Search results for: deep learning algorithms
3216 Echo State Networks for Arabic Phoneme Recognition
Authors: Nadia Hmad, Tony Allen
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This paper presents an ESN-based Arabic phoneme recognition system trained with supervised, forced and combined supervised/forced supervised learning algorithms. Mel-Frequency Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC) techniques are used and compared as the input feature extraction technique. The system is evaluated using 6 speakers from the King Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia dialectic and 34 speakers from the Center for Spoken Language Understanding (CSLU2002) database of speakers with different dialectics from 12 Arabic countries. Results for the KAPD and CSLU2002 Arabic databases show phoneme recognition performances of 72.31% and 38.20% respectively.
Keywords: Arabic phonemes recognition, echo state networks (ESNs), neural networks (NNs), supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24093215 Studies of Zooplankton in Gdańsk Basin (2010-2011)
Authors: Dzierzbicka-Glowacka, A. Lemieszek, M. Figiela
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In 2010-2011, the research on zooplankton was conducted in the southern part of the Baltic Sea to determine seasonal variability in changes occurring throughout the zooplankton in 2010 and 2011, both in the region of Gdańsk Deep, and in the western part of Gdańsk Bay. The research in the sea showed that the taxonomic composition of holoplankton in the southern part of the Baltic Sea was similar to that recorded in this region for many years. The maximum values of abundance and biomass of zooplankton both in the Deep and the Bay of Gdańsk were observed in the summer season. Copepoda dominated in the composition of zooplankton for almost the entire study period, while rotifers occurred in larger numbers only in the summer 2010 in the Gdańsk Deep as well as in May and July 2010 in the western part of Gdańsk Bay, and meroplankton – in April 2011.
Keywords: Baltic Sea, composition, Gdańsk Bay, zooplankton.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34773214 Mining Sequential Patterns Using Hybrid Evolutionary Algorithm
Authors: Mourad Ykhlef, Hebah ElGibreen
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Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem. This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed of evolutionary algorithms convergence. This algorithm is referred to as SP-GAPSO.Keywords: Genetic Algorithm, Hybrid Evolutionary Algorithm, Particle Swarm Optimization algorithm, Sequential Pattern mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20263213 An Interactive Tool for Teaching and Learning English at Upper Primary Level for Mauritius
Authors: Sameerchand Pudaruth, Avinash Mantaye
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E-learning refers to the specific kind of learning experienced within the domain of educational technology, which can be used in or out of the classroom. In this paper, we give an overview of an e-learning platform 'An Innovative Interactive and Online English Platform for Upper Primary Students' is an interactive web-based application which will serve as an aid to the primary school students in Mauritius. The objectives of this platform are to offer quality learning resources for the English subject at our primary level of education, encourage self-learning and hence promote e-learning. The platform developed consists of several interesting features, for example, the English Verb Conjugation tool, Negative Form tool, Interrogative Form tool and Close Test Generator. Thus, this learning platform will be useful at a time where our country is looking for an alternative to private tuition and also, looking forward to increase the pass rate.Keywords: educational technology, e-learning, Mauritius.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22223212 A Machine Learning Based Framework for Education Levelling in Multicultural Countries: UAE as a Case Study
Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker
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In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.
Keywords: Admissions, algorithms, cloud computing, differentiation, fog computing, leveling, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7233211 Improving the Convergence of the Backpropagation Algorithm Using Local Adaptive Techniques
Authors: Z. Zainuddin, N. Mahat, Y. Abu Hassan
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Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.
Keywords: Backpropagation, Dynamic Adaptation Methods, Local Adaptive Techniques, Neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21713210 The Impact of e-Learning and e-Teaching
Authors: Mohammad Mohammad
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With the exponential progress of technological development comes a strong sense that events are moving too quickly for our schools and that teachers may be losing control of them in the process. This paper examines the impact of e-learning and e-teaching in universities, from both the student and teacher perspective. In particular, it is shown that e-teachers should focus not only on the technical capacities and functions of IT materials and activities, but must attempt to more fully understand how their e-learners perceive the learning environment. From the e-learner perspective, this paper indicates that simply having IT tools available does not automatically translate into all students becoming effective learners. More evidence-based evaluative research is needed to allow e-learning and e-teaching to reach full potential.Keywords: e-learning, e-teaching, distance learning, education
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 48253209 The Design and Applied of Learning Management System via Social Media on Internet: Case Study of Operating System for Business Subject
Authors: Pimploi Tirastittam, Sawanath Treesathon, Amornrath Ongkawat
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Learning Management System (LMS) is the system which uses to manage the learning in order to grouping the content and learning activity between the lecturer and learner including online examination and evaluation. Nowadays, it is the borderless learning era so the learning activities can be accessed from everywhere in the world and also anytime via the information technology and media. The learner can easily access to the knowledge so the different in time and distance is not a constraint for learning anymore. The learning pattern which was used in this research is the integration of the in-class learning and online learning via internet and will be able to monitor the progress by the Learning management system which will create the fast response and accessible learning process via the social media. In order to increase the capability and freedom of the learner, the system can show the current and history of the learning document, video conference and also has the chat room for the learner and lecturer to interact to each other. So the objectives of the “The Design and Applied of Learning Management System via Social Media on Internet: Case Study of Operating System for Business Subject” are to expand the opportunity of learning and to increase the efficiency of learning as well as increase the communication channel between lecturer and student. The data of this research was collect from 30 users of the system which are students who enroll in the subject. And the result of the research is in the “Very Good” which is conformed to the hypothesis.
