Search results for: multilevel models

Authors: Rajai Al-Rousan

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This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.

Keywords: predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites

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Authors: A. Elsehemy, M. Abdeen , T. Nazmy

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Since the appearance of the Semantic web, many semantic search techniques and models were proposed to exploit the information in ontology to enhance the traditional keyword-based search. Many advances were made in languages such as English, German, French and Spanish. However, other languages such as Arabic are not fully supported yet. In this paper we present a framework for ontology based information retrieval for Arabic language. Our system consists of four main modules, namely query parser, indexer, search and a ranking module. Our approach includes building a semantic index by linking ontology concepts to documents, including an annotation weight for each link, to be used in ranking the results. We also augmented the framework with an automatic document categorizer, which enhances the overall document ranking. We have built three Arabic domain ontologies: Sports, Economic and Politics as example for the Arabic language. We built a knowledge base that consists of 79 classes and more than 1456 instances. The system is evaluated using the precision and recall metrics. We have done many retrieval operations on a sample of 40,316 documents with a size 320 MB of pure text. The results show that the semantic search enhanced with text classification gives better performance results than the system without classification.

Keywords: Arabic text classification, ontology based retrieval, Arabic semantic web, information retrieval, Arabic ontology

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Harukuni Tokuda, Xu FengHao, Nobutaka Suzuki

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As part of an ongoing our projects to investigate the anti-tumor promoring properties (chemopreventive potency) of Gromwell seed, dry powder materials and its active compounds were carried out through useful test systems. Gromwell seed (Coix lachryma-jobi seed) (GS) is a grass crop that has long been used and played a role in traditional medicine as a nourishing food, and for the treatment of various aliments, paticularly cancer. The application of a new screening procedure which utilizes the synergistic effect of short-chain fatty acids and phorbol esters in enable rapid and easy detection of naturally occurring substances(anti-tumor promoters chemo-preventive agents) with inhibition of Epstein-Barr virus(EBV) activation, using human lymphblastoid cells. In addition, we have now extended these investigations to a new tumorigenesis model in which we initiated the tumors with DMBA intiation and promoted with 1.7 nmol of TPA in two-stage mouse skin test and other models. these results provide a basis for further development of these botanical supplements for human cancer chemoprevention and observations seem that this materials more extensively as one of the trials for the purpose of complementary and alternative medicine.

Keywords: chemoprevention, medicinal plant, mouse, carcinogenesis systems

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Authors: Makito Sakai, Takahiro Kiwata, Takumi Awa, Hiroshi Teramoto, Takaaki Kono, Kuniaki Toyoda

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Using experimental and numerical results, this paper describes the effects of tabs on the flow characteristics of a plane jet at comparatively low Reynolds numbers while focusing on the velocity field and the vortical structure. The flow visualization and velocity measurements were respectively carried out using laser Doppler velocimetry (LDV) and particle image velocimetry (PIV). In addition, three-dimensional (3D) plane jet numerical simulations were performed using ANSYS Fluent, a commercially available computational fluid dynamics (CFD) software application. We found that the spreads of jets perturbed by large delta tabs and round tabs were larger than those produced by the other tabs tested. Additionally, it was determined that a plane jet with square tabs had the smallest jet spread downstream, and the jet’s centerline velocity was larger than those of jets perturbed by the other tabs tested. It was also observed that the spanwise vortical structure of a plane jet with tabs disappeared completely. Good agreement was found between the experimental and numerical simulation velocity profiles in the area near the nozzle exit when the laminar flow model was used. However, we also found that large eddy simulation (LES) is better at predicting the developing flow field of a plane jet than the laminar and the standard k-ε turbulent models.

Keywords: plane jet, flow control, tab, flow measurement, numerical simulation

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Authors: Panpan Fan, Bo Ming, Niels P. R. Anten, Jochem B. Evers, Yaoyao Li, Shaokun Li, Ruizhi Xie

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The reallocation of dry matter (DM) and nitrogen (N) from vegetative tissues to the grain sinks are critical for grain yield. The objective of this study was to quantify the DM and N accumulation, partition, and reallocation at the single-leaf, different-organ, and individual-plant scales and clarify the responses to different levels of N availabilities. A two-year field experiment was conducted in Jinlin province, Northeast China, with three N fertilizer rates to create the different N availability levels: N0 (N deficiency), N1(low supply), and N2 (high supply). The results showed that grain N depends more on reallocations of vegetative organs compared with grain DM. Besides, vegetative organs reallocated more DM and N to grain under lower N availability, whereas more grain DM and grain N were derived from post-silking leaf photosynthesis and post-silking N uptake from the soil under high N availability. Furthermore, the reallocation amount and reallocation efficiency of leaf DM and leaf N content differed among leaf ranks and were regulated by N availability; specifically, the DM reallocation occurs mainly on senesced leaves, whereas the leaf N reallocation was in live leaves. These results provide a theoretical basis for deriving parameters in crop models for the simulation of the demand, uptake, partition, and reallocation processes of DM and N.

