Search results for: structural model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19671

Search results for: structural model

16671 Edmonton Urban Growth Model as a Support Tool for the City Plan Growth Scenarios Development

Authors: Sinisa J. Vukicevic

Abstract:

Edmonton is currently one of the youngest North American cities and has achieved significant growth over the past 40 years. Strong urban shift requires a new approach to how the city is envisioned, planned, and built. This approach is evidence-based scenario development, and an urban growth model was a key support tool in framing Edmonton development strategies, developing urban policies, and assessing policy implications. The urban growth model has been developed using the Metronamica software platform. The Metronamica land use model evaluated the dynamic of land use change under the influence of key development drivers (population and employment), zoning, land suitability, and land and activity accessibility. The model was designed following the Big City Moves ideas: become greener as we grow, develop a rebuildable city, ignite a community of communities, foster a healing city, and create a city of convergence. The Big City Moves were converted to three development scenarios: ‘Strong Central City’, ‘Node City’, and ‘Corridor City’. Each scenario has a narrative story that expressed scenario’s high level goal, scenario’s approach to residential and commercial activities, to transportation vision, and employment and environmental principles. Land use demand was calculated for each scenario according to specific density targets. Spatial policies were analyzed according to their level of importance within the policy set definition for the specific scenario, but also through the policy measures. The model was calibrated on the way to reproduce known historical land use pattern. For the calibration, we used 2006 and 2011 land use data. The validation is done independently, which means we used the data we did not use for the calibration. The model was validated with 2016 data. In general, the modeling process contain three main phases: ‘from qualitative storyline to quantitative modelling’, ‘model development and model run’, and ‘from quantitative modelling to qualitative storyline’. The model also incorporates five spatial indicators: distance from residential to work, distance from residential to recreation, distance to river valley, urban expansion and habitat fragmentation. The major finding of this research could be looked at from two perspectives: the planning perspective and technology perspective. The planning perspective evaluates the model as a tool for scenario development. Using the model, we explored the land use dynamic that is influenced by a different set of policies. The model enables a direct comparison between the three scenarios. We explored the similarities and differences of scenarios and their quantitative indicators: land use change, population change (and spatial allocation), job allocation, density (population, employment, and dwelling unit), habitat connectivity, proximity to objects of interest, etc. From the technology perspective, the model showed one very important characteristic: the model flexibility. The direction for policy testing changed many times during the consultation process and model flexibility in applying all these changes was highly appreciated. The model satisfied our needs as scenario development and evaluation tool, but also as a communication tool during the consultation process.

Keywords: urban growth model, scenario development, spatial indicators, Metronamica

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16670 Developing a Knowledge-Based Lean Six Sigma Model to Improve Healthcare Leadership Performance

Authors: Yousuf N. Al Khamisi, Eduardo M. Hernandez, Khurshid M. Khan

Abstract:

Purpose: This paper presents a model of a Knowledge-Based (KB) using Lean Six Sigma (L6σ) principles to enhance the performance of healthcare leadership. Design/methodology/approach: Using L6σ principles to enhance healthcare leaders’ performance needs a pre-assessment of the healthcare organisation’s capabilities. The model will be developed using a rule-based approach of KB system. Thus, KB system embeds Gauging Absence of Pre-requisite (GAP) for benchmarking and Analytical Hierarchy Process (AHP) for prioritization. A comprehensive literature review will be covered for the main contents of the model with a typical output of GAP analysis and AHP. Findings: The proposed KB system benchmarks the current position of healthcare leadership with the ideal benchmark one (resulting from extensive evaluation by the KB/GAP/AHP system of international leadership concepts in healthcare environments). Research limitations/implications: Future work includes validating the implementation model in healthcare environments around the world. Originality/value: This paper presents a novel application of a hybrid KB combines of GAP and AHP methodology. It implements L6σ principles to enhance healthcare performance. This approach assists healthcare leaders’ decision making to reach performance improvement against a best practice benchmark.

