Search results for: CCR Model

Authors: Adam Bownik, Małgorzata Adamczuk, Barbara Pawlik-Skowrońska

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Certain strains of cyanobacteria, microorganisms forming water blooms, produce toxic secondary metabolites. Although various effects of cyanotoxins in aquatic animals are known, little data can be found on the influence of some cyanobacterial oligopeptides beyond microcystins. The aim of the present study was to determine the toxicity of novel pure cyanobacterial oligopeptides: microginin FR-1 (MGFR1) and anabaenopeptin-A (ANA-A) on a transparent model rotifer Brachionus calyciflorus with the use of fluorescent double staining with Hoechst 34580 and propidium iodide. The obtained results showed that both studied oligopeptides decreased the fluorescence intensity of animals stained with Hoechst 34580 in a concentration-dependent manner. On the other hand, a concentration-dependent increase of propidium iodide fluorescence was noted in the exposed rotifers. The results suggest that MGFR-1 and ANA-A should be considered as a potent toxic agent to freshwater rotifers, and fluorescent staining with Hoechst and propidium iodide may be a valuable tool for determination of toxicity of cyanobacterial oligopeptides in rotifers.

Keywords: cyanobacteria, brachionus, oligopeptides, fluorescent staining, hoechst, propidium iodide

Procedia PDF Downloads 130

Authors: A. Bogdanovic, M. Vitanova, J. Bojadjieva, Z. Rakicevic, V. Sesov, K. Edip, N. Naumovski, F. Manojlovski, A.Popovska, A. Shoklarovski, T. Kitanovski, D. Ivanovski, I. Markovski, D. Filipovski

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The conditions of existing structures change in the course of time and can hardly be characterized particularly if a bridge has long been in function and there is no design documentation related to it. To define the real conditions of a structure, detailed static and dynamic analysis of the structure has to be carried out and its modal parameters have to be defined accurately. Modal analysis enables a quite accurate identification of the natural frequencies and mode shapes. Presented in this paper are the results from the performed detailed analyses of a steel truss bridge that has been in use for more than 7 decades by the military services of R.N. Macedonia and for which there is no documentation at all. Static and dynamic investigations and ambient vibration measurements were performed. The acquired data were used to identify the mode shapes that were used for comparison with the numerical model. Dynamic tests were performed to define the bridge behaviour and the damping index. Finally, based on all the conducted detailed analyses and investigations, conclusions on the conditions of the bridge structure were drawn.

Keywords: ambient vibrations, dynamic identification, in-situ measurement, steel truss bridge

Procedia PDF Downloads 91

Authors: Ming Wen, Nasim Nezamoddini

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Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

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Authors: Ren Moses

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The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: Nassim Labdaoui, Fabienne Nouvel, Stéphane Dutertre

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The Internet of Things (IoT) is emerging as a crucial communication technology for the future. Many solutions have been proposed, and among them, licensed operators have put forward LTE-M and NB-IoT. However, implementing these technologies requires a good understanding of the device energy requirements, which can vary depending on the coverage conditions. In this paper, we investigate the power consumption of LTE-M and NB-IoT devices using Ublox SARA-R422S modules based on relevant standards from two French operators. The measurements were conducted under different coverage conditions, and we also present an empirical consumption model based on the different states of the radio modem as per the RRC protocol specifications. Our findings indicate that these technologies can achieve a 5 years operational battery life under certain conditions. Moreover, we conclude that the size of transmitted data does not have a significant impact on the total power consumption of the device under favorable coverage conditions. However, it can quickly influence the battery life of the device under harsh coverage conditions. Overall, this paper offers insights into the power consumption of LTE-M and NBIoT devices and provides useful information for those considering the use of these technologies.

