Search results for: active learning

Authors: S. Shubha, B. N. Meera

Abstract:

Physics Education Research (PER) results have shown that students do not achieve the expected level of competency in understanding the concepts of different domains of Physics learning when taught by the traditional teaching methods, the concepts of Electricity and Magnetism (E&M) being one among them. Simulation being one of the valuable instructional tools renders an opportunity to visualize varied experiences with such concepts. Considering the electric force concept which requires extensive use of vector representations, we report here the outcome of the research results pertaining to the student understanding of this concept and the role of simulation in using vector representation. The simulation platform provides a positive impact on the use of vector representation. The first stage of this study involves eliciting and analyzing student responses to questions that probe their understanding of the concept of electrostatic force and this is followed by four stages of student interviews as they use the interactive simulations of electric force in one dimension. Student responses to the questions are recorded in real time using electronic pad. A validation test interview is conducted to evaluate students' understanding of the electric force concept after using interactive simulation. Results indicate lack of procedural knowledge of the vector representation. The study emphasizes the need for the choice of appropriate simulation and mode of induction for learning.

Keywords: Electric Force, Interactive, Representation, Simulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2208

Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.

Keywords: Bioinformatics, Protein-protein interactions, Bayesian Kernel, Support Vector Machines.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2142

Authors: Živa Ravnikar, Alfonso Bahillo Martinez, Barbara Goličnik Marušić

Abstract:

Climate change mitigation has been formally adopted and announced by countries over the globe, where cities are targeting carbon neutrality through various more or less successful, systematic, and fragmentary actions. The article is based on the fact that environmental conditions affect human comfort and the usage of space. Urban planning can, with its sustainable solutions, not only support climate mitigation in terms of a planet reduction of global warming but as well enabling natural processes that in the immediate vicinity produce environmental conditions that encourage people to walk or cycle. However, the article draws attention to the importance of integrating climate consideration into urban planning, where detailed environmental data play a key role, enabling urban planners to improve or monitor environmental conditions on cycle paths. In a practical aspect, this paper tests a particular ICT tool, a prototype used for environmental data. Data gathering was performed along the cycling lanes in Ljubljana (Slovenia), where the main objective was to assess the tool's data applicable value within the planning of comfortable cycling lanes. The results suggest that such transportable devices for in-situ measurements can help a researcher interpret detailed environmental information, characterized by fine granularity and precise data spatial and temporal resolution. Data can be interpreted within human comfort zones, where graphical representation is in the form of a map, enabling the link of the environmental conditions with a spatial context. The paper also provides preliminary results in terms of the potential of such tools for identifying the correlations between environmental conditions and different spatial settings, which can help urban planners to prioritize interventions in places. The paper contributes to multidisciplinary approaches as it demonstrates the usefulness of such fine-grained data for better consideration of microclimatology in urban planning, which is a prerequisite for creating climate-comfortable cycling lanes promoting active mobility.

Keywords: Information and communication technology tools, urban planning, human comfort, microclimate, cycling lanes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 432

Authors: Hira Lal Gope, Hidekazu Fukai

Abstract:

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1492

Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

Abstract:

With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: Energy-efficient buildings, Hierarchical model predictive control, Microgrid power flow optimization, Price-optimal building climate control.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1499

Authors: Marco Leite, J. M. Vilas-Boas da Silva, Isabel Duarte de Almeida

Abstract:

New Product Development (NPD) has got its roots on an Engineering background. Thus, one might wonder about the interest, opportunity, contents and delivery process, if students from soft sciences were involved. This paper addressed «What to teach?» and «How to do it?», as the preliminary research questions that originated the introduced propositions. The curriculum-developer model that was purposefully chosen to adapt the coursebook by pursuing macro/micro strategies was found significant by an exploratory qualitative case study. Moreover, learning was developed and value created by implementing the institutional curriculum through a creative, hands-on, experiencing, problem-solving, problem-based but organized teamwork approach. Product design of an orange squeezer complying with ill-defined requirements, including drafts, sketches, prototypes, CAD simulations and a business plan, plus a website, written reports and presentations were the deliverables that confirmed an innovative contribution towards research and practice of teaching and learning of engineering subjects to non-specialist operations managers candidates.

