Search results for: dual phase lag model

Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

Procedia PDF Downloads 87

Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: agro-industry, small medium enterprises, empowerment, design thinking, AHP, business model canvas, social business

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Authors: Majed Ahmadi

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In recent years, the high penetration of different types of renewable energy sources (RESs) has affected most of the available strategies. The main motivations behind the high penetration of RESs are clean energy, modular system and easy installation. Among different types of RESs, wind turbine (WT) is an interesting choice referring to the availability of wind in almost any area. The new technologies of WT can provide energy from residential applications to wide grid connected applications. Regarding the WT, advantages such as reducing the dependence on fossil fuels and enhancing the independence and flexibility of large power grid are the most prominent. Nevertheless, the high volatile nature of wind speed injects much uncertainty in the grid that if not managed optimally can put the analyses far from the reality.the aim of this project is scrutiny and to offer proper ways for renewing distribution networks with envisage the effects of wind power plants and uncertainties related to distribution systems including wind power generating plants output rate and consumers consuming rate and also decrease the incidents of the whole network losses, amount of pollution, voltage refraction and cost extent.to solve this problem we use dual point estimate method.And algorithm used in this paper is reformed bat algorithm, which will be under exact research furthermore the results.

Keywords: order renewal, wind turbines, bat algorithm, outspread production, uncertainty

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Authors: William Fuentes, Melany Gil

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Numerical simulations of offshore wind turbines (OWTs) in shallow waters demand sophisticated models considering the cyclic nature of the environmental loads. For the case of an OWT founded on sands, rapid loading may cause a reduction of the effective stress of the soil surrounding the structure. This eventually leads to its settlement, tilting, or other issues affecting its serviceability. In this work, a 3D FE model of an OWT founded on sand is constructed and analyzed. Cyclic loading with different histories is applied at certain points of the tower to simulate some environmental forces. The mechanical behavior of the soil is simulated through the recently proposed ISA-hypoplastic model for sands. The Intergranular Strain Anisotropy ISA can be interpreted as an enhancement of the intergranular strain theory, often used to extend hypoplastic formulations for the simulation of cyclic loading. In contrast to previous formulations, the proposed constitutive model introduces an elastic range for small strain amplitudes, includes the cyclic mobility effect and is able to capture the cyclic behavior of sands under a larger number of cycles. The model performance is carefully evaluated on the FE dynamic analysis of the OWT.

Keywords: offshore wind turbine, monopile, ISA, hypoplasticity

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

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The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: Abeer S. Elsherbiny, Ali H. Gemeay

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In this study, graphene oxide (GO) nanosheets have been synthesized and characterized using different spectroscopic tools such as X-ray diffraction spectroscopy, infrared Fourier transform (FT-IR) spectroscopy, BET specific surface area and Transmission Electronic Microscope (TEM). The prepared GO was investigated for the removal of malachite green, a cationic dye from aqueous solution. The removal methods of malachite green has been proceeded via adsorption process. GO nanosheets can be predicted as a good adsorbent material for the adsorption of cationic species. The adsorption of the malachite green onto the GO nanosheets has been carried out at different experimental conditions such as adsorption kinetics, concentration of adsorbate, pH, and temperature. The kinetics of the adsorption data were analyzed using four kinetic models such as the pseudo first-order model, pseudo second-order model, intraparticle diffusion, and the Boyd model to understand the adsorption behavior of malachite green onto the GO nanosheets and the mechanism of adsorption. The adsorption isotherm of adsorption of the malachite green onto the GO nanosheets has been investigated at 25, 35 and 45 °C. The equilibrium data were fitted well to the Langmuir model. Various thermodynamic parameters such as the Gibbs free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) change were also evaluated. The interaction of malachite green onto the GO nanosheets has been investigated by infrared Fourier transform (FT-IR) spectroscopy.

