Speaking Personally--With Paul Avon

ERIC Educational Resources Information Center

Martin, D'Arcy

2012-01-01

This article presents an interview with Paul Avon, the former executive director of the Canadian Virtual College Consortium. Avon has spent over fifteen years in the distance learning (DL) field managing the production and delivery of online learning at TVOntario, Humber College, the Sri Lankan National Online Distance Education Service, and the…

A Hierarchy of Needs for a Virtual Class.

ERIC Educational Resources Information Center

Beise, Catherine; Wynekoop, Judy

Distance Learning (DL) initiatives are proceeding full speed ahead, both within traditional universities and in "virtual" institutions specializing in on-line course delivery. Much has been written about the virtues and limitations, the obstacles and enablers, and the "Do's" and "Don'ts" of DL. However, considerable…

Distance Learning Skills and Responsibilities: A Content Analysis of Job Announcements 1996-2010

ERIC Educational Resources Information Center

Rebmann, Kristen Radsliff; Molitor, Simone; Rainey, Bonnie

2012-01-01

Archived job advertisements from the "International Federation of Library Associations and Institutions (IFLA) LIBJOBS" mailing list (1996-2010) were examined using content analysis. Findings suggest that distance learning (DL) skillsets as job qualifications emerged in the late 1990's and continue to be relevant today. Jobs with DL…

Corporate Image of Public Higher Education Institutions: Relevant Factors to Distance Learning Students

ERIC Educational Resources Information Center

da Costa, Fabio R.; Pelissari, Anderson S.; Gonzalez, Inayara V. D. P.

2018-01-01

Technological advances are generating a significant increase in the supply of distance learning (DL) courses via the Internet, increasing the importance of this type of education for the university's structure. This article identifies factors associated with perceptions of the public higher education institutions' image from the perspective of DL…

DL-sQUAL: A Multiple-Item Scale for Measuring Service Quality of Online Distance Learning Programs

ERIC Educational Resources Information Center

Shaik, Naj; Lowe, Sue; Pinegar, Kem

2006-01-01

Education is a service with multiplicity of student interactions over time and across multiple touch points. Quality teaching needs to be supplemented by consistent quality supporting services for programs to succeed under the competitive distance learning landscape. ServQual and e-SQ scales have been proposed for measuring quality of traditional…

Design and Development of a Novel Distance Learning Telementoring System Using Off-the-Shelf Materials and Software.

PubMed

Rosser, James C; Fleming, Jeffrey P; Legare, Timothy B; Choi, Katherine M; Nakagiri, Jamie; Griffith, Elliot

2017-12-22

To design and develop a distance learning (DL) system for the transference of laparoscopic surgery knowledge and skill constructed from off-the-shelf materials and commercially available software. Minimally invasive surgery offers significant benefits over traditional surgical procedures, but adoption rates for many procedures are low. Skill and confidence deficits are two of the culprits. DL combined with simulation training and telementoring may address these issues with scale. The system must be built to meet the instruction requirements of a proven laparoscopic skills course (Top Gun). Thus, the rapid sharing of multimedia educational materials, secure two-way audio/visual communications, and annotation and recording capabilities are requirements for success. These requirements are more in line with telementoring missions than standard distance learning efforts. A DL system with telementor, classroom, and laboratory stations was created. The telementor station consists of a desktop computer and headset with microphone. For the classroom station, a laptop is connected to a digital projector that displays the remote instructor and content. A tripod-mounted webcam provides classroom visualization and a Bluetooth® wireless speaker establishes audio. For the laboratory station, a laptop with universal serial bus (USB) expander is combined with a tabletop laparoscopic skills trainer, a headset with microphone, two webcams and a Bluetooth® speaker. The cameras are mounted on a standard tripod and an adjustable gooseneck camera mount clamp to provide an internal and external view of the training area. Internet meeting software provides audio/visual communications including transmission of educational materials. A DL system was created using off-the-shelf materials and commercially available software. It will allow investigations to evaluate the effectiveness of laparoscopic surgery knowledge and skill transfer utilizing DL techniques.

Determinants of the Use of Technological Innovation in Distance Learning: A Study with Business School Instructors

ERIC Educational Resources Information Center

Araujo Leal, Edvalda; Luiz Albertin, Alberto

2015-01-01

This study's overall purpose is to identify the factors determining the use of technological innovation in Distance Learning (DL), as perceived by instructors of Business Education programs. The theoretical basis for the study is the Innovation Diffusion Theory (IDT). The study's sample is made up of 436 instructors; we used a quantitative…

Learning Styles and the Online Classroom: Implications for Business Students

ERIC Educational Resources Information Center

Nastanski, Michael; Slick, Thomas

2008-01-01

This paper discusses the importance of student learning styles within a Distance Learning (DL) classroom. The study examines the learning style preferences of online business students as measured by the Kolb Learning Style Inventory and determines if a significant difference in course grades and course completion rates exist between students when…

Meeting Teacher Expectations in a DL Professional Development Programme--A Case Study for Sustained Applied Competence as Programme Outcome

ERIC Educational Resources Information Center

Kruger, Cornè Gerda; Van Rensburg, Ona Janse; De Witt, Marike W.

2016-01-01

Meeting teacher expectations for a professional development programme (PDP) is expected to strengthen sustainable applied competence as programme outcome since teachers will be more motivated to apply the programme content in practice. A revised distance learning (DL) programme was augmented by a practical component comprising a work-integrated…

GSBPP Faculty Perceptions of Synchronous Distance Learning Technologies

DTIC Science & Technology

2008-12-01

faculty who teach DL programs in the Graduate School of Business & Public Policy (GSBPP) at Naval Postgraduate School (NPS), and then to recommend...Alice Crawford Second Reader Terry Rea, CAPT, USN, Dean, (Acting) Graduate School of Business and Public Policy iv THIS PAGE...DL programs in the Graduate School of Business & Public Policy (GSBPP) at Naval Postgraduate School (NPS), and then to recommend sound solutions in

Exploring Ways of Influencing Transport Behaviors by Using Telecommunications Technologies

DOT National Transportation Integrated Search

2004-06-01

Information technology can facilitate substitution and modification of transportation behaviors. Distance Learning (DL) can replace library work, meetings, and some traditional face-to-face class meetings. For off-campus full-time students, and for p...

Distance Learning Course for Healthcare Professionals: Continuing Education in Tuberculosis.

PubMed

Cabral, Vagner Kunz; Valentini, Dirceu Felipe; Rocha, Marcos Vinícius Vieira; de Almeida, Carlos Podalírio Borges; Cazella, Sílvio Cesar; Silva, Denise Rossato

2017-12-01

Continuing education of healthcare workers (HCWs) is an essential strategy for the control of tuberculosis (TB) transmission, enabling HCWs in early detection and appropriate treatment of TB cases. We developed a distance learning (DL) course on TB for nurses. We conducted a quasi-experimental before and after study to evaluate the DL community at the participant's learning level. In addition, to evaluate the DL community at the level of participant satisfaction, a cross-sectional study was carried out after the course. Nurses involved in active inpatient or outpatient care of patients were recruited to participate in the study. Sixty-six participants started and completed the course and they were included in the analysis. The overall mean pretest and post-test scores were 10.3 ± 2.2 and 11.4 ± 2.7, respectively. Participants increased their knowledge to a statistically significant degree (p < 0.0001). At baseline, the frequency of correct answers was very low in some questions: number of people infected by Mycobacterium tuberculosis in the world (10.6%); number of TB cases in Brazil (36.4%); contagiousness of latent TB infection (LTBI) (28.8%); and definition of active case finding (45.5%). Course feedback was mostly positive, with majority of users saying they were satisfied or totally satisfied. A brief DL course on TB was associated with some improvement in knowledge among nurses. The baseline knowledge was low regarding TB epidemiologic data, concepts on LTBI, and active case finding. This finding emphasizes the need to further improve the competencies and knowledge of nurses.

Communication between Tutors--Students in DL: A Case Study of the Hellenic Open University

ERIC Educational Resources Information Center

Panagiotis, Anastasiades; Chrysoula, Iliadou

2010-01-01

Two-way communication between students and tutors is one of the two key factors contributing to the success of a Distance Learning programme, the other being the complete and well-designed educational package. Both elements are essential to guide students' learning. By means of this communication the tutor can facilitate the interaction of…

Improved Distance Learning Environment For Marine Forces Reserve

DTIC Science & Technology

2016-09-01

keyboard, to 20 form a desktop computer . Laptop computers share similar components but add mobility to the user. If additional desktop computers ...for stationary computing devices such as desktop PCs and laptops include the Microsoft Windows, Mac OS, and Linux families of OSs 44 (Hopkins...opportunities to all Marines. For active duty Marines, government-provided desktops and laptops (GPDLs) typically support DL T&E or learning resource

The virtual revolution: implications for academe.

PubMed

Pardue, S L

2001-05-01

The global expansion and acceptance of the Internet as been unprecedented. The emergence of the potential for distance learning (DL) has altered the way in which faculty, university administrators, and for-profit corporations view the educational process. In 1998, nearly 80% of public 4-yr institutions offered some DL courses. However, DL courses in agriculture and natural resources represented less than 1% of the total enrollment. Like any technology that ushers in a new era of change, DL has attracted enthusiastic supporters and detractors. Few view DL with neutrality. It is this divergence of opinion that has fueled the debate over the academic value of DL. A valid evaluation of the educational benefits or deficiencies of DL may require additional long-term studies. For some academic traditionalists, DL is viewed as the fusion of education and commerce and borders on the repugnant. Others embrace DL not only because it may provide a source of much needed revenue, but also because it allows for the low-cost delivery of information to a nontraditional pool of students. Well-funded, private, for-profit organizations and universities have developed a number of DL models. Some hybrid DL models exist in which public institutions have created independent for-profit corporations to develop and distribute their web-based courses. The question is not if DL will be a part of the educational landscape; it surely will. The challenge is to define the role DL can most effectively fulfill.

Modified cuspal relationships of mandibular molar teeth in children with Down's syndrome

PubMed Central

PERETZ, BENJAMIN; SHAPIRA, JOSEPH; FARBSTEIN, HANNA; ARIELI, ELIAHU; SMITH, PATRICIA

1998-01-01

A total of 50 permanent mandibular 1st molars of 26 children with Down's syndrome (DS) were examined from dental casts and 59 permanent mandibular 1st molars of normal children were examined from 33 individuals. The following measurements were performed on both right and left molars (teeth 46 and 36 respectively): (a) the intercusp distances (mb-db, mb-d, mb-dl, db-ml, db-d, db-dl, db-ml, d-dl, d-ml, dl-ml); (b) the db-mb-ml, mb-db-ml, mb-ml-db, d-mb-dl, mb-d-dl, mb-dl-d angles; (c) the area of the pentagon formed by connecting the cusp tips. All intercusp distances were significantly smaller in the DS group. Stepwise logistic regression, applied to all the intercusp distances, was used to design a multivariate probability model for DS and normals. A model based on 2 distances only, mb-dl and mb-db, proved sufficient to discriminate between the teeth of DS and the normal population. The model for tooth 36 for example was as follows: formula here A similar model for tooth 46 was also created, as well as a model which incorporated both teeth. With respect to the angles, significant differences between DS and normals were found in 3 out of the 6 angles which were measured: the d-mb-dl angle was smaller than in normals, the mb-d-dl angle was higher, and the mb-dl-d angle was smaller. The dl cusp was located closer to the centre of the tooth. The change in size occurs at an early stage, while the change in shape occurs in a later stage of tooth formation in the DS population. PMID:10029186

Evaluating Students' Perspectives about Virtual Classrooms with Regard to Seven Principles of Good Practice

ERIC Educational Resources Information Center

Çakýroðlu, Ünal

2014-01-01

This study assesses the quality of distance learning (DL) in higher education assessed by considering the Seven Principles of Good Practice (SPGP). The participants were 77 second-year students from the Computer and Instructional Technologies Program (CEIT) of a Faculty of Education in Turkey. A questionnaire was developed in line with the SPGP…

Four Families of Multi-Variant Issues in Graduate-Level Asynchronous Online Courses

ERIC Educational Resources Information Center

Gisburne, Jaclyn M.; Fairchild, Patricia J.

2004-01-01

This is the first of several papers developed from a faculty and student perspective describing a new distance learning (DL) model. Integral to the model are four interrelated families of multi-variant issues, referred to here as (a) the academic divide, (b) student misalignment, (c) administrative influences, and (d) the use of student…

Post-task Effects on EEG Brain Activity Differ for Various Differential Learning and Contextual Interference Protocols

PubMed Central

Henz, Diana; John, Alexander; Merz, Christian; Schöllhorn, Wolfgang I.

2018-01-01

A large body of research has shown superior learning rates in variable practice compared to repetitive practice. More specifically, this has been demonstrated in the contextual interference (CI) and in the differential learning (DL) approach that are both representatives of variable practice. Behavioral studies have indicate different learning processes in CI and DL. Aim of the present study was to examine immediate post-task effects on electroencephalographic (EEG) brain activation patterns after CI and DL protocols that reveal underlying neural processes at the early stage of motor consolidation. Additionally, we tested two DL protocols (gradual DL, chaotic DL) to examine the effect of different degrees of stochastic fluctuations within the DL approach with a low degree of fluctuations in gradual DL and a high degree of fluctuations in chaotic DL. Twenty-two subjects performed badminton serves according to three variable practice protocols (CI, gradual DL, chaotic DL), and a repetitive learning protocol in a within-subjects design. Spontaneous EEG activity was measured before, and immediately after each 20-min practice session from 19 electrodes. Results showed distinguishable neural processes after CI, DL, and repetitive learning. Increases in EEG theta and alpha power were obtained in somatosensory regions (electrodes P3, P7, Pz, P4, P8) in both DL conditions compared to CI, and repetitive learning. Increases in theta and alpha activity in motor areas (electrodes C3, Cz, C4) were found after chaotic DL compared to gradual DL, and CI. Anterior areas (electrodes F3, F7, Fz, F4, F8) showed increased activity in the beta and gamma bands after CI. Alpha activity was increased in occipital areas (electrodes O1, O2) after repetitive learning. Post-task EEG brain activation patterns suggest that DL stimulates the somatosensory and motor system, and engages more regions of the cortex than repetitive learning due to a tighter stimulation of the motor and somatosensory system during DL practice. CI seems to activate specifically executively controlled processing in anterior brain areas. We discuss the obtained patterns of post-training EEG traces as evidence for different underlying neural processes in CI, DL, and repetitive learning at the early stage of motor learning. PMID:29445334

Dissemination and Implementation of Cognitive Behavioral Therapy for Stimulant Dependence: A Randomized Trial Comparison of Three Approaches

PubMed Central

Rawson, Richard A.; Rataemane, Solomon; Rataemane, Lusanda; Ntlhe, Nomvuyo; Fox, Ruthlyn Sodano; McCuller, Jason; Brecht, Mary-Lynn

2012-01-01

This study evaluated the effectiveness of 3 approaches to transferring cognitive behavioral therapy (CBT) to addiction clinicians in the Republic of South Africa (RSA). Clinicians (N = 143) were assigned to 3 training conditions: (1) An in vivo (IV) approach in which clinicians received in-person training and coaching; (2) A distance learning (DL) approach providing training via video conference and coaching through teleconferencing; and (3) A control condition (C) providing a manual and 2-hour orientation. Frequency of use of CBT skills increased significantly with the IV and DL approaches compared to the C approach, and the IV approach facilitated greater use of CBT skills than the DL approach. During the active phase of the study, skill quality declined significantly for clinicians trained in the C condition, whereas those in the DL approach maintained skill quality and those in the IV approach improved skill quality. After coaching was discontinued, clinicians in the IV and DL approaches declined in skill quality. However, those in the IV approach maintained a higher level of skill quality compared to the other approaches. Cost of the IV condition was double that of the DL condition and 10 times greater than the C condition. PMID:23577903

Regularized spherical polar fourier diffusion MRI with optimal dictionary learning.

PubMed

Cheng, Jian; Jiang, Tianzi; Deriche, Rachid; Shen, Dinggang; Yap, Pew-Thian

2013-01-01

Compressed Sensing (CS) takes advantage of signal sparsity or compressibility and allows superb signal reconstruction from relatively few measurements. Based on CS theory, a suitable dictionary for sparse representation of the signal is required. In diffusion MRI (dMRI), CS methods proposed for reconstruction of diffusion-weighted signal and the Ensemble Average Propagator (EAP) utilize two kinds of Dictionary Learning (DL) methods: 1) Discrete Representation DL (DR-DL), and 2) Continuous Representation DL (CR-DL). DR-DL is susceptible to numerical inaccuracy owing to interpolation and regridding errors in a discretized q-space. In this paper, we propose a novel CR-DL approach, called Dictionary Learning - Spherical Polar Fourier Imaging (DL-SPFI) for effective compressed-sensing reconstruction of the q-space diffusion-weighted signal and the EAP. In DL-SPFI, a dictionary that sparsifies the signal is learned from the space of continuous Gaussian diffusion signals. The learned dictionary is then adaptively applied to different voxels using a weighted LASSO framework for robust signal reconstruction. Compared with the start-of-the-art CR-DL and DR-DL methods proposed by Merlet et al. and Bilgic et al., respectively, our work offers the following advantages. First, the learned dictionary is proved to be optimal for Gaussian diffusion signals. Second, to our knowledge, this is the first work to learn a voxel-adaptive dictionary. The importance of the adaptive dictionary in EAP reconstruction will be demonstrated theoretically and empirically. Third, optimization in DL-SPFI is only performed in a small subspace resided by the SPF coefficients, as opposed to the q-space approach utilized by Merlet et al. We experimentally evaluated DL-SPFI with respect to L1-norm regularized SPFI (L1-SPFI), which uses the original SPF basis, and the DR-DL method proposed by Bilgic et al. The experiment results on synthetic and real data indicate that the learned dictionary produces sparser coefficients than the original SPF basis and results in significantly lower reconstruction error than Bilgic et al.'s method.

Differential Training Facilitates Early Consolidation in Motor Learning

PubMed Central

Henz, Diana; Schöllhorn, Wolfgang I.

2016-01-01

Current research demonstrates increased learning rates in differential learning (DL) compared to repetitive training. To date, little is known on the underlying neurophysiological processes in DL that contribute to superior performance over repetitive practice. In the present study, we measured electroencephalographic (EEG) brain activation patterns after DL and repetitive badminton serve training. Twenty-four semi-professional badminton players performed badminton serves in a DL and repetitive training schedule in a within-subjects design. EEG activity was recorded from 19 electrodes according to the 10–20 system before and immediately after each 20-min exercise. Increased theta activity was obtained in contralateral parieto-occipital regions after DL. Further, increased posterior alpha activity was obtained in DL compared to repetitive training. Results indicate different underlying neuronal processes in DL and repetitive training with a higher involvement of parieto-occipital areas in DL. We argue that DL facilitates early consolidation in motor learning indicated by post-training increases in theta and alpha activity. Further, brain activation patterns indicate somatosensory working memory processes where attentional resources are allocated in processing of somatosensory information in DL. Reinforcing a somatosensory memory trace might explain increased motor learning rates in DL. Finally, this memory trace is more stable against interference from internal and external disturbances that afford executively controlled processing such as attentional processes. PMID:27818627

An analysis of student performance benchmarks in dental hygiene via distance education.

PubMed

Olmsted, Jodi L

2010-01-01

Three graduate programs, 35 undergraduate programs and 12 dental hygiene degree completion programs in the United States use varying forms of Distance Learning (DL). Relying heavily on DL leaves an unanswered question: Is learner performance on standard benchmark assessments impacted when using technology as a delivery system? A 10 year, longitudinal examination looked for student performance differences in a Distance Education (DE) dental hygiene program. The purpose of this research was to determine if there was a difference in performance between learners taught in a traditional classroom as compared to their counterparts taking classes through an alternative delivery system. A longitudinal, ex post facto design was used. Two hundred and sixty-six subject records were examined. Seventy-seven individuals (29%) were lost through attrition over 10 years. One hundred and eighty-nine records were used as the study sample, 117 individuals were located face-to-face and 72 were at a distance. Independent variables included time and location, while the dependent variables included course grades, grade point average (GPA) and the National Board of Dental Hygiene Examination (NBDHE). Three research questions were asked: Were there statistically significant differences in learner performance on the National Board of Dental Hygiene Examination (NBDHE)? Were there statistically significant differences in learner performance when considering GPAs? Did statistically significant differences in performance exist relating to individual course grades? T-tests were used for data analysis in answering the research questions. From a cumulative perspective, no statistically significant differences were apparent for the NBDHE and GPAs or for individual courses. Interactive Television (ITV), the synchronous DL system examined, was considered effective for delivering education to learners if similar performance outcomes were the evaluation criteria.

Discover the pythagorean theorem using interactive multimedia learning

NASA Astrophysics Data System (ADS)

Adhitama, I.; Sujadi, I.; Pramudya, I.

2018-04-01

In learning process students are required to play an active role in learning. They do not just accept the concept directly from teachers, but also build their own knowledge so that the learning process becomes more meaningful. Based on the observation, when learning Pythagorean theorem, students got difficulty on determining hypotenuse. One of the solution to solve this problem is using an interactive multimedia learning. This article aims to discuss the interactive multimedia as learning media for students. This was a Research and Development (R&D) by using ADDIE model of development. The results obtained was multimedia which was developed proper for students as learning media. Besides, on Phytagorian theorem learning activity we also compare Discovery Learning (DL) model with interactive multimedia and DL without interactive multimedia, and obtained that DL with interactive gave positive effect better than DL without interactive multimedia. It was also obtainde that interactive multimedia can attract and increase the interest ot the students on learning math. Therefore, the use of interactive multimedia on DL procees can improve student learning achievement.

Criterion validity and accuracy of global positioning satellite and data logging devices for wheelchair tennis court movement

PubMed Central

Sindall, Paul; Lenton, John P.; Whytock, Katie; Tolfrey, Keith; Oyster, Michelle L.; Cooper, Rory A.; Goosey-Tolfrey, Victoria L.

2013-01-01

Purpose To compare the criterion validity and accuracy of a 1 Hz non-differential global positioning system (GPS) and data logger device (DL) for the measurement of wheelchair tennis court movement variables. Methods Initial validation of the DL device was performed. GPS and DL were fitted to the wheelchair and used to record distance (m) and speed (m/second) during (a) tennis field (b) linear track, and (c) match-play test scenarios. Fifteen participants were monitored at the Wheelchair British Tennis Open. Results Data logging validation showed underestimations for distance in right (DLR) and left (DLL) logging devices at speeds >2.5 m/second. In tennis-field tests, GPS underestimated distance in five drills. DLL was lower than both (a) criterion and (b) DLR in drills moving forward. Reversing drill direction showed that DLR was lower than (a) criterion and (b) DLL. GPS values for distance and average speed for match play were significantly lower than equivalent values obtained by DL (distance: 2816 (844) vs. 3952 (1109) m, P = 0.0001; average speed: 0.7 (0.2) vs. 1.0 (0.2) m/second, P = 0.0001). Higher peak speeds were observed in DL (3.4 (0.4) vs. 3.1 (0.5) m/second, P = 0.004) during tennis match play. Conclusions Sampling frequencies of 1 Hz are too low to accurately measure distance and speed during wheelchair tennis. GPS units with a higher sampling rate should be advocated in further studies. Modifications to existing DL devices may be required to increase measurement precision. Further research into the validity of movement devices during match play will further inform the demands and movement patterns associated with wheelchair tennis. PMID:23820154

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

PubMed

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.

Marginal shape deep learning: applications to pediatric lung field segmentation

NASA Astrophysics Data System (ADS)

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

2017-02-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, local- ization, 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 ASM1 (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.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation

PubMed Central

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

2017-01-01

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 ASM1 (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. PMID:28592911

Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

NASA Astrophysics Data System (ADS)

Ball, John E.; Anderson, Derek T.; Chan, Chee Seng

2017-10-01

In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, and natural language processing. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV, e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should not only be aware of advancements such as DL, but also be leading researchers in this area. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools, and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as they relate to (i) inadequate data sets, (ii) human-understandable solutions for modeling physical phenomena, (iii) big data, (iv) nontraditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial, and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.

What does fault tolerant Deep Learning need from MPI?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amatya, Vinay C.; Vishnu, Abhinav; Siegel, Charles M.

Deep Learning (DL) algorithms have become the {\\em de facto} Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive -- even distributed DL implementations which use MPI require days of training (model learning) time on commonly studied datasets. Long running DL applications become susceptible to faults -- requiring development of a fault tolerant system infrastructure, in addition to fault tolerant DL algorithms. This raises an important question: {\\em What is needed from MPI for designing fault tolerant DL implementations?} In this paper, we address this problem for permanent faults. We motivate the need for amore » fault tolerant MPI specification by an in-depth consideration of recent innovations in DL algorithms and their properties, which drive the need for specific fault tolerance features. We present an in-depth discussion on the suitability of different parallelism types (model, data and hybrid); a need (or lack thereof) for check-pointing of any critical data structures; and most importantly, consideration for several fault tolerance proposals (user-level fault mitigation (ULFM), Reinit) in MPI and their applicability to fault tolerant DL implementations. We leverage a distributed memory implementation of Caffe, currently available under the Machine Learning Toolkit for Extreme Scale (MaTEx). We implement our approaches by extending MaTEx-Caffe for using ULFM-based implementation. Our evaluation using the ImageNet dataset and AlexNet neural network topology demonstrates the effectiveness of the proposed fault tolerant DL implementation using OpenMPI based ULFM.« less

Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications.

PubMed

Vieira, Sandra; Pinaya, Walter H L; Mechelli, Andrea

2017-03-01

Deep learning (DL) is a family of machine learning methods that has gained considerable attention in the scientific community, breaking benchmark records in areas such as speech and visual recognition. DL differs from conventional machine learning methods by virtue of its ability to learn the optimal representation from the raw data through consecutive nonlinear transformations, achieving increasingly higher levels of abstraction and complexity. Given its ability to detect abstract and complex patterns, DL has been applied in neuroimaging studies of psychiatric and neurological disorders, which are characterised by subtle and diffuse alterations. Here we introduce the underlying concepts of DL and review studies that have used this approach to classify brain-based disorders. The results of these studies indicate that DL could be a powerful tool in the current search for biomarkers of psychiatric and neurologic disease. We conclude our review by discussing the main promises and challenges of using DL to elucidate brain-based disorders, as well as possible directions for future research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Oral and transdermal DL-methylphenidate-ethanol interactions in C57BL/6J mice: potentiation of locomotor activity with oral delivery.

PubMed

Bell, Guinevere H; Griffin, William C; Patrick, Kennerly S

2011-12-01

Many abusers of dl-methylphenidate co-abuse ethanol. The present animal study examined behavioral effects of oral or transdermal DL-methylphenidate in combination with a high, depressive dose of ethanol to model co-abuse. Locomotor activity of C57BL/6J mice was recorded for 3 h following dosing with either oral DL-methylphenidate (7.5 mg/kg) or transdermal DL-methylphenidate (Daytrana®;1/4 of a 12.5 cm(2) patch; mean dose 7.5 mg/kg), with or without oral ethanol (3 g/kg). Brains were enantiospecifically analyzed for the isomers of methylphenidate and the transesterification metabolite ethylphenidate. An otherwise depressive dose of ethanol significantly potentiated oral DL-methylphenidate induced increases in total distance traveled for the first 100 min (p<0.05). Transdermal DL-methylphenidate increased total distance traveled after a latency of 80 min, though this effect was not potentiated by concomitant ethanol. Mean 3 h brain D-methylphenidate concentrations were significantly elevated by ethanol in both the oral (65% increase) and transdermal (88% increase) groups. The corresponding L-ethylphenidate concentrations were 10 ng/g and 130 ng/g. Stimulant induced motor activity in rodents may correlate with abuse liability. Potentiation of DL-methylphenidate motor effects by concomitant ethanol carries implications regarding increased abuse potential of DL-methylphenidate when combined with ethanol. Copyright © 2011 Elsevier Inc. All rights reserved.

A laboratory study for assessing speech privacy in a simulated open-plan office.

PubMed

Lee, P J; Jeon, J Y

2014-06-01

The aim of this study is to assess speech privacy in open-plan office using two recently introduced single-number quantities: the spatial decay rate of speech, DL(2,S) [dB], and the A-weighted sound pressure level of speech at a distance of 4 m, L(p,A,S,4) m [dB]. Open-plan offices were modeled using a DL(2,S) of 4, 8, and 12 dB, and L(p,A,S,4) m was changed in three steps, from 43 to 57 dB.Auditory experiments were conducted at three locations with source–receiver distances of 8, 16, and 24 m, while background noise level was fixed at 30 dBA.A total of 20 subjects were asked to rate the speech intelligibility and listening difficulty of 240 Korean sentences in such surroundings. The speech intelligibility scores were not affected by DL(2,S) or L(p,A,S,4) m at a source–receiver distance of 8 m; however, listening difficulty ratings were significantly changed with increasing DL(2,S) and L(p,A,S,4) m values. At other locations, the influences of DL(2,S) and L(p,A,S,4) m on speech intelligibility and listening difficulty ratings were significant. It was also found that the speech intelligibility scores and listening difficulty ratings were considerably changed with increasing the distraction distance (r(D)). Furthermore, listening difficulty is more sensitive to variations in DL(2,S) and L(p,A,S,4) m than intelligibility scores for sound fields with high speech transmission performances. The recently introduced single-number quantities in the ISO standard, based on the spatial distribution of sound pressure level, were associated with speech privacy in an open-plan office. The results support single-number quantities being suitable to assess speech privacy, mainly at large distances. This new information can be considered when designing open-plan offices and making acoustic guidelines of open-plan offices.

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

PubMed

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

Deep learning based classification of breast tumors with shear-wave elastography.

PubMed

Zhang, Qi; Xiao, Yang; Dai, Wei; Suo, Jingfeng; Wang, Congzhi; Shi, Jun; Zheng, Hairong

2016-12-01

This study aims to build a deep learning (DL) architecture for automated extraction of learned-from-data image features from the shear-wave elastography (SWE), and to evaluate the DL architecture in differentiation between benign and malignant breast tumors. We construct a two-layer DL architecture for SWE feature extraction, comprised of the point-wise gated Boltzmann machine (PGBM) and the restricted Boltzmann machine (RBM). The PGBM contains task-relevant and task-irrelevant hidden units, and the task-relevant units are connected to the RBM. Experimental evaluation was performed with five-fold cross validation on a set of 227 SWE images, 135 of benign tumors and 92 of malignant tumors, from 121 patients. The features learned with our DL architecture were compared with the statistical features quantifying image intensity and texture. Results showed that the DL features achieved better classification performance with an accuracy of 93.4%, a sensitivity of 88.6%, a specificity of 97.1%, and an area under the receiver operating characteristic curve of 0.947. The DL-based method integrates feature learning with feature selection on SWE. It may be potentially used in clinical computer-aided diagnosis of breast cancer. Copyright © 2016 Elsevier B.V. All rights reserved.

Study of the Asteroid 2009 DL46

NASA Astrophysics Data System (ADS)

Vodniza, Alberto Quijano

2017-06-01

2009 DL46 was discovered by the Catalina Sky Survey on 2009-February 28. This asteroid has a diameter of about 194 meters (119 to 268 meters) [1], and Brian Warner has obtained a rotation period of at least 10 hours [2]. The asteroid 2009 DL46 flew past Earth on May 24/2016 at a distance of about 6.2 lunar distances (0.0158293668567628 A.U) [3]. The NEOWISE mission had a great likelihood to observing this asteroid in early May. Radiotelescopes of Goldstone and Arecibo had planned to make observations of 2009 DL46. “Using the Goldstone facility, we had planned to make radar observations of 2009 DL46” said Landis, Rob R. (HQ-DG000). This asteroid is on list for possible human mission targets. From our Observatory, located in Pasto-Colombia, we captured several pictures, videos and astrometry data during several hours during three days. Our data was published by the Minor Planet Center (MPC) and also appears at the web page of NEODyS [4]. The pictures and data of the asteroid were captured with the following equipment: CGE PRO 1400 CELESTRON (f/11 Schmidt-Cassegrain Telescope) and STL-1001 SBIG camera.. Astrometry was carried out, and we calculated the orbital elements. Summary and conclusions: We obtained the following orbital parameters: eccentricity = 0.30731 +/- 0.00025, semi-major axis = 1.460279 +/- 0.000532 A.U, orbital inclination = 7.9503 +/- 0.0048 deg, longitude of the ascending node = 63.45053 +/- 0.00034 deg, argument of perihelion = 159.8804 +/- 0.0024 deg, mean motion = 0.558535 +/- 0.000305 deg/d, perihelion distance = 1.01151363 +/- 3.39e-6 A.U, aphelion distance = 1.90904 +/- 0.00106 A.U, absolute magnitude = 22.5. The parameters were calculated based on 83 observations. Dates: 2016 May: 18 to 21 with mean residual = 0.29 arcseconds. The asteroid has an orbital period of 1.76 years (644.53 days).[1] http://newton.dm.unipi.it/neodys/index.php?pc=1.1.9&n=2009DL46.[2] http://echo.jpl.nasa.gov/asteroids/2009DL46/2009DL46_planning.html[3] http://ssd.jpl.nasa.gov/sbdb.cgi?sstr=2009%20DL46orb=1old=0cov=0log=0cad=1#cad[4] http://newton.dm.unipi.it/neodys/index.php?pc=2.1.2&o=H78&ab=7

Comparing the NPS MBA Resident and Distance Programs

DTIC Science & Technology

2017-06-01

17 D. ARTICLES ON HYBRID DELIVERY OF EDUCATION .................21 E. BENEFITS AND COSTS OF DL...isolation, potentially reducing the student stress reported by Ni (2013) that can occur in DL programs. E. BENEFITS AND COSTS OF DL Both tangible...PROGRAMS June 2017 By: Mara F. Rosenthal Advisors: Marigee Bacolod Latika Hartmann Approved for public release. Distribution

Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era.

PubMed

Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean

2018-03-30

Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.

Utilization of exploration-based learning and video-assisted learning to teach GlideScope videolaryngoscopy.

PubMed

Johnston, Lindsay C; Auerbach, Marc; Kappus, Liana; Emerson, Beth; Zigmont, Jason; Sudikoff, Stephanie N

2014-01-01

GlideScope (GS) is used in pediatric endotracheal intubation (ETI) but requires a different technique compared to direct laryngoscopy (DL). This article was written to evaluate the efficacy of exploration-based learning on procedural performance using GS for ETI of simulated pediatric airways and establish baseline success rates and procedural duration using DL in airway trainers among pediatric providers at various levels. Fifty-five pediatric residents, fellows, and faculty from Pediatric Critical Care, NICU, and Pediatric Emergency Medicine were enrolled. Nine physicians from Pediatric Anesthesia benchmarked expert performance. Participants completed a demographic survey and viewed a video by the GS manufacturer. Subjects spent 15 minutes exploring GS equipment and practicing the intubation procedure. Participants then intubated neonatal, infant, child, and adult airway simulators, using GS and DL, in random order. Time to ETI was recorded. Procedural performance after exploration-based learning, measured as time to successful ETI, was shorter for DL than for GS for neonatal and child airways at the.05 significance level. Time to ETI in adult airway using DL was correlated with experience level (p =.01). Failure rates were not different among subgroups. A brief video and period of exploration-based learning is insufficient for implementing a new technology. Pediatricians at various levels of training intubated simulated airways faster using DL than GS.

Teaching High School Chemistry in the Context of Pharmacology Helps Both Teachers and Students Learn

PubMed Central

Schwartz-Bloom, Rochelle D.; Halpin, Myra J.; Reiter, Jerome P.

2014-01-01

Few studies demonstrate the impact of teaching chemistry embedded in a context that has relevance to high school students. We build upon our prior work showing that pharmacology topics (i.e., drugs), which are inherently interesting to high school students, provide a useful context for teaching chemistry and biology. In those studies, teachers were provided professional development for the Pharmacology Education Partnership (PEP) in an onsite venue (either five-day or one-day workshop). Given financial difficulties to travel, teachers have asked for alternatives for professional development. Thus, we developed the same PEP training workshop using a distance learning (DL) (two-way live video) approach. In this way, 121 chemistry and biology teachers participated in the DL workshops to learn how to incorporate the PEP modules into their teaching. They field-tested the modules over the year in high school chemistry and biology classes. Teacher knowledge of chemistry and biology increased significantly after the workshop and was maintained for at least a year. Their students (N = 2309) demonstrated a significant increase in knowledge of chemistry and biology concepts, with higher scores as the number of modules used increased. The increase in both teacher and student knowledge in these subjects was similar to that found previously when teachers were provided with onsite professional development. PMID:24882881

Brain tumor image segmentation using kernel dictionary learning.

PubMed

Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

2015-08-01

Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

Teaching basic medical sciences at a distance: strategies for effective teaching and learning in internet-based courses.

PubMed

Ertmer, Peggy A; Nour, Abdelfattah Y M

2007-01-01

In recent years, the Internet has become an effective and accessible delivery mechanism for distance education. In 2003, 81% of all institutions of higher education offered at least one fully online or hybrid course. By 2005, the proportion of institutions that listed online education as important to their long-term goals had increased by 8%. This growth in available online courses and their increased convenience and flexibility have stimulated dramatic increases in enrollment in online programs, including the Veterinary Technology Distance Learning Program (VT-DLP) at Purdue University. Regardless of the obvious benefits, distance learning (DL) can be frustrating for the learners if course developers are unable to merge their knowledge about the learners, the process of instructional design, and the appropriate uses of technology and interactivity options into effective course designs. This article describes strategies that we have used to increase students' learning of physiology content in an online environment. While some of these are similar, if not identical, to strategies that might be used in a face-to-face (f2f) environment (e.g., case studies, videos, concept maps), additional strategies (e.g., animations, virtual microscopy) are needed to replace or supplement what might normally occur in a f2f course. We describe how we have addressed students' need for instructional interaction, specifically in the context of two foundational physiology courses that occur early in the VT-DLP. Although the teaching and learning strategies we have used have led to increasingly high levels of interaction, there is an ongoing need to evaluate these strategies to determine their impact on students' learning of physiology content, their development of problem-solving skills, and their retention of information.

New Tools and Metrics for Evaluating Army Distributed Learning. Monograph

ERIC Educational Resources Information Center

Straus, Susan G.; Shanley, Michael G.; Yeung, Douglas; Rothenberg, Jeff; Steiner, Elizabeth D.; Leuschner, Kristin J.

