methods—a literary and Buddhist reading methods, namely objective corelative and the three-pillared Buddhist ideas of Anicca (impermanence), Dukkha (suffering) and Anatha (No-self). Thus, the study explores the Ādittapariyāya Sutta’s thematic concerns of impermanence, suffering and no-self within the context of The Waste Land. The setting of the poem symbolizes spiritual desolation and existential crisis. By comparing Sutta‘s teachings with modern existential concerns, which is depicted in T.S. Eliot‘s The Waste Land, the analysis emphasizes the relevance of Buddhist insights to contemporary issues of meaning and disillusio

Keywords: Adittapariyaya Sutta, Objective correlative, Eastern Philosophy, Sensual pleasures

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37539 Understanding Primary School Students’ Beliefs Regarding the Adoption of Pro-Environmental Behaviors

Authors: Astrid de Leeuw, Pierre Valois

Abstract:

Environmental education is the key to enhancing or changing students’ ways of thinking and acting in order to create an environmentally robust future for all. The present study investigates the beliefs of 812 primary school students, which merit consideration when developing educational interventions. Results of multiple regression analyses reveal that educational interventions should focus on promoting students’ feelings of control over pro-environmental behaviors (PEB). For example, schools could provide recycling bins on the premises. Furthermore, it is critical to develop positive attitudes in students by stressing the various benefits of PEB for keeping our planet clean and protecting wildlife. Unfortunately, our results indicate that students believe that PEB is boring and annoying. Suggestions are offered for making PEB more interesting and relevant. Further research is needed to test the effectiveness of interventions based on the present results.

Keywords: pro-environmental behavior, primary school students, theory of planned behavior, beliefs, educational interventions

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37538 A Reinforcement Learning Approach for Evaluation of Real-Time Disaster Relief Demand and Network Condition

Authors: Ali Nadi, Ali Edrissi

Abstract:

Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: disaster management, real-time demand, reinforcement learning, relief demand

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37537 Intelligent Human Pose Recognition Based on EMG Signal Analysis and Machine 3D Model

Authors: Si Chen, Quanhong Jiang

Abstract:

In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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37536 High Resolution Satellite Imagery and Lidar Data for Object-Based Tree Species Classification in Quebec, Canada

Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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37535 Kou Jump Diffusion Model: An Application to the SP 500; Nasdaq 100 and Russell 2000 Index Options

Authors: Wajih Abbassi, Zouhaier Ben Khelifa

Abstract:

The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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37534 Cash Flow Optimization on Synthetic CDOs

Authors: Timothée Bligny, Clément Codron, Antoine Estruch, Nicolas Girodet, Clément Ginet

Abstract:

Collateralized Debt Obligations are not as widely used nowadays as they were before 2007 Subprime crisis. Nonetheless there remains an enthralling challenge to optimize cash flows associated with synthetic CDOs. A Gaussian-based model is used here in which default correlation and unconditional probabilities of default are highlighted. Then numerous simulations are performed based on this model for different scenarios in order to evaluate the associated cash flows given a specific number of defaults at different periods of time. Cash flows are not solely calculated on a single bought or sold tranche but rather on a combination of bought and sold tranches. With some assumptions, the simplex algorithm gives a way to find the maximum cash flow according to correlation of defaults and maturities. The used Gaussian model is not realistic in crisis situations. Besides present system does not handle buying or selling a portion of a tranche but only the whole tranche. However the work provides the investor with relevant elements on how to know what and when to buy and sell.

Keywords: synthetic collateralized debt obligation (CDO), credit default swap (CDS), cash flow optimization, probability of default, default correlation, strategies, simulation, simplex

Procedia PDF Downloads 267
37533 An Adaptive Hybrid Surrogate-Assisted Particle Swarm Optimization Algorithm for Expensive Structural Optimization

Authors: Xiongxiong You, Zhanwen Niu

Abstract:

Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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37532 The Adoption and Use of Social Media as a Source of Information by Egyptian Government Journalists

Authors: Essam Mansour

Abstract:

This study purposes to explore the adoption and use of social media as a source of information by Egyptian government journalists. It applied a survey with a total of 386 journalists representing the three official newspapers of Egypt. Findings showed that 27.2% of journalists were found to not use social media, mainly males (69.7%), older than 40 years (77.7%) and mostly with a BA degree (80.4%). On the other hand, 72.8% of them were found to use these platforms who were also males (59.1%), younger than 40 years (65.9%) and mostly with a BA degree (93.2%). More than two-thirds (69.9%) were somewhat old users whose experience ranged from seven to ten years, and more than two-thirds (73.5%) have been heavily using these platforms (four to more than six hours a day. Such results confirm that a large number (95.7%) of users were found to be at least advanced users. Social media users’ home and work were the most significant places to access these platforms, which were found to be easy and useful to use. Most types of social media used were social news, media sharing and micro blogging, blogs comments and forums, social networking sites and bookmarking sites to perform tasks, such as finding information, making communication, keeping up to date, checking materials, sharing information and making discussions. A large number of users tend to accept these media platforms to be a source of information since they are accessible, linked references updated sources, accurate, promote current work, convenient, secured, credible, reliable, stabled, easily identified, copyrighted, build confident and contain filtered information. However, lack of know-how to cite sources, followed by lack of credibility of the source of news, lack of quality of information sources and lack of time were at least significant to journalists when using social media platforms.

Keywords: social media, social networking sites, newspapers, journalists, Egypt

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37531 A Model of Sustainability in the Accommodation Sector

Authors: L. S. Zavodna, J. Zavodny Pospisil

Abstract:

The aim of this paper is to identify the factors for sustainability in the accommodation sector. Although sustainability is a current trend in tourism, not many facilities know how to apply the concept in practice. This paper presents a model for the implementation of sustainability in hotels, hostels, campgrounds, or other facilities. First, there are identified sections of each accommodation facility, which can contribute to sustainability. Furthermore, concrete steps are presented to transfer this model into reality.

Keywords: accommodation sector, model, sustainable tourism, sustainability

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37530 Research on Detection of Web Page Visual Salience Region Based on Eye Tracker and Spectral Residual Model

Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

Abstract:

Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

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37529 Moving Beyond the Limits of Disability Inclusion: Using the Concept of Belonging Through Friendship to Improve the Outcome of the Social Model of Disability

Authors: Luke S. Carlos A. Thompson

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The medical model of disability, though beneficial for the medical professional, is often exclusionary, restrictive and dehumanizing when applied to the lived experience of disability. As a result, a critique of this model was constructed called the social model of disability. Much of the language used to articulate the purpose behind the social model of disability can be summed up within the word inclusion. However, this essay asserts that inclusiveness is an incomplete aspiration. The social model, as it currently stands, does not aid in creating a society where those with impairments actually belong. Rather, the social model aids in lessening the visibility, or negative consequence of, difference. Therefore, the social model does not invite society to welcome those with physical and intellectual impairments. It simply aids society in ignoring the existence of impairment by removing explicit forms of exclusion. Rather than simple inclusion, then, this essay uses John Swinton’s concept of friendship and Jean Vanier’s understanding of belonging to better articulate the intended outcome of the social model—a society where everyone can belong.

Keywords: belong, community, differently-able, disability, exclusion, friendship, inclusion, normality

Procedia PDF Downloads 445
37528 Exploring Health Care Self-Advocacy of Queer Patients

Authors: Tiffany Wicks

Abstract:

Queer patients can face issues with self-advocating due to the factors of implicit provider bias, lack of tools and resources to self-advocate, and lack of comfortability in self-advocating based on prior experiences. In this study, five participants who identify as queer discussed their interactions with their healthcare providers. This exploratory study revealed that there is a need for healthcare provider education to reduce implicit bias and judgments about queer patients. There is also an important need for peer advocates in order to further inform healthcare promotion and decision-making before and during provider visits in an effort for a better outcome. Through this exploration, queer patients voiced their experiences and concerns to inform a need for change in healthcare collaboration between providers and patients in the queer community.

