Search results for: General Linear Model

Authors: Guilherme F. Guimaraes, Alfredo R. De Faria, Ronnie R. Rego, Andre L. R. D'Oliveira

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The development of methods for predicting manufacturing phenomena steadily grows due to their high potential to contribute to the component’s performance and durability. One of the most relevant phenomena in manufacturing is the residual stress state development through the manufacturing chain. In most cases, the residual stresses have their origin due to heterogenous plastifications produced by the processes. Although a few manufacturing processes have been successfully approached by numerical modeling, there is still a lack of understanding on how these processes' interactions will affect the final stress state. The objective of this work is to analyze the influence of previous stresses on the residual stress state induced by plastic deformation of a quasi-static indentation. The model consists of a simplified approach of shot peening, modeling four cases with variations in indenter size and force. This model was validated through topography, measured by optical 3D focus-variation, and residual stress, measured with the X-ray diffraction technique. The validated model was then exposed to several initial stress states, and the effect on the final residual stress was analyzed.

Keywords: plasticity, residual stress, finite element method, manufacturing

Procedia PDF Downloads 198

Authors: Weikang Gong, Chunhua Li

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Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

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Authors: Jing Zhang, Daniel Nikovski

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We propose an approximation algorithm called LINKUMP to compute the Pan Matrix Profile (PMP) under the unnormalized l∞ distance (useful for value-based similarity search) using double-ended queue and linear interpolation. The algorithm has comparable time/space complexities as the state-of-the-art algorithm for typical PMP computation under the normalized l₂ distance (useful for shape-based similarity search). We validate its efficiency and effectiveness through extensive numerical experiments and a real-world anomaly detection application.

Keywords: pan matrix profile, unnormalized euclidean distance, double-ended queue, discord discovery, anomaly detection

Procedia PDF Downloads 241

Authors: Saidi Abdelkrim, Hamouine Abdelmadjid, Abdellatif Megnounif

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The study of interaction between vehicles and bridge structures has become extremely important. Large deflections and vibration induced by heavy and high-speed vehicles affect significantly the safety and efficiency of bridge. The vibration of a bridge caused by passage of vehicles is one of the most imperative considerations in the design of a bridge as a common sort of transportation structure. A major goal of this study is to create a simplified model of a vehicle bridge system in MATLAB. The model will then be used to study the influence of parameters to vehicle-bridge vibrations.

Keywords: vehicle-bridge interaction, Newmark-β, MATLAB code

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Authors: Wafula Simon Peter, Kimuli Nabayego Ibtihal, Nabaggala Kimuli Nashua

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The worldwide use of information and communications technology (ICT) equipment and other electronic equipment is growing and consequently, there is a growing amount of equipment that becomes waste after its time in use. This growth is expected to accelerate since equipment lifetime decreases with time and growing consumption. As a result, e-waste is one of the fastest-growing waste streams globally. The United Nations University (UNU) calculates in its second Global E-waste Monitor 44.7 million metric tonnes (Mt) of e-waste were generated globally in 2016. The study population was 80 respondents, from which a sample of 69 respondents was selected using simple and purposive sampling techniques. This research was carried out to investigate the problem of e-waste and come up with a framework to improve e-waste management. The objective of the study was to develop a framework for improving e-waste management at the College of Engineering, Design, Art and Technology (CEDAT). This was achieved by breaking it down into specific objectives, and these included the establishment of the policy and other Regulatory frameworks being used in e-waste management at CEDAT, the determination of the effectiveness of the e-waste management practices at CEDAT, the establishment of the critical challenges constraining e-waste management at the College, development of a framework for e-waste management. The study reviewed the e-waste regulatory framework used at the college and then collected data which was used to come up with a framework. The study also established that weak policy and regulatory framework, lack of proper infrastructure, improper disposal of e-waste and a general lack of awareness of the e-waste and the magnitude of the problem are the critical challenges of e-waste management. In conclusion, the policy and regulatory framework should be revised, localized and strengthened to contextually address the problem. Awareness campaigns, the development of proper infrastructure and extensive research to establish the volumes and magnitude of the problems will come in handy. The study recommends a framework for the improvement of e-waste.

