Search results for: cluster model approach

Authors: Abeer Amayri, Akif A. Bulgak

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Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.

Keywords: global supply chains, quality, stochastic programming, supplier selection

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Authors: S. H. Park, D. W. You

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This study is about to the field survey and repair works in a marine approach-bride. In order to evaluate the stability of the ground and the structure, field surveys such as exterior inspection, non-destructive inspection, measurement, and geophysical exploration are carried out. Numerical analysis is conducted to investigate the cause of the abutment displacement at the same time. In addition, repair works are practiced to the region damaged with intent to sustain long-term safety.

Keywords: field survey, expansion joint, repair, maintenance

Procedia PDF Downloads 280

Authors: Francisca Alves, Diana Figueiredo, Paula Vagos, Luiza Lima, Maria do Céu Salvador, Daniel Rijo

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In recent years, Acceptance and Commitment Therapy (ACT) has been shown to be effective in the treatment of numerous anxiety disorders, including social anxiety disorder (SAD). However, limited evidence exists on its therapeutic gains for adolescents with SAD. The current work presents a weekly 10-session manualized online ACT approach to adolescent SAD, being the first study to do so in a clinical sample of adolescents. The intervention ACT@TeenSAD addresses the six proposed processes of psychological inflexibility (i.e., experiential avoidance, cognitive fusion, lack of values clarity, unworkable action, dominance of the conceptualized past and future, attachment to the conceptualized self) in social situations relevant to adolescents (e.g., doing a presentation). It is organized into four modules. The first module explores the role of psychological (in)flexibility in SAD (session 1 and 2), addressing psychoeducation (i.e., functioning of the mind) according to ACT, the development of an individualized model, and creative hopelessness. The second module focuses on the foundation of psychological flexibility (session 3, 4, and 5), specifically on the development and practice of strategies to promote clarification of values, contact with the present moment, the observing self, defusion, and acceptance. The third module encompasses psychological flexibility in action (sessions 6, 7, 8, and 9), encouraging committed action based on values in social situations relevant to the adolescents. The fourth modules’ focus is the revision of gains and relapse prevention (session 10). This intervention further includes two booster sessions after therapy has ended (3 and 6-month follow-up) that aim to review the continued practice of learned abilities and to plan for their future application to potentially anxious social events. As part of an ongoing clinical trial, the intervention will be assessed on its feasibility with adolescents diagnosed with SAD and on its therapeutic efficacy based on a longitudinal design including pretreatment, posttreatment, 3 and 6-month follow-up. If promising, findings may support the online delivery of ACT interventions for SAD, contributing to increased treatment availability to adolescents. This availability of an effective therapeutic approach will be helpful not only in relation to adolescents who face obstacles (e.g., distance) when attending to face-to-face sessions but also particularly to adolescents with SAD, who are usually more reluctant to look for specialized treatment in public or private health facilities.

Keywords: acceptance and commitment therapy, social anxiety disorder, adolescence, manualized online approach

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Authors: Raouf Fareh, Maarouf Saad, Sofiane Khadraoui, Tamer Rabie

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This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.

Keywords: mobile robot, trajectory tracking, Lyapunov, stability

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Sai-Kit Choi

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While traditional social services heavily depended on Government funding and support, there were always time lag, and resources mismatch with the fast growing and changing social needs. This study aims at investigating the effectiveness of implementing Circular Economy concept in a social service setting with comparison to Government Policy in response to social needs in 3 areas: response time, suitability, and community participation. To investigate the effectiveness of implementing Circular Economy concept in a social service setting, a real service model, a community resources sharing platform, was set up and statistics of the first 6 months’ operation data were used as comparison with traditional social services. Literature review was conducted as a reference basis of traditional social services under Government Policy. Case studies were conducted to provide the qualitative perspectives of the innovative approach. The results suggest that the Circular Economy model showed extraordinarily high level of community participation. In addition, it could utilize community resources in response precisely to the burning social needs. On the other hand, the available resources were unstable when comparing to those services supported by Government funding. The research team concluded that Circular Economy has high potential in applications in social service, especially in certain areas, such as resources sharing platform. Notwithstanding, it should be aware of the stability of resources when the services targeted to support some crucial needs.