Keywords: adsorption, graphene oxide, kinetics, malachite green

Procedia PDF Downloads 418

Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Sung-Jun Yoo, Kazuhide Ito

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In this study, a comprehensive computer simulated person (CSP) that integrates computational human model (virtual manikin) and respiratory tract model (virtual airway), was applied for estimation of indoor environmental quality. Moreover, an inclusive prediction method was established by integrating computational fluid dynamics (CFD) analysis with advanced CSP which is combined with physiologically-based pharmacokinetic (PBPK) model, unsteady thermoregulation model for analysis targeting micro-climate around human body and respiratory area with high accuracy. This comprehensive method can estimate not only the contaminant inhalation but also constant interaction in the contaminant transfer between indoor spaces, i.e., a target area for indoor air quality (IAQ) assessment, and respiratory zone for health risk assessment. This study focused on the usage of the CSP as an air/thermal quality sensor in indoors, which means the application of comprehensive model for assessment of IAQ and thermal environmental quality. Demonstrative analysis was performed in order to examine the applicability of the comprehensive model to the heating, ventilation, air conditioning (HVAC) control scheme. CSP was located at the center of the simple model room which has dimension of 3m×3m×3m. Formaldehyde which is generated from floor material was assumed as a target contaminant, and flow field, sensible/latent heat and contaminant transfer analysis in indoor space were conducted by using CFD simulation coupled with CSP. In this analysis, thermal comfort was evaluated by thermoregulatory analysis, and respiratory exposure risks represented by adsorption flux/concentration at airway wall surface were estimated by PBPK-CFD hybrid analysis. These Analysis results concerning IAQ and thermal comfort will be fed back to the HVAC control and could be used to find a suitable ventilation rate and energy requirement for air conditioning system.

Keywords: CFD simulation, computer simulated person, HVAC control, indoor environmental quality

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Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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Authors: Dauda A. Oladosu, Kamorudeen A Olaiya, Abdurahman Bello

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The deployment of smart meters by utility providers to gather fine grained spatiotemporal consumption data has grossly influenced the consumers’ emotion and behavior towards energy utilization. The quest for reduction in power consumption is now a subject of concern and one the methods adopted by the consumers to achieve this is Non-intrusive Load (appliance) Monitoring. Hence, this work presents performance Analysis of Domotics System as a tool for load monitoring when integrated with Consumer Control Unit of residential building. The system was developed with basic elements which enhance remote sensing, DTMF (Dual Tone Multi-frequency) recognition and cryptic messaging when specific task was performed. To demonstrate its applicability and suitability, this prototype was used consistently for six months at different load demands and the utilities consumed were documented. The results obtained shows good response when phone dialed, and the packet delivery of feedback SMS was quite satisfactory, making the implemented system to be of good quality with affordable cost and performs the desired functions. Besides, comparative analysis showed notable reduction in energy consumption and invariably lessened electrical bill of the consumer.

Keywords: automation, domotics, energy, load, remote, schedule

Procedia PDF Downloads 322

Authors: K. Kouzi

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In order to have stable and high performance of direct torque and flux control (DTFC) of double star induction motor drive (DSIM), proper on-line adaptation of the stator resistance is very important. This is inevitably due to the variation of the stator resistance during operating conditions, which introduces error in estimated flux position and the magnitude of the stator flux. Error in the estimated stator flux deteriorates the performance of the DTFC drive. Also, the effect of error in estimation is very important especially at low speed. Due to this, our aim is to overcome the sensitivity of the DTFC to the stator resistance variation by proposing on-line fuzzy estimation stator resistance. The fuzzy estimation method is based on an on-line stator resistance correction through the variations of the stator current estimation error and its variations. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of the suggested algorithm control is to avoid the drive instability that may occur in certain situations and ensure the tracking of the actual stator resistance. The validity of the technique and the improvement of the whole system performance are proved by the results.

Keywords: direct torque control, dual stator induction motor, Fuzzy Logic estimation, stator resistance adaptation