Keywords: e-waste, treatment, disposal, computers, model, management policy and guidelines

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Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Manjie Li, Xiangju Cheng, Yongcan Chen

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With rapid development of industrialization and urbanization, water environmental deterioration is widespread in majority of urban rivers, which seriously affects city image and life satisfaction of residents. As an emergency measure to improve water quality, clean water diversion is introduced for water environmental management. Lubao River and Southwest River, two urban rivers in typical plain tidal river network, are identified as technically and economically feasible for the application of clean water diversion. One-dimensional hydrodynamic-water quality model is developed to simulate temporal and spatial variations of water level and water quality, with satisfactory accuracy. The mathematical model after calibration is applied to investigate hydrodynamic and water quality variations in rivers as well as determine the optimum operation scheme of water diversion. Assessment system is developed for evaluation of positive and negative effects of water diversion, demonstrating the effectiveness of clean water diversion and the necessity of pollution reduction.

Keywords: assessment system, clean water diversion, hydrodynamic-water quality model, tidal river network, urban rivers, water environment improvement

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Authors: Aniya Everette

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In June of 1971, President Richard Nixon made his first public declaration regarding the “War on Drugs,” deeming it America’s number one public enemy. Since then, the drug war has been a divisive topic in the US. Black and brown children have been unfairly targeted and imprisoned at alarming rates as a result of this policy, which has had a negative effect on them. Black and Latino youth have faced significant obstacles that have impacted their educational opportunities, employment prospects, and general quality of life due to harsh mandatory sentences, aggressive policing tactics, and racial profiling.

Keywords: war, drugs, crime, racial profiling

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Authors: Harvard Najoan, Sarwono Sutikno, Yusep Rosmansyah

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Most enterprises are now using information technology services as their assets to support business objectives. These kinds of services are provided by the internal service provider (inside the enterprise) or external service provider (outside enterprise). To deliver quality information technology services, the service provider (which from now on will be called ‘organization’) either internal or external, must have a standard for service management system. At present, the standard that is recognized as best practice for service management system for the organization is international standard ISO/IEC 20000:2011. The most important part of this international standard is the first part or ISO/IEC 20000-1:2011-Service Management System Requirement, because it contains 22 for organization processes as a requirement to be implemented in an organizational environment in order to build, manage and deliver quality service to the customer. Assessing organization management processes is the first step to implementing ISO/IEC 20000:2011 into the organization management processes. This assessment needs Process Assessment Model (PAM) as an assessment instrument. PAM comprises two parts: Process Reference Model (PRM) and Measurement Framework (MF). PRM is built by transforming the 22 process of ISO/IEC 20000-1:2011 and MF is based on ISO/IEC 33020. This assessment instrument was designed to assess the capability of service management process in Divisi Teknologi dan Sistem Informasi (Information Systems and Technology Division) as an internal organization of PT Pos Indonesia. The result of this assessment model can be proposed to improve the capability of service management system.

Keywords: ISO/IEC 20000-1:2011, ISO/IEC 33020:2015, process assessment, process capability, service management system

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Authors: Frank Papworth, Inam Khan

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Fib’s model code 2020 has four approaches for design life verification. Historically ‘deemed to satisfy provisions have been the principal approach, but this has limited options for materials and covers. The use of an equation in fib’s model code for service life design to predict time to corrosion initiation has become increasingly popular to justify further options, but in some cases, the analysis approaches are incorrect. Even when the equations are computed using full probabilistic analysis, there are common mistakes. This paper reviews the work of recent fib commissions on implementing the service life model to assess the reliability of durability designs, including initiation and propagation periods. The paper goes on to consider the assessment of deemed to satisfy requirements in national codes and considers the influence of various options, including different steel types, various cement systems, quality of concrete and cover, on reliability achieved. As modelling is based on achieving agreed target reliability, consideration is given to how a project might determine appropriate target reliability.

Keywords: chlorides, marine, exposure, design life, reliability, modelling

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Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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Authors: Shewangizaw Tesfaye Wolde

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The current engineering community has developed a method called performance based seismic design in which we design structures based on predefined performance levels set by the parties. Since we design our structures economically for the maximum actions expected in the life of structures they go beyond their elastic limit, in need of nonlinear analysis. In this paper conventional pushover analysis (nonlinear static analysis) is used for the performance assessment of the case study Reinforced Concrete (RC) Frame building located in Addis Ababa City, Ethiopia where proposed peak ground acceleration value by RADIUS 1999 project and others is more than twice as of EBCS-8:1995 (RADIUS 1999 project) by taking critical planar frame. Fiber beam-column model is used to control material nonlinearity with tension stiffening effect. The reliability of the fiber model and validation of software outputs are checked under verification chapter. Therefore, the aim of this paper is to propose a way for structural performance assessment of existing reinforced concrete frame buildings as well as design check.