Keywords: queer, LGBT, patient, self-advocacy, healthcare

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37527 'Gender' and 'Gender Equalities': Conceptual Issues

Authors: Moustafa Ali

Abstract:

The aim of this paper is to discuss and question some of the widely accepted concepts within the conceptual framework of gender from terminological, scientific, and Muslim cultural perspectives, and to introduce a new definition and a model of gender in the Arab and Muslim societies. This paper, therefore, uses a generic methodology and document analysis and comes in three sections and a conclusion. The first section discusses some of the terminological issues in the conceptual framework of gender. The second section highlights scientific issues, introduces a definition and a model of gender, whereas the third section offers Muslim cultural perspectives on some issues related to gender in the Muslim world. The paper, then, concludes with findings and recommendations reached so far.

Keywords: gender definition, gender equalities, sex-gender separability, fairness-based model of gender

Procedia PDF Downloads 131
37526 Consumer Welfare in the Platform Economy

Authors: Prama Mukhopadhyay

Abstract:

Starting from transport to food, today’s world platform economy and digital markets have taken over almost every sphere of consumers’ lives. Sellers and buyers are getting connected through platforms, which is acting as an intermediary. It has made consumer’s life easier in terms of time, price, choice and other factors. Having said that, there are several concerns regarding platforms. There are competition law concerns like unfair pricing, deep discounting by the platforms which affect the consumer welfare. Apart from that, the biggest problem is lack of transparency with respect to the business models, how it operates, price calculation, etc. In most of the cases, consumers are unaware of how their personal data are being used. In most of the cases, they are unaware of how algorithm uses their personal data to determine the price of the product or even to show the relevant products using their previous searches. Using personal or non-personal data without consumer’s consent is a huge legal concern. In addition to this, another major issue lies with the question of liability. If a dispute arises, who will be responsible? The seller or the platform? For example, if someone ordered food through a food delivery app and the food was bad, in this situation who will be liable: the restaurant or the food delivery platform? In this paper, the researcher tries to examine the legal concern related to platform economy from the consumer protection and consumer welfare perspectives. The paper analyses the cases from different jurisdictions and approach taken by the judiciaries. The author compares the existing legislation of EU, US and other Asian Countries and tries to highlight the best practices.

Keywords: competition, consumer, data, platform

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37525 Asset Pricing Model: A Quality Paradigm

Authors: Urmi Khatri

Abstract:

Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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37524 Numerical Modelling of Shear Zone and Its Implications on Slope Instability at Letšeng Diamond Open Pit Mine, Lesotho

Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa

Abstract:

Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.

Keywords: numerical modeling, open pit mine, shear zone, slope stability

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37523 Development of a Coupled Thermal-Mechanical-Biological Model to Simulate Impacts of Temperature on Waste Stabilization at a Landfill in Quebec, Canada

Authors: Simran Kaur, Paul J. Van Geel

Abstract:

A coupled Thermal-Mechanical-Biological (TMB) model was developed for the analysis of impacts of temperatures on waste stabilization at a Municipal Solid Waste (MSW) landfill in Quebec, Canada using COMSOL Multiphysics, a finite element-based software. For waste placed in landfills in Northern climates during winter months, it can take months or even years before the waste approaches ideal temperatures for biodegradation to occur. Therefore, the proposed model links biodegradation induced strain in MSW to waste temperatures and corresponding heat generation rates as a result of anaerobic degradation. This provides a link between the thermal-biological and mechanical behavior of MSW. The thermal properties of MSW are further linked to density which is tracked and updated in the mechanical component of the model, providing a mechanical-thermal link. The settlement of MSW is modelled based on the concept of viscoelasticity. The specific viscoelastic model used is a single Kelvin – Voight viscoelastic body in which the finite element response is controlled by the elastic material parameters – Young’s Modulus and Poisson’s ratio. The numerical model was validated with 10 years of temperature and settlement data collected from a landfill in Ste. Sophie, Quebec. The coupled TMB modelling framework, which simulates placement of waste lifts as they are placed progressively in the landfill, allows for optimization of several thermal and mechanical parameters throughout the depth of the waste profile and helps in better understanding of temperature dependence of MSW stabilization. The model is able to illustrate how waste placed in the winter months can delay biodegradation-induced settlement and generation of landfill gas. A delay in waste stabilization will impact the utilization of the approved airspace prior to the placement of a final cover and impact post-closure maintenance. The model provides a valuable tool to assess different waste placement strategies in order to increase airspace utilization within landfills operating under different climates, in addition to understanding conditions for increased gas generation for recovery as a green and renewable energy source.

