Search results for: output from learners

Authors: Karolina Wieczorek, Sophie Wiliams

Abstract:

Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

Procedia PDF Downloads 98

Authors: M. P. Nanda Kumar, K. Dheeraj

Abstract:

The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.

Keywords: inverse optimal control, radial basis function, neural network, controller design

Procedia PDF Downloads 550

Authors: Bola M. Tunde-Awe

Abstract:

The study investigated the influence of teacher’s non-verbal communication on secondary school students’ learning outcomes in English language. The study was a survey research. Participants were three hundred Senior Secondary School II students randomly selected from ten schools in Akoko South West Local Government Area of Ondo State, Nigeria. The instrument used for data collection was a questionnaire containing twenty items on a four-point Likert scale which measured teacher’s use of three types of non-verbal communication modes: body movement, eye contact and spatial distance. The data collected was analysed using simple percentage. Findings revealed that teacher’s use of these non-verbal communication modes enhanced learners’ learning outcomes in English language: a total of 271 (90.33%) participants affirmed that teacher’s body language influenced their learning of English; 224 (74.66%) maintained the same stand for eye contact; while 202 (67.33%) affirmed that teacher’s spatial distance had positive influence. Consequent upon these findings, it was recommended that teachers of English language should constantly utilize non-verbal communication in their instructional delivery. Also, non-verbal communication modes should be included in teacher education programme to equip prospective pre-service teachers with the art of non-verbal communication.

Keywords: non-verbal communication, body language, eye contact, spatial distance, learning outcomes

Procedia PDF Downloads 416

Authors: Krzysztof Malczewski

Abstract:

Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

Procedia PDF Downloads 426

Authors: Mohamed Abdullah Ahmed

Abstract:

In a study of chickpea protein isolate (CPI) preparation, the wet alkaline extraction was carried out. The objectives were to determine the optimal extracting conditions of CPI and apply CPI into a sponge cake recipe to replace egg and make acceptable product. The design used in extraction was a central composite design. The response surface methodology was preferred to graphically express the relationship between extraction time and pH with the output variables of percent yield and protein content of CPI. It was noted that optimal extracting conditions were 60 min and pH 10.5 resulting in 90.07% protein content and 89.15% yield of CPI. The protein isolate (CPI) could be incorporated in cake to 20% without adversely affecting the cake physical properties such as cake hardness and sensory attributes. The higher protein content in cake was corresponding to the amount of CPI added. Therefore, adding CPI can significantly (p<0.05) increase protein content in cake. However, sensory evaluation showed that adding more than 20% of CPI decreased the overall acceptability. The results of this investigation could be used as a basic knowledge of CPI utilization in other food products.

Keywords: chick bean protein isolate, sponge cake, utilization, sponge

Procedia PDF Downloads 364

Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou

Abstract:

The application of today's semiconductor transistors in high power UHF DVB-T linear amplifiers has evolved significantly by utilizing LDMOS technology. This fact provides engineers with the option to design a single transistor signal amplifier which enables output power and linearity that was unobtainable previously using bipolar junction transistors or later type first generation MOSFETS. The quiescent current stability in terms of thermal variations of the LDMOS guarantees a robust operation in any topology of DVB-T signal amplifiers. Otherwise, progressively uncontrolled heat dissipation enhancement on the LDMOS case can degrade the amplifier’s crucial parameters in regards to the gain, linearity, and RF stability, resulting in dysfunctional operation or a total destruction of the unit. This paper presents one more sophisticated approach from the traditional biasing circuits used so far in LDMOS DVB-T amplifiers. It utilizes a microprocessor control technology, providing stability in topologies where IDQ must be perfectly accurate.

Keywords: LDMOS, amplifier, back-off, bias circuit

Procedia PDF Downloads 336

Authors: Reginaldo Cardoso, Magno Enrique Mendoza Meza

Abstract:

This work focuses on simulation and comparison of two control skyhook techniques applied to a quarter-car of the active suspension. The objective is to provide comfort to the driver. The main idea of skyhook control is to imagine a damper connected to an imaginary sky; thus, the feedback is performed with the resultant force between the imaginary and the suspension damper. The first control technique is the Mandani fuzzy skyhook and the second control technique is a Takagi-Sugeno fuzzy skyhook controller, in the both controllers the inputs are the relative velocity between the two masses and the vehicle body velocity, the output of the Mandani fuzzy skyhook is the coefficient of imaginary damper viscous-friction and the Takagi-Sugeno fuzzy skyhook is the force. Finally, we compared the techniques. The Mandani fuzzy skyhook showed a more comfortable response to the driver, followed closely by the Takagi- Sugeno fuzzy skyhook.

