Search results for: supervised learning algorithm

Authors: Mohssen Amiri

Abstract:

Lack of motivation among students in learning English can be considered as one of the main obstacles faced by parents, teachers and college/school administrators in Gulf countries and Iran. The question is why this problem still exists among EFL students’ despite of various new methodologies that colleges are implementing by native and non-native instructors. In the paper, it has been explained that why many students fail to know the basic knowledge and conversations of English language even after completing academic levels of colleges. In this study, the answers of all questions have been covered by introducing the concept of the psychology of learning and the importance of motivation which are the main discussions of this study. Additionally, the paper has illustrated that how psychology is the key of success in learning English and how it develops motivation and confidence dramatically among students especially on speaking skill. The study shows that psychology is 70% of success and 30% are the methods and materials that we implement to teach in the classroom. Therefore, this is the role of teachers to develop 70% of positive motivation and psychology among students. The approach of study is descriptive, and the focus will be on speaking skill.

Keywords: psychology, motivation, communication, learning

Procedia PDF Downloads 395

Authors: Elisabeth Eder

Abstract:

Memorizing music plays an important role for instrumentalists and has been researched very little so far. Almost every musician is confronted with memorizing music in the course of their musical career. For numerous competitions, examinations (e.g., at universities, music schools), solo performances, and the like, memorization is a requirement. Learners are often required to learn a piece by heart but are rarely given guidance on how to proceed. This was also confirmed by Eder's preliminary study to examine the topicality and relevance of the topic, in which 111 instrumentalists took part. The preliminary study revealed a great desire for more knowledge or information about learning strategies as well as a greater sense of security when performing by heart on stage through the use of learning strategies by those musicians who use learning strategies. Eder’s research focuses on learning strategies for memorizing music. As part of a large-scale empirical study – an online questionnaire translated into 10 languages was used to conduct the study – 1091 musicians from 64 different countries described how they memorize. The participants in the study also evaluated their learning strategies and justified their choice in terms of their degree of effectiveness. Based on the study and pedagogical literature, 100 learning strategies were identified and categorized; the strategies were examined with regard to their effectiveness, and instrument-specific, age-specific, country-specific, gender-specific, and education-related differences and similarities concerning the choice of learning strategies were investigated. Her research also deals with forms and models of memory and how music-related information can be stored and retrieved and also forgotten again. A further part is devoted to the possibilities that teachers and learners have to support the process of memorization independently of learning strategies. The findings resulting from Elisabeth Eder's research should enable musicians and instrumental students to memorize faster and more confidently.

Keywords: memorizing music, learning strategies, empirical study, effectiveness of strategies

Procedia PDF Downloads 42

Authors: Ya-Hui Lee, Ching-Yi Lu

Abstract:

Taiwan will become an aging society in 2018. The method to face the challenges related to the aging population has become an important topic. Purpose: This study aims to understand the future preparation of middle-age and older adults, and how they prepared themselves to face the problems of aging, and how they took actions to plan and cope with their future life. Moreover, how did they generate the process of learning action, so that they would be able to live a more active and meaningful life when they entered into their older age? Method: We conducted semi-structure interviews with 10 middle-aged and older adults who had taken actions to prepare for their future. We examined the interviewees’ consciousness and learning actions in their future preparation. Preliminary Results: 1. The triggering factors of the interviewees’ consciousness to prepare for the future included: family events, the desire to maintain active social lives after retirement, the continuation of the interviewees’ professional careers after retirement, and the aspiration for participation in volunteer services. 2. 'Health problems' and 'economic security' were issued of the utmost concern for the interviewees’ future. However, they would transform these worries to learning actions, comprising of active participation in learning, finding relevant information through learning; thus, accumulating more resources to cope with their future needs.