2011-01-01

Distributed learning (DL) is a key element of the Army's training strategy, and the Army has ambitious goals for expanding the future use of DL and for changing how it is developed and delivered. Program-level evaluation of DL can play an essential role in accomplishing those goals and in identifying strategic directions for the overall program.…

On the optimal degree of fluctuations in practice for motor learning.

PubMed

Hossner, Ernst-Joachim; Käch, Boris; Enz, Jonas

2016-06-01

In human movement science, it is widely accepted that random practice generally enhances complex motor-skill learning compared to repetitive practice. In two experiments, a particular variability-related concept is put to empirical test, namely the concept of differencial learning (DL), which assumes (i) that learners should not be distracted from task-space exploration by corrections, and (ii) that learning is facilitated by large inter-trial fluctuations. In both experiments, the advantage of DL over repetitive learning was not statistically significant. Moreover, learning was more pronounced when participants either received corrections in addition to DL (Exp. 1) or practiced in an order in which differences between consecutive trials were relatively small (Exp. 2). These findings suggest that the positive DL effects reported in literature cannot be attributed to the reduction of feedback or to the increase of inter-trial fluctuations. These results are discussed in the light of the structural-learning approach and the two-state model of motor learning in which structure-related learning effects are distinguished from the capability to adapt to current changes. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Distributed Learning Enhances Relational Memory Consolidation

ERIC Educational Resources Information Center

Litman, Leib; Davachi, Lila

2008-01-01

It has long been known that distributed learning (DL) provides a mnemonic advantage over massed learning (ML). However, the underlying mechanisms that drive this robust mnemonic effect remain largely unknown. In two experiments, we show that DL across a 24 hr interval does not enhance immediate memory performance but instead slows the rate of…

Bladder cancer treatment response assessment using deep learning in CT with transfer learning

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Samala, Ravi K.; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

2017-03-01

We are developing a CAD system for bladder cancer treatment response assessment in CT. We compared the performance of the deep-learning convolution neural network (DL-CNN) using different network sizes, and with and without transfer learning using natural scene images or regions of interest (ROIs) inside and outside the bladder. The DL-CNN was trained to identify responders (T0 disease) and non-responders to chemotherapy. ROIs were extracted from segmented lesions in pre- and post-treatment scans of a patient and paired to generate hybrid pre-post-treatment paired ROIs. The 87 lesions from 82 patients generated 104 temporal lesion pairs and 6,700 pre-post-treatment paired ROIs. Two-fold cross-validation and receiver operating characteristic analysis were performed and the area under the curve (AUC) was calculated for the DL-CNN estimates. The AUCs for prediction of T0 disease after treatment were 0.77+/-0.08 and 0.75+/-0.08, respectively, for the two partitions using DL-CNN without transfer learning and a small network, and were 0.74+/-0.07 and 0.74+/-0.08 with a large network. The AUCs were 0.73+/-0.08 and 0.62+/-0.08 with transfer learning using a small network pre-trained with bladder ROIs. The AUC values were 0.77+/-0.08 and 0.73+/-0.07 using the large network pre-trained with the same bladder ROIs. With transfer learning using the large network pretrained with the Canadian Institute for Advanced Research (CIFAR-10) data set, the AUCs were 0.72+/-0.06 and 0.64+/-0.09, respectively, for the two partitions. None of the differences in the methods reached statistical significance. Our study demonstrated the feasibility of using DL-CNN for the estimation of treatment response in CT. Transfer learning did not improve the treatment response estimation. The DL-CNN performed better when transfer learning with bladder images was used instead of natural scene images.

Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.

PubMed

Biswas, Mainak; Kuppili, Venkatanareshbabu; Araki, Tadashi; Edla, Damodar Reddy; Godia, Elisa Cuadrado; Saba, Luca; Suri, Harman S; Omerzu, Tomaž; Laird, John R; Khanna, Narendra N; Nicolaides, Andrew; Suri, Jasjit S

2018-07-01

The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of deep-learning (DL) and machine-learning (ML) paradigms. A two-stage DL-based system (a class of AtheroEdge™ systems) was proposed for cIMT measurements. Stage I consisted of a convolution layer-based encoder for feature extraction and a fully convolutional network-based decoder for image segmentation. This stage generated the raw inner lumen borders and raw outer interadventitial borders. To smooth these borders, the DL system used a cascaded stage II that consisted of ML-based regression. The final outputs were the far wall lumen-intima (LI) and media-adventitia (MA) borders which were used for cIMT measurements. There were two sets of gold standards during the DL design, therefore two sets of DL systems (DL1 and DL2) were derived. A total of 396 B-mode ultrasound images of the right and left common carotid artery were used from 203 patients (Institutional Review Board approved, Toho University, Japan). For the test set, the cIMT error for the DL1 and DL2 systems with respect to the gold standard was 0.126 ± 0.134 and 0.124 ± 0.100 mm, respectively. The corresponding LI error for the DL1 and DL2 systems was 0.077 ± 0.057 and 0.077 ± 0.049 mm, respectively, while the corresponding MA error for DL1 and DL2 was 0.113 ± 0.105 and 0.109 ± 0.088 mm, respectively. The results showed up to 20% improvement in cIMT readings for the DL system compared to the sonographer's readings. Four statistical tests were conducted to evaluate reliability, stability, and statistical significance. The results showed that the performance of the DL-based approach was superior to the nonintelligence-based conventional methods that use spatial intensities alone. The DL system can be used for stroke risk assessment during routine or clinical trial modes. Copyright © 2018 Elsevier Ltd. All rights reserved.

United States Navy DL Perspective

DTIC Science & Technology

2010-08-10

United States Navy DL Perspective CAPT Hank Reeves Navy eLearning Project Director 10 August 2010 Report Documentation Page Form ApprovedOMB No...Marine Corps (USMC) Navy eLearning Ongoing Shared with USMC, Coast Guard 9 NeL Help Site https://ile-help.nko.navy.mil/ile/ https://s-ile

Use of the Dichotic Listening Technique with Learning Disabilities

ERIC Educational Resources Information Center

Obrzut, John E.; Mahoney, Emery B.

2011-01-01

Dichotic listening (DL) techniques have been used extensively as a non-invasive procedure to assess language lateralization among children with and without learning disabilities (LD), and with individuals who have other auditory system related brain disorders. Results of studies using DL have indicated that language is lateralized in children with…

Analysis of the vp2 gene sequence of a new mutated mink enteritis parvovirus strain in PR China

PubMed Central

2010-01-01

Background Mink enteritis virus (MEV) causes a highly contagious viral disease of mink with a worldwide distribution. MEV has a linear, single-stranded, negative-sense DNA with a genome length of approximately 5,000 bp. The VP2 protein is the major structural protein of the parvovirus encoded by the vp2 gene. VP2 is highly antigenic and plays important roles in determining viral host ranges and tissue tropisms. This study describes the bionomics and vp2 gene analysis of a mutated strain, MEV-DL, which was isolated recently in China and outlines its homologous relationships with other selected strains registered in Genbank. Results The MEV-DL strain can infect F81 cells with cytopathic effects. Pig erythrocytes were agglutinated by the MEV-DL strain. The generation of MEV-DL in F81 cells could infect mink within three months and cause a disease that was similar to that caused by wild-type MEV. A comparative analysis of the vp2 gene nucleotide (nt) sequence of MEV-DL showed that this was more than 99% homologous with other mink enteritis parvoviruses in Genbank. However, the nucleotide residues at positions 1,065 and 1,238 in the MEV-DL strain of the vp2 gene differed from those of all the other MEV strains described previously. It is noteworthy that the mutation at the nucleotide residues position 1,238 led to Asp/Gly replacement. This may lead to structural changes. A phylogenetic tree and sequence distance table were obtained, which showed that the MEV-DL and ZYL-1 strains had the closest inheritance distance. Conclusions A new variation of the vp2 gene exists in the MEV-DL strain, which may lead to structural changes of the VP2 protein. Phylogenetic analysis showed that MEV-DL may originate from the ZYL-1 strain in DaLian. PMID:20540765

Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

PubMed Central

Cha, Kenny H.; Hadjiiski, Lubomir; Samala, Ravi K.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.

2016-01-01

Purpose: The authors are developing a computerized system for bladder segmentation in CT urography (CTU) as a critical component for computer-aided detection of bladder cancer. Methods: A deep-learning convolutional neural network (DL-CNN) was trained to distinguish between the inside and the outside of the bladder using 160 000 regions of interest (ROI) from CTU images. The trained DL-CNN was used to estimate the likelihood of an ROI being inside the bladder for ROIs centered at each voxel in a CTU case, resulting in a likelihood map. Thresholding and hole-filling were applied to the map to generate the initial contour for the bladder, which was then refined by 3D and 2D level sets. The segmentation performance was evaluated using 173 cases: 81 cases in the training set (42 lesions, 21 wall thickenings, and 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, and 13 normal bladders). The computerized segmentation accuracy using the DL likelihood map was compared to that using a likelihood map generated by Haar features and a random forest classifier, and that using our previous conjoint level set analysis and segmentation system (CLASS) without using a likelihood map. All methods were evaluated relative to the 3D hand-segmented reference contours. Results: With DL-CNN-based likelihood map and level sets, the average volume intersection ratio, average percent volume error, average absolute volume error, average minimum distance, and the Jaccard index for the test set were 81.9% ± 12.1%, 10.2% ± 16.2%, 14.0% ± 13.0%, 3.6 ± 2.0 mm, and 76.2% ± 11.8%, respectively. With the Haar-feature-based likelihood map and level sets, the corresponding values were 74.3% ± 12.7%, 13.0% ± 22.3%, 20.5% ± 15.7%, 5.7 ± 2.6 mm, and 66.7% ± 12.6%, respectively. With our previous CLASS with local contour refinement (LCR) method, the corresponding values were 78.0% ± 14.7%, 16.5% ± 16.8%, 18.2% ± 15.0%, 3.8 ± 2.3 mm, and 73.9% ± 13.5%, respectively. Conclusions: The authors demonstrated that the DL-CNN can overcome the strong boundary between two regions that have large difference in gray levels and provides a seamless mask to guide level set segmentation, which has been a problem for many gradient-based segmentation methods. Compared to our previous CLASS with LCR method, which required two user inputs to initialize the segmentation, DL-CNN with level sets achieved better segmentation performance while using a single user input. Compared to the Haar-feature-based likelihood map, the DL-CNN-based likelihood map could guide the level sets to achieve better segmentation. The results demonstrate the feasibility of our new approach of using DL-CNN in combination with level sets for segmentation of the bladder. PMID:27036584

Deep Learning in Radiology.

PubMed

McBee, Morgan P; Awan, Omer A; Colucci, Andrew T; Ghobadi, Comeron W; Kadom, Nadja; Kansagra, Akash P; Tridandapani, Srini; Auffermann, William F

2018-03-29

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Measurement of anterior tibial muscle size using real-time ultrasound imaging.

PubMed

Martinson, H; Stokes, M J

1991-01-01

Cross-sectional images of the anterior tibial muscle group were obtained using real-time ultrasound scanning in 17 normal women. From photographs taken of the images, the cross-sectional area (CSA) and two linear measurements of muscle cross-section were determined. A measurement of the shortest distance of the muscle depth was termed DS, and a measurement of the longest distance through the muscle group was termed DL. Both linear dimensions showed a positive correlation with CSA and the best correlations were obtained when the dimensions were squared or combined (DS x DL). The correlation values were: CSA vs DS2, r = 0.9; CSA vs DL2, r = 0.75 and CSA vs DS x DL, r = 0.88. An approximate value for CSA could be calculated from DS2 by the equation 2 x DS2 + 1. A shape ratio, obtained by dividing DL by DS, was consistent within the group [mean 2.1 (SD 0.2)] and characterised the muscle geometrically. The CSA of repeated scans was assessed for repeatability between-days and between-scans by analysis of variance and the coefficient of variation (CV) calculated. Areas were repeatable between-days (CV 6.5%) and between-scans (CV 3.6%). Linear dimensions of the anterior tibial muscle group reflected CSA and their potential for assessing changes in muscle size with atrophy and hypertrophy have yet to be established.

Tele-education as method of medical education.

PubMed

Masic, Izet; Pandza, Haris; Kulasin, Igor; Masic, Zlatan; Valjevac, Salih

2009-01-01

Development of computer networks and introduction and application of new technologies in all aspects of human activity needs to be followed by universities in their transformation on how to approach scientific, research, and education teaching curricula. Development and increased use of distance learning (DL) over the past decade have clearly shown the potential and efficiency of information technology applied in education. Use of information technology in medical education is where medical informatics takes its place as important scientific discipline which ensures benefit from IT in teaching and learning process involved. Definition of telemedicine as "use of technologies based on health care delivered on distance" covers areas such as electronic health, tele-health (eHealth), telematics, but also tele-education. Web based medical education today is offered in different forms--from online lectures, online exams, web based continuous education programs, use of electronic libraries, online medical and scientific databases etc. Department of Medical Informatics of Medical Faculty of University of Sarajevo has taken many steps to introduce distance learning in medical curricula--from organising professional--scientific events (congresses, workshop etc), organizing first tele-exam at the faculty and among first at the university, to offering online lectures and online education material at the Department's website (www.unsa-medinfo.org). Distance learning in medical education, as well as telemedicine, significantly influence health care in general and are shaping the future model of medical practice. Basic computer and networks skills must be a part of all future medical curricula. The impact of technical equipment on patient-doctor relationship must be taken into account, and doctors have to be trained and prepared for diagnosing or consulting patients by use of IT. Telemedicine requires special approach in certain medical fields--tele-consultation, tele-surgery, tele-radiology and other specific telemedicine applications should be introduced to the curricula. Telemedicine and distance learning are best suited for medical education and doctor-to-doctor consultation--first contact between doctor and a patient should stay face-to-face when possible. In this paper, we present the results of the project Introduction and Implementation of Distance Learning at the Medical Faculty of University of Sarajevo and compare it with the following expected outcomes: development and integration of information technology in medical education; creation of flexible infrastructure which will enable access to e-learning to all students and teaching staff; improvement of digital literacy of academic population; ensuring high educational standards to students and teaching staff; helping medical staffto develop "life-long learning" approach in work and education.

Hydrogen bonding pattern in N-benzoyl(- DL-)- L-phenylalanines as revealed by solid-state NMR spectroscopy

NASA Astrophysics Data System (ADS)

Potrzebowski, M. J.; Schneider, C.; Tekely, P.

1999-11-01

The nature of the hydrogen bonding pattern has been investigated in N-benzoyl- DL-phenylalanine ( 1) and N-benzoyl- L-phenylalanine ( 2) polymorphes by solid-state NMR spectroscopy. It has been shown that the multiple resonances of carboxyl carbon in 2 are directly connected to different types of hydrogen bonding. The differences in intermolecular distances of carboxyl groups involved in different types of hydrogen bonding have been visualized by the 2D exchange and 1D ODESSA experiments. Potential applications of such a new approach include the exploration of intermolecular distances in hydrogen bonded compounds with singly labeled biomolecules.

Dictionary Learning for Data Recovery in Positron Emission Tomography

PubMed Central

Valiollahzadeh, SeyyedMajid; Clark, John W.; Mawlawi, Osama

2015-01-01

Compressed sensing (CS) aims to recover images from fewer measurements than that governed by the Nyquist sampling theorem. Most CS methods use analytical predefined sparsifying domains such as Total variation (TV), wavelets, curvelets, and finite transforms to perform this task. In this study, we evaluated the use of dictionary learning (DL) as a sparsifying domain to reconstruct PET images from partially sampled data, and compared the results to the partially and fully sampled image (baseline). A CS model based on learning an adaptive dictionary over image patches was developed to recover missing observations in PET data acquisition. The recovery was done iteratively in two steps: a dictionary learning step and an image reconstruction step. Two experiments were performed to evaluate the proposed CS recovery algorithm: an IEC phantom study and five patient studies. In each case, 11% of the detectors of a GE PET/CT system were removed and the acquired sinogram data were recovered using the proposed DL algorithm. The recovered images (DL) as well as the partially sampled images (with detector gaps) for both experiments were then compared to the baseline. Comparisons were done by calculating RMSE, contrast recovery and SNR in ROIs drawn in the background, and spheres of the phantom as well as patient lesions. For the phantom experiment, the RMSE for the DL recovered images were 5.8% when compared with the baseline images while it was 17.5% for the partially sampled images. In the patients’ studies, RMSE for the DL recovered images were 3.8%, while it was 11.3% for the partially sampled images. Our proposed CS with DL is a good approach to recover partially sampled PET data. This approach has implications towards reducing scanner cost while maintaining accurate PET image quantification. PMID:26161630

Dictionary learning for data recovery in positron emission tomography

NASA Astrophysics Data System (ADS)

Valiollahzadeh, SeyyedMajid; Clark, John W., Jr.; Mawlawi, Osama

2015-08-01

Compressed sensing (CS) aims to recover images from fewer measurements than that governed by the Nyquist sampling theorem. Most CS methods use analytical predefined sparsifying domains such as total variation, wavelets, curvelets, and finite transforms to perform this task. In this study, we evaluated the use of dictionary learning (DL) as a sparsifying domain to reconstruct PET images from partially sampled data, and compared the results to the partially and fully sampled image (baseline). A CS model based on learning an adaptive dictionary over image patches was developed to recover missing observations in PET data acquisition. The recovery was done iteratively in two steps: a dictionary learning step and an image reconstruction step. Two experiments were performed to evaluate the proposed CS recovery algorithm: an IEC phantom study and five patient studies. In each case, 11% of the detectors of a GE PET/CT system were removed and the acquired sinogram data were recovered using the proposed DL algorithm. The recovered images (DL) as well as the partially sampled images (with detector gaps) for both experiments were then compared to the baseline. Comparisons were done by calculating RMSE, contrast recovery and SNR in ROIs drawn in the background, and spheres of the phantom as well as patient lesions. For the phantom experiment, the RMSE for the DL recovered images were 5.8% when compared with the baseline images while it was 17.5% for the partially sampled images. In the patients’ studies, RMSE for the DL recovered images were 3.8%, while it was 11.3% for the partially sampled images. Our proposed CS with DL is a good approach to recover partially sampled PET data. This approach has implications toward reducing scanner cost while maintaining accurate PET image quantification.

Applications of Deep Learning and Reinforcement Learning to Biological Data.

PubMed

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.

Geographical topic learning for social images with a deep neural network

NASA Astrophysics Data System (ADS)

Feng, Jiangfan; Xu, Xin

2017-03-01

The use of geographical tagging in social-media images is becoming a part of image metadata and a great interest for geographical information science. It is well recognized that geographical topic learning is crucial for geographical annotation. Existing methods usually exploit geographical characteristics using image preprocessing, pixel-based classification, and feature recognition. How to effectively exploit the high-level semantic feature and underlying correlation among different types of contents is a crucial task for geographical topic learning. Deep learning (DL) has recently demonstrated robust capabilities for image tagging and has been introduced into geoscience. It extracts high-level features computed from a whole image component, where the cluttered background may dominate spatial features in the deep representation. Therefore, a method of spatial-attentional DL for geographical topic learning is provided and we can regard it as a special case of DL combined with various deep networks and tuning tricks. Results demonstrated that the method is discriminative for different types of geographical topic learning. In addition, it outperforms other sequential processing models in a tagging task for a geographical image dataset.

The Pathway Program: A Collaboration between 3 Universities to Deliver a Social Work Distance Education (DL) Program to Underserved Areas of California

ERIC Educational Resources Information Center

Morris, Teresa; Jones, Celeste A.; Sehrawats, Seema

2016-01-01

This paper describes the development of a partnership between three campuses to develop a (DL) education program-serving employees of county and tribal Health and Human Service Departments in remote rural areas of California. Specifically, the program supports the development of a career pathway for students living in isolated regions of Northern…

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis.

PubMed

Liang, Liang; Liu, Minliang; Martin, Caitlin; Sun, Wei

2018-01-01

Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis. © 2018 The Author(s).

Sparsity-constrained PET image reconstruction with learned dictionaries

NASA Astrophysics Data System (ADS)

Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie

2016-09-01

PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging.

Distributed learning enhances relational memory consolidation.

PubMed

Litman, Leib; Davachi, Lila

2008-09-01

It has long been known that distributed learning (DL) provides a mnemonic advantage over massed learning (ML). However, the underlying mechanisms that drive this robust mnemonic effect remain largely unknown. In two experiments, we show that DL across a 24 hr interval does not enhance immediate memory performance but instead slows the rate of forgetting relative to ML. Furthermore, we demonstrate that this savings in forgetting is specific to relational, but not item, memory. In the context of extant theories and knowledge of memory consolidation, these results suggest that an important mechanism underlying the mnemonic benefit of DL is enhanced memory consolidation. We speculate that synaptic strengthening mechanisms supporting long-term memory consolidation may be differentially mediated by the spacing of memory reactivation. These findings have broad implications for the scientific study of episodic memory consolidation and, more generally, for educational curriculum development and policy.

New Tools and Metrics for Evaluating Army Distributed Learning

DTIC Science & Technology

2011-01-01

courseware. Designing DL to provide for more opportunities for interaction with instructors and peers is likely to increase student engagement in IMI...toward blended learning may achieve these goals. Student engagement may also be fostered to the extent that the course pro- vides sufficient numbers of... student engagement . • Design and implement DL in ways that provide greater opportunities to interact with instructors and peers. • Enforce policy of

Deep learning approaches for detection and removal of ghosting artifacts in MR spectroscopy.

PubMed

Kyathanahally, Sreenath P; Döring, André; Kreis, Roland

2018-09-01

To make use of deep learning (DL) methods to detect and remove ghosting artifacts in clinical magnetic resonance spectra of human brain. Deep learning algorithms, including fully connected neural networks, deep-convolutional neural networks, and stacked what-where auto encoders, were implemented to detect and correct MR spectra containing spurious echo ghost signals. The DL methods were trained on a huge database of simulated spectra with and without ghosting artifacts that represent complex variations of ghost-ridden spectra, transformed to time-frequency spectrograms. The trained model was tested on simulated and in vivo spectra. The preliminary results for ghost detection are very promising, reaching almost 100% accuracy, and the DL ghost removal methods show potential in simulated and in vivo spectra, but need further refinement and quantitative testing. Ghosting artifacts in spectroscopy are problematic, as they superimpose with metabolites and lead to inaccurate quantification. Detection and removal of ghosting artifacts using traditional machine learning approaches with feature extraction/selection is difficult, as ghosts appear at different frequencies. Here, we show that DL methods perform extremely well for ghost detection if the spectra are treated as images in the form of time-frequency representations. Further optimization for in vivo spectra will hopefully confirm their "ghostbusting" capacity. Magn Reson Med 80:851-863, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Reduction in training time of a deep learning model in detection of lesions in CT

NASA Astrophysics Data System (ADS)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods

PubMed Central

Burlina, Philippe; Billings, Seth; Joshi, Neil

2017-01-01

Objective To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Methods Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and “engineered” features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. Results The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). Conclusions This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification. PMID:28854220

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

PubMed

Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima

2017-01-01

To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

Is deep dreaming the new collage?

NASA Astrophysics Data System (ADS)

Boden, Margaret A.

2017-10-01

Deep dreaming (DD) can combine and transform images in surprising ways. But, being based in deep learning (DL), it is not analytically understood. Collage is an art form that is constrained along various dimensions. DD will not be able to generate collages until DL can be guided in a disciplined fashion.

Boosting compound-protein interaction prediction by deep learning.

PubMed

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.

Scaling Deep Learning Workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gawande, Nitin A.; Landwehr, Joshua B.; Daily, Jeffrey A.

Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors --- including NVIDIA, Intel, AMD and IBM --- have architectural road-maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. This paper provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path. Our evaluation consists of amore » cross section of convolutional neural net workloads: CifarNet, CaffeNet, AlexNet and GoogleNet topologies using the Cifar10 and ImageNet datasets. The workloads are vendor optimized for each architecture. GPUs provide the highest overall raw performance. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and KNL can be competitive when considering performance/watt. Furthermore, NVLink is critical to GPU scaling.« less

Prevalence of Three-Rooted Mandibular First Molars among Indians Using SCT

PubMed Central

Garg, Amit Kumar; Tewari, Rajendra Kumar; Agrawal, Neha

2013-01-01

Undetected extra roots or root canals are a major reason for failure of endodontic treatment. Failure to recognize an extra distolingual (DL) root in mandibular first molar may lead to incomplete debridement of the root canal system and eventually treatment failure. Therefore, it is crucial that atypical anatomy is identified before and during dental treatment. Spiral computed tomography (SCT) images can show 3D images, and therefore much detail can be used when traditional methods prevent adequate endodontic treatment. The overall incidence of DL roots on the mandibular first molars was 6.40% for all patients and 5.00% for all teeth, respectively. The occurrence of DL roots on the right side and on the left side showed a statistically significant difference. The bilateral incidence of symmetrical distribution of DL roots was 56.25%. The DL root canal orifice was separated from DB canal orifice by 2.79 ± 0.34 mm, from the MB canal orifice by 4.23 ± 0.81 mm, and from the ML canal orifice by 3.29 ± 0.52 mm. The high prevalence of the DL root in permanent mandibular first molars among the Indian population by using SCT and estimations of the interorifice distance of such teeth might be useful for successful endodontic treatments. PMID:23840212

Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares.

PubMed

Zhang, Cheng; Zhang, Tao; Li, Ming; Peng, Chengtao; Liu, Zhaobang; Zheng, Jian

2016-06-18

In order to reduce the radiation dose of CT (computed tomography), compressed sensing theory has been a hot topic since it provides the possibility of a high quality recovery from the sparse sampling data. Recently, the algorithm based on DL (dictionary learning) was developed to deal with the sparse CT reconstruction problem. However, the existing DL algorithm focuses on the minimization problem with the L2-norm regularization term, which leads to reconstruction quality deteriorating while the sampling rate declines further. Therefore, it is essential to improve the DL method to meet the demand of more dose reduction. In this paper, we replaced the L2-norm regularization term with the L1-norm one. It is expected that the proposed L1-DL method could alleviate the over-smoothing effect of the L2-minimization and reserve more image details. The proposed algorithm solves the L1-minimization problem by a weighting strategy, solving the new weighted L2-minimization problem based on IRLS (iteratively reweighted least squares). Through the numerical simulation, the proposed algorithm is compared with the existing DL method (adaptive dictionary based statistical iterative reconstruction, ADSIR) and other two typical compressed sensing algorithms. It is revealed that the proposed algorithm is more accurate than the other algorithms especially when further reducing the sampling rate or increasing the noise. The proposed L1-DL algorithm can utilize more prior information of image sparsity than ADSIR. By transforming the L2-norm regularization term of ADSIR with the L1-norm one and solving the L1-minimization problem by IRLS strategy, L1-DL could reconstruct the image more exactly.

Group-sparse representation with dictionary learning for medical image denoising and fusion.

PubMed

Li, Shutao; Yin, Haitao; Fang, Leyuan

2012-12-01

Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

Deep Direct Reinforcement Learning for Financial Signal Representation and Trading.

PubMed

Deng, Yue; Bao, Feng; Kong, Youyong; Ren, Zhiquan; Dai, Qionghai

2017-03-01

Can we train the computer to beat experienced traders for financial assert trading? In this paper, we try to address this challenge by introducing a recurrent deep neural network (NN) for real-time financial signal representation and trading. Our model is inspired by two biological-related learning concepts of deep learning (DL) and reinforcement learning (RL). In the framework, the DL part automatically senses the dynamic market condition for informative feature learning. Then, the RL module interacts with deep representations and makes trading decisions to accumulate the ultimate rewards in an unknown environment. The learning system is implemented in a complex NN that exhibits both the deep and recurrent structures. Hence, we propose a task-aware backpropagation through time method to cope with the gradient vanishing issue in deep training. The robustness of the neural system is verified on both the stock and the commodity future markets under broad testing conditions.

Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

PubMed Central

Janowczyk, Andrew; Madabhushi, Anant

2016-01-01

Background: Deep learning (DL) is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP). The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events), segmentation (e.g., nuclei), and tissue classification (e.g., cancerous vs. non-cancerous). Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific “handcrafted” features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a) selecting appropriate magnification, (b) managing errors in annotations in the training (or learning) dataset, and (c) identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i) DL experts with minimal digital histology experience, and (ii) DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial. Aims: This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches. Results: Specifically, in this tutorial on DL for DP image analysis, we show how an open source framework (Caffe), with a singular network architecture, can be used to address: (a) nuclei segmentation (F-score of 0.83 across 12,000 nuclei), (b) epithelium segmentation (F-score of 0.84 across 1735 regions), (c) tubule segmentation (F-score of 0.83 from 795 tubules), (d) lymphocyte detection (F-score of 0.90 across 3064 lymphocytes), (e) mitosis detection (F-score of 0.53 across 550 mitotic events), (f) invasive ductal carcinoma detection (F-score of 0.7648 on 50 k testing patches), and (g) lymphoma classification (classification accuracy of 0.97 across 374 images). Conclusion: This paper represents the largest comprehensive study of DL approaches in DP to date, with over 1200 DP images used during evaluation. The supplemental online material that accompanies this paper consists of step-by-step instructions for the usage of the supplied source code, trained models, and input data. PMID:27563488

Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.

PubMed

Janowczyk, Andrew; Madabhushi, Anant

2016-01-01

Deep learning (DL) is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP). The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events), segmentation (e.g., nuclei), and tissue classification (e.g., cancerous vs. non-cancerous). Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific "handcrafted" features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a) selecting appropriate magnification, (b) managing errors in annotations in the training (or learning) dataset, and (c) identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i) DL experts with minimal digital histology experience, and (ii) DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial. This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches. Specifically, in this tutorial on DL for DP image analysis, we show how an open source framework (Caffe), with a singular network architecture, can be used to address: (a) nuclei segmentation (F-score of 0.83 across 12,000 nuclei), (b) epithelium segmentation (F-score of 0.84 across 1735 regions), (c) tubule segmentation (F-score of 0.83 from 795 tubules), (d) lymphocyte detection (F-score of 0.90 across 3064 lymphocytes), (e) mitosis detection (F-score of 0.53 across 550 mitotic events), (f) invasive ductal carcinoma detection (F-score of 0.7648 on 50 k testing patches), and (g) lymphoma classification (classification accuracy of 0.97 across 374 images). This paper represents the largest comprehensive study of DL approaches in DP to date, with over 1200 DP images used during evaluation. The supplemental online material that accompanies this paper consists of step-by-step instructions for the usage of the supplied source code, trained models, and input data.

A comparative study of deep learning models for medical image classification

NASA Astrophysics Data System (ADS)

Dutta, Suvajit; Manideep, B. C. S.; Rai, Shalva; Vijayarajan, V.

2017-11-01

Deep Learning(DL) techniques are conquering over the prevailing traditional approaches of neural network, when it comes to the huge amount of dataset, applications requiring complex functions demanding increase accuracy with lower time complexities. Neurosciences has already exploited DL techniques, thus portrayed itself as an inspirational source for researchers exploring the domain of Machine learning. DL enthusiasts cover the areas of vision, speech recognition, motion planning and NLP as well, moving back and forth among fields. This concerns with building models that can successfully solve variety of tasks requiring intelligence and distributed representation. The accessibility to faster CPUs, introduction of GPUs-performing complex vector and matrix computations, supported agile connectivity to network. Enhanced software infrastructures for distributed computing worked in strengthening the thought that made researchers suffice DL methodologies. The paper emphases on the following DL procedures to traditional approaches which are performed manually for classifying medical images. The medical images are used for the study Diabetic Retinopathy(DR) and computed tomography (CT) emphysema data. Both DR and CT data diagnosis is difficult task for normal image classification methods. The initial work was carried out with basic image processing along with K-means clustering for identification of image severity levels. After determining image severity levels ANN has been applied on the data to get the basic classification result, then it is compared with the result of DNNs (Deep Neural Networks), which performed efficiently because of its multiple hidden layer features basically which increases accuracy factors, but the problem of vanishing gradient in DNNs made to consider Convolution Neural Networks (CNNs) as well for better results. The CNNs are found to be providing better outcomes when compared to other learning models aimed at classification of images. CNNs are favoured as they provide better visual processing models successfully classifying the noisy data as well. The work centres on the detection on Diabetic Retinopathy-loss in vision and recognition of computed tomography (CT) emphysema data measuring the severity levels for both cases. The paper discovers how various Machine Learning algorithms can be implemented ensuing a supervised approach, so as to get accurate results with less complexity possible.

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.

PubMed

Janowczyk, Andrew; Doyle, Scott; Gilmore, Hannah; Madabhushi, Anant

2018-01-01

Deep learning (DL) has recently been successfully applied to a number of image analysis problems. However, DL approaches tend to be inefficient for segmentation on large image data, such as high-resolution digital pathology slide images. For example, typical breast biopsy images scanned at 40× magnification contain billions of pixels, of which usually only a small percentage belong to the class of interest. For a typical naïve deep learning scheme, parsing through and interrogating all the image pixels would represent hundreds if not thousands of hours of compute time using high performance computing environments. In this paper, we present a resolution adaptive deep hierarchical (RADHicaL) learning scheme wherein DL networks at lower resolutions are leveraged to determine if higher levels of magnification, and thus computation, are necessary to provide precise results. We evaluate our approach on a nuclear segmentation task with a cohort of 141 ER+ breast cancer images and show we can reduce computation time on average by about 85%. Expert annotations of 12,000 nuclei across these 141 images were employed for quantitative evaluation of RADHicaL. A head-to-head comparison with a naïve DL approach, operating solely at the highest magnification, yielded the following performance metrics: .9407 vs .9854 Detection Rate, .8218 vs .8489 F -score, .8061 vs .8364 true positive rate and .8822 vs 0.8932 positive predictive value. Our performance indices compare favourably with state of the art nuclear segmentation approaches for digital pathology images.

A comparison of direct versus indirect laryngoscopic visualization during endotracheal intubation of lightly embalmed cadavers utilizing the GlideScope®, Storz Medi Pack Mobile Imaging System™ and the New Storz CMAC™ videolaryngoscope.

PubMed

Boedeker, Ben H; Nicholsal, Thomas A; Carpenter, Jennifer; Singh, Leighton; Bernhagen, Mary A; Murray, W Bosseau; Wadman, Michael C

2011-01-01

Studies indicate that the skills needed to use video laryngoscope systems are easily learned by healthcare providers. This study compared several video laryngoscopic (VL) systems and a direct laryngoscope (DL) view when used by medical residents practicing intubation on cadavers. The video devices used included the Storz Medi Pack Mobile Imaging System™, the Storz CMAC® VL System and the GlideScope®. After Institutional Review Board (IRB) approval, University of Nebraska Medical Center, Department of Emergency Medicine (UNMC EM) residents were recruited and given a brief pre-study informational period. The cadavers were lightly embalmed. The study subjects were asked to perform intubations on two cadavers using both DL and VL while using the three different VL systems. Procedural data was recorded for each attempt and pre and post experience perceptions were collected. N=14. All subjects reported their varied previous intubation experience. The average airway score using DL: for the Storz VL was 1.54 (SD = 0.576) and for the C-MAC was 1.46 (SD = 0.637). Success in intubation of the standard airway using DL was 93% versus a 100% success rate when intubating with indirect VL visualization. Based on our data, we believe that the incorporation of VL into cadaver airway management training provided an improved learning environment for the study residents. In our study, the resident subjects were 93% successful with DL intubation even though 50% had less than 30 intubations. As well, there was a 100% success rate when intubating with indirect VL visualization. In conclusion, the researchers believe this cadaver model incorporated with VL is a powerful tool which may help improve the overall learning curve for orotracheal intubation. 2011.

Evaluating the Generalization Value of Process-based Models in a Deep-in-time Machine Learning framework

NASA Astrophysics Data System (ADS)

Shen, C.; Fang, K.

2017-12-01

Deep Learning (DL) methods have made revolutionary strides in recent years. A core value proposition of DL is that abstract notions and patterns can be extracted purely from data, without the need for domain expertise. Process-based models (PBM), on the other hand, can be regarded as repositories of human knowledge or hypotheses about how systems function. Here, through computational examples, we argue that there is merit in integrating PBMs with DL due to the imbalance and lack of data in many situations, especially in hydrology. We trained a deep-in-time neural network, the Long Short-Term Memory (LSTM), to learn soil moisture dynamics from Soil Moisture Active Passive (SMAP) Level 3 product. We show that when PBM solutions are integrated into LSTM, the network is able to better generalize across regions. LSTM is able to better utilize PBM solutions than simpler statistical methods. Our results suggest PBMs have generalization value which should be carefully assessed and utilized. We also emphasize that when properly regularized, the deep network is robust and is of superior testing performance compared to simpler methods.

Performance analysis of model based iterative reconstruction with dictionary learning in transportation security CT

NASA Astrophysics Data System (ADS)

Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno

2016-05-01

In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.

A Locality-Constrained and Label Embedding Dictionary Learning Algorithm for Image Classification.

PubMed

Zhengming Li; Zhihui Lai; Yong Xu; Jian Yang; Zhang, David

2017-02-01

Locality and label information of training samples play an important role in image classification. However, previous dictionary learning algorithms do not take the locality and label information of atoms into account together in the learning process, and thus their performance is limited. In this paper, a discriminative dictionary learning algorithm, called the locality-constrained and label embedding dictionary learning (LCLE-DL) algorithm, was proposed for image classification. First, the locality information was preserved using the graph Laplacian matrix of the learned dictionary instead of the conventional one derived from the training samples. Then, the label embedding term was constructed using the label information of atoms instead of the classification error term, which contained discriminating information of the learned dictionary. The optimal coding coefficients derived by the locality-based and label-based reconstruction were effective for image classification. Experimental results demonstrated that the LCLE-DL algorithm can achieve better performance than some state-of-the-art algorithms.

Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

DOE PAGES

Gawande, Nitin A.; Daily, Jeff A.; Siegel, Charles; ...