Keywords: circular economy, social innovation, community participation, sharing economy, social response

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Adil Rasheed, Mandar Tabib

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The paper describes the ability of a high-resolution Computational Fluid Dynamics model to predict terrain-induced turbulence and wind shear close to the ground. Various sensitivity studies to choose the optimal simulation setup for modeling the flow characteristics in a complex terrain are presented. The capabilities of the model are demonstrated by applying it to the Sandnessjøen Airport, Stokka in Norway, an airport that is located in a mountainous area. The model is able to forecast turbulence in real time and trigger an alert when atmospheric conditions might result in high wind shear and turbulence.

Keywords: aviation safety, terrain-induced turbulence, atmospheric flow, alert system

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Authors: Naomi Seidu, Edward Poluyi, Chibuikem Ikwuegbuenyi, Eghosa Morgan

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The current poor prognosis of glioblastoma has called for the need for an improvement in treatment methods in order to improve its survival rate. Despite the different interventions currently available for this tumor, the average survival is still only a few months. (12-15). The aim is to create a more favorable prognosis and have a reduction in the resistance to treatment currently being experienced, even with surgical interventions and chemotherapy. From the available literature, there is a relationship between the presence of HOX genes (Homeobox genes) and glioblastoma, which could be attributable to the increasing treatment resistance. Hence silencing these genes can be a key to improving survival rates of glioblastoma. A series of studies have highlighted the role that HOX genes play in glioblastoma prognosis. Promotion of human glioblastoma initiation, aggressiveness, and resistance to Temozolomide has been associated with HOXA9. The role of HOX gene expression in cancer stem cells should be studied as it could provide a means of designing CSC-targeted therapies, as CSCs play a part in the initiation and progression of solid tumors.

Keywords: GBM- glioblastoma, HOXA gene- homeobox genes cluster, signaling pathways, temozolomide

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Authors: Valentina Futoryanova, Hugh Hunt

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One of the common failure modes of the diesel engine turbochargers is high cycle fatigue of the turbine wheel blades. Mistuning of the blades due to the casting process is believed to contribute to the failure mode. Laser vibrometer is used to characterize mistuning for a population of turbine wheels through the analysis of the blade response to piezo speaker induced noise. The turbine wheel design under investigation is radial and is typically used in 6-12 L diesel engine applications. Amplitudes and resonance frequencies are reviewed and summarized. The study also includes test results for a paddle wheel that represents a perfectly tuned system and acts as a reference. Mass spring model is developed for the paddle wheel and the model suitability is tested against the actual data. Randomization is applied to the stiffness matrix to model the mistuning effect in the turbine wheels. Experimental data is shown to have good agreement with the model.

Keywords: vibration, radial turbines, mistuning, turbine blades, modal analysis, periodic structures, finite element

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Authors: Nini Johana Marín Rodríguez, William Fernando Oquendo Patino

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In this work, we model a coupled system where we explore the effects of steady and random behavior on a linear system like an extension of the classic Strogatz model. This is exemplified by modeling a couple love dynamics as a linear system of two coupled differential equations and studying its stability for four types of lovers chosen as CC='Cautious- Cautious', OO='Only other feelings', OP='Opposites' and RR='Romeo the Robot'. We explore the effects of, first, introducing saturation, and second, adding a random variation to one of the CC-type lover, which will shape his character by trying to model how its variability influences the dynamics between love and hate in couple in a long run relationship. This work could also be useful to model other kind of systems where interactions can be modeled as linear systems with external or internal random influence. We found the final results are not easy to predict and a strong dependence on initial conditions appear, which a signature of chaos.