Keywords: middle-age and older adults, preparing for future, older adult learning

Procedia PDF Downloads 230

Authors: Susan Ka Yee Chow

Abstract:

The Coronavirus disease (COVID-19) reached Hong Kong in 2019 resulting in epidemic in late January 2020. Considering the epidemic development, tertiary institutions made announcements that all on-campus classes were suspended since 01/29/2020. In Tung Wah College, e-learning was adopted in all courses for all programmes. For the undergraduate nursing students, the contact hours and curriculum are bounded by the Nursing Council of Hong Kong to ensure core competence after graduation. Unlike the usual e-learning where students are allowed having flexibility of time and place in their learning, real time learning mode using Blackboard was used to mimic the actual classroom learning environment. Students were required to attend classes according to the timetable using online platform. For lectures, voice over PowerPoint file was the initial step for mass lecturing. Real time lecture was then adopted to improve interactions between teacher and students. Post-lecture quizzes were developed to monitor the effectiveness of lecture delivery. The seminars and tutorials were conducted using real time mode where students were separated into small groups with interactive discussions with teacher within the group. Live time demonstrations were conducted during laboratory sessions. All teaching sessions were audio/video recorded for students’ referral. The assessments including seminar presentation and debate were retained. The learning mode creates an atmosphere for students to display the visual, audio and written works in a non-threatening atmosphere. Other students could comment using text or direct voice as they desired. Real time online learning is the pedagogy to replace classroom contacts in the emergent and unforeseeable circumstances. The learning pace and interaction between students and students with teacher are maintained. The learning mode has the advantage of creating an effective and beneficial learning experience.

Keywords: e-learning, nursing curriculum, real time mode, teaching and learning

Procedia PDF Downloads 116

Authors: Moheb R. Girgis, Tarek M. Mahmoud, Bahgat A. Abdullatif, Ahmed M. Rabie

Abstract:

Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions.

Keywords: wireless mesh networks, genetic algorithms, simulated annealing, topology design

Procedia PDF Downloads 459

Authors: Chika Ethel Esege

Abstract:

Electronic learning is learning facilitated by technology which has basically altered approaches globally, including the field of education. This trend is compelling educators to focus on approaches that improve classroom practices in order to enhance students’ learning and participation in a global digital society. However, e-learning is not fully utilized across subject disciplines particularly in the field of humanities, in the context of Nigerian secondary education. This study focused on the use of e-learning to enhance the development of digital skills, particularly, collaboration and communication in secondary school students in Nigeria. The study adopted an ‘action research’ involving 210 students and 7 teachers, who utilised the e-learning platform designed by the researcher for the survey. Mixed methods- qualitative and quantitative- were used for data collection including questionnaire, observation, interview, and analysis of statutory documents. The data were presented using frequency counts for questionnaire responses and figures of screenshots for learning tasks. The VOD Burner software was also used to analyse interviews and video recordings. The study showed that the students acquired collaboration and communication skills through e-learning intervention lesson, and demonstrated satisfaction with this approach. However, the study further revealed that the traditional teaching approach could not provide digital education or develop the digital skills of the students. Based on these findings, recommendations were made that the Nigerian Government should incorporate digital content across subject disciplines into secondary school education curricular and provide adequate infrastructure in order to enable educators to adopt relevant approaches necessary for the enhancement of students’ learning especially in a technologically evolving and advancing world.

Keywords: developing collaboration and communication skills, electronic learning, improving classroom teaching, secondary schools in Nigeria

Procedia PDF Downloads 134

Authors: Hisyam Hidayatullah

Abstract:

Utilization game on a lesson needs to be done in order to provide proper motoric learning model to improve students' skills. Approach to the game, as one of the models of a motoric learning, is intended to improve student learning outcomes math trigonometry materials generally that prioritize a Memory or rote. The purpose of this study is producting innovation to improve a cognitive abilities of students in the field, to improve student performance, and ultimately to improve student understanding in determining a value of trigonometry in various quadrants, and it apply a approach to the game Domino "Cassava H154M" who is adopted from cassava game and it has made total revised in cassava content. The game is divided into 3 sessions: sine cassava, cosine cassava and cassava tangent. Researchers using action of research method, which consists of several stages such as: planning, implementation, observation, reporting and evaluation. Researchers found that a game approaches can improve student learning outcomes, enhance students' creativity in terms of their motoric learning, and creating a supportive learning environment.

