Search results for: technology supported model

Authors: P. W. Chen, C. T. Chang, Y. Peng, J. Y. Wu, D. J. Jan, Md. Manirul Ali

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In the last decade, the nature of cathode spot splitting and the current per spot depended on an oblique magnetic field was investigated. This model for cathode current splitting is developed that we have investigated with relationship the magnetic pressures produced by kinetic pressure, self-magnetic pressure, and changed with an external magnetic field. We propose a theoretical model that has been established to an external magnetic field with components normal and tangential to the cathode surface influenced on magnetic pressure strength. We mainly focus on developed to understand the current per spot influenced with the tangential magnetic field strength and normal magnetic field strength.

Keywords: cathode spot, vacuum arc discharge, oblique magnetic field, tangential magnetic field

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Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

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Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

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Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Muhammad A. Alsubaie

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An iterative learning control framework designed in state feedback structure suffers a lack in investigating load disturbance considerations. The presented work discusses the controller previously designed, highlights the disturbance problem, finds new conditions using singular value principle to assure safe operation conditions with error convergence and reference tracking under the influence of load disturbance. It is known that periodic disturbances can be represented by a delay model in a positive feedback loop acting on the system input. This model can be manipulated by isolating the delay model and finding a controller for the overall system around the delay model to remedy the periodic disturbances using the small signal theorem. The overall system is the base for control design and load disturbance investigation. The major finding of this work is the load disturbance condition found which clearly sets safe operation condition under the influence of load disturbances such that the error tends to nearly zero as the system keeps operating trial after trial.

Keywords: iterative learning control, singular values, state feedback, load disturbance

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: constructive alignment, constructivist theory, educational game, outcome-based education

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Authors: Jan Schmidt, Pierre Köhring

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Permanently excited machines are set up with magnets that are made of highly energetic magnetic materials. Inherently, the permanent magnets warm up while the machine is operating. With an increasing temperature, the electromotive force and hence the degree of efficiency decrease. The reasons for this are slot harmonics and distorted armature currents arising from frequency inverter operation. To prevent or avoid demagnetizing of the permanent magnets it is necessary to ensure that the magnets do not excessively heat up. Demagnetizations of permanent magnets are irreversible and a breakdown of the electrical machine is inevitable. For the design of an electrical machine, the knowledge of the behavior of heating under operating conditions of the permanent magnet is of crucial importance. Therefore, a calculation model is presented with which the machine designer can easily calculate the eddy current losses in the magnetic material.

Keywords: analytical model, eddy current, losses, lattice network, permanent magnet

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Authors: Sagar Ghos, Andrew E. Elaryan, Syed Ashik Ali, Musharraf Zaman, Mohammed Ashiqur Rahman

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Achieving desired density during construction is an important indicator of pavement quality. Insufficient compaction often compromises pavement performance and service life. Intelligent compaction (IC) is an emerging technology for monitoring compaction quality during the construction of asphalt pavements. This paper aims to provide an overview of findings from four case studies in Oklahoma involving the compaction quality of asphalt pavements, namely SE 44th St project (Project 1) and EOC Turnpike project (Project 2), Highway 92 project (Project 3), and 108th Avenue project (Project 4). For this purpose, an IC technology, the intelligent compaction analyzer (ICA), developed at the University of Oklahoma, was used to evaluate compaction quality. Collected data include GPS locations, roller vibrations, roller speed, the direction of movement, and temperature of the asphalt mat. The collected data were analyzed using a widely used software, VETA. The average densities for Projects 1, 2, 3 and 4, were found as 89.8%, 91.50%, 90.7% and 87.5%, respectively. The maximum densities were found as 94.6%, 95.8%, 95.9%, and 89.7% for Projects 1, 2, 3, and 4, respectively. It was observed that the ICA estimated densities correlated well with the field core densities. The ICA results indicated that at least 90% of the asphalt mats were subjected to at least two roller passes. However, the number of passes required to achieve the desired density (94% to 97%) differed from project to project depending on the underlying layer. The results of these case studies show both opportunities and challenges in using IC for monitoring compaction quality during construction in real-time.