Keywords: seismic, performance, fiber model, tension stiffening, reinforced concrete

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Authors: Luis Prada, Jose Gomez, Arlex Chaves, Julio Pedraza

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Polymeric liquids have been used in the oil industry, especially at enhanced oil recovery (EOR). From the rheological point of view, polymers have the particularity of being viscoelastic liquids. One of the most common and useful models to describe that behavior is the Upper Convected Maxwell model (UCM). The main characteristic of the polymer used in EOR process is the increase in viscosity which pushes the oil outside of the reservoir. The elasticity could contribute in the drag of the oil that stays in the reservoir. Studying the elastic effect on the oil drop at the pore scale, bring an explanation if the addition of elastic force could mobilize the oil. This research explores if the contraction and expansion of the polymer in the pore scale may increase the elastic behavior of this kind of fluid. For that reason, this work simplified the pore geometry and build two simple geometries with micrometer lengths. Using source terms with the user define a function this work introduces the UCM model in the ANSYS fluent simulator with the purpose of evaluating the elastic effect of the polymer in a contraction and expansion geometry. Also, using the Eulerian multiphase model, this research considers the possibility that extra elastic force will show a deformation effect on the oil; for that reason, this work considers an oil drop on the upper wall of the geometry. Finally, all the simulations exhibit that at the pore scale conditions exist extra vortices at UCM model but is not possible to deform the oil completely and push it outside of the restrictions, also this research find the conditions for the oil displacement.

Keywords: ANSYS fluent, interfacial fluids mechanics, polymers, pore scale, viscoelasticity

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Authors: Marek Długosz, Paweł Skruch

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One of purposes of home automation systems is to provide appropriate comfort to the users by suitable air temperature control and stabilization inside the rooms. The control of temperature level is not a simple task and the basic difficulty results from the fact that accurate parameters of the object of control, that is a building, remain unknown. Whereas the structure of the model is known, the identification of model parameters is a difficult task. In this paper, a control algorithm allowing the present temperature to be reached inside the building within the specified time without the need to know accurate parameters of the building itself is presented.

Keywords: control, home automation system, wireless networking, automation engineering

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Authors: Kim Michelle Siegling, Thomas Spengler, Sebastian Herzog

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In personnel economics, the choice of a leadership style is about the question of how a supervisor should lead his or her employees in such a way that operational goals are achieved. In this paper, it is assumed that such leadership decisions are made according to the situation. Thus, the optimal or at least a permissible leadership style has to be selected from a set of several possible leadership styles. For this choice, a wide range of models has been developed in the scientific literature, from which the so-called normative decision model will be picked out and focused on. While the original model is based on univocal rules, this paper develops a fuzzy rule system.

Keywords: leadership, leadership styles, rule based systems, fuzzy logic

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Authors: V. A. Dubovsky, V. V. Savchenko, A. A. Baryskevich

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The current trend in the automotive industry towards automatic vehicles is creating new challenges related to human factors. This occurs due to the fact that the driver is increasingly relieved of the need to be constantly involved in driving the vehicle, which can negatively impact his/her situation awareness when manual control is required, and decrease driving skills and abilities. These new problems need to be studied in order to provide road safety during the transition towards self-driving vehicles. For this purpose, it is important to develop an appropriate conceptual model of the interaction between the driver and the automated vehicle, which could serve as a theoretical basis for the development of mathematical and simulation models to explore different aspects of driver behaviour in different road situations. Well-known driver behaviour models describe the impact of different stages of the driver's cognitive process on driving performance but do not describe how the driver controls and adjusts his actions. A more complete description of the driver's cognitive process, including the evaluation of the results of his/her actions, will make it possible to more accurately model various aspects of the human factor in different road situations. This paper presents a conceptual model of the 'driver – highly automated vehicle' system based on the P.K. Anokhin's theory of functional systems, which is a theoretical framework for describing internal processes in purposeful living systems based on such notions as goal, desired and actual results of the purposeful activity. A central feature of the proposed model is a dynamic coupling mechanism between the decision-making of a driver to perform a particular action and changes of road conditions due to driver’s actions. This mechanism is based on the stage by stage evaluation of the deviations of the actual values of the driver’s action results parameters from the expected values. The overall functional structure of the highly automated vehicle in the proposed model includes a driver/vehicle/environment state analyzer to coordinate the interaction between driver and vehicle. The proposed conceptual model can be used as a framework to investigate different aspects of human factors in transitions between automated and manual driving for future improvements in driving safety, and for understanding how driver-vehicle interface must be designed for comfort and safety. A major finding of this study is the demonstration that the theory of functional systems is promising and has the potential to describe the interaction of the driver with the vehicle and the environment.