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

Procedia PDF Downloads 339

Authors: Atif Zafar Khan, Swarnendra Singh, Imrana Naseem

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Breast cancer is one of the most frequent malignancies in women worldwide and a leading cause of cancer-related deaths among women. Therefore, there is a need to identify new chemotherapeutic strategies for cancer treatment. Unlike normal cells, cancer cells contain elevated copper levels which play an integral role in angiogenesis. Copper is an important metal ion associated with the chromatin DNA, particularly with guanine. Thus, targeting copper via copper-specific chelators in cancer cells can serve as effective anticancer strategy. Keeping in view these facts, we evaluated the anticancer activity and copper-dependent cytotoxic effect of coumestrol (phytoestrogen in soybean products) in breast cancer MCF-7 cells. Coumestrol inhibited proliferation and induced apoptosis in MCF-7 cells, which was prevented by copper chelator neocuproine and ROS scavengers. Coumestrol treatment induced ROS generation coupled to DNA fragmentation, up-regulation of p53/p21, cell cycle arrest at G1/S phase, mitochondrial membrane depolarization and caspases 9/3 activation. All these effects were suppressed by ROS scavengers and neocuproine. These results suggest that coumestrol targets elevated copper for redox cycling to generate ROS leading to DNA fragmentation. DNA damage leads to p53 up-regulation which directs the cell cycle arrest at G1/S phase and promotes caspase-dependent apoptosis of MCF-7 cells. In conclusion, coumestrol induces pro-oxidant cell death by chelating cellular copper to produce copper-coumestrol complexes that engages in redox cycling in breast cancer cells. Thus, targeting elevated copper levels might be a potential therapeutic strategy for selective cytotoxic action against malignant cells.

Keywords: apoptosis, breast cancer, copper chelation, coumestrol, reactive oxygens species, redox cycling

Procedia PDF Downloads 248

Authors: Vaikunthan Rajaratnam

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Intro: Motor imagery (MI) and mental practice (MP) can be an alternative to acquire mastery of surgical skills. One component of using this technique is the use of a mental script. The aim of this study was to design and develop a mental script for basic micro suturing training for skill acquisition using a low-fidelity rubber glove model and to describe the detailed methodology for this process. Methods: This study was based on a design and development research framework. The mental script was developed with 5 expert surgeons performing a cognitive walkthrough of the repair of a vertical opening in a rubber glove model using 8/0 nylon. This was followed by a hierarchal task analysis. A draft script was created, and face and content validity assessed with a checking-back process. The final script was validated with the recruitment of 28 participants, assessed using the Mental Imagery Questionnaire (MIQ). Results: The creation of the mental script is detailed in the full text. After assessment by the expert panel, the mental script had good face and content validity. The average overall MIQ score was 5.2 ± 1.1, demonstrating the validity of generating mental imagery from the mental script developed in this study for micro suturing in the rubber glove model. Conclusion: The methodological approach described in this study is based on an instructional design framework to teach surgical skills. This MP model is inexpensive and easily accessible, addressing the challenge of reduced opportunities to practice surgical skills. However, while motor skills are important, other non-technical expertise required by the surgeon is not addressed with this model. Thus, this model should act a surgical training augment, but not replace it.

Keywords: mental script, motor imagery, cognitive walkthrough, verbal protocol analysis, hierarchical task analysis

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Authors: Jihad H. Asad

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An expression for the Green’s function (GF) of anisotropic face cantered cubic (IFCC) lattice is evaluated analytically and numerically for a single impurity problem. The density of states (DOS), phase shift and scattering cross section are expressed in terms of complete elliptic integrals of the first kind.

Keywords: lattice Green's function, elliptic integral, physics, cubic lattice

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Authors: Sumitra Nuanmeesri

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The research focus on study, analyze and design the model of the infrastructure and computer networks for distance education, online learning via new media, e-learning and blended learning. The collected information from study and analyze process that information was evaluated by the index of item objective congruence (IOC) by 9 specialists to design model. The results of evaluate the model with the mean and standard deviation by the sample of 9 specialists value is 3.85. The results showed that the infrastructure and computer networks are designed to be appropriate to a great extent appropriate to a great extent.

Keywords: blended learning, new media, infrastructure and computer network, tele-education, online learning

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Authors: Mehvish Bilal, Navneet Singh, Jasir Mushtaq

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Water pollution puts people's health at risk, and it can also impact the ecology. For practitioners of integrated water resources management (IWRM), water quality modelling may be useful for informing decisions about pollution control (such as discharge permitting) or demand management (such as abstraction permitting). To comprehend the current pollutant load, movement of effective load movement of contaminants generates effective relation between pollutants, mathematical simulation, source, and water quality is regarded as one of the best estimating tools. The current study involves the Qual2k model, which includes manual simulation of the various physiochemical characteristics of water. To this end, various sensors could be installed for the automatic simulation of various physiochemical characteristics of water. An artificial intelligence model has been proposed for the automatic simulation of water quality parameters. Models of water quality have become an effective tool for identifying worldwide water contamination, as well as the ultimate fate and behavior of contaminants in the water environment. Water quality model research is primarily conducted in Europe and other industrialized countries in the first world, where theoretical underpinnings and practical research are prioritized.