Keywords: active suspention, Mandani, quarter-car, skyhook, Sugeno

Procedia PDF Downloads 460

Authors: Alexey V. Klyuev, Arkady V. Yakimov, Mikhail I. Ryzhkin, Andrey V. Klyuev

Abstract:

Fluctuations of Schottky diode parameters in a structure of the mixer are investigated. These fluctuations are manifested in two ways. At the first, they lead to fluctuations in the transfer factor that is lead to the amplitude fluctuations in the signal of intermediate frequency. On the basis of the measurement data of 1/f noise of the diode at forward current, the estimation of a spectrum of relative fluctuations in transfer factor of the mixer is executed. Current dependence of the spectrum of relative fluctuations in transfer factor of the mixer and dependence of the spectrum of relative fluctuations in transfer factor of the mixer on the amplitude of the heterodyne signal are investigated. At the second, fluctuations in parameters of the diode lead to the occurrence of 1/f noise in the output signal of the mixer. This noise limits the sensitivity of the mixer to the value of received signal.

Keywords: current-voltage characteristic, fluctuations, mixer, Schottky diode, 1/f noise

Procedia PDF Downloads 582

Authors: Muhammad Ilyas, Awais Khan, Syed Ali Raza Shah

Abstract:

DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is getting the interest of the scientific community in robotics, especially in the robotic arm, a flexible joint manipulator. The current research work is based on position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in hardware setup based on LabVIEW programming is slightly greater than simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the dc motor varies between 0-8V to ensure minimal steady error while tracking the position and speed of the DC motor.

Keywords: DC motor, labview, proportional integral derivative control, position tracking, speed tracking

Procedia PDF Downloads 102

Authors: Abdel-Aziz M. Mohamed

Abstract:

This research proposes a methodology to estimate the customer order lead time in the supply chain based on the process capability index. The cases when the process output is normally distributed and when it is not are considered. The relationships between the system capability indices in both service and manufacturing applications, delivery system reliability and the percentages of orders delivered after their promised due dates are presented. The proposed method can be used to examine the current process capability to deliver the orders before the promised lead-time. If the system was found to be incapable, the method can be used to help revise the current lead-time to a proper value according to the service reliability level selected by the management. Numerical examples and a case study describing the lead time estimation methodology and testing the system capability of delivering the orders before their promised due date are illustrated.

Keywords: lead-time estimation, process capability index, delivery system reliability, statistical analysis, service achievement index, service quality

Procedia PDF Downloads 554

Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

Abstract:

Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

Procedia PDF Downloads 395

Authors: A. E. Kurtoglu, A. Cevik, M. Bilgehan

Abstract:

In this parametric study, effect of soil and material characteristics on safety of structures is investigated. The soil parameters such as shear strength, unit weight; geometrical parameters of the structure such as foundation depth and height of building; and material properties such as weight of concrete were selected as input parameters. A real accelerogram of 1989 El-Centro earthquake recorded by the USGS in Imperial Valley is used for this study. It is contained in the standard Strong Motion CD-ROM (SMC) format, which can be recognized and interpreted by FEM software used. The soil-structure interaction model subjected to above-mentioned earthquake was analyzed for 729 cases. Effect of input parameters on safety factor of the soil-structure system was then investigated and the interaction between the input and output parameters is presented in graphical form. Findings showed that all input parameters have significant effects on factor of safety results.

Keywords: factor of safety, finite element method, safety of structures, soil structure interaction

Procedia PDF Downloads 503

Authors: Abderraouf Gaaloul, Faouzi Msahli

Abstract:

The use of standard sliding mode controller, usually, leads to the appearing of an undesirable chattering phenomenon affecting the control signal. Such problem can be overcome using a higher-order sliding mode controller (HOSMC) which preserves the main properties of the standard sliding mode and deliberately increases the control smoothness. In this paper, we propose a new HOSMC for a class of uncertain multi-input multi-output nonlinear systems. Based on high gain and integral sliding mode paradigms, the established control scheme removes theoretically the chattering phenomenon and provides the stability of the control system. Numerical simulations are developed to show the effectiveness of the proposed controller when applied to solve a control problem of two water levels into a quadruple-tank process.