Keywords: Lean Six Sigma (L6σ), Knowledge-Based System (KBS), healthcare leadership, Gauge Absence Prerequisites (GAP), Analytical Hierarchy Process (AHP)

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16669 Currency Exchange Rate Forecasts Using Quantile Regression

Authors: Yuzhi Cai

Abstract:

In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: combining forecasts, MCMC, predictive density functions, quantile forecasting, quantile modelling

Procedia PDF Downloads 252
16668 New Moment Rotation Model of Single Web Angle Connections

Authors: Zhengyi Kong, Seung-Eock Kim

Abstract:

Single angle connections, which are bolted to the beam web and the column flange, are studied to investigate moment-rotation behavior. Elastic–perfectly plastic material behavior is assumed. ABAQUS software is used to analyze the nonlinear behavior of a single angle connection. The same geometric and material conditions with Yanglin Gong’s test are used for verifying finite element models. Since Kishi and Chen’s Power model and Lee and Moon’s Log model are accurate only for a limited range, simpler and more accurate hyperbolic function models are proposed. The equation for calculating rotation at ultimate moment is first proposed.

Keywords: finite element method, moment and rotation, rotation at ultimate moment, single-web angle connections

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16667 A Ground Structure Method to Minimize the Total Installed Cost of Steel Frame Structures

Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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16666 Character Education Model for Early Childhood Based Javanese Culture

Authors: Rafika Bayu Kusumandari, Istyarini, Ispen Safrel

Abstract:

Character education will be more meaningful if carried out since early childhood. This is because early childhood education is the foundation of the formation of character. This study intends to find a model of character education in early childhood based on Javanese culture. In keeping with the focus of the study, long-term goals to be achieved through this research is to find once described the development of a model of character education in early childhood Javanese culture based in Semarang are then applied across early childhood education institutions in Semarang City. The specific objective of the study is: Describe the character models and management education in early childhood Java-based culture in Semarang City. The benefits of this research are; Provide an overview of the model and describe the management of character education in early childhood Java-based culture in Semarang City. Referring to the objectives of the research program was designed with a "Research and Development", meaning that a program of research followed by development programs for improvement or refinement. To produce a prototype model of character education in early childhood Java-based culture in the city, taken systematic measures in the form of the action, reflection, evaluation and innovation by applying qualitative research methods, descriptive, development, experimentation, and evaluation. This study aims to gain in-depth description of the model of character education in early childhood Java-based culture in the city of Semarang. The reason for the use of the use of qualitative methods researcher's knowledge, no study results and empirical research specifically about the model of character education in early childhood Java-based culture in the city of Semarang. On the implementation of character education early childhood adapted to the characteristics of each school and the emphasis of each agency arrangements for early childhood education, culture-based Java. Javanese culture should be introduced early in order not to erode the cultural lost outside the entrance as the era of globalization. In addition, Java is promoting a culture of courtesy and manners are very appropriate for the character formation of children of early age.

Keywords: education character, Javanese culture, childhood, character

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16665 3D Model Completion Based on Similarity Search with Slim-Tree

Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

Abstract:

With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

Procedia PDF Downloads 117
16664 Impact of Welding Distortion on the Design of Fabricated T-Girders Using Finite Element Modeling

Authors: Ahmed Hammad, Yehia Abdel-Nasser, Mohamed Shamma

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The main configuration of ship construction consists of standard and fabricated stiffening members which are commonly used in shipbuilding such as fabricated T-sections. During the welding process, the non-uniform heating and rapid cooling lead to the inevitable presence of out-of-plane distortion and welding induced residual stresses. Because of these imperfections, the fabricated structural members may not attain their design load to be carried. The removal of these imperfections will require extra man-hours. In the present work, controlling these imperfections has been investigated at both design and fabrication stages. A typical fabricated T-girder is selected to investigate the problem of these imperfections using double-side welding. A numerical simulation based on finite element (FE) modeling has been used to investigate the effect of different parameters of the selected fabricated T-girder such as geometrical properties and welding sequences on the magnitude of welding imperfections. FE results were compared with the results of experimental model of a double-side fillet weld. The present work concludes that: Firstly, in the design stage, the optimum geometry of the fabricated T- girder is determined based on minimum steel weight and out- of- plane distortion. Secondly, in the fabrication stage, the best welding sequence is determined on the basis of minimum welding out- of- plane distortion.