Keywords: coupled model, finite element modeling, landfill, municipal solid waste, waste stabilization

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37522 Complex Rigid-Plastic Deformation Model of Tow Degree of Freedom Mechanical System under Impulsive Force

Authors: Abdelouaheb Rouabhi

Abstract:

In order to study the plastic resource of structures, the elastic-plastic single degree of freedom model described by Prandtl diagram is widely used. The generalization of this model to tow degree of freedom beyond the scope of a simple rigid-plastic system allows investigating the plastic resource of structures under complex disproportionate by individual components of deformation (earthquake). This macro-model greatly increases the accuracy of the calculations carried out. At the same time, the implementation of the proposed macro-model calculations easier than the detailed dynamic elastic-plastic calculations existing software systems such as ANSYS.

Keywords: elastic-plastic, single degree of freedom model, rigid-plastic system, plastic resource, complex plastic deformation, macro-model

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37521 Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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37520 Two-Stage Launch Vehicle Trajectory Modeling for Low Earth Orbit Applications

Authors: Assem M. F. Sallam, Ah. El-S. Makled

Abstract:

This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

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37519 A Study of Behavioral Phenomena Using an Artificial Neural Network

Authors: Yudhajit Datta

Abstract:

Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

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37518 A Convolution Neural Network Approach to Predict Pes-Planus Using Plantar Pressure Mapping Images

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

Abstract:

Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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37517 Ethical Concerns in the Internet of Things and Smart Devices: Case Studies and Analysis

Authors: Mitchell Browe, Oriehi Destiny Anyaiwe, Zahraddeen Gwarzo

Abstract:

The Internet of Things (IoT) is a major evolution of technology and of the internet, which has the power to revolutionize the way people live. IoT has the power to change the way people interact with each other and with their homes; It has the ability to give people new ways to interact with and monitor their health; It can alter socioeconomic landscapes by providing new and efficient methods of resource management, saving time and money for both individuals and society as a whole; It even has the potential to save lives through autonomous vehicle technology and smart security measures. Unfortunately, nearly every revolution bears challenges which must be addressed to minimize harm by the new technology upon its adopters. IoT represents an internet technology revolution which has the potential to risk privacy, safety, and security of its users, should devices be developed, implemented, or utilized improperly. This article examines past and current examples of these ethical faults in an attempt to highlight the importance of consumer awareness of potential dangers of these technologies in making informed purchasing and utilization decisions, as well as to reveal how deficiencies and limitations of IoT devices should be better addressed by both companies and by regulatory bodies. Aspects such as consumer trust, corporate transparency, and misuse of individual data are all factors in the implementation of proper ethical boundaries in the IoT.

Keywords: IoT, ethical concerns, privacy, safety, security, smart devices

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37516 Developing a South African Model of Neuropsychological Rehabilitation for Adults After Acquired Brain Injury

Authors: Noorjehan Joosub-Vawda

Abstract:

Objectives: The aim of this poster presentation is to examine cultural contextual understandings of ABI that could aid conceptualisation and the development of a model for neuropsychological rehabilitation in this context. Characteristics of the South African context that make the implementation of international NR practices difficult include socioeconomic disparities, sociocultural influences, lack of accessibility to healthcare services, and poverty and unemployment levels. NR services in the developed world have characteristics such as low staff-to-patient ratios and interdisciplinary teams that make them unsuitable for the resource-constrained South African context. Methods: An exploratory, descriptive research design based on programme theory is being followed in the development of a South African model of neuropsychological rehabilitation. Results: The incorporation of African traditional understandings and practices, such as beliefs about ancestral spirits in the etiology of Acquired Brain Injury are relevant to the planning of rehabilitation interventions. Community-Based Rehabilitation workers, psychoeducation, and cooperation among the different systemic levels especially in rural settings is also needed to improve services offered to patients living with ABI. Conclusions. The preliminary model demonstrated in this poster will attempt to build on the strengths of South African communities, incorporating valuable evidence from international models to serve those affected with brain injury in this context.