Keywords: differential equations, dynamical systems, linear system, love dynamics

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Authors: Yasmeen Coaxum

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The year 2020 became synonymous with the words “Emergency Remote Teaching,” which was imposed upon educators during the COVID-19 pandemic. Consequently, teachers were compelled to find new and engaging ways to educate their students outside of the face-to-face classroom setting. Now online instruction has become more of the norm rather than a way to manage educational expectations during a crisis. Therefore, implementing a strategic way to create online environments for students to thrive, create, and fully engage in their learning process is essential. The Synchronous Online Flipped Learning Approach or SOFLA® is a distance learning model that most closely replicates actual classroom teaching. SOFLA® includes structured, interactive, multimodal activities in an eight-step learning cycle with both asynchronous and synchronous components that foster autonomous and interactive learning among today’s online learners. The results of a pilot study in an Intensive English Program at a university, using SOFLA® methodology to facilitate podcasting in an online learning environment will be shared. Previous findings on student-produced podcasting projects have shown that students felt they improved their pronunciation, vocabulary, and speaking skills. However, few if any studies have been conducted on using a structured online flipped learning approach to facilitate such projects. Therefore, the purpose of this study is to assess the effect of using the SOFLA® framework to enhance optimum engagement in the online environment while using podcasts as the primary tool of instruction. Through data from interviews, questionnaires, and the results of formative and summative assessments, this study also investigates the affective and academic impact this flipped learning method combined with podcasting has on the students in terms of speaking confidence and vocabulary retention, and production. The steps of SOFLA will be illustrated, a video demonstration of the Anchor podcasting app will be shown, and final student projects and questionnaire responses will be shared. The specific context is a 14-week advanced level conversation and listening class. Participants vary in age but are all adult language learners representing a diverse array of countries.

Keywords: mall online flipped learning, podcasting, productive vocabulary

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Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

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This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

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Authors: Ren Zuo Wang

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In this paper, in order to investigate the behavior of the wood structure, the non-linearity of wood material model in LS-DYNA is adopted. It is difficult and less efficient to conduct the experiment of the ancient wood structure, hence LS-DYNA software can be used to simulate nonlinear responses of ancient wood structure. In LS-DYNA software, there is material model called *MAT_WOOD or *MAT_143. This model is to simulate a single-element response of the wood subjected to tension and compression under the parallel and the perpendicular material directions. Comparing with the exact solution and numerical simulations results using LS-DYNA, it demonstrates the accuracy and the efficiency of the proposed simulation method.

Keywords: LS-DYNA, wood structure, single-element simulations, MAT_143

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Authors: Florina Dutt, Subhajit Das, Matthew Swartz

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Lighting design and its impact on indoor comfort conditions are an integral part of good interior design. Impact of lighting in an interior space is manifold and it involves many sub components like glare, color, tone, luminance, control, energy efficiency, flexibility etc. While other components have been researched and discussed multiple times, this paper discusses the research done to understand the glare component from an artificial lighting source in an indoor space. Consequently, the paper discusses a parametric model to convey real time glare level in an interior space to the designer/ architect. Our end users are architects and likewise for them it is of utmost importance to know what impression the proposed lighting arrangement and proposed furniture layout will have on indoor comfort quality. This involves specially those furniture elements (or surfaces) which strongly reflect light around the space. Essentially, the designer needs to know the ramification of the ‘discomfortable glare’ at the early stage of design cycle, when he still can afford to make changes to his proposed design and consider different routes of solution for his client. Unfortunately, most of the lighting analysis tools that are present, offer rigorous computation and analysis on the back end eventually making it challenging for the designer to analyze and know the glare from interior light quickly. Moreover, many of them do not focus on glare aspect of the artificial light. That is why, in this paper, we explain a novel approach to approximate interior glare data. Adding to that we visualize this data in a color coded format, expressing the implications of their proposed interior design layout. We focus on making this analysis process very fluid and fast computationally, enabling complete user interaction with the capability to vary different ranges of user inputs adding more degrees of freedom for the user. We test our proposed parametric model on a case study, a Computer Lab space in our college facility.