Keywords: asphalt pavement construction, density, intelligent compaction, intelligent compaction analyzer, intelligent compaction measure value

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: Moise Alin Ionuț Cornel

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In a pilot lesson of prevention of consumption drugs in a classroom of teenager`s where the school want them to know how to manage their thoughts and emotions to protect themself an to be strong in an possible environment of drugs consumption. At this classroom was applied the RAIN(Recognize, Accept, Investigation,Non-identify) spiritual method and the balance model from positive and transcultural psychotherapy (PPT) in a manner of a game play for them to understand the methods in an individual experience. The balance model from PPT with his 4 parts and used in 3 ways, and the RAIN spiritual method was used to see how the teenager`s can bring clarity about theirs individual self and how they spend the time and energy in the daily life. The 3 ways of how they can used this model was explained like a analogy with the 3 periods of the SAKURA (Japanese cherry) flourish (kaika, mankai and chiru). The teenager`s received a new perspective and in the same time new tools from the spiritual point of view combined with the psychotherapeutic point of view to manage their thoughts, emotions, time and energy in the form of a psychoeducational game to be able to prevent the use of drugs.

Keywords: addiction, drugs consumption prevention education, psychotherapy, Self, Spirituality, teenagers

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Authors: Paul V. Thomas, Mostafa S. A. Elsayed, Denis Walch

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Airframe structural optimization at different design stages results in new mass and stiffness distributions which modify the critical design loads envelop. Determination of aircraft critical loads is an extensive analysis procedure which involves simulating the aircraft at thousands of load cases as defined in the certification requirements. It is computationally prohibitive to use a Global Finite Element Model (GFEM) for the load analysis, hence reduced order structural models are required which closely represent the dynamic characteristics of the GFEM. This paper presents the implementation of Component Mode Synthesis (CMS) method for the generation of high fidelity Reduced Order Model (ROM) of complex airframes. Here, sub-structuring technique is used to divide the complex higher order airframe dynamical system into a set of subsystems. Each subsystem is reduced to fewer degrees of freedom using matrix projection onto a carefully chosen reduced order basis subspace. The reduced structural matrices are assembled for all the subsystems through interface coupling and the dynamic response of the total system is solved. The CMS method is employed to develop the ROM of a Bombardier Aerospace business jet which is coupled with an aerodynamic model for dynamic aeroelasticity loads analysis under gust turbulence. Another set of dynamic aeroelastic loads is also generated employing a stick model of the same aircraft. Stick model is the reduced order modelling methodology commonly used in the aerospace industry based on stiffness generation by unitary loading application. The extracted aeroelastic loads from both models are compared against those generated employing the GFEM. Critical loads Modal participation factors and modal characteristics of the different ROMs are investigated and compared against those of the GFEM. Results obtained show that the ROM generated using Craig Bampton CMS reduction process has a superior dynamic characteristics compared to the stick model.

Keywords: component mode synthesis, craig bampton reduction method, dynamic aeroelasticity analysis, model order reduction

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Authors: Subham Kharel, Sudha Ravindranath, A. Vidya, B. Chandrasekaran, K. Ganesha Raj, T. Shesadri

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Digitization of urban features is a tedious and time-consuming process when done manually. In addition to this problem, Indian cities have complex habitat patterns and convoluted clustering patterns, which make it even more difficult to map features. This paper makes an attempt to classify urban objects in the satellite image using object-oriented classification techniques in which various classes such as vegetation, water bodies, buildings, and shadows adjacent to the buildings were mapped semi-automatically. Building layer obtained as a result of object-oriented classification along with already available building layers was used. The main focus, however, lay in the extraction of high-rise buildings using spatial technology, digital image processing, and modeling, which would otherwise be a very difficult task to carry out manually. Results indicated a considerable rise in the total number of buildings in the city. High-rise buildings were successfully mapped using satellite imagery, spatial technology along with logical reasoning and mathematical considerations. The results clearly depict the ability of Remote Sensing and GIS to solve complex problems in urban scenarios like studying urban sprawl and identification of more complex features in an urban area like high-rise buildings and multi-dwelling units. Object-Oriented Technique has been proven to be effective and has yielded an overall efficiency of 80 percent in the classification of high-rise buildings.