Keywords: fabricated T-girder, FEM, out-of-plane distortion, section modulus, welding residual stresses

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16663 Classifying Students for E-Learning in Information Technology Course Using ANN

Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

Abstract:

This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

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16662 On the Well-Posedness of Darcy–Forchheimer Power Model Equation

Authors: Johnson Audu, Faisal Fairag

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In a bounded subset of R^d, d=2 or 3, we consider the Darcy-Forchheimer power model with the exponent 1 < m ≤ 2 for a single-phase strong-inertia fluid flow in a porous medium. Under necessary compatibility condition, and some mild regularity assumptions on the interior and the boundary data, we prove the existence and uniqueness of solution (u, p) in L^(m+1 ) (Ω)^d X (W^(1,(m+1)/m) (Ω)^d ⋂L_0^2 (Ω)^d) and its stability.

Keywords: porous media, power law, strong inertia, nonlinear, monotone type

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16661 Sentiment Analysis of Fake Health News Using Naive Bayes Classification Models

Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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16660 Torrefaction of Biomass Pellets: Modeling of the Process in a Fixed Bed Reactor

Authors: Ekaterina Artiukhina, Panagiotis Grammelis

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Torrefaction of biomass pellets is considered as a useful pretreatment technology in order to convert them into a high quality solid biofuel that is more suitable for pyrolysis, gasification, combustion and co-firing applications. In the course of torrefaction the temperature varies across the pellet, and therefore chemical reactions proceed unevenly within the pellet. However, the uniformity of the thermal distribution along the pellet is generally assumed. The torrefaction process of a single cylindrical pellet is modeled here, accounting for heat transfer coupled with chemical kinetics. The drying sub-model was also introduced. The non-stationary process of wood pellet decomposition is described by the system of non-linear partial differential equations over the temperature and mass. The model captures well the main features of the experimental data.

Keywords: torrefaction, biomass pellets, model, heat, mass transfer

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16659 Building Organisational Culture That Stimulates Creativity and Innovation

Authors: Ala Hanetite

Abstract:

The purpose of this article is to present, by means of a model, the determinants of organisational culture which influence creativity and innovation. A literature study showed that a model, based on the open systems theory and the work of Schein, can offer a holistic approach in describing organisational culture. The relationship between creativity, innovation and culture is discussed in this context. Against the background of this model, the determinants of organisational culture were identified. The determinants are strategy, structure, support mechanisms, behaviour that encourages innovation, and open communication. The influence of each determinant on creativity and innovation is discussed. Values, norms and beliefs that play a role in creativity and innovation can either support or inhibit creativity and innovation depending on how they influence individual and group behaviour. This is also explained in the article.

Keywords: attitudes, creativity, innovation, organisational culture

Procedia PDF Downloads 584
16658 GraphNPP: A Graphormer-Based Architecture for Network Performance Prediction in Software-Defined Networking

Authors: Hanlin Liu, Hua Li, Yintan AI

Abstract:

Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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16657 The Quality Improvement of Painting Assignments for Grade 4-6 Students by Using PDCA Cycle

Authors: Pawinee Sorawech

Abstract:

The purpose of this study was to investigate the quality improvement of painting assignments for grade 4-6 students by using PDCA cycle. This study employed a qualitative technique. Suan Sunandha Rajabhat University and its demonstration school were selected as the area of study. An in-depth interview was utilized. The findings revealed that model of PDCA cycle was a proper model to increase the quality of painting assignments for grade 4-6 students. The six steps of improvement included: studying the PDCA model, setting up a plan, determining the scope of work, creating a strategy, developing a quality for painting assignment, and coming up with a handbook for a quality improvement of painting assignment.

Keywords: quality, painting assignments, PDCA cycle, grade 4-6 students

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16656 A Transient Coupled Numerical Analysis of the Flow of Magnetorheological Fluids in Closed Domains

Authors: Wael Elsaady, S. Olutunde Oyadiji, Adel Nasser

Abstract:

The non-linear flow characteristics of magnetorheological (MR) fluids in MR dampers are studied via a coupled numerical approach that incorporates a two-phase flow model. The approach couples the Finite Element (FE) modelling of the damper magnetic circuit, with the Computational Fluid Dynamics (CFD) analysis of the flow field in the damper. The two-phase flow CFD model accounts for the effect of fluid compressibility due to the presence of liquid and gas in the closed domain of the damper. The dynamic mesh model included in ANSYS/Fluent CFD solver is used to simulate the movement of the MR damper piston in order to perform the fluid excitation. The two-phase flow analysis is studied by both Volume-Of-Fluid (VOF) model and mixture model that are included in ANSYS/Fluent. The CFD models show that the hysteretic behaviour of MR dampers is due to the effect of fluid compressibility. The flow field shows the distributions of pressure, velocity, and viscosity contours. In particular, it shows the high non-Newtonian viscosity in the affected fluid regions by the magnetic field and the low Newtonian viscosity elsewhere. Moreover, the dependence of gas volume fraction on the liquid pressure inside the damper is predicted by the mixture model. The presented approach targets a better understanding of the complicated flow characteristics of viscoplastic fluids that could be applied in different applications.