Keywords: Teaching Engineering to Non-specialists, Operations Managers Education, Teamwork, Product Design and Development, Market- driven NPD, Curriculum development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2388

Authors: Rami Rashkovits, Ilana Lavy

Abstract:

In this study we present our developed formative assessment tool for students' assignments. The tool enables lecturers to define assignments for the course and assign each problem in each assignment a list of criteria and weights by which the students' work is evaluated. During assessment, the lecturers feed the scores for each criterion with justifications. When the scores of the current assignment are completely fed in, the tool automatically generates reports for both students and lecturers. The students receive a report by email including detailed description of their assessed work, their relative score and their progress across the criteria along the course timeline. This information is presented via charts generated automatically by the tool based on the scores fed in. The lecturers receive a report that includes summative (e.g., averages, standard deviations) and detailed (e.g., histogram) data of the current assignment. This information enables the lecturers to follow the class achievements and adjust the learning process accordingly. The tool was examined on two pilot groups of college students that study a course in (1) Object-Oriented Programming (2) Plane Geometry. Results reveal that most of the students were satisfied with the assessment process and the reports produced by the tool. The lecturers who used the tool were also satisfied with the reports and their contribution to the learning process.

Keywords: Computer-based formative assessment tool, science education.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1872

Authors: Rana M. Zeina, Laila AL-Ayadhi, Shahid Bashir

Abstract:

The association between sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a Neuropsychological Test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/little circle (BLC), Simple Reaction Time (SRT) Intra /Extra dimensional set shift (IED), Spatial recognition memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. ASDs individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to a stimulus.

Keywords: Visual memory, Attention, Autism Spectrum Disorders (ASDs).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2503

Authors: Eftah Bte. Moh @ Hj Abdullah, Izazol Binti Idris, Abd Aziz Bin Abd Shukor

Abstract:

This study aimed to identify the alignment of understanding and assessment practices among secondary school teachers. The study was carried out using quantitative descriptive study. The sample consisted of 164 teachers who taught Form 1 and 2 from 11 secondary schools in the district of North Kinta, Perak, Malaysia. Data were obtained from 164 respondents who answered Expectation Alignment Understanding and Practices of School Assessment (PEKDAPS) questionnaire. The data were analysed using SPSS 17.0+. The Cronbach’s alpha value obtained through PEKDAPS questionnaire pilot study was 0.86. The results showed that teachers' performance in PEKDAPS based on the mean value was less than 3, which means that perfect alignment does not occur between the understanding and practices of school assessment. Two major PEKDAPS sub-constructs of articulation across grade and age and usability of the system were higher than the moderate alignment of the understanding and practices of school assessment (Min=2.0). The content focused of PEKDAPs sub-constructs which showed lower than the moderate alignment of the understanding and practices of school assessment (Min=2.0). Another two PEKDAPS subconstructs of transparency and fairness and the pedagogical implications showed moderate alignment (2.0). The implications of the study is that teachers need to fully understand the importance of alignment among components of assessment, learning and teaching and learning objectives as strategies to achieve quality assessment process.

Keywords: Alignment, assessment practices, School Based Assessment, understanding.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1986

Authors: Vinicius Binotte, Guilherme Baldo, Christiane Goulart, Carlos Valadão, Eliete Caldeira, Teodiano Bastos

Abstract:

Socially assistive robotic has become increasingly active and it is present in therapies of people affected for several neurobehavioral conditions, such as Autism Spectrum Disorder (ASD). In fact, robots have played a significant role for positive interaction with children with ASD, by stimulating their social and cognitive skills. This work introduces a mobile socially-assistive robot, which was built for interaction with children with ASD, using non-linear control techniques for this interaction.

Keywords: Socially assistive robotics, mobile robot, autonomous control, autism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1540

Authors: Zakir Husain, Neem Sagar, Neeraj Gupta

Abstract:

Due to the increased penetration of renewable energy resources in the distribution system, the system is no longer passive in nature. In this paper, a steady state analysis of the distribution system has been done with the inclusion of wind generation. The modeling of wind turbine generator system and wind generator has been made to obtain the average active and the reactive power injection into the system. The study has been conducted on a IEEE-33 bus system with two wind generators. The present research work is useful not only to utilities but also to customers.

Keywords: Distributed generation, distribution network, radial network, wind turbine generating system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1038

Authors: Emad E Abdallah, A.F. Otoom, ArwaSaqer, Ola Abu-Aisheh, Diana Omari, Ghadeer Salem

Abstract:

As emails communications have no consistent authentication procedure to ensure the authenticity, we present an investigation analysis approach for detecting forged emails based on Random Forests and Naïve Bays classifiers. Instead of investigating the email headers, we use the body content to extract a unique writing style for all the possible suspects. Our approach consists of four main steps: (1) The cybercrime investigator extract different effective features including structural, lexical, linguistic, and syntactic evidence from previous emails for all the possible suspects, (2) The extracted features vectors are normalized to increase the accuracy rate. (3) The normalized features are then used to train the learning engine, (4) upon receiving the anonymous email (M); we apply the feature extraction process to produce a feature vector. Finally, using the machine learning classifiers the email is assigned to one of the suspects- whose writing style closely matches M. Experimental results on real data sets show the improved performance of the proposed method and the ability of identifying the authors with a very limited number of features.

