Search results for: state space model

Authors: Osama A. Terfas, Abdelhakim A. Hameda, Abdusalam A. Alktiwi

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An investigation on ductile crack growth of shallow semi-elliptical surface cracks with a/w=0.2, a/c=0.33 under bending was carried out, where a is the crack depth, w is the plate thickness and c is the crack length at surface. Finite element analysis and experiments were modelling and the crack growth model were verified with experimental data. The results showed that the initial crack shape was no longer maintained as the crack developed under ductile tearing. The maximum growth at the deepest point at early stages was stopped when the crack depth reached half thickness and growth occurred beneath surface. Excellent agreement in the crack shape patterns was observed between the experiments and the crack growth model.

Keywords: crack growth, ductile tearing, mean stress, surface cracks

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Authors: M. Khazam, M. Altawil, A. Eljabri

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Fluid properties in states near a vapor-liquid critical region are the most difficult to measure and to predict with EoS models. The principal model difficulty is that near-critical property variations do not follow the same mathematics as at conditions far away from the critical region. Libyan NC98 field in Sirte basin is a typical example of near critical fluid characterized by high initial condensate gas ratio (CGR) greater than 160 bbl/MMscf and maximum liquid drop-out of 25%. The objective of this paper is to model NC98 phase behavior with the proper selection of EoS parameters and also to model reservoir depletion versus gas cycling option using measured PVT data and EoS Models. The outcomes of our study revealed that, for accurate gas and condensate recovery forecast during depletion, the most important PVT data to match are the gas phase Z-factor and C7+ fraction as functions of pressure. Reasonable match, within -3% error, was achieved for ultimate condensate recovery at abandonment pressure of 1500 psia. The smooth transition from gas-condensate to volatile oil was fairly simulated by the tuned PR-EoS. The predicted GOC was approximately at 14,380 ftss. The optimum gas cycling scheme, in order to maximize condensate recovery, should not be performed at pressures less than 5700 psia. The contribution of condensate vaporization for such field is marginal, within 8% to 14%, compared to gas-gas miscible displacement. Therefore, it is always recommended, if gas recycle scheme to be considered for this field, to start it at the early stage of field development.

Keywords: EoS models, gas-condensate, gas cycling, near critical fluid

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Authors: Ajay Ivan

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This paper focuses on the cultural politics of health-promotional and disease-preventive pedagogic practices in the context of the national tobacco control programme in India. Tobacco consumption is typically problematised as a paradox: tobacco poses objective health risks such as cancer and heart disease, but its production, sale and export contribute significantly to state revenue. A blanket ban on tobacco products, therefore, is infeasible though desirable. Instead, initiatives against tobacco use have prioritised awareness creation and behaviour change to reduce its demand. This paper argues that public health communication is not, as commonly assumed, an apolitical and neutral transmission of disease-preventive information. Drawing on Michel Foucault’s concept of governmentality, it examines such campaigns as techniques of disciplining people rather than coercing them to give up tobacco use, which would be both impractical and counter-productive. At the level of the population, these programmes constitute a security mechanism that reduces risks without eliminating them, so as to ensure an optimal level of public health without hampering the economy. Anti-tobacco pedagogy thus aligns with a contemporary paradigm of health that emphasises risk-assessment and lifestyle management as tools of governance, using pedagogic techniques to teach people how to be healthy. The paper analyses the pictorial health warnings on tobacco packets and anti-tobacco advertisements in movie theatres mandated by the state, along with awareness-creation messages circulated by anti-tobacco advocacy groups in India, to show how they discursively construct tobacco and its consumption as a health risk. Smoking is resignified from a pleasurable and sociable practice to a deadly addiction that jeopardises the health of those who smoke and those who passively inhale the smoke. While disseminating information about the health risks of tobacco, these initiatives employ emotional and affective techniques of persuasion to discipline tobacco users. They incite fear of death and of social ostracism to motivate behaviour change, complementing their appeals to reason. Tobacco is portrayed as a grave moral danger to the family and a detriment to the vitality of the nation, such that using it contradicts one’s duties as a parent or citizen. Awareness programmes reproduce prevailing societal assumptions about health and disease, normalcy and deviance, and proper and improper conduct. Pedagogy thus functions as an apparatus of public health governance, recruiting subjects as volunteers in their own regulation and aligning their personal goals and aspirations to the objectives of tobacco control. The paper links this calculated management of subjectivity and the self-responsibilisation of the pedagogic subject to a distinct mode of neoliberal civic governance in contemporary India. Health features prominently in this mode of governance that serves the biopolitical obligation of the state as laid down in Article 39 of the Constitution, which includes a duty to ensure the health of its citizens. Insofar as the health of individuals is concerned, the problem is how to balance this duty of the state with the fundamental right of the citizen to choose how to live. Public health pedagogy, by directing the citizen’s ‘free’ choice without unduly infringing upon it, offers a tactical solution.