Keywords: object oriented classification, shadow extraction, high-rise buildings, satellite imagery, spatial technology

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Authors: E. Verduci, I. Aguglia, A. Filocamo, I. Macrì, R. Scala, A. Vinci

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One of the first indicator of autism spectrum disorder (ASD) is a decreasing tendency or failure to respond to name (RTN) call. Despite RTN is important for social and language developmentand it’s a common target for early interventions for children with ASD, research on specific treatments is insufficient and does not consider the importance of the discrimination between the own name and other names. The purpose of the current study was to replicate an assessment and treatment model proposed by Conine et al. (2020) to teach children with ASD to respond to their own name and to not respond to other names (RTO). The model includes three different phases (baseline/screening, treatment, and generalization), and itgradually introduces the different treatment components, starting with the most naturalistic ones (such as social interaction) and adding more intrusive components (such as tangible reinforcements, prompt and fading procedures) if necessary. The participants of this study were three children with ASD diagnosis: D. (5 years old) with a low frequency of RTN, M. (7 years old) with a RTN unstable and no ability of discrimination between his name and other names, S. (3 years old) with a strong RTN but a constant response to other names. Moreover, the treatment for D. and M. consisted of social and tangible reinforcements (treatment T1), for S. the purpose of the treatment was to teach the discrimination between his name and the others. For all participants, results suggest the efficacy of the model to acquire the ability to selectively respond to the own name and the generalization of the behavior with other people and settings.

Keywords: response to name, autism spectrum disorder, progressive training, ABA

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Authors: Zahid Ahmad, Nauman Ali

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This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

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Authors: Alvarez M., Chapela M. J., Balboa E., Rubianes D., Sinde E., Fernandez de Ana C., Rodríguez-Blanco A.

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The gut microbiota plays an important role as gut inflammation could contribute to colorectal cancer development; however, this role is still not fully understood, and tools able to prevent this progression are yet to be developed. The main objective of this study was to monitor the effects of a mushroom extracts formulation in gut microbial community composition of an Azoxymethane (AOM)/Dextran sodium sulfate (DSS) mice model of inflammation-linked carcinogenesis. For the in vivo study, 41 adult male mice of the C57BL / 6 strain were obtained. 36 of them have been induced in a state of colon carcinogenesis by a single intraperitoneal administration of AOM at a dose of 12.5 mg/kg; the control group animals received instead of the same volume of 0.9% saline. DSS is an extremely toxic polysaccharide sulfate that causes chronic inflammation of the colon mucosa, favoring the appearance of severe colitis and the production of tumors induced by AOM. Induction by AOM/DSS is an interesting platform for chemopreventive intervention studies. This time the model was used to monitor gut microbiota changes as a result of supplementation with a specific mushroom extracts formulation previously shown to have prebiotic activity. The animals have been divided into three groups: (i) Cancer + mushroom extracts formulation experimental group: to which the MicoDigest2.0 mushroom extracts formulation developed by Hifas da Terra S.L has been administered dissolved in drinking water at an estimated concentration of 100 mg / ml. (ii) Control group of animals with Cancer: to which normal water has been administered without any type of treatment. (iii) Control group of healthy animals: these are the animals that have not been induced cancer or have not received any treatment in drinking water. This treatment has been maintained for a period of 3 months, after which the animals were sacrificed to obtain tissues that were subsequently analyzed to verify the effects of the mushroom extract formulation. A microbiological analysis has been carried out to compare the microbial communities present in the intestines of the mice belonging to each of the study groups. For this, the methodology of massive sequencing by molecular analysis of the 16S gene has been used (Ion Torrent technology). Initially, DNA extraction and metagenomics libraries were prepared using the 16S Metagenomics kit, always following the manufacturer's instructions. This kit amplifies 7 of the 9 hypervariable regions of the 16S gene that will then be sequenced. Finally, the data obtained will be compared with a database that makes it possible to determine the degree of similarity of the sequences obtained with a wide range of bacterial genomes. Results obtained showed that, similarly to certain natural compounds preventing colorectal tumorigenesis, a mushroom formulation enriched the Firmicutes and Proteobacteria phyla and depleted Bacteroidetes. Therefore, it was demonstrated that the consumption of the mushroom extracts’ formulation developed could promote the recovery of the microbial balance that is disrupted in the mice model of carcinogenesis. More preclinical and clinical studies are needed to validate this promising approach.

