CALL AND COOPERATIVE LEARNING: A SOLUTION TO DEVELOP STUDENTS‟ LISTENING ABILITY

OpenAIRE

Delsa Miranty

2017-01-01

This paper aims to provide some ideas both for English teachers and target learners about how to apply CALL and Cooperative Learning as the solution to develop students‘ listening activities in the classroom. Since teachers need to understand about students‘ needs, background, age and expectations when they learn English as the foreign language in the classroom. Therefore, the English teacher should provide environment which facilitates the children to have fun di the teaching learning proces...

Evaluation of Software Quality to Improve Application Performance Using Mc Call Model

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Inda D Lestantri

2018-04-01

Full Text Available The existence of software should have more value to improve the performance of the organization in addition to having the primary function to automate. Before being implemented in an operational environment, software must pass the test gradually to ensure that the software is functioning properly, meeting user needs and providing convenience for users to use it. This test is performed on a web-based application, by taking a test case in an e-SAP application. E-SAP is an application used to monitor teaching and learning activities used by a university in Jakarta. To measure software quality, testing can be done on users randomly. The user samples selected in this test are users with an age range of 18 years old up to 25 years, background information technology. This test was conducted on 30 respondents. This test is done by using Mc Call model. Model of testing Mc Call consists of 11 dimensions are grouped into 3 categories. This paper describes the testing with reference to the category of product operation, which includes 5 dimensions. The dimensions of testing performed include the dimensions of correctness, usability, efficiency, reliability, and integrity. This paper discusses testing on each dimension to measure software quality as an effort to improve performance. The result of research is e-SAP application has good quality with product operation value equal to 85.09%. This indicates that the e-SAP application has a great quality, so this application deserves to be examined in the next stage on the operational environment.

Help Options in CALL: A Systematic Review

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Cardenas-Claros, Monica S.; Gruba, Paul A.

2009-01-01

This paper is a systematic review of research investigating help options in the different language skills in computer-assisted language learning (CALL). In this review, emerging themes along with is-sues affecting help option research are identified and discussed. We argue that help options in CALL are application resources that do not only seem…

Sustainability in CALL Learning Environments: A Systemic Functional Grammar Approach

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Peter McDonald

2014-09-01

Full Text Available This research aims to define a sustainable resource in Computer-Assisted Language Learning (CALL. In order for a CALL resource to be sustainable it must work within existing educational curricula. This feature is a necessary prerequisite of sustainability because, despite the potential for educational change that digitalization has offered since the nineteen nineties, curricula in traditional educational institutions have not fundamentally changed, even as we move from a pre-digital society towards a digital society. Curricula have failed to incorporate CALL resources because no agreed-upon pedagogical language enables teachers to discuss CALL classroom practices. Systemic Functional Grammar (SFG can help to provide this language and bridge the gap between the needs of the curriculum and the potentiality of CALL-based resources. This paper will outline how SFG principles can be used to create a pedagogical language for CALL and it will give practical examples of how this language can be used to create sustainable resources in classroom contexts.

Attitudes of Jordanian Undergraduate Students towards Using Computer Assisted Language Learning (CALL)

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Saeed, Farah Jamal Abed Alrazeq; Al-Zayed, Norma Nawaf

2018-01-01

The study aimed at investigating the attitudes of Jordanian undergraduate students towards using computer assisted-language learning (CALL) and its effectiveness in the process of learning the English language. In order to fulfill the study's objective, the researchers used a questionnaire to collect data, followed-up with semi-structured…

RAPPORT-BUILDING THROUGH CALL IN TEACHING CHINESE AS A FOREIGN LANGUAGE: AN EXPLORATORY STUDY

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Wenying Jiang

2005-05-01

Full Text Available Technological advances have brought about the ever-increasing utilisation of computer-assisted language learning (CALL media in the learning of a second language (L2. Computer-mediated communication, for example, provides a practical means for extending the learning of spoken language, a challenging process in tonal languages such as Chinese, beyond the realms of the classroom. In order to effectively improve spoken language competency, however, CALL applications must also reproduce the social interaction that lies at the heart of language learning and language use. This study draws on data obtained from the utilisation of CALL in the learning of L2 Chinese to explore whether this medium can be used to extend opportunities for rapport-building in language teaching beyond the face-to-face interaction of the classroom. Rapport's importance lies in its potential to enhance learning, motivate learners, and reduce learner anxiety. To date, CALL's potential in relation to this facet of social interaction remains a neglected area of research. The results of this exploratory study suggest that CALL may help foster learner-teacher rapport and that scaffolding, such as strategically composing rapport-fostering questions in sound-files, is conducive to this outcome. The study provides an instruction model for this application of CALL.

APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN COMPUTER AIDED LANGUAGE LEARNING

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I. B. Tampel

2013-01-01

Full Text Available The article deals with the various ways of application for automatic speech recognition, Text-to-Speech technology, pronunciation and communication skills training, vocabulary check of the taught person, audition skills training in computer aided language learning (CALL-system. In spite of some constraints such technologies application is effective both for education problems simplification and for comfort growth of the system application.

Improving student learning in calculus through applications

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Young, C. Y.; Georgiopoulos, M.; Hagen, S. C.; Geiger, C. L.; Dagley-Falls, M. A.; Islas, A. L.; Ramsey, P. J.; Lancey, P. M.; Straney, R. A.; Forde, D. S.; Bradbury, E. E.

2011-07-01

Nationally only 40% of the incoming freshmen Science, Technology, Engineering and Mathematics (STEM) majors are successful in earning a STEM degree. The University of Central Florida (UCF) EXCEL programme is a National Science Foundation funded STEM Talent Expansion Programme whose goal is to increase the number of UCF STEM graduates. One of the key requirements for STEM majors is a strong foundation in Calculus. To improve student learning in calculus, the EXCEL programme developed two special courses at the freshman level called Applications of Calculus I (Apps I) and Applications of Calculus II (Apps II). Apps I and II are one-credit classes that are co-requisites for Calculus I and II. These classes are teams taught by science and engineering professors whose goal is to demonstrate to students where the calculus topics they are learning appear in upper level science and engineering classes as well as how faculty use calculus in their STEM research programmes. This article outlines the process used in producing the educational materials for the Apps I and II courses, and it also discusses the assessment results pertaining to this specific EXCEL activity. Pre- and post-tests conducted with experimental and control groups indicate significant improvement in student learning in Calculus II as a direct result of the application courses.

CALL AND COOPERATIVE LEARNING: A SOLUTION TO DEVELOP STUDENTS‟ LISTENING ABILITY

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Delsa Miranty

2017-04-01

Full Text Available This paper aims to provide some ideas both for English teachers and target learners about how to apply CALL and Cooperative Learning as the solution to develop students‘ listening activities in the classroom. Since teachers need to understand about students‘ needs, background, age and expectations when they learn English as the foreign language in the classroom. Therefore, the English teacher should provide environment which facilitates the children to have fun di the teaching learning process, nice atmosphere, comfort and enjoyable to learn English and practice it both in the classroom and in the laboratory. Furthermore, this paper will provide what the teachers should do related activities such as: listening to the songs, movies, cartoon by applying STAD (Students Teams – Achievement Divisions in the classroom in order to develop students‘ listening ability both in the classroom and laboratory.

The Effects of the CALL Model on College English Reading Teaching

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Dan Zhang

2017-12-01

Full Text Available Computer Assisted Language Learning (CALL is an important concept in English teaching method reform. College students’ English reading ability is an important indicator in the evaluation on the college students’ English proficiency. Therefore, this paper applies the CALL model in English reading teaching. Firstly, it introduces the application and development prospect of the CALL model, and analyzes its advantages and disadvantages; secondly, it analyzes the present situation of college English teaching and its influencing factors and then designs an application example to integrate the CALL model with different aspect of English reading. Finally, it analyzes the teaching results of college English reading under the CALL model. Therefore, in both theory and practice, this paper proves the effectiveness and innovativeness of the CALL model.

A Call to Action for Research in Digital Learning: Learning without Limits of Time, Place, Path, Pace…or Evidence

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Cavanaugh, Cathy; Sessums, Christopher; Drexler, Wendy

2015-01-01

This essay is a call for rethinking our approach to research in digital learning. It plots a path founded in social trends and advances in education. A brief review of these trends and advances is followed by discussion of what flattened research might look like at scale. Scaling research in digital learning is crucial to advancing understanding…

Tourism websites in English as a source for the autonomous learning of specialized terminology: A CALL application

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Ángel Felices Lago

2016-04-01

Full Text Available For years now, it has been an unquestioned fact that a large majority of textbooks available in English for Tourism, either in book format, CD-Rom or web site access are based on situations and professional contexts connected with the Anglo-Saxon environment, even though the vast majority of graduates in Tourism in Spain (and other countries end up working in the region (autonomous community of origin or in the province of reference for studies. There is, therefore, a clear dysfunction between the textbooks available in the market and the materials and situations that the students will face in their professional future. However, the Internet now allows us to exploit the availability of vast quantities of local resources (websites, blogs, etc. with their corresponding versions in English, which include tourist information referring to, for example, hotels, restaurants, historical and artistic heritage sites, tour operators, travel agencies, trade fairs or specialized services at the national, regional or communal levels. All these sites offer a special showcase of all the linguistic resources available (be they lexical, syntactic or terminological that the learners must acquire for their professional development. Consequently, the purpose of this study is to offer the results of the computer-assisted language learning (CALL project entitled Autonomous Learning of Specialized Vocabulary in English for Tourism (http://wdb.ugr.es/~afelices/, which takes into consideration the previous premises in order to promote, as its title indicates, autonomous learning in a more realistic professional context and to serve as a model for the development of similar e-learning platforms in other regions or countries.

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

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Ni Shu Yan

2017-01-01

Full Text Available The large changing of link capacity and number of users caused by the movement of both platform and users in communication system based on high altitude platform station (HAPS will resulting in high dropping rate of handover and reduce resource utilization. In order to solve these problems, this paper proposes an adaptive call admission control strategy based on reinforcement learning approach. The goal of this strategy is to maximize long-term gains of system, with the introduction of cross-layer interaction and the service downgraded. In order to access different traffics adaptively, the access utility of handover traffics and new call traffics is designed in different state of communication system. Numerical simulation result shows that the proposed call admission control strategy can enhance bandwidth resource utilization and the performances of handover traffics.

Neural correlates of threat perception: neural equivalence of conspecific and heterospecific mobbing calls is learned.

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Marc T Avey

Full Text Available Songbird auditory areas (i.e., CMM and NCM are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators. Mobbing calls produced in response to smaller, higher-threat predators contain more "D" notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned.

Neural Correlates of Threat Perception: Neural Equivalence of Conspecific and Heterospecific Mobbing Calls Is Learned

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Avey, Marc T.; Hoeschele, Marisa; Moscicki, Michele K.; Bloomfield, Laurie L.; Sturdy, Christopher B.

2011-01-01

Songbird auditory areas (i.e., CMM and NCM) are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise [1]–[2]. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators [3]. Mobbing calls produced in response to smaller, higher-threat predators contain more “D” notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators [4]. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG) expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned. PMID:21909363

Neural correlates of threat perception: neural equivalence of conspecific and heterospecific mobbing calls is learned.

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Avey, Marc T; Hoeschele, Marisa; Moscicki, Michele K; Bloomfield, Laurie L; Sturdy, Christopher B

2011-01-01

Songbird auditory areas (i.e., CMM and NCM) are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators. Mobbing calls produced in response to smaller, higher-threat predators contain more "D" notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG) expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned.

Planung einer Mobile Learning Application für medizinische Lerninhalte [Planning of a mobile learning application for medical contents

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Walther, Patrick

2013-11-01

Full Text Available [english] Due to the high popularity of mobile devices barriers for mobile learning are becoming less. Place-and time-independent access to information is part of everyday life. The number of mobile applications is steadily growing. Currently there are more than 500,000 mobile applications, so-called apps, available for the Apple iPhone/iPad which can be downloaded in the Apple iTunes Store. More than ten percent of these apps are mobile learning applications.Before starting development of a mobile app we need to analyze all requirements accurately. This is due to the fact that there is a multiplicity of different operating systems with different functionalities. This paper shows general properties of so-called native, hybrid, and web applications and advantages and disadvantages in development and use of the finished application. In addition, current software, which supports the development of a mobile application is explained.Finally the differences of the various development options are shown based on concrete mobile applications.[german] Aufgrund der hohen Verbreitung mobiler Endgeräte werden die Barrieren für das mobile Lernen immer geringer und orts- und zeitunabhängiger Zugriff auf Informationen ist längst im Alltag angekommen. Die Zahl mobiler Applikation wächst stetig an. So stehen beispielsweise aktuell mehr als 500.000 mobile Applikationen, sogenannte Apps, für das Apple iPhone/iPad, dem Nutzer über den Apple iTunes Store bereit. Hiervon sind mehr als zehn Prozent mobile Lernapplikationen.Vor der eigentlichen Entwicklung einer App muss, u.a. aufgrund der Vielzahl mobiler Betriebssysteme und Funktionen der verschiedenen mobilen Endgeräte, zuvor eine genaue Bedarfsanalyse durchgeführt werden um die passende Entwicklungsvariante zu wählen.In diesem Beitrag werden die verschiedenen Möglichkeiten (nativ, hybrid, web zur Entwicklung einer mobilen Applikation, als auch deren Vor- und Nachteile bei der Entwicklung und Nutzung der

Imbalanced learning foundations, algorithms, and applications

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He, Haibo

2013-01-01

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles,

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

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Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

2018-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Models in Science Education: Applications of Models in Learning and Teaching Science

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Ornek, Funda

2008-01-01

In this paper, I discuss different types of models in science education and applications of them in learning and teaching science, in particular physics. Based on the literature, I categorize models as conceptual and mental models according to their characteristics. In addition to these models, there is another model called "physics model" by the…

From Computer Assisted Language Learning (CALL) to Mobile Assisted Language Use (MALU)

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Jarvis, Huw; Achilleos, Marianna

2013-01-01

This article begins by critiquing the long-established acronym CALL (Computer Assisted Language Learning). We then go on to report on a small-scale study which examines how student non-native speakers of English use a range of digital devices beyond the classroom in both their first (L1) and second (L2) languages. We look also at the extent to…

Call cultures in orang-utans?

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Serge A Wich

Full Text Available BACKGROUND: Several studies suggested great ape cultures, arguing that human cumulative culture presumably evolved from such a foundation. These focused on conspicuous behaviours, and showed rich geographic variation, which could not be attributed to known ecological or genetic differences. Although geographic variation within call types (accents has previously been reported for orang-utans and other primate species, we examine geographic variation in the presence/absence of discrete call types (dialects. Because orang-utans have been shown to have geographic variation that is not completely explicable by genetic or ecological factors we hypothesized that this will be similar in the call domain and predict that discrete call type variation between populations will be found. METHODOLOGY/PRINCIPAL FINDINGS: We examined long-term behavioural data from five orang-utan populations and collected fecal samples for genetic analyses. We show that there is geographic variation in the presence of discrete types of calls. In exactly the same behavioural context (nest building and infant retrieval, individuals in different wild populations customarily emit either qualitatively different calls or calls in some but not in others. By comparing patterns in call-type and genetic similarity, we suggest that the observed variation is not likely to be explained by genetic or ecological differences. CONCLUSION/SIGNIFICANCE: These results are consistent with the potential presence of 'call cultures' and suggest that wild orang-utans possess the ability to invent arbitrary calls, which spread through social learning. These findings differ substantially from those that have been reported for primates before. First, the results reported here are on dialect and not on accent. Second, this study presents cases of production learning whereas most primate studies on vocal learning were cases of contextual learning. We conclude with speculating on how these findings might

Application of heuristic and machine-learning approach to engine model calibration

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Cheng, Jie; Ryu, Kwang R.; Newman, C. E.; Davis, George C.

1993-03-01

Automation of engine model calibration procedures is a very challenging task because (1) the calibration process searches for a goal state in a huge, continuous state space, (2) calibration is often a lengthy and frustrating task because of complicated mutual interference among the target parameters, and (3) the calibration problem is heuristic by nature, and often heuristic knowledge for constraining a search cannot be easily acquired from domain experts. A combined heuristic and machine learning approach has, therefore, been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of a machine learning program called GID3* for automatic acquisition of heuristic rules for ordering target parameters.

Virtual Physics Laboratory Application Based on the Android Smartphone to Improve Learning Independence and Conceptual Understanding

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Arista, Fitra Suci; Kuswanto, Heru

2018-01-01

The research study concerned here was to: (1) produce a virtual physics laboratory application to be called ViPhyLab by using the Android smartphone as basis; (2) determine the appropriateness and quality of the virtual physics laboratory application that had been developed; and (3) describe the improvement in learning independence and conceptual…

Executing application function calls in response to an interrupt

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Almasi, Gheorghe; Archer, Charles J.; Giampapa, Mark E.; Gooding, Thomas M.; Heidelberger, Philip; Parker, Jeffrey J.

2010-05-11

Executing application function calls in response to an interrupt including creating a thread; receiving an interrupt having an interrupt type; determining whether a value of a semaphore represents that interrupts are disabled; if the value of the semaphore represents that interrupts are not disabled: calling, by the thread, one or more preconfigured functions in dependence upon the interrupt type of the interrupt; yielding the thread; and if the value of the semaphore represents that interrupts are disabled: setting the value of the semaphore to represent to a kernel that interrupts are hard-disabled; and hard-disabling interrupts at the kernel.

Learning Analytics: The next frontier for computer assisted language learning in big data age

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Yu Qinglan

2015-01-01

Full Text Available Learning analytics (LA has been applied to various learning environments, though it is quite new in the field of computer assisted language learning (CALL. This article attempts to examine the application of learning analytics in the upcoming big data age. It starts with an introduction and application of learning analytics in other fields, followed by a retrospective review of historical interaction between learning and media in CALL, and a penetrating analysis on why people would go to learning analytics to increase the efficiency of foreign language education. As approved in previous research, new technology, including big data mining and analysis, would inevitably enhance the learning of foreign languages. Potential changes that learning analytics would bring to Chinese foreign language education and researches are also presented in the article.

SEE: improving nurse-patient communications and preventing software piracy in nurse call applications.

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Unluturk, Mehmet S

2012-06-01

Nurse call system is an electrically functioning system by which patients can call upon from a bedside station or from a duty station. An intermittent tone shall be heard and a corridor lamp located outside the room starts blinking with a slow or a faster rate depending on the call origination. It is essential to alert nurses on time so that they can offer care and comfort without any delay. There are currently many devices available for a nurse call system to improve communication between nurses and patients such as pagers, RFID (radio frequency identification) badges, wireless phones and so on. To integrate all these devices into an existing nurse call system and make they communicate with each other, we propose software client applications called bridges in this paper. We also propose a window server application called SEE (Supervised Event Executive) that delivers messages among these devices. A single hardware dongle is utilized for authentication and copy protection for SEE. Protecting SEE with securities provided by dongle only is a weak defense against hackers. In this paper, we develop some defense patterns for hackers such as calculating checksums in runtime, making calls to dongle from multiple places in code and handling errors properly by logging them into database.

Investigating CALL in the Classroom: Situational Variables to Consider

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Darlene Liutkus

2012-01-01

Full Text Available A new paradigm in second language pedagogy has Computer Assisted Language Learning (CALL playing a significant role. Much of the literature to-date claims that CALL can have a positive impact on students’ second language acquisition (SLA. Mixed method of research produces data to investigate if CALL positively affects student language proficiency, motivation and autonomy. Classroom observation of participants in their natural environment is a qualitative technique used but has situational variables that could skew results if not structured. A questionnaire is a quantitative tool that can offer insight regarding participants’ perception of performance but can contradict what the researcher has observed. This paper will take an in-depth look at variables such as: instructor’s pedagogical application; blending CALL into the curriculum; types of CALL implemented; feedback received and their implications for design of the data collection tools

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications.

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Minor, Bryan; Doppa, Janardhan Rao; Cook, Diane J

2017-12-01

Recent progress in Internet of Things (IoT) platforms has allowed us to collect large amounts of sensing data. However, there are significant challenges in converting this large-scale sensing data into decisions for real-world applications. Motivated by applications like health monitoring and intervention and home automation we consider a novel problem called Activity Prediction , where the goal is to predict future activity occurrence times from sensor data. In this paper, we make three main contributions. First, we formulate and solve the activity prediction problem in the framework of imitation learning and reduce it to a simple regression learning problem. This approach allows us to leverage powerful regression learners that can reason about the relational structure of the problem with negligible computational overhead. Second, we present several metrics to evaluate activity predictors in the context of real-world applications. Third, we evaluate our approach using real sensor data collected from 24 smart home testbeds. We also embed the learned predictor into a mobile-device-based activity prompter and evaluate the app for 9 participants living in smart homes. Our results indicate that our activity predictor performs better than the baseline methods, and offers a simple approach for predicting activities from sensor data.

PENGARUH PERMAINAN CALL CARDS TERHADAP HASIL BELAJAR DAN AKTIVITAS PEMBELAJARAN BIOLOGI

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A. Machin

2012-10-01

Full Text Available Tujuan penelitian untuk mengetahui pengaruh permainan call cards terhadap hasil belajar dan aktivitas pembelajaran. Aktivitas pembelajaran yang diukur meliputi aktivitas individual siswa dan kinerja guru. Penelitian ini merupakan penelitian eksperimental. Hasil penelitian menunjukkan bahwa media permainan call cards berkontribusi sebesar 46% terhadap hasil belajar siswa. Hasil belajar siswa yang diberi media permainan call cards lebih baik daripada hasil belajar siswa yang tidak diberi mediapermainan call cards. Dengan demikian, media permainan call cards dapat menjadi alternatif dalam pencapaian hasil belajar biologi yang lebih baik.   Research purposes to determine the effect of call cards game against learning outcomes and learning activities. Learning activities that were measured included the activity of individual student and teacher performance. This research was experimental. The results showed that the media play call cards account for 46% of the student learning outcomes. Learning outcomes of students who were given media cards call the game better than the learning outcomes of students who were not given mediapermainan call cards. Thus, the media play call cards can be an alternative in achieving the learning outcomes of biology better.

Mobile phone application for mathematics learning

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Supandi; Ariyanto, L.; Kusumaningsih, W.; Aini, A. N.

2018-03-01

This research was aimed to determine the role of the use of Mobile Phone Application (MPA) in Mathematics learning. The Pre and Post-test Quasy Experiment method was applied. The Pre-test was performed to understand the initial capability. In contrast, the Post-test was selected to identify changes in student ability after they were introduced to the application of Mobile Technology. Student responses to the use of this application were evaluated by a questionnaire. Based on the questionnaire, high scores were achieved, indicating the student's interest in this application. Also, learning results showed significant improvement in the learning achievement and the student learning behaviour. It was concluded that education supported by the MPA application gave a positive impact on learning outcomes as well as learning atmosphere both in class and outside the classroom.

VIPER: a web application for rapid expert review of variant calls.

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Wöste, Marius; Dugas, Martin

2018-01-15

With the rapid development in next-generation sequencing, cost and time requirements for genomic sequencing are decreasing, enabling applications in many areas such as cancer research. Many tools have been developed to analyze genomic variation ranging from single nucleotide variants to whole chromosomal aberrations. As sequencing throughput increases, the number of variants called by such tools also grows. Often employed manual inspection of such calls is thus becoming a time-consuming procedure. We developed the Variant InsPector and Expert Rating tool (VIPER) to speed up this process by integrating the Integrative Genomics Viewer into a web application. Analysts can then quickly iterate through variants, apply filters and make decisions based on the generated images and variant metadata. VIPER was successfully employed in analyses with manual inspection of more than 10,000 calls. VIPER is implemented in Java and Javascript and is freely available at https://github.com/MarWoes/viper. Marius.Woeste@uni-muenster.de. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Aggregative Learning Method and Its Application for Communication Quality Evaluation

Science.gov (United States)

Akhmetov, Dauren F.; Kotaki, Minoru

2007-12-01

In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

Developing an effective corrective action process : lessons learned from operating a confidential close call reporting system

Science.gov (United States)

2013-03-05

In 2007, the Federal Railroad Administration (FRA) launched : C3RS, the Confidential Close Call Reporting System, as a : demonstration project to learn how to facilitate the effective : reporting and implementation of corrective actions, and assess t...

Learning analytics dashboard applications

NARCIS (Netherlands)

Verbert, K.; Duval, E.; Klerkx, J.; Govaerts, S.; Santos, J.L.

2013-01-01

This article introduces learning analytics dashboards that visualize learning traces for learners and teachers. We present a conceptual framework that helps to analyze learning analytics applications for these kinds of users. We then present our own work in this area and compare with 15 related

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

Science.gov (United States)

van den Akker, Jeroen; Mishne, Gilad; Zimmer, Anjali D; Zhou, Alicia Y

2018-04-17

Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable. However, a small subset of difficult-to-call variants that still do require orthogonal confirmation exist. For this reason, many clinical laboratories confirm NGS results using orthogonal technologies such as Sanger sequencing. Here, we report the development of a deterministic machine-learning-based model to differentiate between these two types of variant calls: those that do not require confirmation using an orthogonal technology (high confidence), and those that require additional quality testing (low confidence). This approach allows reliable NGS-based calling in a clinical setting by identifying the few important variant calls that require orthogonal confirmation. We developed and tested the model using a set of 7179 variants identified by a targeted NGS panel and re-tested by Sanger sequencing. The model incorporated several signals of sequence characteristics and call quality to determine if a variant was identified at high or low confidence. The model was tuned to eliminate false positives, defined as variants that were called by NGS but not confirmed by Sanger sequencing. The model achieved very high accuracy: 99.4% (95% confidence interval: +/- 0.03%). It categorized 92.2% (6622/7179) of the variants as high confidence, and 100% of these were confirmed to be present by Sanger sequencing. Among the variants that were categorized as low confidence, defined as NGS calls of low quality that are likely to be artifacts, 92.1% (513/557) were found to be not present by Sanger sequencing. This work shows that NGS data contains sufficient characteristics for a machine-learning-based model to

Conceptual Design of a Mobile Application for Geography Fieldwork Learning

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Xiaoling Wang

2017-11-01

Full Text Available The use of mobile applications on smartphones has a vast potential to support learning in the field. However, all learning technologies should be properly designed. To this end, we adopt User-Centered Design (UCD to design a mobile application, called GeoFARA (Geography Fieldwork Augmented Reality Application, for university geography fieldwork. This paper is about the conceptual design of GeoFARA based on its use and user requirements. The paper first establishes a review of selected existing mobile AR applications for outdoor use, in order to identify the innovative aspects and the improvements of GeoFARA. Thereafter, we present the results of use and user requirements derived from (1 an online survey of the current use of tools in undergraduate geography fieldwork, (2 a field experiment in which the use of paper maps and a mobile mapping tool were compared, (3 investigations during a human geography fieldwork, (4 post-fieldwork surveys among undergraduates from two universities, (5 our use case, and (6 a use scenario. Based on these requirements, a conceptual design of GeoFARA is provided in terms of technical specifications, main contents, functionalities, as well as user interactions and interfaces. This conceptual design will guide the future prototype development of GeoFARA.

The Differences across Distributed Leadership Practices by School Position According to the Comprehensive Assessment of Leadership for Learning (CALL)

Science.gov (United States)

Blitz, Mark H.; Modeste, Marsha

2015-01-01

The Comprehensive Assessment of Leadership for Learning (CALL) is a multi-source assessment of distributed instructional leadership. As part of the validation of CALL, researchers examined differences between teacher and leader ratings in assessing distributed leadership practices. The authors utilized a t-test for equality of means for the…

Learning style preferences of surgical residency applicants.

Science.gov (United States)

Kim, Roger H; Gilbert, Timothy

2015-09-01

The learning style preferences of general surgery residents have been previously reported; there is evidence that residents who prefer read/write learning styles perform better on the American Board of Surgery In-Training Examination (ABSITE). However, little is known regarding the learning style preferences of applicants to general surgery residency and their impact on educational outcomes. In this study, the preferred learning styles of surgical residency applicants were determined. We hypothesized that applicant rank data are associated with specific learning style preferences. The Fleming VARK learning styles inventory was offered to all general surgery residency applicants that were interviewed at a university hospital-based program. The VARK model categorizes learners as visual (V), aural (A), read/write (R), kinesthetic (K), or multimodal (MM). Responses on the inventory were scored to determine the preferred learning style for each applicant. Applicant data, including United States Medical Licensing Examination (USMLE) scores, class rank, interview score, and overall final applicant ranking, were examined for association with preferred learning styles. Sixty-seven applicants were interviewed. Five applicants were excluded due to not completing the VARK inventory or having incomplete applicant data. The remaining 62 applicants (92%) were included for analysis. Most applicants (57%) had a multimodal preference. Sixty-nine percent of all applicants had some degree of preference for kinesthetic learning. There were statistically significant differences between applicants of different learning styles in terms of USMLE step 1 scores (P = 0.001) and USMLE step 2 clinical knowledge scores (P = 0.01), but not for class ranks (P = 0.27), interview scores (P = 0.20), or final ranks (P = 0.14). Multiple comparison analysis demonstrated that applicants with aural preferences had higher USMLE 1 scores (233.2) than those with kinesthetic (211.8, P = 0.005) or multimodal

Application of Machine Learning Techniques in Aquaculture

OpenAIRE

Rahman, Akhlaqur; Tasnim, Sumaira

2014-01-01

In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.

System Quality Characteristics for Selecting Mobile Learning Applications

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Mohamed SARRAB

2015-10-01

Full Text Available The majority of M-learning (Mobile learning applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased recognition and adoption by different organizations. With the high number of M-learning applications available today, making the right decision about which, application to choose can be quite challenging. To date there is no complete and well defined set of system characteristics for such M-learning applications. This paper presents system quality characteristics for selecting M-learning applications based on the result of a systematic review conducted in this domain.

mCLEV-R: Design and Evaluation of an Interactive and Collaborative M-Learning Application

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Teresa Monahan

2007-06-01

Full Text Available Continuous enhancements in computer technology and the current widespread computer literacy among the public have resulted in a new generation of students that expect increasingly more from their e-learning experiences. To keep up with such expectations, e-learning systems have gone through a radical change from the initial text-based environments to more stimulating multimedia systems. E-learning functionalities are now also being extended to mobile platforms in order to be more available and convenient for users. Many mobile learning applications have now been developed and they too are becoming more advanced. However, providing truly collaborative and interactive mobile learning tools still remains a challenge. In this paper, we present a desktop e-learning system called CLEV-R and in particular a component of the system that we have developed for mobile devices. This mobile component explores the possibility of providing collaboration tools for mobile learners while also presenting the learning experience through an engaging 3D environment.

An e-learning application on electrochemotherapy

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Bester Janez

2009-10-01

Full Text Available Abstract Background Electrochemotherapy is an effective approach in local tumour treatment employing locally applied high-voltage electric pulses in combination with chemotherapeutic drugs. In planning and performing electrochemotherapy a multidisciplinary expertise is required and collaboration, knowledge and experience exchange among the experts from different scientific fields such as medicine, biology and biomedical engineering is needed. The objective of this study was to develop an e-learning application in order to provide the educational content on electrochemotherapy and its underlying principles and to support collaboration, knowledge and experience exchange among the experts involved in the research and clinics. Methods The educational content on electrochemotherapy and cell and tissue electroporation was based on previously published studies from molecular dynamics, lipid bilayers, single cell level and simplified tissue models to complex biological tissues and research and clinical results of electrochemotherapy treatment. We used computer graphics such as model-based visualization (i.e. 3D numerical modelling using finite element method and 3D computer animations and graphical illustrations to facilitate the representation of complex biological and physical aspects in electrochemotherapy. The e-learning application is integrated into an interactive e-learning environment developed at our institution, enabling collaboration and knowledge exchange among the users. We evaluated the designed e-learning application at the International Scientific workshop and postgraduate course (Electroporation Based Technologies and Treatments. The evaluation was carried out by testing the pedagogical efficiency of the presented educational content and by performing the usability study of the application. Results The e-learning content presents three different levels of knowledge on cell and tissue electroporation. In the first part of the e-learning

An e-learning application on electrochemotherapy.

Science.gov (United States)

Corovic, Selma; Bester, Janez; Miklavcic, Damijan

2009-10-20

Electrochemotherapy is an effective approach in local tumour treatment employing locally applied high-voltage electric pulses in combination with chemotherapeutic drugs. In planning and performing electrochemotherapy a multidisciplinary expertise is required and collaboration, knowledge and experience exchange among the experts from different scientific fields such as medicine, biology and biomedical engineering is needed. The objective of this study was to develop an e-learning application in order to provide the educational content on electrochemotherapy and its underlying principles and to support collaboration, knowledge and experience exchange among the experts involved in the research and clinics. The educational content on electrochemotherapy and cell and tissue electroporation was based on previously published studies from molecular dynamics, lipid bilayers, single cell level and simplified tissue models to complex biological tissues and research and clinical results of electrochemotherapy treatment. We used computer graphics such as model-based visualization (i.e. 3D numerical modelling using finite element method) and 3D computer animations and graphical illustrations to facilitate the representation of complex biological and physical aspects in electrochemotherapy. The e-learning application is integrated into an interactive e-learning environment developed at our institution, enabling collaboration and knowledge exchange among the users. We evaluated the designed e-learning application at the International Scientific workshop and postgraduate course (Electroporation Based Technologies and Treatments). The evaluation was carried out by testing the pedagogical efficiency of the presented educational content and by performing the usability study of the application. The e-learning content presents three different levels of knowledge on cell and tissue electroporation. In the first part of the e-learning application we explain basic principles of

Convergence of calls as animals form social bonds, active compensation for noisy communication channels, and the evolution of vocal learning in mammals.