Keywords: public health communication, pedagogic power, tobacco control, neoliberal governance

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Authors: Rabia Aslam

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Overwhelming evidence from all around the world suggests that high-quality teacher professional development facilitates the improvement of teaching practices which in turn could improve student learning outcomes. The new Continuous Professional Development (CPD) model for primary school teachers in Punjab uses a blended approach in which pedagogical content knowledge is delivered through technology (high-quality instructional videos and lesson plans delivered to school tablets or mobile phones) with face-to-face support by Assistant Education Officers (AEOs). The model also develops Communities of Practice operationalized through formal meetings led by the AEOs and informal interactions through social media groups to provide opportunities for teachers to engage with each other and share their ideas, reflect on learning, and come up with solutions to issues they experience. Using Kirkpatrick’s 4 levels of the learning evaluation model, this paper investigates how school tablets and teacher mobile phones may act as transformational cultural tools to potentially expand perceptions and access to teaching and learning resources and explore some of the affordances of social media (Facebook, WhatsApp groups) in learning in an informal context. The results will be used to inform policy-level decisions on what shape could CPD of all teachers take in the context of a developing country like Pakistan.

Keywords: CPD, teaching & learning, blended learning, learning technologies

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Authors: Stephen E. Cross, Donald P. McConnell

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In the past decade, market pressures and decreasing U.S. federal budgets for science and technology have led to a fundamental change in expectations for corporate investments in innovation. The trend to significant, sustained corporate research collaboration with major academic centres has called for rethinking the balance between academic and corporate roles in these relationships. The Georgia Institute of Technology has developed a system-focused strategy for transformational research focused on grand challenges in areas of importance both to faculty and to industry collaborators. A model of an innovation ecosystem is used to guide both research and university-industry collaboration. The paper describes the strategy, the model, and the results to date including the benefits both to university research and industry collaboration. Key lessons learned are presented based on this experience.

Keywords: ecosystem, industry collaboration, innovation, research strategy

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Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

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A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

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The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: building information management, BIM, economic order quantity, EOQ, fixed order point, FOP, BIM 4D, BIM 5D

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Authors: Emmanuel Olugbenga Fakoya

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The study examined the perceived impact of climate change on the livelihood of arable crop farmers in Ipokia Local Government Area of Ogun State, Nigeria. Multistage sampling technique was used to select 80 arable crop farmers in the study area. Data collected were analyzed using percentages, frequencies and Chi square analysis. The result showed that 63.8 percent of the respondents were male while 55.0 percent were married. Less than half (30.0 percent) of the respondents were between the age bracket of 41-50 years and 50.0 percent had 6-10 household size. Furthermore, majority (40.0 percent) of the arable crop farmers farmed on an inherited land and 51.3 percent had 2-3 hectares of land. Majority (38.8 percent) of the farmers intercrop maize with cassava and maize with yam. Various strategies adapted to reduce the effect of climate change on their crop and livelihood include: crop rotation (53.8 percent), planting of leguminous crop (35.0 percent), application of organic fertilizers (45.0 percent), mulching (56.3 percent) and by planting drought resistance crops (46.5 percent). Reported among the effects of climate change on crop and farmers’ livelihood were: discoloration of crop leave (63.8 percent), increase infestation of pests and diseases (58.8 percent) and reduction of crop yield (60.0 percent). Chi- square analysis showed significant relationship between impact of climate change on arable crop production and thus famers’ livelihood. It was concluded from the study that climate change is an impinging factor that seriously affect arable crop production and hence farmers’ livelihood despite coping strategies to minimize its effect. It was however recommended that Agricultural policies and practices that could minimize or eliminate its effect should be seriously enacted to boost production and increase farmers’ livelihood.