Keywords: cassava "H154M", motoric, value of trigonometry, quadrant

Procedia PDF Downloads 327

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

Abstract:

The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

Procedia PDF Downloads 71

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

Abstract:

Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 83

Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

Abstract:

Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

Procedia PDF Downloads 124

Authors: Mehdi Rostamzadeh

Abstract:

Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

Procedia PDF Downloads 275

Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

Procedia PDF Downloads 163

Authors: Hadj Abd El Kader Benghenia, Fethi Bereksi Reguig

Abstract:

In clinical medicine, blood pressure, raised blood hemodynamic monitoring is rich pathophysiological information of cardiovascular system, of course described through factors such as: blood volume, arterial compliance and peripheral resistance. In this work, we are interested in analyzing these signals to propose a detection algorithm to delineate the different sequences and especially systolic blood pressure (SBP), diastolic blood pressure (DBP), and the wave and dicrotic to do their analysis in order to extract the cardiovascular parameters.

Keywords: blood pressure, SBP, DBP, detection algorithm

Procedia PDF Downloads 439

Authors: Salina Budin, Nor Liawati Abu Othman, Shaira Ismail

Abstract:

This study attempts to determine kinesthetic, verbal and visual intelligences among mechanical engineering undergraduate students and explores any probable relation with students’ learning styles and academic performance. The questionnaire used in this study is based on Howard Gardner’s multiple intelligences theory comprising of five elements of learning style; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering. Additional questions on students’ perception of learning styles and their academic performance are included in the questionnaire. The results show that one third of the students are strongly dominant in the kinesthetic intelligent (33%), followed by a combination of kinesthetic and visual intelligences (29%) and 21% are strongly dominant in all three types of intelligences. There is a statistically significant correlation between kinesthetic, verbal and visual intelligences and students learning styles and academic performances. The ANOVA analysis supports that there is a significant relationship between academic performances and level of kinesthetic, verbal and visual intelligences. In addition, it has also proven a remarkable relationship between academic performances and kinesthetic, verbal and visual learning styles amongst the male and female students. Thus, it can be concluded that, academic achievements can be enhanced by understanding as well as capitalizing the students’ types of intelligences and learning styles.

Keywords: kinesthetic intelligent, verbal intelligent, visual intelligent, learning style, academic performances

Procedia PDF Downloads 302

Authors: Danielle Guerra, Marden Silva

Abstract:

The use of active methodologies in the teaching of English has been widely encouraged recently, due to its potential to create propitious conditions for the learners to develop autonomy and studying skills that tend to keep them motivated throughout the learning process. The constant use of technology by the students makes it possible to implement strategies such as blended learning, which blends regular classes with online instruction and practice. (Horn and Staker, 2015) For that reason, the aim of this study was to implement the blended approach in a High School second-grade English class in Brazil, in order to analyze the impacts of this methodology on the students' autonomy. The teacher's role was that of a mediator, being responsible for selecting the best resources for students to study with, and also for helping them with questions when necessary. The results show that taking learner characteristics and learning experiences into account and allowing the students to follow their learning paths at their own pace was crucial to promoting engagement that led to the desired outcomes. In conclusion, the research shows that blended learning is a helpful strategy to foster autonomy and promote motivation in EFL students.

Keywords: active methodologies, autonomy, blended learning, motivation

Procedia PDF Downloads 210

Authors: Saeed Poormoaied, Zumbul Atan

Abstract:

Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.

Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.