Keywords: nonlinear systems, sliding mode control, high gain, higher order

Procedia PDF Downloads 322

Authors: Mojtaba Saeedinezhad, Sarah Yousefi

Abstract:

In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

Procedia PDF Downloads 344

Authors: Naomi Weiner-Levy

Abstract:

The Mofet Institute of Research, established a School of Professional Development, the only one of its kind in Israel and throughout the world. It offers specialized programs for teacher educators, providing them with the professional knowledge and skills. The studies aim at updating teachers about rapidly changing knowledge and skills. Teacher educators are conceptualized as shifting from first order practitioners (school teachers) to second order practitioners. Those who train teachers are referred to as third order practitioners. The instructors in the School of Professional Development are third-order practitioners – teacher educators specializing in teaching their colleagues. Collegial guidance by teachers’ college staff members is no simple task: Tutors must be expert in their field of specialization, as well as in instruction. Moreover, although colleagues, they have to position themselves within the group as authoritative figures in terms of instruction and knowledge. To date, the role and professional identity of these third-order practitioners, has not been studied. To understand the nature and development of professional identity, a qualitative study was conducted in which 12 tutors of various subjects were interviewed. These were analyzed by categorical content analysis. The findings, assessed professional identity through a post-modern prism, while examining the interplay among events that tutors experienced, the knowledge they acquired and the structuring of their professional identity. The Tutors’ identity transformed through negotiating with ‘self’ and ‘other’ in the class, and constructed by their mutual experiences as tutors and learners. Understanding the function and identity of tutors facilitates comprehension of this unique training process for teacher educators.

Keywords: professional development, professional identity, teacher education, tutoring

Procedia PDF Downloads 221

Authors: Mohamed A. Deyab, Ahmed E. Awadallah

Abstract:

Under various conditions, we present a promising method for producing pure hydrogen energy from the electrochemical reaction of Mg metal in waste oilfield water (WOW). Mg metal and WOW are primarily consumed in this process. The results show that the hydrogen gas output is highly dependent on temperature and solution pH. The best conditions for hydrogen production were found to be a low pH (2.5) and a high temperature (338 K). For the first time, the Allyl methylimidazolium bis-trifluoromethyl sulfonyl imide) (IL) ionic liquid is used to regulate the rate of hydrogen generation. It has been confirmed that increasing the solution temperature and decreasing the solution pH accelerates Mg dissolution and produces more hydrogen per unit of time. The adsorption of IL on the active sites of the Mg surface is unrestricted by mixing physical and chemical orientation. Inspections using scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and FT-IR spectroscopy were used to identify and characterise surface corrosion of Mg in WOW. This process is also completely safe and can create energy on demand.

Keywords: hydrogen production, Mg, wastewater, ionic liquid

Procedia PDF Downloads 151

Authors: F. R. M. Nascimento, E. E. S. Lora, J. C. E. Palácio

Abstract:

A mathematical model to investigate the performance of a two stage fixed bed downdraft gasifier operating with air, steam and oxygen mixtures as the gasifying fluid has been developed. The various conditions of mixtures for a double stage fluid entry, have been performed. The model has been validated through a series of experimental tests performed by NEST – The Excellence Group in Thermal and Distributed Generation of the Federal University of Itajubá. Influence of mixtures are analyzed through the Steam to Biomass (SB), Equivalence Ratio (ER) and the Oxygen Concentration (OP) parameters in order to predict the best operating conditions to obtain adequate output gas quality, once is a key parameter for subsequent gas processing in the synthesis of biofuels, heat and electricity generation. Results show that there is an optimal combination in the steam and oxygen content of the gasifying fluid which allows the user find the best conditions to design and operate the equipment according to the desired application.

Keywords: air, equilibrium, downdraft, fixed bed gasification, mathematical modeling, mixtures, oxygen steam

Procedia PDF Downloads 477

Authors: Glaoui Hachemi

Abstract:

In this paper, a scheme based on multi-input multi output Fuzzy Sliding Mode control (MIMO-FSMC) for linear speed regulation of winding system is proposed. Once the uncoupled model of the winding system was obtained, a smooth control function with a threshold was selected to indicate how far away the case was from the sliding surface. nevertheless, this control function depends closely on the higher bound of the uncertainties, which generates overlap. So, this size has to be chosen with broad care to obtain high performances. Usually, the upper bound of uncertainties is difficult to know before motor operation, so, a Fuzzy Sliding Mode controller is investigated to resolve this problem, a simple Fuzzy inference mechanism is used to decrease the chattering phenomenon by simple adjustments. A simulation study is achieved and that the indicate fuzzy sliding mode controllers have great potential for use as an alternative to the conventional sliding mode control.