Keywords: carcinogenesis, microbiota, mushroom extracts, inflammation

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Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

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Authors: Ayman M. Othman, Hassan Y. Ahmed, Tallat A. Ali

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Inadequate maintenance programs and funds allocated for highway networks in the developed countries have led to fast deterioration of road side elements. Therefore, this research focuses on developing a performance model for road side elements periodic maintenance activities. Road side elements that receive periodic maintenance include; earthen shoulder, road signs and traffic markings. Using the level of service concept, the developed model can determine the optimal periodic maintenance intervals for those elements based on a selected level of service suitable with the available periodic maintenance budget. Data related to time periods for progressive deterioration stages for the chosen elements were collected. Ten maintenance experts in Aswan, Sohag and Assiut cities were interviewed for that purpose. Time in months related to 10%, 25%, 40%, 50%, 75%, 90% and 100% deterioration of each road side element was estimated based on the experts opinion. Least square regression analysis has shown that a power function represents the best fit for earthen shoulders edge drop-off and damage of road signs with time. It was also evident that, the progressive dirtiness of road signs could be represented by a quadratic function an a linear function could represent the paint degradation nature of both traffic markings and road signs. Actual measurements of earthen shoulder edge drop-off agree considerably with the developed model.

Keywords: deterioration, level of service, periodic maintenance, performance model, road side element

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

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Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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Authors: Kateryna Zharan, Jan C. Bongaerts

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In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.

Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy

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Authors: Eunice H. Li

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This e-poster explores some of the issues that are linked to Open Educational Resources (OER). It describes how OER is explained by experts in the field and relates its value in attaining and using knowledge. ‘Open', 'open pedagogy', self-direction, freedom, and autonomy are the main issues identified for the discussion. All of these issues make essential contributions to OER in one way or another. Nevertheless, there are seemingly areas of contentions with regard to applying these concepts in teaching and learning practices. For this e-Poster, it is the teaching-learning aspects of OER that it is primarily concerned with. The basis for the discussion comes from a 2013 critique of OER presented by Jeremy Knox of the University of Edinburgh, tutor of the MSc in Digital Education Programme. This discussion is also supported by the analysis of other research work and papers in this area. The general view on OER is that it is a useful tool for the advancement of learner-centred models of education, but in whatever context, pedagogy cannot be diminished and overlooked. It should take into consideration how to deal with the issues identified above in order to allow learners to gain full benefit from OER.

Keywords: open, pedagogy, e-learning technologies, autonomy, knowledge

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Authors: Yangsu Kwon, Hyo-Gyoung Kwak

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Nonlinear tendon constitutive model for nonlinear analysis of pre-stressed concrete structures are presented. Since the post-cracking behavior of concrete structures, in which bonded reinforcements such as tendons and/or reinforcing steels are embedded, depends on many influencing factors(the tensile strength of concrete, anchorage length of reinforcements, concrete cover, and steel spacing) that are deeply related to the bond characteristics between concrete and reinforcements, consideration of the tension stiffening effect on the basis of the bond-slip mechanism is necessary to evaluate ultimate resisting capacity of structures. In this paper, an improved tendon model, which considering the slip effect between concrete and tendon, and effect of tension stiffening, is suggested. The validity of the proposed models is established by comparing between the analytical results and experimental results in pre-stressed concrete beams.

Keywords: bond-slip, prestressed concrete, tendon, ultimate strength

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Authors: Jamilatuzzahro, Rezzy Eko Caraka

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The yield curve is the plot of the yield to maturity of zero-coupon bonds against maturity. In practice, the yield curve is not observed but must be extracted from observed bond prices for a set of (usually) incomplete maturities. There exist many methodologies and theory to analyze of yield curve. We use two methods (the Nelson-Siegel Method, the Svensson Method, and the SVR method) in order to construct and compare our zero-coupon yield curves. The objectives of this research were: (i) to study the adequacy of NSS model and SVR to Indonesian government bonds data, (ii) to choose the best optimization or estimation method for NSS model and SVR. To obtain that objective, this research was done by the following steps: data preparation, cleaning or filtering data, modeling, and model evaluation.