Science.gov (United States)

Tyack, Peter L

2008-08-01

The classic evidence for vocal production learning involves imitation of novel, often anthropogenic sounds. Among mammals, this has been reported for dolphins, elephants, harbor seals, and humans. A broader taxonomic distribution has been reported for vocal convergence, where the acoustic properties of calls from different individuals converge when they are housed together in captivity or form social bonds in the wild. Vocal convergence has been demonstrated for animals as diverse as songbirds, parakeets, hummingbirds, bats, elephants, cetaceans, and primates. For most species, call convergence is thought to reflect a group-distinctive identifier, with shared calls reflecting and strengthening social bonds. A ubiquitous function for vocal production learning that is starting to receive attention involves modifying signals to improve communication in a noisy channel. Pooling data on vocal imitation, vocal convergence, and compensation for noise suggests a wider taxonomic distribution of vocal production learning among mammals than has been generally appreciated. The wide taxonomic distribution of this evidence for vocal production learning suggests that perhaps more of the neural underpinnings for vocal production learning are in place in mammals than is usually recognized. (c) 2008 APA, all rights reserved

Mobile Learning: Using Application "Auralbook" to Learn Aural Skills

Science.gov (United States)

Chen, Chi Wai Jason

2015-01-01

This study is to investigate the effectiveness of using mobile devices such as iPhone/iPad/android phone/tablet to facilitate mobile learning in aural skills. The application "Auralbook" was designed in 2011 by an engineer/musician to use mobile devices to learn aural skills. This application enables students to sing, record, clap and…

The Ghost in the Machine: Are "Teacherless" CALL Programs Really Possible?

Science.gov (United States)

Davies, Ted; Williamson, Rodney

1998-01-01

Reflects critically on pedagogical issues in the production of computer-assisted language learning (CALL) courseware and ways CALL has affected the practice of language learning. Concludes that if CALL is to reach full potential, it must be more than a simple medium of information; it should provide a teaching/learning process, with the real…

A Study of Multimedia Application-Based Vocabulary Acquisition

Science.gov (United States)

Shao, Jing

2012-01-01

The development of computer-assisted language learning (CALL) has created the opportunity for exploring the effects of the multimedia application on foreign language vocabulary acquisition in recent years. This study provides an overview the computer-assisted language learning (CALL) and detailed a developing result of CALL--multimedia. With the…

75 FR 53640 - Call for Applications for the International Buyer Program Calendar Year 2012

Science.gov (United States)

2010-09-01

... addition, the applicant should describe in detail the international marketing program to be conducted for... DEPARTMENT OF COMMERCE International Trade Administration [Docket No.: 100806330-0330-01] Call for Applications for the International Buyer Program Calendar Year 2012 AGENCY: International Trade Administration...

Integrating Collaborative and Decentralized Models to Support Ubiquitous Learning

Science.gov (United States)

Barbosa, Jorge Luis Victória; Barbosa, Débora Nice Ferrari; Rigo, Sandro José; de Oliveira, Jezer Machado; Rabello, Solon Andrade, Jr.

2014-01-01

The application of ubiquitous technologies in the improvement of education strategies is called Ubiquitous Learning. This article proposes the integration between two models dedicated to support ubiquitous learning environments, called Global and CoolEdu. CoolEdu is a generic collaboration model for decentralized environments. Global is an…

System Quality Characteristics for Selecting Mobile Learning Applications

Science.gov (United States)

Sarrab, Mohamed; Al-Shihi, Hafedh; Al-Manthari, Bader

2015-01-01

The majority of M-learning (Mobile learning) applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased…

Quality Assurance in E-Learning: PDPP Evaluation Model and its Application

Directory of Open Access Journals (Sweden)

Weiyuan Zhang

2012-06-01

Full Text Available E-learning has become an increasingly important teaching and learning mode in educational institutions and corporate training. The evaluation of e-learning, however, is essential for the quality assurance of e-learning courses. This paper constructs a four-phase evaluation model for e-learning courses, which includes planning, development, process, and product evaluation, called the PDPP evaluation model. Planning evaluation includes market demand, feasibility, target student group, course objectives, and finance. Development evaluation includes instructional design, course material design, course Web site design, flexibility, student-student interaction, teacher/tutor support, technical support, and assessment. Process evaluation includes technical support, Web site utilization, learning interaction, learning evaluation, learning support, and flexibility. Product evaluation includes student satisfaction, teaching effectiveness, learning effectiveness, and sustainability. Using the PDPP model as a research framework, a purely e-learning course on Research Methods in Distance Education, developed by the School of Professional and Continuing Education at the University of Hong Kong (HKU SPACE and jointly offered with the School of Distance Learning for Medical Education of Peking University (SDLME, PKU, was used as a case study. Sixty students from mainland China, Hong Kong, Macau, and Malaysia were recruited for this course. According to summative evaluation through a student e-learning experience survey, the majority of students were very satisfied/satisfied on all e-learning dimensions of this course. The majority of students thought that the learning effectiveness of this course was equivalent, even better, than face-to-face learning because of cross-border collaborative learning, student-centred learning, sufficient learning support, and learning flexibility. This study shows that a high quality of teaching and learning might be assured by

Classification of large acoustic datasets using machine learning and crowdsourcing: Application to whale calls

NARCIS (Netherlands)

Shamir, L.; Carol Yerby, C.; Simpson, R.; Benda-Beckmann, A.M. von; Tyack, P.; Samarra, F.; Miller, P.; Wallin, J.

2014-01-01

Vocal communication is a primary communication method of killer and pilot whales, and is used for transmitting a broad range of messages and information for short and long distance. The large variation in call types of these species makes it challenging to categorize them. In this study, sounds

A scrutiny of the educational value of EFL mobile learning applications

Directory of Open Access Journals (Sweden)

Cristina Calle Martínez

2014-08-01

Full Text Available Mobile learning is without any doubt the next step in the evolution of educational technology as it offers modern methods of support to the process of learning through the use of mobile instruments. However, although there are a huge number of educational applications in the market at the moment, the educational value of many of them is rather questionable. The final aim of the SO-CALL-ME ((Social Ontology-based Cognitively Augmented Language Learning Mobile Environment (FFI 2011-29829 research project is to design and create EFL mobile applications that successfully combine technical skills and a solid pedagogy. In this light, the present study is the third phase of a line of research which started in 2012. In the first phase 67 MALL applications in the context of EFL were assessed by means of a rubric not on their technical features but on their pedagogic goals. The results gave us an idea of the qualities and limitations of the apps examined. In the second phase, a quality guide was created as the basis for a more elaborate evaluation rubric. Out of the EFL apps previously analyzed with the first rubric, we chose four that fulfilled the features considered most important for the apps to be developed in a final stage of the research project. In the third phase, a rubric was used to evaluate the linguistic adequacy of EFL apps for listening. The present study offers the evaluation of a higher number of apps using the rubrics created in phases 2 and 3 in order to corroborate the first impressions as a final step before using the quality guide for the creation of EFL applications.

Education for a Learning Society.

Science.gov (United States)

Tempero, Howard E., Ed.

The essays contained in this booklet are 1) "Education for a 'Learning Society': The Challenge" by Ernest Bayles in which he calls for focus on learning to live, developing skills of reflection and judgment applicable to vital issues, and reflective teaching; 2) "Teacher Education in a Learning Society" in which David Turney demands teacher…

Application of adobe flash media to optimize jigsaw learning model on geometry material

Science.gov (United States)

Imam, P.; Imam, S.; Ikrar, P.

2018-05-01

This study aims to determine and describe the effectiveness of the application of adobe flash media for jigsaw learning model on geometry material. In this study, the modified jigsaw learning with adobe flash media is called jigsaw-flash model. This research was conducted in Surakarta. The research method used is mix method research with exploratory sequential strategy. The results of this study indicate that students feel more comfortable and interested in studying geometry material taught by jigsaw-flash model. In addition, students taught using the jigsaw-flash model are more active and motivated than the students who were taught using ordinary jigsaw models. This shows that the use of the jigsaw-flash model can increase student participation and motivation. It can be concluded that the adobe flash media can be used as a solution to reduce the level of student abstraction in learning mathematics.

Developing CALL for heritage languages: The 7 Keys of the Dragon

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Anthi Revithiadou

2015-09-01

Full Text Available n this article we present an interactive extensible software, The 7 Keys of the Dragon, for the teaching/learning of Albanian and Russian to students that attend primary and secondary education in Greece with the respective languages as their heritage languages. We address the key challenges we encountered during the conceptualization phase of the project development and the specific design choices we implemented in order to accommodate them. Drawing on recent research on the role of Computer-Assisted Language Learning (CALL applications for young bilingual populations, we aimed at creating a user friendly environment with a clear pedagogical orientation. Furthermore, given that games in language learning are associated with intrinsic motivation and meaningful exposure to the target language, we have integrated a fairy-tale background narrative, a game-inspired reward system, and two cartoon-like assistant characters to stimulate the user’s involvement in the learning tasks. Five chapters for each target language were created, each comprising a text, a variety of scaffolding material and quizzes. The software is designed to provide real-time automatic correction of quizzes and allow for easy expansion with additional quizzes and texts. A separate application for teachers facilitates essay correction and commenting on the students’ language learning progress and achievements.

Skype™ Conference Calls: A Way to Promote Speaking Skills in the Teaching and Learning of English

Directory of Open Access Journals (Sweden)

Yeferson Romaña Correa

2015-01-01

Full Text Available This article presents the results of a research project on the teaching and learning of English through the use of Skype™ conference calls. The research was carried out with a group of 12 English as a foreign language adult learners in the language institute of Universidad Distrital Francisco José de Caldas, Bogotá, Colombia. The findings of this study suggest that Skype™ conference calls might be considered as an influential computer-mediated communication tool in order to promote English as a foreign language adult A1 learners’ speaking skill, especially for social interaction purposes and oral reinforcement of both language fluency and course contents outside of classroom settings.

Machine learning applications in genetics and genomics.

Science.gov (United States)

Libbrecht, Maxwell W; Noble, William Stafford

2015-06-01

The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning applications for the analysis of genome sequencing data sets, including the annotation of sequence elements and epigenetic, proteomic or metabolomic data. We present considerations and recurrent challenges in the application of supervised, semi-supervised and unsupervised machine learning methods, as well as of generative and discriminative modelling approaches. We provide general guidelines to assist in the selection of these machine learning methods and their practical application for the analysis of genetic and genomic data sets.

Indico CONFERENCE: Define the Call for Abstracts

CERN Multimedia

CERN. Geneva; Ferreira, Pedro

2017-01-01

In this tutorial, you will learn how to define and open a call for abstracts. When defining a call for abstracts, you will be able to define settings related to the type of questions asked during a review of an abstract, select the users who will review the abstracts, decide when to open the call for abstracts, and more.

Learning Performance Enhancement Using Computer-Assisted Language Learning by Collaborative Learning Groups

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Ya-huei Wang

2017-08-01

Full Text Available This study attempted to test whether the use of computer-assisted language learning (CALL and innovative collaborative learning could be more effective than the use of traditional collaborative learning in improving students’ English proficiencies. A true experimental design was used in the study. Four randomly-assigned groups participated in the study: a traditional collaborative learning group (TCLG, 34 students, an innovative collaborative learning group (ICLG, 31 students, a CALL traditional collaborative learning group (CALLTCLG, 32 students, and a CALL innovative collaborative learning group (CALLICLG, 31 students. TOEIC (Test of English for International Communication listening, reading, speaking, and writing pre-test and post-test assessments were given to all students at an interval of sixteen weeks. Multivariate analysis of covariance (MANCOVA, multivariate analysis of variance (MANOVA, and analysis of variance (ANOVA were used to analyze the data. The results revealed that students who used CALL had significantly better learning performance than those who did not. Students in innovative collaborative learning had significantly better learning performances than those in traditional collaborative learning. Additionally, students using CALL innovative collaborative learning had better learning performances than those in CALL collaborative learning, those in innovative collaborative learning, and those in traditional collaborative learning.

Editorial (special issue on CALL, e-learning and m-learning

Directory of Open Access Journals (Sweden)

Jo Mynard

2011-09-01

Full Text Available Technology has, in one form of another, been a part of self-access learning since the very first self-access centres (SACs of the 1980s. Some of the better-funded centres featured elaborate listening and recording machinery and (occasionally early personal computers. Early software programmes and language-learning websites available for self-access use tended to be aimed at individual study, initially following the language lab model, and were often designed to teach or test discrete language points. Of course, in 2011 programmes aimed at individual study do still exist and certainly have a place in self-access learning, particularly if a learner has identified a target language area that the software or website covers. However, in this special issue we go beyond language learning software and look at tools and technologies currently available to the learner as self-access resources.

Exercise, character strengths, well-being, and learning climate in the prediction of performance over a 6-month period at a call center.

Science.gov (United States)

Moradi, Saleh; Nima, Ali A; Rapp Ricciardi, Max; Archer, Trevor; Garcia, Danilo

2014-01-01

Performance monitoring might have an adverse influence on call center agents' well-being. We investigate how performance, over a 6-month period, is related to agents' perceptions of their learning climate, character strengths, well-being (subjective and psychological), and physical activity. Agents (N = 135) self-reported perception of the learning climate (Learning Climate Questionnaire), character strengths (Values In Action Inventory Short Version), well-being (Positive Affect, Negative Affect Schedule, Satisfaction With Life Scale, Psychological Well-Being Scales Short Version), and how often/intensively they engaged in physical activity. Performance, "time on the phone," was monitored for 6 consecutive months by the same system handling the calls. Performance was positively related to having opportunities to develop, the character strengths clusters of Wisdom and Knowledge (e.g., curiosity for learning, perspective) and Temperance (e.g., having self-control, being prudent, humble, and modest), and exercise frequency. Performance was negatively related to the sense of autonomy and responsibility, contentedness, the character strengths clusters of Humanity and Love (e.g., helping others, cooperation) and Justice (e.g., affiliation, fairness, leadership), positive affect, life satisfaction and exercise Intensity. Call centers may need to create opportunities to develop to increase agents' performance and focus on individual differences in the recruitment and selection of agents to prevent future shortcomings or worker dissatisfaction. Nevertheless, performance measurement in call centers may need to include other aspects that are more attuned with different character strengths. After all, allowing individuals to put their strengths at work should empower the individual and at the end the organization itself. Finally, physical activity enhancement programs might offer considerable positive work outcomes.

Exercise, Character Strengths, Well-Being and Learning Climate in the Prediction of Performance over a Six-Month Period at a Call Center

Directory of Open Access Journals (Sweden)

Saleh eMoradi

2014-06-01

Full Text Available Background: Performance monitoring might have an adverse influence on call center agents’ well-being. We investigate how performance, over a six-month period, is related to agents’ perceptions of their learning climate, character strengths, well-being (subjective and psychological, and physical activity.Method: Agents (N = 135 self-reported perception of the learning climate (Learning Climate Questionnaire, character strengths (Values In Action Inventory Short Version, well-being (Positive Affect, Negative Affect Schedule, Satisfaction With Life Scale, Psychological Well-Being Scales Short Version, and how often/intensively they engaged in physical activity. Performance, time on the phone, was monitored for six consecutive months by the same system handling the calls. Results: Performance was positively related to having opportunities to develop, the character strengths clusters of Wisdom and Knowledge (e.g., curiosity for learning, perspective and Temperance (e.g., having self-control, being prudent, humble, and modest, and exercise frequency. Performance was negatively related to the sense of autonomy and responsibility, contentedness, the character strengths clusters of Humanity and Love (e.g., helping others, cooperation and Justice (e.g., affiliation, fairness, leadership, positive affect, life satisfaction and exercise Intensity.Conclusion: Call centers may need to create opportunities to develop to increase agents’ performance and focus on individual differences in the recruitment and selection of agents to prevent future shortcomings or worker dissatisfaction. Nevertheless, performance measurement in call centers may need to include other aspects that are more attuned with different character strengths. After all, allowing individuals to put their strengths at work should empower the individual and at the end the organization itself. Finally, physical activity enhancement programs might offer considerable positive work outcomes.

Impact of Using CALL on Iranian EFL Learners' Vocabulary Knowledge

Science.gov (United States)

Yunus, Melor Md; Salehi, Hadi; Amini, Mahdi

2016-01-01

Computer Assisted Language Learning (CALL) integration in EFL contexts has intensified noticeably in recent years. This integration might be in different ways and for different purposes such as vocabulary acquisition, grammar learning, phonology, writing skills, etc. More explicitly, this study is an attempt to explore the effect of using CALL on…

Analisis Unjuk Kerja Aplikasi VoIP Call Android di Jaringan MANET [Performance Analysis of VoIP Call Application Android in MANET (Mobile Ad Hoc Network

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Ryan Ari Setyawan

2015-06-01

Full Text Available Penelitian ini bertujuan menganalisis kinerja aplikasi  VoIP call android di jaringan MANET (mobile ad hoc network.  Hasil pengujian menunjukan bahwa aplikasi VoIP call android dapat digunakan di jaringan MANET. Delay yang dihasilkan paling besar di pengujian indoor dengan jarak 11-15 meter yakni sebesar 0,014624811 seconds. Packet loss yang dihasilkan pada range 1%-2% sedangkan standar packet loss yang ditetapkan oleh CISCO untuk layanan aplikasi VoIP adalah < 5%. Jitter yang dihasilkan yakni antara 0,01-0,06 seconds sedangkan standar yang ditetapkan oleh CISCO adalah ≤ 30 ms atau 0,03 seconds. Throughput yang dihasilkan pada proses pengujian yakni antar 161 kbps-481 kbps. *****This study aims to analyze the performance of VOIP call android application in the MANET (mobile ad hoc network. The results showed that VoIP applications could be implemented in MANET network. The highest  delay is produced in indoor testing  with distance of 11-15 meters,  which is equal to 0.014624811 seconds. Packet loss is generated in the range of 1% -2%, while packet loss standards set by Cisco for VoIP application services are <5%. The jitter is between 0.01 to 0.06 seconds, while the standard set by CISCO is ≤ 30 ms or 0.03 seconds. Throughput generated in the testing process is between 161 kbps-481 kbps.

Deep Learning and Its Applications in Biomedicine.

Science.gov (United States)

Cao, Chensi; Liu, Feng; Tan, Hai; Song, Deshou; Shu, Wenjie; Li, Weizhong; Zhou, Yiming; Bo, Xiaochen; Xie, Zhi

2018-02-01

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning. Copyright © 2018. Production and hosting by Elsevier B.V.

Developing an M-Learning Application for iOS

Directory of Open Access Journals (Sweden)

Paul POCATILU

2013-01-01

Full Text Available The mobile market development has a high impact on all domains including education. Smart mobile devices started to be affordable and the massive use on educational processes does not seem to be too far. Mobile learning applications are be targeted for all major mobile operating systems as native applications or Web-based. The objective of this paper is to present the implementation of the evaluation module for an m-learning application developed for iOS devices. The m-learning application is targeted to a higher education institution. The application uses Web services in order to obtain the content and to authenticate the users.

Going on Safari: The Design and Development of an Early Years Literacy iPad Application to Support Letter-Sound Learning

Science.gov (United States)

McKenzie, Sophie; Spence, Aaron; Nicholas, Maria

2018-01-01

This paper explores the design, development and evaluation of an early childhood literacy iPad application, focusing on the English Alphabet, called "A to Z Safari" trialled in Australian classrooms. A to Z Safari was designed to assist students in the early years of schooling with learning the alphabet and building on their knowledge of…

CALL in the Year 2000: A Look Back from 2016

Science.gov (United States)

Chapelle, Carol A.

2016-01-01

This commentary offers a brief reflection on the state of CALL in 1997, when "Language Learning & Technology" was launched with my paper entitled "CALL in the year 2000: Still in search of research paradigms?" The point of my 1997 paper was to suggest the potential value of research on second language learning for the study…

Functionality for learning networks: lessons learned from social web applications

NARCIS (Netherlands)

Berlanga, Adriana; Sloep, Peter; Brouns, Francis; Van Rosmalen, Peter; Bitter-Rijpkema, Marlies; Koper, Rob

2007-01-01

Berlanga, A. J., Sloep, P., Brouns, F., Van Rosmalen, P., Bitter-Rijpkema, M., & Koper, R. (2007). Functionality for learning networks: lessons learned from social web applications. Proceedings of the ePortfolio 2007 Conference. October, 18-19, 2007, Maastricht, The Netherlands. [See also

Development of Web-Based Learning Application for Generation Z

Science.gov (United States)

Hariadi, Bambang; Dewiyani Sunarto, M. J.; Sudarmaningtyas, Pantjawati

2016-01-01

This study aimed to develop a web-based learning application as a form of learning revolution. The form of learning revolution includes the provision of unlimited teaching materials, real time class organization, and is not limited by time or place. The implementation of this application is in the form of hybrid learning by using Google Apps for…

Machine learning in radiation oncology theory and applications

CERN Document Server

El Naqa, Issam; Murphy, Martin J

2015-01-01

​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided rad

78 FR 68814 - Call for Applications for the International Buyer Program Calendar Year 2015

Science.gov (United States)

2013-11-15

... overseas markets and corresponds to marketing opportunities as identified by ITA. Previous international... overseas. In addition, the applicant should describe in detail the international marketing program to be... DEPARTMENT OF COMMERCE International Trade Administration [Docket No.: 131030913-3913-01] Call for...

A SIMULTANEOUS MOBILE E-LEARNING ENVIRONMENT AND APPLICATION

Directory of Open Access Journals (Sweden)

Hasan KARAL

2010-04-01

Full Text Available The purpose of the present study was to design a mobile learning environment that enables the use of a teleconference application used in simultaneous e-learning with mobile devices and to evaluate this mobile learning environment based on students’ views. With the mobile learning environment developed in the study, the students are able to follow a teleconference application realized by using appropriate mobile devices. The study was carried out with 8 post-graduate students enrolled in Karadeniz Technical University (KTU, Department of Computer Education and Instructional Technologies (CEIT, Graduate School of Natural and Applied Science. The students utilized this teleconference application using mobile devices supporting internet access and Adobe Flash technology. Of the 8 students, 4 accessed the system using EDGE technology and 4 used wireless internet technology. At the end of the application, the audio and display were delayed by 4-5 seconds with EDGE technology, and were delayed by 7-8 seconds with wireless internet technology. Based on the students’ views, it was concluded that the environment had some deficiencies in terms of quality, especially in terms of the screen resolution. Despite this, the students reported that this environment could provide more flexibility in terms of space and time when compared to other simultaneous distance education applications. Although the environment enables interaction, in particular, the problem of resolution caused by screen size is a disadvantage for the system. When this mobile learning application is compared to conventional education environments, it was found that mobile learning does have a role in helping the students overcome the problems of participating in learning activities caused by time and space constraints.

Factors Affecting the Normalization of CALL in Chinese Senior High Schools

Science.gov (United States)

He, Bi; Puakpong, Nattaya; Lian, Andrew

2015-01-01

With the development of Information Technology, increasing attention has been paid to Computer Assisted Language Learning (CALL). Meanwhile, increasing enthusiasm is seen for English learning and teaching in China. Yet, few research studies have focused on the normalization of CALL in ethnically diverse areas. In response to this research gap,…

DESIGN AND DEVELOPMENT OF MOBILE LEARNING APPLICATIONS USING DRUPAL

Directory of Open Access Journals (Sweden)

N.M.A.E.D Wirastuti

2010-07-01

Full Text Available The growth of the mobile industry is an important aspect in the link of the global village. Another aspect is theInternet. The introduction of VoIP, video conferencing, emailing and TV reviewing also support the communicationbecoming much easier. The Internet becomes a reliable source of information; Users learn more from the Internetthan anywhere else. Therefore, there are many educational institutions publishing their learning material on theInternet. So that e-learning becomes an essential learning method now days. Student can access the learning materialeverywhere, every time. While the mobile industry offers many 3G services, mobile operators still lack of theapplication that allowing users to access learning material while on the move. Mobile learning is an excellentsolution to solve this problem. This will be supported by mobile features improvement, cheaper and faster data rates.This paper gives a simple idea of developing mobile learning where users can access learning material in similarway to blackboard via mobile devices, called blackboard mobile.

76 FR 54428 - Call for Applications for the International Buyer Program Calendar Year 2013

Science.gov (United States)

2011-09-01

... in detail the international marketing program to be conducted for the event, and explain how efforts... DEPARTMENT OF COMMERCE International Trade Administration [Docket No. 110729450-1450-01] Call for Applications for the International Buyer Program Calendar Year 2013 AGENCY: International Trade Administration...

Factors Hindering the Integration of CALL in a Tertiary Institution

Directory of Open Access Journals (Sweden)

Izaham Shah Ismail

2008-12-01

Full Text Available The field of Computer Assisted Language Learning (CALL is a field that is constantly evolving as it is very much dependent on the advancement of computer technologies. With new technologies being invented almost every day, experts in the field are looking for ways to apply these new technologies in the language classroom. Despite that, teachers are said to be slow at adopting technology in their classrooms and language teachers, whether at schools or tertiary institutions, are no exception. This study attempts to investigate the factors that hinder ESL instructors at an institution of higher learning from integrating CALL in their lessons. Interviews were conducted with five ESL instructors and results revealed that factors which hinder them from integrating CALL in their teaching are universal factors such as knowledge in technology and pedagogy, computer facilities and resources, absence of exemplary integration of CALL, personal beliefs on language teaching, views on the role of a computers as teacher, and evaluation of learning outcomes.

Online Social Media Applications for Constructivism and Observational Learning

OpenAIRE

Lydia Mbati

2013-01-01

Web 2.0 technologies have a range of possibilities for fostering constructivist learning and observational learning. This is due to the available applications which allow for synchronous and asynchronous interaction and the sharing of knowledge between users. Web 2.0 tools include online social media applications which have potential pedagogical benefits. Despite these potential benefits, there is inadequate utilization of online social media applications in learning management systems for pe...

Applications of Deep Learning and Reinforcement Learning to Biological Data.

Science.gov (United States)

Mahmud, Mufti; Kaiser, Mohammed Shamim; Hussain, Amir; Vassanelli, Stefano

2018-06-01

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence. The growth in computational power accompanied by faster and increased data storage, and declining computing costs have already allowed scientists in various fields to apply these techniques on data sets that were previously intractable owing to their size and complexity. This paper provides a comprehensive survey on the application of DL, RL, and deep RL techniques in mining biological data. In addition, we compare the performances of DL techniques when applied to different data sets across various application domains. Finally, we outline open issues in this challenging research area and discuss future development perspectives.

Zebra finch mates use their forebrain song system in unlearned call communication.

Science.gov (United States)

Ter Maat, Andries; Trost, Lisa; Sagunsky, Hannes; Seltmann, Susanne; Gahr, Manfred

2014-01-01

Unlearned calls are produced by all birds whereas learned songs are only found in three avian taxa, most notably in songbirds. The neural basis for song learning and production is formed by interconnected song nuclei: the song control system. In addition to song, zebra finches produce large numbers of soft, unlearned calls, among which "stack" calls are uttered frequently. To determine unequivocally the calls produced by each member of a group, we mounted miniature wireless microphones on each zebra finch. We find that group living paired males and females communicate using bilateral stack calling. To investigate the role of the song control system in call-based male female communication, we recorded the electrical activity in a premotor nucleus of the song control system in freely behaving male birds. The unique combination of acoustic monitoring together with wireless brain recording of individual zebra finches in groups shows that the neuronal activity of the song system correlates with the production of unlearned stack calls. The results suggest that the song system evolved from a brain circuit controlling simple unlearned calls to a system capable of producing acoustically rich, learned vocalizations.

Student use and pedagogical impact of a mobile learning application.

Science.gov (United States)

Teri, Saskia; Acai, Anita; Griffith, Douglas; Mahmoud, Qusay; Ma, David W L; Newton, Genevieve

2014-01-01

Mobile learning (m-learning) is a relevant innovation in teaching and learning in higher education. A mobile app called NutriBiochem was developed for use in biochemistry and nutrition education for students in a second year Biochemistry and Metabolism course. NutriBiochem was accessed through smartphones, tablets, or computers. Students were surveyed upon completion of the final exam (n = 88). Survey questions assessed frequency of use, motivations for use, and perceptions of app usefulness. The pedagogical impact of NutriBiochem was evaluated by measuring the relationship between frequency of use and final course grade. Just over half of the students used the app, and ∼80% of users accessed the app moderately or infrequently. Smartphones were the most common device and the preferred device on which to access the app. There were no statistical differences in mean final grade between users and nonusers. Students with higher comfort levels with technology accessed the app more broadly than those with lower level of comfort with technology. Over 75% of students agreed that NutriBiochem was a useful learning tool, but fewer (∼45%) felt it helped them perform better in the course. The findings of this study are important, as they suggest that NutriBiochem is an effective study tool for students who are comfortable with technology, and access it regularly. Overall, the use of mobile applications in science education has been shown to be: 1) effective in enhancing students' learning experience; 2) relevant and important as an emergent method of learning given modern pressures facing higher education; and, 3) met with positive student attitudes and perceptions in terms of adopting and using such technology for educational purposes. © 2013 by The International Union of Biochemistry and Molecular Biology.

Learning theories application in nursing education

Science.gov (United States)

Aliakbari, Fatemeh; Parvin, Neda; Heidari, Mohammad; Haghani, Fariba

2015-01-01

Learning theories are the main guide for educational systems planning in the classroom and clinical training included in nursing. The teachers by knowing the general principles of these theories can use their knowledge more effectively according to various learning situations. In this study, Eric, Medline, and Cochrane databases were used for articles in English and for the Persian literature, Magiran, Iran doc, Iran medex, and Sid databases were used with the help of keywords including social cognitive learning, learning theory, behavioral theory, cognitive theory, constructive theory, and nursing education. The search period was considered from 1990 to 2012. Some related books were also studied about each method, its original vision, the founders, practical application of the training theory, especially training of nursing and its strengths and weaknesses. Behaviorists believe that learning is a change in an observable behavior and it happens when the communication occurs between the two events, a stimulus and a response. Among the applications of this approach is the influence on the learner's emotional reactions. Among the theories of this approach, Thorndike and Skinner works are subject to review and critique. Cognitive psychologists unlike the behaviorists believe that learning is an internal process objective and they focus on thinking, understanding, organizing, and consciousness. Fundamentalists believe that learners should be equipped with the skills of inquiry and problem solving in order to learn by the discovery and process of information. Among this group, we will pay attention to analyze Wertheimer, Brunner, Ausubel theories, Ganyeh information processing model, in addition to its applications in nursing education. Humanists in learning pay attention to the feelings and experiences. Carl Rogers support the retention of learning-centered approach and he is believed to a semantic continuum. At the other end of the continuum, experiential learning is

Learning theories application in nursing education.

Science.gov (United States)

Aliakbari, Fatemeh; Parvin, Neda; Heidari, Mohammad; Haghani, Fariba

2015-01-01

Learning theories are the main guide for educational systems planning in the classroom and clinical training included in nursing. The teachers by knowing the general principles of these theories can use their knowledge more effectively according to various learning situations. In this study, Eric, Medline, and Cochrane databases were used for articles in English and for the Persian literature, Magiran, Iran doc, Iran medex, and Sid databases were used with the help of keywords including social cognitive learning, learning theory, behavioral theory, cognitive theory, constructive theory, and nursing education. The search period was considered from 1990 to 2012. Some related books were also studied about each method, its original vision, the founders, practical application of the training theory, especially training of nursing and its strengths and weaknesses. Behaviorists believe that learning is a change in an observable behavior and it happens when the communication occurs between the two events, a stimulus and a response. Among the applications of this approach is the influence on the learner's emotional reactions. Among the theories of this approach, Thorndike and Skinner works are subject to review and critique. Cognitive psychologists unlike the behaviorists believe that learning is an internal process objective and they focus on thinking, understanding, organizing, and consciousness. Fundamentalists believe that learners should be equipped with the skills of inquiry and problem solving in order to learn by the discovery and process of information. Among this group, we will pay attention to analyze Wertheimer, Brunner, Ausubel theories, Ganyeh information processing model, in addition to its applications in nursing education. Humanists in learning pay attention to the feelings and experiences. Carl Rogers support the retention of learning-centered approach and he is believed to a semantic continuum. At the other end of the continuum, experiential learning is

Criteria for Evaluating a Game-Based CALL Platform

Science.gov (United States)

Ní Chiaráin, Neasa; Ní Chasaide, Ailbhe

2017-01-01

Game-based Computer-Assisted Language Learning (CALL) is an area that currently warrants attention, as task-based, interactive, multimodal games increasingly show promise for language learning. This area is inherently multidisciplinary--theories from second language acquisition, games, and psychology must be explored and relevant concepts from…

Learning curve tool applications in DOE materials management activities

International Nuclear Information System (INIS)

Lipinski, A.

1994-01-01

This paper will examine the application of learning curve theory, an economic theory that quantifies cost savings over time in a labor intensive process. Learning curve theory has been traditionally applied to a production process. This paper examines the application of learning curve theory in cost estimating of waste characterization in storage at a DOE facility

Learning Words through Multimedia Application

DEFF Research Database (Denmark)

Zhang, Chun

2007-01-01

  This study explores the relevance of multimedia application in relation to vocabulary acquisition in the classroom of Chinese as a foreign language. The herein depicted application refers to the computer-assisted implicit word-learning, wherein the Danish students built hypertexts to acquire...... meanings of unknown words aiming to research and to enlarging Chinese vocabulary.  ...