Keywords: agricultural extension, extension agent, private sector, perception

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Authors: M. Benjamin Stacey

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Energy efficiency has been increasingly recognized as a high value resource through state policies that require utility companies to implement efficiency programs. While policymakers have recognized the statewide economic, environmental, and health related value to residents who rely on this grid supplied resource, varying interests in energy efficiency between socioeconomic groups stands undifferentiated in most state legislation. Instead, the benefits are oftentimes assumed to be distributed equitably across these groups. Despite this fact, these policies are frequently sited by advocacy groups, regulatory bodies and utility companies for their ability to address the negative financial, health and other social impacts of energy poverty in low income communities. Yet, while most states like Michigan require programs that target low income consumers, oftentimes no requirements exist for the equitable investment and energy savings for low income consumers, nor does it stipulate minimal spending levels on low income programs. To further understand the impact of the absence of these factors in legislation, this study examines the distribution of program funds and energy efficiency savings to answer a fundamental energy justice concern; Are there disparities in the investment and benefits of energy efficiency programs between socioeconomic groups? This study compiles data covering the history of Michigan’s Energy Efficiency policy implementation from 2010-2016, analyzing the energy efficiency portfolios of Michigan’s two main energy providers. To make accurate comparisons between these two energy providers' investments and energy savings in low and non-low income programs, the socioeconomic variation for each utility coverage area was captured and accounted for using GIS and US Census data. Interestingly, this study found that both providers invested more equitably in natural gas efficiency programs, however, together these providers invested roughly three times less per household in low income electricity efficiency programs, which resulted in ten times less electricity savings per household. This study also compares variation in commission approved utility plans and actual spending and savings results, with varying patterns pointing to differing portfolio management strategies between companies. This study reveals that for the history of the implementation of Michigan’s Energy Efficiency Policy, that the 35% of Michigan’s population who qualify as low income have received substantially disproportionate funding and energy savings because of the policy. This study provides an overview of results from a social perspective, raises concerns about the impact on energy poverty and equity between consumer groups and is an applicable tool for law makers, regulatory agencies, utility portfolio managers, and advocacy groups concerned with addressing issues related to energy poverty.

Keywords: energy efficiency, energy justice, low income, state policy

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Authors: Obose Angela Oriazowanlan

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The role of entrepreneurship in preventing poverty and mitigating other post-retirement challenges has been acknowledged to be crucial for effective post-retirement life management, but financial constraints could constitute a bane to pre-retirees’ entrepreneurial intentions. Therefore, the study determined the financial knowledge that could spur their intentions and readiness for a business start that could enable them to surmount post-retirement life challenges. Two research questions guided the study. The descriptive survey research design was adopted and the population comprised all the pre-retirees in universities in Edo State. 250 respondents were randomly selected using the simple random sampling technique from three purposive selected universities. Primary data were gathered through the use of a structured questionnaire, which was validated and tested to have a reliability coefficient value of 0.84. The descriptive statistics of mean and standard deviation were used to answer the research questions and test the respondents’ homogeneity. The findings revealed, among others, that the respondents perceived the benefits of entrepreneurship-business startups to ensure their effective post-retirement life management but intended to rely totally on their retirement savings benefits with the Contributory Pension Scheme (CPS) for business startups. Based on the findings, it was recommended, among others, that pre-retirees should make contingency savings plans and that the employers and government should provide them with financial education in order to acquaint them with relevant financial knowledge to access other forms of business financing such as loans, bank overdraft, angel investors, venture capital and government grants among others prior to final disengagement.