Keywords: computational geometry, glare impact in interior space, info visualization, parametric lighting analysis

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Authors: Sidi Yang, Haiyi Zhang

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Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: text mining, Twitter, topic model, sentiment analysis

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Authors: Thomas Rowan, Mohammed Seaid

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A fast finite volume solver for multi-layered shallow water flows with mass exchange and an erodible bed is developed. This enables the user to solve a number of complex sediment-based problems including (but not limited to), dam-break over an erodible bed, recirculation currents and bed evolution as well as levy and dyke failure. This research develops methodologies crucial to the under-standing of multi-sediment fluvial mechanics and waterway design. In this model mass exchange between the layers is allowed and, in contrast to previous models, sediment and fluid are able to transfer between layers. In the current study we use a two-step finite volume method to avoid the solution of the Riemann problem. Entrainment and deposition rates are calculated for the first time in a model of this nature. In the first step the governing equations are rewritten in a non-conservative form and the intermediate solutions are calculated using the method of characteristics. In the second stage, the numerical fluxes are reconstructed in conservative form and are used to calculate a solution that satisfies the conservation property. This method is found to be considerably faster than other comparative finite volume methods, it also exhibits good shock capturing. For most entrainment and deposition equations a bed level concentration factor is used. This leads to inaccuracies in both near bed level concentration and total scour. To account for diffusion, as no vertical velocities are calculated, a capacity limited diffusion coefficient is used. The additional advantage of this multilayer approach is that there is a variation (from single layer models) in bottom layer fluid velocity: this dramatically reduces erosion, which is often overestimated in simulations of this nature using single layer flows. The model is used to simulate a standard dam break. In the dam break simulation, as expected, the number of fluid layers utilised creates variation in the resultant bed profile, with more layers offering a higher deviation in fluid velocity . These results showed a marked variation in erosion profiles from standard models. The overall the model provides new insight into the problems presented at minimal computational cost.

Keywords: erosion, finite volume method, sediment transport, shallow water equations

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Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: Donglian Sun, Yu Li, Paul Houser, Xiwu Zhan

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California experienced severe drought conditions in the past years. In this study, the drought conditions in California are analyzed using soil moisture anomalies derived from integrated optical and microwave satellite observations along with auxiliary land surface data. Based on the U.S. Drought Monitor (USDM) classifications, three typical drought conditions were selected for the analysis: extreme drought conditions in 2007 and 2013, severe drought conditions in 2004 and 2009, and normal conditions in 2005 and 2006. Drought is defined as negative soil moisture anomaly. To estimate soil moisture at high spatial resolutions, three approaches are explored in this study: the universal triangle model that estimates soil moisture from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST); the basic model that estimates soil moisture under different conditions with auxiliary data like precipitation, soil texture, topography, and surface types; and the refined model that uses accumulated precipitation and its lagging effects. It is found that the basic model shows better agreements with the USDM classifications than the universal triangle model, while the refined model using precipitation accumulated from the previous summer to current time demonstrated the closest agreements with the USDM patterns.

Keywords: soil moisture, high resolution, regional drought, analysis and monitoring

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Authors: Akingeneye Liliane

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The value chain concept in recent times is being used by businesses and organizations to develop and implement their businesses. Chili farming has been identified as a significant contributor to the economic growth of Bugesera district. However, numerous challenges have led to a decrease in production. The primary objective of this research was to assess the current Bugesera chili value chain, identify the bottlenecks in the value chain, and come up with interventions that can help increase the output of the Bugesera chili value chain, in a climate-smart way and enhance Long-term sustainability of the value chain. The research used a case study approach to fulfill its objectives, utilizing primary and secondary data sources. Qualitative and quantitative data were gathered through semi-structured interviews with 22 individual farmers, five exporters, and five supporters within the Bugesera district. A focus group discussion (FGD) with seven stakeholders was also conducted to validate the research findings. The study's results underscore the challenges faced by chili farmers and other actors in the chain, the perceptions of different stakeholders to contribute to chili production, and the importance of promoting strong collaboration among stakeholders in the chili value chain to establish a sustainable framework. Based on these findings, the study puts forward recommendations to address the identified challenges and improve the chili farming sector in Bugesera. The business canvas model, as a proposed recommendation, once implemented, is believed to represent the most effective approach to enhancing chili productivity in Bugesera and securing the long-term sustainability of an export-oriented chili value chain in the district.