Keywords: viscoplastic fluid, magnetic FE analysis, computational fluid dynamics, two-phase flow, dynamic mesh, user-defined functions

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16655 Using Flow Line Modelling, Remote Sensing for Reconstructing Glacier Volume Loss Model for Athabasca Glacier, Canadian Rockies

Authors: Rituparna Nath, Shawn J. Marshall

Abstract:

Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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16654 Numerical Investigation of the Electromagnetic Common Rail Injector Characteristics

Authors: Rafal Sochaczewski, Ksenia Siadkowska, Tytus Tulwin

Abstract:

The paper describes the modeling of a fuel injector for common rail systems. A one-dimensional model of a solenoid-valve-controlled injector with Valve Closes Orifice (VCO) spray was modelled in the AVL Hydsim. This model shows the dynamic phenomena that occur in the injector. The accuracy of the calibration, based on a regulation of the parameters of the control valve and the nozzle needle lift, was verified by comparing the numerical results of injector flow rate. Our model is capable of a precise simulation of injector operating parameters in relation to injection time and fuel pressure in a fuel rail. As a result, there were made characteristics of the injector flow rate and backflow.

Keywords: common rail, diesel engine, fuel injector, modeling

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16653 Physical-Mechanical Characteristics of Monocrystalline Si1-xGex(X 0,02) Solid Solutions

Authors: I. Kurashvili, A. Sichinava, G. Bokuchava, G. Darsavelidze

Abstract:

Si-Ge solid solutions (bulk poly- and monocrystalline samples, thin films) are characterized by high perspectives for application in semiconductor devices, in particular, optoelectronics and microelectronics. In this light complex studying of structural state of the defects and structural-sensitive physical properties of Si-Ge solid solutions depending on the contents of Si and Ge components is very important. Present work deals with the investigations of microstructure, electrophysical characteristics, microhardness, internal friction and shear modulus of Si1-xGex(x≤0,02) bulk monocrystals conducted at a room temperatures. Si-Ge bulk crystals were obtained by Czochralski method in [111] crystallographic direction. Investigated monocrystalline Si-Ge samples are characterized by p-type conductivity and carriers concentration 5.1014-1.1015cm-3, dislocation density 5.103-1.104cm-2, microhardness according to Vickers method 900-1200 Kg/mm2. Investigate samples are characterized with 0,5x0,5x(10-15) mm3 sizes, oriented along [111] direction at torsion oscillations ≈1Hz, multistage changing of internal friction and shear modulus has been revealed in an interval of strain amplitude of 10-5-5.10-3. Critical values of strain amplitude have been determined at which hysteretic changes of inelastic characteristics and microplasticity are observed. The critical strain amplitude and elasticity limit values are also determined. Tendency to decrease of dynamic mechanical characteristics is shown with increasing Ge content in Si-Ge solid solutions. Observed changes are discussed from the point of view of interaction of various dislocations with point defects and their complexes in a real structure of Si-Ge solid solutions.

Keywords: Microhardness, internal friction, shear modulus, Monocrystalline

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16652 Two Layer Photo-Thermal Deflection Model to Investigate the Electronic Properties in BGaAs/GaAs Alloys

Authors: S. Ilahi, M. Baira, F. Saidi, N. Yacoubi, L. Auvray, H. Maaref

Abstract:

Photo-thermal deflection technique (PTD) is used to study the nonradiative recombination process in BGaAs/GaAs alloy with boron composition of 3% and 8% grown by metal organic chemical vapor deposition (MOCVD). A two layer theoretical model has been developed taking into account both thermal and electronic contribution in the photothermal signal allowing to extract the electronic parameters namely electronic diffusivity, surface and interface recombination. It is found that the increase of boron composition alters the BGaAs epilayers transport properties.