Procedia PDF Downloads 141

Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

Abstract:

This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

Procedia PDF Downloads 439

Authors: Jefferson S. Galanza, Jewel An Mischelle R.Camcam, Alyssa Karryl C. Co, Stephanie P. De Guzman, Jet Jet K. Dongui-is, Rodolfo Dane C. Frias, Ovelle C. Jueco, Harvey L. Matbagan, Victoria Luzette T. Rillon, Christelle Romyna H. Saruca, Jeanette Roma M. Villasper

Abstract:

Background: Amidst numerous studies conducted on learning styles of students from a variety of courses, levels and school, a recent study recommended a great need for research on learning styles of student nurses. Moreover, related literatures have not been found exploring both the learning and teaching style of student nurses. Aims: The study aimed to determine the learning and teaching styles of student nurses and if there is an association between them. It also intended to discover whether student nurses are unimodal or multimodal in their styles and identified which faculty teaching style affords maximum outcome for student’s learning styles. Methods: Quantitative Descriptive-Correlational design was used. Participants were randomly selected 312 student nurses at School of Nursing X, Baguio City, Philippines. The questionnaire utilized a modified version of an adopted tool from Fleming’s VARK learning style version 7.2 (Visual, Auditory, Reader/Writer, Kinaesthetic) and Grasha’s teaching styles (Formal Authority, Demonstrator, Facilitator, Delegator). SPSS 19 was used for statistical treatment of data, where Chi square was used for the correlation of unimodal learning and teaching styles. Results/Finding: Majority of student nurses’ learning style is Kinesthetic and their teaching style is Demonstrator, which was also found to be significantly associated. Moreover, 8 out of 10 students are Unimodal in their learning and teaching modalities. In general, their preferred faculty teaching style is similar to their teaching style, which supports the concept, that teachers teach the way they learn. Conclusion: Study concludes that student nurses’ learning styles and teaching styles are varied, which exemplifies the uniqueness of every learner.This diversity in styles provided more evidence that a variety of mode of teaching and learning should be used by faculty and students to increase learning outcome and academic achievement. Recommendation: Future studies could be carried out in various schools of nursing utilizing faculty as respondents. Conduct assessment of learning style at the onset of classes/clinical placements so that faculty will become aware of the diversity of learners leading them to deliver diverse teaching methods.

Keywords: learning, learning styles, teaching styles, student nurses

Procedia PDF Downloads 536

Authors: Rabia Aslam

Abstract:

Overwhelming evidence from all around the world suggests that high-quality teacher professional development facilitates the improvement of teaching practices which in turn could improve student learning outcomes. The new Continuous Professional Development (CPD) model for primary school teachers in Punjab uses a blended approach in which pedagogical content knowledge is delivered through technology (high-quality instructional videos and lesson plans delivered to school tablets or mobile phones) with face-to-face support by Assistant Education Officers (AEOs). The model also develops Communities of Practice operationalized through formal meetings led by the AEOs and informal interactions through social media groups to provide opportunities for teachers to engage with each other and share their ideas, reflect on learning, and come up with solutions to issues they experience. Using Kirkpatrick’s 4 levels of the learning evaluation model, this paper investigates how school tablets and teacher mobile phones may act as transformational cultural tools to potentially expand perceptions and access to teaching and learning resources and explore some of the affordances of social media (Facebook, WhatsApp groups) in learning in an informal context. The results will be used to inform policy-level decisions on what shape could CPD of all teachers take in the context of a developing country like Pakistan.

Keywords: CPD, teaching & learning, blended learning, learning technologies

Procedia PDF Downloads 86

Authors: Srinidhi. A, Naveed Ahmed, Twinkle Hareendran, Vriksha Prakash

Abstract:

This work reviews some of the advanced image processing techniques for deep learning applications. Object detection by template matching, image denoising, edge detection, and super-resolution modelling are but a few of the tasks. The paper looks in into great detail, given that such tasks are crucial preprocessing steps that increase the quality and usability of image datasets in subsequent deep learning tasks. We review some of the methods for the assessment of image quality, more specifically sharpness, which is crucial to ensure a robust performance of models. Further, we will discuss the development of deep learning models specific to facial emotion detection, age classification, and gender classification, which essentially includes the preprocessing techniques interrelated with model performance. Conclusions from this study pinpoint the best practices in the preparation of image datasets, targeting the best trade-off between computational efficiency and retaining important image features critical for effective training of deep learning models.