2018-05-05

Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors—including NVIDIA, Intel, AMD, and IBM—have architectural road maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating large DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. Here, this article provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path or Cray Aries. Our evaluation consistsmore » of a cross section of convolutional neural net workloads: CifarNet, AlexNet, GoogLeNet, and ResNet50 topologies using the Cifar10 and ImageNet datasets. The workloads are vendor-optimized for each architecture. We use sequentially equivalent implementations to maintain iso-accuracy between parallel and sequential DL models. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and the KNL can be competitive in performance/watt. We find that NVLink facilitates scaling efficiency on GPUs. However, its importance is heavily dependent on neural network architecture. Furthermore, for weak-scaling—sometimes encouraged by restricted GPU memory—NVLink is less important.« less

Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gawande, Nitin A.; Daily, Jeff A.; Siegel, Charles

Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors—including NVIDIA, Intel, AMD, and IBM—have architectural road maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating large DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. Here, this article provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path or Cray Aries. Our evaluation consistsmore » of a cross section of convolutional neural net workloads: CifarNet, AlexNet, GoogLeNet, and ResNet50 topologies using the Cifar10 and ImageNet datasets. The workloads are vendor-optimized for each architecture. We use sequentially equivalent implementations to maintain iso-accuracy between parallel and sequential DL models. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and the KNL can be competitive in performance/watt. We find that NVLink facilitates scaling efficiency on GPUs. However, its importance is heavily dependent on neural network architecture. Furthermore, for weak-scaling—sometimes encouraged by restricted GPU memory—NVLink is less important.« less

Comparison of alternative designs for reducing complex neurons to equivalent cables.

PubMed

Burke, R E

2000-01-01

Reduction of the morphological complexity of actual neurons into accurate, computationally efficient surrogate models is an important problem in computational neuroscience. The present work explores the use of two morphoelectrotonic transformations, somatofugal voltage attenuation (AT cables) and signal propagation delay (DL cables), as bases for construction of electrotonically equivalent cable models of neurons. In theory, the AT and DL cables should provide more accurate lumping of membrane regions that have the same transmembrane potential than the familiar equivalent cables that are based only on somatofugal electrotonic distance (LM cables). In practice, AT and DL cables indeed provided more accurate simulations of the somatic transient responses produced by fully branched neuron models than LM cables. This was the case in the presence of a somatic shunt as well as when membrane resistivity was uniform.

Diagnosing Diabetes and Learning about Prediabetes

MedlinePlus

... Listen En Español Diagnosing Diabetes and Learning About Prediabetes There are several ways to diagnose diabetes. Each ... or equal to 200 mg/dl What is Prediabetes? Before people develop type 2 diabetes, they almost ...

An Integral Prediction Method for Three-Dimensional Turbulent Boundary Layers on Rotating Blades.

DTIC Science & Technology

1981-06-01

in’siscid streamline 6 Boundary-dyer thickness 61 StreamwNise displacement thickness. 61 f (I -)d (- ro,,,,isk displacement tikes 0 D~istance along thle...hl 󈧦 h2 ar)+(Uhl al, + 2w3 2022 a U + - 61 + _ I- 022+dl) =-Cf2U Uh 2 8 1 In equations 3a and 3b, 011, 012 , 021 , 022 , dl, and 62 are the momentum...K2 (6-6w)-62 ( h2U arl ( 61 ) Details of the cntrainment function are given in a later section of this paper. ADDITIONAL RELATIONSHIPS Further

MO-G-17A-05: PET Image Deblurring Using Adaptive Dictionary Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valiollahzadeh, S; Clark, J; Mawlawi, O

2014-06-15

Purpose: The aim of this work is to deblur PET images while suppressing Poisson noise effects using adaptive dictionary learning (DL) techniques. Methods: The model that relates a blurred and noisy PET image to the desired image is described as a linear transform y=Hm+n where m is the desired image, H is a blur kernel, n is Poisson noise and y is the blurred image. The approach we follow to recover m involves the sparse representation of y over a learned dictionary, since the image has lots of repeated patterns, edges, textures and smooth regions. The recovery is based onmore » an optimization of a cost function having four major terms: adaptive dictionary learning term, sparsity term, regularization term, and MLEM Poisson noise estimation term. The optimization is solved by a variable splitting method that introduces additional variables. We simulated a 128×128 Hoffman brain PET image (baseline) with varying kernel types and sizes (Gaussian 9×9, σ=5.4mm; Uniform 5×5, σ=2.9mm) with additive Poisson noise (Blurred). Image recovery was performed once when the kernel type was included in the model optimization and once with the model blinded to kernel type. The recovered image was compared to the baseline as well as another recovery algorithm PIDSPLIT+ (Setzer et. al.) by calculating PSNR (Peak SNR) and normalized average differences in pixel intensities (NADPI) of line profiles across the images. Results: For known kernel types, the PSNR of the Gaussian (Uniform) was 28.73 (25.1) and 25.18 (23.4) for DL and PIDSPLIT+ respectively. For blinded deblurring the PSNRs were 25.32 and 22.86 for DL and PIDSPLIT+ respectively. NADPI between baseline and DL, and baseline and blurred for the Gaussian kernel was 2.5 and 10.8 respectively. Conclusion: PET image deblurring using dictionary learning seems to be a good approach to restore image resolution in presence of Poisson noise. GE Health Care.« less

Internet or dvd for distance learning to isolated rural health professionals, what is the best approach?

PubMed

Rakototiana, Lanto Barthelemy; Rajabo; Gottot, Serge

2017-09-06

Distance Learning (DL) is a means to overcome the barriers that prevent health workers access to medical education and training sessions to update their knowledge. The main objective of this study is to compare the knowledge acquisition among practitioners Heads of Health Based Center (HBC) for the management of hypertension in two training modalities, one interactive, via internet (by Visio conferencing and video Conferencing), and other non-interactive, via DVD in the three regions (Miarinarivo, Moramanga and Manjakandriana) of Madagascar. This is a quasi-experimental study comparing two distance learning methodologies, one via internet (VS or VD) and the other via DVD before and after training. Ninety-two (92) Heads of HBC participated in the training, including 56 via the Internet (24 doctors and 32 paramedics) and 36 via DVD (24 doctors and 12 paramedics). According to the training mode: the mean score of knowledge of the participants was 7 (+ -2) for two terms before training. It is 14 (+ -2.5) in the internet group (VS or VD) and 15 (+ -2.7) in the DVD group after training. The difference between the two groups was not significant p = 0.076. For doctors, the score was 7 (+ -3.1) via internet and 8 (+ -2.3) via DVD in pre test and 14 (+ - 2.4) via internet and 16 (+ -. 2.7) via DVD in post test, the difference between the two training methods was significant (p = 0.008). Among the paramedics, the results are the same for both conditions, 7 (+ - 2.4 to + -3.2) in pre test and 14 (+ - 2.2 to + -2.7) in post test. Both training methods have improved participants' knowledge and the DVD mode is the first choice for Heads HBC of Madagascar with the majority located in remote areas.

Periodontal Healing Distally to Second Mandibular Molar After Third Molar Coronectomy.

PubMed

Vignudelli, Elisabetta; Monaco, Giuseppe; Gatto, Maria Rosaria Antonella; Franco, Simonetta; Marchetti, Claudio; Corinaldesi, Giuseppe

2017-01-01

Coronectomy of mandibular third molars is a procedure that still raises a number of questions. The aim of the present study was to answer one unsolved question: the periodontal healing distal to the mandibular second molar after third molar coronectomy. A prospective cohort study was performed of 30 patients treated at the Unit of Oral and Maxillofacial Surgery of the Department of Biomedical and Neuromotor Science of the University of Bologna. The predictor variables were the probing pocket depth (PPD), the distance between the marginal crest (MC) and the bottom of the osseous defect (BOD), and the distance between the cementum enamel junction (CEJ) and the BOD. These clinical indexes were recorded on 3 points of the distal surface of second molar: the distobuccal (DB), distomedial (DM), and distolingual (DL) sites. The other variables evaluated included root migration and postoperative complications. The Wilcoxon test for paired data and Kendall's tau-b correlation coefficient was used to evaluate all variables. The significance level was set at P = .05. The cohort was composed of 30 patients with 34 high-risk mandibular third molars (9 men and 21 women), with a mean age of 28 ± 7 years. At 9 months, a statistically significant reduction in the PPD of 2 ± 3, 1 ± 2, and 2 ± 2 mm and a statistically significant reduction in the MC-BOD distance of 4 ± 4, 4 ± 4, and 4 ± 5 mm for the DB, DM, and DL sites, respectively, was observed (P = .001). Also, the intraoperative CEJ-BOD distance showed a statistically significant reduction for the DB, DM, and DL sites. After coronectomy, restoration of a clinical healthy periodontium distal to the second molar was observed. However, further studies are necessary to confirm these preliminary clinical results and to compare periodontal healing between coronectomy and complete extraction. Copyright © 2016 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon-Ocean Feedback in Typhoon Forecast Models

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qing; Xu, Jing; Wei, Jun

2018-04-01

Two algorithms based on machine learning neural networks are proposed—the shallow learning (S-L) and deep learning (D-L) algorithms—that can potentially be used in atmosphere-only typhoon forecast models to provide flow-dependent typhoon-induced sea surface temperature cooling (SSTC) for improving typhoon predictions. The major challenge of existing SSTC algorithms in forecast models is how to accurately predict SSTC induced by an upcoming typhoon, which requires information not only from historical data but more importantly also from the target typhoon itself. The S-L algorithm composes of a single layer of neurons with mixed atmospheric and oceanic factors. Such a structure is found to be unable to represent correctly the physical typhoon-ocean interaction. It tends to produce an unstable SSTC distribution, for which any perturbations may lead to changes in both SSTC pattern and strength. The D-L algorithm extends the neural network to a 4 × 5 neuron matrix with atmospheric and oceanic factors being separated in different layers of neurons, so that the machine learning can determine the roles of atmospheric and oceanic factors in shaping the SSTC. Therefore, it produces a stable crescent-shaped SSTC distribution, with its large-scale pattern determined mainly by atmospheric factors (e.g., winds) and small-scale features by oceanic factors (e.g., eddies). Sensitivity experiments reveal that the D-L algorithms improve maximum wind intensity errors by 60-70% for four case study simulations, compared to their atmosphere-only model runs.

Image reconstruction from few-view CT data by gradient-domain dictionary learning.

PubMed

Hu, Zhanli; Liu, Qiegen; Zhang, Na; Zhang, Yunwan; Peng, Xi; Wu, Peter Z; Zheng, Hairong; Liang, Dong

2016-05-21

Decreasing the number of projections is an effective way to reduce the radiation dose exposed to patients in medical computed tomography (CT) imaging. However, incomplete projection data for CT reconstruction will result in artifacts and distortions. In this paper, a novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction. Specifically, the dictionaries are trained from the horizontal and vertical gradient images, respectively and the desired image is reconstructed subsequently from the sparse representations of both gradients by solving the least-square method. Since the gradient images are sparser than the image itself, the proposed approach could lead to sparser representations than conventional DL methods in the image-domain, and thus a better reconstruction quality is achieved. To evaluate the proposed Grad-DL algorithm, both qualitative and quantitative studies were employed through computer simulations as well as real data experiments on fan-beam and cone-beam geometry. The results show that the proposed algorithm can yield better images than the existing algorithms.

Scaling deep learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gawande, Nitin A.; Landwehr, Joshua B.; Daily, Jeffrey A.

Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors --- including NVIDIA, Intel, AMD, and IBM --- have architectural road-maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating large DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. This paper provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path or Cray Aries. Ourmore » evaluation consists of a cross section of convolutional neural net workloads: CifarNet, AlexNet, GoogLeNet, and ResNet50 topologies using the Cifar10 and ImageNet datasets. The workloads are vendor-optimized for each architecture. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and the KNL can be competitive in performance/watt. We find that NVLink facilitates scaling efficiency on GPUs. However, its importance is heavily dependent on neural network architecture. Furthermore, for weak-scaling --- sometimes encouraged by restricted GPU memory --- NVLink is less important.« less

Pharmacotherapeutic education through problem based learning and its impact on cognitive and motivational attitude of Indian students.

PubMed

Chandra, D; Sharma, S; Sethi, G; Dkhar, S

1996-01-01

The cognitive and motivational attitudes to problem based learning (i.e., simple didactic problem stated in written form and Programmed Patient) has been compared with those to didactic lectures (DL), the traditional teaching method. The change in recall performance measured in MCQ tests was considered as a change in the cognitive domain. The first test was conducted one week after completion of the topic and second test was taken 3 months later, without prior information. The motivational change was recorded by open-ended questions about the learning method. Three groups of students at second MBBS professional year level consisting of 55, 57 and 59 people, were assigned a simple didactic problem stated in written form (SDP), programmed patients (PP), and didactic lecture (DL), respectively. The average scores obtained by the learners in problem based learning (PBL) groups were similar to the students in the DL group in both the tests. Most of the students in PBL groups appreciated the exercise and suggested including more such exercises in the curriculum. These exercises helped them to better understand patient problems and prescribing behaviour as well as in development of communication skills. However, these exercises were time consuming and were not examination oriented. Pharmacotherapeutic teaching through PBL could be used within a traditional curriculum to develop relevant and rational use of drugs, provided the evaluation method was also modified.

Deep learning for single-molecule science

NASA Astrophysics Data System (ADS)

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.

Attentional Bias in Human Category Learning: The Case of Deep Learning.

PubMed

Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

2018-01-01

Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars) are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error) is reached resulting in rapid asymptotic learning.

Stellar binary black holes in the LISA band: a new class of standard sirens

NASA Astrophysics Data System (ADS)

Del Pozzo, Walter; Sesana, Alberto; Klein, Antoine

2018-04-01

The recent Advanced LIGO detections of coalescing black hole binaries (BHBs) imply a large population of such systems emitting at milli-Hz frequencies, accessible to the Laser Interferometer Space Antenna (LISA). We show that these systems provide a new class of cosmological standard sirens. Direct LISA luminosity distance - Dl - measurements, combined with the inhomogeneous redshift - z - distribution of possible host galaxies provide an effective way to populate the Dl-z diagram at z < 0.1, thus allowing a precise local measurement of the Hubble expansion rate. To be effective, the method requires a sufficiently precise LISA distance determination and sky localization of a sizeable number of BHBs, which is best achieved for a six-link detector configuration. We find that, for a BHB population consistent with current fiducial LIGO rates, the Hubble constant H0 can be determined at the ˜5 per cent and ˜2 per cent level (68 per cent confidence), assuming two and five million kilometre arm-length, respectively.

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

PubMed

Ghesu, Florin C; Krubasik, Edward; Georgescu, Bogdan; Singh, Vivek; Yefeng Zheng; Hornegger, Joachim; Comaniciu, Dorin

2016-05-01

Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volumetric medical image data are typically based on machine learning methods that exploit large annotated image databases. Two main challenges need to be addressed, these are the efficiency in scanning high-dimensional parametric spaces and the need for representative image features which require significant efforts of manual engineering. We propose a pipeline for object detection and segmentation in the context of volumetric image parsing, solving a two-step learning problem: anatomical pose estimation and boundary delineation. For this task we introduce Marginal Space Deep Learning (MSDL), a novel framework exploiting both the strengths of efficient object parametrization in hierarchical marginal spaces and the automated feature design of Deep Learning (DL) network architectures. In the 3D context, the application of deep learning systems is limited by the very high complexity of the parametrization. More specifically 9 parameters are necessary to describe a restricted affine transformation in 3D, resulting in a prohibitive amount of billions of scanning hypotheses. The mechanism of marginal space learning provides excellent run-time performance by learning classifiers in clustered, high-probability regions in spaces of gradually increasing dimensionality. To further increase computational efficiency and robustness, in our system we learn sparse adaptive data sampling patterns that automatically capture the structure of the input. Given the object localization, we propose a DL-based active shape model to estimate the non-rigid object boundary. Experimental results are presented on the aortic valve in ultrasound using an extensive dataset of 2891 volumes from 869 patients, showing significant improvements of up to 45.2% over the state-of-the-art. To our knowledge, this is the first successful demonstration of the DL potential to detection and segmentation in full 3D data with parametrized representations.

The Evolution of Electronic Pedagogy in an Outcome Based Learning Environment: Learning, Teaching, and the Culture of Technology at California's Newest University--CSU Monterey Bay.

ERIC Educational Resources Information Center

Baldwin, George

California State University Monterey Bay (CSUMB) is the newest university in the CSU system. CSUMB's vision statement distinguishes the institution from others in the system by promoting learning paradigms of Outcome Based Education (OBE) and communication technologies of distributed learning (DL). Faculty are committed to the experimental use of…

Hypertext or Textbook: Effects on Motivation and Gain in Knowledge

ERIC Educational Resources Information Center

Conradty, Cathérine; Bogner, Franz X.

2016-01-01

Computers are considered innovative in classrooms, raising expectations of increased cognitive learning outcomes or motivation with effects on Deeper Learning (DL). The "new medium", however, may cause cognitive overloads. Combined with gender-related variations in ability, self-efficacy or self-confidence, computers may even diminish…

The Relation between Coronal Holes and Coronal Mass Ejections during the Rise, Maximum, and Declining Phases of Solar Cycle 23

NASA Technical Reports Server (NTRS)

Mohamed, A. A.; Gopalswamy, N; Yashiro, S.; Akiyama, S.; Makela, P.; Xie, H.; Jung, H.

2012-01-01

We study the interaction between coronal holes (CHs) and coronal mass ejections (CMEs) using a resultant force exerted by all the coronal holes present on the disk and is defined as the coronal hole influence parameter (CHIP). The CHIP magnitude for each CH depends on the CH area, the distance between the CH centroid and the eruption region, and the average magnetic field within the CH at the photospheric level. The CHIP direction for each CH points from the CH centroid to the eruption region. We focus on Solar Cycle 23 CMEs originating from the disk center of the Sun (central meridian distance =15deg) and resulting in magnetic clouds (MCs) and non-MCs in the solar wind. The CHIP is found to be the smallest during the rise phase for MCs and non-MCs. The maximum phase has the largest CHIP value (2.9 G) for non-MCs. The CHIP is the largest (5.8 G) for driverless (DL) shocks, which are shocks at 1 AU with no discernible MC or non-MC. These results suggest that the behavior of non-MCs is similar to that of the DL shocks and different from that of MCs. In other words, the CHs may deflect the CMEs away from the Sun-Earth line and force them to behave like limb CMEs with DL shocks. This finding supports the idea that all CMEs may be flux ropes if viewed from an appropriate vantage point.

Light propagation through black-hole lattices

NASA Astrophysics Data System (ADS)

Bentivegna, Eloisa; Korzyński, Mikołaj; Hinder, Ian; Gerlicher, Daniel

2017-03-01

The apparent properties of distant objects encode information about the way the light they emit propagates to an observer, and therefore about the curvature of the underlying spacetime. Measuring the relationship between the redshift z and the luminosity distance DL of a standard candle, for example, yields information on the Universe's matter content. In practice, however, in order to decode this information the observer needs to make an assumption about the functional form of the DL(z) relation; in other words, a cosmological model needs to be assumed. In this work, we use numerical-relativity simulations, equipped with a new ray-tracing module, to numerically obtain this relation for a few black-hole-lattice cosmologies and compare it to the well-known Friedmann-Lema{ȋtre-Robertson-Walker case, as well as to other relevant cosmologies and to the Empty-Beam Approximation. We find that the latter provides the best estimate of the luminosity distance and formulate a simple argument to account for this agreement. We also find that a Friedmann-Lema{ȋtre-Robertson-Walker model can reproduce this observable exactly, as long as a time-dependent cosmological constant is included in the fit. Finally, the dependence of these results on the lattice mass-to-spacing ratio μ is discussed: we discover that, unlike the expansion rate, the DL(z) relation in a black-hole lattice does not tend to that measured in the corresponding continuum spacetime as 0μ → .

Bridging the Gap Between Scientists and Classrooms: Scientist Engagement in the Expedition Earth and Beyond Program

NASA Technical Reports Server (NTRS)

Graff, P. V.; Stefanov, W. L.; Willis, K. J.; Runco, S.

2012-01-01

Teachers in today s classrooms need to find creative ways to connect students with science, technology, engineering, mathematics (STEM) experts. These STEM experts can serve as role models and help students think about potential future STEM careers. They can also help reinforce academic knowledge and skills. The cost of transportation restricts teachers ability to take students on field trips exposing them to outside experts and unique learning environments. Additionally, arranging to bring in guest speakers to the classroom seems to happen infrequently, especially in schools in rural areas. The Expedition Earth and Beyond (EEAB) Program [1], facilitated by the Astromaterials Research and Exploration Science (ARES) Directorate Education Program at the NASA Johnson Space Center has created a way to enable teachers to connect their students with STEM experts virtually. These virtual connections not only help engage students with role models, but are also designed to help teachers address concepts and content standards they are required to teach. Through EEAB, scientists are able to actively engage with students across the nation in multiple ways. They can work with student teams as mentors, participate in virtual student team science presentations, or connect with students through Classroom Connection Distance Learning (DL) Events.

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints.

PubMed

Wang, Shanshan; Xia, Yong; Dong, Pei; Feng, David Dagan; Luo, Jianhua; Huang, Qiu

2013-01-01

This paper proposes a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal in magnitude magnetic resonance (MR) images. This algorithm explores both the strength of dictionary learning to preserve image structures and the robustness of local variance estimation to remove signal-dependent Rician noise. The magnitude image is first separated into a number of partly overlapping image patches. The statistics of each patch are collected and analyzed to obtain a local noise variance. To better adapt to Rician noise, a correction factor is formulated with the local signal-to-noise ratio (SNR). Finally, the trained dictionary is used to denoise each image patch under spatially adaptive constraints. The proposed algorithm has been compared to the popular nonlocal means (NLM) filtering and unbiased NLM (UNLM) algorithm on simulated T1-weighted, T2-weighted and PD-weighted MR images. Our results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.

A randomised controlled trial of a blended learning education intervention for teaching evidence-based medicine.

PubMed

Ilic, Dragan; Nordin, Rusli Bin; Glasziou, Paul; Tilson, Julie K; Villanueva, Elmer

2015-03-10

Few studies have been performed to inform how best to teach evidence-based medicine (EBM) to medical trainees. Current evidence can only conclude that any form of teaching increases EBM competency, but cannot distinguish which form of teaching is most effective at increasing student competency in EBM. This study compared the effectiveness of a blended learning (BL) versus didactic learning (DL) approach of teaching EBM to medical students with respect to competency, self-efficacy, attitudes and behaviour toward EBM. A mixed methods study consisting of a randomised controlled trial (RCT) and qualitative case study was performed with medical students undertaking their first clinical year of training in EBM. Students were randomly assigned to receive EBM teaching via either a BL approach or the incumbent DL approach. Competency in EBM was assessed using the Berlin questionnaire and the 'Assessing Competency in EBM' (ACE) tool. Students' self-efficacy, attitudes and behaviour was also assessed. A series of focus groups was also performed to contextualise the quantitative results. A total of 147 students completed the RCT, and a further 29 students participated in six focus group discussions. Students who received the BL approach to teaching EBM had significantly higher scores in 5 out of 6 behaviour domains, 3 out of 4 attitude domains and 10 out of 14 self-efficacy domains. Competency in EBM did not differ significantly between students receiving the BL approach versus those receiving the DL approach [Mean Difference (MD)=-0.68, (95% CI-1.71, 0.34), p=0.19]. No significant difference was observed between sites (p=0.89) or by student type (p=0.58). Focus group discussions suggested a strong student preference for teaching using a BL approach, which integrates lectures, online learning and small group activities. BL is no more effective than DL at increasing medical students' knowledge and skills in EBM, but was significantly more effective at increasing student attitudes toward EBM and self-reported use of EBM in clinical practice. Given the various learning styles preferred by students, a multifaceted approach (incorporating BL) may be best suited when teaching EBM to medical students. Further research on the cost-effectiveness of EBM teaching modalities is required.

VizieR Online Data Catalog: Nearby Seyfert galaxies FIR emissions (Garcia-Gonzalez+, 2016)

NASA Astrophysics Data System (ADS)

Garcia-Gonzalez, J.; Alonso-Herrero, A.; Hernan-Caballero, A.; Pereira-Santaella, M.; Ramos-Almeida, C.; Acosta-Pulido, J. A.; Diaz-Santos, T.; Esquej, P.; Gonzalez-Martin, O.; Ichikawa, K.; Lopez-Rodriguez, E.; Povic, M.; Roche, P. F.; Sanchez-Portal, M.

2017-06-01

We selected a sample of 33 nearby (distances DL<70Mpc, Table 1) Seyfert galaxies from the RSA catalogue (Sandage & Tammann 1987, Cat. VII/51) with Herschel/PACS imaging observations in at least two bands and SPIRE imaging observations from our own programmes and from the archive (see Table 3). (6 data files).

Distance learning in academic health education.

PubMed

Mattheos, N; Schittek, M; Attström, R; Lyon, H C

2001-05-01

Distance learning is an apparent alternative to traditional methods in education of health care professionals. Non-interactive distance learning, interactive courses and virtual learning environments exist as three different generations in distance learning, each with unique methodologies, strengths and potential. Different methodologies have been recommended for distance learning, varying from a didactic approach to a problem-based learning procedure. Accreditation, teamwork and personal contact between the tutors and the students during a course provided by distance learning are recommended as motivating factors in order to enhance the effectiveness of the learning. Numerous assessment methods for distance learning courses have been proposed. However, few studies report adequate tests for the effectiveness of the distance-learning environment. Available information indicates that distance learning may significantly decrease the cost of academic health education at all levels. Furthermore, such courses can provide education to students and professionals not accessible by traditional methods. Distance learning applications still lack the support of a solid theoretical framework and are only evaluated to a limited extent. Cases reported so far tend to present enthusiastic results, while more carefully-controlled studies suggest a cautious attitude towards distance learning. There is a vital need for research evidence to identify the factors of importance and variables involved in distance learning. The effectiveness of distance learning courses, especially in relation to traditional teaching methods, must therefore be further investigated.

Joint Entropy Minimization for Learning in Nonparametric Framework

DTIC Science & Technology

2006-06-09

Tibshirani, G. Sherlock , W. C. Chan, T. C. Greiner, D. D. Weisenburger, J. O. Armitage, R. Warnke, R. Levy, W. Wilson, M. R. Grever, J. C. Byrd, D. Botstein, P...Entropy Minimization for Learning in Nonparametric Framework 33 [11] D.L. Collins, A.P. Zijdenbos, J.G. Kollokian, N.J. Sled, C.J. Kabani, C.J. Holmes

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels.

PubMed

Sornapudi, Sudhir; Stanley, Ronald Joe; Stoecker, William V; Almubarak, Haidar; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R

2018-01-01

Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods.

The Influence of Personality and Chronotype on Distance Learning Willingness and Anxiety among Vocational High School Students in Turkey

ERIC Educational Resources Information Center

Randler, Christoph; Horzum, Mehmet Baris; Vollmer, Christian

2014-01-01

There are many studies related to distance learning. Willingness and anxiety are important variables for distance learning. Recent research has shown that anxiety and willingness towards distance learning are moderated by personality. This study sought to investigate whether distance learning willingness and distance learning anxiety are…

Oxytocin receptor neurotransmission in the dorsolateral bed nucleus of the stria terminalis facilitates the acquisition of cued fear in the fear-potentiated startle paradigm in rats.

PubMed

Moaddab, Mahsa; Dabrowska, Joanna

2017-07-15

Oxytocin (OT) is a hypothalamic neuropeptide that modulates fear and anxiety-like behaviors. Dorsolateral bed nucleus of the stria terminalis (BNST dl ) plays a critical role in the regulation of fear and anxiety, and expresses high levels of OT receptor (OTR). However, the role of OTR neurotransmission within the BNST dl in mediating these behaviors is unknown. Here, we used adult male Sprague-Dawley rats to investigate the role of OTR neurotransmission in the BNST dl in the modulation of the acoustic startle response, as well as in the acquisition and consolidation of conditioned fear using fear potentiated startle (FPS) paradigm. Bilateral intra-BNST dl administration of OT (100 ng) did not affect the acquisition of conditioned fear response. However, intra-BNST dl administration of specific OTR antagonist (OTA), (d(CH 2 ) 5 1 , Tyr(Me) 2 , Thr 4 , Orn 8 , des-Gly-NH 2 9 )-vasotocin, (200 ng), prior to the fear conditioning session, impaired the acquisition of cued fear, without affecting a non-cued fear component of FPS. Neither OTA, nor OT affected baseline startle or shock reactivity during fear conditioning. Therefore, the observed impairment of cued fear after OTA infusion resulted from the specific effect on the formation of cued fear. In contrast to the acquisition, neither OTA nor OT affected the consolidation of FPS, when administered after the completion of fear conditioning session. Taken together, these results reveal the important role of OTR neurotransmission in the BNST dl in the formation of conditioned fear to a discrete cue. This study also highlights the role of the BNST dl in learning to discriminate between threatening and safe stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distance Training in the European Union. ZIFF Papiere 96.

ERIC Educational Resources Information Center

Keegan, Desmond

A study examined distance training in the European Union (EU) countries. First, recent literature on the following topics was reviewed: technology-supported learning, flexible and distance learning, development of open distance learning, and teleconferencing and distance learning. Next, enrollments and trends in distance learning in the EU as a…

Cheating experience: Guiding novices to adopt the gaze strategies of experts expedites the learning of technical laparoscopic skills.

PubMed

Vine, Samuel J; Masters, Rich S W; McGrath, John S; Bright, Elizabeth; Wilson, Mark R

2012-07-01

Previous research has demonstrated that trainees can be taught (via explicit verbal instruction) to adopt the gaze strategies of expert laparoscopic surgeons. The current study examined a software template designed to guide trainees to adopt expert gaze control strategies passively, without being provided with explicit instructions. We examined 27 novices (who had no laparoscopic training) performing 50 learning trials of a laparoscopic training task in either a discovery-learning (DL) group or a gaze-training (GT) group while wearing an eye tracker to assess gaze control. The GT group performed trials using a surgery-training template (STT); software that is designed to guide expert-like gaze strategies by highlighting the key locations on the monitor screen. The DL group had a normal, unrestricted view of the scene on the monitor screen. Both groups then took part in a nondelayed retention test (to assess learning) and a stress test (under social evaluative threat) with a normal view of the scene. The STT was successful in guiding the GT group to adopt an expert-like gaze strategy (displaying more target-locking fixations). Adopting expert gaze strategies led to an improvement in performance for the GT group, which outperformed the DL group in both retention and stress tests (faster completion time and fewer errors). The STT is a practical and cost-effective training interface that automatically promotes an optimal gaze strategy. Trainees who are trained to adopt the efficient target-locking gaze strategy of experts gain a performance advantage over trainees left to discover their own strategies for task completion. Copyright © 2012 Mosby, Inc. All rights reserved.

Genetic differentiation of Octopus minor (Mollusca, Cephalopoda) off the northern coast of China as revealed by amplified fragment length polymorphisms.

PubMed

Yang, J M; Sun, G H; Zheng, X D; Ren, L H; Wang, W J; Li, G R; Sun, B C

2015-12-02

Octopus minor (Sasaki, 1920) is an economically important cephalopod that is found in the northern coastal waters of China. In this study, we investigated genetic differentiation in fishery populations using amplified fragment length polymorphisms (AFLPs). A total of 150 individuals were collected from five locations: Dalian (DL), Yan-tai (YT), Qingdao (QD), Lianyungang (LY), and Zhoushan (ZS), and 243 reproducible bands were amplified using five AFLP primer combinations. The percentage of polymorphic bands ranged from 53.33 to 76.08%. Nei's genetic identity ranged from 0.9139 to 0.9713, and the genetic distance ranged from 0.0291 to 0.0900. A phylogenetic tree was constructed using the unweighted pair group method with arithmetic mean, based on the genetic distance. The DL and YT populations originated from one clade, while the QD, LY, and ZS populations originated from another. The results indicate that the O. minor stock consisted of two genetic populations with an overall significantly analogous FST value (0.1088, P < 0.05). Most of the variance was within populations. These findings will be important for more sustainable octopus fisheries, so that this marine resource can be conserved for its long-term utilization.

Making Improvements to The Army Distributed Learning Program

DTIC Science & Technology

2012-01-01

Learning (pre/post comparisons). e Army could develop an IT platform to administer course pretests and posttests . Automatic scoring/reporting... groups with proponent schools, DL contractors, and TRADOC head- quarters sta; reviews of Army processes for developing courseware; and an analysis...Lessons ORD Operational Requirements Document PB President’s Budget PCO Procuring Contract Oce PEG Program Evaluation Group PEO EIS U.S. Army

Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images.

PubMed

Rajaraman, Sivaramakrishnan; Antani, Sameer K; Poostchi, Mahdieh; Silamut, Kamolrat; Hossain, Md A; Maude, Richard J; Jaeger, Stefan; Thoma, George R

2018-01-01

Malaria is a blood disease caused by the Plasmodium parasites transmitted through the bite of female Anopheles mosquito. Microscopists commonly examine thick and thin blood smears to diagnose disease and compute parasitemia. However, their accuracy depends on smear quality and expertise in classifying and counting parasitized and uninfected cells. Such an examination could be arduous for large-scale diagnoses resulting in poor quality. State-of-the-art image-analysis based computer-aided diagnosis (CADx) methods using machine learning (ML) techniques, applied to microscopic images of the smears using hand-engineered features demand expertise in analyzing morphological, textural, and positional variations of the region of interest (ROI). In contrast, Convolutional Neural Networks (CNN), a class of deep learning (DL) models promise highly scalable and superior results with end-to-end feature extraction and classification. Automated malaria screening using DL techniques could, therefore, serve as an effective diagnostic aid. In this study, we evaluate the performance of pre-trained CNN based DL models as feature extractors toward classifying parasitized and uninfected cells to aid in improved disease screening. We experimentally determine the optimal model layers for feature extraction from the underlying data. Statistical validation of the results demonstrates the use of pre-trained CNNs as a promising tool for feature extraction for this purpose.

Country-wide distance training for delivery of screening and brief intervention for problematic substance use: A pilot evaluation of participant experiences and patient outcomes.

PubMed

Carneiro, Ana Paula Leal; Souza-Formigoni, Maria Lucia Oliveira

2018-01-02

In this study, the authors evaluated if the 120-hour distance learning (DL) course SUPERA (an acronym in Portuguese meaning "System for detection of excessive use or dependence on psychoactive substances: brief Intervention, social reinsertion and follow-up") was an effective way to train health professionals and social workers to apply screening and brief intervention (SBI) for patients with substance use disorders. In the first phase, 2420 health professionals or social workers, who had completed the course, answered an online survey about their use of the SBI. In the second phase, 25 of those professionals applied the ASSIST (Alcohol, Smoking and Substance Involvement Screening Test) followed by a brief intervention (BI) to patients with substance use disorders. Three months after the SBI delivery, independent researchers followed up 79 patients who had received SBI, reapplying the ASSIST and a questionnaire to evaluate the patients'/clients' satisfaction with the intervention they received. In the first phase, it was found that most health professionals and social workers who completed the course applied the SBI in their work and felt very motivated to do it. In the second phase of the study, at a 3-month follow-up, most patients had significantly reduced their ASSIST scores in respect of alcohol and cocaine/crack in relation to their baseline levels. Those patients classified by their ASSIST score as "suggestive of dependence" presented a significant reduction in their scores regarding alcohol, tobacco, and cocaine/crack, whereas those classified as "at risk" presented a reduction in respect of alcohol problems only. Patients associated changes in their substance use with the SBI received. A reduction in substance use-related problems was associated with the SBI applied by the health professionals or social workers trained by the DL course SUPERA. Two significant limitations of this study were the small number of participants (professionals and patients in the follow-up) and the absence of a control group in the second phase of the study.

Incidence, predictors, and outcome of difficult mask ventilation combined with difficult laryngoscopy: a report from the multicenter perioperative outcomes group.

PubMed

Kheterpal, Sachin; Healy, David; Aziz, Michael F; Shanks, Amy M; Freundlich, Robert E; Linton, Fiona; Martin, Lizabeth D; Linton, Jonathan; Epps, Jerry L; Fernandez-Bustamante, Ana; Jameson, Leslie C; Tremper, Tyler; Tremper, Kevin K

2013-12-01

Research regarding difficult mask ventilation (DMV) combined with difficult laryngoscopy (DL) is extremely limited even though each technique serves as a rescue for one another. Four tertiary care centers participating in the Multicenter Perioperative Outcomes Group used a consistent structured patient history and airway examination and airway outcome definition. DMV was defined as grade 3 or 4 mask ventilation, and DL was defined as grade 3 or 4 laryngoscopic view or four or more intubation attempts. The primary outcome was DMV combined with DL. Patients with the primary outcome were compared to those without the primary outcome to identify predictors of DMV combined with DL using a non-parsimonious logistic regression. Of 492,239 cases performed at four institutions among adult patients, 176,679 included a documented face mask ventilation and laryngoscopy attempt. Six hundred ninety-eight patients experienced the primary outcome, an overall incidence of 0.40%. One patient required an emergent cricothyrotomy, 177 were intubated using direct laryngoscopy, 284 using direct laryngoscopy with bougie introducer, 163 using videolaryngoscopy, and 73 using other techniques. Independent predictors of the primary outcome included age 46 yr or more, body mass index 30 or more, male sex, Mallampati III or IV, neck mass or radiation, limited thyromental distance, sleep apnea, presence of teeth, beard, thick neck, limited cervical spine mobility, and limited jaw protrusion (c-statistic 0.84 [95% CI, 0.82-0.87]). DMV combined with DL is an infrequent but not rare phenomenon. Most patients can be managed with the use of direct or videolaryngoscopy. An easy to use unweighted risk scale has robust discriminating capacity.

Deep learning and model predictive control for self-tuning mode-locked lasers

NASA Astrophysics Data System (ADS)

Baumeister, Thomas; Brunton, Steven L.; Nathan Kutz, J.

2018-03-01

Self-tuning optical systems are of growing importance in technological applications such as mode-locked fiber lasers. Such self-tuning paradigms require {\\em intelligent} algorithms capable of inferring approximate models of the underlying physics and discovering appropriate control laws in order to maintain robust performance for a given objective. In this work, we demonstrate the first integration of a {\\em deep learning} (DL) architecture with {\\em model predictive control} (MPC) in order to self-tune a mode-locked fiber laser. Not only can our DL-MPC algorithmic architecture approximate the unknown fiber birefringence, it also builds a dynamical model of the laser and appropriate control law for maintaining robust, high-energy pulses despite a stochastically drifting birefringence. We demonstrate the effectiveness of this method on a fiber laser which is mode-locked by nonlinear polarization rotation. The method advocated can be broadly applied to a variety of optical systems that require robust controllers.

Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels

PubMed Central

Sornapudi, Sudhir; Stanley, Ronald Joe; Stoecker, William V.; Almubarak, Haidar; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R.