Keywords: neuropsychological rehabilitation, South Africa, acquired brain injury, developing context

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37515 Using Lean Six-Sigma in the Improvement of Service Quality at Aviation Industry: Case Study at the Departure Area in KKIA

Authors: Tareq Al Muhareb, Jasper Graham-Jones

Abstract:

The service quality is a significant element in aviation industry especially in the international airports. Through this paper, the researchers built a model based on Lean six sigma methodologies and applied it in the departure area at KKIA (King Khalid International Airport) in order to assess it. This model characterized with many special features that can become over the cultural differences in aviation industry since it is considered the most critical circumstance in this field. Applying the model of this study is depending on following the DMAIC procedure systemized in lean thinking aspects. This model of Lean-six-sigma as a managerial procedure is mostly focused on the change management culture that requires high level of planning, organizing, modifying, and controlling in order to benefit from strengths as well as revoke weaknesses.

Keywords: lean-six-sigma, service quality, aviation industry, KKIA (King Khalid International Airport), SERVQUAL

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37514 Invalidation of the Start of Lunar Calendars Based on Sighting of Crescent: A Survey of 101 Years of Data between 1938 and 2038

Authors: Rafik Ouared

Abstract:

The purpose of this paper is to invalidate decisions made by the Islamic conference led at Istanbul in 2016, which had defined two basic criteria to determine the start of the lunar month: (1)they are all based on the sighting of the crescent, be it observed or computed with modern methods, and (2) they've strongly recommended the adoption of the principle of 'unification of sighting', by which any occurrence of sighting anywhere would be applicable everywhere. To demonstrate the invalidation of those statements, a survey of 101 years of data, from 1938 to 2038, have been analyzed to compare the probability density function (PDF) of time difference between different types of fajr and new moon. Two groups of fajr have been considered: the 'natural fajr', which is the very first fajr following new moon, and the 'biased fajr', which is defined by human being inclusively of all chosen definitions. The parametric and non-parametric statistical comparisons between the different groups have shown the all the biased PDFs are significantly different from the unbiased (natural) PDF with probability value (p-value) less than 0.001. The significance level was fixed to 0.05. Conclusion: the on-going reference to sighting of crescent is inducing an significant bias in defining lunar calendar. Therefore, 'natural' calendar would be more applicable requiring a more contextualized revision of issue in fiqh.

Keywords: biased fajr, lunar calendar, natural fajr, probability density function, sighting of crescent, time difference between fajr and new moon

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37513 Implementation of Renewable Energy Technologies in Rural Africa

Authors: Joseph Levodo, Andy Ford, ISSA Chaer

Abstract:

Africa enjoys some of the best solar radiation levels in the world averaging between 4-6 kWh/m2/day for most of the year and the global economic and political conditions that tend to make African countries more dependent on their own energy resources have caused growing interest in wanting renewable energy based technologies. However to-date, implementation of Modern Energy Technologies in Africa is still very low especially the use of solar conversion technologies. It was initially speculated that the low uptake of solar technology in Africa was associated with the continent’s high poverty levels and limitations in technical capacity as well as awareness. Nonetheless, this is not an academic based speculation and the exact reasons for this low trend in technology adoption are unclear and require further investigation. This paper presents literature review and analysis relating to the techno-economic feasibility of solar photovoltaic power generation in Africa. The literature review would include the following four main categories: design methods, techno-economic feasibility of solar photovoltaic power generation, performance evaluations of various systems, Then it looks at the role of policy and potential future of technological development of photovoltaic (PV) by exploring the impact of alternative policy instruments and technology cost reductions on the financial viability of investing solar photovoltaic (PV) in Africa.

Keywords: Africa Solar Potential, policy, photovoltaic, technologies

Procedia PDF Downloads 556