Keywords: financial knowledge, entrepreneurial intentions, availability of business funds, business investment and fulfilled post-retirement living.

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Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

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Authors: Mahdieh Jajroudi

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Developing a pharmacokinetic model for the neuroendocrine tumors therapy agent 177Lu-DOTATATE in nude mice bearing AR42J rat pancreatic tumor to investigate and evaluate the behavior of the complex was the main purpose of this study. The utilization of compartmental analysis permits the mathematical differencing of tissues and organs to become acquainted with the concentration of activity in each fraction of interest. Biodistribution studies are onerous and troublesome to perform in humans, but such data can be obtained facilely in rodents. A physiologically based pharmacokinetic model for scaling up activity concentration in particular organs versus time was developed. The mathematical model exerts physiological parameters including organ volumes, blood flow rates, and vascular permabilities; the compartments (organs) are connected anatomically. This allows the use of scale-up techniques to forecast new complex distribution in humans' each organ. The concentration of the radiopharmaceutical in various organs was measured at different times. The temporal behavior of biodistribution of 177Lu labeled somatostatin analogues was modeled and drawn as function of time. Conclusion: The variation of pharmaceutical concentration in all organs is characterized with summation of six to nine exponential terms and it approximates our experimental data with precision better than 1%.

Keywords: biodistribution modeling, compartmental analysis, 177Lu labeled somatostatin analogues, neuroendocrine tumors

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Authors: Anel Hasić, Naser Prljača

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In the domain of autonomous or piloted flights, the accurate control of quadrotor trajectories is of paramount significance for large numbers of tasks. These adaptable aerial platforms find applications that span from high-precision aerial photography and surveillance to demanding search and rescue missions. Among the fundamental challenges confronting quadrotor operation is the demand for accurate following of desired flight paths. To address this control challenge, among others, two celebrated well-established control strategies have emerged as noteworthy contenders: Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) control. In this work, we focus on the extensive examination of MPC and PID control techniques by using comprehensive simulation studies in MATLAB/Simulink. Intensive simulation results demonstrate the performance of the studied control algorithms.

Keywords: MATLAB, MPC, PID, quadcopter, simulink

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Authors: Rene Hellmuth

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring of the factory building is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A building information model (BIM) is the planning basis for rebuilding measures and becomes an indispensable data repository to be able to react quickly to changes. Use as a planning basis for restructuring measures in factories only succeeds if the BIM model has adequate data quality. Under this aspect and the industrial requirement, three data quality factors are particularly important for this paper regarding the BIM model: up-to-dateness, completeness, and correctness. The research question is: how can a BIM model be kept up to date with required data quality and which visualization techniques can be applied in a short period of time on the construction site during conversion measures? An as-is analysis is made of how BIM models and digital factory models (including laser scans) are currently being kept up to date. Industrial companies are interviewed, and expert interviews are conducted. Subsequently, the results are evaluated, and a procedure conceived how cost-effective and timesaving updating processes can be carried out. The availability of low-cost hardware and the simplicity of the process are of importance to enable service personnel from facility mnagement to keep digital factory models (BIM models and laser scans) up to date. The approach includes the detection of changes to the building, the recording of the changing area, and the insertion into the overall digital twin. Finally, an overview of the possibilities for visualizations suitable for construction sites is compiled. An augmented reality application is created based on an updated BIM model of a factory and installed on a tablet. Conversion scenarios with costs and time expenditure are displayed. A user interface is designed in such a way that all relevant conversion information is available at a glance for the respective conversion scenario. A total of three essential research results are achieved: As-is analysis of current update processes for BIM models and laser scans, development of a time-saving and cost-effective update process and the conception and implementation of an augmented reality solution for BIM models suitable for construction sites.