Keywords: Learning Management System, Social Media.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18783208 WebAppShield: An Approach Exploiting Machine Learning to Detect SQLi Attacks in an Application Layer in Run-Time
Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl
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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.
Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4433207 Design of Encoding Calculator Software for Huffman and Shannon-Fano Algorithms
Authors: Wilson Chanhemo, Henry. R. Mgombelo, Omar F Hamad, T. Marwala
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This paper presents a design of source encoding calculator software which applies the two famous algorithms in the field of information theory- the Shannon-Fano and the Huffman schemes. This design helps to easily realize the algorithms without going into a cumbersome, tedious and prone to error manual mechanism of encoding the signals during the transmission. The work describes the design of the software, how it works, comparison with related works, its efficiency, its usefulness in the field of information technology studies and the future prospects of the software to engineers, students, technicians and alike. The designed “Encodia" software has been developed, tested and found to meet the intended requirements. It is expected that this application will help students and teaching staff in their daily doing of information theory related tasks. The process is ongoing to modify this tool so that it can also be more intensely useful in research activities on source coding.Keywords: Coding techniques, Coding algorithms, Codingefficiency, Encodia, Encoding software.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34723206 M-Learning the Next Generation of Education in Cyberspace
Authors: Nasser Alalwan, Ahmed Alzahrani, Mohamed Sarrab
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The technology usages of high speed Internet leads to establish and start new era of online education. With the advancement of the information technology and communication systems new opportunities have been created. This leads universities to have various online education channels to meet the demand of different learners- needs. One of these channels is M-learning, which can be used to improve the online education environment. With using such mobile technology in learning both students and instructors can easily access educational courses anytime from anywhere. The paper first presents literature about mobile learning and to what extent this approach can be utilized to enhance the overall learning system. It provides a comparison between mobile learning and traditional elearning showing the wide array of benefits of the new generation of technology. The possible challenges and potential advantages of Mlearning in the online education system are also discussed.Keywords: Mobile learning, M-learning, eLearning, Educational system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21093205 The Learning Impact of a 4-Dimensional Digital Construction Learning Environment
Authors: Chris Landorf, Stephen Ward
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This paper addresses a virtual environment approach to work integrated learning for students in construction-related disciplines. The virtual approach provides a safe and pedagogically rigorous environment where students can apply theoretical knowledge in a simulated real-world context. The paper describes the development of a 4-dimensional digital construction environment and associated learning activities funded by the Australian Office for Learning and Teaching. The environment was trialled with over 1,300 students and evaluated through questionnaires, observational studies and coursework analysis. Results demonstrate a positive impact on students’ technical learning and collaboration skills, but there is need for further research in relation to critical thinking skills and work-readiness.