Keywords: dry matter, leaf N content, leaf rank, N availability, reallocation efficiency

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Authors: Joachim Monkelbaan, Marcia Hale

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Now that global frameworks for sustainability governance (e.g. the Sustainable Development Goals, Paris Climate Agreement and Sendai Framework for Disaster Risk Reduction) are in place, the question is how these aspirations that represent major transitions can be put into practice. Water ‘infrasystems’ can play an especially significant role in strengthening regional sustainability. Infrasystems include both hard and soft infrastructure, such as pipes and technology for delivering water, as well as the institutions and governance models that direct its delivery. As such, an integrated infrasystems view is crucial for Integrative Water Management (IWM). Due to frequently contested ownership of and responsibility for water resources, these infrasystems can also play an important role in facilitating conflict and catalysing community empowerment, especially through participatory approaches to governance. In this paper, we analyze the water infrasystem of the Los Angeles region through the lens of global frameworks for sustainability governance. By complementing a solid overview of governance theories with empirical data from interviews with water actors in the LA metropolitan region (including NGOs, water managers, scientists and elected officials), this paper elucidates ways for this infrasystem to be better aligned with global sustainability frameworks. In addition, it opens up the opportunity to scrutinize the appropriateness of global frameworks when it comes to fostering sustainability action at the local level.

Keywords: governance, transitions, global frameworks, infrasystems

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Authors: Kedar S. Prabhavalkar, Nimmy Baby Poovanpallil

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Lamotrigine is approved for maintenance treatment of bipolar I disorder. However, its role in the treatment of acute bipolar depression is not well clear. Its efficacy in the treatment of major depressive disorders including refractory unipolar depression suggested the use of lamotrigine as an augmentation drug for acute bipolar depression. The present study aims to evaluate and perform a comparative analysis of the therapeutic effects of lamotrigine, an epileptic mood stabilizer, when used alone and in combination with duloxetine in treating acute bipolar depression at different doses of lamotrigine. Male swiss albino mice were used. For evaluation of efficacy of combination, immobility period was analyzed 30 min after the treatment from forced swim and tail suspension tests. Further amount of sucrose consumed in sucrose preference test was estimated. The combination of duloxetine and lamotrigine showed potentiation of antidepressant activity in acute models. Decrease in immobility time and increase in the amount of sucrose consumption in stressed mice were higher in combined group compared to lamotrigine monotherapy group. Brain monoamine levels were also attenuated more with combination compared to monotherapy. Results of the present study suggest potential role of lamotrigine and duloxetine combination in the treatment of acute bipolar depression.

Keywords: lamotrigine, duloxetine, acute bipolar depression, augmentation

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Authors: Carlos Cuenca, Diego Sarzosa

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Ductile fracture occurs by the mechanism of void nucleation, void growth and coalescence. Potential sites for initiation are second phase particles or non-metallic inclusions. Modelling of ductile damage at the microscopic level is very difficult and complex task for engineers. Therefore, conservative predictions of ductile failure using simple models are necessary during the design and optimization of critical structures like pressure vessels and pipelines. Nowadays, it is well known that the initiation phase is strongly influenced by the stress triaxiality and plastic deformation at the microscopic level. Thus, a simple model used to study the ductile failure under multiaxial stress condition is the Stress Modified Critical Strain (SMCS) approach. Ductile rupture has been study for a structural steel under different stress triaxiality conditions using the SMCS method. Experimental tests are carried out to characterize the relation between stress triaxiality and equivalent plastic strain by notched round bars. After calibration of the plasticity and damage properties, predictions are made for low constraint bending specimens with and without side grooves. Stress/strain fields evolution are compared between the different geometries. Advantages and disadvantages of the SMCS methodology are discussed.