Call Centre- Computer Telephone Integration

Directory of Open Access Journals (Sweden)

Dražen Kovačević

2012-10-01

Full Text Available Call centre largely came into being as a result of consumerneeds converging with enabling technology- and by the companiesrecognising the revenue opportunities generated by meetingthose needs thereby increasing customer satisfaction. Regardlessof the specific application or activity of a Call centre, customersatisfaction with the interaction is critical to the revenuegenerated or protected by the Call centre. Physical(v, Call centreset up is a place that includes computer, telephone and supervisorstation. Call centre can be available 24 hours a day - whenthe customer wants to make a purchase, needs information, orsimply wishes to register a complaint.

An Evaluation Framework for CALL

Science.gov (United States)

McMurry, Benjamin L.; Williams, David Dwayne; Rich, Peter J.; Hartshorn, K. James

2016-01-01

Searching prestigious Computer-assisted Language Learning (CALL) journals for references to key publications and authors in the field of evaluation yields a short list. The "American Journal of Evaluation"--the flagship journal of the American Evaluation Association--is only cited once in both the "CALICO Journal and Language…

Learning in Non-Stationary Environments Methods and Applications

CERN Document Server

Lughofer, Edwin

2012-01-01

Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences.   Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...

Language teacher education in CALL: history and perspectives

Directory of Open Access Journals (Sweden)

Ana Cristina Biondo Salomão

2013-01-01

Full Text Available Over the last years, the new technologies have changed the way we relate to information and communicate with other people, which has brought on impact to foreign language teaching and learning, and, consequently, to the area of foreign language teacher education. The abbreviation CALL (Computer Assisted Language Learning has been used to designate the processes of language teaching and learning with the use of computers, and language teacher education in CALL to name teacher education for and with the use of new technologies, since a number of authors point to the interdependence of both processes. We intend in this article to present an overview of the literature of the area of language teacher education in CALL nowadays and discuss issues related to the use of new technologies concerning its integration to teacher education and the functional and institutional roles to be taken. We also present two proposals of teacher education with the use of new technologies which are being implemented and at the same time studied in Brazil, which we believe have essential elements for the development of language teachers for and with the use of new technologies currently.

Introduction to spiking neural networks: Information processing, learning and applications.

Science.gov (United States)

Ponulak, Filip; Kasinski, Andrzej

2011-01-01

The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

Kernel Methods for Machine Learning with Life Science Applications

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie

Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

Analysis of applications suitable for mobile learning of preschool children

OpenAIRE

Stoimenovski, Aleksandar; Kraleva, Radoslava; Kralev, Velin

2016-01-01

This article considers the use of mobile learning in Bulgarian education by young children. The most used mobile operating systems are analyzed. Also some of the most used existing applications suitable for mobile learning of preschool children are presented and classified. Keywords: Mobile applications for preschool children, mobile learning.

Don't Call It School

Science.gov (United States)

Robb, Daniel

2006-01-01

"Homeschooling," "deschooling," and "unschooling" are commonly used terms in the alternative-education world, but each lacks specificity. In this article, the author describes what he discovered during several visits to North Star. Known officially as North Star: Self-Directed Learning for Teens, it is not as structured as a so-called "free"…

The application of learning theory in horse training

DEFF Research Database (Denmark)

McLean, Andrew N.; Christensen, Janne Winther

2017-01-01

The millennia-old practices of horse training markedly predate and thus were isolated from the mid-twentieth century revelation of animal learning processes. From this standpoint, the progress made in the application and understanding of learning theory in horse training is reviewed including...... on the correct application of learning theory, and safety and welfare benefits for people and horses would follow. Finally it is also proposed that the term ‘conflict theory’ be taken up in equitation science to facilitate diagnosis of training-related behaviour disorders and thus enable the emergence...

Learning Programming Technique through Visual Programming Application as Learning Media with Fuzzy Rating

Science.gov (United States)

Buditjahjanto, I. G. P. Asto; Nurlaela, Luthfiyah; Ekohariadi; Riduwan, Mochamad

2017-01-01

Programming technique is one of the subjects at Vocational High School in Indonesia. This subject contains theory and application of programming utilizing Visual Programming. Students experience some difficulties to learn textual learning. Therefore, it is necessary to develop media as a tool to transfer learning materials. The objectives of this…

Web Applications That Promote Learning Communities in Today's Online Classrooms

Science.gov (United States)

Reigle, Rosemary R.

2015-01-01

The changing online learning environment requires that instructors depend less on the standard tools built into most educational learning platforms and turn their focus to use of Open Educational Resources (OERs) and free or low-cost commercial applications. These applications permit new and more efficient ways to build online learning communities…

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics

OpenAIRE

HUANG, SHUJUN; CAI, NIANGUANG; PACHECO, PEDRO PENZUTI; NARANDES, SHAVIRA; WANG, YANG; XU, WAYNE

2017-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better ...

Student Teachers and CALL: Personal and Pedagogical Uses and Beliefs

Science.gov (United States)

Hlas, Anne Cummings; Conroy, Kelly; Hildebrandt, Susan A.

2017-01-01

The student teaching semester affords teacher candidates the chance to apply what they have learned during their teacher preparation coursework. Therefore, it can be a prime opportunity for student teachers to use technology for their own language learning and to implement computer assisted language learning (CALL) in their instruction. This study…

The Effect of Computer Assisted Language Learning (CALL) on Performance in the Test of English for International Communication (TOEIC) Listening Module

Science.gov (United States)

van Han, Nguyen; van Rensburg, Henriette

2014-01-01

Many companies and organizations have been using the Test of English for International Communication (TOEIC) for business and commercial communication purpose in Vietnam and around the world. The present study investigated the effect of Computer Assisted Language Learning (CALL) on performance in the Test of English for International Communication…

Project Management Methodology for the Development of M-Learning Web Based Applications

Directory of Open Access Journals (Sweden)

Adrian VISOIU

2010-01-01

Full Text Available M-learning web based applications are a particular case of web applications designed to be operated from mobile devices. Also, their purpose is to implement learning aspects. Project management of such applications takes into account the identified peculiarities. M-learning web based application characteristics are identified. M-learning functionality covers the needs of an educational process. Development is described taking into account the mobile web and its influences over the analysis, design, construction and testing phases. Activities building up a work breakdown structure for development of m-learning web based applications are presented. Project monitoring and control techniques are proposed. Resources required for projects are discussed.

Usability testing of e-learning: an approach incorporating co-discovery and think-aloud

CSIR Research Space (South Africa)

Adebesin, TF

2009-06-01

Full Text Available Computer applications developed to support learning in the cognitive domains are quite different from commercial transaction processing applications. The unique nature of such applications calls for different methods for evaluating their usability...

The influence of affordances on user preferences for multimedia language learning applications

OpenAIRE

Uther, M; Banks, AP

2016-01-01

This study investigates the influence of sensory and cognitive affordances on the user experience of mobile devices for multimedia language learning applications. A primarily audio-based language learning application – ‘Vowel Trainer’, was chosen against a comparison, text and picture-based language learning application – ‘Learn English for Taxi Drivers’. Impressions of the two applications were assessed on two different devices that have virtually the same interface and identical sound outpu...

The Artificial Intelligence Applications to Learning Programme.

Science.gov (United States)

Williams, Noel

1992-01-01

Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

Conformal prediction for reliable machine learning theory, adaptations and applications

CERN Document Server

Balasubramanian, Vineeth; Vovk, Vladimir

2014-01-01

The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detecti

Application of machine learning methods in bioinformatics

Science.gov (United States)

Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

2018-05-01

Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

Investigating the Effectiveness of Computer-Assisted Language Learning (CALL) Using Google Documents in Enhancing Writing--A Study on Senior 1 Students in a Chinese Independent High School

Science.gov (United States)

Ambrose, Regina Maria; Palpanathan, Shanthini

2017-01-01

Computer-assisted language learning (CALL) has evolved through various stages in both technology as well as the pedagogical use of technology (Warschauer & Healey, 1998). Studies show that the CALL trend has facilitated students in their English language writing with useful tools such as computer based activities and word processing. Students…

Investigation of Drive-Reinforcement Learning and Application of Learning to Flight Control

Science.gov (United States)

1993-08-01

WL-TR-93-1153 INVESTIGATION OF DRIVE-REINFORCEMEN% LEARNING AND APPLICATION OF LEARNING TO FLIGHT CONTROL AD-A277 442 WALTER L. BAKER (ED), STEPHEN ...OF LEARNING TO FUIGHT CONTROL PE 62204 ___ ___ ___ ___ __ ___ ___ ___ ___ ___ ___ __ PR 2003 6. AUTHOR(S) TA 05 WALTER L. BAKER (ED), STEPHEN C. ATKINS...34 Computers and Thought, E. A. Freigenbaum and J. Feldman (eds.), Mc- Graw Hill, New York, (1959). [19] Holland, J. H., "Escaping Brittleness: The Possibility

76 Computer Assisted Language Learning (CALL) Software ...

African Journals Online (AJOL)

Ike Odimegwu

combination with other factors which may enhance or ameliorate the ... form of computer-based learning which carries two important features: .... To take some commonplace examples, a ... photographs, and even full-motion video clips.

77 FR 61740 - Call for Applications for the International Buyer Program-Calendar Years 2014 and 2015

Science.gov (United States)

2012-10-11

... should describe in detail the international marketing program to be conducted for the event, and explain... DEPARTMENT OF COMMERCE International Trade Administration [Docket No. 120913451-2451-01] Call for Applications for the International Buyer Program-- Calendar Years 2014 and 2015 AGENCY: International Trade...

Mobile Assisted Language Learning: Review of the Recent Applications of Emerging Mobile Technologies

Science.gov (United States)

Yang, Jaeseok

2013-01-01

As mobile computing technologies have been more powerful and inclusive in people's daily life, the issue of mobile assisted language learning (MALL) has also been widely explored in CALL research. Many researches on MALL consider the emerging mobile technologies have considerable potentials for the effective language learning. This review study…

Designing Adaptive Web Applications

DEFF Research Database (Denmark)

Dolog, Peter

2008-01-01

Learning system to study a discipline. In business to business interaction, different requirements and parameters of exchanged business requests might be served by different services from third parties. Such applications require certain intelligence and a slightly different approach to design. Adpative web......The unique characteristic of web applications is that they are supposed to be used by much bigger and diverse set of users and stakeholders. An example application area is e-Learning or business to business interaction. In eLearning environment, various users with different background use the e......-based applications aim to leave some of their features at the design stage in the form of variables which are dependent on several criteria. The resolution of the variables is called adaptation and can be seen from two perspectives: adaptation by humans to the changed requirements of stakeholders and dynamic system...

Machine Learning applications in CMS

CERN Multimedia

CERN. Geneva

2017-01-01

Machine Learning is used in many aspects of CMS data taking, monitoring, processing and analysis. We review a few of these use cases and the most recent developments, with an outlook to future applications in the LHC Run III and for the High-Luminosity phase.

77 FR 74828 - Call for Applications for the International Buyer Program Calendar Years 2014 and 2015

Science.gov (United States)

2012-12-18

... DEPARTMENT OF COMMERCE International Trade Administration [Docket No. 120913451-2681-02] Call for Applications for the International Buyer Program Calendar Years 2014 and 2015 AGENCY: International Trade... the DOC and trade show organizers to benefit U.S. firms exhibiting at selected events and provides...

Learning Application of Astronomy Based Augmented Reality using Android Platform

Science.gov (United States)

Maleke, B.; Paseru, D.; Padang, R.

2018-02-01

Astronomy is a branch of science involving observations of celestial bodies such as stars, planets, nebular comets, star clusters, and galaxies as well as natural phenomena occurring outside the Earth’s atmosphere. The way of learning of Astronomy is quite varied, such as by using a book or observe directly with a telescope. But both ways of learning have shortcomings, for example learning through books is only presented in the form of interesting 2D drawings. While learning with a telescope requires a fairly expensive cost to buy the equipment. This study will present a more interesting way of learning from the previous one, namely through Augmented Reality (AR) application using Android platform. Augmented Reality is a combination of virtual world (virtual) and real world (real) made by computer. Virtual objects can be text, animation, 3D models or videos that are combined with the actual environment so that the user feels the virtual object is in his environment. With the use of the Android platform, this application makes the learning method more interesting because it can be used on various Android smartphones so that learning can be done anytime and anywhere. The methodology used in making applications is Multimedia Lifecycle, along with C # language for AR programming and flowchart as a modelling tool. The results of research on some users stated that this application can run well and can be used as an alternative way of learning Astronomy with more interesting.

Model-based machine learning.

Science.gov (United States)

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

Developing Deep Learning Applications for Life Science and Pharma Industry.

Science.gov (United States)

Siegismund, Daniel; Tolkachev, Vasily; Heyse, Stephan; Sick, Beate; Duerr, Oliver; Steigele, Stephan

2018-06-01

Deep Learning has boosted artificial intelligence over the past 5 years and is seen now as one of the major technological innovation areas, predicted to replace lots of repetitive, but complex tasks of human labor within the next decade. It is also expected to be 'game changing' for research activities in pharma and life sciences, where large sets of similar yet complex data samples are systematically analyzed. Deep learning is currently conquering formerly expert domains especially in areas requiring perception, previously not amenable to standard machine learning. A typical example is the automated analysis of images which are typically produced en-masse in many domains, e. g., in high-content screening or digital pathology. Deep learning enables to create competitive applications in so-far defined core domains of 'human intelligence'. Applications of artificial intelligence have been enabled in recent years by (i) the massive availability of data samples, collected in pharma driven drug programs (='big data') as well as (ii) deep learning algorithmic advancements and (iii) increase in compute power. Such applications are based on software frameworks with specific strengths and weaknesses. Here, we introduce typical applications and underlying frameworks for deep learning with a set of practical criteria for developing production ready solutions in life science and pharma research. Based on our own experience in successfully developing deep learning applications we provide suggestions and a baseline for selecting the most suited frameworks for a future-proof and cost-effective development. © Georg Thieme Verlag KG Stuttgart · New York.

Machine Learning in Radiology: Applications Beyond Image Interpretation.

Science.gov (United States)

Lakhani, Paras; Prater, Adam B; Hutson, R Kent; Andriole, Kathy P; Dreyer, Keith J; Morey, Jose; Prevedello, Luciano M; Clark, Toshi J; Geis, J Raymond; Itri, Jason N; Hawkins, C Matthew

2018-02-01

Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside of image interpretation long before a fully functional "machine radiologist" is implemented in practice. Here, we describe an overview of machine learning, its application to radiology and other domains, and many cases of use that do not involve image interpretation. We hope that better understanding of these potential applications will help radiology practices prepare for the future and realize performance improvement and efficiency gains. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Videogame-Like Applications to Enhance Autonomous Learning

Science.gov (United States)

Berns, Anke; Valero-Franco, Concepción

2013-01-01

This paper presents the results of an ongoing study which has been carried out with a group of German Foreign Language students at the University of Cadiz since 2012. The purpose of the study was to analyze the impact of videogame-like applications on foreign language learning and their motivational potential to increase learning beyond the…

75 FR 78988 - Post-2014 Resource Pool-Loveland Area Projects, Allocation Procedures and Call for Applications

Science.gov (United States)

2010-12-17

... Administration (Western), a Federal power marketing agency of the Department of Energy (DOE), is publishing this... customers and for other appropriate purposes as determined by Western. These allocation procedures and call for applications, in conjunction with the Loveland Area Projects (LAP) Final Post-1989 Marketing Plan...

“Computer Assisted Language Learning” (CALL

Directory of Open Access Journals (Sweden)

Nazlı Gündüz

2005-10-01

Full Text Available This article will provide an overview of computers; an overview of the history of CALL, itspros and cons, the internet, World Wide Web, Multimedia, and research related to the uses of computers in the language classroom. Also, it also aims to provide some background for the beginnerson using the Internet in language classes today. It discusses some of the common types of Internetactivities that are being used today, what the minimum requirements are for using the Internet forlanguage learning, and some easy activities you can adapt for your classes. Some special terminology related to computers will also be used in this paper. For example, computer assisted language learning(CALL refers to the sets of instructions which need to be loaded into the computer for it to be able to work in the language classroom. It should be borne in mind that CALL does not refer to the use of acomputer by a teacher to type out a worksheet or a class list or preparing his/her own teaching alone.Hardware refers to any computer equipment used, including the computer itself, the keyboard, screen (or the monitor, the disc-drive, and the printer. Software (computer programs refers to the sets of instructions which need to be loaded into the computer for it to be able to work.

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

Science.gov (United States)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Visual Learning in Application of Integration

Science.gov (United States)

Bt Shafie, Afza; Barnachea Janier, Josefina; Bt Wan Ahmad, Wan Fatimah

Innovative use of technology can improve the way how Mathematics should be taught. It can enhance student's learning the concepts through visualization. Visualization in Mathematics refers to us of texts, pictures, graphs and animations to hold the attention of the learners in order to learn the concepts. This paper describes the use of a developed multimedia courseware as an effective tool for visual learning mathematics. The focus is on the application of integration which is a topic in Engineering Mathematics 2. The course is offered to the foundation students in the Universiti Teknologi of PETRONAS. Questionnaire has been distributed to get a feedback on the visual representation and students' attitudes towards using visual representation as a learning tool. The questionnaire consists of 3 sections: Courseware Design (Part A), courseware usability (Part B) and attitudes towards using the courseware (Part C). The results showed that students demonstrated the use of visual representation has benefited them in learning the topic.

Machine learning for epigenetics and future medical applications.

Science.gov (United States)

Holder, Lawrence B; Haque, M Muksitul; Skinner, Michael K

2017-07-03

Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review.

The Dialectical Development of "Storytelling" Learning Organizations: A Case Study of a Public Research University

Science.gov (United States)

Hillon, Yue Cai; Boje, David M.

2017-01-01

Purpose: Calls for dialectical learning process model development in learning organizations have largely gone unheeded, thereby limiting conceptual understanding and application in the field. This paper aims to unify learning organization theory with a new understanding of Hegelian dialectics to trace the development of the storytelling learning…

Beehive: A Software Application for Synchronous Collaborative Learning

Science.gov (United States)

Turani, Aiman; Calvo, Rafael A.

2006-01-01

Purpose: The purpose of this paper is to describe Beehive, a new web application framework for designing and supporting synchronous collaborative learning. Design/methodology/approach: Our web engineering approach integrates educational design expertise into a technology for building tools for collaborative learning activities. Beehive simplifies…

Application of the Experiential Learning Cycle in Learning from a Business Simulation Game

Science.gov (United States)

Ahn, Jung-Hoon

2008-01-01

The purpose of this study was to investigate the effects of engaging students in Kolb's experiential learning cycle on facilitating students' simulation game performance and knowledge application skills in learning with a business simulation game. A sample was drawn from a population of business-major undergraduate students at the School of…

Generalized SMO algorithm for SVM-based multitask learning.

Science.gov (United States)

Cai, Feng; Cherkassky, Vladimir

2012-06-01

Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be naturally separated into several groups, and incorporating this group information into learning may improve generalization. Recently, Vapnik proposed a general approach to formalizing such problems, known as "learning with structured data" and its support vector machine (SVM) based optimization formulation called SVM+. Liang and Cherkassky showed the connection between SVM+ and multitask learning (MTL) approaches in machine learning, and proposed an SVM-based formulation for MTL called SVM+MTL for classification. Training the SVM+MTL classifier requires the solution of a large quadratic programming optimization problem which scales as O(n(3)) with sample size n. So there is a need to develop computationally efficient algorithms for implementing SVM+MTL. This brief generalizes Platt's sequential minimal optimization (SMO) algorithm to the SVM+MTL setting. Empirical results show that, for typical SVM+MTL problems, the proposed generalized SMO achieves over 100 times speed-up, in comparison with general-purpose optimization routines.

Using a collaborative Mobile Augmented Reality learning application (CoMARLA) to improve Improve Student Learning

Science.gov (United States)

Hanafi, Hafizul Fahri bin; Soh Said, Che; Hanee Ariffin, Asma; Azlan Zainuddin, Nur; Samsuddin, Khairulanuar

2016-11-01

This study was carried out to improve student learning in ICT course using a collaborative mobile augmented reality learning application (CoMARLA). This learning application was developed based on the constructivist framework that would engender collaborative learning environment, in which students could learn collaboratively using their mobile phones. The research design was based on the pretest posttest control group design. The dependent variable was students’ learning performance after learning, and the independent variables were learning method and gender. Students’ learning performance before learning was treated as the covariate. The sample of the study comprised 120 non-IT (non-technical) undergraduates, with the mean age of 19.5. They were randomized into two groups, namely the experimental and control group. The experimental group used CoMARLA to learn one of the topics of the ICT Literacy course, namely Computer System; whereas the control group learned using the conventional approach. The research instrument used was a set of multiple-choice questions pertaining to the above topic. Pretesting was carried out before the learning sessions, and posttesting was performed after 6 hours of learning. Using the SPSS, Analysis of Covariance (ANCOVA) was performed on the data. The analysis showed that there were main effects attributed to the learning method and gender. The experimental group outperformed the control group by almost 9%, and male students outstripped their opposite counterparts by as much as 3%. Furthermore, an interaction effect was also observed showing differential performances of male students based on the learning methods, which did not occur among female students. Hence, the tool can be used to help undergraduates learn with greater efficacy when contextualized in an appropriate setting.

Machine learning for epigenetics and future medical applications

OpenAIRE

Holder, Lawrence B.; Haque, M. Muksitul; Skinner, Michael K.

2017-01-01

ABSTRACT Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems w...

Virtual Learning Environments on the Go: CALL Meets MALL

Science.gov (United States)

Arús Hita, Jorge

2016-01-01

This paper presents "Eating out," a Moodle-based digital learning resource for English as a Foreign Language (EFL) teaching that can be run both on computers and mobile devices. It is argued that Mobile Assisted Language Learning (MALL) resources do not necessarily need to be specifically designed for such platforms. Rather, a carefully…

Practical Applications and Experiences in K-20 Blended Learning Environments

Science.gov (United States)

Kyei-Blankson, Lydia, Ed.; Ntuli, Esther, Ed.

2014-01-01

Learning environments continue to change considerably and is no longer confined to the face-to-face classroom setting. As learning options have evolved, educators must adopt a variety of pedagogical strategies and innovative technologies to enable learning. "Practical Applications and Experiences in K-20 Blended Learning Environments"…

Integrating CALL into an Iranian EAP Course: Constraints and Affordances

Science.gov (United States)

Mehran, Parisa; Alizadeh, Mehrasa

2015-01-01

Iranian universities have recently displayed a growing interest in integrating Computer-Assisted Language Learning (CALL) into teaching/learning English. The English for Academic Purposes (EAP) context, however, is not keeping pace with the current changes since EAP courses are strictly text-based and exam-oriented, and little research has thus…

Gaze Awareness in Agent-Based Early-Childhood Learning Application

OpenAIRE

Akkil , Deepak; Dey , Prasenjit; Salian , Deepshika; Rajput , Nitendra

2017-01-01

Part 6: Interaction with Children; International audience; Use of technological devices for early childhood learning is increasing. Now, kindergarten and primary school children use interactive applications on mobile phones and tablet computers to support and complement classroom learning. With increase in cognitive technologies, there is further potential to make such applications more engaging by understanding the user context. In this paper, we present the Little Bear, a gaze aware pedagog...

Learning e-Learning

Directory of Open Access Journals (Sweden)

Gabriel ZAMFIR

2009-01-01

Full Text Available What You Understand Is What Your Cognitive Integrates. Scientific research develops, as a native environment, knowledge. This environment consists of two interdependent divisions: theory and technology. First division occurs as a recursive research, while the second one becomes an application of the research activity. Over time, theories integrate methodologies and technology extends as infrastructure. The engine of this environment is learning, as the human activity of knowledge work. The threshold term of this model is the concepts map; it is based on Bloom’ taxonomy for the cognitive domain and highlights the notion of software scaffolding which is grounded in Vygotsky’s Social Development Theory with its major theme, Zone of Proximal Development. This article is designed as a conceptual paper, which analyzes specific structures of this type of educational research: the model reflects a foundation for a theory and finally, the theory evolves as groundwork for a system. The outcomes of this kind of approach are the examples, which are, theoretically, learning outcomes, and practically exist as educational objects, so-called e-learning.

Machine learning paradigms applications in recommender systems

CERN Document Server

Lampropoulos, Aristomenis S

2015-01-01

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and ...

Employee Learning Theories and Their Organizational Applications

Directory of Open Access Journals (Sweden)

Abdussalaam Iyanda Ismail

2017-12-01

Full Text Available Empirical evidence identifies that organizational success hinges on employees with the required knowledge, skills, and abilities and that employees’ effectiveness at learning new skills and knowledge is connected with the kind of learning technique the organization adopts. Given this, this work explored employee learning theories and their organizational applications. Using far reaching literature survey and extensive theoretical and logical argument and exposition. This paper revealed that cognitive-based approaches, non-cognitive approach and need-based approaches play vital roles in shrinking the occurrence of unwanted behaviors and upturning the occurrence of desired behaviors in the organization. Proper application of the theories can induce positive employee behaviors such as task performance and organizational citizenship behavior and consequently enhance both individual and organizational performance. This work has hopefully contributed to the enrichment of the existing relevant literature and served as a useful guide for stakeholders on how they can stimulate positive employee behaviors and the consequent enhanced organizational performance.

MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS

OpenAIRE

Jerzy Balicki; Waldemar Korłub

2017-01-01

In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because ...

ARLearn - Open source mobile application platform for learning

NARCIS (Netherlands)

Börner, Dirk; Ternier, Stefaan; Klemke, Roland; Schmitz, Birgit; Kalz, Marco; Tabuenca, Bernardo; Specht, Marcus

2013-01-01

Börner, D., Ternier, S., Klemke, R., Schmitz, B., Kalz, M., Tabuenca, B., & Specht, M. (2013). ARLearn - Open source mobile application platform for learning. In D. Hernández-Leo et al. (Eds.), Scaling up Learning for Sustained Impact. Proceedings of the 8th European Conference on Technology

An experimental result of estimating an application volume by machine learning techniques.

Science.gov (United States)

Hasegawa, Tatsuhito; Koshino, Makoto; Kimura, Haruhiko

2015-01-01

In this study, we improved the usability of smartphones by automating a user's operations. We developed an intelligent system using machine learning techniques that periodically detects a user's context on a smartphone. We selected the Android operating system because it has the largest market share and highest flexibility of its development environment. In this paper, we describe an application that automatically adjusts application volume. Adjusting the volume can be easily forgotten because users need to push the volume buttons to alter the volume depending on the given situation. Therefore, we developed an application that automatically adjusts the volume based on learned user settings. Application volume can be set differently from ringtone volume on Android devices, and these volume settings are associated with each specific application including games. Our application records a user's location, the volume setting, the foreground application name and other such attributes as learning data, thereby estimating whether the volume should be adjusted using machine learning techniques via Weka.

Reinforcement learning improves behaviour from evaluative feedback

Science.gov (United States)

Littman, Michael L.

2015-05-01

Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial intelligence problem in a microcosm because learning algorithms must act autonomously to perform well and achieve their goals. Partly driven by the increasing availability of rich data, recent years have seen exciting advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology, leading to increasing applicability to real-life problems.

Application-Driven Educational Game to Assist Young Children in Learning English Vocabulary

Science.gov (United States)

Chen, Zhi-Hong; Lee, Shu-Yu

2018-01-01

This paper describes the development of an educational game, named My-Pet-Shop, to enhance young children's learning of English vocabulary. The educational game is underpinned by an application-driven model, which consists of three components: application scenario, subject learning, and learning regulation. An empirical study is further conducted…

The Implementation of Mobile Learning in Outdoor Education: Application of

Science.gov (United States)

Lai, Hsin-Chih; Chang, Chun-Yen; Li, Wen-Shiane; Fan, Yu-Lin; Wu, Ying-Tien

2013-01-01

This study presents an m-learning method that incorporates Integrated Quick Response (QR) codes. This learning method not only achieves the objectives of outdoor education, but it also increases applications of Cognitive Theory of Multimedia Learning (CTML) (Mayer, 2001) in m-learning for practical use in a diverse range of outdoor locations. When…

Applications of Deep Learning in Biomedicine.

Science.gov (United States)

Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

2016-05-02

Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

Digital Communication Applications in the Online Learning Environment

Science.gov (United States)

Lambeth, Krista Jill

2011-01-01

Scope and method of study. The purpose of this study was for the researcher to obtain a better understanding of the online learning environment, to explore the various ways online class instructors have incorporated digital communication applications to try and provide learner-centered online learning environments, and to examine students'…

Nonpasserine bird produces soft calls and pays retaliation cost

OpenAIRE

Paweł Ręk; Tomasz S. Osiejuk

2011-01-01

Low-amplitude vocalizations produced during aggressive encounters, courtship, or both (quiet/soft songs) have been described for many species of song-learning passerines; however, such signals have not been studied among nonlearning birds. During aggressive interactions, apart from using the broadcast call, male corncrakes (Crex crex) produce a low-amplitude, gurgling--mewing call, which appears to be equivalent to soft songs of songbirds. Previous studies have shown that low-amplitude vocali...

Learning Vue.js 2 learn how to build amazing and complex reactive web applications easily with Vue.js

CERN Document Server

Filipova, Olga

2016-01-01

About This Book Learn how to propagate DOM changes across the website without writing extensive jQuery callbacks code. Learn how to achieve reactivity and easily compose views with Vue.js and understand what it does behind the scenes. Explore the core features of Vue.js with small examples, learn how to build dynamic content into preexisting web applications, and build Vue.js applications from scratch. Who This Book Is For This book is perfect for novice web developer seeking to learn new technologies or frameworks and also for webdev gurus eager to enrich their experience. Whatever your level of expertise, this book is a great introduction to the wonderful world of reactive web apps. What You Will Learn Build a fully functioning reactive web application in Vue.js from scratch. The importance of the MVVM architecture and how Vue.js compares with other frameworks such as Angular.js and React.js. How to bring reactivity to an existing static application using Vue.js. How to use p...

COMPUTER ASSISTED LANGUAGE LEARNING (CALL: ITS PROSPECTS AND CONSEQUENCES FOR NIGERIAN LANGUAGES / L'APPRENTISSAGE DE LA LANGUE À L'AIDE DES TICE: PERSPECTIVES ET CONSÉQUENCES POUR LES LANGUES NIGÉRIENNES / ÎNVĂŢAREA LIMBII CU TIC: PERSPECTIVE ŞI CONSECINŢE PENTRU LIMBILE NIGERIENE

Directory of Open Access Journals (Sweden)

Oyè Táíwò

2014-11-01

Full Text Available The shift in language learning today is from “classical teaching environment” to “self-learning environment”. In Nigeria today, although CALL efforts are made by schools and individuals, these effort are geared towards the English language learning other than Nigerian languages. This paper seeks to explore the development of CALL for Nigerian Languages and the challenges of running CALL in Nigeria. The results indicate that CALL for Nigerian languages is needed and should be promoted. CALL in Nigerian can only be successful if the shortcomings of CALL are recognized and the mitigating circumstances tackled. Adequate arrangements must be made to manage CALL and Teacher-Assisted language learning (TALL in consideration of the socioeconomic impact of CALL on the teachers Nigerian languages. The attitude of Nigerians towards Nigerian languages should be positive. The government, corporate bodies and individuals must intervene in CALL programs in schools so as to control the resulting high tuition fee.

Call Forecasting for Inbound Call Center

Directory of Open Access Journals (Sweden)

Peter Vinje

2009-01-01

Full Text Available In a scenario of inbound call center customer service, the ability to forecast calls is a key element and advantage. By forecasting the correct number of calls a company can predict staffing needs, meet service level requirements, improve customer satisfaction, and benefit from many other optimizations. This project will show how elementary statistics can be used to predict calls for a specific company, forecast the rate at which calls are increasing/decreasing, and determine if the calls may stop at some point.

A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles

Directory of Open Access Journals (Sweden)

Adrian Carrio

2017-01-01

Full Text Available Deep learning is recently showing outstanding results for solving a wide variety of robotic tasks in the areas of perception, planning, localization, and control. Its excellent capabilities for learning representations from the complex data acquired in real environments make it extremely suitable for many kinds of autonomous robotic applications. In parallel, Unmanned Aerial Vehicles (UAVs are currently being extensively applied for several types of civilian tasks in applications going from security, surveillance, and disaster rescue to parcel delivery or warehouse management. In this paper, a thorough review has been performed on recent reported uses and applications of deep learning for UAVs, including the most relevant developments as well as their performances and limitations. In addition, a detailed explanation of the main deep learning techniques is provided. We conclude with a description of the main challenges for the application of deep learning for UAV-based solutions.

Self-enhancement learning: target-creating learning and its application to self-organizing maps.

Science.gov (United States)

Kamimura, Ryotaro

2011-05-01

In this article, we propose a new learning method called "self-enhancement learning." In this method, targets for learning are not given from the outside, but they can be spontaneously created within a neural network. To realize the method, we consider a neural network with two different states, namely, an enhanced and a relaxed state. The enhanced state is one in which the network responds very selectively to input patterns, while in the relaxed state, the network responds almost equally to input patterns. The gap between the two states can be reduced by minimizing the Kullback-Leibler divergence between the two states with free energy. To demonstrate the effectiveness of this method, we applied self-enhancement learning to the self-organizing maps, or SOM, in which lateral interactions were added to an enhanced state. We applied the method to the well-known Iris, wine, housing and cancer machine learning database problems. In addition, we applied the method to real-life data, a student survey. Experimental results showed that the U-matrices obtained were similar to those produced by the conventional SOM. Class boundaries were made clearer in the housing and cancer data. For all the data, except for the cancer data, better performance could be obtained in terms of quantitative and topological errors. In addition, we could see that the trustworthiness and continuity, referring to the quality of neighborhood preservation, could be improved by the self-enhancement learning. Finally, we used modern dimensionality reduction methods and compared their results with those obtained by the self-enhancement learning. The results obtained by the self-enhancement were not superior to but comparable with those obtained by the modern dimensionality reduction methods.