Keywords: Architectural education, construction industry, digital learning environments, immersive learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10103204 Topological Queries on Graph-structured XML Data: Models and Implementations
Authors: Hongzhi Wang, Jianzhong Li, Jizhou Luo
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In many applications, data is in graph structure, which can be naturally represented as graph-structured XML. Existing queries defined on tree-structured and graph-structured XML data mainly focus on subgraph matching, which can not cover all the requirements of querying on graph. In this paper, a new kind of queries, topological query on graph-structured XML is presented. This kind of queries consider not only the structure of subgraph but also the topological relationship between subgraphs. With existing subgraph query processing algorithms, efficient algorithms for topological query processing are designed. Experimental results show the efficiency of implementation algorithms.Keywords: XML, Graph Structure, Topological query.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14143203 Improved Algorithms for Construction of Interface Agent Interaction Model
Authors: Huynh Quyet Thang, Le Hai Quan
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Interaction Model plays an important role in Modelbased Intelligent Interface Agent Architecture for developing Intelligent User Interface. In this paper we are presenting some improvements in the algorithms for development interaction model of interface agent including: the action segmentation algorithm, the action pair selection algorithm, the final action pair selection algorithm, the interaction graph construction algorithm and the probability calculation algorithm. The analysis of the algorithms also presented. At the end of this paper, we introduce an experimental program called “Personal Transfer System".Keywords: interface agent, interaction model, user model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21963202 Collaborative Online Learning for Lecturers
Authors: Lee Bih Ni, Emily Doreen Lee, Wee Hui Yean
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This paper was prepared to see the perceptions of online lectures regarding collaborative learning, in terms of how lecturers view online collaborative learning in the higher learning institution. The purpose of this study was conducted to determine the perceptions of online lectures about collaborative learning, especially how lecturers see online collaborative learning in the university. Adult learning education enhance collaborative learning culture with the target of involving learners in the learning process to make teaching and learning more effective and open at the university. This will finally make students learning that will assist each other. It is also to cut down the pressure of loneliness and isolation might felt among adult learners. Their ways in collaborative online was also determined. In this paper, researchers collect data using questionnaires instruments. The collected data were analyzed and interpreted. By analyzing the data, researchers report the results according the proof taken from the respondents. Results from the study, it is not only dependent on the lecturer but also a student to shape a good collaborative learning practice. Rational concepts and pattern to achieve these targets be clear right from the beginning and may be good seen by a number of proposals submitted and include how the higher learning institution has trained with ongoing lectures online. Advantages of online collaborative learning show that lecturers should be trained effectively. Studies have seen that the lecturer aware of online collaborative learning. This positive attitude will encourage the higher learning institution to continue to give the knowledge and skills required.
Keywords: Collaborative Online Learning, Lecturers’ Training.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24533201 Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals
Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty
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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient, but not the magnitude. A neural network with two hidden layers was then used to learn the coefficient magnitudes, along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.
Keywords: Quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1883200 A Learning Agent for Knowledge Extraction from an Active Semantic Network
Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller
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This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.
Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14943199 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants
Authors: S. Safi, A. Zeroual
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In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14483198 W3-Miner: Mining Weighted Frequent Subtree Patterns in a Collection of Trees
Authors: R. AliMohammadzadeh, M. Haghir Chehreghani, A. Zarnani, M. Rahgozar
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Mining frequent tree patterns have many useful applications in XML mining, bioinformatics, network routing, etc. Most of the frequent subtree mining algorithms (i.e. FREQT, TreeMiner and CMTreeMiner) use anti-monotone property in the phase of candidate subtree generation. However, none of these algorithms have verified the correctness of this property in tree structured data. In this research it is shown that anti-monotonicity does not generally hold, when using weighed support in tree pattern discovery. As a result, tree mining algorithms that are based on this property would probably miss some of the valid frequent subtree patterns in a collection of trees. In this paper, we investigate the correctness of anti-monotone property for the problem of weighted frequent subtree mining. In addition we propose W3-Miner, a new algorithm for full extraction of frequent subtrees. The experimental results confirm that W3-Miner finds some frequent subtrees that the previously proposed algorithms are not able to discover.Keywords: Semi-Structured Data Mining, Anti-Monotone Property, Trees.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13813197 Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process
Authors: H.Mohammadi Majd, M.Jalali Azizpour, A.V. Hoseini
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In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.Keywords: Back-propagation artificial neural network(BPANN), deep drawing, prediction, limiting drawing ratio (LDR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17273196 Medical Imaging Fusion: A Teaching-Learning Simulation Environment
Authors: Cristina M. R. Caridade, Ana Rita F. Morais
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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with health care facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool, developed in MATLAB using Graphical User Interface, for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing to view original images and fusion images, compare processed and original images, adjust parameters and save images. The tool proposed in an innovative teaching and learning environment, consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques, necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides a real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.