Keywords: damage, SMSC, SEB, steel, failure

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Authors: Nor Wahiza Abdul Wahat, Nor Haniza Abdul Wahat, Siti Noormi Alias, Mohamad Sazali Shaari

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This study prepares the groundwork for the development of a strategic model and instrument for workplace inclusivity for deaf and hard-of-hearing employees in Malaysia. In the past, scholars have discussed inclusivity of workplaces to the extent to which employees feel they are significantly part of the organizational processes. Such processes include access to information, connectedness to colleagues and team members as well as their ability to participate in and influence decision-making processes. A qualitative study was conducted to explore on experiences of employed deaf and hard-of-hearing employees in a few Malaysian organizations. Data were collected from two focus group discussions involving male and female deaf and hard of hearing employees. Three in-depth interviews were also conducted with employer representatives. Generated themes highlighted individual, and team approaches towards crafting workplace inclusivity for deaf and hard of hearing employees in Malaysia. The adaptiveness of deaf and hard-of-hearing employees and social inclusion by colleagues were among the emerged sub-themes. This study allowed the researchers to further develop workplace inclusivity instruments and models for the benefit of deaf and hard of hearing Malaysian employees, as well as their employers.

Keywords: deaf, hard of hearing, workplace inclusivity, disabilities

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Authors: Hassan Barau Singhry

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Purpose: Leadership or the absence of it is an important behaviour affecting employees’ job satisfaction. Although, there are many models of leadership, one that stands out in a period of change is the transformational behaviour. The aim of this study is to investigate the role of an organizational justice on the relationship between transformational leadership and employee job satisfaction. The study is based on the assumption that change begins with leaders and leaders should be fair and just. Methodology: A cross-sectional survey through structured questionnaire was employed to collect the data of this study. The population is selected the three tiers of government such as the local, state, and federal governments in Nigeria. The sampling method used in this research is stratified random sampling. 418 middle managers of public organizations respondents to the questionnaire. Multiple regression aided by structural equation modeling was employed to test 4 hypothesized relationships. Finding: The regression results support for the mediating role of organizational justice such as distributive, procedural, interpersonal and informational justice in the link between transformational leadership and job satisfaction. Originality/value: This study adds to the literature of human resource management by empirically validating and integrating transformational leadership behaviour with the four dimensions of organizational justice theory. The study is expected to be beneficial to the top and middle-level administrators as well as theory building and testing.

Keywords: distributive justice, job satisfaction, organizational justice, procedural justice, transformational leadership

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Authors: Bel G Raggad

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An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.

Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection

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Authors: Giselle Maggie Fer Castañeda, Diego Iván González

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The objective of this work was to study the autoshaped choice behavior in the Donahoe, Burgos and Palmer (DBP) neural network model and analyze it under the matching law. Autoshaped choice can be viewed as a form of economic behavior defined as the preference between alternatives according to their relative outcomes. The Donahoe, Burgos and Palmer (DBP) model is a connectionist proposal that unifies operant and Pavlovian conditioning. This model has been used for more than three decades as a neurobehavioral explanation of conditioning phenomena, as well as a generator of predictions suitable for experimental testing with non-human animals and humans. The study consisted of different simulations in which, in each one, a ratio of reinforcement was established for two alternatives, and the responses (i.e., activations) in each of them were measured. Choice studies with animals have demonstrated that the data generally conform closely to the generalized matching law equation, which states that the response ratio equals proportionally to the reinforcement ratio; therefore, it was expected to find similar results with the neural networks of the Donahoe, Burgos and Palmer (DBP) model since these networks have simulated and predicted various conditioning phenomena. The results were analyzed by the generalized matching law equation, and it was observed that under some contingencies, the data from the networks adjusted approximately to what was established by the equation. Implications and limitations are discussed.

Keywords: matching law, neural networks, computational models, behavioral sciences

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

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The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: V. Pourmostaghimi, M. Zadshakoyan

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Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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Authors: Saeed Sayyad Hagh Shomar

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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

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Authors: Esperanza Garcia-Uceda, Josefina L. Murillo-Luna, M. Pilar Latorre-Martinez, Marta Ferrer-Serrano

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Social entrepreneurship represents an innovation of traditional business models. During the last decade, its important role in contributing to rural and regional development has been widely recognized, due to its capacity to combat the problem of depopulation through the creation of employment. However, the success of this type of innovative business initiatives depends to a large extent on the existence of an adequate ecosystem of support resources. Based on the theoretical framework of the quadruple helix (QH), which highlights the need for collaboration between different interest groups -university, industry, government and civil society- for the development of regional innovations, in this work the network analysis is applied to study the ecosystem of resources to support social entrepreneurship in the rural area of the province of Zaragoza (Spain). It is a quantitative analysis that can be used to measure the interactions between the different actors that make up the quadruple helix, as well as the networks created between the different institutions and support organizations, through the study of the complex networks they form. The results show the importance of the involvement of local governments and the university, as key elements in the development process, but also allow identifying other issues that are susceptible to improvement.