Keywords: build, sustainability, chili value chain, export-oriented

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Authors: A. Samer Ezeldin, Jwanda M. El Sarag

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Variation orders are of great importance in any construction project. Variation orders are defined as any change in the scope of works of a project that can be an addition omission, or even modification. This paper investigates the variation orders that occur during construction projects in Egypt. The literature review represents a comparison of causes of variation orders among Egypt, Tanzania, Nigeria, Malaysia and the United Kingdom. A classification of occurrence of variation orders due to owner related factors, consultant related factors and other factors are signified in the literature review. These classified events that lead to variation orders were introduced in a survey with 19 events to observe their frequency of occurrence, and their time and cost impacts. The survey data was obtained from 87 participants that included clients, consultants, and contractors and a database of 42 scenarios was created. A model is then developed to help assist project managers in predicting the frequency of variations and account for a budget for any additional costs and minimize any delays that can take place. Two experts with more than 25 years of experience were given the model to verify that the model was working effectively. The model was then validated on a residential compound that was completed in July 2016 to prove that the model actually produces acceptable results.

Keywords: construction, cost impact, Egypt, time impact, variation orders

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Authors: Yves Lacroix, Van Van Than, Didier Léandri, Pierre Liardet

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The western Tombolo of the Giens peninsula in southern France, known as Almanarre beach, is subject to coastal erosion. We are trying to use computer simulation in order to propose solutions to stop this erosion. Our aim was first to determine the main factors for this erosion and successfully apply a coupled hydro-sedimentological numerical model based on observations and measurements that have been performed on the site for decades. We have gathered all available information and data about waves, winds, currents, tides, bathymetry, coastal line, and sediments concerning the site. These have been divided into two sets: one devoted to calibrating a numerical model using Mike 21 software, the other to serve as a reference in order to numerically compare the present situation to what it could be if we implemented different types of underwater constructions. This paper presents the first part of the study: selecting and melting different sources into a coherent data basis, identifying the main erosion factors, and calibrating the coupled software model against the selected reference period. Our results bring calibration of the numerical model with good fitting coefficients. They also show that the winter South-Western storm events conjugated to depressive weather conditions constitute a major factor of erosion, mainly due to wave impact in the northern part of the Almanarre beach. Together, current and wind impact is shown negligible.

Keywords: Almanarre beach, coastal erosion, hydro-sedimentological, numerical model

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: Abhishek Mukherjee, Juan C. Cajas, Jenny Suckale, Guillaume Houzeaux, Oriol Lehmkuhl, Simone Marras

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The investigation of tsunami flow characteristics and the quantification of tsunami energy reduction through the coastal vegetation is important to understand the protective benefits of nature-based mitigation parks. In the present study, a three-dimensional non-hydrostatic incompressible Computational Fluid Dynamics model with a two-way coupling enabled fluid-structure interaction approach (FSI) is used. After validating the numerical model against experimental data, tsunami flow characteristics have been investigated by varying vegetation density, modulus of elasticity, the gap between stems, and arrangement or distribution of vegetation patches. Streamwise depth average velocity profiles, turbulent kinetic energy, energy flux reflection, and dissipation extracted by the numerical study will be presented in this study. These diagnostics are essential to assess the importance of different parameters to design the proper coastal defense systems. When a tsunami wave reaches the shore, it transforms into undular bores, which induce scour around offshore structures and sediment transport. The bed shear stress, instantaneous turbulent kinetic energy, and the vorticity near-bed will be presented to estimate the importance of vegetation to prevent tsunami-induced scour and sediment transport.