Keywords: support vector regression, Nelson-Siegel-Svensson, yield curve, Indonesian government

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Authors: Nitin Joseph

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Objectives: This study was done to assess emotional intelligence levels and to find out its association with socio demographic variables and perceived stress among medical students. Material and Methods: This study was done among first and second year medical students. Data was collected using a self-administered questionnaire. Results: Emotional intelligence scores was found to significantly increase with age of the participants (F=2.377, P < 0.05). Perceived stress was found to be significantly more among first year (t=1.997, P=0.05). Perceived stress was found to significantly decrease with increasing emotional intelligence scores (r = – 0.226, P < 0.001). Conclusion: First year students were found to be more vulnerable to stress than their seniors probably due to lesser emotional intelligence. As both these parameters are related, ample measures to improve emotional intelligence needs to be supported in the training curriculum of beginners so as to make them more stress free during early student life.

Keywords: emotional intelligence, medical students, perceived stress, socio demographic variables

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Authors: Tarek Aboueldahab, Hanan Farag

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Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

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Authors: Miriam I. Lautenschläger, Max H. Scheiwe, Kay A. Weidenmann, Frank Henning, Peter Elsner

Abstract:

Due to increasing environmental awareness jute fibers are more often used in fiber reinforced composites. In the Sheet Molding Compound (SMC) process, the mold cavity is filled via material flow allowing more complex component design. But, the difficulty of using jute fibers in this process is the decreased capacity of fiber movement in the mold. A comparative flow study with jute nonwoven reinforced SMC was conducted examining the influence of the fiber volume content, the grammage of the jute nonwoven textile and a mechanical modification of the nonwoven textile on the flowability. The nonwoven textile reinforcement was selected to support homogeneous fiber distribution. Trials were performed using two SMC paste formulations differing only in filler type. Platy-shaped kaolin with a mean particle size of 0.8 μm and ashlar calcium carbonate with a mean particle size of 2.7 μm were selected as fillers. Ensuring comparability of the two SMC paste formulations the filler content was determined to reach equal initial viscosity for both systems. The calcium carbonate filled paste was set as reference. The flow study was conducted using a jute nonwoven textile with 300 g/m² as reference. The manufactured SMC sheets were stacked and centrally placed in a square mold. The mold coverage was varied between 25 and 90% keeping the weight of the stack for comparison constant. Comparing the influence of the two fillers kaolin yielded better results regarding a homogeneous fiber distribution. A mold coverage of about 68% was already sufficient to homogeneously fill the mold cavity whereas for calcium carbonate filled system about 79% mold coverage was necessary. The flow study revealed a strong influence of the fiber volume content on the flowability. A fiber volume content of 12 vol.-% and 25 vol.-% were compared for both SMC formulations. The lower fiber volume content strongly supported fiber transport whereas 25 vol.-% showed insignificant influence. The results indicate a limiting fiber volume content for the flowability. The influence of the nonwoven textile grammage was determined using nonwoven jute material with 500 g/m² and a fiber volume content of 20 vol.-%. The 500 g/m² reinforcement material showed inferior results with regard to fiber movement. A mold coverage of about 90 % was required to prevent the destruction of the nonwoven structure. Below this mold coverage the 500 g/m² nonwoven material was ripped and torn apart. Low mold coverages led to damage of the textile reinforcement. Due to the ripped nonwoven structure the textile was modified with cuts in order to facilitate fiber movement in the mold. Parallel cuts of about 20 mm length and 20 mm distance to each other were applied to the textile and stacked with varying orientations prior to molding. Stacks with unidirectional orientated cuts over stacks with cuts in various directions e.g. (0°, 45°, 90°, -45°) were investigated. The mechanical modification supported tearing of the textile without achieving benefit for the flowability.