Keywords: ecosystem of support resources, network analysis, quadruple helix, social entrepreneurship

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Authors: Faci Youcef

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In the present work, an experimental study is carried out using the digital image correlation (DIC) technique to analyze the damage and behavior of woven composite carbon/epoxy under tensile loading. The tension mechanisms associated with failure modes of bolted joints in advanced composites are studied, as well as displacement distribution and strain distribution. The evolution value of bolt angle inclination during tensile tests was studied. In order to compare the distribution of displacements and strains along the surface, figures of image mapping are made. Several factors that are responsible for the failure of fiber-reinforced polymer composite materials are observed. It was found that strain concentrations observed in the specimens can be used to identify full-field damage onset and to monitor damage progression during loading. Moreover, there is an interaction between laminate pattern, laminate thickness, fastener size and type, surface strain concentrations, and out-of-plane displacement. Conclusions include a failure analysis associated with bolt angle inclinations and supported by microscopic visualizations of the composite specimen. The DIC results can be used to develop and accurately validate numerical models.

Keywords: Carbone, woven, damage, digital image, bolted joint, the inclination of angle

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Authors: Ahmed Hamzi, Bryan Norman

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Having scribes help document patient records in electronic health record systems can improve hospitalists’ productivity. But hospitals need to determine the optimum number of scribes to hire to maximize scribe cost effectiveness. Scribe attendance uncertainty due to planned and unplanned absences is a primary challenge. This paper presents simulation and analytical models to determine the optimum number of scribes for a hospital to hire. Scribe staffing practices vary from one context to another; different staffing scenarios are considered where having extra attending scribes provides or does not provide additional value and utilizing on-call scribes to fill in for potentially absent scribes. These staffing scenarios are assessed for different scribe revenue ratios (ratio of the value of the scribe relative to scribe costs) ranging from 100% to 300%. The optimum solution depends on the absenteeism rate, revenue ratio, and desired service level. The analytical model obtains solutions easier and faster than the simulation model, but the simulation model is more accurate. Therefore, the analytical model’s solutions are compared with the simulation model’s solutions regarding both the number of scribes hired and cost-effectiveness. Additionally, an Excel tool has been developed to facilitate decision-makers in easily obtaining solutions using the analytical model.

Keywords: hospitalists, workload, optimization cost, economic analysis

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Authors: Ayan Chakraborty, BV. Rathish Kumar

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Off-late many models in viscoelasticity, signal processing or anomalous diffusion equations are formulated in fractional calculus. Tempered fractional calculus is the generalization of fractional calculus and in the last few years several important partial differential equations occurring in the different field of science have been reconsidered in this term like diffusion wave equations, Schr$\ddot{o}$dinger equation and so on. In the present paper, a time-dependent tempered fractional diffusion equation of order $\gamma \in (0,1)$ with forcing function is considered. Existence, uniqueness, stability, and regularity of the solution has been proved. Crank-Nicolson discretization is used in the time direction. B spline finite element approximation is implemented. Generally, B-splines basis are useful for representing the geometry of a finite element model, interfacing a finite element analysis program. By utilizing this technique a priori space-time estimate in finite element analysis has been derived and we proved that the convergent order is $\mathcal{O}(h²+T²)$ where $h$ is the space step size and $T$ is the time. A couple of numerical examples have been presented to confirm the accuracy of theoretical results. Finally, we conclude that the studied method is useful for solving tempered fractional diffusion equations.