2018-01-01

Background: Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. Methods: In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. Results: The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. Conclusions: The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods. PMID:29619277

Has Distance Learning Become More Flexible? Reflections of a Distance Learning Student

ERIC Educational Resources Information Center

Thomas, Theda

2012-01-01

This paper provides insight into the way in which distance learning had changed over the past 30 years from the perspective of the author as a distance learning student. The question is then asked as to whether current practice is reducing flexibility for distance learning students? The paper starts with a discussion of flexible learning and the…

The El Paso smelter 20 years later: residual impact on Mexican children.

PubMed

Díaz-Barriga, F; Batres, L; Calderón, J; Lugo, A; Galvao, L; Lara, I; Rizo, P; Arroyave, M E; McConnell, R

1997-01-01

Although there has been considerable concern regarding cross-border industrial contamination between Mexico and the United States, there are remarkably few data. One notable case study is the smelter in El Paso, Texas. In 1974 blood lead levels higher than 40 micrograms/dl were detected in 52% of children studied near the smelter, in the adjacent Mexican community of Anapra in Ciudad Juarez, Chihuahua. Lead smelting at this plant was halted in 1985, and as a result, lead levels in air decreased sharply; consequently, children's exposure to lead and other metals should have diminished accordingly. In order to assess the effect of removal of lead emissions from the area, three geographical locations in Anapra, varying in distance from the smelter source, were evaluated for lead, arsenic, and cadmium levels in soil and for lead in blood of children. It was found that lead levels in soil were inversely correlated with distance from the smelter. Arsenic and cadmium levels in soil were constant among the three sectors. However, at residential sites closer to the smelter, a higher percentage of children was found with blood lead levels exceeding the Centers for Disease Control's action level of 10.0 micrograms/dl. In the sector closest to the border 43% of children had blood lead levels greater than 10.0 micrograms/dl. Although blood lead levels in children living in Anapra have dropped approximately fourfold in 20 years, our results indicate a moderate continued risk of lead exposure. This study demonstrates the persistent impact that may result from cross-border contamination and raises provocative questions regarding appropriate action and the responsibility for financing such action.

Interneurons in the Honeybee Primary Auditory Center Responding to Waggle Dance-Like Vibration Pulses.

PubMed

Ai, Hiroyuki; Kai, Kazuki; Kumaraswamy, Ajayrama; Ikeno, Hidetoshi; Wachtler, Thomas

2017-11-01

Female honeybees use the "waggle dance" to communicate the location of nectar sources to their hive mates. Distance information is encoded in the duration of the waggle phase (von Frisch, 1967). During the waggle phase, the dancer produces trains of vibration pulses, which are detected by the follower bees via Johnston's organ located on the antennae. To uncover the neural mechanisms underlying the encoding of distance information in the waggle dance follower, we investigated morphology, physiology, and immunohistochemistry of interneurons arborizing in the primary auditory center of the honeybee ( Apis mellifera ). We identified major interneuron types, named DL-Int-1, DL-Int-2, and bilateral DL-dSEG-LP, that responded with different spiking patterns to vibration pulses applied to the antennae. Experimental and computational analyses suggest that inhibitory connection plays a role in encoding and processing the duration of vibration pulse trains in the primary auditory center of the honeybee. SIGNIFICANCE STATEMENT The waggle dance represents a form of symbolic communication used by honeybees to convey the location of food sources via species-specific sound. The brain mechanisms used to decipher this symbolic information are unknown. We examined interneurons in the honeybee primary auditory center and identified different neuron types with specific properties. The results of our computational analyses suggest that inhibitory connection plays a role in encoding waggle dance signals. Our results are critical for understanding how the honeybee deciphers information from the sound produced by the waggle dance and provide new insights regarding how common neural mechanisms are used by different species to achieve communication. Copyright © 2017 the authors 0270-6474/17/3710624-12$15.00/0.

Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

PubMed

Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

2018-01-05

Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value <0.05) that cannot be discovered by other machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

Periaqueductal gray glutamatergic, cannabinoid and vanilloid receptor interplay in defensive behavior and aversive memory formation.

PubMed

Back, Franklin P; Carobrez, Antonio P

2018-06-01

Stimulation of the midbrain periaqueductal gray matter (PAG) in humans elicits sensations of fear and impending terror, and mediates predator defensive responses in rodents. In rats, pharmacological stimulation of the dorsolateral portion of the PAG (dlPAG) with N-Methyl-d-Aspartate (NMDA) induces aversive conditioning that acts as an unconditioned stimulus (US). In the present work, we investigated the interplay between the vanilloid TRPV1 and cannabinoid CB1 receptors in the NMDA-dlPAG defensive response and in subsequent aversive learning. Rats were subjected to dlPAG NMDA infusion in an olfactory conditioned stimulus (CS) task allowing the evaluation of immediate and long-term defensive behavioral responses during CS presentation. The results indicated that an intermediate dose of NMDA (50 pmol) induced both immediate and long-term effects. A sub-effective dose of NMDA (25 pmol) was potentiated by the TRPV1 receptor agonist capsaicin (CAP, 1 nmol) and the CB1 receptor antagonist, AM251 (200 pmol). CAP (10 nmol) or the combination of CAP (1 nmol) and AM251 (200 pmol) induced long-term effects without increasing immediate defensive responses. The glutamate release inhibitor riluzole (2 or 4 nmol) and the AMPA/kainate receptor antagonist DNQX (2 or 4 nmol) potentiated the immediate effects but blocked the long-term effects. The results showed that immediate defensive responses rely on NMDA receptors, and aversive learning on the fine-tuning of TRPV1, CB1, metabotropic glutamate and AMPA receptors located in pre- and postsynaptic membranes. In conclusion, the activity of the dlPAG determines core affective aspects of aversive memory formation controlled by local TRPV1/CB1 balance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Root and Canal Morphology of Mandibular Molars in a Selected Iranian Population Using Cone-Beam Computed Tomography

PubMed Central

Madani, Zahra Sadat; Mehraban, Nika; Moudi, Ehsan; Bijani, Ali

2017-01-01

Introduction: The aim of this study was to evaluate the root canal morphology of mandibular first and second molars using cone-beam computed tomography (CBCT) in northern Iranian population and also to indicate the thinnest area around root canals. Methods and Materials: We evaluated CBCT images of 154 first molars and 147 second molars. By evaluating three axial, sagittal and coronal planes of each tooth we determined the number of root canals, prevalence of C-shaped Melton types, and prevalence of Vertucci configuration and inter orifice distance. Also the minimum wall thickness of root canals was determined by measuring buccal, lingual, distal and mesial wall thicknesses of each canal in levels with 2 mm intervals from apex to orifice. Results: Amongst 154 first mandibular molars, 149 (96.7%) had two roots, 3 (1.9%) had three roots and 2 (1.2%) had C-shaped root configuration. Of 147 second mandibular molars, 120 (81.6%) had two roots, 1 (0.6%) had three roots and 26 (17.6%) had C-shaped roots. There was no significant difference in the prevalence of Vertucci’s type between two genders. The most common configuration in mesial roots of first and second molars were type IV (57%-42.9%) and type II (31.5%-28%). Mesial and distal walls had the most frequency as the thinnest wall in all levels of root canals with mostly less than 1 mm thickness. In second molars the DB-DL inter orifice distance and in first molars the MB-ML distance were the minimum. MB-D in first molars had the maximum distance while ML-DL, MB-DB and ML-D had the same and maximum distance in second molars. Conclusion: Vertucci’s type IV and type I were the most prevalent configurations in mesial and distal roots of first and second mandibular molars and the thickness of thinnest area around the canals should be considered during endodontic treatments. PMID:28512476

Modified Regge calculus as an explanation of dark energy

NASA Astrophysics Data System (ADS)

Stuckey, W. M.; McDevitt, T. J.; Silberstein, M.

2012-03-01

Using the Regge calculus, we construct a Regge differential equation for the time evolution of the scale factor a(t) in the Einstein-de Sitter cosmology model (EdS). We propose two modifications to the Regge calculus approach: (1) we allow the graphical links on spatial hypersurfaces to be large, as in direct particle interaction when the interacting particles reside in different galaxies, and (2) we assume that luminosity distance DL is related to graphical proper distance Dp by the equation D_L = (1+z)\\sqrt{\\overrightarrow{D_p}\\cdot \\overrightarrow{D_p}}, where the inner product can differ from its usual trivial form. The modified Regge calculus model (MORC), EdS and ΛCDM are compared using the data from the Union2 Compilation, i.e. distance moduli and redshifts for type Ia supernovae. We find that a best fit line through log {\\big(\\frac{D_L}{{Gpc}}\\big)} versus log z gives a correlation of 0.9955 and a sum of squares error (SSE) of 1.95. By comparison, the best fit ΛCDM gives SSE = 1.79 using Ho = 69.2 km s-1 Mpc, ΩM = 0.29 and ΩΛ = 0.71. The best fit EdS gives SSE = 2.68 using Ho = 60.9 km s-1 Mpc. The best-fit MORC gives SSE = 1.77 and Ho = 73.9 km s-1 Mpc using R = A-1 = 8.38 Gcy and m = 1.71 × 1052 kg, where R is the current graphical proper distance between nodes, A-1 is the scaling factor from our non-trivial inner product, and m is the nodal mass. Thus, the MORC improves the EdS as well as ΛCDM in accounting for distance moduli and redshifts for type Ia supernovae without having to invoke accelerated expansion, i.e. there is no dark energy and the universe is always decelerating.

Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

ERIC Educational Resources Information Center

Akhmetova, Daniya Z.

2014-01-01

Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…

Distance Learning.

ERIC Educational Resources Information Center

Orey, Michael; Koenecke, Lynne; Snider, Richard C.; Perkins, Ross A.; Holmes, Glen A.; Lockee, Barbara B.; Moller, Leslie A.; Harvey, Douglas; Downs, Margaret; Godshalk, Veronica M.

2003-01-01

Contains four articles covering trends and issues on distance learning including: the experience of two learners learning via the Internet; a systematic approach to determining the scalability of a distance education program; identifying factors that affect learning community development and performance in asynchronous distance education; and…

46 CFR 10.412 - Distance and e-learning.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 1 2014-10-01 2014-10-01 false Distance and e-learning. 10.412 Section 10.412 Shipping... CREDENTIAL Training Courses and Programs § 10.412 Distance and e-learning. The Coast Guard may allow the training of mariners by means of distance learning and e-learning in accordance with the standards of...

Self-Regulated Learning Ability of Chinese Distance Learners

ERIC Educational Resources Information Center

Zhao, Hong; Chen, Li; Panda, Santosh

2014-01-01

This study reports on self-regulated learning (SRL) of Chinese distance learners by using a structured SRL scale. SRL of adult and lifelong learners is a well-researched area, though its application within distance education is a new area of investigation. Open and distance learning lean heavily on self-learning and self-learning resources, though…

Learning characteristics of veterinary technology students in a distance-education and an on-campus program.

PubMed

Varnhagen, Connie K; Wright, David L

2008-01-01

Distance-education programs have the potential to greatly increase the number of veterinary technicians. The demographic characteristics, readiness for independent and online learning, learning styles, and academic locus of control of a group of distance-education and on-campus veterinary technology students were examined. Distance-education students preferred independent learning and were more internally motivated to learn. Distance-education students with greater degrees of independence and internal motivation participated more fully, were more satisfied with their learning, and achieved higher grades. Students who preferred problem solving and active experimentation were particularly successful in distance education. These findings could have important implications for advising students interested in distance-education programs.

Removal of copper powder from aqueous solution by cementation using an agitated vessel.

PubMed

Amin, N K; El-Ashtouky, E-S Z; Abdelwahab, O

2014-01-01

The present study is concerned with the removal of copper powder from aqueous solution by cementation on a stationary disc placed inside an agitated vessel. The influence of several parameters on the rate of cementation, such as initial copper sulphate concentration, impeller rotational speed, presence of surfactant (Triton X-100), distance between the disc and the impeller, type of blade turbine and presence of baffles, has been investigated. The rate of cementation was found to increase with increasing impeller rotational speed and initial copper sulphate concentration. On the other hand, the rate decreases with increasing distance between the disc and the impeller. The rate of cementation was inhibited in solutions containing Triton X-100. Performance of a four-blade 90 degree turbine with regard to the rate of copper cementation was superior to the performance of a four-blade 45 degree pitched turbine. The present data can be correlated in terms of mass transfer coefficient of cementation as Sh = 0.905 Sc0.33 Re0.89 (d/l)0.41 (four-blade 90 degree turbine); Sh = 0.815 Sc0.33Re0.79 (d/l)0.47 (four-blade 45 degree pitched turbine), for the conditions 2035 < Sc < 2810 and 35,000 < Re < 179,000.

The significance of heterogeneity of evolving scales to transport in porous formations

NASA Astrophysics Data System (ADS)

Dagan, Gedeon

1994-12-01

Flow takes place in a heterogeneous formation of spatially variable conductivity, which is modeled as a stationary space random function. To model the variability at the regional scale, the formation is viewed as one of a two-dimensional, horizontal structure. A constant head gradient is applied on the formation boundary such that the flow is uniform in the mean. A plume of inert solute is injected at t = 0 in a volume V0. Under ergodic conditions the plume centroid moves with the constant, mean flow velocity U, and a longitudinal macrodispersion coefficient dL may be defined as half of the time rate of change of the plume second spatial moment with respect to the centroid. For a log-conductivity covariance CY of finite integral scale I, at first order in the variance σY2 and for a travel distance L = Ut ≫ I, dL → σY2UI and transport is coined as Fickian. Ergodicity of the moments is ensured if l ≫ I, where l is the initial plume scale. Some field observations have suggested that heterogeneity may be of evolving scales and that the macrodispersion coefficient may grow with L without reaching a constant limit (anomalous diffusion). To model such a behavior, previous studies have assumed that CY is stationary but of unbounded integral scale with CY ˜ arβ (-1 < β < 0) for large lag r. Under ergodic conditions, it was found that asymptotically dL ˜ aUL1+β, i.e., non-Fickian behavior and anomalous dispersion. The present study claims that an ergodic behavior is not possible for a given finite plume of initial size l, since the basic requirement that l ≫ I cannot be satisfied for CY of unbounded scale. For instance, the centroid does not move any more with U but is random (Figure 1), owing to the large-scale heterogeneity. In such a situation the actual effective dispersion coefficient DL is defined as half the rate of change of the mean second spatial moment with respect to the plume centroid in each realization. This is the accessible entity in a given experiment. We show that in contrast with dL, the behavior of DL is controlled by l and it has the Fickian limit DL ˜ aUl1+β (Figure 3). We also discuss the case in which Y is of stationary increments and is characterized by its variogram γy. Then U and dL can be defined only if γY is truncated (equivalently, an "infrared cutoff" is carried out in the spectrum of Y). However, for a bounded U it is shown that DL depends only on γY. Furthermore, for γY = arβ, DL ˜ aUl2Lβ-1; i.e., dispersion is Fickian for 0 < β < 1, whereas for 1 < β < 2, transport is non-Fickian. Since β < 2, DL cannot grow faster than L = Ut. This is in contrast with a recently proposed model (Neuman, 1990) in which the dispersion coefficient is independent of the plume size and it grows approximately like L1.5.

Joint learning of labels and distance metric.

PubMed

Liu, Bo; Wang, Meng; Hong, Richang; Zha, Zhengjun; Hua, Xian-Sheng

2010-06-01

Machine learning algorithms frequently suffer from the insufficiency of training data and the usage of inappropriate distance metric. In this paper, we propose a joint learning of labels and distance metric (JLLDM) approach, which is able to simultaneously address the two difficulties. In comparison with the existing semi-supervised learning and distance metric learning methods that focus only on label prediction or distance metric construction, the JLLDM algorithm optimizes the labels of unlabeled samples and a Mahalanobis distance metric in a unified scheme. The advantage of JLLDM is multifold: 1) the problem of training data insufficiency can be tackled; 2) a good distance metric can be constructed with only very few training samples; and 3) no radius parameter is needed since the algorithm automatically determines the scale of the metric. Extensive experiments are conducted to compare the JLLDM approach with different semi-supervised learning and distance metric learning methods, and empirical results demonstrate its effectiveness.

Distance and Face-to-Face Learning Culture and Values: A Conceptual Analysis

ERIC Educational Resources Information Center

Tejeda-Delgado, Carmen; Millan, Brett J.; Slate, John R.

2011-01-01

With distance learning increasing in popularity across the country and the world, a review of the extant literature as it relates to distance learning and face-to-face learning is warranted. In particular, this paper examined distance learning, including a historical overview, prevailing themes in past research, and studies relating the importance…

Neural Correlates of Three Promising Endophenotypes of Depression: Evidence from the EMBARC Study

PubMed Central

Webb, Christian A; Dillon, Daniel G; Pechtel, Pia; Goer, Franziska K; Murray, Laura; Huys, Quentin JM; Fava, Maurizio; McGrath, Patrick J; Weissman, Myrna; Parsey, Ramin; Kurian, Benji T; Adams, Phillip; Weyandt, Sarah; Trombello, Joseph M; Grannemann, Bruce; Cooper, Crystal M; Deldin, Patricia; Tenke, Craig; Trivedi, Madhukar; Bruder, Gerard; Pizzagalli, Diego A

2016-01-01

Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5–44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5–8 Hz) and alpha2 (10.5–12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities. PMID:26068725

Comparing deep learning models for population screening using chest radiography

NASA Astrophysics Data System (ADS)

Sivaramakrishnan, R.; Antani, Sameer; Candemir, Sema; Xue, Zhiyun; Abuya, Joseph; Kohli, Marc; Alderson, Philip; Thoma, George

2018-02-01

According to the World Health Organization (WHO), tuberculosis (TB) remains the most deadly infectious disease in the world. In a 2015 global annual TB report, 1.5 million TB related deaths were reported. The conditions worsened in 2016 with 1.7 million reported deaths and more than 10 million people infected with the disease. Analysis of frontal chest X-rays (CXR) is one of the most popular methods for initial TB screening, however, the method is impacted by the lack of experts for screening chest radiographs. Computer-aided diagnosis (CADx) tools have gained significance because they reduce the human burden in screening and diagnosis, particularly in countries that lack substantial radiology services. State-of-the-art CADx software typically is based on machine learning (ML) approaches that use hand-engineered features, demanding expertise in analyzing the input variances and accounting for the changes in size, background, angle, and position of the region of interest (ROI) on the underlying medical imagery. More automatic Deep Learning (DL) tools have demonstrated promising results in a wide range of ML applications. Convolutional Neural Networks (CNN), a class of DL models, have gained research prominence in image classification, detection, and localization tasks because they are highly scalable and deliver superior results with end-to-end feature extraction and classification. In this study, we evaluated the performance of CNN based DL models for population screening using frontal CXRs. The results demonstrate that pre-trained CNNs are a promising feature extracting tool for medical imagery including the automated diagnosis of TB from chest radiographs but emphasize the importance of large data sets for the most accurate classification.

Testing a dual-systems model of adolescent brain development using resting-state connectivity analyses.

PubMed

van Duijvenvoorde, A C K; Achterberg, M; Braams, B R; Peters, S; Crone, E A

2016-01-01

The current study aimed to test a dual-systems model of adolescent brain development by studying changes in intrinsic functional connectivity within and across networks typically associated with cognitive-control and affective-motivational processes. To this end, resting-state and task-related fMRI data were collected of 269 participants (ages 8-25). Resting-state analyses focused on seeds derived from task-related neural activation in the same participants: the dorsal lateral prefrontal cortex (dlPFC) from a cognitive rule-learning paradigm and the nucleus accumbens (NAcc) from a reward-paradigm. Whole-brain seed-based resting-state analyses showed an age-related increase in dlPFC connectivity with the caudate and thalamus, and an age-related decrease in connectivity with the (pre)motor cortex. nAcc connectivity showed a strengthening of connectivity with the dorsal anterior cingulate cortex (ACC) and subcortical structures such as the hippocampus, and a specific age-related decrease in connectivity with the ventral medial PFC (vmPFC). Behavioral measures from both functional paradigms correlated with resting-state connectivity strength with their respective seed. That is, age-related change in learning performance was mediated by connectivity between the dlPFC and thalamus, and age-related change in winning pleasure was mediated by connectivity between the nAcc and vmPFC. These patterns indicate (i) strengthening of connectivity between regions that support control and learning, (ii) more independent functioning of regions that support motor and control networks, and (iii) more independent functioning of regions that support motivation and valuation networks with age. These results are interpreted vis-à-vis a dual-systems model of adolescent brain development. Copyright © 2015. Published by Elsevier Inc.

Quantitative Structure – Property Relationship Modeling of Remote Liposome Loading Of Drugs

PubMed Central

Cern, Ahuva; Golbraikh, Alexander; Sedykh, Aleck; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2012-01-01

Remote loading of liposomes by trans-membrane gradients is used to achieve therapeutically efficacious intra-liposome concentrations of drugs. We have developed Quantitative Structure Property Relationship (QSPR) models of remote liposome loading for a dataset including 60 drugs studied in 366 loading experiments internally or elsewhere. Both experimental conditions and computed chemical descriptors were employed as independent variables to predict the initial drug/lipid ratio (D/L) required to achieve high loading efficiency. Both binary (to distinguish high vs. low initial D/L) and continuous (to predict real D/L values) models were generated using advanced machine learning approaches and five-fold external validation. The external prediction accuracy for binary models was as high as 91–96%; for continuous models the mean coefficient R2 for regression between predicted versus observed values was 0.76–0.79. We conclude that QSPR models can be used to identify candidate drugs expected to have high remote loading capacity while simultaneously optimizing the design of formulation experiments. PMID:22154932

International Perspectives of Distance Learning in Higher Education

ERIC Educational Resources Information Center

Moore, Joi L., Ed.; Benson, Angela D., Ed.

2012-01-01

This book, written by authors representing 12 countries and five continents, is a collection of international perspectives on distance learning and distance learning implementations in higher education. The perspectives are presented in the form of practical case studies of distance learning implementations, research studies on teaching and…

Internet-Based Distance Learning in Higher Education.

ERIC Educational Resources Information Center

Hofmann, Donald W.

2002-01-01

Suggests that the effectiveness of Internet-based distance learning has increased with its increased popularity. Looks at the differences between the effectiveness of Internet-based distance learning and traditional methods. Indicates that distance learning is more effective because of the necessity for students to become active learners.…

Distance Education and Distance Learning: Some Psychological Considerations.

ERIC Educational Resources Information Center

Cropley, Arthur J.; Kahl, Thomas N.

1983-01-01

Compares and contrasts distance education and face-to-face education in terms of selected psychological dimensions, i.e., organization and learning, motivation, learning and communication processes, didactic activities and materials, and evaluation and feedback. Psychological aspects of distance education that may be favorable to learning are also…

Evaluation of a distance-learning immunology and pathology module in a postgraduate biomedical science course.

PubMed

Ryan, M T; Mulholland, C W

2005-01-01

An electronic presentation of materials for a distance-learning immunology and pathology module from a postgraduate biomedical science course is evaluated. Two different electronic presentation formats for the delivery of the educational material to distance learners are assessed. Responses from users of this material highlighted a preference for a format that has a design tailored to distance learning. There was no significant difference in learning outcome between those taking the module on campus and by distance learning. This suggests that the prerequisites for entry, learning materials and direction given to the students studying by distance learning are adequate for these students to achieve the learning objectives outlined in the course. The evaluation also gave direction for areas within the (CAL) application that can be improved for future students.

Lead reduction of petrol and blood lead concentrations of athletes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maresky, L.S.; Kotze, T.J.V.W.; Grobler, S.R.

In 1984, it was determined that the blood of long-distance runners in South Africa contained unacceptably high concentrations of lead. Subsequently, the petrol lead level in South Africa was reduced from 0.8 g/l to 0.4 g/l. In view of this reduction, a follow-up investigation of its effect on the blood lead concentration of South African runners was undertaken. Blood lead samples were analyzed by graphite furnace atomic absorption spectrophotometry. The mean values of blood lead concentrations dropped from 52 to 13 {mu}g/dl and from 20 to 8.5 {mu}g/dl for the urban and rural trainers, respectively. A highly significant decrease inmore » blood lead levels was found and was mainly attributable to the reduction in the petrol lead levels. The blood lead results for rural trainers indicated that there still exists a certain degree of lead pollution in athletes from nonremote areas.« less

A Delphi Study on Collaborative Learning in Distance Education: The Faculty Perspective

ERIC Educational Resources Information Center

O'Neill, Susan; Scott, Murray; Conboy, Kieran

2011-01-01

This paper focuses on the factors that influence collaborative learning in distance education. Distance education has been around for many years and the use of collaborative learning techniques in distance education is becoming increasingly popular. Several studies have demonstrated the superiority of collaborative learning over traditional modes…

Distance Learning in Higher Education. CHEA Update Number 3.

ERIC Educational Resources Information Center

Council for Higher Education Accreditation, Washington, DC.

This report discusses issues related to distance learning in higher education. Section 1, "The Expanding Universe of Distance Learning," examines: data from a new national survey on higher education distance learning; Internet access in elementary and secondary schools; the 1999 national survey of information technology in higher…

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

Tidewater Community College Distance Learning Report.

ERIC Educational Resources Information Center

Tidewater Community Coll., Norfolk, VA.

This study of distance learning at Tidewater Community College (TCC) was conducted to determine enrollment patterns, retention, and success in distance learning courses and student perceptions. Distance learning was defined as students enrolled in one of three modes of course delivery: telecourse, online, and compressed video. The time frame for…

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

Distance Learning: A Way of Life-Long Learning

DTIC Science & Technology

2005-09-01

promise of future benefits. 15. SUBJECT TERMS training, educational technology , distributed learning , distance learning , collaboration, online instruction...knowledge." - Aristotle Introduction Modern learning technology assumes various names: distance learning , distributed training, computer-based...training, web-based learning , or advanced distributed learning . No matter the name, the basic concept is using computer technology for instruction with no

Deep Learning and Image Processing for Automated Crack Detection and Defect Measurement in Underground Structures

NASA Astrophysics Data System (ADS)

Panella, F.; Boehm, J.; Loo, Y.; Kaushik, A.; Gonzalez, D.

2018-05-01

This work presents the combination of Deep-Learning (DL) and image processing to produce an automated cracks recognition and defect measurement tool for civil structures. The authors focus on tunnel civil structures and survey and have developed an end to end tool for asset management of underground structures. In order to maintain the serviceability of tunnels, regular inspection is needed to assess their structural status. The traditional method of carrying out the survey is the visual inspection: simple, but slow and relatively expensive and the quality of the output depends on the ability and experience of the engineer as well as on the total workload (stress and tiredness may influence the ability to observe and record information). As a result of these issues, in the last decade there is the desire to automate the monitoring using new methods of inspection. The present paper has the goal of combining DL with traditional image processing to create a tool able to detect, locate and measure the structural defect.

Highly undersampled MR image reconstruction using an improved dual-dictionary learning method with self-adaptive dictionaries.

PubMed

Li, Jiansen; Song, Ying; Zhu, Zhen; Zhao, Jun

2017-05-01

Dual-dictionary learning (Dual-DL) method utilizes both a low-resolution dictionary and a high-resolution dictionary, which are co-trained for sparse coding and image updating, respectively. It can effectively exploit a priori knowledge regarding the typical structures, specific features, and local details of training sets images. The prior knowledge helps to improve the reconstruction quality greatly. This method has been successfully applied in magnetic resonance (MR) image reconstruction. However, it relies heavily on the training sets, and dictionaries are fixed and nonadaptive. In this research, we improve Dual-DL by using self-adaptive dictionaries. The low- and high-resolution dictionaries are updated correspondingly along with the image updating stage to ensure their self-adaptivity. The updated dictionaries incorporate both the prior information of the training sets and the test image directly. Both dictionaries feature improved adaptability. Experimental results demonstrate that the proposed method can efficiently and significantly improve the quality and robustness of MR image reconstruction.

Innovation in Open & Distance Learning: Successful Development of Online and Web-Based Learning.

ERIC Educational Resources Information Center

Lockwood, Fred, Ed.; Gooley, Anne, Ed.

This book contains 19 papers examining innovation in open and distance learning through development of online and World Wide Web-based learning. The following papers are included: "Innovation in Distributed Learning: Creating the Environment" (Fred Lockwood); "Innovation in Open and Distance Learning: Some Lessons from Experience…

Higher Education through Open and Distance Learning. World Review of Distance Education and Open Learning, Volume 1. A Commonwealth of Learning Series.

ERIC Educational Resources Information Center

Harry, Keith, Ed.

This book reports on the expansion of open and distance learning during the past decade, examining ways in which open and distance learning for higher education has responded to the needs of the new society, and summarizing the lessons of recent practice for policymakers and educators. After an introductory chapter, "Open and Distance…

Making Distance Learning E.R.O.T.I.C.: Applying Interpretation Principles to Distance Learning

ERIC Educational Resources Information Center

Ross, Anne; Siepen, Greg; O'Connor, Sue

2003-01-01

Distance learners are self-directed learners traditionally taught via study books, collections of readings, and exercises to test understanding of learning packages. Despite advances in e-Learning environments and computer-based teaching interfaces, distance learners still lack opportunities to participate in exercises and debates available to…

Accreditation and Assuring Quality in Distance Learning. CHEA Monograph Series, 2002.

ERIC Educational Resources Information Center

Council for Higher Education Accreditation, Washington, DC.

This report describes the scope and impact of distance learning on higher education and identifies the primary challenges that distance learning poses for accreditation. The responses of the accrediting community designed to assure quality in distance learning are outlined. Data from a variety of sources show that 5,655 institutions are accredited…

Distance Learning and Non-Formal Education: Existing Trends and New Possibilities of Distance Learning Experiences.

ERIC Educational Resources Information Center

Romi, Shlomo

2000-01-01

Reviews the characteristics of non-formal education as expressed in various academic-theoretical definitions, presents the links in this field to distance learning, and recommends future directions for exploring distance learning in non-formal education. Discusses the use of information and communication technology and considers problems with…

Testing the Distance-Duality Relation in the Rh = ct Universe

NASA Astrophysics Data System (ADS)

Hu, J.; Wang, F. Y.

2018-04-01

In this paper, we test the cosmic distance duality (CDD) relation using the luminosity distances from joint light-curve analysis (JLA) type Ia supernovae (SNe Ia) sample and angular diameter distance sample from galaxy clusters. The Rh = ct and ΛCDM models are considered. In order to compare the two models, we constrain the CCD relation and the SNe Ia light-curve parameters simultaneously. Considering the effects of Hubble constant, we find that η ≡ DA(1 + z)2/DL = 1 is valid at the 2σ confidence level in both models with H0 = 67.8 ± 0.9 km/s/Mpc. However, the CDD relation is valid at 3σ confidence level with H0 = 73.45 ± 1.66 km/s/Mpc. Using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), we find that the ΛCDM model is very strongly preferred over the Rh = ct model with these data sets for the CDD relation test.

Testing the distance-duality relation in the Rh = ct universe

NASA Astrophysics Data System (ADS)

Hu, J.; Wang, F. Y.

2018-07-01

In this paper, we test the cosmic distance-duality (CDD) relation using the luminosity distances from joint light-curve analysis Type Ia supernovae (SNe Ia) sample and angular diameter distance sample from galaxy clusters. The Rh = ct and Λ cold dark matter (CDM) models are considered. In order to compare the two models, we constrain the CDD relation and the SNe Ia light-curve parameters simultaneously. Considering the effects of Hubble constant, we find that η ≡ DA(1 + z)2/DL = 1 is valid at the 2σ confidence level in both models with H0= 67.8 ± 0.9 km -1s-1 Mpc. However, the CDD relation is valid at 3σ confidence level with H0= 73.45 ± 1.66 km -1s-1Mpc. Using the Akaike Information Criterion and the Bayesian Information Criterion, we find that the ΛCDM model is very stongly preferred over the Rh = ct model with these data sets for the CDD relation test.

The Leadership Roles of Distance Learning Administrators (DLAs) in Increasing Educational Value and Quality Perceptions

ERIC Educational Resources Information Center

McFarlane, Donovan A.

2011-01-01

This paper examines the leadership roles of distance learning administrators (DLAs) in light of the demand and need for value and quality in educational distance learning programs and schools. The author explores the development of distance learning using available and emerging technologies in relation to increased demand for education, training,…

Teaching and Learning at a Distance: What it Takes To Effectively Design, Deliver, and Evaluate Programs.

ERIC Educational Resources Information Center

Cyrs, Thomas E., Ed.; Menges, Robert J., Ed.; Svinicki, Marilla D., Ed.

1997-01-01

In this volume, experienced distance educators provide insights into new trends in computer-based teaching and learning in postsecondary education. The book is divided into four parts: (1) Issues and Trends; (2) Instructional Design Principles for Distance Learning; (3) Alternative Delivery Systems for Distance Learning; and (4) Administrative…

Facebook Mediated Interaction and Learning in Distance Learning at Makerere University

ERIC Educational Resources Information Center

Mayende, Godfrey; Muyinda, Paul Birevu; Isabwe, Ghislain Maurice Norbert; Walimbwa, Michael; Siminyu, Samuel Ndeda

2014-01-01

This paper reports on an investigation of the use of Facebook as a tool to mediate learning amongst distance learners at Makerere University, a dual-mode institution offering both conventional and distance learning programs. While conventional courses take 17 weeks in a semester, the distance learners come in for two residential sessions, each…

Distance Learning 2001: Proceedings of the Annual Conference on Distance Teaching & Learning (17th, Madison, Wisconsin, August 8-10, 2001).

ERIC Educational Resources Information Center

Wisconsin Univ. System, Madison.

This document contains 82 papers and 6 workshop presentations from a conference on distance teaching and learning. The following are among the papers included: "Examples and Tools for Building Web-Based Learning Experiences" (Steven A. Ackerman, Thomas Whittaker); "Online Testing in Distance Education" (Tricia Ahern);…

Distance Learning for Food Security and Rural Development: A Perspective from the United Nations Food and Agriculture Organization.

ERIC Educational Resources Information Center

McLean, Scott; Gasperini, Lavinia; Rudgard, Stephen

2002-01-01

The distance learning experiences of the United Nations Food and Agriculture Organization led to the following suggestions for applying distance learning strategies to the challenges of food security and rural development: use distance learning for the right reasons, be sensitive to context, use existing infrastructure, engage stakeholders, and…

Topics on Distance Learning Conference Proceedings (Hammond, Indiana, June 5-6, 2001).

ERIC Educational Resources Information Center

Purdue Univ., Hammond, IN. Calumet Campus.

The purpose of this conference was to focus attention on the increasing role of distance learning in academia and industry and to inform and educate the participants in several key aspects of distance learning. In addition, the conference spotlights the accomplishments of technology in education and showcases the many leaders in distance learning.…

The Evolution of Distance Learning: Technology-Mediated Interactive Learning.

ERIC Educational Resources Information Center

Dede, Christopher J.

1990-01-01

Summarizes a paper prepared for the Office of Technology Assessment (OTA) on the evolution of distance learning which begins by describing technological, the demographic, economic, political, and pedagogical forces involved. A new field is proposed called technology-mediated interactive learning (TMIL), which synthesizes distance learning,…

Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia.

PubMed

Morabito, Francesco Carlo; Campolo, Maurizio; Mammone, Nadia; Versaci, Mario; Franceschetti, Silvana; Tagliavini, Fabrizio; Sofia, Vito; Fatuzzo, Daniela; Gambardella, Antonio; Labate, Angelo; Mumoli, Laura; Tripodi, Giovanbattista Gaspare; Gasparini, Sara; Cianci, Vittoria; Sueri, Chiara; Ferlazzo, Edoardo; Aguglia, Umberto

2017-03-01

A novel technique of quantitative EEG for differentiating patients with early-stage Creutzfeldt-Jakob disease (CJD) from other forms of rapidly progressive dementia (RPD) is proposed. The discrimination is based on the extraction of suitable features from the time-frequency representation of the EEG signals through continuous wavelet transform (CWT). An average measure of complexity of the EEG signal obtained by permutation entropy (PE) is also included. The dimensionality of the feature space is reduced through a multilayer processing system based on the recently emerged deep learning (DL) concept. The DL processor includes a stacked auto-encoder, trained by unsupervised learning techniques, and a classifier whose parameters are determined in a supervised way by associating the known category labels to the reduced vector of high-level features generated by the previous processing blocks. The supervised learning step is carried out by using either support vector machines (SVM) or multilayer neural networks (MLP-NN). A subset of EEG from patients suffering from Alzheimer's Disease (AD) and healthy controls (HC) is considered for differentiating CJD patients. When fine-tuning the parameters of the global processing system by a supervised learning procedure, the proposed system is able to achieve an average accuracy of 89%, an average sensitivity of 92%, and an average specificity of 89% in differentiating CJD from RPD. Similar results are obtained for CJD versus AD and CJD versus HC.

A Conceptual Model for Effective Distance Learning in Higher Education

ERIC Educational Resources Information Center

Farajollahi, Mehran; Zare, Hosein; Hormozi, Mahmood; Sarmadi, Mohammad Reza; Zarifsanaee, Nahid

2010-01-01

The present research aims at presenting a conceptual model for effective distance learning in higher education. Findings of this research shows that an understanding of the technological capabilities and learning theories especially constructive theory and independent learning theory and communicative and interaction theory in Distance learning is…

Distance Learning: What's Holding Back This Boundless Delivery System?

ERIC Educational Resources Information Center

Bruder, Isabelle

1989-01-01

Discusses distance learning, identifies who distance learners may be, and examines issues involved in establishing distance learning systems. Topics discussed include teacher concerns, including job security and certification; curriculum concerns, including state and local requirements and cross-cultural issues; cooperative development,…

Case-based Learning in Microbiology: Observations from a North West Indian Medical College.

PubMed

Singhal, Anita

2017-12-01

Microbiology is usually taught by conventional lectures, and its retention and application is observed to be poor among medical graduates/practitioners. Introduction of case-based learning (CBL) in microbiology for second-year professional MBBS students. Students were divided into two groups of fifty each. Four clinical cases were used for CBL. One group had two CBL sessions whereas the other had didactic lectures (DLs) and then the groups were crossed over. Case scenario handouts were given to students a week before the session, and smaller groups were formed for discussions and presentations in CBL sessions. Posttest, in multiple choice questions format, was conducted in two phases: First, immediately after the completion of the four CBL and DL sessions, and second, 6 weeks after the first posttest. Student and faculty feedback was taken about CBL sessions. Hundred MBBS students of the fourth semester voluntarily participated in the CBL study. The CBL scores were significantly higher than DL session scores ( P = 0.015). This difference was more marked in scoring done after 6 weeks of session completion ( P < 0.001). Student reported satisfaction in being taught by CBL method in 5-point Likert scale feedback form. Faculty feedback was positive for CBL. CBL helped in retention of knowledge and its application better than DL in our observation. More sessions on commonly encountered case scenarios will be useful for students in recalling basic science knowledge in their later years as practitioners.