Keywords: image processing, machine learning applications, template matching, emotion detection

Procedia PDF Downloads 20

Authors: Amira Abdulrazzaq

Abstract:

This paper is studying the opinion of faculty members and students about the future of education (e-learning) at the University of Bahrain. Through quantitative analysis a distribution of two surveys, one targeting students of IT College, and College of Arts and the other targeting Faculty members of both Colleges. Through the above survey, the paper measures the following factors: awareness and acceptance, satisfaction, usability, and usefulness. Results indicate positive reactions of all above factors.

Keywords: e-learning, education, moodle, WebCT

Procedia PDF Downloads 467

Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

Abstract:

Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

Procedia PDF Downloads 514

Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

Abstract:

Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

Procedia PDF Downloads 224

Authors: Adrian Florin Busu

Abstract:

The communicative approach, or communicative language teaching, used for enhancing communicative skills in students in automatics is a modern teaching approach based on the concept of learning a language through having to communicate real meaning. In the communicative approach, real communication is both the objective of learning and the means through which it takes place. This approach was initiated during the 1970’s and quickly became prominent, as it proposed an alternative to the previous systems-oriented approaches. In other words, instead of focusing on the acquisition of grammar and vocabulary, the communicative approach aims at developing students’ competence to communicate in the target language with an enhanced focus on real-life situations. To put it in an nutshell, CLT considers using the language to be just as important as actually learning the language.

Keywords: communication, approach, objective, learning

Procedia PDF Downloads 161

Authors: Malathi Balakrishnan, Gananathan M. Nadarajah, Saraswathy Vellasamy, Evelyn Gnanam William George

Abstract:

The purpose of the study is to explore how the fun game-learning approach enhances teacher trainers’ higher order thinking skills. Two-day fun filled fun game learning-approach was introduced to teacher trainers as a Continuous Professional Development Program (CPD). 26 teacher trainers participated in this Transformation of Teaching and Learning Fun Way Program, organized by Institute of Teacher Education Malaysia. Qualitative research technique was adopted as the researchers observed the participants’ higher order thinking skills developed during the program. Data were collected from observational checklist; interview transcriptions of four participants and participants’ reflection notes. All the data were later analyzed with NVivo data analysis process. The finding of this study presented five main themes, which are critical thinking, hands on activities, creating, application and use of technology. The studies showed that the teacher trainers’ higher order thinking skills were enhanced after the two-day CPD program. Therefore, Institute of Teacher Education will have more success using the fun way game-learning approach to develop higher order thinking skills among its teacher trainers who can implement these skills to their trainee teachers in future. This study also added knowledge to Constructivism learning theory, which will further highlight the prominence of the fun way learning approach to enhance higher order thinking skills.

Keywords: constructivism, game-learning approach, higher order thinking skill, teacher trainer

Procedia PDF Downloads 295

Authors: Arshad Mehmood Ch, Riaz Ahmad, Imran Ali Ch, Waqas Durrani

Abstract:

This study deals with the application of Ant Colony Optimization (ACO) approach to solve no-wait flowshop scheduling problem (NW-FSSP). ACO algorithm so developed has been coded on Matlab computer application. The paper covers detailed steps to apply ACO and focuses on judging the strength of ACO in relation to other solution techniques previously applied to solve no-wait flowshop problem. The general purpose approach was able to find reasonably accurate solutions for almost all the problems under consideration and was able to handle a fairly large spectrum of problems with far reduced CPU effort. Careful scrutiny of the results reveals that the algorithm presented results better than other approaches like Genetic algorithm and Tabu Search heuristics etc; earlier applied to solve NW-FSSP data sets.