Keywords: artificial intelligence, QUAL2K, simulation, physiochemical parameters

Procedia PDF Downloads 113

Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

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Authors: Chen Li-Ching

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The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test.

Keywords: case-control studies, goodness-of-fit test, Kolmogorov-Smirnov test, multinomial logistic regression

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Authors: Hossein Afzali

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Increasingly, decision analytic models are used to inform decisions about whether or not to publicly fund new health technologies. It is well noted that the accuracy of model predictions is strongly influenced by the appropriateness of model structuring. However, there is relatively inadequate methodological guidance surrounding this issue in guidelines developed by national funding bodies such as the Australian Pharmaceutical Benefits Advisory Committee (PBAC) and The National Institute for Health and Care Excellence (NICE) in the UK. This presentation aims to discuss issues around model structuring within decision making with a focus on (1) the need for a transparent and evidence-based model structuring process to inform the most appropriate set of structural aspects as the base case analysis; (2) the need to characterise structural uncertainty (If there exist alternative plausible structural assumptions (or judgements), there is a need to appropriately characterise the related structural uncertainty). The presentation will provide an opportunity to share ideas and experiences on how the guidelines developed by national funding bodies address the above issues and identify areas for further improvements. First, a review and analysis of the literature and guidelines developed by PBAC and NICE will be provided. Then, it will be discussed how the issues around model structuring (including structural uncertainty) are not handled and justified in a systematic way within the decision-making process, its potential impact on the quality of public funding decisions, and how it should be presented in submissions to national funding bodies. This presentation represents a contribution to the good modelling practice within the decision-making process. Although the presentation focuses on the PBAC and NICE guidelines, the discussion can be applied more widely to many other national funding bodies that use economic evaluation to inform funding decisions but do not transparently address model structuring issues e.g. the Medical Services Advisory Committee (MSAC) in Australia or the Canadian Agency for Drugs and Technologies in Health.

Keywords: decision-making process, economic evaluation, good modelling practice, structural uncertainty

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Authors: Katharine Pollock

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Feminist scholars assert that a defining aspect of feminist confessional literature is that it expresses both an individual and communal identity, one which is predicated on the commonly-shared aspects of female experience. Reading feminist confessional literature in this way accommodates a plurality of readerly experiences and textual interpretations. It affirms the individual whilst acknowledging those experiences which bind women together, and refuses traditional objective criticism. It invites readers to see themselves reflected in the text, and encourages them to share their own stories. Similarly, music which communicates women’s personal experience, fictive or not, expresses a dual identity. There is an inherent risk of imposing a confessional reading upon a musical or literary text. Understanding music as being multivocal in the same way as confessional literature negates this patriarchal tendency, and allows listeners to engage with both the subjective and collective aspects of a text. By hearing their own stories reflected in the music, listeners engage in an ongoing dialogic process in which female stories are prioritised. This refuses patriarchal silencing and ensures a diversity of female voices. To demonstrate the veracity of these claims, literary criticism is applied to Lily Allen’s music, and memoir My Thoughts Exactly.

Keywords: confession, female, feminist, literature, music

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Authors: Ozgu Turgut

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Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. Although in recent years, the efforts to make the transition to dripping or spring watering systems instead of using surface watering started to pay off. It is also known that this transition is not necessarily translated into an increase in the capacity dedicated to other water consumption channels such as city water or power usage. In order to control and allocate the water resource more purposefully, new watering systems have to be used with monitoring abilities that can limit the usage capacity for each farm. In this study, a decision support model which relies on a bi-objective stochastic linear optimization is proposed, which takes crop yield and price volatility into account. The model generates annual planting plans as well as water usage limits for each farmer in the region while taking the total value (i.e., profit) of the overall harvest. The mathematical model is solved using the L-shaped method optimally. The decision support model can be especially useful for regional administrations to plan next year's planting and water incomes and expenses. That is why not only a single optimum but also a set of representative solutions from the Pareto set is generated with the proposed approach.