Keywords: automated vehicle, driver behavior, human factors, human-machine system

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Authors: Sandeep, A. Joshi, Kamal, Piu Dhibar, Parveen Kumar

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In the present work strong ground motion has been simulated using a modified semi-empirical technique (MSET), with frequency dependent radiation pattern model. Joshi et al. (2014) have modified the semi-empirical technique to incorporate the modeling of strong motion generation areas (SMGAs). A frequency dependent radiation pattern model is applied to simulate high frequency ground motion more precisely. Identified SMGAs (Kurahashi and Irikura 2012) of the 2011 Tohoku earthquake (Mw 9.0) were modeled using this modified technique. Records are simulated for both frequency dependent and constant radiation pattern function. Simulated records for both cases are compared with observed records in terms of peak ground acceleration and pseudo acceleration response spectra at different stations. Comparison of simulated and observed records in terms of root mean square error suggests that the method is capable of simulating record which matches in a wide frequency range for this earthquake and bears realistic appearance in terms of shape and strong motion parameters. The results confirm the efficacy and suitability of rupture model defined by five SMGAs for the developed modified technique.

Keywords: strong ground motion, semi-empirical, strong motion generation area, frequency dependent radiation pattern, 2011 Tohoku Earthquake

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Authors: Francis O. Nwawuru

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The convergence analysis of split monotone inclusion problems and fixed point problems of certain nonlinear mappings are investigated in the setting of real Hilbert spaces. Inertial extrapolation term in the spirit of Polyak is incorporated to speed up the rate of convergence. Under standard assumptions, a strong convergence of the proposed algorithm is established without computing the resolvent operator or involving Yosida approximation method. The stepsize involved in the algorithm does not depend on the spectral radius of the linear operator. Furthermore, applications of the proposed algorithm in solving some related optimization problems are also considered. Our result complements and extends numerous results in the literature.

Keywords: fixedpoint, hilbertspace, monotonemapping, resolventoperators

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Authors: Norbert W. Paul

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Since a number of years, scientific interest in human resilience is rapidly increasing especially in psychology and more recently and highly visible in neurobiological research. Concepts of resilience are regularly discussed in the light of liminal experiences and existential challenges in human life. Resilience research is providing both, explanatory models and strategies to promote or foster human resilience. Surprisingly, these approaches attracted little attention so far in philosophy in general and in ethics in particular. This is even more astonishing given the fact that the neurosciences as such have been and still are of major interest to philosophy and ethics and even brought about the specialized field of neuroethics, which, however, is not concerned with concepts of resilience, so far. As a result of the little attention given to the topic of resilience, the whole concept has to date been a philosophically under-theorized. This abstinence of ethics and philosophy in resilience research is lamentable because resilience as a concept as well as resilience interventions based on neurobiological findings do undoubtedly pose philosophical, social and ethical questions. In this paper, we will argue that particular notions of resilience are crossing the sometimes fine line between maintaining a person’s mental health despite the impact of severe psychological or physical adverse events and ethically more debatable discourses of enhancement. While we neither argue for or against enhancement nor re-interpret resilience research and interventions by subsuming them strategies of psychological and/or neuro-enhancement, we encourage those who see social or ethical problems with enhancement technologies should also take a closer look on resilience and the related neurobiological concepts. We will proceed in three steps. In our first step, we will describe the concept of resilience in general and its neurobiological study in particular. Here, we will point out some important differences in the way ‘resilience’ is conceptualized and how neurobiological research understands resilience. In what follows we will try to show that a one-sided concept of resilience – as it is often presented in neurobiological research on resilience – does pose social and ethical problems. Secondly, we will identify and explore the social and ethical challenges of (neurobiological) enhancement. In the last and final step of this paper, we will argue that a one-sided reading of resilience can be understood as latent form of enhancement in transition and poses ethical questions similar to those discussed in relation to other approaches to the biomedical enhancement of humans.