Keywords: internet of things, LTE-M, NB-IoT, MQTT, cellular IoT, power consumption

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Armin Parsian Nejad

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The rapidly growing wind industry is highly expressing the need for education and training worldwide, particularly on the system level. Modelling and simulating wind generator system using Matlab-Simulink provides expert help in understanding wind systems engineering and system design. Working under Matlab-Simulink we present the integration of the developed WECS model with public electrical grid. A test of the calculated power and Cp related to the experimental equivalent data, using statistical analysis is performed. The statistical indicators of accuracy show better results of the presented method with RMSE: 21%, 22%, MBE : 0.77%, 0.12 % and MAE :3%, 4%.On the other hand we study its behavior when integrated in whole power system. Three level of wind speeds have been chosen: low with 5m/s as the mean value, medium with 8m/s as the mean value and high speed with 12m/s as the mean value. These allowed predicting and supervising the active power produced by the system, characterized respectively by the middle powers of -150 kW, -250kW and -480 kW which will be injected directly into the public electrical grid and the reactive power, characterized respectively by the middle powers of 60 kW, 180 kW and 320 kW and will be consumed by the wind generator.

Keywords: modelling, simulation, wind generator, fixed speed wind turbine, Matlab-Simulink

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Authors: Naoum Mylonas, Eugenia Petridou

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Objectives: The objectives of this research are firstly, to develop an integrated model of predicting factors to new ventures performance, taking into account certain issues and specificities related to creative industry and female entrepreneurship based on the prior research; secondly, to determine the appropriate measures of venture performance in a creative industry context, drawing upon previous surveys; thirdly, to illustrate the importance of entrepreneurial orientation, networking ties, environment dynamism and access to financial capital on new ventures performance. Prior Work: An extant review of the creative industry literature highlights the special nature of entrepreneurship in this field. Entrepreneurs in creative industry share certain specific characteristics and intensions, such as to produce something aesthetic, to enrich their talents and their creativity, and to combine their entrepreneurial with their artistic orientation. Thus, assessing venture performance and success in creative industry entails an examination of how creative people or artists conceptualize success. Moreover, female entrepreneurs manifest more positive attitudes towards sectors primarily based on creativity, rather than innovation in which males outbalance. As creative industry entrepreneurship based mainly on the creative personality of the creator / artist, a high interest is accrued to examine female entrepreneurship in the creative industry. Hypotheses development: H1a: Female entrepreneurs who are more entrepreneurially-oriented show a higher financial performance. H1b: Female entrepreneurs who are more artistically-oriented show a higher creative performance. H2: Female entrepreneurs who have personality that is more creative perform better. H3: Female entrepreneurs who participate in or belong to networks perform better. H4: Female entrepreneurs who have been consulted by a mentor perform better. Η5a: Female entrepreneurs who are motivated more by pull-factors perform better. H5b: Female entrepreneurs who are motivated more by push-factors perform worse. Approach: A mixed method triangulation design has been adopted for the collection and analysis of data. The data are collected through a structured questionnaire for the quantitative part and through semi-structured interviews for the qualitative part as well. The sample is 293 Greek female entrepreneurs in the creative industry. Main findings: All research hypotheses are accepted. The majority of creative industry entrepreneurs evaluate themselves in creative performance terms rather than financial ones. The individuals who are closely related to traditional arts sectors have no EO but also evaluate themselves highly in terms of venture performance. Creative personality of creators is appeared as the most important predictor of venture performance. Pull factors in accordance with our hypothesis lead to higher levels of performance compared to push factors. Networking and mentoring are viewed as very important, particularly now during the turbulent economic environment in Greece. Implications-Value: Our research provides an integrated model with several moderating variables to predict ventures performance in the creative industry, taking also into account the complicated nature of arts and the way artists and creators define success. At the end, the findings may be used for the appropriate design of educational programs in creative industry entrepreneurship. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.

Keywords: venture performance, female entrepreneurship, creative industry, networks

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Nader Pourmahmoud, Amir Hassanzadeh

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This article investigates the effects of inlet pressure in a newly introduced vortex tube which has been equipped with an additional vortex chamber. A 3-D compressible turbulent flow computation has been carried out toward analysis of complex flow field in this apparatus. Numerical results of flows are derived by utilizing the standard k-ε turbulence model for analyzing high rotating complex flow field. The present research has focused on cooling effect and given a characteristics curve for minimum cool temperature. In addition, the effect of inlet pressure for both chambers has been studied in details. To be presented numerical results show that the effect of inlet pressure in second chamber has more important role in improving the performance of the vortex tube than first one. By increasing the pressure in the second chamber, cold outlet temperature reaches a higher decrease. When both chambers are fed with high pressure fluid, best operation condition of vortex tube occurs. However, it is not possible to feed both chambers with high pressure due to the conditions of working environment.