How To Design a Mobile Application to Enhance Teaching and Learning?

Directory of Open Access Journals (Sweden)

Dothang Truong

2014-05-01

Full Text Available The rapid growth of mobile devices, especially smart phones, has changed the way instructors deliver instructions and students learn class materials. Many universities initiate promoting economic transformation by working to eliminate barriers to educational attainment through incorporating new technologies to enhance the delivery of instructions and student learning outcomes. The purpose of this research is to explore the usage of mobile applications in higher education and develop an application to help college students understand better the class materials, and thereby, enhance their learning outcomes. The detailed description, design, and interface of the application are presented along with dissemination plan.

Mobile Application Development for Quran Verse Recognition and Interpretations

Directory of Open Access Journals (Sweden)

Maha Alqahtani

2015-01-01

Full Text Available Mobile learning or “m-learning” is the process of learning when learners are not at a fixed location or time and can exploit the advantage of learning opportunities using mobile technologies. Nowadays, speech recognition is being used in many mobile applications. Speech recognition helps people to interact with the device as if were they talking to another person. This technology helps people to learn anything using computers by promoting self-study over extended periods of time. The objective of this study is focusing on designing and developing a mobile application for the Arabic recognition of spoken Quranic verses. The application is suitable for Android-based devices. The application is called Say Quran and is available on Google Play Store. Moreover, this paper presents the results of a preliminary experimentation to gather feedback from students regarding the developed application

Ensemble Machine Learning Methods and Applications

CERN Document Server

Ma, Yunqian

2012-01-01

It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

The use of mobile learning application to the fundament of digital electronics course

Science.gov (United States)

Rakhmawati, L.; Firdha, A.

2018-01-01

A new trend in e-learning is known as Mobile Learning. Learning through mobile phones have become part of the educative process. Thus, the purposes of this study are to develop a mobile application for the Fundament of Digital Electronics course that consists of number systems operation, logic gates, and Boolean Algebra, and to assess the readiness, perceptions, and effectiveness of students in the use of mobile devices for learning in the classroom. This research uses Research and Development (R&D) method. The design used in this research, by doing treatment in one class and observing by using Android-based mobile application instructional media. The result obtained from this research shows that the test has 80 % validity aspect, 82 % of the user from senior high school students gives a positive response in using the application of mobile learning, and based on the result of post-test, 90, 90% students passed the exam. At last, it can be concluded that the use of the mobile learning application makes the learning process more effective when it is used in the teaching-learning process.

Make a 21st century phone call

CERN Multimedia

Katarina Anthony

2014-01-01

Want to avoid roaming charges? Click to call anyone at CERN? How about merging your CERN landline with your existing smartphone? That's all easily done with Lync, CERN's new opt-in service that can take your calls to the next level.   The Lync application on Windows (left) and iPhone (right). Lync unites CERN's traditional telephone service with the digital sphere. "Lync gives you the gift of mobility, by letting you access your CERN landline on the go," explains Pawel Grzywaczewski, service manager of the Lync system. "Once you've registered your CERN telephone with the service, you can run the Lync application and make calls from a range of supported devices. No matter where you are in the world - be it simply out to lunch or off at an international conference - you can make a CERN call as though you were in the office. All you need is an Internet connection!" Following a recent upgrade, CERN's Lync service now has...

Machine learning in manufacturing: advantages, challenges, and applications

Directory of Open Access Journals (Sweden)

Thorsten Wuest

2016-01-01

Full Text Available The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means available. One area, which saw fast pace developments in terms of not only promising results but also usability, is machine learning. Promising an answer to many of the old and new challenges of manufacturing, machine learning is widely discussed by researchers and practitioners alike. However, the field is very broad and even confusing which presents a challenge and a barrier hindering wide application. Here, this paper contributes in presenting an overview of available machine learning techniques and structuring this rather complicated area. A special focus is laid on the potential benefit, and examples of successful applications in a manufacturing environment.

Bidirectional extreme learning machine for regression problem and its learning effectiveness.

Science.gov (United States)

Yang, Yimin; Wang, Yaonan; Yuan, Xiaofang

2012-09-01

It is clear that the learning effectiveness and learning speed of neural networks are in general far slower than required, which has been a major bottleneck for many applications. Recently, a simple and efficient learning method, referred to as extreme learning machine (ELM), was proposed by Huang , which has shown that, compared to some conventional methods, the training time of neural networks can be reduced by a thousand times. However, one of the open problems in ELM research is whether the number of hidden nodes can be further reduced without affecting learning effectiveness. This brief proposes a new learning algorithm, called bidirectional extreme learning machine (B-ELM), in which some hidden nodes are not randomly selected. In theory, this algorithm tends to reduce network output error to 0 at an extremely early learning stage. Furthermore, we find a relationship between the network output error and the network output weights in the proposed B-ELM. Simulation results demonstrate that the proposed method can be tens to hundreds of times faster than other incremental ELM algorithms.

HTML5 for Mobile Applications for Learning

NARCIS (Netherlands)

Glahn, Christian

2011-01-01

Glahn, C. (2011). HTML5 for Mobile Applications for Learning. Presentation held at the Blueteam-Workshop, Bluetea/Stepco-group. February, 21, 2011, Heerlen, The Netherlands: Open University of the Netherlands, CELSTEC.

Design, Development, and Evaluation of a Mobile Learning Application for Computing Education

Science.gov (United States)

Oyelere, Solomon Sunday; Suhonen, Jarkko; Wajiga, Greg M.; Sutinen, Erkki

2018-01-01

The study focused on the application of the design science research approach in the course of developing a mobile learning application, MobileEdu, for computing education in the Nigerian higher education context. MobileEdu facilitates the learning of computer science courses on mobile devices. The application supports ubiquitous, collaborative,…

ZooQuest: A mobile game-based learning application for fifth graders

NARCIS (Netherlands)

Veenhof, G.; Sandberg, J.A.C.; Maris, M.G.

2012-01-01

This study examined ZooQuest, a mobile game that supported fifth graders in the process of learning English as a second language. ZooQuest embedded the Mobile English Learning (MEL) application and was compared to MEL as a stand-alone application. Two groups were compared in a quasi-experimental

Designing Learning for Co-Creation

DEFF Research Database (Denmark)

Gnaur, Dorina; Larsen-Nielsen, Marie

2017-01-01

Designing learning for co-creation - conceptual and practical considerations, Dorina Gnaur and Inger Marie Larsen-Nielsen explore the practical educational point of view. The question they are posing themselves is: how can higher and further education (HE) educate for co-creation, that is, provide...... educational frameworks that respond to the societal demand for co-creation, particularly within the public welfare sector? First, they focus on which organisational and individual requirements an HE learning design should take into account in order to support the diffusion of co-creation competences....... Then they argue for the need to integrate these considerations in the learning design and demonstrate a practical application in the form of a didactical design. They call this a hybrid learning design, in that it takes advantage of technological developments to mediate co-creative learning in multiple learning...

Learning analytics fundaments, applications, and trends : a view of the current state of the art to enhance e-learning

CERN Document Server

2017-01-01

This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art. By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.

Orion: a web-based application designed to monitor resident and fellow performance on-call.

Science.gov (United States)

Itri, Jason N; Kim, Woojin; Scanlon, Mary H

2011-10-01

Radiology residency and fellowship training provides a unique opportunity to evaluate trainee performance and determine the impact of various educational interventions. We have developed a simple software application (Orion) using open-source tools to facilitate the identification and monitoring of resident and fellow discrepancies in on-call preliminary reports. Over a 6-month period, 19,200 on-call studies were interpreted by 20 radiology residents, and 13,953 on-call studies were interpreted by 25 board-certified radiology fellows representing eight subspecialties. Using standard review macros during faculty interpretation, each of these reports was classified as "agreement", "minor discrepancy", and "major discrepancy" based on the potential to impact patient management or outcome. Major discrepancy rates were used to establish benchmarks for resident and fellow performance by year of training, modality, and subspecialty, and to identify residents and fellows demonstrating a significantly higher major discrepancy rate compared with their classmates. Trends in discrepancies were used to identify subspecialty-specific areas of increased major discrepancy rates in an effort to tailor the didactic and case-based curriculum. A series of missed-case conferences were developed based on trends in discrepancies, and the impact of these conferences is currently being evaluated. Orion is a powerful information technology tool that can be used by residency program directors, fellowship programs directors, residents, and fellows to improve radiology education and training.

Editorial: Practical applications of KM systems for organizational learning

Directory of Open Access Journals (Sweden)

Murali Raman

2013-12-01

Full Text Available Modern-day organizations are subject to continuous change. To remain relevant and competitive, it is imperative that organizations cultivate and foster learning capabilities. This special issue focus on examining practical applications of knowledge management systems in support of organizational learning efforts.

Modern machine learning techniques and their applications in cartoon animation research

CERN Document Server

Yu, Jun

2013-01-01

The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations

MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS

Directory of Open Access Journals (Sweden)

Jerzy Balicki

2017-03-01

Full Text Available In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming. To obtain a competitive advantage, machine learning can be used for the management of self-organizing cloud computing systems performing calculations for business. Also the use of selected economic self-organizing distributed systems has been described, including some testing methods of predicting borrower reliability. Finally, some conclusions and directions for further research have been proposed.

Utilizing the Quantile Regression to Explore the Determinants on the Application of E-Learning

OpenAIRE

Quang Linh Huynh; Thuy Lan Le Thi

2014-01-01

In this research, the quantile regression is applied to investigate the affecting factors associated with the application of e-learning. The findings provide a comprehensive picture about the relationships between the application of e-learning and its determinants. It sheds light on these complicated relationships that, at the different quantiles of the conditional distribution of e-learning adopting levels, the influence of the determinants on the application of e-learning is different. More...

Sex differences in the representation of call stimuli in a songbird secondary auditory area.

Science.gov (United States)

Giret, Nicolas; Menardy, Fabien; Del Negro, Catherine

2015-01-01

Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM), while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer, and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird's own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of information about the

Sex differences in the representation of call stimuli in a songbird secondary auditory area

Directory of Open Access Journals (Sweden)

Nicolas eGiret

2015-10-01

Full Text Available Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM, while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird’s own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of

e-Learning applications for radiological protection training

International Nuclear Information System (INIS)

Gonzalez, F.; Gomez-Arguello, B.; Callejo, J. L.

2003-01-01

The unattended training, through e-learning platforms, offers advantages in comparison with the traditional attended training, such as, freedom to study when, where and how the trance desires, the student is learning customization, a continuous self evaluation of the learning process and the rhythm of study, etc. To explore the possibilities of the radiological protection training in a WEB site, a first application for External Workers has been developed. The high number of students, their geographical dispersion and their different level of knowledge and experience arise attended training limitations in this area. In this article, the WEB course Basic Radiological Protection is presented and the results, preliminarily conclusions and lesson learnt are analysed. (Author) 7 refs

Application of ICT supported learning in fluid mechanics

DEFF Research Database (Denmark)

Brohus, Henrik; Svidt, Kjeld

2004-01-01

of tools for knowledge transfer facilitates deep understanding and increases learning efficiency. Air flow is by nature invisible and represents a further challenge in the effort of providing sufficient understanding of typical flow patterns and behaviour of room air flow. An example of visualisation......This paper focuses on the application of ICT, Information & Communication Technology, supported learning in the area of fluid mechanics education. Taking a starting point in a course in Ventilation Technology, including room air flow and contaminant distribution, it explains how ICT may be used...... actively in the learning environment to increase efficiency in the learning process. The paper comprises past experiences and lessons learnt as well as prospect for future development in the area. A model is presented that describes a high efficiency learning environment where ICT plays an important role...

Rethinking the lecture: the application of problem based learning methods to atypical contexts.

Science.gov (United States)

Rogal, Sonya M M; Snider, Paul D

2008-05-01

Problem based learning is a teaching and learning strategy that uses a problematic stimulus as a means of motivating and directing students to develop and acquire knowledge. Problem based learning is a strategy that is typically used with small groups attending a series of sessions. This article describes the principles of problem based learning and its application in atypical contexts; large groups attending discrete, stand-alone sessions. The principles of problem based learning are based on Socratic teaching, constructivism and group facilitation. To demonstrate the application of problem based learning in an atypical setting, this article focuses on the graduate nurse intake from a teaching hospital. The groups are relatively large and meet for single day sessions. The modified applications of problem based learning to meet the needs of atypical groups are described. This article contains a step by step guide of constructing a problem based learning package for large, single session groups. Nurse educators facing similar groups will find they can modify problem based learning to suit their teaching context.

Interdisciplinary Research at the Intersection of CALL, NLP, and SLA: Methodological Implications from an Input Enhancement Project

Science.gov (United States)

Ziegler, Nicole; Meurers, Detmar; Rebuschat, Patrick; Ruiz, Simón; Moreno-Vega, José L.; Chinkina, Maria; Li, Wenjing; Grey, Sarah

2017-01-01

Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The…

Evaluating the Motivational Impact of CALL Systems: Current Practices and Future Directions

Science.gov (United States)

Bodnar, Stephen; Cucchiarini, Catia; Strik, Helmer; van Hout, Roeland

2016-01-01

A major aim of computer-assisted language learning (CALL) is to create computer environments that facilitate students' second language (L2) acquisition. To achieve this aim, CALL employs technological innovations to create novel types of language practice. Evaluations of the new practice types serve the important role of distinguishing effective…

The Activity Theory Approach to Learning

Directory of Open Access Journals (Sweden)

Ritva Engeström

2014-12-01

Full Text Available In this paper the author offers a practical view of the theory-grounded research on education action. She draws on studies carried out at the Center for Research on Activity, Development and Learning (CRADLE at the University of Helsinki in Finland. In its work, the Center draws on cultural-historical activity theory (CHAT and is well-known for the theory of Expansive Learning and its more practical application called Developmental Work Research (DWR. These approaches are widely used to understand professional learning and have served as a theoreticaland methodological foundation for studies examining change and professional development in various human activities.

Call mimicry by eastern towhees and its significance in relation to auditory learning

Science.gov (United States)

Jon S. Greenlaw; Clifford E. Shackelford; Raymond E. Brown

1998-01-01

The authors document cases of eastern towhees (Pipilo erythrophthalmus) using mimicked alarm calls from three presumptive models (blue jay (Cyanocitta cristata), brown thrasher (Toxostoma rufum), and American robin (Turdus migratorius)). In four instances, male towhees employed heterospecific calls without substitution in their own call repertoires. Three birds (New...

Comparison the Application of PBL (Project Based Learning and PBL (Problem Based Learning Learning Model on Online Marketing Subjects

Directory of Open Access Journals (Sweden)

Agnes Dini Mardani

2017-09-01

Full Text Available Purpose of this study are (1 the application of learning PjBL with PBL to improve study results students, (2 assessing the domain affective, cognitive, and psychomotor, (3 the difference study results use the PjBL with PBL to improve study results students. The research is research quantitative and including research apparent experiment (quasi eksperiment by taking sample class two classes X PM 1 as a class experiment and class X PM 2 as a class control. Research instruments used for data collection namely: (1 tests to pretes and postest used to determine the cognitive assessment, (2 sheets observation affective, (3 sheets of the process for the psychomotor. The trial research instruments use the validity and reabilitas. Analysis techniques data using: (1 test a prerequisite analysis consisting of normality test and the homogeneity (2 T test unpaired which ended with the help of computer programs spss. Based on the result of this research can be concluded that: (1 the application of PjBL (Project Based Learning and PBL (Problem Based Learning should be conducted well in accordance syntax learning, (2 assessing the cognitive students have a difference and class experiment having an average higher than class control, (3 assessing the results affective students have a difference and on the application of PjBL is better than PBL.

Analysis of jitter due to call-level fluctuations

NARCIS (Netherlands)

M.R.H. Mandjes (Michel)

2005-01-01

textabstractIn communication networks used by constant bit rate applications, call-level dynamics (i.e., entering and leaving calls) lead to fluctuations in the load, and therefore also fluctuations in the delay (jitter). By intentionally delaying the packets at the destination, one can transform

Using Semantic Similarity In Automated Call Quality Evaluator For Call Centers

Directory of Open Access Journals (Sweden)

Ria A. Sagum

2015-08-01

Full Text Available Conversation between the agent and client are being evaluated manually by a quality assurance officer QA. This job is only one of the responsibilities being done by a QA and particularly eat ups a lot of time for them which lead to late evaluation results that may cause untimely response of the company to concerns raised by their clients. This research developed an application software that automates and evaluates the quality assurance in business process outsourcing companies or customer service management implementing sentence similarity. The developed system includes two modules speaker diarization which includes transcription and question and answer extraction and similarity checker which checks the similarity between the extracted answer and the answer of the call center agent to a question. The system was evaluated for Correctness of the extracted answers and accurateness of the evaluation for a particular call. Audio conversations were tested for the accuracy of the transcription module which has an accuracy of 27.96. The Precision Recall and F-measure of the extracted answer was tested as 78.03 96.26 and 86.19 respectively. The Accuracy of the system in evaluating a call is 70.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation.

Science.gov (United States)

Mansoor, Awais; Cerrolaza, Juan J; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-11

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM 1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

The Game Embedded CALL System to Facilitate English Vocabulary Acquisition and Pronunciation

Science.gov (United States)

Young, Shelley Shwu-Ching; Wang, Yi-Hsuan

2014-01-01

The aim of this study is to make a new attempt to explore the potential of integrating game strategies with automatic speech recognition technologies to provide learners with individual opportunities for English pronunciation learning. The study developed the Game Embedded CALL (GeCALL) system with two activities for on-line speaking practice. For…

Active Learning in the Era of Big Data

Energy Technology Data Exchange (ETDEWEB)

Jamieson, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Davis, IV, Warren L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-10-01

Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.

Neutrality as Obstructionist in Academic Activism: Calling Bullshit

Science.gov (United States)

Rose, Barbara J.

2018-01-01

In this essay, the author uses experiences as a teacher educator and learning from a historically significant activism movement to (a) compare values in activism-centered and education-centered organizations, (b) posit ways that the concept of neutrality weakens academic activism, and (c) call for teacher education curricula and practices that…

Young doctors' problem solving strategies on call may be improved.

Science.gov (United States)

Michelsen, Jens; Malchow-Møller, Axel; Charles, Peder; Eika, Berit

2013-03-01

The first year following graduation from medical school is challenging as learning from books changes to workplace-based learning. Analysis and reflection on experience may ease this transition. We used Significant Event Analysis (SEA) as a tool to explore what pre-registration house officers (PRHOs) consider successful and problematic events, and to identify what problem-solving strategies they employ. A senior house officer systematically led the PRHO through the SEA of one successful and one problematic event following a night call. The PRHO wrote answers to questions about diagnosis, what happened, how he or she contributed and what knowledge-gaining activities the PRHO would prioritise before the next call. By using an inductive, thematic data analysis, we identified five problem-solving strategies: non-analytical reasoning, analytical reasoning, communication with patients, communication with colleagues and professional behaviour. On average, 1.5 strategies were used in the successful events and 1.2 strategies in the problematic events. Most PRHOs were unable to suggest activities other than reading textbooks. SEA was valuable for the identification of PRHOs' problem-solving strategies in a natural setting. PRHOs should be assisted in increasing their repertoire of strategies, and they should also be helped to "learn to learn" as they were largely unable to point to new learning strategies. not relevant. not relevant.

Applications of machine learning in cancer prediction and prognosis.

Science.gov (United States)

Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Duolingo: A Mobile Application to Assist Second Language Learning

Science.gov (United States)

Nushi, Musa; Eqbali, Mohamad Hosein

2017-01-01

Technology is changing the way languages are taught and learned. It has provided teachers with new facilities and approaches to teaching that can stimulate learners' interest while challenging their intellect (Blake, 2013, 2016; Stanley, 2013). As an example, new smartphone applications are being developed that make the task of learning ever more…

Enhancing Children's Outdoor Learning Experiences with a Mobile Application

Science.gov (United States)

Rikala, Jenni

2015-01-01

This paper examines how a mobile learning application can enhance children's outdoor learning experiences. The study draws upon empirical evidence gathered in one case study conducted in a Finnish primary school setting in the fall of 2012. The data were collected with student and teacher surveys. The case study indicated that the mobile…

Applications of Augmented Reality in Informal Science Learning Sites: a Review

Science.gov (United States)

Goff, Eric E.; Mulvey, Kelly Lynn; Irvin, Matthew J.; Hartstone-Rose, Adam

2018-05-01

The importance of increasing interest in the STEM disciplines has been noted in a number of recent national reports. While many previous studies have focused on such efforts inside of the formal classroom, comparatively few have looked closely at informal learning environments. We investigate the innovative use of technology in informal learning by reviewing research on the incorporation of augmented reality (AR) at exhibit-based informal science education (ISE) settings in the literature. We report on the common STEM-focused topics that are covered by current AR applications for ISE learning, as well as the different devices used to support these applications. Additionally, we report on the prevalence of positive learning outcomes and engagement factors commonly associated with the use AR applications in informal environments. This review aims to foster continued development and implementation of AR technology in exhibit-based ISE settings by informing the community of recent findings and promoting additional rigorous research for the future.

The learning styles of orthopedic residents, faculty, and applicants at an academic program.

Science.gov (United States)

Richard, Raveesh Daniel; Deegan, Brian Francis; Klena, Joel Christian

2014-01-01

To train surgeons effectively, it is important to understand how they are learning. The Kolb Learning Style Inventory (LSI) is based on the theory of experiential learning, which divides the learning cycle into 4 stages: active experimentation (AE), abstract conceptualization (AC), concrete experience, and reflective observation. The purpose of this investigation was to assess the learning styles of orthopedic residents, faculty, and applicants at an east-coast residency program. A total of 90 Kolb LSI, Version 3.1 surveys, and demographic questionnaires were distributed to all residency applicants, residents, and faculty at an academic program. Data collected included age, sex, type of medical school (MD or DO), foreign medical graduate status, and either year since college graduation, postgraduate year level (residents only), or years since completion of residency (faculty only). Seventy-one completed Kolb LSI surveys (14 residents, 14 faculty members, and 43 applicants) were recorded and analyzed for statistical significance. The most prevalent learning style among all participants was converging (53.5%), followed by accommodating (18.3%), diverging (18.3%), and assimilating (9.9%) (p = 0.13). The applicant and resident groups demonstrated a high tendency toward AE followed by AC. The faculty group demonstrated a high tendency toward AC followed by AE. None of the 24 subjects who were 26 years or under had assimilating learning styles, in significant contrast to the 12% of 27- to 30-year-olds and 18% of 31 and older group (p learning style involves problem solving and decision making, with the practical application of ideas and the use of hypothetical-deductive reasoning. Learning through AE decreased with age, whereas learning through AC increased. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Co-Labeling for Multi-View Weakly Labeled Learning.

Science.gov (United States)

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi

Ethical and Privacy Issues in the Design of Learning Analytics Applications

NARCIS (Netherlands)

Drachsler, Hendrik; Hoel, Tore; Cooper, Adam; Kismihok, Gabor; Berg, Alan; Scheffel, Maren; Chen, Weiqin; Ferguson, Rebecca

2017-01-01

Issues related to Ethics and Privacy have become a major stumbling block in application of Learning Analytics technologies on a large scale. Recently, the learning analytics community at large has more actively addressed the EP4LA issues, and we are now starting to see learning analytics solutions

INTEGRATING CORPUS-BASED RESOURCES AND NATURAL LANGUAGE PROCESSING TOOLS INTO CALL

Directory of Open Access Journals (Sweden)

Pascual Cantos Gomez

2002-06-01

Full Text Available This paper ainis at presenting a survey of computational linguistic tools presently available but whose potential has been neither fully considered not exploited to its full in modern CALL. It starts with a discussion on the rationale of DDL to language learning, presenting typical DDL-activities. DDL-software and potential extensions of non-typical DDL-software (electronic dictionaries and electronic dictionary facilities to DDL . An extended section is devoted to describe NLP-technology and how it can be integrated into CALL, within already existing software or as stand alone resources. A range of NLP-tools is presentcd (MT programs, taggers, lemn~atizersp, arsers and speech technologies with special emphasis on tagged concordancing. The paper finishes with a number of reflections and ideas on how language technologies can be used efficiently within the language learning context and how extensive exploration and integration of these technologies might change and extend both modern CAI,I, and the present language learning paradigiii..

THE BLENDED LEARNING OF ELECTRICITY USING LEARNING OBJECTS IN ENGINEERING

Directory of Open Access Journals (Sweden)

Lilia Maria Siqueira

2010-09-01

Full Text Available This work presents a proposal for the blended learning of Electricity education in Engineering, using resources called learning objects. The experience occurred with students enrolled on the Electrical Engineering and Computer Engineering courses at PUCPR University. It made possible the contact with interdisciplinary themes related to the study of electricity and the professional curriculum contents. The learning objects, offered during the semester, were anchored on PUCPR’s proprietary virtual educational environment, called Eureka. The students’ evaluation results showed that the study through learning objects in a virtual environment is significant for learning.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Science.gov (United States)

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

LDA merging and splitting with applications to multiagent cooperative learning and system alteration.

Science.gov (United States)

Pang, Shaoning; Ban, Tao; Kadobayashi, Youki; Kasabov, Nikola K

2012-04-01

To adapt linear discriminant analysis (LDA) to real-world applications, there is a pressing need to equip it with an incremental learning ability to integrate knowledge presented by one-pass data streams, a functionality to join multiple LDA models to make the knowledge sharing between independent learning agents more efficient, and a forgetting functionality to avoid reconstruction of the overall discriminant eigenspace caused by some irregular changes. To this end, we introduce two adaptive LDA learning methods: LDA merging and LDA splitting. These provide the benefits of ability of online learning with one-pass data streams, retained class separability identical to the batch learning method, high efficiency for knowledge sharing due to condensed knowledge representation by the eigenspace model, and more preferable time and storage costs than traditional approaches under common application conditions. These properties are validated by experiments on a benchmark face image data set. By a case study on the application of the proposed method to multiagent cooperative learning and system alternation of a face recognition system, we further clarified the adaptability of the proposed methods to complex dynamic learning tasks.

The Effect of Mobile Learning Applications on Students' Academic Achievement and Attitudes toward Mobile Learning

Science.gov (United States)

Demir, Kadir; Akpinar, Ercan

2018-01-01

This study examines the effect of mobile learning applications on undergraduate students' academic achievement, attitudes toward mobile learning and animation development levels. Quasi-experimental design was used in the study. Participants of the study were students of the Buca Faculty of Education at Dokuz Eylul University in Turkey. The…

Opportunity to Participate in ESSE 21: The 2003 Call for Participation

Science.gov (United States)

Ruzek, M.; Johnson, D. R.

2003-12-01

Earth System Science Education for the 21st Century (ESSE 21), sponsored by NASA through the Universities Space Research Association (USRA), is a collaborative undergraduate/graduate education program offering small grants to colleges and universities to engage a diverse interdisciplinary community of faculty and scientists in the development of courses, curricula and degree programs and sharing of learning resources focused on the fundamental understanding and application of Earth system principles for the classroom and laboratory. Through an expanded focus including partnerships with minority institutions, ESSE 21 is further developing broadly based courses, educational resources, electronic learning materials and degree programs that extend Earth system science concepts in both undergraduate and graduate classrooms and laboratories. These resources emphasizing the fundamentals of Earth system science advance the nation's broader agenda for improving science, technology, engineering and mathematics competency. The thrust to establish Earth system and global change science within the classrooms of colleges and universities is critical to laying and extending the foundation for knowledge-based decision making in the 21st century by both scientists and society in an effort to achieve sustainability. ESSE 21 released a Call for Participation (CFP) in the Fall of 2002 soliciting proposals from undergraduate institutions to create and adopt undergraduate and graduate level Earth system science content in courses, curricula and degree programs. In February 2003, twelve college and university teams were competitively selected through the CFP as the Year 1 and Year 2 Program participants. Eight of the participating teams are from minority institutions. The goal for all is to effect systemic change through developing Earth system science learning materials, courses, curricula, degree tracks or programs, and departments that are self-sustaining in the coming decades. ESSE

A Foreign Language Learning Application using Mobile Augmented Reality

Directory of Open Access Journals (Sweden)

Florentin-Alexandru DITA

2016-01-01

Full Text Available In this paper is described a foreign language learning application using mobile augmented reality based on gamification method and text recognition. The mobile augmented reality is a technology that extends the real world elements with 2D or 3D computer generated objects and lets the users interact with them. A Gamification system is based on different mechanisms that increase the motivation of students, due to the impact that videogames have in their emotional, cognitive and social areas. The proposed solution applies Optical Character Recognition technique, using the camera of the mobile device, in order to identify the text written on a card. The implementation combines the features of gamification system and mobile augmented reality in order to make the learning process more easy and fun. This paper aims to present the results after testing the foreign language learning application in different scenarios.

New CALL-SLA Research Interfaces for the 21st Century: Towards Equitable Multilingualism

Science.gov (United States)

Ortega, Lourdes

2017-01-01

The majority of the world is multilingual, but inequitably multilingual, and much of the world is also technologized, but inequitably so. Thus, researchers in the fields of computer-assisted language learning (CALL) and second language acquisition (SLA) would profit from considering multilingualism and social justice when envisioning new CALL-SLA…

ASR performance analysis of an experimental call routing system

CSIR Research Space (South Africa)

Modipa, T

2009-11-01

Full Text Available Call routing is an important application of Automatic Speech Recognition (ASR) technology. In this paper the authors discuss the main issues affecting the performance of a call routing system and describe the ASR component of the "Auto...

Survey on Multimedia Technologies for Mobile Learning Applications

Directory of Open Access Journals (Sweden)

Paul POCATILU

2009-01-01

Full Text Available Mobile technologies are developing very fast. This paper presents a survey on multimedia technologies for mobile learning applications, focusing on multimedia programming techniques for Windows Mobile, Symbian, and Java ME.

Application of a smartphone nurse call system for nursing care.

Science.gov (United States)

Chuang, Shu-Ting; Liu, Yi-Fang; Fu, Zi-Xuan; Liu, Kuang-Chung; Chien, Sou-Hsin; Lin, Chin-Lon; Lin, Pi-Yu

2015-02-01

Traditionally, a patient presses the nurse call button and alerts the central nursing station. This system cannot reach the primary care nurse directly. The aim of this study was to apply a new smartphone system through the cloud system and information technology that linked a smartphone and a mobile nursing station for nursing care service. A smartphone and mobile nursing station were integrated into a smartphone nurse call system through the cloud and information technology for better nursing care. Waiting time for a patient to contact the most responsible nurse was reduced from 3.8 min to 6 s. The average time for pharmacists to locate the nurse for medication problem was reduced from 4.2 min to 1.8 min by the new system. After implementation of the smartphone nurse call system, patients received a more rapid response. This improved patients' satisfaction and reduced the number of complaints about longer waiting time due to the shortage of nurses.

Developments in Interpreting Learning Curves and Applications to Energy Technology Policy

International Nuclear Information System (INIS)

Van der Zwaan, B.C.C.; Wene, C.O.

2011-01-01

The book 'Learning Curves: Theory, Models, and Applications' first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve. Chapter 23 on 'Developments in Interpreting Learning Curves and Applications to Energy Technology Policy' is written by Bob van der Zwaan and Clas-Otto Wene. In this chapter they provide some interpretations of experience and learning curves starting from three different theoretical platforms. These interpretations are aimed at explaining learning rates for different energy technologies. The ultimate purpose is to find the role that experience and learning curves can legitimately play in designing efficient government deployment programs and in analyzing the implications of different energy scenarios. The 'Component Learning' section summarizes recent work by the authors that focuses on the disaggregation of technologies in their respective components and argues that traditional learning for overall technology should perhaps be replaced by a phenomenology that recognizes learning for individual components. The 'Learning and Time' section presents an approach that departs more strongly from the conventional learning curve methodology, by suggesting that exponential growth and progress may be the deeper underlying processes behind observed learning-by-doing. Contrary to this view, the cybernetic approach presented in the 'Cybernetic Approach' section sees learning curves as expressing a fundamental property of organizations in competitive markets and applies the findings from second order cybernetics to calculate the learning rates for operationally closed systems. All three interpretations find empirical support. The 'Conclusions' section summarizes the

Developments in Interpreting Learning Curves and Applications to Energy Technology Policy

Energy Technology Data Exchange (ETDEWEB)

Van der Zwaan, B.C.C. [Energy research Centre of the Netherlands, ECN Policy Studies, Petten (Netherlands); Wene, C.O. [Wenergy, Lund (Sweden)

2011-06-15

The book 'Learning Curves: Theory, Models, and Applications' first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve. Chapter 23 on 'Developments in Interpreting Learning Curves and Applications to Energy Technology Policy' is written by Bob van der Zwaan and Clas-Otto Wene. In this chapter they provide some interpretations of experience and learning curves starting from three different theoretical platforms. These interpretations are aimed at explaining learning rates for different energy technologies. The ultimate purpose is to find the role that experience and learning curves can legitimately play in designing efficient government deployment programs and in analyzing the implications of different energy scenarios. The 'Component Learning' section summarizes recent work by the authors that focuses on the disaggregation of technologies in their respective components and argues that traditional learning for overall technology should perhaps be replaced by a phenomenology that recognizes learning for individual components. The 'Learning and Time' section presents an approach that departs more strongly from the conventional learning curve methodology, by suggesting that exponential growth and progress may be the deeper underlying processes behind observed learning-by-doing. Contrary to this view, the cybernetic approach presented in the 'Cybernetic Approach' section sees learning curves as expressing a fundamental property of organizations in competitive markets and applies the findings from second order cybernetics to calculate the learning rates for operationally closed systems. All three interpretations find empirical

E-Learning Application of Tarsier with Virtual Reality using Android Platform

Science.gov (United States)

Oroh, H. N.; Munir, R.; Paseru, D.