Evaluation of the impact of deep learning architectural components selection and dataset size on a medical imaging task

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Gros, Eric

2018-03-01

Deep Learning (DL) has been successfully applied in numerous fields fueled by increasing computational power and access to data. However, for medical imaging tasks, limited training set size is a common challenge when applying DL. This paper explores the applicability of DL to the task of classifying a single axial slice from a CT exam into one of six anatomy regions. A total of 29000 images selected from 223 CT exams were manually labeled for ground truth. An additional 54 exams were labeled and used as an independent test set. The network architecture developed for this application is composed of 6 convolutional layers and 2 fully connected layers with RELU non-linear activations between each layer. Max-pooling was used after every second convolutional layer, and a softmax layer was used at the end. Given this base architecture, the effect of inclusion of network architecture components such as Dropout and Batch Normalization on network performance and training is explored. The network performance as a function of training and validation set size is characterized by training each network architecture variation using 5,10,20,40,50 and 100% of the available training data. The performance comparison of the various network architectures was done for anatomy classification as well as two computer vision datasets. The anatomy classifier accuracy varied from 74.1% to 92.3% in this study depending on the training size and network layout used. Dropout layers improved the model accuracy for all training sizes.

Rethinking Lifelong Learning through Online Distance Learning in Chinese Educational Policies, Practices and Research

ERIC Educational Resources Information Center

Yang, Min

2008-01-01

This paper offers a critique of the Chinese philosophy of online distance learning as a means of building a lifelong learning society. Literature about lifelong learning and its implications for online distance learning is reviewed. Documents, reports and research papers are examined to explore the characteristics of the Chinese philosophy of…

Reliability of Maximal Strength Testing in Novice Weightlifters

NASA Technical Reports Server (NTRS)

Loehr, James A.; Lee, Stuart M. C.; Feiveson, Alan H.; Ploutz-Snyder, Lori L.

2009-01-01

The one repetition maximum (1RM) is a criterion measure of muscle strength. However, the reliability of 1RM testing in novice subjects has received little attention. Understanding this information is crucial to accurately interpret changes in muscle strength. To evaluate the test-retest reliability of a squat (SQ), heel raise (HR), and deadlift (DL) 1RM in novice subjects. Twenty healthy males (31 plus or minus 5 y, 179.1 plus or minus 6.1 cm, 81.4 plus or minus 10.6 kg) with no weight training experience in the previous six months participated in four 1RM testing sessions, with each session separated by 5-7 days. SQ and HR 1RM were conducted using a smith machine; DL 1RM was assessed using free weights. Session 1 was considered a familiarization and was not included in the statistical analyses. Repeated measures analysis of variance with Tukey fs post-hoc tests were used to detect between-session differences in 1RM (p.0.05). Test-retest reliability was evaluated by intraclass correlation coefficients (ICC). During Session 2, the SQ and DL 1RM (SQ: 90.2 }4.3, DL: 75.9 }3.3 kg) were less than Session 3 (SQ: 95.3 }4.1, DL: 81.5 plus or minus 3.5 kg) and Session 4 (SQ: 96.6 }4.0, DL: 82.4 }3.9 kg), but there were no differences between Session 3 and Session 4. HR 1RM measured during Session 2 (150.1 }3.7 kg) and Session 3 (152.5 }3.9 kg) were not different from one another, but both were less than Session 4 (157.5 }3.8 kg). The reliability (ICC) of 1RM measures for Sessions 2-4 were 0.88, 0.83, and 0.87, for SQ, HR, and DL, respectively. When considering only Sessions 3 and 4, the reliability was 0.93, 0.91, and 0.86 for SQ, HR, and DL, respectively. One familiarization session and 2 test sessions (for SQ and DL) were required to obtain excellent reliability (ICC greater than or equal to 0.90) in 1RM values with novice subjects. We were unable to attain this level of reliability following 3 HR testing sessions therefore additional sessions may be required to obtain an ICC of greater than or equal to 0.90. Future resistive exercise studies should consider the reliability of specific measures to ensure that changes in strength with training are attributable to training and not learning effects associated with 1RM testing.

Facilities Offered by the University of Ibadan (Nigeria) Distance Learning Centre towards Learners' Academic Goal--An Evaluation

ERIC Educational Resources Information Center

Adegbile, J. A.; Oyekanmi, J. O.

2011-01-01

Distance learners in the University of Ibadan, Nigeria unlike other distance learners of different parts of the world are faced with various educational, social and psychological problems associated with the code of distance learning. The facilities offered by the University of Ibadan distance learning centre towards the users' multifarious needs…

New Ways of Learning: Comparing the Effectiveness of Interactive Online Media in Distance Education with the European Textbook Tradition

ERIC Educational Resources Information Center

Krämer, Bernd J.; Neugebauer, Jonas; Magenheim, Johannes; Huppertz, Helga

2015-01-01

Although many innovations exploiting web technologies have been suggested in distance higher education, very little original research exists investigating the impact of web-based learning environments on distance students' learning processes and outcomes. To close this gap, four sets of data have been collected in a distance-learning course:…

Application of Distance Learning Technology to Strategic Education.

DTIC Science & Technology

1996-02-26

service or government agency. STRATEGY RESEARCH PROJECT APPLICATION OF DISTANCE LEARNING TECHNOLOGY TO STRATEGIC EDUCATION BY LIEUTENANT COLONEL...APPLICATION OF DISTANCE LEARNING TECHNOLOGY TO STRATEGIC EDUCATION by Lieutenant Colonel Greig W. Mitchell United States Army Commander David M...distance learning technology can also enhance the functions of research and public service. The purpose of research programs in higher education is

Community of inquiry model: advancing distance learning in nurse anesthesia education.

PubMed

Pecka, Shannon L; Kotcherlakota, Suhasini; Berger, Ann M

2014-06-01

The number of distance education courses offered by nurse anesthesia programs has increased substantially. Emerging distance learning trends must be researched to ensure high-quality education for student registered nurse anesthetists. However, research to examine distance learning has been hampered by a lack of theoretical models. This article introduces the Community of Inquiry model for use in nurse anesthesia education. This model has been used for more than a decade to guide and research distance learning in higher education. A major strength of this model learning. However, it lacks applicability to the development of higher order thinking for student registered nurse anesthetists. Thus, a new derived Community of Inquiry model was designed to improve these students' higher order thinking in distance learning. The derived model integrates Bloom's revised taxonomy into the original Community of Inquiry model and provides a means to design, evaluate, and research higher order thinking in nurse anesthesia distance education courses.

Occasional Papers in Open and Distance Learning, Number 18.

ERIC Educational Resources Information Center

Donnan, Peter, Ed.

Six papers examine innovations and trends in distance learning, frequently drawing upon empirical research or informal observations on distance learning students at Charles Sturt University (Australia). "On-Line Study Packages for Distance Education: Some Considerations of Conceptual Parameters" (Dirk M. R. Spennemann) discusses issues…

Tutors' Influence on Distance Language Students' Learning Motivation: Voices from Learners and Tutors

ERIC Educational Resources Information Center

Xiao, Junhong

2012-01-01

Teachers' influence on students' learning motivation is a well-researched topic. Nevertheless, the majority of such studies are situated in the conventional learning context despite the rapid growth of distance language learning. This study set out to investigate tutors' influence on students' learning motivation in the Chinese distance language…

Challenges Encountered by a Distance Learning Organisation

ERIC Educational Resources Information Center

Malik, Sangeeta

2012-01-01

Distance learning as the name indicates is a learning, learner gets from distant places. In this learning system, learner and educators are separated by space & time. Lots of distance learning organizations are spreading to meet the increased demand of current & future needs of adult education. The rapid spread of these organizations doesn't mean…

Challenges in Delivering Library Services for Distance Learning.

ERIC Educational Resources Information Center

Swaine, Cynthia Wright

The first section of this paper on library services for distance education discusses the status of distance learning in higher education. What distance learning means for libraries is addressed in the second section, including considerations related to diverse locations, agreements with participating institutions, delivery limitations, librarian…

Distance Learning: Information Access and Services for Virtual Users.

ERIC Educational Resources Information Center

Iyer, Hemalata, Ed.

This volume centers broadly on information support services for distance education. The articles in this book can be categorized into two areas: access to information resources for distance learners, and studies of distance learning programs. Contents include: "The Challenges and Benefits of Asynchronous Learning Networks" (Daphne…

Interactive Distance Learning in Connecticut.

ERIC Educational Resources Information Center

Pietras, Jesse John; Murphy, Robert J.

This paper provides an overview of distance learning activities in Connecticut and addresses the feasibility of such activities. Distance education programs have evolved from the one dimensional electronic mail systems to the use of sophisticated digital fiber networks. The Middlesex Distance Learning Consortium has developed a long-range plan to…

Gastric Emptying During Exercise: Effects of Acute Heat Stress, Acclimation and Hypohydration,

DTIC Science & Technology

1987-10-01

dehydrate to 5% of their baseline body weight. Subjects achieving a weight reduction greater than 5% were allowed an appropriate amount of fruit juices ...Saltin. Factors limiting gastric emptying during rest and exercise. J. Appl . Physiol. 37: 679-683, 1974. 3. Costill, D.L., W. F. Krammer, and A. Fisher...Fluid ingestion during distance running. Arch. Environ. Health. 21: 520-525, 1970. 4. Crane, R.K. The physiology of the intestinal absorption of sugars

Educational technology integration and distance learning in respiratory care: practices and attitudes.

PubMed

Hopper, Keith B; Johns, Carol L

2007-11-01

Educational technologies have had an important role in respiratory care. Distance learning via postal correspondence has been used extensively in respiratory care, and Internet-based distance learning is now used in the training of respiratory therapists (RTs), clinical continuing education, and in baccalaureate degree and higher programs for RTs and educators. To describe the current scope of respiratory care educational technology integration, including distance learning. To investigate online research potential in respiratory care. A probabilistic online survey of United States respiratory care program directors was conducted on educational technology practices and attitudes, including distance learning. A parallel exploratory study of United States respiratory care managers was conducted. One-hundred seventy-seven (53%) program directors participated. One-hundred twenty-eight respiratory care managers participated. For instructional purposes, the respiratory care programs heavily use office-productivity software, the Internet, e-mail, and commercial respiratory care content-based computer-based instruction. The programs use, or would use, online resources provided by text publishers, but there is a paucity. Many program directors reported that their faculty use personal digital assistants (PDAs), often in instructional roles. 74.6% of the programs offer no fully online courses, but 61.0% reported at least one course delivered partially online. The managers considered continuing education via online technologies appropriate, but one third reported that they have not/will not hire RTs trained via distance learning. Neither group considered fully online courses a good match for RT training, nor did they consider training via distance learning of comparable quality to on-campus programs. Both groups rated baccalaureate and higher degrees via distance learning higher if the program included face-to-face instruction. Online distance-learning participatory experience generally improved attitudes toward distance learning. There was a good match between manager RT expectations in office-productivity software and program instructional practices. Educational technologies have an important role in respiratory care. Online distance learning for baccalaureate and higher degrees in respiratory care is promising. Online distance learning in respiratory care must include face-to-face instruction. Distance-learning deployment in respiratory care will require resources. A follow-up probabilistic survey of United States respiratory care managers is needed. Online surveys conducted for respiratory care are promising, but neither less expensive nor easier than conventional means.

A Path-Analytic Study of Some Correlates Predicting Persistence and Student's Success in Distance Education in Nigeria

ERIC Educational Resources Information Center

Ojokheta, K. O.

2010-01-01

This study examined the influence of some predictors in the enhancement of persistence and students success in distance education in the two most recognised and respected distance learning institutions in Nigeria--the Distance Learning Institute (DLI) of University of Lagos and Distance Learning Centre of University of Ibadan. The need for this…

The Challenges of Quality Assurance in a Distance Learning Environment. A Report and Recommendations in a Series on Distance Learning Policy Issues.

ERIC Educational Resources Information Center

Southern Regional Education Board, Atlanta, GA.

The Distance Learning Policy Laboratory of the Southern Regional Education Board (SREB) and many states and regional organizations are coming to a consensus on the principles and goals that should shape distance learning policies. In the case of quality assurance, the SREB believes there are four guiding principles that states should follow.…

Using Finance Policy To Reduce Barriers to Distance Learning. A Report and Recommendations in a Series on Distance Learning Policy Issues.

ERIC Educational Resources Information Center

Southern Regional Education Board, Atlanta, GA.

This study explored the ways in which state and system financing policies can advance the use of distance learning technologies and the goals outlined in other reports by the Distance Learning Policy Laboratory more effectively. The subcommittee on finance that examined the issue approached the task by establishing a framework that considered:…

The Role of Gender in Distance Learning: A Meta-Analytic Review of Gender Differences in Academic Performance and Self-Efficacy in Distance Learning

ERIC Educational Resources Information Center

Perkowski, Justine

2013-01-01

This meta-analytic review was performed to determine the relationship between gender and two constructs measuring success in distance learning--academic performance and self-efficacy--with a particular interest in identifying whether females or males have an advantage in distance learning environments. Data from 15 studies resulted in 18 effect…

Can you go the distance? Attending the virtual classroom.

PubMed

Bigony, Lorraine

2010-01-01

Distance learning via the World Wide Web offers convenience and flexibility. Online education connects nurses geographically in a manner that the traditional face-to-face learning environment lacks. Delivered in both a synchronous (real time interaction) or asynchronous (delayed interaction) format, distance programs continue to provide nurses with choice, especially in the pursuit of advanced degrees. This article explores the pros and cons of distance education, in addition to the most popular platform used in distance learning today, the Blackboard Academic Suite. Characteristics of the potential enrollee to ensure a successful distance education experience are also discussed. Distance nursing programs are here to stay. Although rigorous, the ease of accessibility makes distance learning a viable alternative for busy nurses.

Effectiveness of Mobile Learning in Distance Education

ERIC Educational Resources Information Center

Yousuf, Muhammad Imran

2007-01-01

The main aim of this research is to better understand and measure students' attitudes and perceptions towards the importance of mobile learning in distance education. Results of this survey clearly indicate that facilitating mobile learning can improve the entire distance education by enhancing ways of communication among distance learners, tutors…

A Journey to Legitimacy: The Historical Development of Distance Education through Technology

ERIC Educational Resources Information Center

Casey, Denise M.

2008-01-01

This article demonstrates the parallels between development of technology and the increased acceptance of distance learning. First, definitions of distance learning are provided. Second, the history of distance learning and its use of technological innovations are presented. Third, an overview of the academic institutions that are offering…

Using Multimedia for Distance Learning in Adult, Career, and Vocational Education. Information Series No. 362.

ERIC Educational Resources Information Center

Stammen, Ronald M.

This paper explores how educators are using multimedia for distance learning, beginning with definitions of the concepts of multimedia, hypermedia, hypertext, distance education and distance learning. Three types of telecommunications technologies are described: multimedia with broadcast television, multimedia with interactive video (television),…

Open Classroom: Distance Learning In and Out of Schools. Open and Distance Learning Series.

ERIC Educational Resources Information Center

Bradley, Jo, Ed.

This collection of essays, which is separated into 4 sections, concerns open and distance learning at school level, or grades K-12. The first section, "The Knowledge Society," includes the following chapters: "Classroom Open Learning: A Case of Old Wine in New Bottles?" (Jenkins); "Living and Learning in the Information…

Quantitative structure-property relationship modeling of remote liposome loading of drugs.

PubMed

Cern, Ahuva; Golbraikh, Alexander; Sedykh, Aleck; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2012-06-10

Remote loading of liposomes by trans-membrane gradients is used to achieve therapeutically efficacious intra-liposome concentrations of drugs. We have developed Quantitative Structure Property Relationship (QSPR) models of remote liposome loading for a data set including 60 drugs studied in 366 loading experiments internally or elsewhere. Both experimental conditions and computed chemical descriptors were employed as independent variables to predict the initial drug/lipid ratio (D/L) required to achieve high loading efficiency. Both binary (to distinguish high vs. low initial D/L) and continuous (to predict real D/L values) models were generated using advanced machine learning approaches and 5-fold external validation. The external prediction accuracy for binary models was as high as 91-96%; for continuous models the mean coefficient R(2) for regression between predicted versus observed values was 0.76-0.79. We conclude that QSPR models can be used to identify candidate drugs expected to have high remote loading capacity while simultaneously optimizing the design of formulation experiments. Copyright © 2011 Elsevier B.V. All rights reserved.

Supporting Distance Learners for Collaborative Problem Solving.

ERIC Educational Resources Information Center

Verdejo, M. F.; Barros, B.; Abad, M. T.

This paper describes a computer-supported environment designed to facilitate distance learning through collaborative problem-solving. The goal is to encourage distance learning students to work together, in order to promote both learning of collaboration and learning through collaboration. Collaboration is defined as working together on a common…

Distance Learning in British Universities: Is It Possible?

ERIC Educational Resources Information Center

Lentell, Helen

2012-01-01

The wider context (political and economic) for developing sustainable distance learning in UK universities is encouraging and new learning technologies promise much improved products and services. But conventional campus-based universities struggle to build and/or expand sustainable distance learning provision. This article identifies the core…

Using Satellite Classes to Optimise Access to and Participation in First-Year Business Management: A Case at an Open and Distance-Learning University in South Africa

ERIC Educational Resources Information Center

Swanepoel, Elana; De Beer, Andreas; Muller, Helene

2009-01-01

We investigated the effect of satellite classes as a component of blended learning, to enhance student performance of the Business Management I and Management I students at an open and distance-learning university. We discuss the evolution of distance education, the interactivities promoted by open and distance learning and the concept of blended…

Blood lead level and types of aviation fuel in aircraft maintenance crew.

PubMed

Park, Won-Ju; Gu, Hye-Min; Lee, Suk-Ho

2013-10-01

This study inquired into any significant difference in blood lead levels (BLLs) among aircraft maintenance crews at the air-bases, each with a different aviation fuel in use, and confirmed an environmental impact of leaded aviation gasoline (AVGAS). This study included a total of 256 male aircraft maintenance personnel, among whom 105 used only AVGAS as their aviation fuel, while 151 used only jet propellant 8 (JP-8), a kerosene variety. BLLs were measured and the data on related factors were obtained. The arithmetic and geometric means of BLLs of the personnel at the airbases that used only AVGAS were 4.20 microg x dl(-1) and 4.01 microg x dl(-1) and that used only JP-8 were 3.79 microg x dl(-1) and 3.57 microg x dl(-1), respectively. The BLLs of the maintenance crew of the main workspace that was located within a 200-m distance from the runway were higher than those of the main workspace that was located 200 m or farther from the runway. The longer the work hours in the runway or the longer the work duration, the higher the BLLs of the maintenance crew. This investigation exposed the fact that a body's BLL could be increased by AVGAS emissions through the examination of aircraft maintenance crew. This result is in agreement with results of previous studies that suggest proximity to an airport may be associated with elevated BLLs for adults and children. Collectively, the results of the current study and previous research suggest that long-duration inhabitation and/or activities in close proximity to an air facility should be limited given that lead poses known health risks.

Exploring Cloud Computing for Distance Learning

ERIC Educational Resources Information Center

He, Wu; Cernusca, Dan; Abdous, M'hammed

2011-01-01

The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

Cooperative Learning at a Distance: An Experiment with Wikis

ERIC Educational Resources Information Center

Campbell, Katherine; Ellingson, Dee Ann

2010-01-01

The merits of incorporating group work into learning environments are well established. Online classes and other distance learning settings, however, can make it challenging to introduce traditional group projects. Wikis use technology to facilitate group work in distance learning settings. Wikis allow individuals in different locations to…

Topics on Distance Learning: Proceedings 2000 (Hammond, Indiana, June 6-7, 2000).

ERIC Educational Resources Information Center

Purdue Univ., Hammond, IN. Calumet Campus.

This proceedings of the 2000 Topics on Distance Learning conference contains summaries of the following presentations: "The ABC's of Distance Learning via Full Motion Video" (Liz Owens); "Assessing the Cost of Technology in Instruction Using an Economic Model" (Joseph Lovrinic); "Collaboration Lessons Learned from the…

A Begrudging, Recalcitrant Academic Observes What She's Learning: Distance Learning in Leadership Formation

ERIC Educational Resources Information Center

Hess, Lisa M.

2014-01-01

Neither advocacy nor condemnation of distance learning, this essay offers observations and critical reflection on four years' longitudinal engagement with distance learning pedagogies for formation in higher theological education. Instead, readers are invited to curiosity, communal-institutional discernment, and intense ambivalence.…

Map for Decision Making in Operating Distance Learning System--Research Results.

ERIC Educational Resources Information Center

Offir, Baruch

2000-01-01

Examines decision-making aspects of the introduction of distance learning into university instruction and learning based on experiences in Israel. Discusses the introduction of information technology into the classroom; examines teacher/student interactions; and suggests a model for introducing distance learning that focuses on the role of the…

Greeting You Online: Selecting Web-Based Conferencing Tools for Instruction in E-Learning Mode

ERIC Educational Resources Information Center

Li, Judy

2014-01-01

Academic distance learning programs have gained popularity and added to the demand for online library services. Librarians are now conducting instruction for distance learning students beyond their traditional work. Technology advancements have enhanced the delivery mode in distance learning across academic disciplines. Online conference tools…

Blended Learning in Distance Education: Sri Lankan Perspective

ERIC Educational Resources Information Center

Liyanagunawardena, T. R.; Adams, A. A.; Rassool, N.; Williams, S. A.

2014-01-01

The purpose of this paper is to explore the implementation of online learning in distance educational delivery at Yellow Fields University (pseudonymous) in Sri Lanka. The implementation of online distance education at the University included the use of blended learning. The policy initiative to introduce online for distance education in Sri Lanka…

Transactional Distance and Second Life: The Effects of Video Game Experience

ERIC Educational Resources Information Center

Atkinson, Mark

2013-01-01

As a subset of distance education, online learning takes place primarily in learning management systems through asynchronous interaction, that can cause transactional distance between instructor and learners. This study investigated how transactional distance may be affected by the use of Second Life, a 3-D virtual world, as a learning environment…

From Add-On to Mainstream: Applying Distance Learning Models for ALL Students

ERIC Educational Resources Information Center

Zai, Robert, III.; Wesley, Threasa L.

2013-01-01

The use of distance learning technology has allowed Northern Kentucky University's W. Frank Steely Library to remove traditional boundaries between both distance and on-campus students. An emerging model that applies these distance learning methodologies to all students has proven effective for enhancing reference and instructional services. This…

E-Learning and Distance Education in Nigeria

ERIC Educational Resources Information Center

Ajadi, Timothy Olugbenga; Salawu, Ibrahim Olatunde; Adeoye, Femi Adetunji

2008-01-01

This paper discusses the relevance of e-learning in the position of distance education in Nigeria. It commences by discussing the meaning of e-learning and distance education. It also discusses the historical background of distance education in Nigeria as well as the operations of National Open University of Nigeria (NOUN) as the first federal…

Implications of Online Learning for the Conceptual Development and Practice of Distance Education

ERIC Educational Resources Information Center

Garrison, Randy

2009-01-01

The purpose of this article is to examine the foundational principles and practices of distance education for the purpose of understanding recent developments in the areas of online and blended learning. It is argued that mainstream distance education has not embraced the full collaborative potential of online learning. Distance education…

Measuring Self-Regulation in Self-Paced Open and Distance Learning Environments

ERIC Educational Resources Information Center

Kocdar, Serpil; Karadeniz, Abdulkadir; Bozkurt, Aras; Buyuk, Koksal

2018-01-01

Previous studies have described many scales for measuring self-regulation; however, no scale has been developed specifically for self-paced open and distance learning environments. Therefore, the aim of this study is to develop a scale for determining the self-regulated learning skills of distance learners in selfpaced open and distance learning…

Mobile Distance Learning with PDAs: Development and Testing of Pedagogical and System Solutions Supporting Mobile Distance Learners

ERIC Educational Resources Information Center

Rekkedal, Torstein; Dye, Aleksander

2007-01-01

The article discusses basic teaching-learning philosophies and experiences from the development and testing of mobile learning integrated with the online distance education system at NKI (Norwegian Knowledge Institute) Distance Education. The article builds on experiences from three European Union (EU) supported "Leonardo da Vinci"…

Collaborative distance learning: Developing an online learning community

NASA Astrophysics Data System (ADS)

Stoytcheva, Maria

2017-12-01

The method of collaborative distance learning has been applied for years in a number of distance learning courses, but they are relatively few in foreign language learning. The context of this research is a hybrid distance learning of French for specific purposes, delivered through the platform UNIV-RcT (Strasbourg University), which combines collaborative activities for the realization of a common problem-solving task online. The study focuses on a couple of aspects: on-line interactions carried out in small, tutored groups and the process of community building online. By analyzing the learner's perceptions of community and collaborative learning, we have tried to understand the process of building and maintenance of online learning community and to see to what extent the collaborative distance learning contribute to the development of the competence expectations at the end of the course. The analysis of the results allows us to distinguish the advantages and limitations of this type of e-learning and thus evaluate their pertinence.

Effects of help-seeking in a blended high school Biology class

NASA Astrophysics Data System (ADS)

Deguzman, Paolo

Distance learning provides an opportunity for students to learn valuable information through technology and interactive media. Distance learning additionally offers educational institutions the flexibility of synchronous and asynchronous instruction while increasing enrollment and lowering cost. However, distance education has not been well documented within the context of urban high schools. Distance learning may allow high school students to understand material at an individualized pace for either enrichment or remediation. A successful high school student who participates in distance learning should exhibit high self regulatory skills. However, most urban high school students have not been exposed to distance learning and should be introduced to proper self regulatory strategies that should increase the likelihood of understanding the material. To help facilitate a move into distance learning, a blended distance learning model, the combination of distance learning and traditional learning, will be used. According to O'Neil's (in preparation) revised problem solving model, self regulation is a component of problem solving. Within the Blended Biology course, urban high school students will be trained in help-seeking strategies to further their understanding of genetics and Punnett Square problem solving. This study investigated the effects of help-seeking in a blended high school Biology course. The main study consisted of a help-seeking group (n=55) and a control group (n=53). Both the help-seeking group and the control group were taught by one teacher for two weeks. The help-seeking group had access to Blended Biology with Help-Seeking while the control group only had access to Blended Biology. The main study used a pretest and posttest to measure Genetics Content Understanding, Punnett Square Problem Solving, Adaptive Help-Seeking, Maladaptive Help-Seeking, and Self Regulation. The analysis showed no significant difference in any of the measures in terms of help seeking. However, blended distance learning appeared to work as posttest means increased significantly from the pretest means. Future studies should consider the method of communication for help-seeking and help-giving within a high school distance learning context. Further studies should consider developing instruments to measure the difference in knowing when help is needed versus active choice.

A Critical Examination of the Teaching Methodologies Pertaining to Distance Learning in Geographic Education: Andragogy in an Adult Online Certificate Program

ERIC Educational Resources Information Center

Schultz, Richard B.

2012-01-01

Differences between student audiences are an important aspect not only of traditional learning in higher education, but also in the distance learning environment. Facilitators of distance learning coursework must be cognizant of the differences which adult students bring to the classroom and their varying expectations and reasons for learning.…

Machine learning enhanced optical distance sensor

NASA Astrophysics Data System (ADS)

Amin, M. Junaid; Riza, N. A.

2018-01-01

Presented for the first time is a machine learning enhanced optical distance sensor. The distance sensor is based on our previously demonstrated distance measurement technique that uses an Electronically Controlled Variable Focus Lens (ECVFL) with a laser source to illuminate a target plane with a controlled optical beam spot. This spot with varying spot sizes is viewed by an off-axis camera and the spot size data is processed to compute the distance. In particular, proposed and demonstrated in this paper is the use of a regularized polynomial regression based supervised machine learning algorithm to enhance the accuracy of the operational sensor. The algorithm uses the acquired features and corresponding labels that are the actual target distance values to train a machine learning model. The optimized training model is trained over a 1000 mm (or 1 m) experimental target distance range. Using the machine learning algorithm produces a training set and testing set distance measurement errors of <0.8 mm and <2.2 mm, respectively. The test measurement error is at least a factor of 4 improvement over our prior sensor demonstration without the use of machine learning. Applications for the proposed sensor include industrial scenario distance sensing where target material specific training models can be generated to realize low <1% measurement error distance measurements.

E-learning in Type 1 Medical Universities of Iran

ERIC Educational Resources Information Center

Rokni, Mohammad Bagher

2005-01-01

Nowadays the Internet is the technological pedestal of organization in the information society and one of the main applications that the Internet offers is the Digital Library (DL). Each society, especially those that claim training of the public, predictably need implementation and endorsement these systems. The time of chalk and board is passed…

Separable Neural Mechanisms Contribute to Feedback Processing in a Rule-Learning Task

ERIC Educational Resources Information Center

Zanolie, K.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

2008-01-01

To adjust performance appropriately to environmental demands, it is important to monitor ongoing action and process performance feedback for possible errors. In this study, we used fMRI to test whether medial prefrontal cortex (PFC)/anterior cingulate cortex (ACC) and dorsolateral (DL) PFC have different roles in feedback processing. Twenty adults…

Distance Learning With NASA Lewis Research Center's Learning Technologies Project

NASA Technical Reports Server (NTRS)

Petersen, Ruth

1998-01-01

The NASA Lewis Research Center's Learning Technologies Project (LTP) has responded to requests from local school district technology coordinators to provide content for videoconferencing workshops. Over the past year we have offered three teacher professional development workshops that showcase NASA Lewis-developed educational products and NASA educational Internet sites. In order to determine the direction of our involvement with distance learning, the LTP staff conducted a survey of 500 U.S. schools. We received responses from 72 schools that either currently use distance learning or will be using distance learning in 98-99 school year. The results of the survey are summarized in the article. In addition, the article provides information on distance learners, distance learning technologies, and the NASA Lewis LTP videoconferencing workshops. The LTP staff will continue to offer teacher development workshops through videoconferencing during the 98-99 school year. We hope to add workshops on new educational products as they are developed at NASA Lewis.

Learning styles and preferences for live and distance education: an example of a specialisation course in epidemiology.

PubMed

Groenwold, Rolf H H; Knol, Mirjam J

2013-07-02

Distance learning through the internet is increasingly popular in higher education. However, it is unknown how participants in epidemiology courses value live vs. distance education. All participants of a 5-day specialisation course in epidemiology were asked to keep a diary on the number of hours they spent on course activities (both live and distance education). Attendance was not compulsory during the course and participants were therefore also asked for the reasons to attend live education (lectures and practicals). In addition, the relation between participants' learning styles (Index of Learning Styles) and their participation in live and distance education was studied. All 54 (100%) participants in the course completed the questionnaire on attendance and 46 (85%) completed the questionnaire on learning styles. The number of hours attending live education was negatively correlated with the number of hours going studying distance learning materials (Pearson correlation -0.5; p < 0.001). The most important reasons to attend live education was to stay focused during lectures (50%), and to ask questions during practicals (50%). A lack of time was the most important reason not to attend lectures (52%) or practicals (61%). Learning styles were not association with the number of hours spent on live or distance education. Distance learning may play an important role in epidemiology courses, since it allows participants to study whenever and wherever they prefer, which provides the opportunity to combine courses with clinical duties. An important requirement for distance learning education appears to be the possibility to ask questions and to interact with instructors.

Assessing the Applicability of 3D Holographic Technology as an Enhanced Technology for Distance Learning

ERIC Educational Resources Information Center

Kalansooriya, Pradeep; Marasinghe, Ashu; Bandara, K. M. D. N.

2015-01-01

Distance learning has provided an excellent platform for students in geographically remote locations while enabling them to learn at their own pace and convenience. A number of technologies are currently being utilized to conceptualize, design, enhance and foster distance learning. Teleconferences, electronic field trips, podcasts, webinars, video…

Automated Categorization Scheme for Digital Libraries in Distance Learning: A Pattern Recognition Approach

ERIC Educational Resources Information Center

Gunal, Serkan

2008-01-01

Digital libraries play a crucial role in distance learning. Nowadays, they are one of the fundamental information sources for the students enrolled in this learning system. These libraries contain huge amount of instructional data (text, audio and video) offered by the distance learning program. Organization of the digital libraries is…

Distance Learning for Mobile Internet Users

ERIC Educational Resources Information Center

Necat, Beran

2007-01-01

This paper provides an overview on the current state of art in the field of Distance learning for mobile users. It mentions a large range of technologies, services and approaches that may be used to bring distance learning to mobile internet users. These technologies are supposed to considerably increase innovative e-learning solutions for the…

Connecting Multiple Intelligences through Open and Distance Learning: Going towards a Collective Intelligence?

ERIC Educational Resources Information Center

Medeiros Vieira, Leandro Mauricio; Ferasso, Marcos; Schröeder, Christine da Silva

2014-01-01

This theoretical essay is a learning approach reflexion on Howard Gardner's Theory of Multiple Intelligences and the possibilities provided by the education model known as open and distance learning. Open and distance learning can revolutionize traditional pedagogical practice, meeting the needs of those who have different forms of cognitive…

Vocational Education Distance Learning Delivery System. Final Report.

ERIC Educational Resources Information Center

Hardy, Darcy Walsh

A project was conducted to identify criteria and procedures for using a distance learning delivery system at the University of Texas TeleLearning Center to teach Health Occupations II to high school seniors. Another objective was expanding the current distance learning program for health occupations to include between 15 and 20 school districts.…

The Impact of Student Motivation on Participation and Academic Performance in Distance Learning

ERIC Educational Resources Information Center

Pittman, Candice Nicole

2013-01-01

This study investigated the impact of motivation on students' participation and academic performance in distance learning. Distance learning continues to grow in popularity as more and more students enroll in distance education courses. These courses require more responsibility on the part of the student. Some students are unaware of the amount of…

Distance learning perspectives.

PubMed

Pandza, Haris; Masic, Izet

2013-01-01

The development of modern technology and the Internet has enabled the explosive growth of distance learning. distance learning is a process that is increasingly present in the world. This is the field of education focused on educating students who are not physically present in the traditional classrooms or student's campus. described as a process where the source of information is separated from the students in space and time. If there are situations that require the physical presence of students, such as when a student is required to physically attend the exam, this is called a hybrid form of distance learning. This technology is increasingly used worldwide. The Internet has become the main communication channel for the development of distance learning.

Open and Distance Learning Today. Routledge Studies in Distance Education Series.

ERIC Educational Resources Information Center

Lockwood, Fred, Ed.

This book contains the following papers on open and distance learning today: "Preface" (Daniel); "Big Bang Theory in Distance Education" (Hawkridge); "Practical Agenda for Theorists of Distance Education" (Perraton); "Trends, Directions and Needs: A View from Developing Countries" (Koul); "American…

GLADE: A Galaxy Catalogue for Multi-Messenger Searches in the Advanced Gravitational-Wave Detector Era

NASA Astrophysics Data System (ADS)

Dálya, G.; Galgóczi, G.; Dobos, L.; Frei, Z.; Heng, I. S.; Macas, R.; Messenger, C.; Raffai, P.; de Souza, R. S.

2018-06-01

We introduce a value-added full-sky catalogue of galaxies, named as Galaxy List for the Advanced Detector Era, or GLADE. The purpose of this catalogue is to (i) help identifications of host candidates for gravitational-wave events, (ii) support target selections for electromagnetic follow-up observations of gravitational-wave candidates, (iii) provide input data on the matter distribution of the local universe for astrophysical or cosmological simulations, and (iv) help identifications of host candidates for poorly localised electromagnetic transients, such as gamma-ray bursts observed with the InterPlanetary Network. Both being potential hosts of astrophysical sources of gravitational waves, GLADE includes inactive and active galaxies as well. GLADE was constructed by cross-matching and combining data from five separate (but not independent) astronomical catalogues: GWGC, 2MPZ, 2MASS XSC, HyperLEDA and SDSS-DR12Q. GLADE is complete up to d_L=37^{+3}_{-4} Mpc in terms of the cumulative B-band luminosity of galaxies within luminosity distance dL, and contains all of the brightest galaxies giving half of the total B-band luminosity up to dL = 91 Mpc. As B-band luminosity is expected to be a tracer of binary neutron star mergers (currently the prime targets of joint GW+EM detections), our completeness measures can be used as estimations of completeness for containing all binary neutron star merger hosts in the local universe.

Transactional Distance as a Predictor of Perceived Learner Satisfaction in Distance Learning Courses: A Case Study of Bachelor of Education Arts Program, University of Nairobi, Kenya

ERIC Educational Resources Information Center

Mbwesa, Joyce Kanini

2014-01-01

There is a long history of study and recognition of the critical role of interaction in supporting and even defining distance education. Interaction has been identified as key to the success of distance learning. It is key in fostering, supporting and engaging in the learning process. Moore (1989) posits that the physical distance that exists in…

Real-time ultrasound transducer localization in fluoroscopy images by transfer learning from synthetic training data.

PubMed

Heimann, Tobias; Mountney, Peter; John, Matthias; Ionasec, Razvan

2014-12-01

The fusion of image data from trans-esophageal echography (TEE) and X-ray fluoroscopy is attracting increasing interest in minimally-invasive treatment of structural heart disease. In order to calculate the needed transformation between both imaging systems, we employ a discriminative learning (DL) based approach to localize the TEE transducer in X-ray images. The successful application of DL methods is strongly dependent on the available training data, which entails three challenges: (1) the transducer can move with six degrees of freedom meaning it requires a large number of images to represent its appearance, (2) manual labeling is time consuming, and (3) manual labeling has inherent errors. This paper proposes to generate the required training data automatically from a single volumetric image of the transducer. In order to adapt this system to real X-ray data, we use unlabeled fluoroscopy images to estimate differences in feature space density and correct covariate shift by instance weighting. Two approaches for instance weighting, probabilistic classification and Kullback-Leibler importance estimation (KLIEP), are evaluated for different stages of the proposed DL pipeline. An analysis on more than 1900 images reveals that our approach reduces detection failures from 7.3% in cross validation on the test set to zero and improves the localization error from 1.5 to 0.8mm. Due to the automatic generation of training data, the proposed system is highly flexible and can be adapted to any medical device with minimal efforts. Copyright © 2014 Elsevier B.V. All rights reserved.

