Abstract: The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represent another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.
Abstract: This work shows the methodology of application and the effectiveness of the Flipped Learning technique for Civil Engineering laboratory classes. It was experimented by some of the professors of the Department of Civil Engineering at Tecnológico de Monterrey while teaching their laboratory classes. A total of 28 videos were created. The videos primarily demonstrate instructions of the experimental practices other than the usage of tools and materials. The technique allowed the students to prepare for their classes in advance. A survey was conducted on the participating professors and students (semester of August-December 2019) to quantify the effectiveness of the Flipped Learning technique. The students reported it as an excellent way of improving their learning aptitude, including self-learning whereas, the professors felt it as an efficient technique for optimizing their class session, which also provided an extra slot for class-interaction. A comparison of grades was analyzed between the students of the traditional classes and with Flipped Learning. It did not distinguish the benefits of Flipped Learning. However, the positive responses from the students and the professors provide an impetus for continuing and promoting the Flipped Learning technique in future classes.
Abstract: Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.
Abstract: This research aimed to measure the impact of the use of a mobile learning (iTunes U) app for the development of metacognition skills delivered in the enrichment program offered to gifted students at the secondary level in Jeddah. The author targeted a group of students on an experimental scale to evaluate the achievement. The research sample consisted of a group of 38 gifted female students. The scale of evaluation of the metacognition skills used to measure the performance of students in the enrichment program was as follows: Satisfaction scale for the assessment of the technique used and the final product form after completion of the program. Appropriate statistical treatment used includes Paired Samples T-Test Cronbach’s alpha formula and eta squared formula. It was concluded in the results the difference of α≤ 0.05, which means the performance of students in the skills of metacognition in favor of using iTunes U. In light of the conclusion of the experiment, a number of recommendations and suggestions were present; the most important benefit of mobile learning applications is to provide enrichment programs for gifted students in the Kingdom of Saudi Arabia, as well as conducting further research on mobile learning and gifted student teaching.
Abstract: 2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.
Abstract: It is very common to observe, especially in Computer
Science studies that students have difficulties to correctly understand
how some mechanisms based on Artificial Intelligence work. In
addition, the scope and limitations of most of these mechanisms
are usually presented by professors only in a theoretical way,
which does not help students to understand them adequately. In this
work, we focus on the problems found when teaching Evolutionary
Algorithms (EAs), which imitate the principles of natural evolution,
as a method to solve parameter optimization problems. Although
this kind of algorithms can be very powerful to solve relatively
complex problems, students often have difficulties to understand
how they work, and how to apply them to solve problems in
real cases. In this paper, we present two interactive graphical
applications which have been specially designed with the aim of
making Evolutionary Algorithms easy to be understood by students.
Specifically, we present: (i) TSPS, an application able to solve the
”Traveling Salesman Problem”, and (ii) FotEvol, an application able
to reconstruct a given image by using Evolution Strategies. The
main objective is that students learn how these techniques can be
implemented, and the great possibilities they offer.
Abstract: This study was intended to provide a more efficient and convenient way for mobile users to enhance their knowledge about ASEAN countries. The researchers evaluated the utility of the developed crossword puzzle application and assessed the general usability of its user interface for its intended purpose and audience of users. The descriptive qualitative research method for the research design and the Mobile-D methodology was employed for the development of the software application output. With a generally favorable reception from its users, the researchers concluded that the iSEA Mobile Based Learning Application can be considered ready for general deployment and use. It was also concluded that additional studies can also be done to make a more complete assessment of the knowledge gained by its users before and after using the application.
Abstract: In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.
Abstract: Web applications are an integral part of modem life. They are mostly based upon the HyperText Markup Language (HTML). While HTML meets the basic needs, there are some shortcomings. For example, applications can cease to work once user goes offline, real-time updates may be lagging, and user interface can freeze on computationally intensive tasks. The latest language specification HTML5 attempts to rectify the situation with new tools and protocols. This paper studies the new Web Storage, Geolocation, Web Worker, Canvas, and Web Socket APIs, and presents applications to test their features and efficiencies.
Abstract: E-Learning enables the users to learn at anywhere at
any time. In E-Learning systems, authenticating the E-Learning user
has security issues. The usage of appropriate communication
networks for providing the internet connectivity for E-learning is
another challenge. WiMAX networks provide Broadband Wireless
Access through the Multicast Broadcast Service so these networks
can be most suitable for E-Learning applications. The authentication
of E-Learning user is vulnerable to session hijacking problems. The
repeated authentication of users can be done to overcome these
issues. In this paper, session based Profile Caching Authentication is
proposed. In this scheme, the credentials of E-Learning users can be
cached at authentication server during the initial authentication
through the appropriate subscriber station. The proposed cache based
authentication scheme performs fast authentication by using cached
user profile. Thus, the proposed authentication protocol reduces the
delay in repeated authentication to enhance the security in ELearning.
Abstract: The use of information technology in education have
changed not only the learners learning style but also the way they
taught, where nowadays learners are connected with diversity of
information sources with means of knowledge available everywhere.