Keywords: filler, flowability, jute fiber, nonwoven, sheet molding compound

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

Abstract:

Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

Procedia PDF Downloads 513

Authors: Antoinette Maarawi, Zoe Anxionnaz-Minvielle, Pierre Coste, Nathalie Di Miceli Raimondi, Michel Cabassud

Abstract:

Milli-structured heat exchanger/reactors have been recently widely used, especially in the chemical industry, due to their enhanced performances in heat and mass transfer compared to conventional apparatuses. In our work, the ‘DeanHex’ heat exchanger/reactor with a 2D-meandering channel is investigated both experimentally and numerically. The square cross-sectioned channel has a hydraulic diameter of 2mm. The aim of our study is to model local physico-chemical phenomena (heat and mass transfer, axial dispersion, etc.) for a liquid-liquid two-phase flow in our lab-scale meandering channel, which represents the central part of the heat exchanger/reactor design. The numerical approach of the reactor is based on a 1D model for the flow channel encapsulated in a 3D model for the surrounding solid, using COMSOL Multiphysics V5.5. The use of the 1D approach to model the milli-channel reduces significantly the calculation time compared to 3D approaches, which are generally focused on local effects. Our 1D/3D approach intends to bridge the gap between the simulation at a small scale and the simulation at the reactor scale at a reasonable CPU cost. The heat transfer process between the 1D milli-channel and its 3D surrounding is modeled. The feasibility of this 1D/3D coupling was verified by comparing simulation results to experimental ones originated from two previous works. Temperature profiles along the channel axis obtained by simulation fit the experimental profiles for both cases. The next step is to integrate the liquid-liquid mass transfer model and to validate it with our experimental results. The hydrodynamics of the liquid-liquid two-phase system is modeled using the ‘mixture model approach’. The mass transfer behavior is represented by an overall volumetric mass transfer coefficient ‘kLa’ correlation obtained from our experimental results in the millimetric size meandering channel. The present work is a first step towards the scale-up of our ‘DeanHex’ expecting future industrialization of such equipment. Therefore, a generalized scaled-up model of the reactor comprising all the transfer processes will be built in order to predict the performance of the reactor in terms of conversion rate and energy efficiency at an industrial scale.

Keywords: liquid-liquid mass transfer, milli-structured reactor, 1D/3D model, process intensification

Procedia PDF Downloads 130

Authors: Siyathorn Khunon, Thanawit Buafai

Abstract:

This paper aims to investigate management of beach safety with a focus on tourist drownings in Samui. The data collected in this investigation will then lead to the proposal of a practical management model suitable for use in Samui. Qualitative research was conducted in the following manner: nine stakeholders from local government organizations and tourism businesses were interviewed in-depth. Additionally, a best practice case study from Phuket was applied to analyze beach safety. Twelve foreign tourists were also interviewed. Then, a focus group comprised of 32 people was used to determine practical solutions for enhancing tourists’ safety on the beach in Samui. A steering committee to coordinate between public and private organizations was proposed to manage and enhance tourists’ safety. A practical model is proposed to increase the safety level of tourists in Samui

Keywords: beach safety, drowning, tourist, Samui

Procedia PDF Downloads 274

Authors: Praveen Battula

Abstract:

Any high performance car has the tendency to over steer and Understeer under slippery conditions, An Electronic Stability Control System is needed under these conditions to regulate the steering of the car. It uses Anti-Lock Braking System (ABS) and Traction Control and Wheel Speed Sensor, Steering Angle Sensor, Rotational Speed Sensors to correct the problems. The focus of this paper is to improve the driving dynamics and safety by controlling the forces applied on each wheel. ESC Control the Yaw Stability, traction controls the Roll Stability, where actually the vehicle slip rate and lateral acceleration is controlled. ESC uses differential braking on all four brakes independently to control the vehicle’s motion. A mathematical model is developed in Simulink for the FlexRay based Electronic Stability Control. Vehicle steering is developed using Neuro Fuzzy Logic Controller. 7 Degrees of Freedom Vehicle Model is used as a Plant Model using dSpace autobox. The Performance of the system is assessed using two different road Scenarios, Vehicle Control under standard maneuvering conditions. The entire system is set using Dspace Control Desk. Results are provided by comparison of how a Vehicle with and without Electronic Stability Control which shows an improved performance in control.

Keywords: ESC, flexray, chassis control, steering, neuro fuzzy, vehicle dynamics

Procedia PDF Downloads 448