Testing the limits of long-distance learning: Learning beyond a three-segment window

PubMed Central

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones since long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ('sh') and triggered a suffix that was either [−su] or [−∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. PMID:22303815

Comparison between project-based learning and discovery learning toward students' metacognitive strategies on global warming concept

NASA Astrophysics Data System (ADS)

Tumewu, Widya Anjelia; Wulan, Ana Ratna; Sanjaya, Yayan

2017-05-01

The purpose of this study was to know comparing the effectiveness of learning using Project-based learning (PjBL) and Discovery Learning (DL) toward students metacognitive strategies on global warming concept. A quasi-experimental research design with a The Matching-Only Pretest-Posttest Control Group Design was used in this study. The subjects were students of two classes 7th grade of one of junior high school in Bandung City, West Java of 2015/2016 academic year. The study was conducted on two experimental class, that were project-based learning treatment on the experimental class I and discovery learning treatment was done on the experimental class II. The data was collected through questionnaire to know students metacognitive strategies. The statistical analysis showed that there were statistically significant differences in students metacognitive strategies between project-based learning and discovery learning.

Facilitating Distance Education.

ERIC Educational Resources Information Center

Rossman, Mark H., Ed.; Rossman, Maxine E., Ed.

1995-01-01

This collection of articles on distance learning reflects the perspectives and concerns of the learner and the facilitator of learning in distance education setting. Eight chapters are included: (1) "The Evolution and Advantages of Distance Education" (John E. Cantelon) traces the history of distance education and demonstrates how it transcends…

Distance Learning '99. Proceedings of the Annual Conference on Distance Teaching and Learning (15th, Madison, Wisconsin, August 4-6, 1999).

ERIC Educational Resources Information Center

Wisconsin Univ. System, Madison.

This document contains 71 papers and 11 workshop presentations on distance teaching and learning from a conference on educational research. The following are among the papers included: "Bridging Distances and Differences" (Nancy Anderson); "The Role of Site Directors in Faculty and Student Success" (Edith M. Barnett, Jeanie P.…

What's the Difference, Still? A Follow-Up Review of the Quantitative Research Methodology in Distance Learning

ERIC Educational Resources Information Center

Randolph, Justus

2005-01-01

A high quality review of the distance learning literature from 1992-1999 concluded that most of the research on distance learning had serious methodological flaws. This paper presents the results of a small-scale replication of that review. From three leading distance education journals, a sample of 66 articles was categorized by study type and…

A Comparative Study of Student Satisfaction Level in Distance Learning and Live Classroom at Higher Education Level

ERIC Educational Resources Information Center

Mahmood, Azhar; Mahmood, Sheikh Tariq; Malik, Allah Bakhsh

2012-01-01

The technology has embraced the innovative learning methodologies. Distance Learning has taken the place of traditional face-to-face educational environment. The purpose of this study was to compare the level of student satisfaction of graduate distance learning educational psychology course to a traditional classroom educational psychology course…

Effectiveness of Computer-Based Educational Technology in Distance Learning: A Review of the Literature.

ERIC Educational Resources Information Center

Lesh, Steven G.; Rampp, Lary C.

Learning at a distance has been on the fringe of educational acceptance since the first correspondence course was delivered through the mail system in return for academic credit. As distance learning has matured, elements of enhanced instructional design and advances in educational technology have migrated this medium of learning closer to the…

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2012 CFR

2012-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2013 CFR

2013-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

Distance Learning and the Music Teacher: Before Signing Up for a Distance-Learning Program, It Is Essential to Learn as much about the Program as Possible

ERIC Educational Resources Information Center

Sherbon, James W.; Kish, David L.

2005-01-01

Most music teachers today are accustomed to teaching and learning practices that have undergone little change throughout many decades. Face-to-face instruction in music education has been the norm at all levels, although elements of technology and distance learning have filtered into their personal and professional lives, often in small and…

Adaptive distance metric learning for diffusion tensor image segmentation.

PubMed

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

PubMed Central

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

Learning styles and preferences for live and distance education: an example of a specialisation course in epidemiology

PubMed Central

2013-01-01

Background Distance learning through the internet is increasingly popular in higher education. However, it is unknown how participants in epidemiology courses value live vs. distance education. Methods All participants of a 5-day specialisation course in epidemiology were asked to keep a diary on the number of hours they spent on course activities (both live and distance education). Attendance was not compulsory during the course and participants were therefore also asked for the reasons to attend live education (lectures and practicals). In addition, the relation between participants’ learning styles (Index of Learning Styles) and their participation in live and distance education was studied. Results All 54 (100%) participants in the course completed the questionnaire on attendance and 46 (85%) completed the questionnaire on learning styles. The number of hours attending live education was negatively correlated with the number of hours going studying distance learning materials (Pearson correlation −0.5; p < 0.001). The most important reasons to attend live education was to stay focused during lectures (50%), and to ask questions during practicals (50%). A lack of time was the most important reason not to attend lectures (52%) or practicals (61%). Learning styles were not association with the number of hours spent on live or distance education. Conclusion Distance learning may play an important role in epidemiology courses, since it allows participants to study whenever and wherever they prefer, which provides the opportunity to combine courses with clinical duties. An important requirement for distance learning education appears to be the possibility to ask questions and to interact with instructors. PMID:23819522

Trend of E-Learning: The Service Mashup

ERIC Educational Resources Information Center

Yen, Neil Y.; Shih, Timothy K.; Jin, Qun; Hsu, Hui-Huang; Chao, Louis R.

2010-01-01

With the improvement of internet technologies and multimedia resources, traditional learning has been replaced by distance learning, web-based learning or others' e-learning learning styles. According to distance learning, there are many research organizations and companies who make efforts in developing the relevant systems. But they lack…

Future Directions in Distance Learning and Communication Technologies

ERIC Educational Resources Information Center

Shih, Timothy; Hung, Jason

2007-01-01

Future Directions in Distance Learning and Communication Technologies presents theoretical studies and practical solutions for engineers, educational professionals, and graduate students in the research areas of e-learning, distance education, and instructional design. This book provides readers with cutting-edge solutions and research directions…

A Review of Two Distance Learning Books [book review].

ERIC Educational Resources Information Center

Koszalka, Tiffany A.; Spector, J. Michael

2003-01-01

Reviews two books that are representative of the substantive books aimed at those who wish to design effective distance learning. Together these books provide a reasonably complete perspective on how to design effective distance learning. They have many strengths, and few weaknesses. (SLD)

Neuroanatomy of the vmPFC and dlPFC predicts individual differences in cognitive regulation during dietary self-control across regulation strategies.

PubMed

Schmidt, Liane; Tusche, Anita; Manoharan, Nicolas; Hutcherson, Cendri; Hare, Todd; Plassmann, Hilke

2018-06-04

Making healthy food choices is challenging for many people. Individuals differ greatly in their ability to follow health goals in the face of temptation, but it is unclear what underlies such differences. Using voxel-based morphometry (VBM), we investigated in healthy humans (i.e., men and women) links between structural variation in gray matter volume and individuals' level of success in shifting toward healthier food choices. We combined MRI and choice data into a joint dataset by pooling across three independent studies that employed a task prompting participants to explicitly focus on the healthiness of food items before making their food choices. Within this dataset, we found that individual differences in gray matter volume in the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) predicted regulatory success. We extended and confirmed these initial findings by predicting regulatory success out of sample and across tasks in a second dataset requiring participants to apply a different regulation strategy that entailed distancing from cravings for unhealthy, appetitive foods. Our findings suggest that neuroanatomical markers in the vmPFC and dlPFC generalized to different forms of dietary regulation strategies across participant groups. They provide novel evidence that structural differences in neuroanatomy of two key regions for valuation and its control, the vmPFC and dlPFC, predict an individual's ability to exert control in dietary choices. SIGNIFICANCE STATEMENT Dieting involves regulating food choices in order to eat healthier foods and fewer unhealthy foods. People differ dramatically in their ability to achieve or maintain this regulation, but it is unclear why. Here, we show that individuals with more gray matter volume in the dorsolateral and ventromedial prefrontal cortex are better at exercising dietary self-control. This relationship was observed across four different studies examining two different forms of dietary self-regulation, suggesting that neuroanatomical differences in the vmPFC and dlPFC may represent a general marker for self-control abilities. These results identify candidate neuroanatomical markers for dieting success and failure, and suggest potential targets for therapies aimed at preventing or treating obesity and related eating disorders. Copyright © 2018 the authors.

Globalization, Information and Communication Technologies (ICTs) and Open/Distance Learning in Nigeria: Trends, Issues and Solution

ERIC Educational Resources Information Center

Olusola, Akande Joshua; Alaba, Sofowora Olaniyi

2011-01-01

The main thrust of this paper is to discuss the development of open and distance education in Nigeria and the major manifestations of the use of information and communication technologies (ICTs) in education in open and distance learning. This study further discusses the importance and use of ICTs in open and distance learning in making education…

Blending Face-to-Face and Distance Learning Methods in Adult and Career-Technical Education. Practice Application Brief No. 23.

ERIC Educational Resources Information Center

Wonacott, Michael E.

Both face-to-face and distance learning methods are currently being used in adult education and career and technical education. In theory, the advantages of face-to-face and distance learning methods complement each other. In practice, however, both face-to-face and information and communications technology (ICT)-based distance programs often rely…

Problem based learning with scaffolding technique on geometry

NASA Astrophysics Data System (ADS)

Bayuningsih, A. S.; Usodo, B.; Subanti, S.

2018-05-01

Geometry as one of the branches of mathematics has an important role in the study of mathematics. This research aims to explore the effectiveness of Problem Based Learning (PBL) with scaffolding technique viewed from self-regulation learning toward students’ achievement learning in mathematics. The research data obtained through mathematics learning achievement test and self-regulated learning (SRL) questionnaire. This research employed quasi-experimental research. The subjects of this research are students of the junior high school in Banyumas Central Java. The result of the research showed that problem-based learning model with scaffolding technique is more effective to generate students’ mathematics learning achievement than direct learning (DL). This is because in PBL model students are more able to think actively and creatively. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.

Dental hygiene students' perceptions of distance learning: do they change over time?

PubMed

Sledge, Rhonda; Vuk, Jasna; Long, Susan

2014-02-01

The University of Arkansas for Medical Sciences dental hygiene program established a distant site where the didactic curriculum was broadcast via interactive video from the main campus to the distant site, supplemented with on-line learning via Blackboard. This study compared the perceptions of students towards distance learning as they progressed through the 21 month curriculum. Specifically, the study sought to answer the following questions: Is there a difference in the initial perceptions of students on the main campus and at the distant site toward distance learning? Do students' perceptions change over time with exposure to synchronous distance learning over the course of the curriculum? All 39 subjects were women between the ages of 20 and 35 years. Of the 39 subjects, 37 were Caucasian and 2 were African-American. A 15-question Likert scale survey was administered at 4 different periods during the 21 month program to compare changes in perceptions toward distance learning as students progressed through the program. An independent sample t-test and ANOVA were utilized for statistical analysis. At the beginning of the program, independent samples t-test revealed that students at the main campus (n=34) perceived statistically significantly higher effectiveness of distance learning than students at the distant site (n=5). Repeated measures of ANOVA revealed that perceptions of students at the main campus on effectiveness and advantages of distance learning statistically significantly decreased whereas perceptions of students at distant site statistically significantly increased over time. Distance learning in the dental hygiene program was discussed, and replication of the study with larger samples of students was recommended.

Exploring Differences between Self-Regulated Learning Strategies of High and Low Achievers in Open Distance Learning

ERIC Educational Resources Information Center

Geduld, Bernadette

2016-01-01

Open distance students differ in their preparedness for higher education studies. Students who are less self-regulated risk failure and drop out in the challenging milieu of open distance learning. In this study, the differences between the application of self-regulated learning strategies by low and high achievers were explored. A multi-method…

e-Learning for Expanding Distance Education in Tertiary Level in Bangladesh: Problems and Progress

ERIC Educational Resources Information Center

Al-Masum, Md. Abdullah; Chowdhury, Saiful Islam

2013-01-01

E-learning has broadly become an important enabler to promote distance education (DE) and lifelong learning in most of the developed countries, but in Bangladesh it is still a new successful progressive system for the learning communities. Distance education is thought to be introduced as an effective way of educating people of all sections in…

Learner Agency in Language Learning: The Story of a Distance Learner of EFL in China

ERIC Educational Resources Information Center

Xiao, Junhong

2014-01-01

Learner agency plays a key role in self-regulated learning. Yet, there is a paucity of research into its role in the distance learning context. Using reflective narratives written by a distance learner of English in China, this longitudinal case study aims to investigate the ways in which learner agency mediates the language learning in the…

Cross-Language Correlates in Phonological Awareness and Naming Speed: Evidence from Deep and Shallow Orthographies

ERIC Educational Resources Information Center

Pae, Hye Kyeong; Sevcik, Rose A.; Morris, Robin D.

2010-01-01

Phonological awareness (PA) and rapid automatised naming (RAN) skills in relation to reading acquisition were examined using two languages, one with a deep orthography (English) and the other with a shallow orthography (Korean). Participants were 50 Korean American children who spoke English as a dominant language (DL) and were learning to read…

Reducing the distance: equity issues in distance learning in public education

NASA Astrophysics Data System (ADS)

Campbell, Patricia B.; Storo, Jennifer

1996-12-01

Distance learning and educational equity both began with an emphasis on access, on providing underserved students with an increased access to education. Today definitions of equity have gone beyond simple access to include equal or equivalent treatment and outcomes while definitions of underserved students have expanded to include girls, children of color, children with limited English proficiency and children with disabilities. At the same time the definition of distance learning has expanded to include new technologies, new audiences and new roles. Based on these new definitions and roles, the article raises a number of equity challenges for distance learning educators centering around who is taught, what is taught and how the teaching is done. To answer these challenges, a series of recommendations are suggested that educators can implement to make distance learning a leader in increasing educational equity for all students. The time to act is now.

The use of multimodal strategies for distance education in the GRECCs.

PubMed

Kresevic, Denise; Burant, Christopher; Denton, Jennifer; Heath, Barbara; Kypriotakis, George

2011-01-01

The Department of Veterans Affairs (VA) has found distance education to be particularly valuable as a means to disseminate information to large numbers of busy learners in geographically diverse settings. Specifically, Geriatric Research, Education and Clinical Centers (GRECCs) of the VA have used various forms of distance learning to provide geriatrics-focused education to diverse health care providers. Such formats allow programs to be available to audiences regardless of distance or time. Although the distance-learning format has clear benefits, there are also some barriers that have hindered its wider adoption, including technical difficulties and ease of use. Organizers of distance education programs are challenged to overcome these barriers to provide a quality learning experience for the audience. The GRECCs will likely continue to be leaders in exploring innovative distance-learning strategies to accomplish their mission of quality geriatric education.

Designing Instruction for the Distance Learner

ERIC Educational Resources Information Center

Asunda, Paul A.

2010-01-01

A changing education landscape, diverse learner needs and technological advancements make this the perfect time for online and distance learning. Distance learning is increasingly becoming a preferred means for individuals to gain access to education and job preparation opportunities; this meets the public's learning needs "and" that of an…

Instructor and Student Attitudes Toward Distance Learning.

ERIC Educational Resources Information Center

Inman, Elliot; Kerwin, Michael; Mayes, Larry

1999-01-01

Discusses data collected from 11 distance-learning classes. The instructors were willing to teach distance-learning classes again, but said the courses were of equal or lesser quality than traditional classes. The 334 students surveyed were highly satisfied with the courses and instructors. Contains 17 references. (TGO)

Testing the limits of long-distance learning: learning beyond a three-segment window.

PubMed

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones because long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant-harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ("sh") and triggered a suffix that was either [-su] or [-∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. Copyright © 2012 Cognitive Science Society, Inc.

Practice Makes Learning.

ERIC Educational Resources Information Center

Neill, Judy

This paper focuses on how people learn to help educators design curriculum that will enable students to successfully complete a distance learning class. Up-front organization, clear communication about performance expectations, outcome driven assessment, and imaginative learning strategies are critical to successful distance learning.…

Developing Distance Learning Courses in a "Traditional" University.

ERIC Educational Resources Information Center

Lawton, Sally; Barnes, Richard

1998-01-01

Comparison of distance learning that was developed with a business-planning approach (market research, cost-benefit analysis, feasibility study, strategic marketing) with one that did not use these techniques showed that business planning ensures that distance-learning courses are not viewed as a "cheap" option. The method identifies…

Designing, Developing and Implementing WWW-Based Distance Learning.

ERIC Educational Resources Information Center

Riley, Peter C.

The rapid advancement of communication technologies is resulting in a wide array of design and development choices for distance learning projects. The 58th Special Operations Wing at Kirtland Air Force Base, New Mexico, is developing a prototype distance learning project designed to serve geographically separated learner populations. Project staff…

Development of a Framework for Guiding Interaction Design in Distance Learning

ERIC Educational Resources Information Center

Li, Wei

2015-01-01

As one of the most critical elements in distance learning, interaction has been identified empirically as increasing learner motivation, satisfaction, participation, communication, and achievement. Fostering pedagogically effective interaction is a major challenge for educators in distance learning. In response to this challenge, the goal of this…

An Investigation of Teaching Strategy in the Distance Learning Mathematics Classroom

ERIC Educational Resources Information Center

DePriter, Tiffany

2013-01-01

Distance learning has become increasingly popular among higher learning institutions, and more academic disciplines, such as mathematics, are now being offered at a distance. This experimental study investigated whether an objectivist-based teaching strategy or a constructivist-based teaching strategy yields greater achievement scores for adult…

Language Distance Learning for the Digital Generation

ERIC Educational Resources Information Center

Duran-Cerda, Dolores

2010-01-01

The purpose of this article was to shed light on the potential of distance learning to overcome challenges in distance, space, time, and human and economic resources that limit access to language learning opportunities in cultural, literary, historical, geographical, and cross-cultural frames. Language and literature educators collectively have…

Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach

ERIC Educational Resources Information Center

Hassan, Moshood Ayinde

2011-01-01

The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…

The Distance Learning of Foreign Languages: A Research Agenda

ERIC Educational Resources Information Center

White, Cynthia

2014-01-01

Research into the distance learning of languages is now established as a significant avenue of enquiry in language teaching, with evident research trajectories in several domains. This article selects and analyses significant areas of investigation in distance language learning and teaching to identify new and emerging gaps, along with research…

Distance Learning in Scientific and Professional Fields of Communication (Interdisciplinary Approach)

ERIC Educational Resources Information Center

Skorikova, Tatyana Petrovna; Khromova, Sergey Sergeevich; Dneprovskaya, Natalia Vitalievna

2016-01-01

Modern level of informational technologies development allows the authors of educational courses to decrease their dependence from technical specialists and to independently develop distance-learning courses and their separate online components, which require special methodical learning. The aim of present study is to develop a distance-learning…

Evaluation of Hybrid and Distance Education Learning Environments in Spain

ERIC Educational Resources Information Center

Ferrer-Cascales, Rosario; Walker, Scott L.; Reig-Ferrer, Abilio; Fernandez-Pascual, Maria Dolores; Albaladejo-Blazquez, Natalia

2011-01-01

This article describes the adaptation and validation of the "Distance Education Learning Environments Survey" (DELES) for use in investigating the qualities found in distance and hybrid education psycho-social learning environments in Spain. As Europe moves toward post-secondary student mobility, equanimity in access to higher education,…

Effects of Distance Learning on Learning Effectiveness

ERIC Educational Resources Information Center

Liu, Hong-Cheng; Yen, Jih-Rong

2014-01-01

The development of computers in the past two decades has resulted in the changes of education in enterprises and schools. The advance of computer hardware and platforms allow colleges generally applying distance courses to instruction that both Ministry of Education and colleges have paid attention to the development of Distance Learning. To…

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

Nursing Distance Learning Course Comparison of Assignments and Examination Scores

ERIC Educational Resources Information Center

Mundine, Jennifer

2016-01-01

Nursing programs have embraced distance learning in their curricula, but discussion is ongoing about course assignments and grading criteria to increase examination scores in nursing distance learning courses. Because course examinations are a predictor of success on the postgraduate licensing examination (NCLEX-RN), the purpose of this study was…

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

Virtual Bioinformatics Distance Learning Suite

ERIC Educational Resources Information Center

Tolvanen, Martti; Vihinen, Mauno

2004-01-01

Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…

Costing Distance Education and Open Learning in Sub-Saharan Africa: Working Group on Distance Education and Open Learning-- A Survey of Policy and Practice. Final Report

ERIC Educational Resources Information Center

Commonwealth of Learning, 2004

2004-01-01

Ideological arguments are made for open learning, economic ones for distance education. If it can produce similar results to those of conventional education at a lower cost, then distance education has a powerful appeal. With increasing demand for access to educational opportunities at all levels, and often decreasing budgets in real terms for…

Strategy for a Sustained Quality Delivery Mode of ODL Programmes for Massive Enrollments and E-Learning: The Case for Zimbabwe Open University

ERIC Educational Resources Information Center

Kabanda, Gabriel

2014-01-01

The market dynamics in distance education has precipitated phenomenal growth opportunities in enrollments and e-learning. The purpose of the paper was to develop a strategy for sustained quality delivery mode of distance education progammes that precipitate massive enrollments and e-learning in an open and distance learning (ODL) institution using…

Integration of an OWL-DL knowledge base with an EHR prototype and providing customized information.

PubMed

Jing, Xia; Kay, Stephen; Marley, Tom; Hardiker, Nicholas R

2014-09-01

When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledge is often an important contribution to their ability to make more informed decisions. In this paper we describe a method by which an external, formal representation of clinical and molecular genetic knowledge can be integrated into an EHR such that customized knowledge can be delivered to clinicians in a context-appropriate manner.Web Ontology Language-Description Logic (OWL-DL) is a formal knowledge representation language that is widely used for creating, organizing and managing biomedical knowledge through the use of explicit definitions, consistent structure and a computer-processable format, particularly in biomedical fields. In this paper we describe: 1) integration of an OWL-DL knowledge base with a standards-based EHR prototype, 2) presentation of customized information from the knowledge base via the EHR interface, and 3) lessons learned via the process. The integration was achieved through a combination of manual and automatic methods. Our method has advantages for scaling up to and maintaining knowledge bases of any size, with the goal of assisting clinicians and other EHR users in making better informed health care decisions.

Assessing Learning Styles among Students with and without Learning Disabilities at a Distance-Learning University

ERIC Educational Resources Information Center

Heiman, Tali

2006-01-01

Differences in the learning styles of students with and without learning disabilities (LD) at a distance-learning university were examined. Two hundred and twelve students answered self-report questionnaires on their learning styles. Results revealed that students with LD preferred to use more stepwise processing, including memorizing and…

E-Learning in Malaysia: Moving forward in Open Distance Learning

ERIC Educational Resources Information Center

Abas, Zoraini Wati

2009-01-01

Many higher education institutions have embarked on e-learning as a means to support their learning and teaching activities. In distance learning institutions, e-learning has enabled them to reach out to students dispersed over a wide geographical area, locally and internationally. In some countries, e-learning has also given students the…

E-Learning and Technologies for Open Distance Learning in Management Accounting

ERIC Educational Resources Information Center

Kashora, Trust; van der Poll, Huibrecht M.; van der Poll, John A.

2016-01-01

This research develops a knowledge acquisition and construction framework for e-learning for Management Accounting students at the University of South Africa, an Open Distance Learning institution which utilises e-learning. E-learning refers to the use of electronic applications and processes for learning, including the transfer of skills and…

The Future of Learning: From eLearning to mLearning.

ERIC Educational Resources Information Center

Keegan, Desmond

The future of electronic learning was explored in an analysis that viewed the provision of learning at a distance as a continuum and traced the evolution from distance learning to electronic learning to mobile learning in Europe and elsewhere. Special attention was paid to the following topics: (1) the impact of the industrial revolution, the…

New Definitions for New Higher Education Institutions

ERIC Educational Resources Information Center

Meyer, Katrina A.

2009-01-01

New terms were exploding early in the development of distance learning and virtual universities. Distance learning, online learning, e-learning, and distributed learning were applied to the various new forms of learning using online or Web-based materials and processes. However, largely thanks to the immediate popularity of the Western Governors'…

Solving the Credit Assignment Problem With the Prefrontal Cortex

PubMed Central

Stolyarova, Alexandra

2018-01-01

In naturalistic multi-cue and multi-step learning tasks, where outcomes of behavior are delayed in time, discovering which choices are responsible for rewards can present a challenge, known as the credit assignment problem. In this review, I summarize recent work that highlighted a critical role for the prefrontal cortex (PFC) in assigning credit where it is due in tasks where only a few of the multitude of cues or choices are relevant to the final outcome of behavior. Collectively, these investigations have provided compelling support for specialized roles of the orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal (dlPFC) cortices in contingent learning. However, recent work has similarly revealed shared contributions and emphasized rich and heterogeneous response properties of neurons in these brain regions. Such functional overlap is not surprising given the complexity of reciprocal projections spanning the PFC. In the concluding section, I overview the evidence suggesting that the OFC, ACC and dlPFC communicate extensively, sharing the information about presented options, executed decisions and received rewards, which enables them to assign credit for outcomes to choices on which they are contingent. This account suggests that lesion or inactivation/inhibition experiments targeting a localized PFC subregion will be insufficient to gain a fine-grained understanding of credit assignment during learning and instead poses refined questions for future research, shifting the focus from focal manipulations to experimental techniques targeting cortico-cortical projections. PMID:29636659

Behavioral contagion during learning about another agent’s risk-preferences acts on the neural representation of decision-risk

PubMed Central

Suzuki, Shinsuke; Jensen, Emily L. S.; Bossaerts, Peter; O’Doherty, John P.

2016-01-01

Our attitude toward risk plays a crucial role in influencing our everyday decision-making. Despite its importance, little is known about how human risk-preference can be modulated by observing risky behavior in other agents at either the behavioral or the neural level. Using fMRI combined with computational modeling of behavioral data, we show that human risk-preference can be systematically altered by the act of observing and learning from others’ risk-related decisions. The contagion is driven specifically by brain regions involved in the assessment of risk: the behavioral shift is implemented via a neural representation of risk in the caudate nucleus, whereas the representations of other decision-related variables such as expected value are not affected. Furthermore, we uncover neural computations underlying learning about others’ risk-preferences and describe how these signals interact with the neural representation of risk in the caudate. Updating of the belief about others’ preferences is associated with neural activity in the dorsolateral prefrontal cortex (dlPFC). Functional coupling between the dlPFC and the caudate correlates with the degree of susceptibility to the contagion effect, suggesting that a frontal–subcortical loop, the so-called dorsolateral prefrontal–striatal circuit, underlies the modulation of risk-preference. Taken together, these findings provide a mechanistic account for how observation of others’ risky behavior can modulate an individual’s own risk-preference. PMID:27001826

Integrating E-Learning into the Workplace.

ERIC Educational Resources Information Center

Harun, Mohd Hishamuddin

2001-01-01

Discussion of electronic learning and knowledge management in the workplace focuses on learning and training in the medical and health care setting in Malaysia. Highlights include learning and the knowledge economy; just-in-time continuing medical education; distance education; and modular distance learning. (Author/LRW)

Improving Distance Courses: Understanding Teacher Trainees and Their Learning Styles for the Design of Teacher Training Courses and Materials at a Distance

ERIC Educational Resources Information Center

Dzakiria, Hisham; Razak, Asmahan Abdul; Mohamed, Abdul Halim

2004-01-01

Literature on distance education and teacher education seems to show that what we do not know about Distance Teacher Trainees (DTT) and their learning process involved exceeds what we know about it. As more DTT enroll in distance education programmes globally, distance education providers and institutions will witness trainees coming with…

Determination of Critical Achievement Factors in Distance Education by Using Structural Equality Model: A Case Study of E-MBA Program Held in Sakarya University

ERIC Educational Resources Information Center

Evirgen, Hayrettin; Cengel, Metin

2012-01-01

Nowadays, distance learning education has started to become familiar in behalf of classical face to face education (F2F) model. Web based learning is a major part of distance education systems. Web based distance learning can be defined shortly as an education type which doesn't force students and educators being into the same mediums. This…

Comparison of immunogenicity and protective efficacy of genital herpes vaccine candidates herpes simplex virus 2 dl5-29 and dl5-29-41L in mice and guinea pigs.

PubMed

Hoshino, Yo; Pesnicak, Lesley; Dowdell, Kennichi C; Lacayo, Juan; Dudek, Timothy; Knipe, David M; Straus, Stephen E; Cohen, Jeffrey I

2008-07-29

A replication-defective herpes simplex virus (HSV)-2 vaccine, dl5-29, which is deleted for two essential early genes, UL5 and UL29, is highly immunogenic and protective in mice and guinea pigs. In a prior study, a derivative of HSV-2 dl5-29 termed dl5-29-41L, which has an additional deletion in UL41 (that encodes the virion-host shut-off protein), was more immunogenic and protective against challenge with wild-type HSV-2 in mice when compared with dl5-29. To determine if deletion of UL41 improves the efficacy of dl5-29 in protecting guinea pigs from HSV-2, animals were immunized with dl5-29, dl5-29-41L, or PBS. The geometric mean neutralizing antibody titers from the dl5-29 and dl5-29-41L recipients were comparable (10(1.97) and 10(2.19), respectively, p=0.15). After intravaginal challenge with wild-type HSV-2, the dl5-29-41L and dl5-29 recipients shed similar titers of HSV-2 from the vagina. Mean acute disease severity scores, numbers of recurrences during 3 months after infection, and latent viral loads in sacral ganglia were similar for dl5-29 and dl5-29-41L (all p values >0.05). dl5-29 and dl5-29-41L completely protected mice from lethal challenge with HSV-2 and induced virus-specific CD8(+) T cells in the spleens of the animals. Thus, dl5-29 was as immunogenic and protective as dl5-29-41L under these conditions. dl5-29 was at least 250,000-fold less virulent than parental virus by intracranial inoculation in healthy mice, and caused no disease in SCID mice. Both dl5-29-41L and dl5-29 are equally effective and immunogenic in guinea pigs, and dl5-29 is very safe in immunocompromised animals.

A Comparative Analysis of the Academic Performance of Distance and On-Campus Learners

ERIC Educational Resources Information Center

Magagula, C. M.; Ngwenya, A. P.

2004-01-01

This study examined (1) the profile of the distance and on-campus learners, (2) the academic performance of distance and on-campus learners, (3) the advantages and disadvantages of learning through distance education and on-campus education, and (4) how the disadvantages of learning through distance education could be reduced. The study found that…

Learning across Distance

ERIC Educational Resources Information Center

Cowan, Kristina

2009-01-01

A 2008 report, "Keeping Pace with K-12 Online Learning," commissioned by North American Council for Online Learning (NACOL) and others, defines online learning as "teacher-led education that takes place over the Internet, with the teacher and student separated geographically." The term "distance learning" includes online education, but is…

Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning

ERIC Educational Resources Information Center

Howard, Caroline; Schenk, Karen; Discenza, Richard

2004-01-01

"Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning" addresses the challenges and opportunities associated with information and communication technologies (ICTs) as related to education. From discussing new and innovative educational paradigms and learning models resulting from ICTs to addressing…

Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources

ERIC Educational Resources Information Center

García-Floriano, Andrés; Ferreira-Santiago, Angel; Yáñez-Márquez, Cornelio; Camacho-Nieto, Oscar; Aldape-Pérez, Mario; Villuendas-Rey, Yenny

2017-01-01

Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present.…

Distance Learning and the Health Professions: A Synthesis Report of the Literature Investigating Continuing Professional Health Education at a Distance.

ERIC Educational Resources Information Center

Curran, Vernon; Noseworthy, Tanya

This synthesis report provides an extensive overview of literature evaluating use and effectiveness of distance learning technologies in delivering continuing education (CE) for health professionals. Chapter 2 discusses advantages and disadvantages of correspondence materials, explores suggestions for improving print-based learning materials, and…

Distance Learning Courses on the Web: The Authoring Approach.

ERIC Educational Resources Information Center

Santos, Neide; Diaz, Alicia; Bibbo, Luis Mariano

This paper proposes a framework for supporting the authoring process of distance learning courses. An overview of distance learning courses and the World Wide Web is presented. The proposed framework is then described, including: (1) components of the framework--a hypermedia design methodology for authoring the course, links to related Web sites,…

A Study of Distance Learning Technology in Utah: A Statewide Overview.

ERIC Educational Resources Information Center

Chow, Stanley H. L.; And Others

This report was commissioned by the Utah State Office of Education (USOE) to provide USOE with information about the potential applications of distance learning technology in schools. The study includes: (1) a statewide assessment of instructional, staff development, and administrative needs which may be met by distance learning technology; and…

Distance Learning 2000: Proceedings of the Annual Conference on Distance Teaching & Learning (16th, Madison, Wisconsin, August 2-4, 2000).

ERIC Educational Resources Information Center

Wisconsin Univ. System, Madison.

These proceedings contain 75 papers from information sessions that address important human factors in distance education from several perspectives, including implementation planning, management and policy, instructional design, teaching methods, faculty development, learning environments, learner supports, and evaluation. Among the papers are:…

Characteristics and Activities of Teachers on Distance Learning Programs That Affect Their Ratings

ERIC Educational Resources Information Center

Stanišic Stojic, Svetlana M.; Dobrijevic, Gordana; Stanišic, Nemanja; Stanic, Nenad

2014-01-01

This paper presents an analysis of teachers' ratings on distance learning undergraduate study programs: 7,156 students enrolled in traditional and 528 students enrolled in distance learning studies took part in the evaluation questionnaire, assessing 71 teachers. The data were collected from the Moodle platform and from the Singidunum University…

Distance Education in the United States: From Correspondence Courses to the Internet

ERIC Educational Resources Information Center

Caruth, Gail D.; Caruth, Donald L.

2013-01-01

Online learning is a descendant of distance education. Online education has a shared history with correspondence learning. In 1873, Anna Eliot Ticknor founded the Society to Encourage Studies at Home. Ticknor's Society established one of America's first correspondence schools, a distance learning option conducted through the mail. This Society was…

Incorporating Distance Learning into Counselor Education Programs: A Research Study.

ERIC Educational Resources Information Center

Wantz, Richard A.; Tromski, Donna M.; Mortsolf, Christina Joelle; Yoxtheimer, Greggory; Brill, Samantha; Cole, Alison

The purpose of this study is to determine the number of counselor education programs that utilize distance learning, to identify the distance learning software delivery products used, and to identify features of software used. The researchers also attempt to identify faculty perceptions related to and experience with the importance of distance…

Bibliometric and Social Network Analysis of Doctoral Research: Research Trends in Distance Learning

ERIC Educational Resources Information Center

Skinner, Jason Kirtland

2015-01-01

The study investigated research topics of doctoral dissertations that examined issues in distance learning from 2000-2014. Twelve reviews of research on distance learning, spanning from 1997-2015, were identified. It was found that only one of these reviews of research (Davies, Howell, & Petri, 2010) looked at doctoral dissertations. The…

The Open College of the North West, Distance Learning, and the "Open Tech" Programme.

ERIC Educational Resources Information Center

Percy, Keith; Saunders, Murray

1982-01-01

A regional program of pre-university courses in northwestern England open to adults with no entry qualifications is discussed. It uses some distance learning techniques but is investigating expansion to technical education through distance learning. The complexities and potential costs of such a substantial directional change are examined. (MSE)

Effectiveness of Asynchronous Reference Services for Distance Learning Students within Florida's Community College System

ERIC Educational Resources Information Center

Profeta, Patricia C.

2007-01-01

The provision of equitable library services to distance learning students emerged as a critical area during the 1990s. Library services available to distance learning students included digital reference and instructional services, remote access to online research tools, database and research tutorials, interlibrary loan, and document delivery.…

NASA Langley/CNU Distance Learning Programs.

ERIC Educational Resources Information Center

Caton, Randall; Pinelli, Thomas E.

NASA Langley Research Center and Christopher Newport University (CNU) provide, free to the public, distance learning programs that focus on math, science, and/or technology over a spectrum of education levels from K-adult. The effort started in 1997, and currently there are a suite of five distance-learning programs. This paper presents the major…

New-to-College "Academic Transformation" Distance Learning: A Paradox

ERIC Educational Resources Information Center

Goomas, David T.; Clayton, Alexis

2013-01-01

At an urban Dallas community college, first-time-in-college (FTIC) distance learning students enrolled in a three-credit academic transformation class were compared with FTIC students enrolled in the same course in on-campus classes. The distance-learning students were more at risk as measured by final semester grades and retention compared to…

Distance-Learning Programs. Case Studies in TESOL Practice Series.

ERIC Educational Resources Information Center

Henrichsen, Lynn E., Ed.

The 14 cases in this book show how distance learning takes a variety of forms in teaching English to speakers of other languages (TESOL). The 15 chapters include the following: (1) "Beyond Adding Telecommunications to a Traditional Course: Insights into Human and Instructional Factors Affecting Distance Learning in TESOL" (Lynn E.…

Implementing a Learning Model for a Practical Subject in Distance Education.

ERIC Educational Resources Information Center

Weller, M. J.; Hopgood, A. A.

1997-01-01

Artificial Intelligence for Technology, a distance learning course at the Open University, is based on a learning model that combines conceptualization, construction, and dialog. This allows a practical emphasis which has been difficult to implement in distance education. The course uses commercial software, real-world-based assignments, and a…

Adding Interactivity to Web Based Distance Learning.

ERIC Educational Resources Information Center

Cafolla, Ralph; Knee, Richard

Web Based Distance Learning (WBDL) is a form of distance learning based on providing instruction mainly on the World Wide Web. This paradigm has limitations, especially the lack of interactivity inherent in the Web. The purpose of this paper is to discuss some of the technologies the authors have used in their courses at Florida Atlantic…

Student Support Gaps in an Open Distance Learning Context

ERIC Educational Resources Information Center

Arko-Achemfuor, Akwasi

2017-01-01

Studying through distance education can be problematic for any student, but it can be worse for rural students for diverse reasons. To ensure that students studying through the open distance learning (ODL) system have an enduring learning experience, ODL builds student support as one of its components. The University of South Africa (Unisa)…

The Effects of Videoconferenced Distance-Learning Instruction in a Taiwanese Company

ERIC Educational Resources Information Center

Lin, Chin-Hung; Yang, Shu-Ching

2011-01-01

Distance learning, where instruction is given to students despite wide separations of students and teachers, is increasingly popular. Videoconferencing, which is examined in this study, is a distance learning mode of featuring real-time interaction of students and teachers and provides sequence, real-time, vision, and actual interaction. This…

Embracing Distance Education in a Blended Learning Model: Challenges and Prospects

ERIC Educational Resources Information Center

Fresen, Jill W.