Keywords: Digital investigation, cybercrimes, emails forensics, anonymous emails, writing style, and authorship analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5226

Authors: Camelia Petrescu, Lavinia Ferariu

Abstract:

The paper presents an optimization study based on genetic algorithms (GA-s) for a radio-frequency applicator used in heating dielectric band products. The weakly coupled electro-thermal problem is analyzed using 2D-FEM. The design variables in the optimization process are: the voltage of a supplementary “guard" electrode and six geometric parameters of the applicator. Two objective functions are used: temperature uniformity and total active power absorbed by the dielectric. Both mono-objective and multiobjective formulations are implemented in GA optimization.

Keywords: Dielectric heating, genetic algorithms, optimization, RF applicators.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915

Authors: Christiana Gauci-Sciberras

Abstract:

The first language (L1) could be used in foreign language teaching and learning as a pedagogical tool to scaffold new knowledge in the target language (TL) upon linguistic knowledge that the learner already has. In a bilingual context, code-switching between the two languages usually occurs in classrooms. One of the reasons for code-switching is because both languages are used for scaffolding new knowledge. This research paper aims to find out why both the L1 (Maltese) and the L2 (English) are used in the classroom of Mandarin Chinese as a foreign language (CFL) in the bilingual context of Malta. This research paper also aims to find out the learners’ perceptions of the use of a bilingual medium of instruction. Two research methods were used to collect qualitative data; semi-structured interviews with adult learners of Mandarin Chinese and lesson observations. These two research methods were used so that the data collected in the interviews would be triangulated with data collected in lesson observations. The L1 (Maltese) is the language of instruction mostly used. The teacher and the learners switch to the L2 (English) or to any other foreign language according to the need at a particular instance during the lesson.

Keywords: Chinese, bilingual, pedagogical purpose of L1 and L2, CFL acquisition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 470

Authors: Tania Elena González Alvarado, Ma. Antonieta Martín Granados

Abstract:

The aim of this paper is to explain what a multienterprise tie is, what evidence its analysis provides and how does the cooperation mechanism influence the establishment of a multienterprise tie. The study focuses on businesses of smaller dimension, geographically dispersed and whose businessmen are learning to cooperate in an international environment. The empirical evidence obtained at this moment permits to conclude the following: The tie is not long-lasting, it has an end; opportunism is an opportunity to learn; the multi-enterprise tie is a space to learn about the cooperation mechanism; the local tie permits a businessman to alternate between competition and cooperation strategies; the disappearance of a tie is an experience of learning for a businessman, diminishing the possibility of failure in the next tie; the cooperation mechanism tends to eliminate hierarchical relations; the multienterprise tie diminishes the asymmetries and permits SME-s to have a better position when they negotiate with large companies; the multi-enterprise tie impacts positively on the local system. The collection of empirical evidence was done trough the following instruments: direct observation in a business encounter to which the businesses attended in 2003 (202 Mexican agro industry SME-s), a survey applied in 2004 (129), a questionnaire applied in 2005 (86 businesses), field visits to the businesses during the period 2006-2008 and; a survey applied by telephone in 2008 (55 Mexican agro industry SME-s).

Keywords: Cooperation, multi-enterprise tie, links, networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1253

Authors: Christian Endisch, Christoph Hackl, Dierk Schröder

Abstract:

This paper presents an exact pruning algorithm with adaptive pruning interval for general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The structure of the plant is unknown, so the identification process is started with a larger network architecture than necessary. During parameter optimization with the Levenberg- Marquardt (LM) algorithm irrelevant weights of the dynamic neural network are deleted in order to find a model for the plant as simple as possible. The weights to be pruned are found by direct evaluation of the training data within a sliding time window. The influence of pruning on the identification system depends on the network architecture at pruning time and the selected weight to be deleted. As the architecture of the model is changed drastically during the identification and pruning process, it is suggested to adapt the pruning interval online. Two system identification examples show the architecture selection ability of the proposed pruning approach.