Keywords: energy separation, inlet pressure, numerical simulation, vortex chamber, vortex tube

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Authors: Seyed Jamal Haddadi, M. Reza Mehranpour, Roya Sadat Mortazavi, Zahra Sadat Mortazavi

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Principal aim of this research is trajectory tracking, attitude and position control scheme in real flight mode by an Octorotor helicopter. For more stability, in this Unmanned Aerial Vehicle (UAV), number of motors is increased to eight motors which end of each arm installed two coaxial counter rotating motors. Dynamic model of this Octorotor includes of motion equation for translation and rotation. Utilized controller is proportional-integral-derivative (PID) control loop. The proposed controller is designed such that to be able to attenuate an effect of external wind disturbance and guarantee stability in this condition. The trajectory is determined by a Global Positioning System (GPS). Also an ARM CortexM4 is used as microprocessor. Electronic board of this UAV designed as able to records all of the sensors data, similar to an aircraft black box in external memory. Finally after auto landing of Octorotor, flight data is shown in MATLAB software and Experimental results of the proposed controller show the effectiveness of our approach on the Autonomous Quadrotor in real conditions.

Keywords: octorotor, design, PID controller, autonomous, trajectory tracking

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Sireesha Tamada, Debraj Bhattacharjee, Pranab K. Dan, Prabha Bhola

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The most important component in an automotive transmission system is the gearbox which controls the speed of the vehicle. In an automatic transmission, the right positioning of actuators ensures efficient transmission mechanism embodiment, wherein the challenge lies in formulating the number of actuators associated with modelling a gearbox. Data with respect to actuation and gear shifting sequence has been retrieved from the available literature, including patent documents, and has been used in this proposed heuristics based methodology for modelling actuation sequence in a gear box. This paper presents a methodological approach in designing a gearbox for the purpose of obtaining an optimal shifting sequence. The computational model considers factors namely, the number of stages and gear teeth as input parameters since these two are the determinants of the gear ratios in an epicyclic gear train. The proposed transmission schematic or stick diagram aids in developing the gearbox layout design. The number of iterations and development time required to design a gearbox layout is reduced by using this approach.

Keywords: automatic transmission, gear-shifting, multi-stage planetary gearbox, rank ordered clustering

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Authors: Aline M. C. Santoro, João C. Pantoja, Eduardo P. Rossetti

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While the aim of the modernist movement was to deny known typology, the creation of a new formal language also gave it new meaning, which was now related to Form. This is specifically true in the modern capital of Brazil, where Niemeyer sought to demonstrate the manner in which the new materials available, such as reinforced concrete, were able to produce innovative forms. With this study, we aim to demonstrate the relationship between Niemeyer’s forms and the topological typology known as tessellation, through the presentation of two case studies, the Monument to Caxias and the Saint George Orthodox Church. At a first glance, our purpose is to present the definition of Form, especially with relationship to the works of Niemeyer, seeking to identify in them the concepts presented by Moussavi. Afterwards, we will use a computer-based approach to study and model the forms of two of his buildings with the McNeel Rhinoceros program, where, with the aid of diagrams and renderings, we will be able to clearly and legibly represent their organic forms and further understand their structural systems. When we recognise the concept of typology as a starting point for structural form, it can be concluded that the case studies presented here are encompassed by the typology presented by Moussavi since they derive from his basic structural systems.

Keywords: form, Niemeyer, structure, typology, topology

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Authors: Kehinde Damilola Ilesanmi, Dev Datt Tewari

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South Africa is in its post-industrial era moving from the primary and secondary sector to the tertiary sector. The study investigated the impact of the disaggregated energy consumption (coal, oil, and electricity) on the primary, secondary and tertiary sectors of the economy between 1980 and 2012 in South Africa. Using vector error correction model, it was established that South Africa is an energy dependent economy, and that energy (especially electricity and oil) is a limiting factor of growth. This implies that implementation of energy conservation policies may hamper economic growth. Output growth is significantly outpacing energy supply, which has necessitated load shedding. To meet up the excess energy demand, there is a need to increase the generating capacity which will necessitate increased investment in the electricity sector as well as strategic steps to increase oil production. There is also need to explore more renewable energy sources, in order to meet the growing energy demand without compromising growth and environmental sustainability. Policy makers should also pursue energy efficiency policies especially at sectoral level of the economy.