Keywords: decision support, farming, water, tactical planning, optimization, stochastic, pareto

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Authors: Watin Alkhelaiwi, Iseult Wilson, Marian Traynor, Katherine Rogers

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Clinical nursing education allows nursing students to gain essential knowledge from practice experience and develop nursing skills in a variety of clinical environments. Integrating theoretical knowledge and practical skills is made easier for nursing students by providing opportunities for practice in a clinical environment. Nursing competency is an essential capability required to fulfill nursing responsibilities. Effective mentoring in clinical settings helps nursing students develop the necessary competence and promotes the integration of theory and practice. Preceptors play a considerable role in clinical nursing education, including the supervision of nursing students undergoing a rigorous clinical practicum. Preceptors are also involved in the clinical assessment of nursing students’ competency. The assessment of nursing students’ competence by professional practitioners is essential to investigate whether nurses have developed an adequate level of competence to deliver safe nursing care. Competency assessment remains challenging among nursing educators and preceptors, particularly owing to the complexity of the process. Consistency in terms of assessment methods and tools and valid and reliable assessment tools for measuring competence in clinical practice are lacking. Nurse preceptors must assess students’ competencies to prepare them for future professional responsibilities. Preceptors encounter difficulties in the assessment of competency owing to the nature of the assessment process, lack of standardised assessment tools, and a demanding clinical environment. The purpose of the study is to examine nursing preceptors’ experiences of assessing nursing interns’ competency in Saudi Arabia. There are three objectives in this study; the first objective is to examine the preceptors’ view of the Saudi assessment tool in relation to preceptorship, assessment, the assessment tool, the nursing curriculum, and the grading system. The second and third objectives are to examine preceptors’ view of "competency'' in nursing and their interpretations of the concept of competency and to assess the implications of the research in relation to the Saudi 2030 vision. The study uses an exploratory sequential mixed-methods design that involves a two-phase project: a qualitative focus group study is conducted in phase 1, and a quantitative study- a descriptive cross-sectional design (online survey) is conducted in phase 2. The results will inform the preceptors’ view of the Saudi assessment tool in relation to specific areas, including preceptorship and how the preceptors are prepared to be assessors, and assessment and assessment tools through identifying the appropriateness of the instrument for clinical practice. The results will also inform the challenges and difficulties that face the preceptors. These results will be analysed thematically for the focus group interview data, and SPSS software will be used for the analysis of the online survey data.

Keywords: clinical assessment tools, clinical competence, competency assessment, mentor, nursing, nurses, preceptor

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Authors: Sh. Heidari, A. J. Andrews, A. Oberoi

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Electrochemical storage of hydrogen in activated carbon electrodes as part of a reversible fuel cell offers a potentially attractive option for storing surplus electrical energy from inherently variable solar and wind energy resources. Such a system – which we have called a proton flow battery – promises to have a roundtrip energy efficiency comparable to lithium ion batteries, while having higher gravimetric and volumetric energy densities. In this paper, a theoretical model is presented of the process of H+ ion (proton) conduction through an acid electrolyte into a highly porous activated carbon electrode where it is neutralised and absorbed on the inner surfaces of pores. A Butler-Volmer type equation relates the rate of adsorption to the potential difference between the activated carbon surface and the electrolyte. This model for the hydrogen storage electrode is then incorporated into a more general computer model based on MATLAB software of the entire electrochemical cell including the oxygen electrode. Hence a theoretical voltage-current curve is generated for given input parameters for a particular activated carbon electrode. It is shown that theoretical VI curves produced by the model can be fitted accurately to experimental data from an actual electrochemical cell with the same characteristics. By obtaining the best-fit values of input parameters, such as the exchange current density and charge transfer coefficient for the hydrogen adsorption reaction, an improved understanding of the adsorption reaction is obtained. This new model will assist in designing improved proton flow batteries for storing solar and wind energy.