Keywords: Image fusion, image processing, teaching-learning simulation tool, biomedical engineering education.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 143195 Convergence Analysis of Training Two-Hidden-Layer Partially Over-Parameterized ReLU Networks via Gradient Descent
Authors: Zhifeng Kong
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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8963194 Learning Styles of University Students in Bangkok: The Characteristics and the Relevant Instructional Context
Authors: Chaiwat Tantarangsee
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The purposes of this study are 1) to identify learning styles of university students in Bangkok, and 2) to study the frequency of the relevant instructional context of the identified learning styles. Learning Styles employed in this study are those of Honey and Mumford, which include 1) Reflectors, 2) Theorists, 3) Pragmatists, and 4) Activists. The population comprises 1383 students and 5 lecturers. Research tools are 2 questionnaires – one used for identifying students- learning styles, and the other used for identifying the frequency of the relevant instructional context of the identified learning styles. The research findings reveal that 32.30 percent - are Activists, while 28.10 percent are Theorists, 20.10 are Reflectors, and 19.50 are Pragmatists. In terms of the relevant instructional context of the identified 4 learning styles, it is found that the frequency level of the instructional context is totally in high level. Moreover, 2 lists of the context being conducted most frequently are 'Lead'in activity to review background knowledge,- and 'Information retrieval report.' And these two activities serve the learning styles of theorists and activists. It is, therefore, suggested that more instructional context supporting the activists, the majority of the population, learning best by doing, as well as emotional learning situation should be added.Keywords: Instructional Context, Learning Styles, Learning Style Preference, and Learning Style Questionnaire.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18523193 Prediction the Limiting Drawing Ratio in Deep Drawing Process by Back Propagation Artificial Neural Network
Authors: H.Mohammadi Majd, M.Jalali Azizpour, M. Goodarzi
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In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.Keywords: BPANN, deep drawing, prediction, limiting drawingratio (LDR), Levenberg–Marquardt algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18543192 Virtual Learning Process Environment: Cohort Analytics for Learning and Learning Processes
Authors: Ayodeji Adesina, Derek Molloy
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Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.
Keywords: Business process management, cohort analytics, learning processes, virtual learning environment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28153191 A Rigid Point Set Registration of Remote Sensing Images Based on Genetic Algorithms and Hausdorff Distance
Authors: F. Meskine, N. Taleb, M. Chikr El-Mezouar, K. Kpalma, A. Almhdie
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Image registration is the process of establishing point by point correspondence between images obtained from a same scene. This process is very useful in remote sensing, medicine, cartography, computer vision, etc. Then, the task of registration is to place the data into a common reference frame by estimating the transformations between the data sets. In this work, we develop a rigid point registration method based on the application of genetic algorithms and Hausdorff distance. First, we extract the feature points from both images based on the algorithm of global and local curvature corner. After refining the feature points, we use Hausdorff distance as similarity measure between the two data sets and for optimizing the search space we use genetic algorithms to achieve high computation speed for its inertial parallel. The results show the efficiency of this method for registration of satellite images.Keywords: Feature extraction, Genetic algorithms, Hausdorff distance, Image registration, Point registration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19313190 Integration of Inter-Organisational Learning with Supply Chain Management: A Literature Review
Authors: Masimuddin Mohd Khaled
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This paper subsidises to the discussion of inter-organisational learning. This study has a main aim which is to examine the inter-organisational learning from a supply chain perspective. The integration and importance of supply chain with inter-organisational learning till date is discussed. The steps that are involved in the consideration of inter-organisational learning are looked throughout with emphasis done to supply chain management. The paper studies the impact of absorptive capacity, the supply chain orientation and design as well as discusses on fostering the inter-organisational learning.
Keywords: Absorptive Capacity, Inter-organisational Learning, Supply Chain Management, supply chain orientation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17573189 Understanding E-Learning Satisfaction in the Context of University Teachers
Authors: Anne M. Sørebø, Øystein Sørebø
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The present study was designed to test the influence of confirmed expectations, perceived usefulness and perceived competence on e-learning satisfaction among university teachers. A questionnaire was completed by 125 university teachers from 12 different universities in Norway. We found that 51% of the variance in university teachers- satisfaction with e-learning could be explained by the three proposed antecedents. Perceived usefulness seems to be the most important predictor of teachers- satisfaction with e-learning.Keywords: E-learning, User satisfaction, Teachers, IS success.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14233188 Satisfaction on English Language Learning with Online System
Authors: Suwaree Yordchim, Toby J. Gibbs
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The objective is to study the satisfaction on English with an online learning. Online learning system mainly consists of English lessons, exercises, tests, web boards, and supplementary lessons for language practice. The sample groups are 80 Thai students studying English for Business Communication, majoring in Hotel and Lodging Management. The data are analyzed by mean, standard deviation (S.D.) value from the questionnaires. The results were found that the most average of satisfaction on academic aspects are technological searching tool through E-learning system that support the students’ learning (4.51), knowledge evaluation on pre-post learning and teaching (4.45), and change for project selections according to their interest, subject contents including practice in the real situations (4.45), respectively.
Keywords: English Learning, Online System, Satisfaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26123187 Developing Learning in Organizations with Innovation Pedagogy Methods
Authors: T. Konst
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Most jobs include training and communication tasks, but often the people in these jobs lack pedagogical competences to plan, implement and assess learning. This paper aims to discuss how a learning approach called innovation pedagogy developed in higher education can be utilized for learning development in various organizations. The methods presented how to implement innovation pedagogy such as process consultation and train the trainer model can provide added value to develop pedagogical knowhow in organizations and thus support their internal learning and development.
Keywords: Innovation pedagogy, learning, organizational development, process consultation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1256