Keywords: B-spline finite element, error estimates, Gronwall's lemma, stability, tempered fractional

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Authors: Fereshteh Pashaei Kamali, Elham Kazemi, Shokooh Neshani Fam

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The subject of sustainable development is a reformist revision of modernism and tradition, proposing reconciliatory strategies between these two. Sustainability in architecture cannot only be interpreted as the construction’s physical stability, but also as stability, the preserving of the continuous totality of earth and its energy resources as well, whose available resources and materials should be employed more efficiently. In other words, by referring to the building ecology, emphasizing the combinatory capacity of the building with the environmental factors (existence context), the aim of sustainability is to achieve spatial quality and comfort, as well as proper design in the architectural composition. To achieve these traditional Iranian architecture objectives, it is essential to plan on protecting the environment, maintaining aesthetic measures and responding to the needs of each climatic region. This study was conducted based on the descriptive-analytical method, and aimed to express the design patterns compatible with the climate of the Tabriz residential fabric. The present article attempts to express the techniques and patterns used in traditional Iranian architecture, especially the Tabriz Sharbatoglu houses and Ghadaki houses, which are supposed to be in accordance with modern concepts of sustainable architecture.

Keywords: sustainable architecture, climate, Tabriz, Sharbatoglu house, Ghadaki house

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Authors: Mehmet Savsar, Majid Aldaihani

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Flexible Manufacturing Systems (FMS) are used to produce a variety of parts on the same equipment. Therefore, their utilization is higher than traditional machining systems. Higher utilization, on the other hand, results in more frequent equipment failures and additional need for maintenance. Therefore, it is necessary to carefully analyze operational characteristics and productivity of FMS or Flexible Manufacturing Cells (FMC), which are smaller configuration of FMS, before installation or during their operation. Appropriate models should be developed to determine production rates based on operational conditions, including equipment reliability, availability, and repair capacity. In this paper, a stochastic model is developed for an automated FMC system, which consists of two machines served by two robots and a single repairman. The model is used to determine system productivity and equipment utilization under different operational conditions, including random machine failures, random repairs, and limited repair capacity. The results are compared to previous study results for FMC system with sufficient repair capacity assigned to each machine. The results show that the model will be useful for design engineers and operational managers to analyze performance of manufacturing systems at the design or operational stages.

Keywords: flexible manufacturing, FMS, FMC, stochastic modeling, production rate, reliability, availability

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

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Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

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Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

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Authors: Yu Chen

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This paper investigates the influence of flaw on failure process of rock-like material under uniaxial compression. In laboratory, the uniaxial compression tests of intact specimens and a series of specimens within single flaw were conducted. The inclination angle of flaws includes 0°, 15°, 30°, 45°, 60°, 75° and 90°. Based on the laboratory tests, the corresponding models of numerical simulation were built and loaded in PFC2D. After analysing the crack initiation and failure modes, deformation field, and energy mechanism for both laboratory tests and numerical simulation, it can be concluded that the influence of flaws on the failure process is determined by its inclination. The characteristic stresses increase as flaw angle rising basically. The tensile cracks develop from gentle flaws (α ≤ 30°) and the shear cracks develop from other flaws. The propagation of cracks changes during failure process and the failure mode of a specimen corresponds to the orientation of the flaw. A flaw has significant influence on the transverse deformation field at the middle of the specimen, except the 75° and 90° flaw sample. The input energy, strain energy and dissipation energy of specimens show approximate increase trends with flaw angle rising and it presents large difference on the energy distribution.

Keywords: failure pattern, particle deformation field, energy mechanism, PFC

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Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

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The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching, including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders, including Ghana Football Association (GFA), to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

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Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders including Ghana Football Association (GFA) to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 43

Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

Abstract:

The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

Procedia PDF Downloads 110

Authors: Kholil, Laksanto Utomo

Abstract:

The food needs of the Indonesian people will continue increase year to year due to the increase of population growth. For ensuring food securityand and resilience, the government has developed a program food self-resilience village since 2006. Food resilience is a complex system, consisting of subsystem availability, distribution and consumption of the sufficiency of food consumed both in quantity and quality. Low access, and limited assets to food sources is the dominant factor vulnerable of food. Women have a major role in supporting the productive activities of the family to meet food sufficiency and resilience. The purpose of this paper is to discuss the model of food self-resilience village wich gender responsive by using a dynamic system model. Model will be developed into 3 level: family, vilage, and regency in accordance with the concept of village food resilience model wich has been developed by ministry of agriculture. Model development based on the results of experts discussion and field study. By some scenarios and simulation models we will able to develop appropriate policy strategies for family food resilience. The result of study show that food resilience was influenced by many factors: goverment policies, technology, human resource, and in the same time it will be a feed back for goverment policies and number of poor family.

Keywords: food availability, food sufficiency, gender, model dynamic, law enfrocement

Procedia PDF Downloads 516