Keywords: photothermal defelction technique, two layer model, BGaAs/GaAs alloys, boron composition

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16651 Numerical Homogenization of Nacre

Authors: M. Arunachalam, M. Pandey

Abstract:

Nacre, a biological material that forms the inner-layer of sea shells can achieve high toughness and strength by way of staggered arrangement of strong tablets with soft and weak organic interface. Under applied loads the tablets slide over the adjacent tablets, thus generating inelastic deformation and toughness on macroscopic scale. A two dimensional finite element based homogenization methodology is adopted for obtaining the effective material properties of Nacre using a representative volume element (RVE) at finite deformations. In this work, the material behaviour for tablet and interface are assumed to be Isotropic elastic and Isotropic elastic-perfectly plastic with strain softening respectively. Numerical experiments such as uniaxial tension test along X, Y directions and simple shear test are performed on the RVE with uniform displacement and periodic constraints applied at the RVE boundaries to obtain the anisotropic homogenized response and maximum local stresses within each constituents of Nacre. Homogenized material model is then tested for macroscopic structure under three point bending condition and the results obtained are comparable with the results obtained for detailed microstructure based structure, thus homogenization provides a bridge between macroscopic scale and microscopic scale and homogenized material properties obtained from microstructural (RVE) analysis could be used in large scale structural analysis.

Keywords: finite element, homogenization, inelastic deformation, staggered arrangement

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16650 Dow Polyols near Infrared Chemometric Model Reduction Based on Clustering: Reducing Thirty Global Hydroxyl Number (OH) Models to Less Than Five

Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

Abstract:

Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

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16649 Control HVAC Parameters by Brain Emotional Learning Based Intelligent Controller (BELBIC)

Authors: Javad Abdi, Azam Famil Khalili

Abstract:

Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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16648 A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images

Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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16647 The Effect of the Structural Arrangement of Binary Bisamide Organogelators on their Self-Assembly Behavior

Authors: Elmira Ghanbari, Jan Van Esch, Stephen J. Picken, Sahil Aggarwal

Abstract:

Low-molecular-weight organogelators form gels by self-assembly into the crystalline network which immobilizes the organic solvent. For single bisamide organogelator systems, the effect of the molecular structure on the molecular interaction and their self-assembly behavior has been explored. The spatial arrangement of bisamide molecules in the gel-state is driven by a combination of hydrogen bonding and Van der Waals interactions. The hydrogen-bonding pattern between the amide groups of bisamide molecules is regulated by the number of methylene spacers; the even number of methylene spacers between two amide groups, in even-spaced bisamides, leads to the antiparallel position of amide groups within a molecule. An even-spaced bisamide molecule with antiparallel amide groups can make two pairs of hydrogen bonding with the molecules on the same plane. The odd-spaced bisamide with a parallel directionality of amide groups can form four independent hydrogen bonds with four other bisamide molecules on different planes. The arrangement of bisamide molecules in the crystalline state and the interaction of these molecules depends on the molecular structure, particularly the parity of the spacer length between the amide groups in the bisamide molecule. In this study, the directionality of amide groups has been exploited as a structural characteristic to affect the arrangement of molecules in the crystalline state and produce different binary bisamide gelators with different degrees of crystallinities. Single odd- and even-spaced single bisamides were synthesized and blended to produce binary bisamide organogelators to be characterized in order to understand the effect of the different directionality of amide groups on the molecular interaction in the crystalline state. The pattern of molecular interactions between these blended molecules, mixing or phase separation, has been monitored via differential scanning calorimetry (DSC) and crystallography techniques; X-ray powder diffraction (XRD) and Small-angle X-ray scattering (SAXS). The formation of lamellar structures for odd- and even-spaced bisamide gelators was confirmed by using SAXS and XRD techniques. DSC results have shown that binary bisamide organogelators with different parity of methylene spacers (odd-even binary blends) have a higher tendency for phase separation compared to the binary bisamides with the same parity (odd-odd or even-even binary blends). Phase separation in binary odd-even bisamides was confirmed by the presence of individual (100) reflections of odd and even lamellar structures. The structural characteristic of bisamide organogelators, the parity of spacer length in binary systems, is a promising tool to control the arrangement of molecules and their crystalline structure.