Keywords: coastal defense, energy flux, fluid-structure interaction, natural hazards, sediment transport, tsunami mitigation

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Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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Authors: Ferzat Anka

Abstract:

Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: A. M. Halahla, M. H. Baluch, M. K. Rahman, A. H. Al-Gadhib, M. N. Akhtar

Abstract:

In the present study, 3D simulation of a typical exterior (RC) beam–column joint (BCJ) strengthened with carbon fiber-reinforced plastic (CFRP) sheet are carried out. Numerical investigations are performed using a nonlinear finite element ( FE) analysis by incorporating damage plasticity model (CDP), for material behaviour the concrete response in compression, tension softening were used, linear plastic with isotropic hardening for reinforcing steel, and linear elastic lamina material model for CFRP sheets using the commercial FE software ABAQUS. The numerical models developed in the present study are validated with the results obtained from the experiment under monotonic loading using the hydraulic Jack in displacement control mode. The experimental program includes casting of deficient BCJ loaded to failure load for both un-strengthened and strengthened BCJ. The failure mode, and deformation response of CFRP strengthened and un-strengthened joints and propagation of damage in the components of BCJ are discussed. Finite element simulations are compared with the experimental result and are noted to yield reasonable comparisons. The damage plasticity model was able to capture with good accuracy of the ultimate load and the mode of failure in the beam column joint.

Keywords: reinforced concrete, exterior beam-column joints, concrete damage plasticity model, computational simulation, 3-D finite element model

Procedia PDF Downloads 362

Authors: Azadeh Malekan, Shahin Rouhani

Abstract:

Superlubricity is a phenomenon where two surfaces in contact show negligible friction;this may be because the asperities of the two surfaces do not interlock. Two rough surfaces, when pressed against each other, can get into a formation where the summits of asperities of one surface lock into the valleys of the other surface. The amount of interlock depends on the geometry of the two surfaces. We suggest the friction force may then be proportional to the amount of interlock; this explains Superlubricity as the situation where there is little interlock. Then the friction force will be directly proportional to the normal force as it is related to the work necessary to lift the upper surface in order to clear the interlock. To investigate this model, we simulate the contact of two surfaces. In order to validate our model, we first investigate Amontons‘ law. Assuming that asperities retain deformations in the time scale while the top asperity moves across the lattice spacing Amonton’s law is observed. Structural superlubricity is examined by the hypothesis that surfaces are very rigid and there is no deformation in asperities. This may happen at small normal forces. When two identical surfaces come into contact, rotating the top surface we observe a peak in friction force near the angle of orientation where the two surfaces can interlock.

Keywords: friction, amonton`s law, superlubricity, contact model

Procedia PDF Downloads 135

Authors: Walailak Atthirawong

Abstract:

By the end of 2015, the Association of Southeast Asian Nations (ASEAN) countries proclaim to transform into the next stage of an economic era by having a single market and production base called ASEAN Economic Community (AEC). One objective of the AEC is to establish ASEAN as a single market and one production base making ASEAN highly competitive economic region and competitive with new mechanisms. As a result, it will open more opportunities to enterprises in both trade and investment, which offering a competitive market of US$ 2.6 trillion and over 622 million people. Location decision plays a key role in achieving corporate competitiveness. Hence, it may be necessary for enterprises to redesign their supply chains via enlarging a new production base which has low labor cost, high labor skill and numerous of labor available. This strategy will help companies especially for apparel industry in order to maintain a competitive position in the global market. Therefore, in this paper a generic model for location selection decision for Thai apparel industry using Fuzzy Analytical Network Process (FANP) is proposed. Myanmar, Vietnam and Cambodia are referred for alternative location decision from interviewing expert persons in this industry who have planned to enlarge their businesses in AEC countries. The contribution of this paper lies in proposing an approach model that is more practical and trustworthy to top management in making a decision on location selection.

Keywords: apparel industry, ASEAN Economic Community (AEC), Fuzzy Analytical Network Process (FANP), location decision

Procedia PDF Downloads 221

Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem

Abstract:

Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic aspect-based sentiment analysis approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Keywords: sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity

Procedia PDF Downloads 144