Keywords: resilience, neurosciences, epistemology, bioethics

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we propose a new approach to coverage control problem by using adaptive coordination and power aware control laws. Nonholonomic mobile nodes position themselves suboptimally according to a time-varying density function using Centroidal Voronoi Tesellations. The Lyapunov stability analysis of the adaptive and decentralized approach is given. A linear consensus protocol is used to establish synchronization among the mobile nodes. Also, repulsive forces prevent nodes from collision. Simulation results show that by using power aware control laws, energy consumption of the nodes can be reduced.

Keywords: power aware, coverage control, adaptive, consensus, nonholonomic, coordination

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Authors: Taha Benarbia, Kay W. Axhausen, Anugrah Ilahi

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Electric car sharing system as ecologic transportation increasing in the world. The complexity of managing electric car sharing systems, especially one-way trips and battery autonomy have direct influence to on supply and demand of system. One must be able to precisely model the demand and supply of these systems to better operate electric car sharing and estimate its effect on mobility management and the accessibility that it provides in urban areas. In this context, our work focus to develop performances optimization model of the system based on discrete event simulation and stochastic Petri net. The objective is to search optimal decisions and management parameters of the system in order to fulfil at best demand while minimizing undesirable situations. In this paper, we present new model of electric cars sharing with relocation based on monitoring system. The proposed approach also help to precise the influence of battery charging level on the behaviour of system as important decision parameter of this complex and dynamical system.

Keywords: electric car-sharing systems, smart mobility, Petri nets modelling, discrete event simulation

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Authors: Jing-Jing Wang, Yang Gao, Heather H. M. Kwok, Wendy Y. J. Huang

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Objectives: Intellectual disability (ID) ranks among the top 20 most costly disorders. A child with ID creates a wide set of challenges to the individual, family, and society, and overweight and obesity aggravate those challenges. People with ID have the right to attain optimal health like the rest of the population. They should be given priority to eliminate existing health inequities. Childhood obesity epidemic and associated factors among children, in general, has been well documented, while knowledge about overweight and obesity in children with ID is scarce. Methods: A cross-sectional study was conducted among 524 Chinese children with ID (males: 68.9%, mean age: 12.2 years) in Hong Kong in 2015. Children’s height and weight were measured at school. Parents, in the presence of their children, completed a self-administered questionnaire at home about the children’s physical activity (PA), eating habits, and sleep duration in a typical week as well as parenting practices regarding children’s eating and PA, and their socio-demographic characteristics. Multivariate logistic regression estimated the potential risk factors for children being overweight. Results: The prevalence of overweight and obesity in children with ID was 31.3%, which was higher than their general counterparts (18.7%-19.9%). Multivariate analyses revealed that the risk factors of overweight and obese in children with ID included: comorbidity with autism, the maternal side being overweight or obese, parenting practices with less pressure to eat more, children having shorter sleep duration, longer periods of sedentary behavior, and higher intake frequencies of sweetened food, fried food, and meats, fish, and eggs. Children born in other places, having snacks more frequently, and having irregular meals were also more likely to be overweight or obese, with marginal significance. Conclusions: Children with ID are more vulnerable to being overweight or obese than their typically developing counterparts. Identified risk factors in this study highlight a multifaceted approach to the involvement of parents as well as the modification of some children’s questionable behaviors to help them achieve a healthy weight.

Keywords: prevalence, risk factors, obesity, children with disability

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: apartment complex, big data, life-cycle building value analysis, machine learning

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

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Authors: Ismail Halijah, Abdullah Rusli

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Introduction: This systematic literature review aims to identify the Knowledge Management Best Practice components in the Knowledge Management Model for Higher Learning Institutions environment. Study design: Systematic literature review. Methods: A systematic literature re-view of Knowledge Management Best Practice to identify and define the components of Best Practice from the Knowledge Management models was conducted recently. Results: This review of published papers of conference and journals’ articles shows the components of Best Practice in Knowledge Management are basically divided into two aspect which is the soft aspect and the hard aspect. The lacks of combination of these two aspects into an integrated model decelerate Knowledge Management Best Practice to fully throttle. Evidence from the literature shows the lack of integration of this two aspects leads to the immaturity of the Higher Learning Institution (HLI) towards the implementation of Knowledge Management System. Conclusion: The first steps of identifying the attributes to measure the Knowledge Management Best Practice components from the models in the literature will led to the definition of the Knowledge Management Best Practice component for the higher learning environment.