Keywords: System identification, dynamic neural network, recurrentneural network, GDNN, optimization, Levenberg Marquardt, realtime recurrent learning, network pruning, quasi-online learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1914

Authors: Alexey P. Antropov, Alexander V. Ragutkin, Nicolay A. Yashtulov

Abstract:

The original controlled technology for power active nanocomposite membrane-electrode assembly engineering on the basis of porous silicon is presented. The functional nanocomposites were studied by electron microscopy and cyclic voltammetry methods. The application possibility of the obtained nanocomposites as high performance renewable energy sources for micro-power electronic devices is demonstrated.

Keywords: Cyclic voltammetry, electron microscopy, nanotechnology, platinum-palladium nanocomposites, porous silicon, power activity, renewable energy sources.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1200

Authors: Mirabbos Mirkamalov, Zavkiddin Mirtoshev

Abstract:

The M 1.6 class flare occurred on 6^th of September 2012. Our observations correspond to the active region NOAA 11560 with the heliographic coordinates N04W71. The event took place between 04:00 UT and 04:45 UT, and was close to the solar limb at the western region. The flare temperature correlates with flux peak, increases for a short period (between 04:08 UT and 04:12 UT), rises impulsively, attains a maximum value of about 17 MK at 04:12 UT and gradually decreases after peak value. Around the peak we observe significant emissions of X-ray sources. Flux profiles of the X-ray emission exhibit a progressively faster raise and decline as the higher energy channels are considered.

Keywords: Magnetic reconnection, solar atmosphere, solar flare, X-ray emission.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 893

Authors: Goh Yung Hong, Mona Masood

Abstract:

This paper explores the effects of gamification on lower secondary school students’ motivation and engagement in the classroom. Two-group posttest-only experimental design were employed to study the influence of gamification teaching method (GTM) when compared with conventional teaching method (CTM) on 60 lower secondary school students. The Student Engagement Instrument (SEI) and Intrinsic Motivation Inventory (IMI) were used to assess students’ intrinsic motivation and engagement level towards the respective teaching method. Finding indicates that students who completed the GTM lesson were significantly higher in intrinsic motivation to learn than those from the CTM. Although the result were insignificant and only marginal difference in the engagement mean, GTM still show better potential in raising student’s engagement in class when compared with CTM. This finding proves that the GTM is likely to solve the current issue of low motivation to learn and low engagement in class among lower secondary school students in Malaysia. On the other hand, despite being not significant, higher mean indicates that CTM positively contribute to higher peer support for learning and better teacher and student relationship when compared with GTM. As a conclusion, gamification approach is flexible and can be adapted into many learning content to enhance the intrinsic motivation to learn and to some extent, encourage better student engagement in class.

Keywords: Conventional teaching method, Gamification teaching method, Motivation, Engagement.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5758

Authors: Derya Burcu Ozkan, Onur Kiziler, Duriye Bilge

Abstract:

Cogeneration may be defined as a system which contains electricity production and regain of the thermo value of exhaust gases simultaneously. The examination is based on the data-s of an active cogeneration plant. This study, it is aimed to determine which component of the system should be revised first to raise the efficiency and decrease the loss of exergy. For this purpose, second law analysis of thermodynamics is applied to each component due to consider the effects of environmental conditions and take the quality of energy into consideration as well as the quantity of it. The exergy balance equations are produced and exergy loss is calculated for each component. 44,44 % loss of exergy in heat exchanger, 29,59 % in combustion chamber, 18,68 % in steam boiler, 5,25 % in gas turbine and 2,03 % in compressor is calculated.

Keywords: Cogeneration, Exergy loss, Second law analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2500

Authors: A. A. Penin

Abstract:

Requirements that should be met when determining the regimes of circuits with variable elements are formulated. The interpretation of the variations in the regimes, based on projective geometry, enables adequate expressions for determining and comparing the regimes to be derived. It is proposed to use as the parameters of a generalized equivalent generator of an active two-pole with changeable resistor such load current and voltage which provide the current through this resistor equal to zero.

Keywords: Equivalent generator, geometric circuits theory, circuits regimes, load characteristics, variable elements.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1375

Authors: Mahesh Pal

Abstract:

In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.