Keywords: no-wait, flowshop, scheduling, ant colony optimization (ACO), makespan

Procedia PDF Downloads 436

Authors: E. Behmanesh, J. Pannek

Abstract:

Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

Procedia PDF Downloads 191

Authors: Orit Baruth, Anat Cohen

Abstract:

Online courses have become common in many learning programs and various learning environments, particularly in higher education. Social distancing forced in response to the COVID-19 pandemic has increased the demand for these courses. Yet, despite the frequency of use, online learning is not free of limitations and may not suit all learners. Hence, the growth of online learning alongside with learners' diversity raises the question: is online learning, as it currently offered, meets the needs of each learner? Fortunately, today's technology allows to produce tailored learning platforms, namely, personalization. Personality influences learner's satisfaction and therefore has a significant impact on learning effectiveness. A better understanding of personality can lead to a greater appreciation of learning needs, as well to assists educators ensure that an optimal learning environment is provided. In the context of online learning and personality, the research on learning design according to personality traits is lacking. This study explores the relations between personality traits (using the 'Big-five' model) and students' satisfaction with five techno-pedagogical learning solutions (TPLS): discussion groups, digital books, online assignments, surveys/polls, and media, in order to provide an online learning process to students' satisfaction. Satisfaction level and personality identification of 108 students who participated in a fully online learning course at a large, accredited university were measured. Cluster analysis methods (k-mean) were applied to identify learners’ clusters according to their personality traits. Correlation analysis was performed to examine the relations between the obtained clusters and satisfaction with the offered TPLS. Findings suggest that learners associated with the 'Neurotic' cluster showed low satisfaction with all TPLS compared to learners associated with the 'Non-neurotics' cluster. learners associated with the 'Consciences' cluster were satisfied with all TPLS except discussion groups, and those in the 'Open-Extroverts' cluster were satisfied with assignments and media. All clusters except 'Neurotic' were highly satisfied with the online course in general. According to the findings, dividing learners into four clusters based on personality traits may help define tailor learning paths for them, combining various TPLS to increase their satisfaction. As personality has a set of traits, several TPLS may be offered in each learning path. For the neurotics, however, an extended selection may suit more, or alternatively offering them the TPLS they less dislike. Study findings clearly indicate that personality plays a significant role in a learner's satisfaction level. Consequently, personality traits should be considered when designing personalized learning activities. The current research seeks to bridge the theoretical gap in this specific research area. Establishing the assumption that different personalities need different learning solutions may contribute towards a better design of online courses, leaving no learner behind, whether he\ she likes online learning or not, since different personalities need different learning solutions.

Keywords: online learning, personality traits, personalization, techno-pedagogical learning solutions

Procedia PDF Downloads 105

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Abstract:

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 168

Authors: María-Dolores Afonso-Suárez, Nayra Pumar-Carreras, Juan Ruiz-Alzola

Abstract:

This research addresses the use of an e-Learning creation methodology for learning objects. Throughout the process, indicators are being gathered, to determine if it responds to the main objectives of an engineering discipline. These parameters will also indicate if it is necessary to review the creation cycle and readjust any phase. Within the project developed for this study, apart from the use of structured methods, there has been a central objective: the establishment of a learning atmosphere. A place where all the professionals involved are able to collaborate, plan, solve problems and determine guides to follow in order to develop creative and innovative solutions. It has been outlined as a blended learning program with an assessment plan that proposes face to face lessons, coaching, collaboration, multimedia and web based learning objects as well as support resources. The project has been drawn as a long term task, the pilot teaching actions designed provide the preliminary results object of study. This methodology is been used in the creation of learning content for the African countries of Senegal, Mauritania and Cape Verde. It has been developed within the framework of the MACbioIDi, an Interreg European project for the International cooperation and development. The educational area of this project is focused in the training and advice of professionals of the medicine as well as engineers in the use of applications of medical imaging technology, specifically the 3DSlicer application and the Open Anatomy Browser.

Keywords: teaching contents engineering, e-learning, blended learning, international cooperation, 3dslicer, open anatomy browser

Procedia PDF Downloads 173