The advantage of network wireless technologies and mobility
technologies used in the education and learning processes lead to
mobile learning as a new model of learning technology. Currently,
most of mobile learning applications are developed for the formal
education and learning environment. Despite the long history and
large amount of research on mobile learning and instruction design
model still there is a need of well-defined process in designing
mobile learning applications. Based on this situation, this paper
emphasizes on identifying instruction design phase’s considerations
and influencing factors in developing mobile learning application.
This set of instruction design steps includes analysis, design,
development, implementation, evaluation and continuous has been
built from a literature study, with focus on standards for learning,
mobile application software quality and guidelines. The effort is part
of an Omani-funded research project investigating the development,
adoption and dissemination of mobile learning in Oman.
Abstract: Guided by the theory of learning styles, this study is
based on the development of a multimedia learning application for
students with mastery learning style. The learning material was
developed by applying a graduated difficulty learning strategy.
Algebra was chosen as the learning topic for this application. The
effectiveness of this application in helping students learn is measured
by giving a pre- and post-test. The result shows that students who
learn using the learning material that matches their preferred learning
style perform better than the students with a non-personalized
learning material.
Abstract: Children today use computer based application in
various activities especially for learning and education. Many of
these tools and application such as the Computer Aided
Pronunciation Training (CAPT) systems enable children to explore
and experience them with little supervision from the adults. In order
for these tools and application to have maximum effect on the
children’s learning and education, it must be attractive to the children
to use them. This could be achieved with the proper user interface
(UI) design. As children grow, so do their ability, taste and
preferences. They interact differently with these applications as they
grow older. This study reviews several articles on how age factors
influence the UI design. The review focuses on age related abilities
such as cognitive, literacy, concentration and feedback requirement.
We have also evaluated few of existing CAPT systems and determine
the influence of age-based factors on the interface design.
Abstract: Learning is the acquisition of new mental schemata, knowledge, abilities and skills which can be used to solve problems potentially more successfully. The learning process is optimum when it is assisted and personalized. Learning is not a single activity, but should involve many possible activities to make learning become meaningful. Many e-learning applications provide facilities to support teaching and learning activities. One way to identify whether the e-learning system is being used by the learners is through the number of hits that can be obtained from the e-learning system's log data. However, we cannot rely solely to the number of hits in order to determine whether learning had occurred meaningfully. This is due to the fact that meaningful learning should engage five characteristics namely active, constructive, intentional, authentic and cooperative. This paper aims to analyze the e-learning activities that is meaningful to learning. By focusing on the meaningful learning characteristics, we match it to the corresponding Moodle e-learning activities. This analysis discovers the activities that have high impact to meaningful learning, as well as activities that are less meaningful. The high impact activities is given high weights since it become important to meaningful learning, while the low impact has less weight and said to be supportive e-learning activities. The result of this analysis helps us categorize which e-learning activities that are meaningful to learning and guide us to measure the effectiveness of e-learning usage.
Abstract: Mobile learning (m-learning) is a new method in teaching and learning process which combines technology of mobile device with learning materials. It can enhance student's engagement in learning activities and facilitate them to access the learning materials at anytime and anywhere. In Kolej Poly-Tech Mara (KPTM), this method is seen as an important effort in teaching practice and to improve student learning performance. The aim of this paper is to discuss the development of m-learning application called Mobile EEF Learning System (MEEFLS) to be implemented for Electric and Electronic Fundamentals course using Flash, XML (Extensible Markup Language) and J2ME (Java 2 micro edition). System Development Life Cycle (SDLC) was used as an application development approach. It has three modules in this application such as notes or course material, exercises and video. MEELFS development is seen as a tool or a pilot test for m-learning in KPTM.
Abstract: A Web-based learning tool, the Learn IN Context
(LINC) system, designed and being used in some institution-s
courses in mixed-mode learning, is presented in this paper. This
mode combines face-to-face and distance approaches to education.
LINC can achieve both collaborative and competitive learning. In
order to provide both learners and tutors with a more natural way to
interact with e-learning applications, a conversational interface has
been included in LINC. Hence, the components and essential features
of LINC+, the voice enhanced version of LINC, are described. We
report evaluation experiments of LINC/LINC+ in a real use context
of a computer programming course taught at the Université de
Moncton (Canada). The findings show that when the learning
material is delivered in the form of a collaborative and voice-enabled
presentation, the majority of learners seem to be satisfied with this
new media, and confirm that it does not negatively affect their
cognitive load.
Abstract: Within the healthcare system, training and continued professional development although essential, can be effected by cost and logistical restraints due to the nature of healthcare provision e.g employee shift patterns, access to expertise, cost factors in releasing staff to attend training etc. The use of multimedia technology for the development of e-learning applications is also a major cost consideration for healthcare management staff, and this type of media whether optical or on line requires careful planning in order to remain inclusive of all staff with potentially varied access to multimedia computing. This paper discusses a project in which the use of DVD authoring technology has been successfully implemented to meet the needs of distance learning and user considerations, and is based on film production techniques and reduced product turnaround deadlines.