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In distance learning platforms the training is adapted to each learner's cognitive profile. It combined between the individualization of course units according to each learner and the collaboration between learners themselves and tutors. However, teachers no longer have direct contact with learners that allow them to assess their evolution. Hence the importance of integrating the tracking of learners...
This research is an attempt to identify the impact of effectiveness of the maritime simulator training program on different factors of needs and interest of the program. Model is developed to understand the impact. Data was collected from the course participants attending various simulator based training programmes from three training centers. Confirmatory factor analysis was employed to examine the...
This paper introduces a set of devices for training and evaluation on repair electric fault of lathe machine based on the wireless network. These devices is a network structure which consists of one principle computer and some slaves, that is to say that it contains single master and multi-followers. It employs a wireless digital transfer method as its communication mode. It can manage to complete...
Indonesia has high mortality caused by cardiovascular diseases. To minimize the mortality, we build a tele-ecg system for heart diseases early detection and monitoring. In this research, the tele-ecg system was enhanced using Hadoop framework, in order to deal with big data processing. The system was build on cluster computer with 4 nodes. The server is able to handle 60 requests at the same time...
Imagine you are an operating room nurse. Could training with virtual human teammates empower you to speak up to a bullying teammate? Could virtual teammates change the way you speak as to reduce errors? How about learn new patient safety policies or efficiently transfer care?In this talk, we will explore the emerging area of using virtual humans to subtly influence healthcare teams' teamwork and communication...
It is important to provide detailed and instructive feedback in computer assisted pronunciation training (CAPT) system. However the feedback is limited to the accuracy of the erroneous tendency detection. This paper proposed to apply senone log-likelihood ratio based articulatory features (AFs) to improve pronunciation erroneous tendency (PET) detection performance. Also the feedback information of...
Commercial/Military-Off-The-Shelf (COTS/MOTS) Computer Generated Forces (CGF) packages are widely used in modeling and simulation for training purposes. Conventional CGF packages often include artificial intelligence (AI) interfaces, but lack behavior generation and other adaptive capabilities. We believe Machine Learning (ML) techniques can be beneficial to the behavior modeling process, yet such...
This paper contributes to the ongoing efforts in the cybersecurity community to strengthen cyber workforce development by providing an overview of key gaps and proposing practical education strategies. Leveraging documented incidents from defense, industry, and academia and the rest of the United States government, we identify emerging cyber-education opportunities highlighting human-centric elements...
This study reviews the current situation of Self-Access Media (SAM) and independent learning by looking at Self-Access Learning Materials (SALM) available for Computer Graphics (CG) artists. Since past two decades huge progress in software, hardware, Graphical User Interface (GUI) and World Wide Web (WWW) has enabled many individuals to develop an independent learning attitude by using SALM (mostly...
Motor imagery brain-computer interfaces (MIBCI) use hand or foot MI to control computers. However, MIBCI control accuracy is low. Previously, we determined that using max power in the mu band method, i.e., the peak trace method (PTM), improves event-related desynchronization (ERD) detection accuracy. Control accuracy may be improved by improving ERD detection accuracy in an MIBCI. In this study, we...
This paper provides an example of using genetic programming for engendering computational creativity in computer generated forces, i.e. simulated entities used to represent own, opponent and neutral forces in military training or decision support applications. We envision that applying computational creativity in the development of computer generated forces may not only reduce development costs but...
This paper presents a data-driven approach towards the modeling of agent behaviors in a full-fledged, commercial off-the-shelf simulation milieu for tactical military training. The modeling approach employs machine learning to identify behavioral rules and patterns in data. Potential advantages of this approach are that it may improve modeling efficiency and, perhaps more importantly, increase the...
Convolutional Neural Networks (CNN) are on the forefront of accurate character recognition. This paper explores CNNs at their maximum capacity by implementing the use of large datasets. We show a near-perfect performance by using a dataset of about 820,000 real samples of isolated handwritten digits, much larger than the conventional MNIST database. In addition, we report a near-perfect performance...
Axial and radial power peaking factors (Fq, Fah) were estimated in Chashma Nuclear Power Plant Unit-1 (C-1) core using artificial Neural Network Technique (ANNT). Position of T4 control bank, axial offsets in four quadrants and quadrant power tilt ratios were taken as input variables in neural network designing. Power Peaking Factors (PPF) were calculated using computer codes FCXS, TWODFD and 3D-NB-2P...
This paper tries to present authors vision on how to transmit knowledge to the current generation of students, using technologies and new methods, so that the future graduates knows how to think and to solve problems, how to propose and implement projects, not only to read and memories what they read without understanding anything. More than that authors try to suggest ideas to help future graduates...
Many theoretical and empirical studies that analyze the factors associated to academic achievement identify gender as a highly significant element. Within the assessment of information literacy skills, the effect of gender seems apparent. However, the contextual nature of gender makes it difficult for the results of the studies to result in specific improvements and innovations in the schools. The...
Decision trees are common algorithms in machine learning. Traditionally, these algorithms make trees recursively and at each step, they inspect data to induce the part of the tree. However decision trees are famous for their instability and high variance in error. In this paper a solution which adds error correction rule to a traditional decision tree algorithm is examined. In fact an algorithm which...
The purpose of this work is to evaluate possible minimisation of the time needed for expansion of the scope of a CNN (convolutional neural network) classifier without the need to fully re-train it. We investigate the effects of applying k-NN (k-Nearest Neighbours) based classification and transfer learning (via fine-tuning) for the purpose of adding new classes to an existing deep convolutional neural...
Information and communication technologies play an increasingly important role in society, in the sense that all areas and professions make use of digital resources. The school can not be brushed off this reality, aim to create full subjects and integrated in society today. Educational software can be used very early in the education of children, but they must be carefully and monitoring. This article...
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