Keywords: causality, economic growth, energy consumption, hypothesis, sectoral output

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Authors: Shidvash Vakilipour, Mehdi Habibnia, Rouzbeh Riazi, Masoud Mohammadi, Mohammad H. Sabour

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The flow field passing through a highly loaded low pressure (LP) turbine cascade is numerically investigated at design and off-design conditions. The Field Operation And Manipulation (OpenFOAM) platform is used as the computational Fluid Dynamics (CFD) tool. Firstly, the influences of grid resolution on the results of k-ε, k-ω, and LES turbulence models are investigated and compared with those of experimental measurements. A numerical pressure under-shoot is appeared near the end of blade pressure surface which is sensitive to grid resolution and flow turbulence modeling. The LES model is able to resolve separation on a coarse and fine grid resolutions. Secondly, the off-design flow condition is modeled by negative and positive inflow incidence angles. The numerical experiments show that a separation bubble generated on blade pressure side is predicted by LES. The total pressure drop is also been calculated at incidence angle between -20◦ and +8◦. The minimum total pressure drop is obtained by k-ω and LES at the design point.

Keywords: low pressure turbine, off-design performance, openFOAM, turbulence modeling, flow separation

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Authors: M. Sumida, T. Fujimoto

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Fiber-concentration distributions in pulp liquid flows behind dispersion promoters were experimentally investigated to explore the feasibility of improving operational performance of hydraulic headboxes in papermaking machines. The proposed research was performed in the form of a basic test conducted on a screen-type model comprising a circular cylinder inserted within a channel. Tests were performed using pulp liquid possessing fiber concentrations ranging from 0.3-1.0 wt% under different flow velocities of 0.016-0.74 m/s. Fiber-concentration distributions were measured using the transmitted light attenuation method. Obtained test results were analyzed, and the influence of the flow velocities on wake characteristics behind the cylinder has been investigated with reference to findings of our preceding studies concerning pulp liquid flows in straight channels. Changes in fiber-concentration distribution along the flow direction were observed to be substantially large in the section from the cylinder to four times its diameter downstream of its centerline. Findings of this study provide useful information concerning the development of hydraulic headboxes.

Keywords: dispersion promoter, fiber-concentration distribution, hydraulic headbox, pulp liquid flow

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Authors: Yuan Li, Yitao Han, Zhao Zhu

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In this paper, the effect of blasting loads on steel-concrete composite bridges has been investigated considering the slope reflection effect. Reasonable values of girder size, plate thickness, stiffening rib, and other design parameters were selected according to design specifications. Modified RHT (Riedel-Hiermaier-Thoma) was used as constitutive relation in analyses. In order to simulate the slope reflection effect, the slope of the bridge was precisely built in the model. Different blasting conditions, including top, middle, and bottom explosions, were simulated. The multi-Euler domain method based on fully coupled Lagrange and Euler models was adopted for the structural analysis of the explosion process using commercial software AUTODYN. The obtained results showed that explosion overpressure was increased by 3006, 879, and 449kPa, corresponding to explosions occurring at the top, middle, and bottom of the slope, respectively. At the same time, due to energy accumulation and transmission dissipation caused by slope reflection, the corresponding yield lengths of steel beams were increased by 8, 0, and 5m, respectively.

Keywords: steel-concrete composite bridge, explosion damage, slope reflection, blasting loads, RHT

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Authors: John Sweeney, Martin Leeming, Raj Thaker, Cristina L. Tuinea-Bobe

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Shrink wrapping is widely used as a method for secondary packaging to assemble individual items, such as cans or other consumer products, into single packages. This method involves conveying the packages into heated tunnels and so has the disadvantages that it is energy-intensive, and, in the case of aerosol products, potentially hazardous. We are developing an automated packaging system that uses stretch wrapping to address both these problems, by using a mechanical rather than a thermal process. In this study, we present a comparative study of shrink wrapping and stretch wrapping materials to assess the relative capability of candidate stretch wrap polymer film in terms of mechanical response. The stretch wrap materials are of oriented polymer and therefore elastically anisotropic. We are developing material constitutive models that include both anisotropy and nonlinearity. These material models are to be incorporated into computer simulations of the automated stretch wrapping system. We present results showing the validity of these models and the feasibility of applying them in the simulations.