2017-01-01

Spectral Tarsier is a primitive primate that can only be found in the province of North Sulawesi. To study these primates can be used an e-learning application with Augmented Reality technology that uses a marker to confronted the camera computer to interact with three dimensions Tarsier object. But that application only shows tarsier object in three dimensions without habitat and requires a lot of resources because it runs on a Personal Computer. The same technology can be shown three dimensions’ objects is Virtual Reality to excess can make the user like venturing into the virtual world with Android platform that requires fewer resources. So, put on Virtual Reality technology using the Android platform that can make users not only to view and interact with the tarsiers but also the habitat. The results of this research indicate that the user can learn the Tarsier and habitat with good. Thus, the use of Virtual Reality technology in the e-learning application of tarsiers can help people to see, know, and learn about Spectral Tarsier.

eLearning in education and advanced training in neuroradiology: introduction of a web-based teaching and learning application

International Nuclear Information System (INIS)

Zajaczek, J.E.W.; Goetz, F.; Haubitz, B.; Donnerstag, F.; Becker, H.; Kupka, T.; Behrends, M.; Matthies, H.K.; Rodt, T.; Walter, G.F.

2006-01-01

New information technologies offer the possibility of major improvements in the professional education and advanced training of physicians. The web-based, multimedia teaching and learning application Schoolbook has been created and utilized for neuroradiology. Schoolbook is technically based as a content management system and is realized in a LAMP environment. The content is generated with the help of the developed system and stored in a database. The layout is defined by a PHP application, and the webpages are generated from the system. Schoolbook is realized as an authoring tool so that it can be integrated into daily practice. This enables the teacher to autonomously process the content into the web-based application which is used for lectures, seminars and self-study. A multimedia case library is the central building block of Schoolbook for neuroradiology, whereby the learner is provided with original diagnostic and therapeutic data from numerous individual cases. The user can put individual emphasis on key learning points as there are various ways to work with the case histories. Besides the case-based way of teaching and learning, a systematically structured way of dealing with the content is available. eLearning offers various opportunities for teaching and learning in academic and scientific as well as in economic contexts. Web-based applications such as Schoolbook may be beneficial not only for basic university education but also for the realization of international educational programmes such as the European Master of Medical Science with a major in neuroradiology. (orig.)

eLearning in education and advanced training in neuroradiology: introduction of a web-based teaching and learning application.

Science.gov (United States)

Zajaczek, J E W; Götz, F; Kupka, T; Behrends, M; Haubitz, B; Donnerstag, F; Rodt, T; Walter, G F; Matthies, H K; Becker, H

2006-09-01

New information technologies offer the possibility of major improvements in the professional education and advanced training of physicians. The web-based, multimedia teaching and learning application Schoolbook has been created and utilized for neuroradiology. Schoolbook is technically based as a content management system and is realized in a LAMP environment. The content is generated with the help of the developed system and stored in a database. The layout is defined by a PHP application, and the webpages are generated from the system. Schoolbook is realized as an authoring tool so that it can be integrated into daily practice. This enables the teacher to autonomously process the content into the web-based application which is used for lectures, seminars and self-study. A multimedia case library is the central building block of Schoolbook for neuroradiology, whereby the learner is provided with original diagnostic and therapeutic data from numerous individual cases. The user can put individual emphasis on key learning points as there are various ways to work with the case histories. Besides the case-based way of teaching and learning, a systematically structured way of dealing with the content is available. eLearning offers various opportunities for teaching and learning in academic and scientific as well as in economic contexts. Web-based applications such as Schoolbook may be beneficial not only for basic university education but also for the realization of international educational programmes such as the European Master of Medical Science with a major in neuroradiology.

eLearning in education and advanced training in neuroradiology: introduction of a web-based teaching and learning application

Energy Technology Data Exchange (ETDEWEB)

Zajaczek, J.E.W. [Hannover Medical School, Department of Neuroradiology (OE 8210), Hannover (Germany); Hannover Medical School, Department of Medical Informatics, Hannover (Germany); Goetz, F.; Haubitz, B.; Donnerstag, F.; Becker, H. [Hannover Medical School, Department of Neuroradiology (OE 8210), Hannover (Germany); Kupka, T.; Behrends, M.; Matthies, H.K. [Hannover Medical School, Department of Medical Informatics, Hannover (Germany); Rodt, T. [Hannover Medical School, Department of Neurosurgery, Hannover (Germany); Walter, G.F. [Medical University of Graz, Graz (Austria)

2006-09-15

New information technologies offer the possibility of major improvements in the professional education and advanced training of physicians. The web-based, multimedia teaching and learning application Schoolbook has been created and utilized for neuroradiology. Schoolbook is technically based as a content management system and is realized in a LAMP environment. The content is generated with the help of the developed system and stored in a database. The layout is defined by a PHP application, and the webpages are generated from the system. Schoolbook is realized as an authoring tool so that it can be integrated into daily practice. This enables the teacher to autonomously process the content into the web-based application which is used for lectures, seminars and self-study. A multimedia case library is the central building block of Schoolbook for neuroradiology, whereby the learner is provided with original diagnostic and therapeutic data from numerous individual cases. The user can put individual emphasis on key learning points as there are various ways to work with the case histories. Besides the case-based way of teaching and learning, a systematically structured way of dealing with the content is available. eLearning offers various opportunities for teaching and learning in academic and scientific as well as in economic contexts. Web-based applications such as Schoolbook may be beneficial not only for basic university education but also for the realization of international educational programmes such as the European Master of Medical Science with a major in neuroradiology. (orig.)

Systems configured to distribute a telephone call, communication systems, communication methods and methods of routing a telephone call to a service representative

Science.gov (United States)

Harris, Scott H.; Johnson, Joel A.; Neiswanger, Jeffery R.; Twitchell, Kevin E.

2004-03-09

The present invention includes systems configured to distribute a telephone call, communication systems, communication methods and methods of routing a telephone call to a customer service representative. In one embodiment of the invention, a system configured to distribute a telephone call within a network includes a distributor adapted to connect with a telephone system, the distributor being configured to connect a telephone call using the telephone system and output the telephone call and associated data of the telephone call; and a plurality of customer service representative terminals connected with the distributor and a selected customer service representative terminal being configured to receive the telephone call and the associated data, the distributor and the selected customer service representative terminal being configured to synchronize, application of the telephone call and associated data from the distributor to the selected customer service representative terminal.

Learning Progressions as Tools for Assessment and Learning

Science.gov (United States)

Shepard, Lorrie A.

2018-01-01

This article addresses the teaching and learning side of the learning progressions literature, calling out for measurement specialists the knowledge most needed when collaborating with subject-matter experts in the development of learning progressions. Learning progressions are one of the strongest instantiations of principles from "Knowing…

On the Edge: Intelligent CALL in the 1990s.

Science.gov (United States)

Underwood, John

1989-01-01

Examines the possibilities of developing computer-assisted language learning (CALL) based on the best of modern technology, arguing that artificial intelligence (AI) strategies will radically improve the kinds of exercises that can be performed. Recommends combining AI technology with other tools for delivering instruction, such as simulation and…

Tablets for Informal Language Learning: Student Usage and Attitudes

Science.gov (United States)

Chen, Xiao-Bin

2013-01-01

Mobile-assisted language learning (MALL), a relatively new area of CALL inquiry, is gaining more and more attention from language educators with the development of new mobile devices. Tablet computers--featuring high mobility, convenient network connectivity, and smart application extendibility--are part of a wave of the latest mobile inventions;…

Do Multimedia Applications Benefit Learning-Disabled Children?

Science.gov (United States)

Raja, B. William Dharma; Kumar, S. Praveen

2010-01-01

This paper focusses on the need and benefit of using multimedia applications to cater to the needs of children with learning disabilities. The children with special educational needs found in various schools may face difficulties in acquiring academic skills such as reading, spelling, writing, speaking, understanding, listening, thinking or…

User Acceptance of Mobile Technology: A Campus-Wide Implementation of Blackboard's Mobile™ Learn Application

Science.gov (United States)

Chen, Baiyun; Sivo, Stephen; Seilhamer, Ryan; Sugar, Amy; Mao, Jin

2013-01-01

Mobile learning is a fast growing trend in higher education. This study examined how an extended technology acceptance model (TAM) could evaluate and predict the use of a mobile application in learning. A path analysis design was used to measure the mediating effects on the use of Blackboard's Mobile™ Learn application in coursework (N = 77). The…

ELLIPS: providing web-based language learning for Higher Education in the Netherlands

NARCIS (Netherlands)

Corda, A.; Jager, S.

2004-01-01

This paper presents the overall considerations and pedagogical approach which were at the basis of the development of an innovative web-based CALL application, Ellips (Electronic Language Learning Interactive Practising System). It describes the program’s most salient features, illustrating in

Performance analysis of CRF-based learning for processing WoT application requests expressed in natural language.

Science.gov (United States)

Yoon, Young

2016-01-01

In this paper, we investigate the effectiveness of a CRF-based learning method for identifying necessary Web of Things (WoT) application components that would satisfy the users' requests issued in natural language. For instance, a user request such as "archive all sports breaking news" can be satisfied by composing a WoT application that consists of ESPN breaking news service and Dropbox as a storage service. We built an engine that can identify the necessary application components by recognizing a main act (MA) or named entities (NEs) from a given request. We trained this engine with the descriptions of WoT applications (called recipes) that were collected from IFTTT WoT platform. IFTTT hosts over 300 WoT entities that offer thousands of functions referred to as triggers and actions. There are more than 270,000 publicly-available recipes composed with those functions by real users. Therefore, the set of these recipes is well-qualified for the training of our MA and NE recognition engine. We share our unique experience of generating the training and test set from these recipe descriptions and assess the performance of the CRF-based language method. Based on the performance evaluation, we introduce further research directions.

Performance evaluation of a distance learning program.

OpenAIRE

Dailey, D. J.; Eno, K. R.; Brinkley, J. F.

1994-01-01

This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macint...

Applications of Machine Learning in Cancer Prediction and Prognosis

Directory of Open Access Journals (Sweden)

Joseph A. Cruz

2006-01-01

Full Text Available Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25% improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Adaptive Load Balancing of Parallel Applications with Multi-Agent Reinforcement Learning on Heterogeneous Systems

Directory of Open Access Journals (Sweden)

Johan Parent

2004-01-01

Full Text Available We report on the improvements that can be achieved by applying machine learning techniques, in particular reinforcement learning, for the dynamic load balancing of parallel applications. The applications being considered in this paper are coarse grain data intensive applications. Such applications put high pressure on the interconnect of the hardware. Synchronization and load balancing in complex, heterogeneous networks need fast, flexible, adaptive load balancing algorithms. Viewing a parallel application as a one-state coordination game in the framework of multi-agent reinforcement learning, and by using a recently introduced multi-agent exploration technique, we are able to improve upon the classic job farming approach. The improvements are achieved with limited computation and communication overhead.

Global learning on carbon capture and storage: A call for strong international cooperation on CCS demonstration

International Nuclear Information System (INIS)

Coninck, Heleen de; Stephens, Jennie C.; Metz, Bert

2009-01-01

Closing the gap between carbon dioxide capture and storage (CCS) rhetoric and technical progress is critically important to global climate mitigation efforts. Developing strong international cooperation on CCS demonstration with global coordination, transparency, cost-sharing and communication as guiding principles would facilitate efficient and cost-effective collaborative global learning on CCS, would allow for improved understanding of the global capacity and applicability of CCS, and would strengthen global trust, awareness and public confidence in the technology.

Acoustic model optimisation for a call routing system

CSIR Research Space (South Africa)

Kleynhans, N

2012-11-01

Full Text Available Secretary system and provides background on some application-specific ASR issues. Section III details the ASR development effort as well as corpus selection and design. Our experiments are described Fig. 1. High level AutoSecretary call flow. in Section IV... and results and a discussion are presented in Section V. Lastly, the conclusion and possible future work appear in Section VI. II. BACKGROUND A. AutoSecretary IVR System Figure 1 shows the high level call flow of the AutoSecretary call routing system...

Implementation and evaluation of LMS mobile application: scele mobile based on user-centered design

Science.gov (United States)

Banimahendra, R. D.; Santoso, H. B.

2018-03-01

The development of mobile technology is now increasing rapidly, demanding all activities including learning should be done on mobile devices. It shows that the implementation of mobile application as a learning medium needs to be done. This study describes the process of developing and evaluating the Moodle-based mobile Learning Management System (LMS) application called Student Centered e-Learning Environment (SCeLE). This study discusses the process of defining features, implementing features into the application, and evaluating the application. We define the features using user research and literature study, then we implement the application with user-centered design basis, at the last phase we evaluated the application using usability testing and system usability score (SUS). The purpose of this study is to determine the extent to which this application can help the users doing their tasks and provide recommendation for the next research and development.

Cognitive diffusion model with user-oriented context-to-text recognition for learning to promote high level cognitive processes

Directory of Open Access Journals (Sweden)

Wu-Yuin Hwang

2014-03-01

Full Text Available There is a large number of studies on how to promote students’ cognitive processes and learning achievements through various learning activities supported by advanced learning technologies. However, not many of them focus on applying the knowledge that students learn in school to solve authentic daily life problems. This study aims to propose a cognitive diffusion model called User-oriented Context-to-Text Recognition for Learning (U-CTRL to facilitate and improve students’ learning and cognitive processes from lower levels (i.e., Remember and Understand to higher levels (i.e., Apply and above through an innovative approach, called User-Oriented Context-to-Text Recognition for Learning (U-CTRL. With U-CTRL, students participate in learning activities in which they capture the learning context that can be scanned and recognized by a computer application as text. Furthermore, this study proposes the use of an innovative model, called Cognitive Diffusion Model, to investigate the diffusion and transition of students’ cognitive processes in different learning stages including pre-schooling, after-schooling, crossing the chasm, and higher cognitive processing. Finally, two cases are presented to demonstrate how the U-CTRL approach can be used to facilitate student cognition in their learning of English and Natural science.

Importance and difficulties of cooperative learning application in class teaching from teachers' perspective

Directory of Open Access Journals (Sweden)

Ilić Marina Ž.

2016-01-01

Full Text Available Based on previous knowledge of cooperative learning two approaches stand out in researching the importance of cooperative learning: a the first approach tries to examine the effects, conditions and mechanisms by which educational outcomes are realized in the application of cooperative learning; and b the second approach moves the focus towards attitudes and perceptions of teachers and students on the relevance of cooperative learning. By applying descriptive-analytical technique we conducted a research aimed at examining the opinions of teachers (N=305 about the importance and difficulties in application of cooperative learning in the context of class teaching. The results show that the teachers had positive attitudes towards the importance of cooperative learning for reaching various educational goals and socio-affective and cognitive development of students. It turned out that the opinions of the teachers were not determined by the level of their education or work experience. Additionally, it turned out that the teachers' opinions about the difficulties of application in class are due more to work organization and were not assessed from the aspect of knowledge, attitudes and convictions of the participants in the teaching process. The obtained results, although generally encouraging for teaching practice indicate a need for further advancement of this segment of the teacher's work in order to understand better the value of cooperative learning and consider more critically the difficulties for its application in classroom.

Evaluating the Effectiveness of Computer Applications in Developing English Learning

Science.gov (United States)

Whitaker, James Todd

2016-01-01

I examined the effectiveness of self-directed learning and English learning with computer applications on college students in Bangkok, Thailand, in a control-group experimental-group pretest-posttest design. The hypothesis was tested using a t test: two-sample assuming unequal variances to establish the significance of mean scores between the two…

There's a Call for You. Whenever the Phone Rings. The Helping Hand Series.

Science.gov (United States)

Nash, Claire

This booklet is intended to assist employees in the hotel and catering industry in learning to make effective use of the telephone in their jobs. The first two sections review some unpleasant experiences that a person can have when calling another organization or when receiving a business call from someone. The importance of the impression created…

Quality in e-learning

DEFF Research Database (Denmark)

Masoumi, Davoud; Lindstrom, Berner

2012-01-01

With the growing demand for e-learning along with striving for excellence associated with globalization, there are worldwide calls for enhancing and assuring quality in e-learning, specifically in the context of the developing countries. Such calls for quality enhancement, accountability, added v...

Professionals calling in lifelong learning centers

Directory of Open Access Journals (Sweden)

Victor Manuel Monteiro Seco

2013-06-01

Full Text Available Purpose: This study aims to understand how the way people see their work and the authentizotic character of their organizational climate contribute to the building of a Great Place to Work. Design/methodology/approach: This paper presents the results of a quantitative investigation that correlate the perceptions of organizational climate and the work orientations of professionals with different occupations on Portuguese lifelong education centers. Findings: The study indicates that all the core elements of an authentizotic organization contribute to explain what people potentially expect from their companies:  adequate  material  conditions  plus  a  meaningful contribution. Practical implications: The study has implications in the future for National Qualification Agency directors, education politicians and human resource managers who are responsible for providing good expectations within a healthy context of talent retention. Originality/value: The novel contribution of this paper is the finding that employee’s work orientations and authentizotic climate are related to each other in a Lifelong learning Center in the public education sector.

The Application of E-learning in Maritime Education and Training in China

OpenAIRE

Xi Chen; Xiangen Bai; Yingjie Xiao

2017-01-01

E-learning brings the third wave to Internet applications. E-learning is a new training mode with the open characteristics, which is completely different with traditional training. E-learning teaches students the specialized knowledge of theories, work experience and technology by information networks and computer hardware equipment. Students can through a variety of terminal equipment to learn anytime and anywhere, so as to improve student learning results. Maritime education and training mu...

Acquiring organizational learning norms: a contingency approach for understanding deutero learning

NARCIS (Netherlands)

Wijnhoven, Alphonsus B.J.M.

2001-01-01

'The Learning Organization' is a configuration of learning norms (called a learning prototype here), which is seldom related to varying levels of learning needs. This article assumes that organizational environmental complexity and dynamics define four learning needs levels. Consequently, four

Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers

OpenAIRE

Rosenberg, Ishai; Shabtai, Asaf; Rokach, Lior; Elovici, Yuval

2017-01-01

In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and static features (e.g., printable strings) that will be misclassified by the classifier without affecting the malware functionality. We show that this attack is effective against many classifiers due to the transferability principle between RNN variants, feed forward DNNs, and traditional machine learning classifiers such...

29 CFR 778.221 - “Call-back” pay.

Science.gov (United States)

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false âCall-backâ pay. 778.221 Section 778.221 Labor Regulations...Regular Rateâ Payments Not for Hours Worked § 778.221 “Call-back” pay. (a) General. In the interest of... payments consist of a specified number of hours' pay at the applicable straight time or overtime rates...

76 FR 36130 - Call for Candidates

Science.gov (United States)

2011-06-21

... financial information in decision-making. The Board meets in Washington, DC, for two days every other month... FEDERAL ACCOUNTING STANDARDS ADVISORY BOARD Call for Candidates AGENCY: Federal Accounting... candidates. Any applicant who provided the Federal Accounting Standards Advisory Board (FASAB or the Board...

Knowledge Representation and Reasoning in Personalized Web-Based e-Learning Applications

DEFF Research Database (Denmark)

Dolog, Peter

2006-01-01

a user inferred from user interactions with the eLeanrning systems is used to adapt o®ered learning resources and guide a learner through them. This keynote gives an overview about knowledge and rules taken into account in current adaptive eLearning prototypes when adapting learning instructions....... Adaptation is usually based on knowledge about learning esources and users. Rules are used for heuristics to match the learning resources with learners and infer adaptation decisions.......Adaptation that is so natural for teaching by humans is a challenging issue for electronic learning tools. Adaptation in classic teaching is based on observations made about students during teaching. Similar idea was employed in user-adapted (personalized) eLearning applications. Knowledge about...

e-Learning Application for Machine Maintenance Process using Iterative Method in XYZ Company

Science.gov (United States)

Nurunisa, Suaidah; Kurniawati, Amelia; Pramuditya Soesanto, Rayinda; Yunan Kurnia Septo Hediyanto, Umar

2016-02-01

XYZ Company is a company based on manufacturing part for airplane, one of the machine that is categorized as key facility in the company is Millac 5H6P. As a key facility, the machines should be assured to work well and in peak condition, therefore, maintenance process is needed periodically. From the data gathering, it is known that there are lack of competency from the maintenance staff to maintain different type of machine which is not assigned by the supervisor, this indicate that knowledge which possessed by maintenance staff are uneven. The purpose of this research is to create knowledge-based e-learning application as a realization from externalization process in knowledge transfer process to maintain the machine. The application feature are adjusted for maintenance purpose using e-learning framework for maintenance process, the content of the application support multimedia for learning purpose. QFD is used in this research to understand the needs from user. The application is built using moodle with iterative method for software development cycle and UML Diagram. The result from this research is e-learning application as sharing knowledge media for maintenance staff in the company. From the test, it is known that the application make maintenance staff easy to understand the competencies.

CopperCore: a service based approach towards implementing the IMS Learning Design specification.

NARCIS (Netherlands)

Vogten, Hubert

2006-01-01

This paper presents a service developed by the Open University of the Netherlands, called CopperCore which implements an IMS Learning Design engine as service. The overall architecture is described including a detailed description of the web service application programming interfaces.

Update on Research and Application of Problem-Based Learning in Medical Science Education

Science.gov (United States)

Fan, Chuifeng; Jiang, Biying; Shi, Xiuying; Wang, Enhua; Li, Qingchang

2018-01-01

Problem-based learning (PBL) is a unique form of pedagogy dedicated to developing students' self-learning and clinical practice skills. After several decades of development, although applications vary, PBL has been recognized all over the world and implemented by many medical schools. This review summarizes and updates the application and study of…

CLIL and CALL for a teacher’s expertise: an international training experience

Directory of Open Access Journals (Sweden)

Letizia Cinganotto

2016-07-01

Full Text Available The paper deals with the link between Content and Language Integrated Learning (CLIL and Computer Assisted Language Learning (CALL, that is the use of ICT to enhance language teaching-learning and the teaching of subject content in a foreign language. Starting from this background, the paper describes an online training initiative promoted by the authors within an international community of peers, made up of teachers, trainers and educators from all over the world, named “Techno-CLIL for EVO 2016”. The initiative was aimed at supporting and guiding participants to discover and experiment digital tools for CLIL lessons, offering the opportunity to share ideas, materials, good practices in an international perspective. Particular attention is devoted to the personal and professional enrichment and growth this training pathway may have helped the 5.000 participants to achieve.CLIL e CALL nell’expertise del docente: un’esperienza di formazione internazionaleIl contributo focalizza l’attenzione sulla correlazione tra Content and Language Integrated Learning (CLIL e Computer Assisted Language Learning (CALL, cioè l’uso delle tecnologie per una maggiore efficacia dell’insegnamento-apprendimento delle lingue o di contenuti disciplinari veicolati in lingua straniera. Partendo da questo background, il contributo descrive una iniziativa di formazione online in lingua inglese promossa dalle autrici all’interno di un contesto internazionale, costituito da una comunità di pratica di docenti, formatori, educatori di tutto il mondo, denominata “Techno-CLIL for EVO 2016”. L’iniziativa mirava a sensibilizzare e guidare i partecipanti nella scoperta e sperimentazione della didattica CLIL in modalità digitale, offrendo l’opportunità di un confronto ed uno scambio di idee, materiali, buone pratiche in una prospettiva internazionale. Particolarmente significative le ricadute che questo percorso ha comportato per i circa 5.000 partecipanti

Standardization of computer-assisted semen analysis using an e-learning application.

Science.gov (United States)

Ehlers, J; Behr, M; Bollwein, H; Beyerbach, M; Waberski, D

2011-08-01

Computer-assisted semen analysis (CASA) is primarily used to obtain accurate and objective kinetic sperm measurements. Additionally, AI centers use computer-assessed sperm concentration in the sample as a basis for calculating the number of insemination doses available from a given ejaculate. The reliability of data is often limited and results can vary even when the same CASA systems with identical settings are used. The objective of the present study was to develop a computer-based training module for standardized measurements with a CASA system and to evaluate its training effect on the quality of the assessment of sperm motility and concentration. A digital versatile disc (DVD) has been produced showing the standardization of sample preparation and analysis with the CASA system SpermVision™ version 3.0 (Minitube, Verona, WI, USA) in words, pictures, and videos, as well as the most probable sources of error. Eight test persons educated in spermatology, but with different levels of experience with the CASA system, prepared and assessed 10 aliquots from one prediluted bull ejaculate using the same CASA system and laboratory equipment before and after electronic learning (e-learning). After using the e-learning application, the coefficient of variation was reduced on average for the sperm concentration from 26.1% to 11.3% (P ≤ 0.01), and for motility from 5.8% to 3.1% (P ≤ 0.05). For five test persons, the difference in the coefficient of variation before and after use of the e-learning application was significant (P ≤ 0.05). Individual deviations of means from the group mean before e-learning were reduced compared with individual deviations from the group mean after e-learning. According to a survey, the e-learning application was highly accepted by users. In conclusion, e-learning presents an effective, efficient, and accepted tool for improvement of the precision of CASA measurements. This study provides a model for the standardization of other

Blended Learning Implementation in “Guru Pembelajar” Program

Science.gov (United States)

Mahdan, D.; Kamaludin, M.; Wendi, H. F.; Simanjuntak, M. V.

2018-02-01

The rapid development of information and communication technology (ICT), especially the internet, computers and communication devices requires the innovation in learning; one of which is Blended Learning. The concept of Blended Learning is the mixing of face-to-face learning models by learning online. Blended learning used in the learner teacher program organized by the Indonesian department of education and culture that a program to improve the competence of teachers, called “Guru Pembelajar” (GP). Blended learning model is perfect for learning for teachers, due to limited distance and time because online learning can be done anywhere and anytime. but the problems that arise from the implementation of this activity are many teachers who do not follow the activities because teachers, especially the elderly do not want to follow the activities because they cannot use computers and the internet, applications that are difficult to understand by participants, unstable internet connection in the area where the teacher lives and facilities and infrastructure are not adequate.

Translating and transforming (a) CALL for leadership for learning

DEFF Research Database (Denmark)

Weinreich, Elvi; Bjerg, Helle

2015-01-01

"The paper pursues the argument that the process of translation is not solely a linguistic exercise. It also implies methodological and conceptual questions related to the translation and as such transformation of general and theoretical research based models of leadership for learning...

The application of learning theory in horse training

DEFF Research Database (Denmark)

McLean, Andrew N.; Christensen, Janne Winther

2017-01-01

additional techniques (approach conditioning and stimulus blending). The salience of different types of cues, the interaction of operant and classical conditioning and the impact of stress are also discussed. This paper also exposes the inflexibility and occasional inadequacy of the terminology of learning...... on the correct application of learning theory, and safety and welfare benefits for people and horses would follow. Finally it is also proposed that the term ‘conflict theory’ be taken up in equitation science to facilitate diagnosis of training-related behaviour disorders and thus enable the emergence...

An ELT's Solution to Combat Plagiarism: "Birth" of CALL.

Science.gov (United States)

Sabieh, Christine

One English-as-a Second-Language professor fought plagiarism using computer assisted language learning (CALL). She succeeded in getting half of her class to write documented research papers free of plagiarism. Although all of the students claimed to know how to avoid plagiarizing, 35 percent presented the work with minor traces of plagiarism. The…

Virtual language learning environments: the standardization of evaluation

Directory of Open Access Journals (Sweden)

Francesca Romero Forteza

2014-03-01

Full Text Available Nowadays there are many approaches aimed at helping learners acquire knowledge through the Internet. Virtual Learning Environments (VLE facilitate the acquisition and practice of skills, but some of these learning platforms are not evaluated or do not follow a standard that guarantees the quality of the tasks involved. In this paper, we set out a proposal for the standardization of the evaluation of VLEs available on the World Wide Web. Thus, the main objective of this study is to establish an evaluation template with which to test whether a VLE is appropriate for computer-assisted language learning (CALL. In the methodology section, a learning platform is analysed and tested to establish the characteristics learning platforms must have. Having established the design of the template for language learning environments, we concluded that a VLE must be versatile enough for application with different language learning and teaching approaches.

The Significant Incidents and Close Calls in Human Space Flight Chart: Lessons Learned Gone Viral

Science.gov (United States)

Wood, Bill; Pate, Dennis; Thelen, David

2010-01-01

This presentation will explore the surprising history and events that transformed a mundane spreadsheet of historical spaceflight incidents into a popular and widely distributed visual compendium of lessons learned. The Significant Incidents and Close Calls in Human Space Flight Chart (a.k.a. The Significant Incidents Chart) is a popular and visually captivating reference product that has arisen from the work of the Johnson Space Center (JSC) Safety and Mission Assurance (S&MA) Flight Safety Office (FSO). It began as an internal tool intended to increase our team s awareness of historical and modern space flight incidents. Today, the chart is widely recognized across the agency as a reference tool. It appears in several training and education programs. It is used in familiarization training in the JSC Building 9 Mockup Facility and is seen by hundreds of center visitors each week. The chart visually summarizes injuries, fatalities, and close calls sustained during the continuing development of human space flight. The poster-sized chart displays over 100 total events that have direct connections to human space flight endeavors. The chart is updated periodically. The update process itself has become a collaborative effort. Many people, spanning multiple NASA organizations, have provided suggestions for additional entries. The FSO maintains a growing list of subscribers who have requested to receive updates. The presenters will discuss the origins and motivations behind the significant incidents chart. A review of the inclusion criteria used to select events will be offered. We will address how the chart is used today by S&MA and offer a vision of how it might be used by other organizations now and in the future. Particular emphasis will be placed on features of the chart that have met with broad acceptance and have helped spread awareness of the most important lessons in human spaceflight.

Learning theories and skills in online second language teaching and learning

DEFF Research Database (Denmark)

Petersen, Karen Bjerg

2014-01-01

For decades foreign and second language teachers have taken advantage of the technology development and ensuing possibilities to use e-learning facilities for language training. Since the 1980s, the use of computer assisted language learning (CALL), Internet, web 2.0, and various kinds of e-learning...... in Denmark with special attention towards the development of web-based materials for Danish pronunciation. This paper sets out to introduce differences between the international and Danish use of web-based language learning and teaching. Finally, dilemmas and challenges for the use of CALL, IT, and web 2.0 in...

Ethical Issues in E-Learning: Insights from the Application of Stakeholder Analysis in Three E-Learning Cases.

Science.gov (United States)

Chozos, Polyneikis; Lytras, Miltos; Pouloudi, Nancy

The application of emerging digital technologies such as e-mail, the World Wide Web and the Internet in the educational setting has received wide acceptance all over the world. Both corporate and academic agendas have recognized the potential advantages of e-learning; however, as a new field, e-learning courses comes with important issues that…

Students’ Readiness for E-learning Application in Higher Education

Directory of Open Access Journals (Sweden)

Atousa Rasouli

2016-07-01

Full Text Available The main goal of this research was to investigate the readiness of art students in applying e-learning. This study adopted a survey research design. From three public Iranian Universities (Alzahra, Tarbiat Modares, and Tehran, 347 students were selected by multistage cluster sampling and via Morgan Table. Their readiness for E-learning application was assessed by a self-developed questionnaire. Data analysis was done by indexes of descriptive statistics and one sample t-test. Analysis of results found a significant relationship between the readiness of undergraduate students, graduate students, and post-graduate students to apply E-learning, but there was no significant relationship between students’ readiness and gender, university, and subject. Results revealed that Art students were in a moderate level of readiness for applying E-learning.

Manifold Regularized Experimental Design for Active Learning.

Science.gov (United States)

Zhang, Lining; Shum, Hubert P H; Shao, Ling

2016-12-02

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.

The effect of the use of android-based application in learning together to improve students' academic performance

Science.gov (United States)

Ulfa, Andi Maria; Sugiyarto, Kristian H.; Ikhsan, Jaslin

2017-05-01

Poor achievement of students' performance on Chemistry may result from unfavourable learning processes. Therefore, innovation on learning process must be created. Regarding fast development of mobile technology, learning process cannot ignore the crucial role of the technology. This research and development (R&D) studies was done to develop android based application and to study the effect of its integration in Learning together (LT) into the improvement of students' learning creativity and cognitive achievement. The development of the application was carried out by adapting Borg & Gall and Dick & Carey model. The developed-product was reviewed by chemist, learning media practitioners, peer reviewers, and educators. After the revision based on the reviews, the application was used in the LT model on the topic of Stoichiometry in a senior high school. The instruments were questionnaires to get comments and suggestion from the reviewers about the application, and the another questionnaire was to collect the data of learning creativity. Another instrument used was a set of test by which data of students' achievement was collected. The results showed that the use of the mobile based application on Learning Together can bring about significant improvement of students' performance including creativity and cognitive achievement.

Online Learning for Mobile Technology Applications in Health Surveys

International Development Research Centre (IDRC) Digital Library (Canada)

Online Learning for Mobile Technology Applications in Health Surveys. In light of ... to develop a globally accessible asynchronous Internet-based training packaged backed by a real-time coaching service. Project ID. 105932. Project status.

Applications and Lessons Learned using Data from the Atmospheric Infrared Sounder

Science.gov (United States)

Ray, S. E.; Fetzer, E. J.; Olsen, E. T.; Lambrigtsen, B.; Pagano, T. S.; Teixeira, J.; Licata, S. J.; Hall, J. R.