Keywords: binary bisamide organogelators, crystalline structure, phase separation, self-assembly behavior

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16646 The Significance of Intellectual Capital and Strategic Orientations on Innovation Capability in Malaysian ICTSMEs

Authors: Juliana Osman, David Gilbert, Caroline Tan

Abstract:

Innovation capability is recognized as a critical factor that contributes to promoting firm growth and wealth creation. While studies on innovation are in abundance, few empirical studies have been undertaken to examine the relationships of intellectual capital with innovation capability, and research investigating the combinations of strategic orientation dimensions is limited and virtually nothing in regard to the Malaysian context. This research investigates the impact of intellectual capital and three strategic orientations on the innovation capability and firm performance of Malaysian ICT SMEs. Data was collected from 213 firms relating to intellectual capital and the three strategic orientations; market orientation, learning orientation and technology orientation. Using partial least squares structural equation modelling (PLS-SEM) to analyse the data, results indicate that while market orientation has a direct negative relationship to firm performance, it is positively related to performance through the mediating effect of innovation capability. Learning orientation and technology orientation are mediated by innovation capability, while intellectual capital was found to be partially mediated by innovation capability. Findings indicate that firm performance is positively and significantly related to innovation capability and that market orientation, learning orientation, technology orientation and intellectual capital are all significant and positively related to innovation capability. The developed model indicates that Malaysian ICT SMEs would perform better with greater emphasis on developing innovation capability through enhancement of intellectual capital and the strategic orientations measured in this study.

Keywords: innovation capability, intellectual capital, strategic orientations, PLS-SEM

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16645 Bracing Applications for Improving the Earthquake Performance of Reinforced Concrete Structures

Authors: Diyar Yousif Ali

Abstract:

Braced frames, besides other structural systems, such as shear walls or moment resisting frames, have been a valuable and effective technique to increase structures against seismic loads. In wind or seismic excitations, diagonal members react as truss web elements which would afford tension or compression stresses. This study proposes to consider the effect of bracing diagonal configuration on values of base shear and displacement of building. Two models were created, and nonlinear pushover analysis was implemented. Results show that bracing members enhance the lateral load performance of the Concentric Braced Frame (CBF) considerably. The purpose of this article is to study the nonlinear response of reinforced concrete structures which contain hollow pipe steel braces as the major structural elements against earthquake loads. A five-storey reinforced concrete structure was selected in this study; two different reinforced concrete frames were considered. The first system was an un-braced frame, while the last one was a braced frame with diagonal bracing. Analytical modelings of the bare frame and braced frame were realized by means of SAP 2000. The performances of all structures were evaluated using nonlinear static analyses. From these analyses, the base shear and displacements were compared. Results are plotted in diagrams and discussed extensively, and the results of the analyses showed that the braced frame was seemed to capable of more lateral load carrying and had a high value for stiffness and lower roof displacement in comparison with the bare frame.

Keywords: reinforced concrete structures, pushover analysis, base shear, steel bracing

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16644 Association Between Short-term NOx Exposure and Asthma Exacerbations in East London: A Time Series Regression Model

Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker

Abstract:

Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.

Keywords: air pollution, time series modeling, public health, road transport

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16643 Early Evaluation of Long-Span Suspension Bridges Using Smartphone Accelerometers

Authors: Ekin Ozer, Maria Q. Feng, Rupa Purasinghe

Abstract:

Structural deterioration of bridge systems possesses an ongoing threat to the transportation networks. Besides, landmark bridges’ integrity and safety are more than sole functionality, since they provide a strong presence for the society and nations. Therefore, an innovative and sustainable method to inspect landmark bridges is essential to ensure their resiliency in the long run. In this paper, a recently introduced concept, smartphone-based modal frequency estimation is addressed, and this paper targets to authenticate the fidelity of smartphone-based vibration measurements gathered from three landmark suspension bridges. Firstly, smartphones located at the bridge mid-span are adopted as portable and standalone vibration measurement devices. Then, their embedded accelerometers are utilized to gather vibration response under operational loads, and eventually frequency domain characteristics are deduced. The preliminary analysis results are compared with the reference publications and high-quality monitoring data to validate the usability of smartphones on long-span landmark suspension bridges. If the technical challenges such as high period of vibration, low amplitude excitation, embedded smartphone sensor features, sampling, and citizen engagement are tackled, smartphones can provide a novel and cost-free crowdsourcing tool for maintenance of these landmark structures. This study presents the early phase findings from three signature structures located in the United States.

Keywords: smart and mobile sensing, structural health monitoring, suspension bridges, vibration analysis

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16642 Level Set Based Extraction and Update of Lake Contours Using Multi-Temporal Satellite Images

Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

Abstract:

The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

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