Keywords: constitutive model, polymer, mechanical testing, wrapping system

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Authors: Marco Tulio C. Faria

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Fixed-geometry hydrodynamic journal bearings are one of the best supporting systems for several applications of rotating machinery. Cylindrical journal bearings present excellent load-carrying capacity and low manufacturing costs, but they are subjected to the oil-film instability at high speeds. An attempt of overcoming this instability problem has been the development of non-circular journal bearings. This work deals with an analysis of oil-lubricated elliptical journal bearings using the finite element method. Steady-state and dynamic performance characteristics of elliptical bearings are rendered by zeroth- and first-order lubrication equations obtained through a linearized perturbation method applied on the classical Reynolds equation. Four-node isoparametric rectangular finite elements are employed to model the bearing thin film flow. Curves of elliptical bearing load capacity and dynamic force coefficients are rendered at several operating conditions. The results presented in this work demonstrate the influence of the bearing ellipticity on its performance at different loading conditions.

Keywords: elliptical journal bearings, non-circular journal bearings, hydrodynamic bearings, finite element method

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Authors: A. Radwan, A. Elbatran, A. Mehanna, M. Shehadeh

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The corrosion is natural chemical phenomenon that is applied in many engineering structures. Hence, it is one of the important topics to study in the engineering research. Ship and offshore structures are most exposed to corrosion due to the presence of corrosive medium of air and the seawater. Consequently, investigation of the corrosion behavior and properties over ship and offshore hulls is one of the important topics to study in the marine engineering research. Using sacrificial anode is the most popular solution for protecting marine structures from corrosion. Hence, this research investigates the extent of corrosion between the composite ship model and relative velocity of water, along with the sacrificial aluminum anode consumption and its degree of protection in seawater. In this study, the consumption rate of sacrificial aluminum anode with respect to relative velocity at different Reynold’s numbers was studied experimentally, and it was found that, the degree of cathodic protection represented by the cathode potential at a given distance from the aluminum anode was decreased slightly with increment of the relative velocity.

Keywords: corrosion, Reynold's numbers, sacrificial anode, velocity

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Authors: Swati Tyagi, Syed Abbas

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Fractional-order Hopfield neural networks are generally used to model the information processing among the interacting neurons. To show the constancy of the processed information, it is required to analyze the stability of these systems. In this work, we perform Mittag-Leffler stability for the corresponding Caputo fractional-order bidirectional associative memory (BAM) neural networks with various time-delays. We derive sufficient conditions to ensure the existence and uniqueness of the equilibrium point by using the theory of topological degree theory. By applying the fractional Lyapunov method and Mittag-Leffler functions, we derive sufficient conditions for the global Mittag-Leffler stability, which further imply the global asymptotic stability of the network equilibrium. Finally, we present two suitable examples to show the effectiveness of the obtained results.

Keywords: bidirectional associative memory neural network, existence and uniqueness, fractional-order, Lyapunov function, Mittag-Leffler stability

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Authors: Faezeh Shalchy

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Concrete is the most used materials in the world. It is also one of the most versatile while complex materials which human have used for construction. However, concrete is weak in tension, over the past thirty years many studies were accomplished to improve the tensile properties of concrete (cement-based materials) using a variety of methods. One of the most successful attempts is to use polymeric fibers in the structure of concrete to obtain a composite with high tensile strength and ductility. Understanding the mechanical behavior of fiber reinforced concrete requires the knowledge of the fiber/matrix interfaces at the small scale. In this study, a combination of numerical simulations and experimental techniques have been used to study the nano structure of fiber/matrix interfaces. A new model for calcium-silicate-hydrate (C-S-H)/fiber interfaces is proposed based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) analysis. The adhesion energy between the C-S-H gel and 2 different polymeric fibers (polyvinyl alcohol and polypropylene) was numerically studied at the atomistic level since adhesion is one of the key factors in the design of fiber reinforced composites. The mechanisms of adhesion as a function of the nano structure of fiber/matrix interfaces are also studied and discussed.