Keywords: Ensemble learning, decision tree, remote sensingclassification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2555

Authors: Jian Huang, Weixin Qian, Haitao Zhang, Weiyong Ying

Abstract:

Cobalt-gadolinium catalyst for Fischer-Tropsch synthesis was prepared by impregnation method with commercial silica gel, and its texture properties were characterized by BET, XRD, and TPR. The catalytic performance of the catalyst was tested in a fixed bed reactor. The results showed that the addition of gadolinium to the cobalt catalyst might decrease the size of cobalt particles, and increased the dispersion of catalytic active cobalt phases. The carbon number distributions for the catalysts was calculated by ASF equation.

Keywords: Fischer-Tropsch synthesis, cobalt-based catalysts, gadolinium, carbon number distributions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1577

Authors: Morteza Mirhosseini, Amir B. Khoshnevis

Abstract:

The boundary layer separation and new active flow control of a NACA 0025 airfoil were studied experimentally. This new flow control is sometimes known as a co-flow jet (cfj) airfoil. This paper presents the fluctuating velocity in a wall jet over the co-flow jet airfoil subjected to an adverse pressure gradient and a curved surface. In these results, the fluctuating velocity at the inner part increasing by increased the angle of attack up to 12^o and this has due to the jet energized, while the angle of attack 20^o has different. The airfoil cord based Reynolds number has 10⁵.

Keywords: Adverse pressure gradient, fluctuating velocity, wall jet, co-flow jet airfoil.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1448

Authors: Andreas Theissler, Ian Dear

Abstract:

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2454

Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

Abstract:

A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1709

Authors: Sunho Ki, Daehwan Kim, Seongwon Cho, Sun-Tae Chung, Jaemin Kim, Yun-Kwang Hong, Chang Joon Park, Dongmin Kwon, Minhee Kang, Yusung Kim, Younghan Yoon

Abstract:

AAM (active appearance model) has been successfully applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard AAM-based face alignment method.

Keywords: AAM, Face Alignment, Feature Extraction, PCA

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1456

Authors: Yanwei Pang, Lei Zhang, Zhengkai Liu

Abstract:

Studies in neuroscience suggest that both global and local feature information are crucial for perception and recognition of faces. It is widely believed that local feature is less sensitive to variations caused by illumination, expression and illumination. In this paper, we target at designing and learning local features for face recognition. We designed three types of local features. They are semi-global feature, local patch feature and tangent shape feature. The designing of semi-global feature aims at taking advantage of global-like feature and meanwhile avoiding suppressing AdaBoost algorithm in boosting weak classifies established from small local patches. The designing of local patch feature targets at automatically selecting discriminative features, and is thus different with traditional ways, in which local patches are usually selected manually to cover the salient facial components. Also, shape feature is considered in this paper for frontal view face recognition. These features are selected and combined under the framework of boosting algorithm and cascade structure. The experimental results demonstrate that the proposed approach outperforms the standard eigenface method and Bayesian method. Moreover, the selected local features and observations in the experiments are enlightening to researches in local feature design in face recognition.

Keywords: Face recognition, local feature, AdaBoost, subspace analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1571

Authors: G. Settanni, A. Panarese, R. Vaira, A. Galiano

Abstract:

Nowadays, artificial intelligence is used successfully in the field of e-commerce for its ability to learn from a large amount of data. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them the most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Also, Long Short-Term Memory algorithms have been implemented and trained on historical data in order to predict customer scores of the different items. Items with the highest scores are recommended to customers.

Keywords: Deep Learning, Long Short-Term Memory, Machine Learning, Recommender Systems, Support Vector Machine.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 278

Authors: Samal Abzhanova, Saule Mussabekova

Abstract:

Today, a new system of education is being created in Kazakhstan in order to develop the system of education and to satisfy the world class standards. For this purpose, there have been established new requirements and responsibilities to the instructors. Students should not be limited with providing only theoretical knowledge. Also, they should be encouraged to be competitive, to think creatively and critically. Moreover, students should be able to implement these skills into practice. These issues could be resolved through the permanent improvement of teaching methods. Therefore, a specialist who teaches the languages should use up-to-date methods and introduce new technologies. The result of the investigation suggests that an interactive teaching method is one of the new technologies in this field. This paper aims to provide information about implementing new technologies in the process of teaching language. The paper will discuss about necessity of introducing innovative technologies and the techniques of organizing interactive lessons. At the same time, the structure of the interactive lesson, conditions, principles, discussions, small group works and role-playing games will be considered. Interactive methods are carried out with the help of several types of activities, such as working in a team (with two or more group of people), playing situational or role-playing games, working with different sources of information, discussions, presentations, creative works and learning through solving situational tasks and etc.

Keywords: Games, interactive learning, Kazakh language, teaching methods.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1410