Keywords: building information modeling, digital factory model, factory planning, restructuring

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Authors: Lungile Maliba, O. I. Nkwonta, E Onyari

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Water resources development and management are regarded as crucial for poverty reduction in many developing countries and sustainable economic growth such as South Africa. The contribution of large hydraulic infrastructure and management of it, particularly reservoirs, to development remains controversial. This controversy stems from the fact that from a historical point of view construction of reservoirs has brought fewer benefits than envisaged and has resulted in significant environmental and social costs. A further complexity in reservoir management is the variety of stakeholders involved, all with different objectives, including domestic and industrial water use, flood control, irrigation and hydropower generation. The objective was to evaluate technical adaptation options for kleinfontein Dam’s current operating rule curves. To achieve this objective, the current operating rules curves being used in the sub-basin were analysed. An objective methodology was implemented in other to get the operating rules with regards to the target storage curves. These were derived using the Water Resources Yield/Planning Model (WRY/PM), with the aim of maximising of releases to demand zones. The result showed that the system is over allocated and in addition the demands exceed the long-term yield that is available for the system. It was concluded that the current operating rules in the system do not produce the optimum operation such as target storage curves to avoid supply failures in the system.

Keywords: infrastructure, Kleinfontein dam, operating rule curve, water resources yield and planning model

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Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Asmaa Zaraq

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In the present work we report X-ray powder diffraction measurements of SrCaCoTeO6 and SrCaNiTeO6, at different temperatures. The crystal structures at room temperature of both compounds are determined; and results showing the existence of high-temperature phase transitions in them are presented. Both compounds have double perovskite structure with 1:1 ordered arrangement of the B site cations. At room temperature their symmetries are described with the P21/n space group, that correspond to the (a+b-b-) tilt system. The evolution with temperature of the structure of both compounds shows the presence of three phase transitions: a continuous one, at 450 and 500 K, a discontinuous one, at 700 and 775 K, and a continuous one at 900 and 950 K for SrCaCoTeO6 and SrCaNiTeO6, respectively with the following phase-transition sequence: P21/n → I2/m → I4/m → Fm-3m.

Keywords: double perovskites, caracterisation DRX, transition de phase

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Authors: Tehreem Fatima, Enjun Xia

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The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Rong-Tsorng Wang

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In this paper, we derive a pricing formula for catastrophe equity put options (or CatEPut) with non-homogeneous loss and approximated compound distributions. We assume that the loss claims arrival process is a nonhomogeneous Poisson process (NHPP) representing the clustering occurrences of loss claims, the size of loss claims is a sequence of independent and identically distributed random variables, and the accumulated loss distribution forms a compound distribution and is approximated by a heavy-tailed distribution. A numerical example is given to calibrate parameters, and we discuss how the value of CatEPut is affected by the changes of parameters in the pricing model we provided.

Keywords: catastrophe equity put options, compound distributions, nonhomogeneous Poisson process, pricing model

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Authors: Yohei Saika

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On the basis of Bayesian inference using the maximizer of the posterior marginal estimate, we carry out phase unwrapping using multiple interferograms via generalized mean-field theory. Numerical calculations for a typical wave-front in remote sensing using the synthetic aperture radar interferometry, phase diagram in hyper-parameter space clarifies that the present method succeeds in phase unwrapping perfectly under the constraint of surface- consistency condition, if the interferograms are not corrupted by any noises. Also, we find that prior is useful for extending a phase in which phase unwrapping under the constraint of the surface-consistency condition. These results are quantitatively confirmed by the Monte Carlo simulation.