Keywords: fiber-reinforced concrete, adhesion, molecular modeling

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Authors: Hyo Lim Kang, Tae An Kim, Seung Ho Han

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A 3-way reversing valve has been used in automotive washing machines to remove remaining oil and dirt on machined engine and transmission blocks. It provides rapid and accurate changes of water flow direction without any precise control device. However, due to its complicated bottom-plug shape, a cavitation occurs in a wide range of the bottom-plug in a downstream. In this study, the cavitation index and POC (percent of cavitation) were used to evaluate quantitatively the cavitation phenomena occurring at the bottom-plug. An optimal shape design was carried out via parametric study for geometries of the bottom-plug, in which a simple CAE-model was used in order to avoid time-consuming CFD analysis and hard to achieve convergence. To verify the results of numerical analysis, a flow visualization test was carried out using a test specimen with a transparent acryl pipe according to ISA-RP75.23. The flow characteristics such as the cavitation occurring in the downstream were investigated by using a flow test equipment with valve and pump including a flow control system and high-speed camera.

Keywords: cavitation, flow visualization test, optimal shape design, percent of cavitation, reversing valve

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Mohieddine Benghersallah, Lakhdar Boulanouar, Salim Belhadi

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Currently, higher production rate with required quality and low cost is the basic principle in the competitive manufacturing industry. This is mainly achieved by using high cutting speed and feed rates. Elevated temperatures in the cutting zone under these conditions shorten tool life and adversely affect the dimensional accuracy and surface integrity of component. Thus it is necessary to find optimum cutting conditions (cutting speed, feed rate, machining environment, tool material and geometry) that can produce components in accordance with the project and having a relatively high production rate. Response surface methodology is a collection of mathematical and statistical techniques that are useful for modelling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) on to the surface roughness through the mathematical model developed by using the data gathered from a series of milling experiments performed.

Keywords: Statistical analysis (RSM), Bearing steel, Coating inserts, Tool life, Surface Roughness, End milling.

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Authors: Jarmon Sirigunna

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The objective of this study were to investigate the success of the implementation of problem-based learning in classroom and to evaluate the level of satisfaction of Suan Sunandra Rajabhat University’s students who participated in the study. This paper aimed to study and focus on a university students survey conducted in Suan Sunandha Rajabhat University during January to March of 2014. The quota sampling was utilized to obtain the sample which included 60 students, 50 percent male and 50 percent female students. The pretest and posttest method was utilized. The findings revealed that the majority of respondents had gained higher knowledge after the posttest significantly. The respondents’ knowledge increased about 40 percent after the experiment. Also, the findings revealed the top three highest level of satisfaction as follows: 1) the proper roles of teacher and students, 2) the knowledge gained from the method of the problem-based learning, 3) the activities of the problem-based learning, 4) the interaction of students from the problem-based learning, and 5) the problem-based learning model. Also, the mean score of all categories was 4.22 with a standard deviation of 0.7435 which indicated that the level of satisfaction was high.

Keywords: implement, problem-based learning, satisfaction, university students

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Authors: Hami Ashraf, Farid Kosari

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Graft-versus-host disease (GvHD) is a common complication of allogeneic hematopoietic stem cell transplantation that can lead to significant morbidity and mortality. Histopathological examination of affected tissues is an essential tool for diagnosing and grading GvHD in animal models, which are used to study disease mechanisms and evaluate new therapies. In this systematic review, we identified and analyzed original research articles in PubMed, Scopus, Web of Science, and Google Scholar that described grading systems for GvHD in animal models based on histopathological features. We found that several grading systems have been developed, which vary in the tissues and criteria they assess, the severity scoring scales they use, and the level of detail they provide. Skin, liver, and gut are the most commonly evaluated tissues, but lung and thymus are also included in some systems. Our analysis highlights the need for standardized criteria and consistent use of grading systems to enable comparisons between studies and facilitate the translation of preclinical findings to clinical practice.