2016-12-01

Applications and Lessons Learned using Data from the Atmospheric Infrared SounderSharon Ray, Jet Propulsion Laboratory, California Institute of Technology The Atmospheric Infrared Sounder (AIRS) on NASA's Aqua spacecraft has been returning daily global observations of Earth's atmospheric constituents and properties since 2002. With a 12-year data record and daily, global observations in near real-time, AIRS can play a role in applications that fall under many of the NASA Applied Sciences focus areas. AIRS' involvement in applications is two years in, so what have we learned and what are the pitfalls? AIRS has made gains in drought applications with products under consideration for inclusion in the U.S. Drought Monitor national map, as also with volcano rapid response with an internal alert system and automated products to help characterize plume extent. Efforts are underway with cold air aloft for aviation, influenza outbreak prediction, and vector borne disease. But challenges have occurred both in validation and in crossing the "valley of death" between products and decision makers. AIRS now has improved maps of standard products to be distributed in near real-time via NASA LANCE and by the Goddard DAAC as part of the Obama's administration Big Earth Data Initiative. In addition internal tools have been developed to support development and distribution of our application products. This talk will communicate the status of the AIRS applications effort along with lessons learned, and provide examples of new product imagery designed to best communicate AIRS data.

Communication Networks - Analysis of jitter due to call-level fluctuations

NARCIS (Netherlands)

Mandjes, M.R.H.

2007-01-01

Abstract In communication networks used by constant bit rate applications, call-level dynamics (i.e. entering and leaving calls) lead to fluctuations in the load, and therefore also fluctuations in the delay (jitter). By intentionally delaying the packets at the destination, one can transform the

Frogs Call at a Higher Pitch in Traffic Noise

Directory of Open Access Journals (Sweden)

Kirsten M. Parris

2009-06-01

Full Text Available Male frogs call to attract females for mating and to defend territories from rival males. Female frogs of some species prefer lower-pitched calls, which indicate larger, more experienced males. Acoustic interference occurs when background noise reduces the active distance or the distance over which an acoustic signal can be detected. Birds are known to call at a higher pitch or frequency in urban noise, decreasing acoustic interference from low-frequency noise. Using Bayesian linear regression, we investigated the effect of traffic noise on the pitch of advertisement calls in two species of frogs, the southern brown tree frog (Litoria ewingii and the common eastern froglet (Crinia signifera. We found evidence that L. ewingii calls at a higher pitch in traffic noise, with an average increase in dominant frequency of 4.1 Hz/dB of traffic noise, and a total effect size of 123 Hz. This frequency shift is smaller than that observed in birds, but is still large enough to be detected by conspecific frogs and confer a significant benefit to the caller. Mathematical modelling predicted a 24% increase in the active distance of a L. ewingii call in traffic noise with a frequency shift of this size. Crinia signifera may also call at a higher pitch in traffic noise, but more data are required to be confident of this effect. Because frog calls are innate rather than learned, the frequency shift demonstrated by L. ewingii may represent an evolutionary adaptation to noisy conditions. The phenomenon of frogs calling at a higher pitch in traffic noise could therefore constitute an intriguing trade-off between audibility and attractiveness to potential mates.

Teaching-Learning-Based Optimization with Learning Enthusiasm Mechanism and Its Application in Chemical Engineering

Directory of Open Access Journals (Sweden)

Xu Chen

2018-01-01

Full Text Available Teaching-learning-based optimization (TLBO is a population-based metaheuristic search algorithm inspired by the teaching and learning process in a classroom. It has been successfully applied to many scientific and engineering applications in the past few years. In the basic TLBO and most of its variants, all the learners have the same probability of getting knowledge from others. However, in the real world, learners are different, and each learner’s learning enthusiasm is not the same, resulting in different probabilities of acquiring knowledge. Motivated by this phenomenon, this study introduces a learning enthusiasm mechanism into the basic TLBO and proposes a learning enthusiasm based TLBO (LebTLBO. In the LebTLBO, learners with good grades have high learning enthusiasm, and they have large probabilities of acquiring knowledge from others; by contrast, learners with bad grades have low learning enthusiasm, and they have relative small probabilities of acquiring knowledge from others. In addition, a poor student tutoring phase is introduced to improve the quality of the poor learners. The proposed method is evaluated on the CEC2014 benchmark functions, and the computational results demonstrate that it offers promising results compared with other efficient TLBO and non-TLBO algorithms. Finally, LebTLBO is applied to solve three optimal control problems in chemical engineering, and the competitive results show its potential for real-world problems.

Performance evaluation of a distance learning program.

Science.gov (United States)

Dailey, D J; Eno, K R; Brinkley, J F

1994-01-01

This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macintosh on the other side of the country accessing the data over the Internet." The methodology presented is applicable to other client-server applications that are rapidly appearing on the Internet.

The Internet, Language Learning, and International Dialogue: Constructing Online Foreign Language Learning Websites

Science.gov (United States)

Kartal, Erdogan; Uzun, Levent

2010-01-01

In the present study we call attention to the close connection between languages and globalization, and we also emphasize the importance of the Internet and online websites in foreign language teaching and learning as unavoidable elements of computer assisted language learning (CALL). We prepared a checklist by which we investigated 28 foreign…

Proposing a Framework for Mobile Applications in Disaster Health Learning.

Science.gov (United States)

Liu, Alexander G; Altman, Brian A; Schor, Kenneth; Strauss-Riggs, Kandra; Thomas, Tracy N; Sager, Catherine; Leander-Griffith, Michelle; Harp, Victoria

2017-08-01

Mobile applications, or apps, have gained widespread use with the advent of modern smartphone technologies. Previous research has been conducted in the use of mobile devices for learning. However, there is decidedly less research into the use of mobile apps for health learning (eg, patient self-monitoring, medical student learning). This deficiency in research on using apps in a learning context is especially severe in the disaster health field. The objectives of this article were to provide an overview of the current state of disaster health apps being used for learning, to situate the use of apps in a health learning context, and to adapt a learning framework for the use of mobile apps in the disaster health field. A systematic literature review was conducted by using the PRISMA checklist, and peer-reviewed articles found through the PubMed and CINAHL databases were examined. This resulted in 107 nonduplicative articles, which underwent a 3-phase review, culminating in a final selection of 17 articles. While several learning models were identified, none were sufficient as an app learning framework for the field. Therefore, we propose a learning framework to inform the use of mobile apps in disaster health learning. (Disaster Med Public Health Preparedness. 2017;11:487-495).

Development of an Android-based Learning Media Application for Visually Impaired Students

Directory of Open Access Journals (Sweden)

Nurul Azmi

2017-06-01

Full Text Available This research aims to develop the English for Disability (EFORD application, on Android-based learning english media for Visually Impaired students and determine its based this on assessment of matter expert, media expert, special needs teacher and students. The research method adopted in this research is Research and Development (R&D. The development of this application through five phases: (1 Analysis of problems, through observation and interviews. (2 Collecting information as product planning / analysis of the needs of the media as required of blind children. (3 The design phase of products such as the manufacture of flow and storyboard navigation map.(4 Design validation phase form of an expert assessment of the media is developed. (5 testing products phase, such as assessment of the application by blind students. The results of this research is EFORD application which is feasible to be used as English learning media for visual impairment application based on assessment: 1Media expert it's obtained a percentage scored 95%, include for very worthy category, 2Subject matter, expert its obtained percentage scored 75% include for worthy category and 3 Special needs teacher it's obtained a percentage scored 83% include for very worthy category. Upon demonstration, students indicated the positive response of ≥ 70% in each indicator. Therefore English learning media with Android based application English for Disability (EFORD is very feasible to be used as an English learning media especially grammar and speaking English content for students of visual impairment for a number of reasons. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Social Media and Social Networking Applications for Teaching and Learning

Science.gov (United States)

Yeo, Michelle Mei Ling

2014-01-01

This paper aims to better understand the experiences of the youth and the educators with the tapping of social media like YouTube videos and the social networking application of Facebook for teaching and learning. This paper is interested in appropriating the benefits of leveraging of social media and networking applications like YouTube and…

Application of Learning Theories on Medical Imaging Education

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Osama A. Mabrouk Kheiralla

2018-05-01

Full Text Available The main objective of the education process is that student must learn well rather than the educators to teach well. If radiologists get involved in the process of medical education, it is important for them to do it through sound knowledge of how students learn. Researches have proved that most of the teachers in the field of medical education including diagnostic imaging are actually doctors or technicians, who didn’t have an opportunity to study the basics of learning. Mostly they have gained their knowledge through watching other educators, and they mostly rely on their personal skills and experience in doing their job. This will hinder them from conveying knowledge in an effective and scientific way, and they will find themselves lagging away behind the latest advances in the field of medical education and educational research, which will lead to negative cognitive outcomes among learners. This article presents an overview of three of the most influential basic theories of learning, upon which many teachers rely in their practical applications, which must be considered by radiologist who act as medical educators.

Sparse representation, modeling and learning in visual recognition theory, algorithms and applications

CERN Document Server

Cheng, Hong

2015-01-01

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition; describes sparse recovery approaches, robust and efficient sparse represen

QoS Adaptation in Multimedia Multicast Conference Applications for E-Learning Services

Science.gov (United States)

Deusdado, Sérgio; Carvalho, Paulo

2006-01-01

The evolution of the World Wide Web service has incorporated new distributed multimedia conference applications, powering a new generation of e-learning development and allowing improved interactivity and prohuman relations. Groupware applications are increasingly representative in the Internet home applications market, however, the Quality of…

Pharmacy Students Perception of the Application of Learning ...

African Journals Online (AJOL)

Objective: To evaluate pharmacy students' perception of the application of learning management system (LMS) in their education in a Doctor of Pharmacy program in Benin City. Method: In a special ICT class, 165 pharmacy students were introduced to LMS using an open source program, DoceboÓ after which a ...

Probabilistic Anomaly Detection Based On System Calls Analysis

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Przemysław Maciołek

2007-01-01

Full Text Available We present an application of probabilistic approach to the anomaly detection (PAD. Byanalyzing selected system calls (and their arguments, the chosen applications are monitoredin the Linux environment. This allows us to estimate “(abnormality” of their behavior (bycomparison to previously collected profiles. We’ve attached results of threat detection ina typical computer environment.

Attitudes towards using mobile applications for teaching mathematics in open learning systems

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Bahjat Hamid Altakhyneh

2018-05-01

Full Text Available This study investigated attitudes towards teaching mathematics via mobile learning in open learning systems. The sample of the study consisted of 57 male and female students enrolled in the mathematics course in the department of educational studies at the Arab Open University/ Jordan for the academic year 2016/2017. Results of the study showed that positive student attitudes toward using mobile applications reached 80%. Each of the following scores is ranked as ascending: mathematical thinking (75%, achievement motivation (76%, developing social and emotional skills (77%, and application technology (96%. There was no statistical significance difference (α ≤0.01 between the variable type of general secondary certificate (scientific / arts stream as well as the nature of employment in terms of whether the learner was either an employee or non-employee. In light of results of the study, the researcher recommends using mobile applications in teaching courses of mathematics in open learning systems.

A new learning paradigm: learning using privileged information.

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Vapnik, Vladimir; Vashist, Akshay

2009-01-01

In the Afterword to the second edition of the book "Estimation of Dependences Based on Empirical Data" by V. Vapnik, an advanced learning paradigm called Learning Using Hidden Information (LUHI) was introduced. This Afterword also suggested an extension of the SVM method (the so called SVM(gamma)+ method) to implement algorithms which address the LUHI paradigm (Vapnik, 1982-2006, Sections 2.4.2 and 2.5.3 of the Afterword). See also (Vapnik, Vashist, & Pavlovitch, 2008, 2009) for further development of the algorithms. In contrast to the existing machine learning paradigm where a teacher does not play an important role, the advanced learning paradigm considers some elements of human teaching. In the new paradigm along with examples, a teacher can provide students with hidden information that exists in explanations, comments, comparisons, and so on. This paper discusses details of the new paradigm and corresponding algorithms, introduces some new algorithms, considers several specific forms of privileged information, demonstrates superiority of the new learning paradigm over the classical learning paradigm when solving practical problems, and discusses general questions related to the new ideas.

An Island Called Cuba

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Jean Stubbs

2011-06-01

Full Text Available Review of: An Island Called Home: Returning to Jewish Cuba. Ruth Behar, photographs by Humberto Mayol. New Brunswick NJ: Rutgers University Press, 2007. xiii + 297 pp. (Cloth US$ 29.95 Fidel Castro: My Life: A Spoken Autobiography. Fidel Castro & Ignacio Ramonet. New York: Scribner/Simon & Schuster, 2008. vii + 724 pp. (Paper US$ 22.00, e-book US$ 14.99 Cuba: What Everyone Needs to Know. Julia E. Sweig. New York: Oxford University Press, 2009. xiv + 279 pp. (Paper US$ 16.95 [First paragraph] These three ostensibly very different books tell a compelling story of each author’s approach, as much as the subject matter itself. Fidel Castro: My Life: A Spoken Autobiography is based on a series of long interviews granted by the then-president of Cuba, Fidel Castro, to Spanish-Franco journalist Ignacio Ramonet. Cuba: What Everyone Needs to Know, by U.S. political analyst Julia Sweig, is one of a set country series, and, like Ramonet’s, presented in question/answer format. An Island Called Home: Returning to Jewish Cuba, with a narrative by Cuban-American anthropologist Ruth Behar and photographs by Cuban photographer Humberto Mayol, is a retrospective/introspective account of the Jewish presence in Cuba. While from Ramonet and Sweig we learn much about the revolutionary project, Behar and Mayol convey the lived experience of the small Jewish community against that backdrop.

Authoring a Web-enhanced interface for a new language-learning environment

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Dominique Hémard

2000-12-01

Full Text Available Computer-based applications in second language teaching have now been used for a protracted period of time, evolving from a deductive approach relying on grammatical progression to inductive methods and, more recently, exploratory interaction better suited to the constructivist mode. However, despite the initial adoption of a traditional learning environment, the first, albeit influential, generation of software design was poorly recognized, or worse, even met with scepticism by academics inasmuch as it did not seem to represent or, indeed, symbolize good teaching practices (Laurillard, 1991. As a result, original CALL programmes, such as gap-filling or substituting exercises, were often only considered appropriate as supplementary teaching material and, as such, referred to or introduced within courses as convenient adjuncts providing students with greater practical experience. Equally, students as users were never consulted on the use of CALL or, indeed, implicated beyond the designed interaction. Indeed, it was generally assumed that, since computer-based learning was a new concept, it would be, by itself, attractive and generate increased enthusiasm within the language-learning context. This situation was made even worse by a developmental process, dominated by self-taught, in-house authoring, which was too often amateurish, task-based in approach and empirical. Unfortunately, despite recent development in multimedia and hypermedia, this CALL legacy has been affecting CALL in design, practice and projected use.

EFL Teachers' Knowledge of the Use and Development of Computer-Assisted Language Learning (CALL) Materials

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Dashtestani, Reza

2014-01-01

Even though there are a plethora of CALL materials available to EFL teachers nowadays, very limited attention has been directed toward the issue that most EFL teachers are merely the consumers of CALL materials. The main challenge is to equip EFL teachers with the required CALL materials development skills to enable them to be contributors to CALL…

E-learning tools for education: regulatory aspects, current applications in radiology and future prospects.

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Pinto, A; Selvaggi, S; Sicignano, G; Vollono, E; Iervolino, L; Amato, F; Molinari, A; Grassi, R

2008-02-01

E-learning, an abbreviation of electronic learning, indicates the provision of education and training on the Internet or the World Wide Web. The impact of networks and the Internet on radiology is undoubtedly important, as it is for medicine as a whole. The Internet offers numerous advantages compared with other mass media: it provides access to a large amount of information previously known only to individual specialists; it is flexible, permitting the use of images or video; and it allows linking to Web sites on a specific subject, thus contributing to further expand knowledge. Our purpose is to illustrate the regulatory aspects (including Internet copyright laws), current radiological applications and future prospects of e-learning. Our experience with the installation of an e-learning platform is also presented. We performed a PubMed search on the published literature (without time limits) dealing with e-learning tools and applications in the health sector with specific reference to radiology. The search included all study types in the English language with the following key words: e-learning, education, teaching, online exam, radiology and radiologists. The Fiaso study was referred to for the regulatory aspects of e-learning. The application of e-learning to radiology requires the development of a model that involves selecting and creating e-learning platforms, creating and technologically adapting multimedia teaching modules, creating and managing a unified catalogue of teaching modules, planning training actions, defining training pathways and Continuing Education in Medicine (CME) credits, identifying levels of teaching and technological complexity of support tools, sharing an organisational and methodological model, training the trainers, operators' participation and relational devices, providing training, monitoring progress of the activities, and measuring the effectiveness of training. Since 2004, a platform--LiveLearning--has been used at our

Concept maps and the meaningful learning of science

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José Antonio C. S. Valadares

2013-03-01

Full Text Available The foundations of the Meaningful Learning Theory (MLT were laid by David Ausubel. The MLT was highly valued by the contributions of Joseph Novak and D. B. Gowin. Unlike other learning theories, the MLT has an operational component, since there are some instruments based on it and with the meaningful learning facilitation as aim. These tools were designated graphic organizers by John Trowbridge and James Wandersee (2000, pp. 100-129. One of them is the concept map created by Novak to extract meanings from an amalgam of information, having currently many applications. The other one is the Vee diagram or knowledge Vee, also called epistemological Vee or heuristic Vee. It was created by Gowin, and is an excellent organizer, for example to unpack and make transparent the unclear information from an information source. Both instruments help us in processing and becoming conceptually transparent the information, to facilitate the cognitive process of new meanings construction. In this work, after a brief introduction, it will be developed the epistemological and psychological grounds of MLT, followed by a reference to constructivist learning environments facilitators of the meaningful learning, the characterization of concept maps and exemplification of its use in various applications that have proved to be very effective from the standpoint of meaningful learning.

The Meaningful Learning of Intellectual Skills: An Application of Ausubel's Subsumption Theory to the Domain of Intellectual Skills Learning.

Science.gov (United States)

West, Leo H. T.; Kellett, Natalie C.

1981-01-01

Tests the applicability of Ausubel's theory to the meaningful learning of intellectual skills. Results of three studies of high school students indicate that advance organizers enhance learning of skills related to solubility product problems. This effect was removed if prior teaching in relevant background knowledge was included. (Author/WB)

The application of machine learning techniques in the clinical drug therapy.

Science.gov (United States)

Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan

2018-05-25

The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

PLANNING APPLICATION OF WEB 2.0 FOR ORGANIZATIONAL LEARNING IN UNIVERSITAS PENDIDIKAN INDONESIA LIBRARY

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Santi Santika

2017-07-01

Full Text Available Library of Universitas Pendidikan Indonesia (UPI has a quality policy commitment to continuous improvement in every area and process. It can be achieved by continuously optimizing organizational learning. Web 2.0 is a media application that can help the organizational learning process because it has the characteristics of read and write, as well as having the flexibility of time use, but the application must be in accordance with the culture and character of the organization. Therefore, this study aimed to find out the Web 2.0 application that can be applied to the organizational learning in the Library of UPI. The method used is a mixed method qualitative and quantitative approach. Research stage refers to the stage of planning and support phases of Web 2.0 Tools Implementation Model. The results showed that the application of Web 2.0 can be applied to the organizational learning in the Library UPI. It refers to the tendency of organizational culture Library of UPI that is good and tendency of HR Library UPI attitude against the use of the Internet and computers are very good. Web 2.0 applications that can be used by UPI library are blogs, online forums, and wiki as a primary tools. Facebook, Youtube, chat application, twitter and Instagram as a supporting tools.

Deep Learning and its Applications in the Natural Sciences

CERN Multimedia

CERN. Geneva

2015-01-01

Starting from a brief historical perspective on scientific discovery, this talk will review some of the theory and open problems of deep learning and describe how to design efficient feedforward and recursive deep learning architectures for applications in the natural sciences. In particular, the focus will be on multiple particle problems at different scales: in biology (e.g. prediction of protein structures), chemistry (e.g. prediction of molecular properties and reactions), and high-energy physics (e.g. detection of exotic particles, jet substructure and tagging, "dark matter and dark knowledge")

Machine learning a probabilistic perspective

CERN Document Server

Murphy, Kevin P

2012-01-01

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic method...

Design of a Braille Learning Application for Visually Impaired Students in Bangladesh.

Science.gov (United States)

Nahar, Lutfun; Jaafar, Azizah; Ahamed, Eistiak; Kaish, A B M A

2015-01-01

Visually impaired students (VIS) are unable to get visual information, which has made their learning process complicated. This paper discusses the overall situation of VIS in Bangladesh and identifies major challenges that they are facing in getting education. The Braille system is followed to educate blind students in Bangladesh. However, lack of Braille based educational resources and technological solutions have made the learning process lengthy and complicated for VIS. As a developing country, Bangladesh cannot afford for the costly Braille related technological tools for VIS. Therefore, a mobile phone based Braille application, "mBRAILLE", for Android platform is designed to provide an easy Braille learning technology for VIS in Bangladesh. The proposed design is evaluated by experts in assistive technology for students with disabilities, and advanced learners of Braille. The application aims to provide a Bangla and English Braille learning platform for VIS. In this paper, we depict iterative (participatory) design of the application along with a preliminary evaluation with 5 blind subjects, and 1 sighted and 2 blind experts. The results show that the design scored an overall satisfaction level of 4.53 out of 5 by all respondents, indicating that our design is ready for the next step of development.

Learning Organization Models and Their Application to the U.S. Army

Science.gov (United States)

2016-06-01

learner and a teacher . Risk-taking and innovation are encouraged, mistakes are valued as sources of learning, and there exists a commitment to...consistent with Army’s values. Leadership commitment and empowerment 45. Senior leaders resist change and are afraid of new ideas. 46. Senior... Research Report 1998 Learning Organization Models and Their Application to the U.S. Army Jasmine Snyder Consortium of

Blended call center with idling times during the call service

NARCIS (Netherlands)

Legros, Benjamin; Jouini, Oualid; Koole, Ger

We consider a blended call center with calls arriving over time and an infinitely backlogged amount of outbound jobs. Inbound calls have a non-preemptive priority over outbound jobs. The inbound call service is characterized by three successive stages where the second one is a break; i.e., there is

Boosting compound-protein interaction prediction by deep learning.

Science.gov (United States)

Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

2016-11-01

The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

Investigating Teachers’ and Students’ Beliefs and Assumptions about CALL Programme at Caledonian College of Engineering

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Holi Ibrahim Holi Ali

2012-01-01

Full Text Available This study is set to investigate students’ and teachers’ perceptions and assumptions about newly implemented CALL Programme at the School of Foundation Studies, Caledonian College of Engineering, Oman. Two versions of questionnaire were administered to 24 teachers and 90 students to collect their beliefs and assumption about CALL programame. The results shows that the great majority of the students report that CALL is very interesting, motivating and useful to them and they learn a lot form it. However, the number of CALL hours should be increased, lab should be equipped and arranged in user friendly way, assessment should be integrated into CALL, and smart boards, black boards should be incorporated into the programme.

Carbon Monitoring System Applications Framework: Lessons Learned from Stakeholder Engagement Activities

Science.gov (United States)

Sepulveda Carlo, E.; Escobar, V. M.; Delgado Arias, S.; Forgotson, C.

2017-12-01

The NASA Carbon Monitoring System initiated by U.S. Congress in 2010 is developing products that characterize and quantify carbon sources and sinks in the United States and the global tropics. In 2013, an applications effort was selected to engage potential end users and gather feedback about their data needs. For the past four years the CMS applications efforts has expanded and implemented a number of strategies to connect carbon scientists to decision-makers, contributing to the societal benefits of CMS data products. The applications efforts use crowd sourcing to collects feedback from stakeholders on challenges and lessons learned in the use of CMS data products. Some of the most common data needs from engaged organizations include above and below-ground biomass and fluxes in forestlands and wetlands, and greenhouse gas (GHG) emissions across all land use/cover and land use changes. Stakeholder organizations' needs for CMS data products support national GHG inventories following the Paris Agreement, carbon markets, and sub-national natural resources management and policies. The lessons learned report presents stakeholder specific applications, challenges, and successes from using CMS data products. To date, the most common uses of CMS products include: conservation efforts, emissions inventory, forestry and land cover applications, and carbon offset projects. The most common challenges include: the need for familiar and consistent products over time, budget constraints, and concern with uncertainty of modeled results. Recurrent recommendations from stakeholder indicate that CMS should provide high resolution (30m) and frequent data products updates (annually). The applications efforts have also helped identified success stories from different CMS projects, including the development of the GHG emissions inventory from Providence, RI, the improvement of the U.S. GHG Inventory though the use of satellite data, and the use of high resolution canopy cover maps for

The Learning Preferences of Applicants Who Interview for General Surgery Residency: A Multiinstitutional Study.

Science.gov (United States)

Kim, Roger H; Kurtzman, Scott H; Collier, Ashley N; Shabahang, Mohsen M

Learning styles theory posits that learners have distinct preferences for how they assimilate new information. The VARK model categorizes learners based on combinations of 4 learning preferences: visual (V), aural (A), read/write (R), and kinesthetic (K). A previous single institution study demonstrated that the VARK preferences of applicants who interview for general surgery residency are different from that of the general population and that learning preferences were associated with performance on standardized tests. This multiinstitutional study was conducted to determine the distribution of VARK preferences among interviewees for general surgery residency and the effect of those preferences on United States Medical Licensing Examination (USMLE) scores. The VARK learning inventory was administered to applicants who interviewed at 3 general surgery programs during the 2014 to 2015 academic year. The distribution of VARK learning preferences among interviewees was compared with that of the general population of VARK respondents. Performance on USMLE Step 1 and Step 2 Clinical Knowledge was analyzed for associations with VARK learning preferences. Chi-square, analysis of variance, and Dunnett's test were used for statistical analysis, with p learning modality. The distribution of VARK preferences of interviewees was different than that of the general population (p = 0.02). By analysis of variance, there were no overall differences in USMLE Step 1 and Step 2 Clinical Knowledge scores by VARK preference (p = 0.06 and 0.21, respectively). However, multiple comparison analysis using Dunnett's test revealed that interviewees with R preferences had significantly higher scores than those with multimodal preferences on USMLE Step 1 (239 vs. 222, p = 0.02). Applicants who interview for general surgery residency have a different pattern of VARK preferences than that of the general population. Interviewees with preferences for read/write learning modalities have higher scores

Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

Science.gov (United States)

Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

2017-01-01

This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…

Implementing Distributed Algorithms using Remote Procedure Call

NARCIS (Netherlands)

Bal, H.E.; van Renesse, R.; Tanenbaum, A.S.

1987-01-01

Remote procedure call (RPC) is a simple yet powerful primitiv~ for communication and synchronization between distributed processes. A problem with RPC is that it tends to decrease the amount of parallelism in an application due to its synchronous nature. This paper shows how light-weight processes

Blended Learning

OpenAIRE

Bauerová, Andrea

2013-01-01

This thesis is focused on a new approach of education called blended learning. The history and developement of Blended Learning is described in the first part. Then the methods and tools of Blended Learning are evaluated and compared to the traditional methods of education. At the final part an efficient developement of the educational programs is emphasized.

An Educational Data Mining Approach to Concept Map Construction for Web based Learning

Directory of Open Access Journals (Sweden)

Anal ACHARYA

2017-01-01

Full Text Available This aim of this article is to study the use of Educational Data Mining (EDM techniques in constructing concept maps for organizing knowledge in web based learning systems whereby studying their synergistic effects in enhancing learning. This article first provides a tutorial based introduction to EDM. The applicability of web based learning systems in enhancing the efficiency of EDM techniques in real time environment is investigated. Web based learning systems often use a tool for organizing knowledge. This article explores the use of one such tool called concept map for this purpose. The pioneering works by various researchers who proposed web based learning systems in personalized and collaborative environment in this arena are next presented. A set of parameters are proposed based on which personalized and collaborative learning applications may be generalized and their performances compared. It is found that personalized learning environment uses EDM techniques more exhaustively compared to collaborative learning for concept map construction in web based environment. This article can be used as a starting point for freshers who would like to use EDM techniques for concept map construction for web based learning purposes.

Mobile Learning Application Interfaces: First Steps to a Cognitive Load Aware System

Science.gov (United States)

Deegan, Robin

2013-01-01

Mobile learning is a cognitively demanding application and more frequently the ubiquitous nature of mobile computing means that mobile devices are used in cognitively demanding environments. This paper examines the nature of this use of mobile devices from a Learning, Usability and Cognitive Load Theory perspective. It suggests scenarios where…

A Dependence between Average Call Duration and Voice Transmission Quality: Measurement and applications

NARCIS (Netherlands)

Holub, J.; Beerends, J.G.; Smid, R.

2004-01-01

This contribution deals with the estimation of the relation between speech transmission quality and average call duration for a given network and portfolio of customers. It uses non-intrusive speech quality measurements on live speech calls. The basic idea behind this analysis is an expectation that

Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants

Science.gov (United States)

Hüllermeier, Eyke; Fürnkranz, Johannes

The term “preference learning” refers to the application of machine learning methods for inducing preference models from empirical data. In the recent literature, corresponding problems appear in various guises. After a brief overview of the field, this work focuses on a particular learning scenario called label ranking where the problem is to learn a mapping from instances to rankings over a finite number of labels. Our approach for learning such a ranking function, called ranking by pairwise comparison (RPC), first induces a binary preference relation from suitable training data, using a natural extension of pairwise classification. A ranking is then derived from this relation by means of a ranking procedure. This paper elaborates on a key advantage of such an approach, namely the fact that our learner can be adapted to different loss functions by using different ranking procedures on the same underlying order relations. In particular, the Spearman rank correlation is minimized by using a simple weighted voting procedure. Moreover, we discuss a loss function suitable for settings where candidate labels must be tested successively until a target label is found. In this context, we propose the idea of “empirical conditioning” of class probabilities. A related ranking procedure, called “ranking through iterated choice”, is investigated experimentally.

A Review of Multimedia Glosses and Their Effects on L2 Vocabulary Acquisition in CALL Literature

Science.gov (United States)

Mohsen, Mohammed Ali; Balakumar, M.

2011-01-01

This article reviews the literature of multimedia glosses in computer assisted language learning (CALL) and their effects on L2 vocabulary acquisition during the past seventeen years. Several studies have touched on this area to examine the potential of multimedia in a CALL environment in aiding L2 vocabulary acquisition. In this review, the…

Leaders Learning Orientation and the HCM-turn in call centres

DEFF Research Database (Denmark)

Gnaur, Dorina

2013-01-01

as a significant leadership quality that promotes reflexivity in the ongoing processes of interpretation and meaning creation enhancing the human dimension in the production of service. Learning orientation will be related to high-commitment management (HCM) as a way to reconcile the logics of efficiency...

Usability of English Note-Taking Applications in a Foreign Language Learning Context

Science.gov (United States)

Roy, Debopriyo; Brine, John; Murasawa, Fuyuki

2016-01-01

The act of note-taking offloads cognitive pressure and note-taking applications could be used as an important tool for foreign language acquisition. Its use, importance, and efficacy in a foreign language learning context could be justifiably debated. However, existing computer-assisted language learning literature is almost silent on the topic.…

Reflexive Photography, Attitudes, Behavior, and CALL: ITAs Improving Spoken English Intelligibility

Science.gov (United States)

Wallace, Lara

2015-01-01

Research in the field of Computer-Assisted Language Learning (CALL) has frequently taken a top-down approach when investigating learners' attitudes and behavior, both in the course as well as for their personal use. Suggestions are given for use of technology, and future research (Beatty, 2010; Levy & Stockwell, 2006). One perspective that has…

The Short Readings Project: A CALL Reading Activity Utilizing Vocabulary Recycling

Science.gov (United States)

Johnson, Andrew; Heffernan, Neil

2006-01-01

In 2003 multimedia-based English Trailers (www.english-trailers.com) joined the vast array of web sites dedicated to language learning enabling students, either autonomously or in a CALL classroom, to study English via movie commercials. To assist students in comprehending 10 trailers found on the site, the authors created the Short Readings…

Attitudes of Medical Graduate and Undergraduate Students toward the Learning and Application of Medical Statistics

Science.gov (United States)

Wu, Yazhou; Zhang, Ling; Liu, Ling; Zhang, Yanqi; Liu, Xiaoyu; Yi, Dong

2015-01-01

It is clear that the teaching of medical statistics needs to be improved, yet areas for priority are unclear as medical students' learning and application of statistics at different levels is not well known. Our goal is to assess the attitudes of medical students toward the learning and application of medical statistics, and discover their…

A strategy for quantum algorithm design assisted by machine learning

International Nuclear Information System (INIS)

Bang, Jeongho; Lee, Jinhyoung; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin

2014-01-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum–classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch–Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method. (paper)

A strategy for quantum algorithm design assisted by machine learning

Science.gov (United States)

Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung

2014-07-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.

Learning from the application of the systematic approach to training

International Nuclear Information System (INIS)

Haber, S.B.; Yoder, J.A.

1998-01-01

The paper describes the objectives, lessons learned, key accomplishments and related activities of the application of the systematic approach to training initiated by DOE in Russia and Ukraine in 1992 focused on single facility in each country

TADtool: visual parameter identification for TAD-calling algorithms.