2018-01-01

Distance education reaches out to non-traditional students in geographically dispersed locations, who are unable to attend face-to-face classes. Contact institutions have been quick to realise the many advantages of distance (online) learning, such as easy access to learning materials, interactive activities, assessment and communication tools.…

Assessment of Readiness to Participate in Distance Learning of the Certified Florida Behavioral Workforce

ERIC Educational Resources Information Center

Baston, George R.

2011-01-01

This research study explored perceptions of readiness to participate in distance learning among the certified behavioral workforce in Florida. The study sought to determine if there were significant differences in perception of readiness to participate in distance learning between certified behavioral health professionals at the administrator…

Distance Learning and Jihad: The Dark Side of the Force

ERIC Educational Resources Information Center

Bates, Rodger; Mooney, Mara

2014-01-01

The ability to reach a variety of audiences in diverse environments has made distance learning a major form of education and training in the 21st century. Though traditionally encountered in the educational and business communities, distance learning has proven an important resource for a variety of other constituencies. Terrorist groups have…

Factors Affecting Corporate Image from the Perspective of Distance Learning Students in Public Higher Education Institutions

ERIC Educational Resources Information Center

da Costa, Fábio Reis; Pelissari, Anderson Soncini

2016-01-01

New information technologies enable different interactions in the educational environment, affecting how the image of educational institutions adopting distance-learning programmes is perceived. This article identifies factors affecting the perception of corporate image from the viewpoint of distance-learning students at public higher education…

Distance Learning for Gifted Students: Outcomes for Elementary, Middle, and High School Aged Students

ERIC Educational Resources Information Center

Wallace, Patricia

2009-01-01

Although distance learning often is cited as a potentially useful strategy to provide appropriately challenging academic coursework to gifted students, little research has been conducted on its use or effectiveness with this population, particularly with younger students in elementary school. In this study, distance learning outcomes for gifted…

Access and Success in Learning: Technologies for Scaling Up Open and Distance Learning Programme in the Institute of Distance Learning, KNUST, Kumasi, Ghana

ERIC Educational Resources Information Center

Essel, Rebecca; Owusu-Boateng, William

2011-01-01

ODL (Open and Distance Learning) has come to stay. In recent years, there has been some extra-ordinary increasing international interest in it and Ghana is no exception. Currently, new ways of providing education are inevitable and ODL provides an effective alternate way. It represents approaches that focus on opening access to education and…

A regularized approach for geodesic-based semisupervised multimanifold learning.

PubMed

Fan, Mingyu; Zhang, Xiaoqin; Lin, Zhouchen; Zhang, Zhongfei; Bao, Hujun

2014-05-01

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.

College Students Attitudes toward Learning Process and Outcome of Online Instruction and Distance Learning across Learning Styles

ERIC Educational Resources Information Center

Nguyen, Dat-Dao; Zhang, Yue

2011-01-01

This study uses the Learning-Style Inventory--LSI (Smith & Kolb, 1985) to explore to what extent student attitudes toward learning process and outcome of online instruction and Distance Learning are affected by their cognitive styles and learning behaviors. It finds that there are not much statistically significant differences in perceptions…

Organization of the gymnotiform fish pallium in relation to learning and memory: IV. Expression of conserved transcription factors and implications for the evolution of dorsal telencephalon.

PubMed

Harvey-Girard, Erik; Giassi, Ana C C; Ellis, William; Maler, Leonard

2012-10-15

We have cloned the apteronotid homologs of FoxP2, Otx1, and FoxO3. There was, in the case of all three genes, good similarity between the apteronotid and human amino acid sequences: FoxP2, 78%; Otx1, 54%; FoxO3, 71%. The functional domains of these genes were conserved to a far greater extent, on average: FoxP2, 89%; Otx1, 76%; FoxO3, 82%. This led us to hypothesize that the cellular functions of these genes might also be conserved. We used in situ hybridization to examine the distribution of the mRNA transcripts of these genes in the apteronotid telencephalon. We confined our analysis to the pallial regions previously associated with learning about social signals, whose circuitry has been closely examined in the other articles of this series. We found that AptFoxP2 and AptOtx1 transcripts were expressed predominantly in the dorsocentral division of the pallium (DC); the dorsolateral division of the pallium (DL) contained only weakly labeled neurons. In both cases, the distribution of labeled neurons was very heterogeneous, and unlabeled neurons could be found adjacent to strongly labeled ones. In contrast, we found that most neurons in DL strongly expressed AptFoxO3 mRNA, although there was only weak expression in a small number of cells within DC. We briefly discuss the relevance of our results regarding the functional roles of AptFoxP2/AptOtx1-expressing neurons in DC for communication vs. foraging behavior. We extensively discuss the implications of our results for possible homologies between DL and DC and medial and dorsal pallium of tetrapods, respectively. Copyright © 2012 Wiley Periodicals, Inc.

Forecasting influenza in Hong Kong with Google search queries and statistical model fusion.

PubMed

Xu, Qinneng; Gel, Yulia R; Ramirez Ramirez, L Leticia; Nezafati, Kusha; Zhang, Qingpeng; Tsui, Kwok-Leung

2017-01-01

The objective of this study is to investigate predictive utility of online social media and web search queries, particularly, Google search data, to forecast new cases of influenza-like-illness (ILI) in general outpatient clinics (GOPC) in Hong Kong. To mitigate the impact of sensitivity to self-excitement (i.e., fickle media interest) and other artifacts of online social media data, in our approach we fuse multiple offline and online data sources. Four individual models: generalized linear model (GLM), least absolute shrinkage and selection operator (LASSO), autoregressive integrated moving average (ARIMA), and deep learning (DL) with Feedforward Neural Networks (FNN) are employed to forecast ILI-GOPC both one week and two weeks in advance. The covariates include Google search queries, meteorological data, and previously recorded offline ILI. To our knowledge, this is the first study that introduces deep learning methodology into surveillance of infectious diseases and investigates its predictive utility. Furthermore, to exploit the strength from each individual forecasting models, we use statistical model fusion, using Bayesian model averaging (BMA), which allows a systematic integration of multiple forecast scenarios. For each model, an adaptive approach is used to capture the recent relationship between ILI and covariates. DL with FNN appears to deliver the most competitive predictive performance among the four considered individual models. Combing all four models in a comprehensive BMA framework allows to further improve such predictive evaluation metrics as root mean squared error (RMSE) and mean absolute predictive error (MAPE). Nevertheless, DL with FNN remains the preferred method for predicting locations of influenza peaks. The proposed approach can be viewed a feasible alternative to forecast ILI in Hong Kong or other countries where ILI has no constant seasonal trend and influenza data resources are limited. The proposed methodology is easily tractable and computationally efficient.

Bladder Cancer Segmentation in CT for Treatment Response Assessment: Application of Deep-Learning Convolution Neural Network-A Pilot Study.

PubMed

Cha, Kenny H; Hadjiiski, Lubomir M; Samala, Ravi K; Chan, Heang-Ping; Cohan, Richard H; Caoili, Elaine M; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z

2016-12-01

Assessing the response of bladder cancer to neoadjuvant chemotherapy is crucial for reducing morbidity and increasing quality of life of patients. Changes in tumor volume during treatment is generally used to predict treatment outcome. We are developing a method for bladder cancer segmentation in CT using a pilot data set of 62 cases. 65 000 regions of interests were extracted from pre-treatment CT images to train a deep-learning convolution neural network (DL-CNN) for tumor boundary detection using leave-one-case-out cross-validation. The results were compared to our previous AI-CALS method. For all lesions in the data set, the longest diameter and its perpendicular were measured by two radiologists, and 3D manual segmentation was obtained from one radiologist. The World Health Organization (WHO) criteria and the Response Evaluation Criteria In Solid Tumors (RECIST) were calculated, and the prediction accuracy of complete response to chemotherapy was estimated by the area under the receiver operating characteristic curve (AUC). The AUCs were 0.73 ± 0.06, 0.70 ± 0.07, and 0.70 ± 0.06, respectively, for the volume change calculated using DL-CNN segmentation, the AI-CALS and the manual contours. The differences did not achieve statistical significance. The AUCs using the WHO criteria were 0.63 ± 0.07 and 0.61 ± 0.06, while the AUCs using RECIST were 0.65 ± 007 and 0.63 ± 0.06 for the two radiologists, respectively. Our results indicate that DL-CNN can produce accurate bladder cancer segmentation for calculation of tumor size change in response to treatment. The volume change performed better than the estimations from the WHO criteria and RECIST for the prediction of complete response.

Bladder Cancer Segmentation in CT for Treatment Response Assessment: Application of Deep-Learning Convolution Neural Network—A Pilot Study

PubMed Central

Cha, Kenny H.; Hadjiiski, Lubomir M.; Samala, Ravi K.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

2017-01-01

Assessing the response of bladder cancer to neoadjuvant chemotherapy is crucial for reducing morbidity and increasing quality of life of patients. Changes in tumor volume during treatment is generally used to predict treatment outcome. We are developing a method for bladder cancer segmentation in CT using a pilot data set of 62 cases. 65 000 regions of interests were extracted from pre-treatment CT images to train a deep-learning convolution neural network (DL-CNN) for tumor boundary detection using leave-one-case-out cross-validation. The results were compared to our previous AI-CALS method. For all lesions in the data set, the longest diameter and its perpendicular were measured by two radiologists, and 3D manual segmentation was obtained from one radiologist. The World Health Organization (WHO) criteria and the Response Evaluation Criteria In Solid Tumors (RECIST) were calculated, and the prediction accuracy of complete response to chemotherapy was estimated by the area under the receiver operating characteristic curve (AUC). The AUCs were 0.73 ± 0.06, 0.70 ± 0.07, and 0.70 ± 0.06, respectively, for the volume change calculated using DL-CNN segmentation, the AI-CALS and the manual contours. The differences did not achieve statistical significance. The AUCs using the WHO criteria were 0.63 ± 0.07 and 0.61 ± 0.06, while the AUCs using RECIST were 0.65 ± 007 and 0.63 ± 0.06 for the two radiologists, respectively. Our results indicate that DL-CNN can produce accurate bladder cancer segmentation for calculation of tumor size change in response to treatment. The volume change performed better than the estimations from the WHO criteria and RECIST for the prediction of complete response. PMID:28105470

Designing, delivering and evaluating a distance learning nursing course responsive to students needs.

PubMed

Sowan, Azizeh K; Jenkins, Louise S

2013-06-01

The majority of available studies in distance learning in nursing and health lack the sufficient details of course design and delivery processes which greatly affect the learning outcomes. Also, little is available about the fairness of this method of education to students with limited access to course resources. We describe the design and delivery processes and experience, in terms of satisfaction and achievement, of undergraduate nursing students in a distance course. The difference in achievement between the distance students and a comparable cohort of hybrid students is also examined. We also demonstrate the possibility of providing accessible education to students with limited technological resources. Participants included all undergraduate nursing students who were enrolled in a distance and a hybrid section of a communication skills course offered at a School of Nursing in Jordan. The distance course was created using Blackboard and Tegrity learning management systems. The design and delivery processes of the distance course incorporated three pedagogical principles that enhance: (a) course access and navigation; (b) communication and interaction; and (c) active and collaborative learning experiences. After course completion, distance students completed a 27-item satisfaction questionnaire. Achievement in the course and correlates of satisfaction were measured. The final sample included 25 students in the distance section and 35 in the hybrid section (N=60). The mean score of overall satisfaction in the distance section was 4.14 (0.32) out of a 5-point scale, indicating a high satisfaction. Results revealed significant associations between total satisfaction score and achievement in the distance course, grade expected in the course, and frequency of accessing the course materials (p<.05). All distance students, including students with limited technological resources available at home, managed to successfully complete the course. Major concerns reported by distance students were related to lack of time management skills and negative attitudes toward group assignments. The mean final course grade of the distance section (80±8.2) was significantly higher than the hybrid section (72.2±9.5), (t=3.5, p<.05). The use of effective instructional strategies resulted in delivering successful distance learning, even for students with limited resources. Institutions have to make strategic decisions on how to optimize the use of technology to fit their individualized learning environments. Instructors need to become familiar with the characteristics of students cohort served by the course and design the course accordingly. In addition, students should be guided on how to manage their time in distance learning environments and work effectively in group assignments. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

AVIATION COMPETITION: Regional Jet Service Yet to Reach Many Small Communities

DTIC Science & Technology

2001-02-01

1997), AA (2000), NW (2000) Colorado Springs CO DL (1997), CO (1999), HP (1999) Columbia SC DL (1997), CO (1998), UA (1999), US (1999) Corpus...DL (1999) Small cities Bangor ME DL (1999) Bozeman MT DL (1997), UA (2000) Butte MT DL (1997) Casper WY DL (1997) Durango CO HP (1999) Grand Forks ND

Dose-Escalated Intensity-Modulated Radiotherapy Is Feasible and May Improve Locoregional Control and Laryngeal Preservation in Laryngo-Hypopharyngeal Cancers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miah, Aisha B.; Bhide, Shreerang A.; Guerrero-Urbano, M. Teresa

2012-02-01

Purpose: To determine the safety and outcomes of induction chemotherapy followed by dose-escalated intensity-modulated radiotherapy (IMRT) with concomitant chemotherapy in locally advanced squamous cell cancer of the larynx and hypopharynx (LA-SCCL/H). Methods and Materials: A sequential cohort Phase I/II trial design was used to evaluate moderate acceleration and dose escalation. Patients with LA-SCCL/H received IMRT at two dose levels (DL): DL1, 63 Gy/28 fractions (Fx) to planning target volume 1 (PTV1) and 51.8 Gy/28 Fx to PTV2; DL2, 67.2 Gy/28 Fx and 56 Gy/28 Fx to PTV1 and PTV2, respectively. Patients received induction cisplatin/5-fluorouracil and concomitant cisplatin. Acute and latemore » toxicities and tumor control rates were recorded. Results: Between September 2002 and January 2008, 60 patients (29 DL1, 31 DL2) with Stage III (41% DL1, 52% DL2) and Stage IV (52% DL1, 48% DL2) disease were recruited. Median (range) follow-up for DL1 was 51.2 (12.1-77.3) months and for DL2 was 36.2 (4.2-63.3) months. Acute Grade 3 (G3) dysphagia was higher in DL2 (87% DL2 vs. 59% DL1), but other toxicities were equivalent. One patient in DL1 required dilatation of a pharyngeal stricture (G3 dysphagia). In DL2, 2 patients developed benign pharyngeal strictures at 1 year. One underwent a laryngo-pharyngectomy and the other a dilatation. No other G3/G4 toxicities were reported. Overall complete response was 79% (DL1) and 84% (DL2). Two-year locoregional progression-free survival rates were 64.2% (95% confidence interval, 43.5-78.9%) in DL1 and 78.4% (58.1-89.7%) in DL2. Two-year laryngeal preservation rates were 88.7% (68.5-96.3%) in DL1 and 96.4% (77.7-99.5%) in DL2. Conclusions: At a mean follow-up of 36 months, dose-escalated chemotherapy-IMRT at DL2 has so far been safe to deliver. In this study, DL2 delivered high rates of locoregional control, progression-free survival, and organ preservation and has been selected as the experimental arm in a Cancer Research UK Phase III study.« less

Enhancing SCORM Metadata for Assessment Authoring in E-Learning

ERIC Educational Resources Information Center

Chang, Wen-Chih; Hsu, Hui-Huang; Smith, Timothy K.; Wang, Chun-Chia

2004-01-01

With the rapid development of distance learning and the XML technology, metadata play an important role in e-Learning. Nowadays, many distance learning standards, such as SCORM, AICC CMI, IEEE LTSC LOM and IMS, use metadata to tag learning materials. However, most metadata models are used to define learning materials and test problems. Few…

An Assistive Computerized Learning Environment for Distance Learning Students with Learning Disabilities

ERIC Educational Resources Information Center

Klemes, Joel; Epstein, Alit; Zuker, Michal; Grinberg, Nira; Ilovitch, Tamar

2006-01-01

The current study examines how a computerized learning environment assists students with learning disabilities (LD) enrolled in a distance learning course at the Open University of Israel. The technology provides computer display of the text, synchronized with auditory output and accompanied by additional computerized study skill tools which…

A distance learning model in a physical therapy curriculum.

PubMed

English, T; Harrison, A L; Hart, A L

1998-01-01

In response to the rural health initiative established in 1991, the University of Kentucky has developed an innovative distance learning program of physical therapy instruction that combines classroom lecture and discussion via compressed video technology with laboratory experiences. The authors describe the process of planning, implementing, and evaluating a specific distance learning course in pathomechanics for the professional-level master's-degree physical therapy students at the University of Kentucky. This presentation may serve as a model for teaching distance learning. Descriptions of optimal approaches to preclass preparation, scheduling, course delivery, use of audiovisual aids, use of handout material, and video production are given. Special activities that may enhance or deter the achievement of the learning objectives are outlined, and a problem-solving approach to common problems encountered is presented. An approach to evaluating and comparing course outcomes for the distance learnere is presented. For this particular course, there was no statistically significant difference in the outcome measures utilized to compare the distance learners with the on-site learners.

Measuring the Accuracy of Simple Evolving Connectionist System with Varying Distance Formulas

NASA Astrophysics Data System (ADS)

Al-Khowarizmi; Sitompul, O. S.; Suherman; Nababan, E. B.

2017-12-01

Simple Evolving Connectionist System (SECoS) is a minimal implementation of Evolving Connectionist Systems (ECoS) in artificial neural networks. The three-layer network architecture of the SECoS could be built based on the given input. In this study, the activation value for the SECoS learning process, which is commonly calculated using normalized Hamming distance, is also calculated using normalized Manhattan distance and normalized Euclidean distance in order to compare the smallest error value and best learning rate obtained. The accuracy of measurement resulted by the three distance formulas are calculated using mean absolute percentage error. In the training phase with several parameters, such as sensitivity threshold, error threshold, first learning rate, and second learning rate, it was found that normalized Euclidean distance is more accurate than both normalized Hamming distance and normalized Manhattan distance. In the case of beta fibrinogen gene -455 G/A polymorphism patients used as training data, the highest mean absolute percentage error value is obtained with normalized Manhattan distance compared to normalized Euclidean distance and normalized Hamming distance. However, the differences are very small that it can be concluded that the three distance formulas used in SECoS do not have a significant effect on the accuracy of the training results.

Study of CT image texture using deep learning techniques

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Fan, Jiahua; Chevalier, David

2018-03-01

For CT imaging, reduction of radiation dose while improving or maintaining image quality (IQ) is currently a very active research and development topic. Iterative Reconstruction (IR) approaches have been suggested to be able to offer better IQ to dose ratio compared to the conventional Filtered Back Projection (FBP) reconstruction. However, it has been widely reported that often CT image texture from IR is different compared to that from FBP. Researchers have proposed different figure of metrics to quantitate the texture from different reconstruction methods. But there is still a lack of practical and robust method in the field for texture description. This work applied deep learning method for CT image texture study. Multiple dose scans of a 20cm diameter cylindrical water phantom was performed on Revolution CT scanner (GE Healthcare, Waukesha) and the images were reconstructed with FBP and four different IR reconstruction settings. The training images generated were randomly allotted (80:20) to a training and validation set. An independent test set of 256-512 images/class were collected with the same scan and reconstruction settings. Multiple deep learning (DL) networks with Convolution, RELU activation, max-pooling, fully-connected, global average pooling and softmax activation layers were investigated. Impact of different image patch size for training was investigated. Original pixel data as well as normalized image data were evaluated. DL models were reliably able to classify CT image texture with accuracy up to 99%. Results show that the deep learning techniques suggest that CT IR techniques may help lower the radiation dose compared to FBP.

Distance Education and Open Learning in Sub-Saharan Africa: Criteria and Conditions for Quality and Critical Success Factor-- Working Group on Distance Education and Open Learning. A Survey of Policy and Practice. Final Report

ERIC Educational Resources Information Center

Commonwealth of Learning, 2004

2004-01-01

Both of these "Surveys of policy and practice" were conducted on behalf of COL by the South African Institute for Distance Education (SAIDE) as part of COL's partnership agreement with the Association for the Development of Education in Africa (ADEA) Working Group on Distance Education and Open Learning. The first report identifies…

A Strategic Planning Process Model for Distance Education

ERIC Educational Resources Information Center

Pisel, Kenneth P.

2008-01-01

As more institutions seek to implement or expand distance learning programs, it becomes critical to integrate distance learning programs into broader strategic visions and plans. Using the informed opinion from a panel of peer-nominated experts via iterative Delphi questionnaires, a 10-phased strategic planning process model for distance education…

Quality Assurance, Open and Distance Learning, and Australian Universities

ERIC Educational Resources Information Center

Reid, Ian C.

2005-01-01

Open and distance education has integrated quality assurance processes since its inception. Recently, the increased use of distance teaching systems, technologies, and pedagogies by universities without a distance education heritage has enabled them to provide flexible learning opportunities. They have done this in addition to, or instead of,…

Quality Assurance in Distance Learning Libraries

ERIC Educational Resources Information Center

Tripathi, Manorama; Jeevan, V. K. J.

2009-01-01

Purpose: The paper aims to study how the present distance learning libraries can improve upon their existing services and introduce new ones to enhance quality of services to distance learners. Design/methodology/approach: The paper includes a review of literature on quality assurance in open and distance education in general and student support…

Distance Education and Distributed Learning. Current Perspectives on Applied Information Technologies.

ERIC Educational Resources Information Center

Vrasidas, Charalambos, Ed.; Glass, Gene V., Ed.

This book describes the current state of developments in distance education and distributed learning. The volume brings together some of the leading contemporary contributors in the areas of educational technology and distance education. Topics covered include research and evaluation in distance education, online communities, faculty productivity,…

Strategic Plan for the Academic Component of the Army National Guard Distance Learning Demonstration.

DTIC Science & Technology

1998-07-01

II - Directed study on Distance Learning Technologies - Action Memorandum. a reserve unit where they perform the same job as they did as full-time...a virtual learning community and provide a classroom without walls. The harnessing of appropriate technology to meet the training needs offers...its force through training, the Distance Learning capabilities also becomes part of community resources that advance the education of local residents

Burnout Syndrome in Students of a Distance Learning Program: The Open University of Cyprus Experience

ERIC Educational Resources Information Center

Pavlakis, Andreas; Kaitelidou, Dafni

2012-01-01

Introduction: Distance learning seems to have a crucial impact on the social and emotional life of students. Within the framework of distance learning at the Open University of Cyprus, the "Healthcare Management" department conducted a study regarding the levels of stress, anxiety and depression reported by the student population. The…

From Radio, to Satellite, to M-Learning: Interactive Distance Education in Australia

ERIC Educational Resources Information Center

Crump, Stephen

2013-01-01

This paper provides reflections on M-learning as a form of "distance education," based on a summary of the findings of the Interactive Distance e-Learning (IDL) research project in rural and remote Australia under an Australian Research Council Linkage grant. This project was a joint undertaking between 3 government agencies and an…

Distance Learning Course Design Expectations in China and the United Kingdom

ERIC Educational Resources Information Center

Xu, Jingjing; Rees, Terri

2016-01-01

This article provides insight into different expectations between Chinese and British academic culture for distance learning. The article is based on a pedagogic research project, a case study, and is centered on a distance learning course in maritime law proposed by a British university for a university in China. Some important commonalities and…

The Development of a Survey Instrument to Measure Transactional Distance in Secondary Blended Learning Environments

ERIC Educational Resources Information Center

Lane, Dennis Glenn

2017-01-01

The goal of this study was to develop a survey instrument to measure transactional distance in secondary blended learning environments. This study resulted in a 35-item survey instrument, the Blended Learning Assessment Scale of Transactional Distance (BLASTD), which was tested using a convenience sample of secondary students (n = 222) at a…

Automated Inattention and Fatigue Detection System in Distance Education for Elementary School Students

ERIC Educational Resources Information Center

Hwang, Kuo-An; Yang, Chia-Hao

2009-01-01

Most courses based on distance learning focus on the cognitive domain of learning. Because students are sometimes inattentive or tired, they may neglect the attention goal of learning. This study proposes an auto-detection and reinforcement mechanism for the distance-education system based on the reinforcement teaching strategy. If a student is…

Distance Training: How Innovative Organizations Are Using Technology To Maximize Learning and Meet Business Objectives. Jossey-Bass Business and Management Series.

ERIC Educational Resources Information Center

Schreiber, Deborah A.; Berge, Zane L.

This book contains 19 papers examining ways in which innovative organizations are using distance learning technology to maximize learning and meet business objectives. The following papers are included: "Preface" (Deborah A. Schreiber, Zane L. Berge); "Organizational Technology and Its Impact on Distance Training" (Deborah A.…

What Is the Role of Distance Learning in the State University System? Information Brief. Volume 6, Issue 2

ERIC Educational Resources Information Center

Florida Board of Governors, State University System, 2008

2008-01-01

Distance learning is the term used when the delivery of instruction involves the separation of student(s) and the instructor by time and/or space. Some forms of distance learning include correspondence, telecourses, online instruction, computer assisted instruction, and instructional delivery that relies upon satellite, cable, broadcast (TV or…

Supporting Students in Open and Distance Learning. Open and Distance Learning Series.

ERIC Educational Resources Information Center

Simpson, Ormond

This book, which is intended for individuals involved in recruiting and teaching students in open and distance learning (ODL) situations, examines academic and nonacademic student support issues in ODL. The following are among the topics discussed in the book's 14 chapters: (1) models and definitions of ODL systems; (2) rationale for student…

The Resonance Factor: Probing the Impact of Video on Student Retention in Distance Learning

ERIC Educational Resources Information Center

Geri, Nitza

2012-01-01

Teaching and instructing is one of the challenging manifestations of informing, within which distance learning is considered harder than face-to-face instruction. Student retention is one of the major challenges of distance learning. Current innovative technologies enable widespread use of video lectures that may ease the loneliness of the…

Perspectives on Distance Education and Social Media

ERIC Educational Resources Information Center

Powers, Lisa; Alhussain, Ruqaya; Averbeck, Clemens; Warner, Andre

2012-01-01

There is a dramatic shift in the tools that are used in today's technology-based distance education. While distance education is not new, there are new types of socially rich, mobile technologies that empower learners to be more in control of what they learn, when they learn it, and how they learn it. Students are taking more responsibility for…

A Framework for Developing Competencies in Open and Distance Learning

ERIC Educational Resources Information Center

Arinto, Patricia B.

2013-01-01

Many open universities and distance education institutions have shifted from a predominantly print-based mode of delivery to an online mode characterised by the use of virtual learning environments and various web technologies. This paper describes the impact of the shift to open and distance e-learning (ODeL), as this trend might be called, on…

Transactional Distance among Open University Students: How Does it Affect the Learning Process?

ERIC Educational Resources Information Center

Kassandrinou, Amanda; Angelaki, Christina; Mavroidis, Ilias

2014-01-01

This study examines the presence of transactional distance among students, the factors affecting it, as well as the way it influences the learning process of students in a blended distance learning setting in Greece. The present study involved 12 postgraduate students of the Hellenic Open University (HOU). A qualitative research was conducted,…

Survey on Uses of Distance Learning in the U.S.

ERIC Educational Resources Information Center

Downing, Diane E.

A December 1983 survey queried the chief state school officers of the 50 states on the extent to which distance learning techniques are used in public education in their states. Respondents were asked to focus on interactive forms of distance learning, such as audio and video teleconferencing. A total of 28 states (56%) responded, with the…

Cross-Sectional Evaluation of Distance Education Students' Learning Styles and Critical Thinking Dispositions in Turkey

ERIC Educational Resources Information Center

Yüksel, Ismail; Türkses, Ercüment

2015-01-01

This study aims to examine distance education students' learning styles and critical thinking dispositions. This cross sectional survey was conducted on 114 Turkish distance education students from various departments in a state university. The data of the study were collected through Grasha-Riechmann Student Learning Style Scale (GRSLSS) and…

China's Radio and TV Universities: Reflections on Theory and Practice of Open and Distance Learning

ERIC Educational Resources Information Center

Wei, Runfang

2010-01-01

Distance education and open learning are western innovations, representing the educational concepts, cultures and societies of western countries. The introduction of distance education and the adoption of open learning in China's radio and TV universities are by no means an indication that they will and can be copied wholesale. Open and distance…

High School Students in the New Learning Environment: A Profile of Distance E-Learners

ERIC Educational Resources Information Center

Kirby, Dale; Sharpe, Dennis

2010-01-01

The relative ubiquity of computer access and the rapid development of information and communication technology have profoundly impacted teaching and learning at a distance. Relatively little is currently known about the characteristics of those students who participate in distance e-learning courses at the secondary school level. In an effort to…

Attitudes and Perceptions of Students to Open and Distance Learning in Nigeria

ERIC Educational Resources Information Center

Ojo, David Olugbenga; Olakulehin, Felix Kayode

2006-01-01

In the West African Region of Africa, the National Open University of Nigeria (NOUN) is the first full fledged university that operates in an exclusively open and distance learning (ODL) mode of education. NOUN focuses mainly on open and distance teaching and learning system, and delivers its courses materials via print in conjunction with…

An Analysis of the Market Potential for Distance Learning Opportunities in Transportation Professional Development.

ERIC Educational Resources Information Center

Durkop, Brooke R.; Jasek, Debbie; Kuhn, Beverly T.

The feasibility and sustainability of a distance learning program at the Texas Transportation Institute, which is part of the Texas A&M University system, was investigated. A literature review and online survey of current transportation professionals were conducted to examine the market potential for a distance learning program and to identify…

Curriculum Integration in Distance Learning at Primary and Secondary Educational Levels on the Example of eTwinning Projects

ERIC Educational Resources Information Center

Gajek, Elzbieta

2018-01-01

Curriculum integration is one of the concepts which has been discussed for years. Telecollaborative projects, which employ elements of distance learning, provide opportunities for putting the idea into practice. Analysis of eTwinning projects undertaken in Polish schools aims at demonstrating the integrative role of distance learning approaches…

Survey of Distance Learning Provision in Continuing Health Professional Education in Canada

ERIC Educational Resources Information Center

Curran, Vernon; Kirby, Fran; Fleet, Lisa

2003-01-01

In Canada, the trend is towards greater use of distance learning technologies in the provision of continuing professional education in the health professions. Lack of access to professional development is a common deterrent to practice in rural and remote areas. Distance learning technologies have an important role to play in addressing the…

Application of the Classification Tree Model in Predicting Learner Dropout Behaviour in Open and Distance Learning

ERIC Educational Resources Information Center

Yasmin, Dr.

2013-01-01

This paper demonstrates the meaningful application of learning analytics for determining dropout predictors in the context of open and distance learning in a large developing country. The study was conducted at the Directorate of Distance Education at the University of North Bengal, West Bengal, India. This study employed a quantitative research…

Analysis of Risks in a Learning Management System: A Case Study in the Spanish National University of Distance Education (UNED)

ERIC Educational Resources Information Center

Vázquez-Cano, Esteban; Sevillano García, Ma. Luisa

2015-01-01

This article presents a research that examines the university students' risk perception when using a Learning Management System called "aLF" and implemented by the Spanish National University of Distance Education (UNED) for the development of its university distance studies. The development of comprehensive Learning Management Systems…

Television and Learning Systems (Distance Education). Papers on Information Technology No. 245.

ERIC Educational Resources Information Center

Bates, A. W.

Arguing that television has a very important role to play in distance education courses, this paper outlines some of the unique roles that television can play and gives examples of how television can provide learning material not otherwise available to distance learners and help in the development of thinking and learning. Examples of how…

A Flow Theory Perspective on Learner Motivation and Behavior in Distance Education

ERIC Educational Resources Information Center

Liao, Li-Fen

2006-01-01

Motivating learners to continue to study and enjoy learning is one of the critical factors in distance education. Flow theory is a useful framework for studying the individual experience of learning through using computers. In this study, I examine students' emotional and cognitive responses to distance learning systems by constructing two models…

Science Practical Work Instructional Technologies and Open Distance Learning in Science Teacher Training: A Case Study in Zimbabwe

ERIC Educational Resources Information Center

Bhukuvhani, Crispen; Mupa, Mathew; Mhishi, Misheck; Dziva, Daimond

2012-01-01

The practical work component offers unique challenges for university science courses. This is even more pertinent in an Open and Distance Learning (ODL) environment like the Bindura University of Science Education's Virtual and Open Distance Learning (VODL) programme. Effective ODL education should be flexible enough to accommodate science…

Empirical Investigation into Motives for Choosing Web-Based Distance Learning Programs

ERIC Educational Resources Information Center

Alkhattabi, Mona

2016-01-01

Today, in association with rapid social and economic changes, there is an increasing level of demand for distance and online learning programs. This study will focus on identifying the main motivational factors for choosing a web-based distance-learning program. Moreover, it will investigate how these factors relate to age, gender, marital status…

Going the Distance: A National Distance Learning Initiative.

ERIC Educational Resources Information Center

Dubois, Jaques R.

1996-01-01

Going the Distance is a Public Broadcasting Service project through which over 130 colleges and universities are offering telecourses for adults seeking associate degrees. It is the beginning of a global learning community. (SK)

Student outcomes of distance learning in nursing education: an integrative review.

PubMed

Patterson, Barbara J; Krouse, Anne M; Roy, Linda

2012-09-01

Distance learning offers a distinctive environment to educate nursing students. While there is a significant body of evidence in the literature related to course, program, and faculty outcomes of distance education, little attention has been given by researchers to evaluate student outcomes, with the exception of student satisfaction. There is a need to evaluate and translate findings related to student outcomes in distance learning into educational practice. Integrative reviews offer one strategy to contribute to evidence-based teaching practice initiatives. A search of available published qualitative and quantitative research on student outcomes of distance learning from 1999 to 2009 was conducted using a number of databases. Astin's Input-Environment-Output conceptual model provided a framework for this review. Thirty-three studies met the inclusion criteria. Bothcognitive and affective student outcomes emerged. The cognitive outcomes were student learning, learning process, and technology proficiency. Affective outcomes included personal and professional growth, satisfaction, and connectedness. Implications, recommendations, and future research are discussed.

Rain/No-Rain Identification from Bispectral Satellite Information using Deep Neural Networks

NASA Astrophysics Data System (ADS)

Tao, Y.

2016-12-01

Satellite-based precipitation estimation products have the advantage of high resolution and global coverage. However, they still suffer from insufficient accuracy. To accurately estimate precipitation from satellite data, there are two most important aspects: sufficient precipitation information in the satellite information and proper methodologies to extract such information effectively. This study applies the state-of-the-art machine learning methodologies to bispectral satellite information for Rain/No-Rain detection. Specifically, we use deep neural networks to extract features from infrared and water vapor channels and connect it to precipitation identification. To evaluate the effectiveness of the methodology, we first applies it to the infrared data only (Model DL-IR only), the most commonly used inputs for satellite-based precipitation estimation. Then we incorporates water vapor data (Model DL-IR + WV) to further improve the prediction performance. Radar stage IV dataset is used as ground measurement for parameter calibration. The operational product, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), is used as a reference to compare the performance of both models in both winter and summer seasons.The experiments show significant improvement for both models in precipitation identification. The overall performance gains in the Critical Success Index (CSI) are 21.60% and 43.66% over the verification periods for Model DL-IR only and Model DL-IR+WV model compared to PERSIANN-CCS, respectively. Moreover, specific case studies show that the water vapor channel information and the deep neural networks effectively help recover a large number of missing precipitation pixels under warm clouds while reducing false alarms under cold clouds.

A New Distance Metric for Unsupervised Learning of Categorical Data.

PubMed

Jia, Hong; Cheung, Yiu-Ming; Liu, Jiming

2016-05-01

Distance metric is the basis of many learning algorithms, and its effectiveness usually has a significant influence on the learning results. In general, measuring distance for numerical data is a tractable task, but it could be a nontrivial problem for categorical data sets. This paper, therefore, presents a new distance metric for categorical data based on the characteristics of categorical values. In particular, the distance between two values from one attribute measured by this metric is determined by both the frequency probabilities of these two values and the values of other attributes that have high interdependence with the calculated one. Dynamic attribute weight is further designed to adjust the contribution of each attribute-distance to the distance between the whole data objects. Promising experimental results on different real data sets have shown the effectiveness of the proposed distance metric.

Environmental and occupational exposures as a cause of male infertility.

PubMed

Wijesekara, G U S; Fernando, D M S; Wijerathna, S; Bandara, N

2015-06-01

To determine the association between environmental and occupational exposures, semen parameters and lead (Pb) and cadmium (Cd) levels in seminal plasma of men investigated for infertility. Data were collected from 300 men investigated for infertility using an interviewer administered questionnaire. Seminal fluid analysis and classification was done according to WHO guidelines. Positive exposure was defined as environmental or occupational exposure to agro or industrial chemicals, heavy metals and living in areas within 50 m of potential sources of pollution for three months or more. Seminal plasma lead and cadmium levels were estimated by graphite furnace atomic absorption spectrophotometry after digestion with nitric acid. The means of sperm parameters, Pb and Cd concentrations between exposed and non exposed groups were compared using t-test. Mean age was 34.8 (95% CI 34.2-35.4) years BMI was 24.3 (95% CI 23.8-24.7) kg/m2 and duration of the infertility was 45.7 (41.7-49.6) months. In this study, 54.6% were exposed to toxins through environmental or occupational sources. All sperm parameters were lower in the exposed group when compared to the non exposed. Lead and cadmium were detected in 38.3% and 23% of men respectively. The distance from the source of possible environmental or occupational exposure was negatively correlated to seminal plasma Pb (r=0.06, p>0.05) and Cd (r=0.26, p<0.05) concentrations. In the exposed, mean lead concentration was 17.7 (95% CI 15.0-20.4) μg/dl and 13.5 (95% CI 11.2-15.7) μg/dl in non exposed and cadmium concentration in exposed was 1.2 (95% CI 1.1-1.4) μg/dl and 1.1 (0.9-1.3) μg/dl in non-exposed. Environmental and occupational exposures were associated with reduced sperm count motility, viability, normal forms and detectable levels of lead and cadmium in seminal plasma.