Keywords: Bayesian inference, generalized mean-field theory, phase unwrapping, multiple interferograms, statistical mechanics

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Authors: Shilpa Sahoo, Michel Louge, Anthony Reeves, Olivier Desjardins, Susan Daniel, Sadik Omowunmi

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The microgravity on the International Space Station (ISS) was exploited to study the imbibition of water into a network of hydrophilic cylindrical capillaries on time and length scales long enough to observe details hitherto inaccessible under Earth gravity. When a drop touches a porous medium, it spreads as if laid on a composite surface. The surface first behaves as a hydrophobic material, as liquid must penetrate pores filled with air. When contact is established, some of the liquid is drawn into pores by a capillarity that is resisted by viscous forces growing with length of the imbibed region. This process always begins with an inertial regime that is complicated by possible contact pinning. To study imbibition on Earth, time and distance must be shrunk to mitigate gravity-induced distortion. These small scales make it impossible to observe the inertial and pinning processes in detail. Instead, in the International Space Station (ISS), astronaut Luca Parmitano slowly extruded water spheres until they touched any of nine capillary plates. The 12mm diameter droplets were large enough for high-speed GX1050C video cameras on top and side to visualize details near individual capillaries, and long enough to observe dynamics of the entire imbibition process. To investigate the role of contact pinning, a text matrix was produced which consisted nine kinds of porous capillary plates made of gold-coated brass treated with Self-Assembled Monolayers (SAM) that fixed advancing and receding contact angles to known values. In the ISS, long-term microgravity allowed unambiguous observations of the role of contact line pinning during the inertial phase of imbibition. The high-speed videos of spreading and imbibition on the porous plates were analyzed using computer vision software to calculate the radius of the droplet contact patch with the plate and height of the droplet vs time. These observations are compared with numerical simulations and with data that we obtained at the ESA ZARM free-fall tower in Bremen with a unique mechanism producing relatively large water spheres and similarity in the results were observed. The data obtained from the ISS can be used as a benchmark for further numerical simulations in the field.

Keywords: droplet imbibition, hydrophilic surface, inertial phase, porous medium

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Authors: M. Gowri, E. K. Girija, V. Ganesh

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Background and Significance: Among the dental infections, inflammation and infection of the root canal are common among all age groups. Currently, the management of root canal infections involves cleaning the canal with powerful irrigants followed by intracanal medicament application. Though these treatments have been in vogue for a long time, root canal failures do occur. Treatment for root canal infections is limited due to the anatomical complexity in terms of small micrometer volumes and poor penetration of drugs. Thus, infections of the root canal seem to be a challenge that demands development of new agents that can eradicate E. faecalis. Methodology: In the present study, we synthesized and screened silver-curcumin nanoparticle against E. faecalis. Morphological cell damage and antibiofilm activity of silver-curcumin nanoparticle on E. faecalis was studied using scanning electron microscopy (SEM). Biochemical evidence for membrane damage was studied using flow cytometry. Further, the antifungal activity of silver-curcumin nanoparticle was evaluated in an ex vivo dentinal tubule infection model. Results: Screening data showed that silver-curcumin nanoparticle was active against E. faecalis. silver-curcumin nanoparticle exerted time kill effect. Further, SEM images of E. faecalis showed that silver-curcumin nanoparticle caused membrane damage and inhibited biofilm formation. Biochemical evidence for membrane damage was confirmed by increased propidium iodide (PI) uptake in flow cytometry. Further, the antifungal activity of silver-curcumin nanoparticle was evaluated in an ex vivo dentinal tubule infection model, which mimics human tooth root canal infection. Confocal laser scanning microscopy studies showed eradication of E. faecalis and reduction in colony forming unit (CFU) after 24 h treatment in the infected tooth samples in this model. Further, silver-curcumin nanoparticle was found to be hemocompatible, not cytotoxic to normal mammalian NIH 3T3 cells and non-mutagenic. Conclusion: The results of this study can pave the way for developing new antibacterial agents with well deciphered mechanisms of action and can be a promising antibacterial agent or medicament against root canal infection.