Science.gov (United States)

Kruse, Kai; Hug, Clemens B; Hernández-Rodríguez, Benjamín; Vaquerizas, Juan M

2016-10-15

Eukaryotic genomes are hierarchically organized into topologically associating domains (TADs). The computational identification of these domains and their associated properties critically depends on the choice of suitable parameters of TAD-calling algorithms. To reduce the element of trial-and-error in parameter selection, we have developed TADtool: an interactive plot to find robust TAD-calling parameters with immediate visual feedback. TADtool allows the direct export of TADs called with a chosen set of parameters for two of the most common TAD calling algorithms: directionality and insulation index. It can be used as an intuitive, standalone application or as a Python package for maximum flexibility. TADtool is available as a Python package from GitHub (https://github.com/vaquerizaslab/tadtool) or can be installed directly via PyPI, the Python package index (tadtool). kai.kruse@mpi-muenster.mpg.de, jmv@mpi-muenster.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Learning to learn: self-managed learning

Directory of Open Access Journals (Sweden)

Jesús Miranda Izquierdo

2006-09-01

Full Text Available Thi is article analyzes the potentialities and weaknesses that non directive Pedagogy presents, an example of the so called self managed pedagogy, whose postulates are good to analyze for the contributions that this position can make to the search of new ways of learning.

The Usefulness and Ease of Use of a Mobile Simulation Application for Learning of ERP Systems

Directory of Open Access Journals (Sweden)

Brenda Scholtz

2017-10-01

Full Text Available The hands-on use of complex, industrial Enterprise Resource Planning (ERP systems in educational contexts can be costly and complex. Tools that simulate the hands-on use of an ERP system have been proposed as alternatives. Research into the perceived usefulness (PU and perceived ease of use (PEOU of these simulation tools in an m-learning environment is limited. As part of this study, an m-learning simulation application (SYSPRO Latte was designed based on experiential learning theory and on a previously proposed theoretical framework for m-learning. The application simulates the hands-on experience of an ERP system. The purpose of this paper is to analyse the results of a study of 49 students who used SYSPRO Latte and completed a questionnaire on its PEOU and PU. The results revealed that students perceived SYSPRO Latte to be easy to use and useful, and verified other studies identifying a correlation between PEOU and PU. The study also confirmed the benefits of simulation-based learning and m-learning particularly for content presentation. The importance of considering design principles for m-learning applications was highlighted. This study is part of a larger, comprehensive research project that aims at improving learning of ERP systems in higher education.

Help Options for L2 Listening in CALL: A Research Agenda

Science.gov (United States)

Cross, Jeremy

2017-01-01

In this article, I present an agenda for researching help options for second language (L2) listening in computer-assisted language learning (CALL) environments. I outline several theories which researchers in the area draw on, then present common points of concern identified from a review of related literature. This serves as a means to…

Campbell's monkeys concatenate vocalizations into context-specific call sequences

Science.gov (United States)

Ouattara, Karim; Lemasson, Alban; Zuberbühler, Klaus

2009-01-01

Primate vocal behavior is often considered irrelevant in modeling human language evolution, mainly because of the caller's limited vocal control and apparent lack of intentional signaling. Here, we present the results of a long-term study on Campbell's monkeys, which has revealed an unrivaled degree of vocal complexity. Adult males produced six different loud call types, which they combined into various sequences in highly context-specific ways. We found stereotyped sequences that were strongly associated with cohesion and travel, falling trees, neighboring groups, nonpredatory animals, unspecific predatory threat, and specific predator classes. Within the responses to predators, we found that crowned eagles triggered four and leopards three different sequences, depending on how the caller learned about their presence. Callers followed a number of principles when concatenating sequences, such as nonrandom transition probabilities of call types, addition of specific calls into an existing sequence to form a different one, or recombination of two sequences to form a third one. We conclude that these primates have overcome some of the constraints of limited vocal control by combinatorial organization. As the different sequences were so tightly linked to specific external events, the Campbell's monkey call system may be the most complex example of ‘proto-syntax’ in animal communication known to date. PMID:20007377

Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey

Science.gov (United States)

Xue, Yong; Chen, Shihui; Liu, Yong

2017-01-01

Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, which is of great significance for early detection of cancer. In recent years, deep leaning has been widely used in medical imaging analysis, as it overcomes the limitations of visual assessment and traditional machine learning techniques by extracting hierarchical features with powerful representation capability. Research on cancer molecular images using deep learning techniques is also increasing dynamically. Hence, in this paper, we review the applications of deep learning in molecular imaging in terms of tumor lesion segmentation, tumor classification, and survival prediction. We also outline some future directions in which researchers may develop more powerful deep learning models for better performance in the applications in cancer molecular imaging. PMID:29114182

Investigating the Use of a Smartphone Social Networking Application on Language Learning

Science.gov (United States)

Sung, Ko-Yin; Poole, Frederick

2017-01-01

This study explored college students' use of a popular smartphone social networking application, WeChat, in a tandem language learning project. The research questions included (1) How do Chinese-English dyads utilize the WeChat app for weekly language learning?, and (2) What are the perceptions of the Chinese-English dyads on the use of the WeChat…

The Applicability of eLearning in Community-Based Rehabilitation

Directory of Open Access Journals (Sweden)

Karly Michelle Dagys

2015-12-01

Full Text Available Community-based rehabilitation (CBR strives to enhance quality of life for individuals with disabilities and their families by increasing social participation and equalizing opportunities in the global south. Aligning with the Sustainable Development Goals, CBR also aims to address the high rates of poverty faced by individuals with disability. Empowerment, a pillar of CBR, involves strengthening the capacity of people with disabilities, their families, and their communities to ensure reduction of disparities. This article outlines a scoping review that guided by the question: “What is known from the existing literature about the applicability of eLearning for capacity building in CBR?” This review did not uncover literature related to eLearning in CBR; however findings suggest that other disciplines, not explicitly tied to CBR, currently use eLearning to educate and empower professionals in the global south. We argue that eLearning technology could be an effective and sustainable solution for CBR programming in the global south for capacity development. Such technology could increase individuals with disabilities’ access to education and could provide opportunities for wider dissemination of knowledge, beyond typical funding cycles. With a goal of informing future CBR practice in eLearning, this article concludes by highlighting key lessons taken from other disciplines that have utilized eLearning in the global south.

Intrinsic motivation, curiosity, and learning: Theory and applications in educational technologies.

Science.gov (United States)

Oudeyer, P-Y; Gottlieb, J; Lopes, M

2016-01-01

This chapter studies the bidirectional causal interactions between curiosity and learning and discusses how understanding these interactions can be leveraged in educational technology applications. First, we review recent results showing how state curiosity, and more generally the experience of novelty and surprise, can enhance learning and memory retention. Then, we discuss how psychology and neuroscience have conceptualized curiosity and intrinsic motivation, studying how the brain can be intrinsically rewarded by novelty, complexity, or other measures of information. We explain how the framework of computational reinforcement learning can be used to model such mechanisms of curiosity. Then, we discuss the learning progress (LP) hypothesis, which posits a positive feedback loop between curiosity and learning. We outline experiments with robots that show how LP-driven attention and exploration can self-organize a developmental learning curriculum scaffolding efficient acquisition of multiple skills/tasks. Finally, we discuss recent work exploiting these conceptual and computational models in educational technologies, showing in particular how intelligent tutoring systems can be designed to foster curiosity and learning. © 2016 Elsevier B.V. All rights reserved.

Computer Assisted Language Learning. Routledge Studies in Computer Assisted Language Learning

Science.gov (United States)

Pennington, Martha

2011-01-01

Computer-assisted language learning (CALL) is an approach to language teaching and learning in which computer technology is used as an aid to the presentation, reinforcement and assessment of material to be learned, usually including a substantial interactive element. This books provides an up-to date and comprehensive overview of…

Mobile telephones: a comparison of radiated power between 3G VoIP calls and 3G VoCS calls.

Science.gov (United States)

Jovanovic, Dragan; Bragard, Guillaume; Picard, Dominique; Chauvin, Sébastien

2015-01-01

The purpose of this study is to assess the mean RF power radiated by mobile telephones during voice calls in 3G VoIP (Voice over Internet Protocol) using an application well known to mobile Internet users, and to compare it with the mean power radiated during voice calls in 3G VoCS (Voice over Circuit Switch) on a traditional network. Knowing that the specific absorption rate (SAR) is proportional to the mean radiated power, the user's exposure could be clearly identified at the same time. Three 3G (High Speed Packet Access) smartphones from three different manufacturers, all dual-band for GSM (900 MHz, 1800 MHz) and dual-band for UMTS (900 MHz, 1950 MHz), were used between 28 July and 04 August 2011 in Paris (France) to make 220 two-minute calls on a mobile telephone network with national coverage. The places where the calls were made were selected in such a way as to describe the whole range of usage situations of the mobile telephone. The measuring equipment, called "SYRPOM", recorded the radiation power levels and the frequency bands used during the calls with a sampling rate of 20,000 per second. In the framework of this study, the mean normalised power radiated by a telephone in 3G VoIP calls was evaluated at 0.75% maximum power of the smartphone, compared with 0.22% in 3G VoCS calls. The very low average power levels associated with use of 3G devices with VoIP or VoCS support the view that RF exposure resulting from their use is far from exceeding the basic restrictions of current exposure limits in terms of SAR.

Active Learning Using Hint Information.

Science.gov (United States)

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

Application of machine learning on brain cancer multiclass classification

Science.gov (United States)

Panca, V.; Rustam, Z.

2017-07-01

Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

Machine Learning-Empowered Biometric Methods for Biomedicine Applications

Directory of Open Access Journals (Sweden)

Qingxue Zhang

2017-07-01

Full Text Available Nowadays, pervasive computing technologies are paving a promising way for advanced smart health applications. However, a key impediment faced by wide deployment of these assistive smart devices, is the increasing privacy and security issue, such as how to protect access to sensitive patient data in the health record. Focusing on this challenge, biometrics are attracting intense attention in terms of effective user identification to enable confidential health applications. In this paper, we take special interest in two bio-potential-based biometric modalities, electrocardiogram (ECG and electroencephalogram (EEG, considering that they are both unique to individuals, and more reliable than token (identity card and knowledge-based (username/password methods. After extracting effective features in multiple domains from ECG/EEG signals, several advanced machine learning algorithms are introduced to perform the user identification task, including Neural Network, K-nearest Neighbor, Bagging, Random Forest and AdaBoost. Experimental results on two public ECG and EEG datasets show that ECG is a more robust biometric modality compared to EEG, leveraging a higher signal to noise ratio and also more distinguishable morphological patterns. Among different machine learning classifiers, the random forest greatly outperforms the others and owns an identification rate as high as 98%. This study is expected to demonstrate that properly selected biometric empowered by an effective machine learner owns a great potential, to enable confidential biomedicine applications in the era of smart digital health.

Designing an E-Learning Application to Facilitate Health Care Professionals' Cross-Cultural Communication.

Science.gov (United States)

Balasubramaniam, Nagadivya; Kujala, Sari; Ayzit, Dicle; Kauppinen, Marjo; Heponiemi, Tarja; Hietapakka, Laura; Kaihlanen, Anu

2018-01-01

In recent times, health care professionals (HCP) have come across a number of migrants as their patients. The cultural differences lead to communicational challenges between the migrant patients and health care professionals. Our project aimed to discover HCPs' attitudes, challenges and needs on cross-cultural communication, so that we can develop an e-learning solution that would be helpful for them. By conducting interviews with HCPs, we identified five crucial categories of problems and the current solutions that experienced professionals use to tackle those problems. These interviews also helped us in understanding the motivational factors of HCPs, when using e-learning application. Health care professionals prefer a focus on examples and themes such as death and pain that they face in their everyday work. Changing attitudes by e-learning application is challenging. However, e-learning was recognized as a flexible way for supporting traditional training with HCPs who are busy at work most of the time.

Postinterview communication with residency applicants: a call for clarity!

Science.gov (United States)

Frishman, Gary N; Matteson, Kristen A; Bienstock, Jessica L; George, Karen E; Ogburn, Tony; Rauk, Phillip N; Schnatz, Peter F; Learman, Lee A

2014-10-01

The residency match is an increasingly competitive process. Communication from medical student applicants to programs varies, and the effect this has on their rank status is unclear. We assessed how obstetrics and gynecology program directors interpret and act on postinterview communication initiated by applicants by conducting an anonymous cross-sectional web-based survey of allopathic obstetrics and gynecology program directors. One hundred thirty-seven program directors (55%) responded to the survey. Twenty-nine percent would consider ranking an applicant more favorably if the applicant expressed interest (beyond a routine thank you) or if a faculty mentor personally known to the program director stated that the applicant was ranking the program first. Fifty-two percent indicated that they would rank an applicant more favorably if a mentor known to them endorsed the applicant as outstanding. Approximately 30% responded that applicants who did not communicate with their program were disadvantaged compared with those who did. Approximately 17% stated it was desirable to create additional specialty-specific guidelines regarding postinterview contact between programs and applications. Based on the wide variation in how program directors interpret and act on postinterview communication from applicants, residency programs should formulate and communicate a clear policy about whether they request and how they respond to postinterview communication from applicants and their mentors. This will establish a more level playing field and eliminate potential inequities resulting from inconsistent communication practices. Copyright © 2014 Elsevier Inc. All rights reserved.

Metabolic interrelationships software application: Interactive learning tool for intermediary metabolism

NARCIS (Netherlands)

A.J.M. Verhoeven (Adrie); M. Doets (Mathijs); J.M.J. Lamers (Jos); J.F. Koster (Johan)

2005-01-01

textabstractWe developed and implemented the software application titled Metabolic Interrelationships as a self-learning and -teaching tool for intermediary metabolism. It is used by undergraduate medical students in an integrated organ systems-based and disease-oriented core curriculum, which

New AIDA-2020 call for breakthrough detector technologies

CERN Multimedia

2016-01-01

Physicists, engineers, and industry will be interested in a new proof-of-concept fund for breakthrough projects from the general field of detector development and testing.   Launched in the framework of the European project AIDA-2020, this open call will provide up to 200k€ of seed funding to support innovative and societal applications with a focus on industry-oriented applications. The deadline for applying is 20 October 2016. More information here.

Application of Machine Learning to Rotorcraft Health Monitoring

Science.gov (United States)

Cody, Tyler; Dempsey, Paula J.

2017-01-01

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

Learning theories 101: application to everyday teaching and scholarship.

Science.gov (United States)

Kay, Denise; Kibble, Jonathan

2016-03-01

Shifts in educational research, in how scholarship in higher education is defined, and in how funding is appropriated suggest that educators within basic science fields can benefit from increased understanding of learning theory and how it applies to classroom practice. This article uses a mock curriculum design scenario as a framework for the introduction of five major learning theories. Foundational constructs and principles from each theory and how they apply to the proposed curriculum designs are described. A summative table that includes basic principles, constructs, and classroom applications as well as the role of the teacher and learner is also provided for each theory. Copyright © 2016 The American Physiological Society.

ICT Application and Utilization for Distance and Open Learning ...

African Journals Online (AJOL)

This study examined the extent of ICT application and utilization for distance and open learning education at the National Open University of Nigeria (NOUN). The descriptive survey research method was adopted for the study while questionnaire was adopted as major instrument of data collection. A total of 113 copie/s of ...

Enhancing the Design and Analysis of Flipped Learning Strategies

Science.gov (United States)

Jenkins, Martin; Bokosmaty, Rena; Brown, Melanie; Browne, Chris; Gao, Qi; Hanson, Julie; Kupatadze, Ketevan

2017-01-01

There are numerous calls in the literature for research into the flipped learning approach to match the flood of popular media articles praising its impact on student learning and educational outcomes. This paper addresses those calls by proposing pedagogical strategies that promote active learning in "flipped" approaches and improved…

Algorithm Building and Learning Programming Languages Using a New Educational Paradigm

Science.gov (United States)

Jain, Anshul K.; Singhal, Manik; Gupta, Manu Sheel

2011-08-01

This research paper presents a new concept of using a single tool to associate syntax of various programming languages, algorithms and basic coding techniques. A simple framework has been programmed in Python that helps students learn skills to develop algorithms, and implement them in various programming languages. The tool provides an innovative and a unified graphical user interface for development of multimedia objects, educational games and applications. It also aids collaborative learning amongst students and teachers through an integrated mechanism based on Remote Procedure Calls. The paper also elucidates an innovative method for code generation to enable students to learn the basics of programming languages using drag-n-drop methods for image objects.

Dynamic call center routing policies using call waiting and agent idle times

NARCIS (Netherlands)

Chan, W.; Koole, G.M.; L'Ecuyer, P.

2014-01-01

We study call routing policies for call centers with multiple call types and multiple agent groups. We introduce new weight-based routing policies where each pair (call type, agent group) is given a matching priority defined as an affine combination of the longest waiting time for that call type and

The Views of Undergraduates about Problem-Based Learning Applications in a Biochemistry Course

Science.gov (United States)

Tarhan, Leman; Ayyildiz, Yildizay

2015-01-01

The effect of problem-based learning (PBL) applications in an undergraduate biochemistry course on students' interest in this course was investigated through four modules during one semester. Students' views about active learning and improvement in social skills were also collected and evaluated. We conducted the study with 36 senior students from…

Adapting Team-Based Learning for Application in the Basic Electric Circuit Theory Sequence

Science.gov (United States)

O'Connell, Robert M.

2015-01-01

Team-based learning (TBL) is a form of student-centered active learning in which students independently study new conceptual material before it is treated in the classroom, and then subsequently spend considerable classroom time working in groups on increasingly challenging problems and applications based on that new material. TBL provides…

Online transfer learning with extreme learning machine

Science.gov (United States)

Yin, Haibo; Yang, Yun-an

2017-05-01

In this paper, we propose a new transfer learning algorithm for online training. The proposed algorithm, which is called Online Transfer Extreme Learning Machine (OTELM), is based on Online Sequential Extreme Learning Machine (OSELM) while it introduces Semi-Supervised Extreme Learning Machine (SSELM) to transfer knowledge from the source to the target domain. With the manifold regularization, SSELM picks out instances from the source domain that are less relevant to those in the target domain to initialize the online training, so as to improve the classification performance. Experimental results demonstrate that the proposed OTELM can effectively use instances in the source domain to enhance the learning performance.

Android: Call C Functions with the Native Development Kit (NDK)

Science.gov (United States)

2016-09-01

from a Java application. 15. SUBJECT TERMS Android , NDK, Native Development Kit, C callable, Java Native Interface, JNI, Java, C/C++ 16. SECURITY ...ARL-TN-0782 ● SEP 2016 US Army Research Laboratory Android : Call C Functions with the Native Development Kit (NDK) by Hao Q...Do not return it to the originator. ARL-TN-0782 ● SEP 2016 US Army Research Laboratory Android : Call C Functions with the Native

Call for proposals: Innovations for the economic inclusion of ...

International Development Research Centre (IDRC) Digital Library (Canada)

2018-03-20

Mar 20, 2018 ... ... cooperation agreement to support joint research projects in December 2017. ... but in most cases they have difficulty reaching marginalized youth ... Visit the call page for detailed information and to access application forms.

Design Requirements for Communication-Intensive Interactive Applications

Science.gov (United States)

Bolchini, Davide; Garzotto, Franca; Paolini, Paolo

Online interactive applications call for new requirements paradigms to capture the growing complexity of computer-mediated communication. Crafting successful interactive applications (such as websites and multimedia) involves modeling the requirements for the user experience, including those leading to content design, usable information architecture and interaction, in profound coordination with the communication goals of all stakeholders involved, ranging from persuasion to social engagement, to call for action. To face this grand challenge, we propose a methodology for modeling communication requirements and provide a set of operational conceptual tools to be used in complex projects with multiple stakeholders. Through examples from real-life projects and lessons-learned from direct experience, we draw on the concepts of brand, value, communication goals, information and persuasion requirements to systematically guide analysts to master the multifaceted connections of these elements as drivers to inform successful communication designs.

Failure of operant control of vocal learning in budgerigars

Directory of Open Access Journals (Sweden)

Yoshimasa Seki

2018-02-01

Full Text Available Budgerigars were trained by operant conditioning to produce contact calls immediately after hearing a stimulus contact call. In Experiments 1 and 2, playback stimuli were chosen from two different contact call classes from the bird’s repertoire. Once this task was learned, the birds were then tested with other probe stimulus calls from its repertoire, which differed from the original calls drawn from the two classes. Birds failed to mimic the probe stimuli but instead produced one of the two call classes as in the training sessions, showing that birds learned that each stimulus call served as a discriminative stimulus but not as a vocal template for imitation. In Experiment 3, birds were then trained with stimulus calls falling along a 24-step acoustic gradient which varied between the two sounds representing the two contact call categories. As before, birds obtained a reward when the bird’s vocalization matched that of the stimulus above a criterion level. Since the first step and the last step in the gradient were the birds’ original contact calls,　these two patterns were easily matched. Intermediate contact calls in the gradient were much harder for the birds to match. After extensive training, one bird learned to produce contact calls that had only a modest similarity to the intermediate contact calls along the gradient. In spite of remarkable vocal plasticity under natural conditions, operant conditioning methods with budgerigars, even after extensive training and rigorous control of vocal discriminative stimuli, failed to show vocal learning.

Optimal service using Matlab - simulink controlled Queuing system at call centers

Science.gov (United States)

Balaji, N.; Siva, E. P.; Chandrasekaran, A. D.; Tamilazhagan, V.

2018-04-01

This paper presents graphical integrated model based academic research on telephone call centres. This paper introduces an important feature of impatient customers and abandonments in the queue system. However the modern call centre is a complex socio-technical system. Queuing theory has now become a suitable application in the telecom industry to provide better online services. Through this Matlab-simulink multi queuing structured models provide better solutions in complex situations at call centres. Service performance measures analyzed at optimal level through Simulink queuing model.

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

Science.gov (United States)

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Providing QoS through machine-learning-driven adaptive multimedia applications.

Science.gov (United States)

Ruiz, Pedro M; Botía, Juan A; Gómez-Skarmeta, Antonio

2004-06-01

We investigate the optimization of the quality of service (QoS) offered by real-time multimedia adaptive applications through machine learning algorithms. These applications are able to adapt in real time their internal settings (i.e., video sizes, audio and video codecs, among others) to the unpredictably changing capacity of the network. Traditional adaptive applications just select a set of settings to consume less than the available bandwidth. We propose a novel approach in which the selected set of settings is the one which offers a better user-perceived QoS among all those combinations which satisfy the bandwidth restrictions. We use a genetic algorithm to decide when to trigger the adaptation process depending on the network conditions (i.e., loss-rate, jitter, etc.). Additionally, the selection of the new set of settings is done according to a set of rules which model the user-perceived QoS. These rules are learned using the SLIPPER rule induction algorithm over a set of examples extracted from scores provided by real users. We will demonstrate that the proposed approach guarantees a good user-perceived QoS even when the network conditions are constantly changing.

Construction of SPOC-based Learning Model and its Application in Linguistics Teaching

Directory of Open Access Journals (Sweden)

Hua Lu

2018-02-01

Full Text Available The design of a reasonable learning model must take the new internet age into consideration. Following a contrastive study between MOOCs and SPOCs, a SPOC-based learning model is proposed in this paper. This new learning model consists of four components, the preliminary component composed of anterior analysis and course construction, the restrictive admission component for student number control, the learning procedure component which is subdivided into pre-class session, class session and post-class session, and the evaluation component which includes both online assessment and classroom assessment. This model has its advantages and is shown to be effective through the demonstration of its application in teaching linguistics to college students.

"UML Quiz": Automatic Conversion of Web-Based E-Learning Content in Mobile Applications

Science.gov (United States)

von Franqué, Alexander; Tellioglu, Hilda

2014-01-01

Many educational institutions use Learning Management Systems to provide e-learning content to their students. This often includes quizzes that can help students to prepare for exams. However, the content is usually web-optimized and not very usable on mobile devices. In this work a native mobile application ("UML Quiz") that imports…

Theories and control models and motor learning: clinical applications in neuro-rehabilitation.

Science.gov (United States)

Cano-de-la-Cuerda, R; Molero-Sánchez, A; Carratalá-Tejada, M; Alguacil-Diego, I M; Molina-Rueda, F; Miangolarra-Page, J C; Torricelli, D

2015-01-01

In recent decades there has been a special interest in theories that could explain the regulation of motor control, and their applications. These theories are often based on models of brain function, philosophically reflecting different criteria on how movement is controlled by the brain, each being emphasised in different neural components of the movement. The concept of motor learning, regarded as the set of internal processes associated with practice and experience that produce relatively permanent changes in the ability to produce motor activities through a specific skill, is also relevant in the context of neuroscience. Thus, both motor control and learning are seen as key fields of study for health professionals in the field of neuro-rehabilitation. The major theories of motor control are described, which include, motor programming theory, systems theory, the theory of dynamic action, and the theory of parallel distributed processing, as well as the factors that influence motor learning and its applications in neuro-rehabilitation. At present there is no consensus on which theory or model defines the regulations to explain motor control. Theories of motor learning should be the basis for motor rehabilitation. The new research should apply the knowledge generated in the fields of control and motor learning in neuro-rehabilitation. Copyright © 2011 Sociedad Española de Neurología. Published by Elsevier Espana. All rights reserved.

Application of Technology in Project-Based Distance Learning

Directory of Open Access Journals (Sweden)

Ali Mehrabian

2008-06-01

Full Text Available Present technology and the accessibility of internet have made distance learning easier, more efficient, and more convenient for students. This technology allows instructors and students to communicate asynchronously, at times and locations of their own choosing, by exchanging printed or electronic information. The use of project-based approach is being recognized in the literature as a potential component of courses in the faculties of engineering, science, and technology. Instructors may have to restructure their course differently to accommodate and facilitate the effectiveness of distance learning. A project-based engineering course, traditionally taught in a classroom settings using live mode at the College of Engineering and Computer Sciences at the University of Central Florida (UCF has been transformed to a distance course taught using distance modes. In this case, pedagogical transitions and adjustments are required, in particular for obtaining an optimal balance between the course material and the project work. Project collaboration in groups requires communication, which is possible with extensive utilization of new information and communication technology, such as virtual meetings. This paper discusses the course transition from live to distance modes and touches on some issues as they relate to the effectiveness of this methodology and the lessons learned from its application within different context. More specifically, this discussion includes the benefit of implementing project-based work in the domain of the distance learning courses.

Learning about “wicked” problems in the Global South. Creating a film-based learning environment with “Visual Problem Appraisal”

NARCIS (Netherlands)

Witteveen, L.M.; Lie, R.

2012-01-01

The current complexity of sustainable development in the Global South calls for the design of learning strategies that can deal with this complexity. One such innovative learning strategy, called Visual Problem Appraisal (VPA), is highlighted in this article. The strategy is termed visual as it

The added value of a gaming context and intelligent adaptation for a mobile application for vocabulary learning

NARCIS (Netherlands)

Sandberg, J.; Maris, M.; Hoogendoorn, P.

2014-01-01

Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The

[Deep learning and neuronal networks in ophthalmology : Applications in the field of optical coherence tomography].

Science.gov (United States)

Treder, M; Eter, N

2018-04-19

Deep learning is increasingly becoming the focus of various imaging methods in medicine. Due to the large number of different imaging modalities, ophthalmology is particularly suitable for this field of application. This article gives a general overview on the topic of deep learning and its current applications in the field of optical coherence tomography. For the benefit of the reader it focuses on the clinical rather than the technical aspects.

[Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment].

Science.gov (United States)

Hu, T H; Wan, L; Liu, T A; Wang, M W; Chen, T; Wang, Y H

2017-12-01

Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech recognitions, and also has been extensively used in the fields of face recognition and information retrieval because of its special superiority. Bone X-ray images express different variations in black-white-gray gradations, which have image features of black and white contrasts and level differences. Based on these advantages of deep learning in image recognition, we combine it with the research of bone age assessment to provide basic datum for constructing a forensic automatic system of bone age assessment. This paper reviews the basic concept and network architectures of deep learning, and describes its recent research progress on image recognition in different research fields at home and abroad, and explores its advantages and application prospects in bone age assessment. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Learning to Support Learning Together: An Experience with the Soft Systems Methodology

Science.gov (United States)

Sanchez, Adolfo; Mejia, Andres

2008-01-01

An action research approach called soft systems methodology (SSM) was used to foster organisational learning in a school regarding the role of the learning support department within the school and its relation with the normal teaching-learning activities. From an initial situation of lack of coordination as well as mutual misunderstanding and…

Team-based learning for midwifery education.

Science.gov (United States)

Moore-Davis, Tonia L; Schorn, Mavis N; Collins, Michelle R; Phillippi, Julia; Holley, Sharon

2015-01-01

Many US health care and education stakeholder groups, recognizing the need to prepare learners for collaborative practice in complex care environments, have called for innovative approaches in health care education. Team-based learning is an educational method that relies on in-depth student preparation prior to class, individual and team knowledge assessment, and use of small-group learning to apply knowledge to complex scenarios. Although team-based learning has been studied as an approach to health care education, its application to midwifery education is not well described. A master's-level, nurse-midwifery, didactic antepartum course was revised to a team-based learning format. Student grades, course evaluations, and aggregate American Midwifery Certification Board examination pass rates for 3 student cohorts participating in the team-based course were compared with 3 student cohorts receiving traditional, lecture-based instruction. Students had mixed responses to the team-based learning format. Student evaluations improved when faculty added recorded lectures as part of student preclass preparation. Statistical comparisons were limited by variations across cohorts; however, student grades and certification examination pass rates did not change substantially after the course revision. Although initial course revision was time-consuming for faculty, subsequent iterations of the course required less effort. Team-based learning provides students with more opportunity to interact during on-site classes and may spur application of knowledge into practice. However, it is difficult to assess the effect of the team-based learning approach with current measures. Further research is needed to determine the effects of team-based learning on communication and collaboration skills, as well as long-term performance in clinical practice. This article is part of a special series of articles that address midwifery innovations in clinical practice, education, interprofessional

The Internet, Language Learning, And International Dialogue: 
Constructing Online Foreign Language Learning Websites

OpenAIRE

KARTAL, Erdogan; UZUN, Levent

2015-01-01

In the present study we call attention to the close connection between languages and globalization, and we also emphasize the importance of the Internet and online websites in foreign language teaching and learning as unavoidable elements of computer assisted language learning (CALL). We prepared a checklist by which we investigated 28 foreign language teaching websites (4 from each of seven languages including English, French, German, Italian, Russian, Spanish and Turkish). The participants ...

Active and Adaptive Learning from Biased Data with Applications in Astronomy

DEFF Research Database (Denmark)

Kremer, Jan

This thesis addresses the problem of machine learning from biased datasets in the context of astronomical applications. In astronomy there are many cases in which the training sample does not follow the true distribution. The thesis examines different types of biases and proposes algorithms...... set. Against this background, the thesis begins with a survey of active learning algorithms for the support vector machine. If the cost of additional labeling is prohibitive, unlabeled data can often be utilized instead and the sample selection bias can be overcome through domain adaptation, that is...... to handle them. During learning and when applying the predictive model, active learning enables algorithms to select training examples from a pool of unlabeled data and to request the labels. This allows for selecting examples that maximize the algorithm's accuracy despite an initial bias in the training...

A Proposed Pedagogical Mobile Application for Learning Sign Language

Directory of Open Access Journals (Sweden)

Samir Abou El-Seoud

2013-01-01

Full Text Available A handheld device system, such as cellular phone or a PDA, can be used in acquiring Sign Language (SL. The developed system uses graphic applications. The user uses the graphical system to view and to acquire knowledge about sign grammar and syntax based on the local vernacular particular to the country. This paper explores and exploits the possibility of the development of a mobile system to help the deaf and other people to communicate and learn using handheld devices. The pedagogical assessment of the prototype application that uses a recognition-based interface e.g., images and videos, gave evidence that the mobile application is memorable and learnable. Additionally, considering primary and recency effects in the interface design will improve memorability and learnability.

Machine learning application in online lending risk prediction

OpenAIRE

Yu, Xiaojiao

2017-01-01

Online leading has disrupted the traditional consumer banking sector with more effective loan processing. Risk prediction and monitoring is critical for the success of the business model. Traditional credit score models fall short in applying big data technology in building risk model. In this manuscript, data with various format and size were collected from public website, third-parties and assembled with client's loan application information data. Ensemble machine learning models, random fo...

Teaching and Learning Numerical Analysis and Optimization: A Didactic Framework and Applications of Inquiry-Based Learning

Science.gov (United States)

Lappas, Pantelis Z.; Kritikos, Manolis N.

2018-01-01

The main objective of this paper is to propose a didactic framework for teaching Applied Mathematics in higher education. After describing the structure of the framework, several applications of inquiry-based learning in teaching numerical analysis and optimization are provided to illustrate the potential of the proposed framework. The framework…

Intelligent Machine Learning Approaches for Aerospace Applications

Science.gov (United States)

Sathyan, Anoop

Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire

Facilitation of social learning in teacher education: the ‘Dimensions of Social Learning Framework’

NARCIS (Netherlands)

de Laat, M.M.; Vrieling, E.; van den Beemt, A.A.J.; McDonald, J.; Cater-Steel, A.

2017-01-01

To understand the organization of social learning by groups in practice, this chapter elaborates on the use of a framework of dimensions and indicators to explore social learning within (prospective) teacher groups. The applied framework that we call the ‘Dimensions of Social Learning (DSL)

If I am unsuccessful, when is the next call if I wish t

International Development Research Centre (IDRC) Digital Library (Canada)

IDRC CRDI

Section 11 of the call document for the specific call to which you applied includes the date by which all applicants will ... We will not support “pure” hard science projects, however well ... possible. Availability of funding from other sources is a plus.