Keywords: knowledge management, knowledge management system, knowledge management best practice, knowledge management higher learning institution

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Authors: Maria Francesca Scannone, Martina Bochicchio

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One of the major environmental problems today is hydrocarbon contamination. The promising sustainable technologies for the treatment of these contaminated sites involves the use of biological organisms. In Agri Valley (Basilicata Region) there is a living laboratory (natural oil seeps) where the selective pressure has enriched the environmental matrices with microorganisms, fungi and plant species able to use the hydrocarbons as a source of metabolic energy, to degrade or tolerate hydrocarbons. Observers visiting this area are fascinated by its unspoiled nature, and the condition of the ecosystem does not appear to has been damaged. The amazing resiliency observed in Tramutola site is of key importance to try to bring green remediation technologies, but no research has been done to identify high-performing native species. The aim of this research was to study how natural processes affect the fate of released oil or how individual species or communities of plants and animals are capable of dealing with the burden of otherwise toxic chemicals. The survey of vegetation was carried out, more than 60 species have been identified and divided into tree, shrub and herb layer. Plant data sheets have been completed only for the species that showed the most appropriate properties for phytoremediation. In general, members of the Salicales, Cyperales, Poales, Fagales, Cornales, Equisetales orders were the most commonly identified orders. They are pioneer plants with high adaptive capacity and vegetative propagation. The literature review has highlighted the existence of rhizosphere effect and a green liver model on selected plants. The study provides significant information on the environmental stress adaptation processes of many indigenous plants that are living and growing on a natural leak of crude oil and gas that migrates up through subsurface.

Keywords: green liver, hydrocarbon degradation, oil seeps, phytoremediation

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Authors: Wu Qinglong, Zhou Qicai, Xiong Xiaolei, Zhang Richeng

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In order to achieve the layout and size optimization of the web members of tower crane boom, a truss topology and cross section size optimization method based on continuum is proposed considering three typical working conditions. Firstly, the optimization model is established by replacing web members with web plates. And the web plates are divided into several sub-domains so that periodic soft kill option (SKO) method can be carried out for topology optimization of the slender boom. After getting the optimized topology of web plates, the optimized layout of web members is formed through extracting the principal stress distribution. Finally, using the web member radius as design variable, the boom compliance as objective and the material volume of the boom as constraint, the cross section size optimization mathematical model is established. The size optimization criterion is deduced from the mathematical model by Lagrange multiplier method and Kuhn-Tucker condition. By comparing the original boom with the optimal boom, it is identified that this optimization method can effectively lighten the boom and improve its performance.

Keywords: tower crane boom, topology optimization, size optimization, periodic, SKO, optimization criterion

Procedia PDF Downloads 547

Authors: Taiebe Shokri, Shahram Yazdani, Leila Afshar, Soleiman Ahmadi

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Introduction: The importance of professionalism in higher education not only determines the appropriate and inappropriate behaviors and guides faculty members in the implementation of professional responsibilities, but also guarantees faculty members' adherence to professional principles and values, ensures the quality of teaching and facilitator will be the teaching-learning process in universities and will increase the commitment to meet the needs of students as well as the development of an ethical culture based on ethics. Therefore, considering the important role of medical education teachers to prepare teachers and students in the future, the need to determine the concept of professional teacher and teacher, and the characteristics of teacher professionalism, we have explained the concept of professionalism in teachers in this study. Methods: The concept analysis method used in this study was Walker and Avant method which has eight steps. Walker and Avant state the purpose of concept analysis as follows: The process of distinguishing between the defining features of a concept and its unrelated features. The process of concept analysis includes selecting a concept, determining the purpose of the analysis, identifying the uses of the concept, determining the defining features of the concept, identifying a model, identifying boundary and adversarial items, identifying the precedents and consequences of the concept, and defining empirical references. is. Results: Professionalism in its general sense, requires deep knowledge, insight, creating a healthy and safe environment, honesty and trust, impartiality, commitment to the profession and continuous improvement, punctuality, criticism, professional competence, responsibility, and Individual accountability, especially in social interactions, is an effort for continuous improvement, the acquisition of these characteristics is not easily possible and requires education, especially continuous learning. Professionalism is a set of values, behaviors, and relationships that underpin public trust in teachers.

Keywords: concept analysis, medical education, professionalism, faculty members

Procedia PDF Downloads 145