Keywords: graft-versus-host disease, GvHD, animal model, histopathology, grading system

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Authors: Yohanes Kristianto

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The objective of this paper is to compose a sustainable supply chain that integrates product, process and networks design. An integrated life cycle assessment and techno-economic optimization is proposed that might deliver more economically feasible operations, minimizes environmental impacts and maximizes social contributions. Closed loop economy of the supply chain is achieved by reusing waste to be raw material of final products. Societal benefit is given by the supply chain by absorbing waste as source of raw material and opening new work opportunities. A case study of ethanol supply chain from rice straws is considered. The modeling results show that optimization within the scope of LCA is capable of minimizing both CO₂ emissions and energy and utility consumptions and thus enhancing raw materials utilization. Furthermore, the supply chain is capable of contributing to local economy through jobs creation. While the model is quite comprehensive, the future research recommendation on energy integration and global sustainability is proposed.

Keywords: life cycle assessment, techno-economic optimization, sustainable supply chains, closed loop economy

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Authors: Karim Kootahi, Seyed Abolhasan Naeini

Abstract:

The soil-water characteristic curve (SWCC), which represents the relationship between suction and water content (or degree of saturation), is an important property of unsaturated soils. The conventional method for determining SWCC is through specialized testing procedures. Since these procedures require specialized unsaturated soil testing apparatus and lengthy testing programs, several index properties-based correlations have been developed for estimating the SWCC of fine-grained soils. There are, however, considerable inconsistencies among the published correlations and there is no validation study on the predictive ability of existing correlations. In the present study, all existing index properties-based correlations are evaluated using a high quality worldwide database. The performances of existing correlations are assessed both graphically and quantitatively using statistical measures. The results of the validation indicate that most of the existing correlations provide unacceptable estimates of degree of saturation but the most recent model appears to be promising.

Keywords: SWCC, correlations, index properties, validation

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Authors: Eunice Oluwakemi Chukwuma-Nwuba

Abstract:

Nigeria is a developing country with an increasing rate of graduate unemployment. This has triggered successive government administrations to promote the variety of programmes to address the situation. However, none of these efforts yielded the desired outcome. Accordingly, in 2006 the government included entrepreneurship module in the curriculum of universities as a compulsory general programme for all undergraduate courses. This is in the hope that the programme will help to promote entrepreneurial mind-set and new venture creation among graduates and as a result reduce the rate of graduate unemployment. The study explores the effectiveness of entrepreneurship education in promoting entrepreneurship. This study is significant in view of the endemic graduate unemployment in Nigeria and the social consequences such as youth restiveness and militancy. It is guided by the theory of planned behaviour. It employed the two-stage structural equation modelling (AMOS) to model entrepreneurial intentions as a function of innovative teaching methods, traditional teaching methods and culture Personal attitude and subjective norm are proposed to mediate the relationships between the exogenous and the endogenous variables. The first stage was tested using multi-group confirmatory factor analysis (MGCFA) framework to confirm that the two groups assign the same meaning to the scale items and to obtain goodness-of-fit indices. The multi-group confirmatory factor analysis included the tests of configural, metric and scalar invariance. With the attainment of full configural invariance and partial metric and scalar invariance, the second stage – the structural model was applied hypothesising that, the entrepreneurial intentions of graduates (respondents who have participated in the compulsory entrepreneurship programme) will be higher than those of undergraduates (respondents who are yet to participate in the programme). The study uses the quasi-experimental design. The samples comprised 409 graduates (experimental group) and 402 undergraduates (control group) from six federal universities in Nigeria. Our findings suggest that personal attitude is positively related with entrepreneurial intentions, largely confirming prior literature. However, unlike previous studies, our results indicate that subjective norm has significant direct and indirect impact on entrepreneurial intentions indicating that reference people of the participants have important roles to play in their decision to be entrepreneurial. Furthermore, unlike the assertions in prior studies, the result suggests that traditional teaching methods have indirect effect on entrepreneurial intentions supporting that since personal characteristics can change in an educational situation, an education purposively directed at entrepreneurship might achieve similar results if not better. This study has implication for practice and theory. The research extends to the theoretical understanding of the formation of entrepreneurial intentions and explains the role of the reference others in relation to how graduates perceive entrepreneurship. Further, the study adds to the body of knowledge on entrepreneurship education in Nigeria universities and provides a developing country perspective. It proposes further research in the exploration of entrepreneurship education and entrepreneurial intentions of graduates from across the country’s universities as necessary and imperative.

Keywords: entrepreneurship education, entrepreneurial intention, structural equation modeling, theory of planned behaviour

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