Keywords: electrochemical hydrogen storage, proton flow battery, butler-volmer equation, activated carbon

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Authors: Tobias Schramm, Günther Prokop

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Degraded vehicle shock absorbers represent a risk for road safety. The exact effect of degraded vehicle dampers on road safety is still the subject of research. This work is intended to contribute to estimating the effect of degraded twin-tube dampers of passenger cars on road safety. An axle model was built using a damper model to simulate different degradation levels. To parameterize the model, a realistic parameter space was estimated based on test rig measurements and database analyses, which is intended to represent the vehicle field in Germany. Within the parameter space, simulations of the axle model were carried out, which calculated the transmittable lateral forces of the various axle configurations as a function of vehicle speed, road surface, damper conditions and axle parameters. A degraded damper has the greatest effect on the transmittable lateral forces at high speeds and in poor road conditions. If a vehicle is traveling at a speed of 100 kph on a Class D road, a degraded damper reduces the transmissible lateral forces of an axle by 20 % on average. For individual parameter configurations, this value can rise to 50 %. The axle parameters that most influence the effect of a degraded damper are the vertical stiffness of the tire, the unsprung mass and the stabilizer stiffness of the axle.

Keywords: vehicle dynamics, vehicle simulation, vehicle component degradation, shock absorber model, shock absorber degradation

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Authors: Igor V. Kuzminov

Abstract:

The proposed article is a development of the topics of gravity, the inverse temperature dependence of gravity, the action of the inverse temperature dependence of gravity, and the second law of thermodynamics, dark matter, the identity of gravity, inertial forces, and centrifugal forces. All interaction schemes are built on the basis of Newton's laws of classical mechanics and Rutherford's planetary model of the structure of the atom. The basis of all constructions is the gyroscopic effect of rotation of all particles of the atomic structure. In this case, interatomic and intermolecular bonds are accepted as the static part of the gyroscope, and the rotation of an electron in an atom is accepted as the dynamic part. The structure of the planet Earth is accepted as a model of the structure of the Black Hole. Namely, gravitational and thermodynamic phenomena in the structure of the planet Earth are accepted as a model. Based on this model, assumptions are made about the processes inside the Black Hole. Moreover, a version is put forward, a scheme of a closed cycle of transformation of matter in the Universe.

Keywords: black hole, gravity, inverse temperature dependence of gravitational forces, second law of thermodynamics, gyroscopic effect, dark matter

Procedia PDF Downloads 34

Authors: Shingo Murakami, Shinichi Enoki

Abstract:

In structures, stress concentration is a factor of fatigue fracture. Basically, the stress concentration is a phenomenon that should be avoided. However, it is difficult to avoid the stress concentration. Therefore, relaxation of the stress concentration is important. The stress concentration arises from notches and circular holes. There is a relaxation method that a composite patch covers a notch and a circular hole. This relaxation method is used to repair aerial wings, but it is not systematized. Composites are more expensive than single materials. Accordingly, we propose the relaxation method that a single material patch covers a notch and a circular hole, and aim to systematize this relaxation method. We performed FEA (Finite Element Analysis) about an object by using a three-dimensional FEA model. The object was that a patch adheres to a plate with a circular hole. And, a uniaxial tensile load acts on the patched plate with a circular hole. In the three-dimensional FEA model, it is not easy to model the adhesion layer. Basically, the yield stress of the adhesive is smaller than that of adherents. Accordingly, the adhesion layer gets to plastic deformation earlier than the adherents under the yield stress of adherents. Therefore, we propose the three-dimensional FEA model which is applied a nonlinear elastic region to the adhesion layer. The nonlinear elastic region was calculated by a bilinear approximation. We compared the analysis results with the tensile test results to confirm whether the analysis model has usefulness. As a result, the analysis results agreed with the tensile test results. And, we confirmed that the analysis model has usefulness. As a result that the three-dimensional FEA model was used to the analysis, it was confirmed that an out-of-plane deformation occurred to the patched plate with a circular hole. The out-of-plane deformation causes stress increase of the patched plate with a circular hole. Therefore, we investigate that the out-of-plane deformation affects relaxation of the stress concentration in the plate with a circular hole on this relaxation method. As a result, it was confirmed that the out-of-plane deformation inhibits relaxation of the stress concentration on the plate with a circular hole.