Keywords: Winding system, induction machine, Mechanical tension, Proportional-integral (PI), sliding mode control, Fuzzy logic

Procedia PDF Downloads 92

Authors: Amer Ait Sidhoum

Abstract:

Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

Procedia PDF Downloads 120

Authors: P. Pistelok

Abstract:

The article presents the concept of an electromagnetic circuit generator with permanent magnets mounted on the surface rotor core designed for single phase work. Computation field-circuit model was shown. The spectrum of time course of voltages in the idle work was presented. The cross section with graphically presentation of magnetic induction in particular parts of electromagnetic circuits was presented. Distribution of magnetic induction at the rated load point for each phase were shown. The time course of voltages and currents for each phases for rated power were displayed. An analysis of laboratory results and measurement of load characteristics of the generator was discussed. The work deals with three electromagnetic circuits of generators with permanent magnet where output voltage characteristics versus rated power were expressed.

Keywords: permanent magnet generator, permanent magnets, vibration, course of torque, single phase work, asymmetrical three phase work

Procedia PDF Downloads 284

Authors: Lei Zhang, Li Ji

Abstract:

Formal learning and informal learning represent two distinct learning styles: one is systematic and organized, another is causal and unstructured. Although there are many factors influencing online learning satisfaction, including self-regulation, self-efficacy, and interaction, factors influencing online formal learning and informal learning satisfaction may differ from each other. This paper investigated and compared influential factors of online formal and informal learning. Two questionnaires were created based on previous studies to explore factors influencing online formal learning and online informal learning satisfaction, respectively. A sample of 105 college students from different departments in a university located in the eastern part of China was selected to participate in this study. They all had an online learning experience and agreed to fill out questionnaires. Correlation analysis, variance analysis, and regression analysis were employed in this study. In addition, five participants were chosen for interviews. The study found that student-content, interaction, self-regulation, and self-efficacy related positively to both online formal learning and informal learning satisfaction. In addition, compared to online formal learning, student-content interaction in informal learning was the most influential factor for online learning satisfaction, perhaps that online informal learning was more goal-oriented and learners paid attention to the quality of content. In addition, results also revealed that interactions among students or teachers had little impact on online informal learning satisfaction. This study compared influential factors in online formal and informal learning satisfaction helped to add discussions to online learning satisfaction and contributed to further practices of online learning.

Keywords: learning satisfaction, formal learning, informal learning, online learning

Procedia PDF Downloads 160

Authors: A. Peniak, J. Makarovič, P. Rafajdus, P. Dúbravka

Abstract:

The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.

Keywords: automotive, drive system, electric car, finite element method, hybrid car, optimization, switched reluctance motor

Procedia PDF Downloads 516

Authors: Tetsuki Taniguchi, Yoshio Karasawa

Abstract:

This paper describes a node pair selection scheme in relay-aided multiple source multiple destination communication system based on stable marriage problem. A general case is assumed in which all of source, relay and destination nodes are equipped with multiantenna and carry out multistream transmission. Based on several metrics introduced from inter-node channel condition, the preference order is determined about all source-relay and relay-destination relations, and then the node pairs are determined using Gale-Shapley algorithm. The computer simulations show that the effectiveness of node pair selection is larger in multihop communication. Some additional aspects which are different from relay-less case are also investigated.

Keywords: relay, multiple input multiple output (MIMO), multiuser, amplify and forward, stable marriage problem, Gale-Shapley algorithm

Procedia PDF Downloads 396

Authors: Salima Smiti, Ines Gasmi, Makram Soui

Abstract:

Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

Procedia PDF Downloads 179

Authors: Sarita Agarwal, Deepika Delsa Dean

Abstract:

Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

Procedia PDF Downloads 127

Authors: Marcel Kohler

Abstract:

The effect of trade liberalization on environmental conditions has yielded a great deal of debate in the current energy economics literature. Although research on the relationship between income growth and CO2 emissions is not new in South Africa, few studies address the role that South Africa’s foreign trade plays in this context. This paper undertakes to investigate empirically the impact of South Africa’s foreign trade reforms over the last four decades on its energy consumption and CO2 emissions by taking into account not only the direct effect of trade on each, but also its indirect effect through income induced growth. Using co integration techniques we attempt to disentangle the long and short-run relationship between trade openness, income per capita and energy consumption and CO2 emissions in South Africa. The preliminary results of this study find support for a positive bi-directional relationship between output and CO2 emissions, as well as between trade openness and CO2. This evidence confirms the expectation that as the South African economy opens up to foreign trade and experiences growth in per capita income, the countries CO2 emissions will increase.