Toward Mobile Assisted Language Learning Apps for Professionals That Integrate Learning into the Daily Routine

Science.gov (United States)

Pareja-Lora, Antonio; Arús-Hita, Jorge; Read, Timothy; Rodríguez-Arancón, Pilar; Calle-Martínez, Cristina; Pomposo, Lourdes; Martín-Monje, Elena; Bárcena, Elena

2013-01-01

In this short paper, we present some initial work on Mobile Assisted Language Learning (MALL) undertaken by the ATLAS research group. ATLAS embraced this multidisciplinary field cutting across Mobile Learning and Computer Assisted Language Learning (CALL) as a natural step in their quest to find learning formulas for professional English that…

47 CFR 22.921 - 911 call processing procedures; 911-only calling mode.

Science.gov (United States)

2010-10-01

... programming in the mobile unit that determines the handling of a non-911 call and permit the call to be... CARRIER SERVICES PUBLIC MOBILE SERVICES Cellular Radiotelephone Service § 22.921 911 call processing procedures; 911-only calling mode. Mobile telephones manufactured after February 13, 2000 that are capable of...

Pervasive Learning

DEFF Research Database (Denmark)

Helms, Niels Henrik; Larsen, Lasse Juel

2009-01-01

, it is not a specific place where you can access scarce information. Pervasive or ubiquitous communication opens up for taking the organizing and design of learning landscapes a step further. Furthermore it calls for theoretical developments, which can open up for a deeper understanding of the relationship between...... emerging contexts, design of contexts and learning....

It's not maths; it's science: exploring thinking dispositions, learning thresholds and mindfulness in science learning

Science.gov (United States)

Quinnell, R.; Thompson, R.; LeBard, R. J.

2013-09-01

Developing quantitative skills, or being academically numerate, is part of the curriculum agenda in science teaching and learning. For many of our students, being asked to 'do maths' as part of 'doing science' leads to disengagement from learning. Notions of 'I can't do maths' speak of a rigidity of mind, a 'standoff', forming a barrier to learning in science that needs to be addressed if we, as science educators, are to offer solutions to the so-called 'maths problem' and to support students as they move from being novice to expert. Moving from novice to expert is complex and we lean on several theoretical frameworks (thinking dispositions, threshold concepts and mindfulness in learning) to characterize this pathway in science, with a focus on quantitative skills. Fluid thinking and application of numeracy skills are required to manipulate experimental data sets and are integral to our science practice; we need to stop students from seeing them as optional 'maths' or 'statistics' tasks within our discipline. Being explicit about the ways those in the discipline think, how quantitative data is processed, and allowing places for students to address their skills (including their confidence) offer some ways forward.

Performance, Cognitive Load, and Behaviour of Technology-Assisted English Listening Learning: From CALL to MALL

Science.gov (United States)

Chang, Chi-Cheng; Warden, Clyde A.; Liang, Chaoyun; Chou, Pao-Nan

2018-01-01

This study examines differences in English listening comprehension, cognitive load, and learning behaviour between outdoor ubiquitous learning and indoor computer-assisted learning. An experimental design, employing a pretest-posttest control group is employed. Randomly assigned foreign language university majors joined either the experimental…

Community-Based Art Education and Performance: Pointing to a Place Called Home

Science.gov (United States)

Washington, G. E.

2011-01-01

Can art make a difference? This is a call for a new sense of interconnectivity among visual art programs in and out of schools. This common ground will be found in the embodiment of performance, critical reflection, and social change within art learning. One goal of this article is to encourage educators to use the "verbs of art" for…

Rethinking expansive learning

DEFF Research Database (Denmark)

Kolbæk, Ditte; Lundh Snis, Ulrika

Abstract: This paper analyses an online community of master’s students taking a course in ICT and organisational learning. The students initiated and facilitated an educational design for organisational learning called Proactive Review in the organisation where they are employed. By using an online...... discussion forum on Google groups, they created new ways of reflecting and learning. We used netnography to select qualitative postings from the online community and expansive learning concepts for data analysis. The findings show how students changed practices of organisational learning...

Social Learning Theory: its application in the context of nurse education.

Science.gov (United States)

Bahn, D

2001-02-01

Cognitive theories are fundamental to enable problem solving and the ability to understand and apply principles in a variety of situations. This article looks at Social Learning Theory, critically analysing its principles, which are based on observational learning and modelling, and considering its value and application in the context of nurse education. It also considers the component processes that will determine the outcome of observed behaviour, other than reinforcement, as identified by Bandura, namely: attention, retention, motor reproduction, and motivation. Copyright 2001 Harcourt Publishers Ltd.

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

Science.gov (United States)

Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

An Adaptive Web-Based Learning Environment for the Application of Remote Sensing in Schools

Science.gov (United States)

Wolf, N.; Fuchsgruber, V.; Riembauer, G.; Siegmund, A.

2016-06-01

Satellite images have great educational potential for teaching on environmental issues and can promote the motivation of young people to enter careers in natural science and technology. Due to the importance and ubiquity of remote sensing in science, industry and the public, the use of satellite imagery has been included into many school curricular in Germany. However, its implementation into school practice is still hesitant, mainly due to lack of teachers' know-how and education materials that align with the curricula. In the project "Space4Geography" a web-based learning platform is developed with the aim to facilitate the application of satellite imagery in secondary school teaching and to foster effective student learning experiences in geography and other related subjects in an interdisciplinary way. The platform features ten learning modules demonstrating the exemplary application of original high spatial resolution remote sensing data (RapidEye and TerraSAR-X) to examine current environmental issues such as droughts, deforestation and urban sprawl. In this way, students will be introduced into the versatile applications of spaceborne earth observation and geospatial technologies. The integrated web-based remote sensing software "BLIF" equips the students with a toolset to explore, process and analyze the satellite images, thereby fostering the competence of students to work on geographical and environmental questions without requiring prior knowledge of remote sensing. This contribution presents the educational concept of the learning environment and its realization by the example of the learning module "Deforestation of the rainforest in Brasil".

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Application of artificial neural network with extreme learning machine for economic growth estimation

Science.gov (United States)

Milačić, Ljubiša; Jović, Srđan; Vujović, Tanja; Miljković, Jovica

2017-01-01

The purpose of this research is to develop and apply the artificial neural network (ANN) with extreme learning machine (ELM) to forecast gross domestic product (GDP) growth rate. The economic growth forecasting was analyzed based on agriculture, manufacturing, industry and services value added in GDP. The results were compared with ANN with back propagation (BP) learning approach since BP could be considered as conventional learning methodology. The reliability of the computational models was accessed based on simulation results and using several statistical indicators. Based on results, it was shown that ANN with ELM learning methodology can be applied effectively in applications of GDP forecasting.

Stand-alone photovoltaic applications. Lessons learned

International Nuclear Information System (INIS)

Loois, G.; Van Hemert, B.

1999-02-01

The IEA Photovoltaic Power Systems Programme (PVPS) is one of the collaborative R and D agreements established within the IEA. The objective of Task III is to promote and facilitate the exchange of information and experiences in the field of PV Systems in Stand-alone and Island Applications (SAPV). The book focuses on the practical experiences gained, and does not aim to provide a complete manual on SAPV. When Task III started its activities in 1993, a collection of 50 'State of the art' projects was published in the book 'Examples of Stand-Alone Photovoltaic Systems'. This publication marked the base line for the work of the task. Now, in 1998, the showcases from each country demonstrate the lessons learned in five years of cooperation. The book consists of two parts. The first part contains eight chapters dealing with a specific aspect of stand-alone PV. The second part introduces 14 national showcase projects in a systematic presentation. Each chapter and showcase can be read independently from the rest of the book. Chapter 2, contributed by The Netherlands, analyses the market for stand-alone PV systems. It gives an overview of the 'traditional' application of stand-alone PV, which is the electrification of remote buildings and which has been addressed in depth in other publications. The focus is on the market niches of service applications that are also interesting for more densely populated areas, e.g. in industrialised countries. The United Kingdom illustrates the economic aspects in Chapter 3. Cost comparisons are made, but more important is the illustration of the non-financial considerations that make PV the preferred choice as a power source for many applications. Switzerland explores in Chapter 4 (financing aspects) different financing mechanisms, and financial policies used to overcome the initial cost barrier. Most of these approaches have been applied in developing countries rather than in the western world. Using various examples from all over the

Application of Computer-Assisted Learning Methods in the Teaching of Chemical Spectroscopy.

Science.gov (United States)

Ayscough, P. B.; And Others

1979-01-01

Discusses the application of computer-assisted learning methods to the interpretation of infrared, nuclear magnetic resonance, and mass spectra; and outlines extensions into the area of integrated spectroscopy. (Author/CMV)

Teachers' Reports of Learning and Application to Pedagogy Based on Engagement in Collaborative Peer Video Analysis

Science.gov (United States)

Christ, Tanya; Arya, Poonam; Chiu, Ming Ming

2014-01-01

Given international use of video-based reflective discussions in teacher education, and the limited knowledge about whether teachers apply learning from these discussions, we explored teachers' learning of new ideas about pedagogy and their self-reported application of this learning. Nine inservice and 48 preservice teachers participated in…

CALL--Enhanced L2 Listening Skills--Aiming for Automatization in a Multimedia Environment

Science.gov (United States)

Mayor, Maria Jesus Blasco

2009-01-01

Computer Assisted Language Learning (CALL) and L2 listening comprehension skill training are bound together for good. A neglected macroskill for decades, developing listening comprehension skill is now considered crucial for L2 acquisition. Thus this paper makes an attempt to offer latest information on processing theories and L2 listening…

Teaching learning based optimization algorithm and its engineering applications

CERN Document Server

Rao, R Venkata

2016-01-01

Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.

Learning about “wicked” problems in the Global South. Creating a film-based learning environment with “Visual Problem Appraisal”

OpenAIRE

Loes Witteveen; Rico Lie

2012-01-01

The current complexity of sustainable development in the Global South calls for the design of learning strategies that can deal with this complexity. One such innovative learning strategy, called Visual Problem Appraisal (VPA), is highlighted in this article. The strategy is termed visual as it creates a learning environment that is film-based. VPA enhances the analysis of complex issues, and facilitates stakeholder dialogue and action planning. The strategy is used in workshops dealing with ...

Greedy Deep Dictionary Learning

OpenAIRE

Tariyal, Snigdha; Majumdar, Angshul; Singh, Richa; Vatsa, Mayank

2016-01-01

In this work we propose a new deep learning tool called deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion, one layer at a time. This requires solving a simple (shallow) dictionary learning problem, the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like stacked autoencoder and deep belief network; and state of the art supervised dictionary learning t...

Language Learners Perceptions and Experiences on the Use of Mobile Applications for Independent Language Learning in Higher Education

Directory of Open Access Journals (Sweden)

Ana Niño

2015-08-01

Full Text Available With the widespread use of mobile phones and portable devices it is inevitable to think of Mobile Assisted Language Learning as a means of independent learning in Higher Education. Nowadays many learners are keen to explore the wide variety of applications available in their portable and always readily available mobile phones and tablets. The fact that they are keen to take control of their learning and autonomy is thought to lead to greater motivation and engagement, and the link with games-based learning suggests that the fun factor involved should not be overseen. This paper focuses on the use of mobile applications for independent language learning in higher education. It investigates how learners use mobile apps in line with their classes to enhance their learning experience. We base our analysis on a survey carried out in autumn 2013 in which 286 credited and non-credited language students from various levels of proficiency at The University of Manchester express their perceptions on the advantages and disadvantages of the use of mobile applications for independent language learning, together with examples of useful apps and suggestions of how these could be integrated in the language class.

Incentive structure in team-based learning: graded versus ungraded Group Application exercises.

Science.gov (United States)

Deardorff, Adam S; Moore, Jeremy A; McCormick, Colleen; Koles, Paul G; Borges, Nicole J

2014-04-21

Previous studies on team-based learning (TBL) in medical education demonstrated improved learner engagement, learner satisfaction, and academic performance; however, a paucity of information exists on modifications of the incentive structure of "traditional" TBL practices. The current study investigates the impact of modification to conventional Group Application exercises by examining student preference and student perceptions of TBL outcomes when Group Application exercises are excluded from TBL grades. During the 2009-2010 and 2010-2011 academic years, 175 students (95.6% response rate) completed a 22-item multiple choice survey followed by 3 open response questions at the end of their second year of medical school. These students had participated in a TBL supplemented preclinical curriculum with graded Group Application exercises during year one and ungraded Group Application exercises during year two of medical school. Chi-square analyses showed significant differences between grading categories for general assessment of TBL, participation and communication, intra-team discussion, inter-team discussion, student perceptions of their own effort and development of teamwork skills. Furthermore, 83.8% of students polled prefer ungraded Group Application exercises with only 7.2% preferring graded and 9.0% indicating no preference. The use of ungraded Group Application exercises appears to be a successful modification of TBL, making it more "student-friendly" while maintaining the goals of active learning and development of teamwork skills.

Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms

Science.gov (United States)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.

2017-12-01

Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p  =  0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.

Deep learning for single-molecule science

Science.gov (United States)

Albrecht, Tim; Slabaugh, Gregory; Alonso, Eduardo; Al-Arif, SM Masudur R.

2017-10-01

Exploring and making predictions based on single-molecule data can be challenging, not only due to the sheer size of the datasets, but also because a priori knowledge about the signal characteristics is typically limited and poor signal-to-noise ratio. For example, hypothesis-driven data exploration, informed by an expectation of the signal characteristics, can lead to interpretation bias or loss of information. Equally, even when the different data categories are known, e.g., the four bases in DNA sequencing, it is often difficult to know how to make best use of the available information content. The latest developments in machine learning (ML), so-called deep learning (DL) offer interesting, new avenues to address such challenges. In some applications, such as speech and image recognition, DL has been able to outperform conventional ML strategies and even human performance. However, to date DL has not been applied much in single-molecule science, presumably in part because relatively little is known about the ‘internal workings’ of such DL tools within single-molecule science as a field. In this Tutorial, we make an attempt to illustrate in a step-by-step guide how one of those, a convolutional neural network (CNN), may be used for base calling in DNA sequencing applications. We compare it with a SVM as a more conventional ML method, and discuss some of the strengths and weaknesses of the approach. In particular, a ‘deep’ neural network has many features of a ‘black box’, which has important implications on how we look at and interpret data.

Implications of Multimodal Learning Models for foreign language teaching and learning

Directory of Open Access Journals (Sweden)

Miguel Farías

2011-04-01

Full Text Available This literature review article approaches the topic of information and communications technologies from the perspective of their impact on the language learning process, with particular emphasis on the most appropriate designs of multimodal texts as informed by models of multimodal learning. The first part contextualizes multimodality within the fields of discourse studies, the psychology of learning and CALL; the second, deals with multimodal conceptions of reading and writing by discussing hypertextuality and literacy. A final section outlines the possible implications of multimodal learning models for foreign language teaching and learning.

A Call for Expanding Inclusive Student Engagement in SoTL

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Peter Felten

2013-09-01

of student-faculty partnerships focused on inquiry into teaching and learning. However, some students tend to be privileged in SoTL initiatives while others are discouraged, implicitly or explicitly, from engaging in this work. In this paper, we consider why certain students tend to be excluded from SoTL, summarize the possible developmental gains made by students and faculty when diverse student voices are included, and highlight strategies for generating a more inclusive SoTL. We call for expanding student engagement in SoTL by encouraging a diversity of student voices to engage in co-inquiry with faculty. Inclusive engagement has tremendous potential to enhance student and faculty learning, to deepen SoTL initiatives, and to help redress the exclusionary practices that too often occur in higher education.

Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent

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Zunyi Tang

2013-01-01

Full Text Available Sparse representation of signals via an overcomplete dictionary has recently received much attention as it has produced promising results in various applications. Since the nonnegativities of the signals and the dictionary are required in some applications, for example, multispectral data analysis, the conventional dictionary learning methods imposed simply with nonnegativity may become inapplicable. In this paper, we propose a novel method for learning a nonnegative, overcomplete dictionary for such a case. This is accomplished by posing the sparse representation of nonnegative signals as a problem of nonnegative matrix factorization (NMF with a sparsity constraint. By employing the coordinate descent strategy for optimization and extending it to multivariable case for processing in parallel, we develop a so-called parallel coordinate descent dictionary learning (PCDDL algorithm, which is structured by iteratively solving the two optimal problems, the learning process of the dictionary and the estimating process of the coefficients for constructing the signals. Numerical experiments demonstrate that the proposed algorithm performs better than the conventional nonnegative K-SVD (NN-KSVD algorithm and several other algorithms for comparison. What is more, its computational consumption is remarkably lower than that of the compared algorithms.

Incentive structure in team-based learning: graded versus ungraded Group Application exercises

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Adam S Deardorff

2014-04-01

Conclusion: The use of ungraded Group Application exercises appears to be a successful modification of TBL, making it more “student-friendly” while maintaining the goals of active learning and development of teamwork skills.

Short Project-Based Learning with MATLAB Applications to Support the Learning of Video-Image Processing

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Gil, Pablo

2017-10-01

University courses concerning Computer Vision and Image Processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the development, implementation and assessment of a short project-based engineering course with MATLAB applications Multimedia Engineering being taken by Bachelor's degree students. The principal goal of all course lectures and hands-on laboratory activities was for the students to not only acquire image-specific technical skills but also a general knowledge of data analysis so as to locate phenomena in pixel regions of images and video frames. This would hopefully enable the students to develop skills regarding the implementation of the filters, operators, methods and techniques used for image processing and computer vision software libraries. Our teaching-learning process thus permits the accomplishment of knowledge assimilation, student motivation and skill development through the use of a continuous evaluation strategy to solve practical and real problems by means of short projects designed using MATLAB applications. Project-based learning is not new. This approach has been used in STEM learning in recent decades. But there are many types of projects. The aim of the current study is to analyse the efficacy of short projects as a learning tool when compared to long projects during which the students work with more independence. This work additionally presents the impact of different types of activities, and not only short projects, on students' overall results in this subject. Moreover, a statistical study has allowed the author to suggest a link between the students' success ratio and the type of content covered and activities completed on the course. The results described in this paper show that those students who took part

Learning Theories and Skills in Online Second Language Teaching and Learning: Dilemmas and Challenges

Science.gov (United States)

Petersen, Karen Bjerg

2014-01-01

For decades foreign and second language teachers have taken advantage of the technology development and ensuing possibilities to use e-learning facilities for language training. Since the 1980s, the use of computer assisted language learning (CALL), Internet, web 2.0, and various kinds of e-learning technology has been developed and researched…

Learning Flex 4 Getting Up to Speed with Rich Internet Application Design and Development

CERN Document Server

Cole, Alaric

2010-01-01

Learn Adobe Flex 4 in a fun and engaging way with this book's unique, hands-on approach. Using clear examples and step-by-step coaching from two experts, you'll create four applications that demonstrate fundamental Flex programming concepts. Throughout the course of this book, you'll learn how to enhance user interaction with ActionScript, and create and skin a user interface with Flex's UI components (MXML) and Adobe's new FXG graphics format. You'll also be trained to manage dynamic data, connect to a database using server-side script, and deploy applications to both the Web and the deskto

APPLICABILITY OF COOPERATIVE LEARNING TECHNIQUES IN DIFFERENT CLASSROOM CONTEXTS

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Dr. Issy Yuliasri

2017-04-01

Full Text Available This paper is based on the results of pre-test post-test, feedback questionnaire and observation during a community service program entitled ―Training on English Teaching using Cooperative Learning Techniques for Elementary and Junior High School Teachers of Sekolah Alam Arridho Semarang‖. It was an English teaching training program intended to equip the teachers with the knowledge and skills of using the different cooperative learning techniques such as jigsaw, think-pair-share, three-step interview, roundrobin braistorming, three-minute review, numbered heads together, team-pair-solo, circle the sage, dan partners. This program was participated by 8 teachers of different subjects (not only English, but most of them had good mastery of English. The objectives of this program was to improve teachers‘ skills in using the different cooperative learning techniques to vary their teaching, so that students would be more motivated to learn and improve their English skill. Besides, the training also gave the teachers the knowledge and skills to adjust their techniques with the basic competence and learning objectives to be achieved as well as with the teaching materials to be used. This was also done through workshops using cooperative learning techniques, so that the participants had real experiences of using cooperative learning techniques (learning by doing. The participants were also encouraged to explore the applicability of the techniques in their classroom contexts, in different areas of their teaching. This community service program showed very positive results. The pre-test and post-test results showed that before the training program all the participants did not know the nine cooperative techniques to be trained, but after the program they mastered the techniques as shown from the teaching-learning scenarios they developed following the test instructions. In addition, the anonymous questionnaires showed that all the participants

"Knowing Is Not Enough; We Must Apply": Reflections on a Failed Action Learning Application

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Reese, Simon

2015-01-01

This paper reflects upon a sub-optimal action learning application with a strategic business re-design project. The objective of the project was to improve the long-term business performance of a subsidiary business and build the strategic plan. Action learning was introduced to aid the group in expanding their view of the real problems…

Learning to trade via direct reinforcement.

Science.gov (United States)

Moody, J; Saffell, M

2001-01-01

We present methods for optimizing portfolios, asset allocations, and trading systems based on direct reinforcement (DR). In this approach, investment decision-making is viewed as a stochastic control problem, and strategies are discovered directly. We present an adaptive algorithm called recurrent reinforcement learning (RRL) for discovering investment policies. The need to build forecasting models is eliminated, and better trading performance is obtained. The direct reinforcement approach differs from dynamic programming and reinforcement algorithms such as TD-learning and Q-learning, which attempt to estimate a value function for the control problem. We find that the RRL direct reinforcement framework enables a simpler problem representation, avoids Bellman's curse of dimensionality and offers compelling advantages in efficiency. We demonstrate how direct reinforcement can be used to optimize risk-adjusted investment returns (including the differential Sharpe ratio), while accounting for the effects of transaction costs. In extensive simulation work using real financial data, we find that our approach based on RRL produces better trading strategies than systems utilizing Q-learning (a value function method). Real-world applications include an intra-daily currency trader and a monthly asset allocation system for the S&P 500 Stock Index and T-Bills.

Applications of Adaptive Learning Controller to Synthetic Aperture Radar.

Science.gov (United States)

1985-02-01

TERMS (Continue on retuerse if necessary and identify by block num ber) FIELD YGROUP SUB. GR. Adaptive control, aritificial intelligence , synthetic aetr1...application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning...wavelength Al SE!RI M RADAR DIVISION REFERENCES 1. Barto, A.G. and R.S. Sutton, Goal Seeking Components for Adaptive Intelligence : An Initial Assessment

TO LEARN FROM TEACHERS AT SCHOOL, IDEAL TEACHER OR E-LEARNING APPLICATIONS FROM THE PERSPECTIVES OF GIFTED STUDENTS

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Bahadir ERISTI,

2012-08-01

Full Text Available The present study, aimed at revealing the views of elementary school gifted students about the roles and behaviors of their teachers in class as well as about the in-class roles and behaviors that they expect from an ideal teacher with respect to different variables. Another question in the study was directed to determine students’ views about learning academic subjects via e-learning applications instead of at teachers. The participants of the study were 46 gifted students identified with the diagnosis system of “Education program for the gifted” executed in the Department of Gifted Education at the Education Faculty of Anadolu University. The research data were collected via a five-point Likert-type scale developed and tested by the researcher for its validity and reliability. For the analysis of the research data, paired sample t-test, one of descriptive parametrical statistical techniques, was applied. The findings obtained in the study revealed that according to gifted students, the in-class behaviors demonstrated by the course teachers were mostly those related to their roles of guidance for students. The behaviors of the course teachers within the scope of this role were followed by those related to providing information and maintaining the discipline, respectively. The behaviors least demonstrated by the teachers were those related to the role of supporting the students and those related to being a model for them. According to the students, an ideal teacher should at most demonstrate behaviors in class regarding the role of guiding the students and those regarding the role of providing information. According to the gifted students, the roles and behaviors of their teachers in class are quite different from the behaviors expected from an ideal teacher. Students do not regard e-learning applications as an alternative to learning from teachers. Rather, they prefer learning from their teachers to technology-aided learning environments

Detection and Classification of Baleen Whale Foraging Calls Combining Pattern Recognition and Machine Learning Techniques

Science.gov (United States)

2016-12-01

for a call is also a time- consuming task. None of these chores bothers the analyst when applying the selection algorithm. With help from the...1365- 2907.2007.00106.x. Castellote, M., C. W. Clark, and M. O. Lammers, 2012: Acoustic and behavioural changes by fin whales (Balaenoptera physalus...separation of blue whale call types on a southern California feeding ground. Animal Behaviour , 74, 881–894, doi:10.1016/j.anbehav.2007.01.022. Rocha, R

“Call for Prices”: Strategic Implications of Raising Consumers' Costs

OpenAIRE

Preyas S. Desai; Anand Krishnamoorthy; Preethika Sainam

2010-01-01

Many consumer durable retailers often do not advertise their prices and instead ask consumers to call them for prices. It is easy to see that this practice increases the consumers' cost of learning the prices of products they are considering, yet firms commonly use such practices. Not advertising prices may reduce the firm's advertising costs, but the strategic effects of doing so are not clear. Our objective is to examine the strategic effects of this practice. In particular, how does making...

Robust representation and recognition of facial emotions using extreme sparse learning.

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Shojaeilangari, Seyedehsamaneh; Yau, Wei-Yun; Nandakumar, Karthik; Li, Jun; Teoh, Eam Khwang

2015-07-01

Recognition of natural emotions from human faces is an interesting topic with a wide range of potential applications, such as human-computer interaction, automated tutoring systems, image and video retrieval, smart environments, and driver warning systems. Traditionally, facial emotion recognition systems have been evaluated on laboratory controlled data, which is not representative of the environment faced in real-world applications. To robustly recognize the facial emotions in real-world natural situations, this paper proposes an approach called extreme sparse learning, which has the ability to jointly learn a dictionary (set of basis) and a nonlinear classification model. The proposed approach combines the discriminative power of extreme learning machine with the reconstruction property of sparse representation to enable accurate classification when presented with noisy signals and imperfect data recorded in natural settings. In addition, this paper presents a new local spatio-temporal descriptor that is distinctive and pose-invariant. The proposed framework is able to achieve the state-of-the-art recognition accuracy on both acted and spontaneous facial emotion databases.

WHAT CAN WE LEARN FROM THE “WATER BEARS” FOR THE ADHESION SYSTEMS USING IN SPACE APPLICATIONS?

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Alexander E. Filippov

2015-12-01

Full Text Available Recent progress in space research and in particular appearance of complex movable constructions with a number of components exposed to the extreme conditions of open space causes a strong demand for development of new tribological and adhesion systems which are able to resist such conditions. In the last few years, many engineering solutions in the field of tribology and adhesion have been found based on “biomimetics approach” that is searching for ideas originally created by living nature and optimized during billions of years of natural selection. Surprisingly some of the living creatures are found to be optimized even for survival for a long time in the conditions of open space. Such ability is very promising from the point of view of development of new adhesives for future space applications. In this paper we discuss what we can learn in this context from the so-called “water bears” (tardigrades in a combination with some other features, already adopted to reversible technical adhesives from other animals, such as insects and Gecko lizards.

Education and learning: what's on the horizon?

Science.gov (United States)

Pilcher, Jobeth

2014-01-01

Numerous organizations have called for significant changes in education for health care professionals. The call has included the need to incorporate evidence-based as well as innovative strategies. Previous articles in this column have focused primarily on evidence-based teaching strategies, including concept mapping, brain-based learning strategies, methods of competency assessment, and so forth. This article shifts the focus to new ways of thinking about knowledge and education. The article will also introduce evolving, innovative, less commonly used learning strategies and provide a peek into the future of learning.

Army, Presidential, and Corporate Strategic Transitions: The Importance of Transition Teams and the Application of Lessons Learned

Science.gov (United States)

2006-05-25

accessed from http://www.american.edu/15pointplan/WhatIsABestPractice.html on 17 Feb 2006. Argenti , Paul A., Corporate Communication . 3rd ed. Boston...Army, Presidential, and Corporate Strategic Transitions: The Importance of Transition Teams and the Application of Lessons Learned A Monograph...SUBTITLE Army, Presidential, and Corporate Strategic Transitions: The Importance of Transition Teams and the Application of Lessons Learned 5c

Metaphysics and Learning

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Verran, Helen

2007-01-01

Is it possible to learn and simultaneously articulate the metaphysical basis of that learning? In my contribution to the forum I tell of how I came to recognise that bilingual Yoruba children could articulate the contrasting metaphysical framings of Yoruba and English numbering. The story introduces an arena I call "ontics" that recognises the…

Designing Applications for Physics Learning: Facilitating High School Students' Conceptual Understanding by Using Tablet PCs

Science.gov (United States)

Wang, June-Yi; Wu, Hsin-Kai; Chien, Sung-Pei; Hwang, Fu-Kwun; Hsu, Ying-Shao

2015-01-01

So far relatively little research in education has explored the pedagogical and learning potentials of applications (Apps) on tablet PCs (TPCs). Drawing upon research on learning technologies and taking an embodied perspective, this study first identified educational functionalities of TPCs and generated guidelines to design educational Apps for…

Machine learning with quantum relative entropy

International Nuclear Information System (INIS)

Tsuda, Koji

2009-01-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Machine learning with quantum relative entropy

Energy Technology Data Exchange (ETDEWEB)

Tsuda, Koji [Max Planck Institute for Biological Cybernetics, Spemannstr. 38, Tuebingen, 72076 (Germany)], E-mail: koji.tsuda@tuebingen.mpg.de

2009-12-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Systematic Poisoning Attacks on and Defenses for Machine Learning in Healthcare.

Science.gov (United States)

Mozaffari-Kermani, Mehran; Sur-Kolay, Susmita; Raghunathan, Anand; Jha, Niraj K

2015-11-01

Machine learning is being used in a wide range of application domains to discover patterns in large datasets. Increasingly, the results of machine learning drive critical decisions in applications related to healthcare and biomedicine. Such health-related applications are often sensitive, and thus, any security breach would be catastrophic. Naturally, the integrity of the results computed by machine learning is of great importance. Recent research has shown that some machine-learning algorithms can be compromised by augmenting their training datasets with malicious data, leading to a new class of attacks called poisoning attacks. Hindrance of a diagnosis may have life-threatening consequences and could cause distrust. On the other hand, not only may a false diagnosis prompt users to distrust the machine-learning algorithm and even abandon the entire system but also such a false positive classification may cause patient distress. In this paper, we present a systematic, algorithm-independent approach for mounting poisoning attacks across a wide range of machine-learning algorithms and healthcare datasets. The proposed attack procedure generates input data, which, when added to the training set, can either cause the results of machine learning to have targeted errors (e.g., increase the likelihood of classification into a specific class), or simply introduce arbitrary errors (incorrect classification). These attacks may be applied to both fixed and evolving datasets. They can be applied even when only statistics of the training dataset are available or, in some cases, even without access to the training dataset, although at a lower efficacy. We establish the effectiveness of the proposed attacks using a suite of six machine-learning algorithms and five healthcare datasets. Finally, we present countermeasures against the proposed generic attacks that are based on tracking and detecting deviations in various accuracy metrics, and benchmark their effectiveness.

Perceiving a calling, living a calling, and job satisfaction: testing a moderated, multiple mediator model.

Science.gov (United States)

Duffy, Ryan D; Bott, Elizabeth M; Allan, Blake A; Torrey, Carrie L; Dik, Bryan J

2012-01-01

The current study examined the relation between perceiving a calling, living a calling, and job satisfaction among a diverse group of employed adults who completed an online survey (N = 201). Perceiving a calling and living a calling were positively correlated with career commitment, work meaning, and job satisfaction. Living a calling moderated the relations of perceiving a calling with career commitment and work meaning, such that these relations were more robust for those with a stronger sense they were living their calling. Additionally, a moderated, multiple mediator model was run to examine the mediating role of career commitment and work meaning in the relation of perceiving a calling and job satisfaction, while accounting for the moderating role of living a calling. Results indicated that work meaning and career commitment fully mediated the relation between perceiving a calling and job satisfaction. However, the indirect effects of work meaning and career commitment were only significant for individuals with high levels of living a calling, indicating the importance of living a calling in the link between perceiving a calling and job satisfaction. Implications for research and practice are discussed. (c) 2012 APA, all rights reserved.

Call Center Capacity Planning

DEFF Research Database (Denmark)

Nielsen, Thomas Bang

in order to relate the results to the service levels used in call centers. Furthermore, the generic nature of the approximation is demonstrated by applying it to a system incorporating a dynamic priority scheme. In the last paper Optimization of overflow policies in call centers, overflows between agent......The main topics of the thesis are theoretical and applied queueing theory within a call center setting. Call centers have in recent years become the main means of communication between customers and companies, and between citizens and public institutions. The extensively computerized infrastructure...... in modern call centers allows for a high level of customization, but also induces complicated operational processes. The size of the industry together with the complex and labor intensive nature of large call centers motivates the research carried out to understand the underlying processes. The customizable...

Teaching Compassion in Prison: A Key to Learning

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Em Strang

2015-12-01

Full Text Available In a project with long-term prisoners at HMP Dumfries, Scotland, tutors and students explore the notion and application of compassion, focusing in particular on the ways in which understanding compassion enables learning – not just the learning of academic subjects but also of interpersonal skills and emotional intelligence. The project highlights the benefits of teaching a so-called extracurricular subject, at the same time as revealing its centrality to learning in the first place. A lack of adequate teaching time in prison, and the fact that compassion is not considered a core subject in education, are both cited as obstacles in consolidating the work of the project. The benefits of teaching compassion - emotional, intellectual and spiritual - was made clear through written and verbal student feedback. Three short workshops highlighted the enormous potential in developing and establishing compassion as both subject and practice in prison education. It is hoped that practitioners and researchers will support the expansion of this work throughout prisons.

Deep learning guided stroke management: a review of clinical applications.

Science.gov (United States)

Feng, Rui; Badgeley, Marcus; Mocco, J; Oermann, Eric K