Keywords: ex vivo dentine model, inhibition of biofilm formation, root canal infection, silver-curcumin nanoparticle

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Authors: K. Debkowska

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The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

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Authors: John Akpesiri Olotewo

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One of the controversies in existing marketing literatures is on how to retain existing and new customers to have repurchase intention in the long-run; however, empirical answer to this question is scanty in existing studies. Thus, this study investigates the moderating effect of consumer loyalty on long-run repurchase intentions in telecommunication industry using Lagos State environs. The study adopted field survey research design using questionnaire to elicit responses from 250 respondents who were selected using random and stratified random sampling techniques from the telecommunication industry in Lagos State, Nigeria. The internal consistency of the research instrument was verified using the Cronbach’s alpha, the result of 0.89 implies the acceptability of the internal consistency of the survey instrument. The test of the research hypotheses were analyzed using Pearson Product Method of Correlation (PPMC), simple regression analysis and inferential statistics with the aid of Statistical Package for Social Science version 20.0 (SPSS). The study confirmed that customer satisfaction has a significant relationship with customer loyalty in the telecommunication industry; also Service quality has a significant relationship with customer loyalty to a brand; loyalty programs have a significant relationship with customer loyalty to a network operator in Nigeria and Customer loyalty has a significant effect on the long run repurchase intentions of the customer. The study concluded that one of the determinants of long term profitability of a business entity is the long run repurchase intentions of its customers which hinges on the level of brand loyalty of the customer. Thus, it was recommended that service providers in Nigeria should improve on factors like customer satisfaction, service quality, and loyalty programs in order to increase the loyalty of their customer to their brands thereby increasing their repurchase intentions.

Keywords: customer loyalty, long run repurchase intentions, brands, service quality and customer satisfaction

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Authors: Manasa Kalla, Narasimha Raju Chebrolu, Ashok Chatterjee

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We have studied the quantum transport properties of a single molecular transistor in the presence of an external magnetic field using the Keldysh Green function technique. We also used the Anderson-Holstein-Caldeira-Leggett Model to describe the single molecular transistor that consists of a molecular quantum dot (QD) coupled to two metallic leads and placed on a substrate that acts as a heat bath. The phonons are eliminated by the Lang-Firsov transformation and the effective Hamiltonian is used to study the effect of an external magnetic field on the spectral density function, Tunneling Current, Differential Conductance and Spin polarization. A peak in the spectral function corresponds to a possible excitation. In the presence of a magnetic field, the spin-up and spin-down states are degenerate and this degeneracy is lifted by the magnetic field leading to the splitting of the central peak of the spectral function. The tunneling current decreases with increasing magnetic field. We have observed that even the differential conductance peak in the zero magnetic field curve is split in the presence electron-phonon interaction. As the magnetic field is increased, each peak splits into two peaks. And each peak indicates the existence of an energy level. Thus the number of energy levels for transport in the bias window increases with the magnetic field. In the presence of the electron-phonon interaction, Differential Conductance in general gets reduced and decreases faster with the magnetic field. As magnetic field strength increases, the spin polarization of the current is increasing. Our results show that a strongly interacting QD coupled to metallic leads in the presence of external magnetic field parallel to the plane of QD acts as a spin filter at zero temperature.

Keywords: Anderson-Holstein model, Caldeira-Leggett model, spin-polarization, quantum dots

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Authors: Huseyin Gokberk, Shian Gao

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CFD analysis of the relationship between the coefficients of lift and drag with respect to the angle of attack on a NACA 2412 wing section of an RC plane is conducted. Both the 2D and 3D models are investigated with the turbulence model. The 2D analysis has a free stream velocity of 10m/s at different AoA of 0°, 2°, 5°, 10°, 12°, and 15°. The induced drag and drag coefficient increased throughout the changes in angles even after the critical angle had been exceeded, whereas the lift force and coefficient of lift increased but had a limit at the critical stall angle, which results in values to reduce sharply. Turbulence flow characteristics are analysed around the aerofoil with the additions caused due to a finite 3D model. 3D results highlight how wing tip vortexes develop and alter the flow around the wing with the effects of the tapered configuration.

Keywords: CFD, turbulence modelling, aerofoil, angle of attack

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

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

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

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: palm oil, fatty acid, NIRS, regression

Procedia PDF Downloads 489