Keywords: trade openness, CO2 emissions, cointegration, South Africa

Procedia PDF Downloads 405

Authors: Changqiao Wu, Guoqing Ding, Xin Chen

Abstract:

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

Procedia PDF Downloads 124

Authors: Tatiana Tunon, Gottfried Pestal

Abstract:

Government agencies responsible for the management of fisheries resources publish many types of grey literature, and these materials are increasingly accessible to the public on agency websites. However, scope and quality vary considerably, and end-users need meta-data about the report series when deciding whether to use the information (e.g. apply the methods, include the results in a systematic review), or when prioritizing materials for archiving (e.g. library holdings, reference databases). A proposed taxonomy for these report series was developed based on a review of 41 report series from 6 government agencies in 4 countries (Canada, New Zealand, Scotland, and United States). Each report series was categorized according to multiple criteria describing peer-review process, content, and purpose. A robust classification tree was then fitted to these descriptions, and the resulting taxonomic groups were used to compare agency output from 4 countries using reports available in their online repositories.

Keywords: classification tree, fisheries, government, grey literature

Procedia PDF Downloads 279

Authors: Tingneyuc Sekac, Sujoy Kumar Jana, Indrajit Pal, Dilip Kumar Pal

Abstract:

Tectonism induced Tsunami, landslide, ground shaking leading to liquefaction, infrastructure collapse, conflagration are the common earthquake hazards that are experienced worldwide. Apart from human casualty, the damage to built-up infrastructures like roads, bridges, buildings and other properties are the collateral episodes. The appropriate planning must precede with a view to safeguarding people’s welfare, infrastructures and other properties at a site based on proper evaluation and assessments of the potential level of earthquake hazard. The information or output results can be used as a tool that can assist in minimizing risk from earthquakes and also can foster appropriate construction design and formulation of building codes at a particular site. Different disciplines adopt different approaches in assessing and monitoring earthquake hazard throughout the world. For the present study, GIS and Remote Sensing potentials were utilized to evaluate and assess earthquake hazards of the study region. Subsurface geology and geomorphology were the common features or factors that were assessed and integrated within GIS environment coupling with seismicity data layers like; Peak Ground Acceleration (PGA), historical earthquake magnitude and earthquake depth to evaluate and prepare liquefaction potential zones (LPZ) culminating in earthquake hazard zonation of our study sites. The liquefaction can eventuate in the aftermath of severe ground shaking with amenable site soil condition, geology and geomorphology. The latter site conditions or the wave propagation media were assessed to identify the potential zones. The precept has been that during any earthquake event the seismic wave is generated and propagates from earthquake focus to the surface. As it propagates, it passes through certain geological or geomorphological and specific soil features, where these features according to their strength/stiffness/moisture content, aggravates or attenuates the strength of wave propagation to the surface. Accordingly, the resulting intensity of shaking may or may not culminate in the collapse of built-up infrastructures. For the case of earthquake hazard zonation, the overall assessment was carried out through integrating seismicity data layers with LPZ. Multi-criteria Evaluation (MCE) with Saaty’s Analytical Hierarchy Process (AHP) was adopted for this study. It is a GIS technology that involves integration of several factors (thematic layers) that can have a potential contribution to liquefaction triggered by earthquake hazard. The factors are to be weighted and ranked in the order of their contribution to earthquake induced liquefaction. The weightage and ranking assigned to each factor are to be normalized with AHP technique. The spatial analysis tools i.e., Raster calculator, reclassify, overlay analysis in ArcGIS 10 software were mainly employed in the study. The final output of LPZ and Earthquake hazard zones were reclassified to ‘Very high’, ‘High’, ‘Moderate’, ‘Low’ and ‘Very Low’ to indicate levels of hazard within a study region.

Keywords: hazard micro-zonation, liquefaction, multi criteria evaluation, tectonism

Procedia PDF Downloads 264

Authors: M. Heydari Vini

Abstract:

There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

Procedia PDF Downloads 501