Keywords: stress concentration, patch, out-of-plane deformation, Finite Element Analysis

Procedia PDF Downloads 271

Authors: Seema Paul, Jesper Oppelstrup, Roger Thunvik, Vladimir Cvetkovic

Abstract:

Lake Victoria is the second largest fresh water body in the world, located in East Africa with a catchment area of 250,000 km², of which 68,800 km² is the actual lake surface. The hydrodynamic processes of the shallow (40–80 m deep) water system are unique due to its location at the equator, which makes Coriolis effects weak. The paper describes a St.Venant shallow water model of Lake Victoria developed in COMSOL Multiphysics software, a general purpose finite element tool for solving partial differential equations. Depth soundings taken in smaller parts of the lake were combined with recent more extensive data to resolve the discrepancies of the lake shore coordinates. The topography model must have continuous gradients, and Delaunay triangulation with Gaussian smoothing was used to produce the lake depth model. The model shows large-scale flow patterns, passive tracer concentration and water level variations in response to river and tracer inflow, rain and evaporation, and wind stress. Actual data of precipitation, evaporation, in- and outflows were applied in a fifty-year simulation model. It should be noted that the water balance is dominated by rain and evaporation and model simulations are validated by Matlab and COMSOL. The model conserves water volume, the celerity gradients are very small, and the volume flow is very slow and irrotational except at river mouths. Numerical experiments show that the single outflow can be modelled by a simple linear control law responding only to mean water level, except for a few instances. Experiments with tracer input in rivers show very slow dispersion of the tracer, a result of the slow mean velocities, in turn, caused by the near-balance of rain with evaporation. The numerical and hydrodynamical model can evaluate the effects of wind stress which is exerted by the wind on the lake surface that will impact on lake water level. Also, model can evaluate the effects of the expected climate change, as manifest in changes to rainfall over the catchment area of Lake Victoria in the future.

Keywords: bathymetry, lake flow and steady state analysis, water level validation and concentration, wind stress

Procedia PDF Downloads 232

Authors: Abhishek Jha, Manoj Kumar

Abstract:

This paper proposes a new type of two wheels differential type odometry to estimate the next position and orientation of mobile robots. The proposed odometry is composed for two independent wheels with respective encoders. The two wheels rotate independently, and the change is determined by the difference in the velocity of the two wheels. Angular velocities of the two wheels are measured by rotary encoders. A mathematical model is proposed for the mobile robots to precisely move towards the goal. Using measured values of the two encoders, the current displacement vector of a mobile robot is calculated by kinematics of the mathematical model. Using the displacement vector, the next position and orientation of the mobile robot are estimated by proposed odometry. Result of simulator experiment by the developed odometry is shown.

Keywords: mobile robot, odometry, unicycle, differential type, encoders, infrared range sensors, kinematic model

Procedia PDF Downloads 457

Authors: Gul Nihal Gugul, Merih Aydinalp-Koksal

Abstract:

In this study, hourly energy consumption model of a single detached house in Ankara, Turkey is developed using ESP-r building energy simulation software. Natural gas is used for space heating, cooking, and domestic water heating in this two story 4500 square feet four-bedroom home. Hourly electricity consumption of the home is monitored by an automated meter reading system, and daily natural gas consumption is recorded by the owners during 2013. Climate data of the region and building envelope data are used to develop the model. The heating energy consumption of the house that is estimated by the ESP-r model is then compared with the actual heating demand to determine the performance of the model. Scenarios are applied to the model to determine the amount of reduction in the total energy consumption of the house. The scenarios are using photovoltaic panels to generate electricity, ground source heat pumps for space heating and solar panels for domestic hot water generation. Alternative scenarios such as improving wall and roof insulations and window glazing are also applied. These scenarios are evaluated based on annual energy, associated CO2 emissions, and fuel expenditure savings. The pay-back periods for each scenario are also calculated to determine best alternative energy source or technology option for this home to reduce annual energy use and CO2 emission.

Keywords: ESP-r, building energy simulation, residential energy saving, CO2 reduction

Procedia PDF Downloads 201