SU-G-201-04: Can the Dynamic Library of Flap Applicators Replace Treatment Planning in Surface Brachytherapy?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buzurovic, I; Devlin, P; Hansen, J

Purpose: Contemporary brachytherapy treatment planning systems-(TPS) include the applicator model libraries to improve digitization; however, the library of surface-flap-applicators-(SFA) is not incorporated into the commercial TPS. We propose the dynamic library-(DL) for SFA and investigate if such library can eliminate applicator reconstruction, source activation and dose normalization. Methods: DL was generated for the SFA using the C++class libraries of the Visualization Toolkit-(VTK) and Qt-application framework for complete abstraction of the graphical interface. DL was designed such that the user can initially choose the size of the applicator that corresponds to the one clinically placed to the patient. The virtual applicator-(VA)more » has an elastic property so that it can be registered to the clinical CT images with a real applicator-(RA) on it. The VA and RA matching is performed by adjusting the position and curvature of the VA. The VA does not elongate or change its size so each catheter could always be at a distance of 5mm from the skin and 10mm apart from the closest catheter maintaining the physical accuracy of the clinical setup. Upon the applicator placement, the dwell positions were automatically activated, and the dose is normalized to the prescription depth. The accuracy of source positioning was evaluated using various applicator sizes. Results: The accuracy of the applicator placement was in the sub-millimeter range. The time-study reveals that up to 50% of the planning time can be saved depending on the complexity of the clinical setup. Unlike in the classic approach, the planning time was not highly dependent on the applicator size. Conclusion: The practical benefits of the DL of the SFA were demonstrated. The time demanding planning processes can be partially automated. Consequently, the planner can dedicate effort to fine tuning, which can result in the improvement of the quality of treatment plans in surface brachytherapy.« less

Local CD-ROM in interaction with HTML documents over the Internet.

PubMed

Mattheos, N; Nattestad, A; Attström, R

2000-08-01

The internet and computer assisted learning have enhanced the possibilities of providing quality distance learning in dentistry. The use of multimedia material is an essential part of such distance learning courses. However the Internet technology available has limitations regarding transmission of large multimedia files. Therefore especially when addressing undergraduate students or geographically isolated professionals, large download times make distance learning unattractive. This problem was technically solved in a distance learning course for undergraduate students from all over Europe. The present communication describes a method to bypass the problem of transmitting large multimedia files by the use of a specially designed CD-ROM. This CD-ROM was run locally on the students' PC interacting with HTML documents sent over the Internet.

Distance Learning as a Tool for Poverty Reduction and Economic Development: A Focus on China and Mexico

NASA Astrophysics Data System (ADS)

Larson, Richard C.; Murray, M. Elizabeth

2008-04-01

This paper uses case studies to focus on distance learning in developing countries as an enabler for economic development and poverty reduction. To provide perspective, we first review the history of telecottages, local technology-equipped facilities to foster community-based learning, which have evolved into "telecenters" or "Community Learning Centers" (CLCs). Second, we describe extensive site visits to CLCs in impoverished portions of China and Mexico, the centers operated by premier universities in each respective country. These CLCs constitute the core of new emerging systems of distance education, and their newness poses challenges and opportunities, which are discussed. Finally, we offer 12 points to develop further the concept and reality of distance learning in support of economic development.

C3 toxin and poly-DL-lactide-ε-caprolactone conduits in the critically damaged peripheral nervous system: a combined therapeutic approach.

PubMed

Leibig, Nico; Boyle, Veronika; Kraus, Daniel; Stark, Gerhard Bjoern; Penna, Vincenzo

2015-03-01

Peripheral nerve regeneration over longer distances through conduits is limited. In the presented study, critical size nerve gap bridging with a poly-DL-lactide-ε-caprolactone (PLC) conduit was combined with application of C3 toxin to facilitate axonal sprouting. The PLC filled with fibrin (n = 10) and fibrin gel loaded with 1-μg C3-C2I and 2-μg C2II (n = 10) were compared to autologous nerve grafts (n = 10) in a 15-mm sciatic nerve gap lesion model of the rat. Functional and electrophysiological analyses were performed before histological evaluation. Evaluation of motor function and nerve conduction velocity at 16 weeks revealed no differences between the groups. All histological parameters and muscle weight were significantly elevated in nerve graft group. No differences were observed in both PLC groups. The PLCs are permissive for nerve regeneration over a 15-mm defect in rats. Intraluminal application of C3 toxin did not lead to significant enhancement of nerve sprouting.

E-Learning and North-South collaboration: the experience of two public health schools in France and Benin.

PubMed

Edouard, Guévart; Dominique, Billot; Moussiliou, Paraïso Noël; Francis, Guillemin; Khaled, Bessaoud; Serge, Briançon

2009-10-14

Distance learning (e-learning) can facilitate access to training. Yet few public health E-learning experiments have been reported; institutes in developing countries experience difficulties in establishing on-line curricula, while developed countries struggle with adapting existing curricula to realities on the ground. In 2005, two schools of public health, one in France and one in Benin, began collaborating through contact sessions organised for Nancy University distance-learning students. This experience gave rise to a partnership aimed at developing training materials for e-Learning for African students. The distance-learning public health course at Nancy teaches public health professionals through a module entitled "Health and Development." The module is specifically tailored for professionals from developing countries. To promote student-teacher exchanges, clarify content and supervise dissertations, contact sessions are organized in centres proximate and accessible to African students. The Benin Institute's main feature is residential team learning; distance-learning courses are currently being prepared. The two collaborating institutions have developed a joint distance-learning module geared toward developing countries. The collaboration provides for the development, diffusion, and joint delivery of teaching modules featuring issues that are familiar to African staff, gives the French Institute credibility in assessing research work produced, and enables modules on specific African issues and approaches to be put online. While E-learning is a viable educational option for public health professionals, periodic contact can be advantageous. Our analysis showed that the benefit of the collaboration between the two institutions is mutual; the French Institute extends its geographical, cultural and contextual reach and expands its pool of teaching staff. The Benin Institute benefits from the technical partnership and expertise, which allow it to offer distance learning for Africa-specific contexts and applications.

Lifelong Learning & Distance Higher Education. Perspectives on Distance Education

ERIC Educational Resources Information Center

McIntosh, Christopher, Ed.

2005-01-01

Reflecting a common objective of ensuring quality Education for All, this book is a joint initiative of UNESCO and COL and jointly published. Lifelong Learning in Distance Higher Education brings together a diverse group of experts from many countries. The book provides a clear picture of the challenges, problems and potential of distance higher…

Use of Distance Education by Christian Religion to Train, Edify and Educate Adherents

ERIC Educational Resources Information Center

Satyanarayana, P.; DK Meduri, Emmanuel

2013-01-01

Distance Education has been growing fast, in a marvelously diverse fashion. The efficiency, effectiveness, validity and utility of distance teaching-learning are on increase. All communities and religious groups are making use of distance learning methodology to upgrade their knowledge, skills and attitudes. Christian educational institutions in…

A Basic Hybrid Library Support Model to Distance Learners in Sudan

ERIC Educational Resources Information Center

Abdelrahman, Omer Hassan

2012-01-01

Distance learning has flourished in Sudan during the last two decades; more and more higher education institutions offer distance learning programmes to off-campus students. Like on-campus students, distance learners should have access to appropriate library and information support services. They also have specific needs for library and…

The Knowledge Base as an Extension of Distance Learning Reference Service

ERIC Educational Resources Information Center

Casey, Anne Marie

2012-01-01

This study explores knowledge bases as extension of reference services for distance learners. Through a survey and follow-up interviews with distance learning librarians, this paper discusses their interest in creating and maintaining a knowledge base as a resource for reference services to distance learners. It also investigates their perceptions…

Implications of the University of South Africa's (UNISA) Shift to Open Distance e-Learning on Teacher Education

ERIC Educational Resources Information Center

Ngubane-Mokiwa, Sindile A.

2017-01-01

This conceptual and exploratory article seeks to explore the implications of the University of South Africa's (Unisa) shift from open distance learning (ODL) to open distance e-learning (ODeL) on Teacher Education. In addition, the article problematizes the shift as a policy imperative. Unisa's mandate to provide teacher education opportunities to…

An Evolution of Distance Learning Issues: From Exporting to Enhancing the Classroom Experience

ERIC Educational Resources Information Center

Johnstone, Sally M.

2004-01-01

There are many different formats being used for distance learning and each has implications for institutional and public policies. With almost 90% of U.S. public colleges and universities offering distance learning courses, it is important for all members of the academy to be aware of these implications as they consider their own involvement in…

Increasing Access to Higher Education through Open and Distance Learning: Empirical Findings from Mzuzu University, Malawi

ERIC Educational Resources Information Center

Chawinga, Winner Dominic; Zozie, Paxton Andrew

2016-01-01

Slowly but surely, open and distance learning (ODL) programmes are being regarded as one of the most practical ways that universities across the world are increasingly adopting in order to increase access to university education. Likewise, Mzuzu University (MZUNI) set up the Centre for Open and Distance Learning (CODL) to oversee the running of…

The Place of Multiple Intelligence in Achieving the Objectives and Goals of Open and Distance Learning Institutions: A Critical Analysis

ERIC Educational Resources Information Center

Ojo, Olugbenga David; Olakulehin, Felix Kayode

2006-01-01

This paper examined the nature of open and distance learning institutions as organizations where synergy of efforts of all personnel is required in order to achieve the aims and objectives of the institution. It explored the huge infrastructural and personnel requirements of distance learning institutions, especially at inception, and the…

Building Capacity for Open and Distance Learning (ODL) in West Africa Sub-Region: The Pivotal Role of RETRIDAL

ERIC Educational Resources Information Center

Amini, Clifford; Oluyide, Oluwaseun

2016-01-01

The paper posits the Regional Training and Research Institute for Distance and Open Learning (RETRIDAL) as an institution established for the purpose of enhancing Open and Distance Learning in the West African sub-region. The institute has pursued this mandate with an unparalleled vigour since its establishment in 2003--a partnership of the…

Quality Assurance in Open and Distance Learning. Knowledge Series. A Topical, Start-Up Guide to Distance Education Practice and Delivery

ERIC Educational Resources Information Center

Kirkpatrick, Denise

2005-01-01

Assuring the quality of education provision is a fundamental aspect of gaining and maintaining credibility for programmes, institutions and national systems of higher education worldwide. Despite a long and generally successful track record, open and distance learning (ODL) is still required to prove that the quality of student learning is at…

Factors Affecting Student Success in Distance Learning Courses at a Local California Community College: Joint Governance Perspectives

ERIC Educational Resources Information Center

Gonzalez, Luis A.

2012-01-01

The purpose of this study was to explore the perspectives of staff and faculty regarding factors affecting student success in distance learning at a California community college (CCC). Participants were members of the leadership group known as the distance learning committee. Data were collected through in-depth interviews using open-ended…

Two GH3 genes from longan are differentially regulated during fruit growth and development.

PubMed

Kuang, Jian-Fei; Zhang, Yu; Chen, Jian-ye; Chen, Qiu-Jin; Jiang, Yue-Ming; Lin, He-Tong; Xu, Shi-Juan; Lu, Wang-Jin

2011-10-01

In the present work, two full length cDNAs of GH3 genes, named DlGH3.1 and DlGH3.2 were cloned from pericarp and aril tissues of the longan fruit, respectively. Three conserved motifs, SSGTSAGERK, YASSE and YRVGD, as a characteristic of the acyladenylate/thioester forming enzyme superfamily were observed in DlGH3.1 and DlGH3.2 proteins. DlGH3.1 mainly expressed in pericarp tissues while DlGH3.2 accumulated in both the pericarp and aril tissues during fruit growth and development. In addition, NAA treatment induced the expression of DlGH3.1 and DlGH3.2 in the pericarp tissues at 21 and 77days after anthesis (DAA), while only DlGH3.2 in the aril tissues could be induced by NAA at 77DAA. More importantly, ABA and ethrel treatments suppressed the accumulations of DlGH3.1 and DlGH3.2 in the pericarp tissues of longan fruit at 21DAA (a rapid growth stage of pericarp), but enhanced DlGH3.2 expression in the aril tissues at 77DAA (a fruit ripening stage). Furthermore, the expression patterns of DlGH3.1 and DlGH3.2 showed different tissue specificity. Thus, our results suggest that DlGH3.1 gene expression might be associated with pericarp growth, while DlGH3.2 accumulation is likely to be related to both pericarp growth and fruit ripening, and the responses of DlGH3s to plant growth hormones are different and dependent on fruit development stage and fruit tissue. Copyright © 2011 Elsevier B.V. All rights reserved.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

Expanding Learning Opportunities for High School Students with Distance Learning

ERIC Educational Resources Information Center

Beese, Jane

2014-01-01

The purpose of the Synchronous Interactive Video Conference Distance Learning pilot program was to use emerging technologies to expand learning opportunities for students at an urban public high school. Through grant funding, students were able to enroll in Advanced Placement and foreign language courses through an online learning provider. Using…

New Learning Design in Distance Education: The Impact on Student Perception and Motivation

ERIC Educational Resources Information Center

Martens, Rob; Bastiaens, Theo; Kirschner, Paul A.

2007-01-01

Many forms of e-learning (such as online courses with authentic tasks and computer-supported collaborative learning) have become important in distance education. Very often, such e-learning courses or tasks are set up following constructivist design principles. Often, this leads to learning environments with authentic problems in ill-structured…

Increased Technology Provision and Learning: Giving More for Nothing?

ERIC Educational Resources Information Center

Quillerou, Emmanuelle

2011-01-01

The development of new communication technologies has led to a push for greater technology use for teaching and learning. This is most true for distance learning education, which relies heavily on new technologies. Distance learning students, however, seem to have very limited time available for studying and learning because of work and/or family…

Determinants of Student Satisfaction in Online Tutorial: A Study of A Distance Education Institution

ERIC Educational Resources Information Center

Harsasi, Meirani; Sutawijaya, Adrian

2018-01-01

Education system nowadays tends to utilize online learning, including in higher education. Online learning system becomes a major requirement in implementing learning process, including in Indonesia. Universitas Terbuka has implemented online learning system known as online tutorials to support the distance learning system. One interesting issue…

Enhancing Online Teaching and Learning from Students' Perspectives

ERIC Educational Resources Information Center

Edwards, Francisca

2014-01-01

The vast growth of technology has brought about new ways of learning. Distance learning has evolved over the years and, due to the growth of the Internet, has presented itself to be a growing phenomenon. Distance learning changed the way educational institutes and organizations train, learn, and do research. Past studies have shown academia's…

A position paper of the EFLM Committee on Education and Training and Working Group on Distance Education Programmes/E-Learning: developing an e-learning platform for the education of stakeholders in laboratory medicine.

PubMed

Gruson, Damien; Faure, Gilbert; Gouget, Bernard; Haliassos, Alexandre; Kisikuchin, Darya; Reguengo, Henrique; Topic, Elizabeta; Blaton, Victor

2013-04-01

The progress of information and communication technologies has strongly influenced changes in healthcare and laboratory medicine. E-learning, the learning or teaching through electronic means, contributes to the effective knowledge translation in medicine and healthcare, which is an essential element of a modern healthcare system and for the improvement of patient care. E-learning also represents a great vector for the transfer knowledge into laboratory practice, stimulate multidisciplinary interactions, enhance continuing professional development and promote laboratory medicine. The European Federation of Laboratory Medicine (EFLM) has initiated a distance learning program and the development of a collaborative network for e-learning. The EFLM dedicated working group encourages the organization of distance education programs and e-learning courses as well as critically evaluate information from courses, lectures and documents including electronic learning tools. The objectives of the present paper are to provide some specifications for distance learning and be compatible with laboratory medicine practices.

Adventure Learning: Transformative Hybrid Online Education

ERIC Educational Resources Information Center

Doering, Aaron

2006-01-01

Adventure learning (AL) is a hybrid distance education approach that provides students with opportunities to explore real-world issues through authentic learning experiences within collaborative learning environments. This article defines this online distance education approach, outlines an AL framework, and showcases an AL archetype. In AL…

In a year, memory will benefit from learning, tomorrow it won't: distance and construal level effects on the basis of metamemory judgments.

PubMed

Halamish, Vered; Nussinson, Ravit; Ben-Ari, Liat

2013-09-01

Metamemory judgments may rely on 2 bases of information: subjective experience and abstract theories about memory. On the basis of construal level theory, we predicted that psychological distance and construal level (i.e., concrete vs. abstract thinking) would have a qualitative impact on the relative reliance on these 2 bases: When considering learning from proximity or under a low-construal mindset, learners would rely more heavily on their experience, whereas when considering learning from a distance or under a high-construal mindset, they would rely more heavily on their abstract theories. Consistent with this prediction, results of 2 experiments revealed that temporal distance (Experiment 1) and construal level (Experiment 2) affected the stability bias--the failure to predict the benefits of learning. When considering learning from proximity or using a low-construal mindset, participants relied less heavily on their theory regarding the benefits of learning and were therefore insensitive to future learning. However, when considering learning from temporal distance or using a high-construal mindset, participants relied more heavily on their theory and were therefore better able to predict the benefits of future learning, thus overcoming the stability bias. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Distance Learning Can Be as Effective as Traditional Learning for Medical Students in the Initial Assessment of Trauma Patients.

PubMed

Farahmand, Shervin; Jalili, Ebrahim; Arbab, Mona; Sedaghat, Mojtaba; Shirazi, Mandana; Keshmiri, Fatemeh; Azizpour, Arsalan; Valadkhani, Somayeh; Bagheri-Hariri, Shahram

2016-09-01

Distance learning is expanding and replacing the traditional academic medical settings. Managing trauma patients seems to be a prerequisite skill for medical students. This study has been done to evaluate the efficiency of distance learning on performing the initial assessment and management in trauma patients, compared with the traditional learning among senior medical students. One hundred and twenty senior medical students enrolled in this single-blind quasi-experimental study and were equally divided into the experimental (distance learning) and control group (traditional learning). All participants did a written MCQ before the study. The control group attended a workshop with a 50-minute lecture on initial management of trauma patients and a case simulation scenario followed by a hands-on session. On the other hand, the experimental group was given a DVD with a similar 50-minute lecture and a case simulation scenario, and they also attended a hands-on session to practice the skills. Both groups were evaluated by a trauma station in an objective structured clinical examination (OSCE) after a month. The performance in the experimental group was statistically better (P=0.001) in OSCE. Distance learning seems to be an appropriate adjunct to traditional learning.

Deep learning architectures for multi-label classification of intelligent health risk prediction.

PubMed

Maxwell, Andrew; Li, Runzhi; Yang, Bei; Weng, Heng; Ou, Aihua; Hong, Huixiao; Zhou, Zhaoxian; Gong, Ping; Zhang, Chaoyang

2017-12-28

Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients could have symptoms of multiple different diseases at the same time and it is important to develop tools that help to identify problems early. Intelligent health risk prediction models built with deep learning architectures offer a powerful tool for physicians to identify patterns in patient data that indicate risks associated with certain types of chronic diseases. Physical examination records of 110,300 anonymous patients were used to predict diabetes, hypertension, fatty liver, a combination of these three chronic diseases, and the absence of disease (8 classes in total). The dataset was split into training (90%) and testing (10%) sub-datasets. Ten-fold cross validation was used to evaluate prediction accuracy with metrics such as precision, recall, and F-score. Deep Learning (DL) architectures were compared with standard and state-of-the-art multi-label classification methods. Preliminary results suggest that Deep Neural Networks (DNN), a DL architecture, when applied to multi-label classification of chronic diseases, produced accuracy that was comparable to that of common methods such as Support Vector Machines. We have implemented DNNs to handle both problem transformation and algorithm adaption type multi-label methods and compare both to see which is preferable. Deep Learning architectures have the potential of inferring more information about the patterns of physical examination data than common classification methods. The advanced techniques of Deep Learning can be used to identify the significance of different features from physical examination data as well as to learn the contributions of each feature that impact a patient's risk for chronic diseases. However, accurate prediction of chronic disease risks remains a challenging problem that warrants further studies.

Veterinary parasitology teaching at London - Meeting the 'Day-One Competency' needs of new veterinarians.

PubMed

Fox, Mark; Blake, Damer; Jacobs, Dennis

2018-04-30

Over the past four decades, there has been an exponential increase in veterinary parasitology knowledge, coinciding with the advent of molecular biology in research. Therefore, it is unrealistic for teachers to expect students to graduate with an encyclopaedic knowledge of the subject. As a result, a new curriculum was introduced at The Royal Veterinary College (University of London) in 2007, designed to meet the needs of our new graduates, i.e. RCVS Day-One Competences. The aims of this curriculum are, inter alia, to ensure that new graduates have an up-to-date body of core knowledge and are able to apply such knowledge and newly-acquired information to scientific and clinical problem-solving. Veterinary parasitology is taught primarily in Year 2, following a brief introduction in Year 1; clinical aspects are covered in Year 3, with original research projects undertaken in Years 4 and 5. Parasitology is taught in parallel with other subjects, enabling both horizontal and vertical integration. Core material is provided in lectures supplemented by directed learning (DL) in small groups and interactive, clinical scenario-based practical classes. Student learning is supported by Moodle 3.2 (Virtual Learning Environment [VLE], RVC Learn) which provides access to an on-line study guide (annotated using Adobe Reader), PowerPoint presentations with synchronized lecturer commentary (Echo Active Learning Platform [ALP]), detailed feedback for DL and practical classes, parasite 'potcasts' and CAL packages, and a Clinical Skills Centre. A parasitology textbook has also been published recently to support courses taught at the College. Assessment of student learning is achieved using a variety of written formats (essay, problem-solving questions [PSQ], multiple choice questions [MCQ] and extended matching questions [EMQ]), integrated oral examinations and objective structured clinical examinations (OSCEs). Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Prefrontal Neurons Encode a Solution to the Credit-Assignment Problem

PubMed Central

Perge, János A.; Eskandar, Emad N.

2017-01-01

To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects. SIGNIFICANCE STATEMENT Credit assignment is the process by which we infer the causes of our successes and failures. We found that neuronal activity in the dorsolateral prefrontal cortex conveyed the necessary information for performing credit assignment. Importantly, while there are various potential mechanisms to retain a “trace” of the causal events over time, we observed that spiking activity was sufficiently stable to act as the link between causes and effects, in contrast to prior reports that suggested spiking representations were unstable over time. In addition, we observed that this stability varied as a function of learning, such that the neural code was more reliable over time during early learning, when it was most needed. PMID:28634307

Performance of the CONTOUR® TS Blood Glucose Monitoring System.

PubMed

Frank, Joy; Wallace, Jane F; Pardo, Scott; Parkes, Joan Lee

2011-01-01

Self-monitoring of blood glucose (SMBG) remains an important component of diabetes management, engendering a need for affordable blood glucose (BG) meters that are accurate, precise, and convenient. The CONTOUR® TS is a BG meter that endeavors to meet this need. It uses glucose dehydrogenase/flavin dinucleotide chemistry, automatic test strip calibration, and autocompensation for hematocrit along with the ease of use that has come to be expected of a modern meter. The objective of this clinical trial was to determine whether the CONTOUR TS system met these criteria. The system was evaluated at a single clinical site with 106 subjects with type 1 or type 2 diabetes. Blood glucose values ranged from 60 to 333 mg/dl over all subjects. Both lay users and health care professionals (HCPs) tested the meters, with test strips from three different lots. Results were compared to a reference analyzer of verified precision and accuracy. Forty-nine of the subjects also participated in a home study of the meter. Lay users learned to use the system without assistance and were surveyed on its use at the end of the study. When used with capillary blood, both subjects and HCPs obtained results that exceeded the International Organization for Standardization 15197:2003 criteria, (i.e., ≥95% of values fell within 20% or 15 mg/dl of the laboratory value for BG levels greater than or less than 75 mg/dl, respectively). Specifically, lay users achieved 97.9% and HCPs 98.6%. When used with venous blood, 99.8% of measurements were within the criteria. All measurements for both capillary and venous blood fell into zones A or B of the Parkes error grid, deemed clinically accurate. Hematocrit was found to have no influence on BG measurements. A large majority of the subjects found the system easy to learn and to use. The CONTOUR TS BG meter system gave accurate and reproducible results with both capillary and venous blood; subjects learned to use the meter system by following the user guide and quick reference guide. © 2010 Diabetes Technology Society.

Self-Learning through Programmed Learning in Distance Mode.

ERIC Educational Resources Information Center

Rao, D. Prakasa; Reddy, B. Sudhakar

2002-01-01

Presents the characteristics and development of self-learning material (SLM) in distance education. Discusses teaching with programmed learning; structure of SLM; and how SLM helps in self-study. Discusses the advantages of print materials as accompanying programmed instruction, because they are portable, well-structured, compact, and easily…

Cooperative Learning in Distance Learning: A Mixed Methods Study

ERIC Educational Resources Information Center

Kupczynski, Lori; Mundy, Marie Anne; Goswami, Jaya; Meling, Vanessa

2012-01-01

Distance learning has facilitated innovative means to include Cooperative Learning (CL) in virtual settings. This study, conducted at a Hispanic-Serving Institution, compared the effectiveness of online CL strategies in discussion forums with traditional online forums. Quantitative and qualitative data were collected from 56 graduate student…

A Question of Questions.

ERIC Educational Resources Information Center

Fenwick, John; McMillan, Rod

In a conventional teaching situation, a lecturer may use a wide range of questioning techniques aimed at helping students to become active learners. In distance learning, students are often isolated and have limited opportunities for interaction in a social learning environment. Hence, learning strategies in distance learning need to be structured…

Combining Feminist Pedagogy and Transactional Distance to Create Gender-Sensitive Technology-Enhanced Learning

ERIC Educational Resources Information Center

Herman, Clem; Kirkup, Gill

2017-01-01

In this paper, we argue for a new synthesis of two pedagogic theories: feminist pedagogy and transactional distance, which explain why and how distance education has been such a positive system for women in a national distance learning university. We illustrate this with examples of positive action initiatives for women. The concept of…

Assessment of the Effectiveness of Internet-Based Distance Learning through the VClass e-Education Platform

ERIC Educational Resources Information Center

Pukkaew, Chadchadaporn

2013-01-01

This study assesses the effectiveness of internet-based distance learning (IBDL) through the VClass live e-education platform. The research examines (1) the effectiveness of IBDL for regular and distance students and (2) the distance students' experience of VClass in the IBDL course entitled Computer Programming 1. The study employed the common…

Distance Teaching of Environmental Engineering Courses at the Open University.

ERIC Educational Resources Information Center

Porteous, Andrew; Nesaratnam, Suresh T.; Anderson, Judith

1997-01-01

Describes two integrated distance learning environmental engineering degree courses offered by the environmental engineering group of the Open University in Great Britain. Discusses admission requirements for courses, advantages offered by distance learning, professional accreditation, site visits, and tutors. (AIM)

Embracing Change: Adapting and Evolving Your Distance Learning Library Services to Meet the New ACRL Distance Learning Library Services Standards

ERIC Educational Resources Information Center

Marcum, Brad

2016-01-01

This article examines the update and revision of the current Association of College and Research Libraries (ACRL) Distance Learning Standards that has been proposed and submitted to the ACRL Standards Committee. An in-depth analysis of the update is included, along with some comparisons between the old and new. Practical advice detailing…

Open and Distance Learning: Case Studies from Industry and Education. Open and Distance Learning Series.

ERIC Educational Resources Information Center

Brown, Stephen C., Ed.

This book contains 14 case studies, written by those involved in the teaching and training initiatives, that illustrate the use of open and distance learning strategies. The case studies, drawn from many parts of the world (but mostly British based), feature efforts in large and small companies in a variety of industries. The first part of the…

The Relationship between Academic Integration and Student Success in Distance Learning in the Kentucky Community and Technical College System

ERIC Educational Resources Information Center

Johnson, Robert White

2009-01-01

This dissertation is a study of factors that contribute to dropout from distance learning classes in the Kentucky Community and Technical College System (KCTCS). It is divided into five chapters. Chapter One gives a history of distance learning through in KCTCS. It includes the background of the study, statement of the problem, purpose of the…

Exploring Distance Learning Experiences of In-Service Music Teachers from Puerto Rico in a Master's Program

ERIC Educational Resources Information Center

Vega-Martinez, Juan Carlos

2013-01-01

The purpose of this study was to explore the experiences of in-service music teachers who chose to pursue a master's degree in music education through distance learning. In this study, I examined the motivations of in-service music teachers for choosing to pursue a master's degree in music education through distance learning; the benefits teachers…

Increasing health worker capacity through distance learning: a comprehensive review of programmes in Tanzania.

PubMed

Nartker, Anya J; Stevens, Liz; Shumays, Alyson; Kalowela, Martin; Kisimbo, Daniel; Potter, Katy

2010-12-31

Tanzania, like many developing countries, faces a crisis in human resources for health. The government has looked for ways to increase the number and skills of health workers, including using distance learning in their training. In 2008, the authors reviewed and assessed the country's current distance learning programmes for health care workers, as well as those in countries with similar human resource challenges, to determine the feasibility of distance learning to meet the need of an increased and more skilled health workforce. Data were collected from 25 distance learning programmes at health training institutions, universities, and non-governmental organizations throughout the country from May to August 2008. Methods included internet research; desk review; telephone, email and mail-in surveys; on-site observations; interviews with programme managers, instructors, students, information technology specialists, preceptors, health care workers and Ministry of Health and Social Welfare representatives; and a focus group with national HIV/AIDS care and treatment organizations. Challenges include lack of guidelines for administrators, instructors and preceptors of distance learning programmes regarding roles and responsibilities; absence of competencies for clinical components of curricula; and technological constraints such as lack of access to computers and to the internet. Insufficient funding resulted in personnel shortages, lack of appropriate training for personnel, and lack of materials for students.Nonetheless, current and prospective students expressed overwhelming enthusiasm for scale-up of distance learning because of the unique financial and social benefits offered by these programs. Participants were retained as employees in their health care facilities, and remained in their communities and supported their families while advancing their careers. Space in health training institutions was freed up for new students entering in-residence pre-service training. A blended print-based distance learning model is most feasible at the national level due to current resource and infrastructure constraints. With an increase in staffing; improvement of infrastructure, coordination and curricula; and decentralization to the zonal or district level, distance learning can be an effective method to increase both the skills and the numbers of qualified health care workers capable of meeting the health care needs of the Tanzanian population.

Increasing health worker capacity through distance learning: a comprehensive review of programmes in Tanzania

PubMed Central

2010-01-01

Background Tanzania, like many developing countries, faces a crisis in human resources for health. The government has looked for ways to increase the number and skills of health workers, including using distance learning in their training. In 2008, the authors reviewed and assessed the country's current distance learning programmes for health care workers, as well as those in countries with similar human resource challenges, to determine the feasibility of distance learning to meet the need of an increased and more skilled health workforce. Methods Data were collected from 25 distance learning programmes at health training institutions, universities, and non-governmental organizations throughout the country from May to August 2008. Methods included internet research; desk review; telephone, email and mail-in surveys; on-site observations; interviews with programme managers, instructors, students, information technology specialists, preceptors, health care workers and Ministry of Health and Social Welfare representatives; and a focus group with national HIV/AIDS care and treatment organizations. Results Challenges include lack of guidelines for administrators, instructors and preceptors of distance learning programmes regarding roles and responsibilities; absence of competencies for clinical components of curricula; and technological constraints such as lack of access to computers and to the internet. Insufficient funding resulted in personnel shortages, lack of appropriate training for personnel, and lack of materials for students. Nonetheless, current and prospective students expressed overwhelming enthusiasm for scale-up of distance learning because of the unique financial and social benefits offered by these programs. Participants were retained as employees in their health care facilities, and remained in their communities and supported their families while advancing their careers. Space in health training institutions was freed up for new students entering in-residence pre-service training. Conclusions A blended print-based distance learning model is most feasible at the national level due to current resource and infrastructure constraints. With an increase in staffing; improvement of infrastructure, coordination and curricula; and decentralization to the zonal or district level, distance learning can be an effective method to increase both the skills and the numbers of qualified health care workers capable of meeting the health care needs of the Tanzanian population. PMID:21194417

The Development of Online Tutorial Program Design Using Problem-Based Learning in Open Distance Learning System

ERIC Educational Resources Information Center

Said, Asnah; Syarif, Edy

2016-01-01

This research aimed to evaluate of online tutorial program design by applying problem-based learning Research Methods currently implemented in the system of Open Distance Learning (ODL). The students must take a Research Methods course to prepare themselves for academic writing projects. Problem-based learning basically emphasizes the process of…

Language Learning Strategies Used by Distance Learners of English: A Study with a Group of Turkish Distance Learners of EFL

ERIC Educational Resources Information Center

Altunay, Dilek

2014-01-01

Use of language learning strategies is important for language learning. Some researchers state that language learning strategies are important because their use affects the development of communicative competence (Lessard-Clouston, 1997 & Oxford, 1990). Effective use of language learning strategies has particular importance for distance…

Integrated methods for teaching population health.

PubMed

Sistrom, Maria Gilson; Zeigen, Laura; Jones, Melissa; Durham, Korana Fiol; Boudrot, Thomas

2011-01-01

The Institute of Medicine recommends reforms to public health education to better prepare the public health workforce. This study addresses the application of two of the recommended reforms in the population health nursing curriculum at one university: use of an ecological model and distance learning methods. Using interdisciplinary faculty, integrated teaching and learning methods, and a multimedia curriculum, this study examined the following question: can distance learning be designed to support learning goals and outcomes specific to an ecological approach and population health concepts in general? Course content was evaluated using students' perception of practice utility and understanding of population health concepts. Integrated teaching methods were evaluated using a scale as well as comparison to other student distance learning experiences within the university. Findings demonstrated that both the ecological model and distance learning methods were successfully used to teach population health to a large nursing student cohort. 2011, SLACK Incorporated.

The child brain computes and utilizes internalized maternal choices

PubMed Central

Lim, Seung-Lark; Cherry, J. Bradley C.; Davis, Ann M.; Balakrishnan, S. N.; Ha, Oh-Ryeong; Bruce, Jared M.; Bruce, Amanda S.

2016-01-01

As children grow, they gradually learn how to make decisions independently. However, decisions like choosing healthy but less-tasty foods can be challenging for children whose self-regulation and executive cognitive functions are still maturing. We propose a computational decision-making process in which children estimate their mother's choices for them as well as their individual food preferences. By employing functional magnetic resonance imaging during real food choices, we find that the ventromedial prefrontal cortex (vmPFC) encodes children's own preferences and the left dorsolateral prefrontal cortex (dlPFC) encodes the projected mom's choices for them at the time of children's choice. Also, the left dlPFC region shows an inhibitory functional connectivity with the vmPFC at the time of children's own choice. Our study suggests that in part, children utilize their perceived caregiver's choices when making choices for themselves, which may serve as an external regulator of decision-making, leading to optimal healthy decisions. PMID:27218420

Bridging the Learning Gap: Cross-Cultural Learning and Teaching through Distance

ERIC Educational Resources Information Center

Mullings, Delores V.

2015-01-01

This project engaged students, practitioners, and educators from University of Labor and Social Affairs, Cau Giay District, Hanoi and Newfoundland and Labrador, Canada, in a cross-cultural distance learning and teaching collaboration. Two groups met simultaneously through Skype videoconferencing to discuss and learn about field supervision and…

The Effect of Professor's Attractiveness on Distance Learning Students

ERIC Educational Resources Information Center

Liu, Jeanny; Tomasi, Stella D.

2015-01-01

Technology enabled learning is becoming more popular and pervasive in education. While the effectiveness of distance learning versus traditional classroom education is strongly debated, human factors such as students' perception of their professors can influence their desire to learn. This research examines the perceptual effect of attractive…

Online Collaborative Learning in Health Care Education

ERIC Educational Resources Information Center

Westbrook, Catherine

2012-01-01

At our University, the Faculty of Health, Social Care and Education has delivered a variety of undergraduate and postgraduate courses via flexible distance learning for many years. Distance learning can be a lonely experience for students who may feel isolated and unsupported. However e-learning provides an opportunity to use technology to…

Mobile Learning: From Single Project Status into the Mainstream?

ERIC Educational Resources Information Center

Zawacki-Richter, Olaf; Brown, Tom; Delport, Rhena

2009-01-01

During recent years, many distance teaching as well as residential institutions have started to experiment with mobile learning through pilot projects as part of their e-learning and technology enhanced learning environments. The practical experience gained with the employment of strategies and approaches within distance education can assist with…

A "Virtual Fieldtrip": Service Learning in Distance Education Technical Writing Courses

ERIC Educational Resources Information Center

Soria, Krista M.; Weiner, Brad

2013-01-01

This mixed-methods experimental study examined the effect of service learning in a distance education technical writing course. Quantitative analysis of data found evidence for a positive relationship between participation in service learning and technical writing learning outcomes. Additionally, qualitative analysis suggests that service learning…

Exploring Moodle Functionality for Managing Open Distance Learning E-Assessments

ERIC Educational Resources Information Center

Koneru, Indira

2017-01-01

Current and emerging technologies enable Open Distance Learning (ODL) institutions integrate e-Learning in innovative ways and add value to the existing teaching-learning and assessment processes. ODL e-Assessment systems have evolved from Computer Assisted/Aided Assessment (CAA) systems through intelligent assessment and feedback systems.…

Simulation Training: Evaluating the Instructor’s Contribution to a Wizard of Oz Simulator in Obstetrics and Gynecology Ultrasound Training

PubMed Central

Tepper, Ronnie

2017-01-01

Background Workplaces today demand graduates who are prepared with field-specific knowledge, advanced social skills, problem-solving skills, and integration capabilities. Meeting these goals with didactic learning (DL) is becoming increasingly difficult. Enhanced training methods that would better prepare tomorrow’s graduates must be more engaging and game-like, such as feedback based e-learning or simulation-based training, while saving time. Empirical evidence regarding the effectiveness of advanced learning methods is lacking. Objective quantitative research comparing advanced training methods with DL is sparse. Objectives This quantitative study assessed the effectiveness of a computerized interactive simulator coupled with an instructor who monitored students’ progress and provided Web-based immediate feedback. Methods A low-cost, globally accessible, telemedicine simulator, developed at the Technion—Israel Institute of Technology, Haifa, Israel—was used. A previous study in the field of interventional cardiology, evaluating the efficacy of the simulator to enhanced learning via knowledge exams, presented promising results of average scores varying from 94% after training and 54% before training (n=20) with P<.001. Two independent experiments involving obstetrics and gynecology (Ob-Gyn) physicians and senior ultrasound sonographers, with 32 subjects, were conducted using a new interactive concept of the WOZ (Wizard of OZ) simulator platform. The contribution of an instructor to learning outcomes was evaluated by comparing students’ knowledge before and after each interactive instructor-led session as well as after fully automated e-learning in the field of Ob-Gyn. Results from objective knowledge tests were analyzed using hypothesis testing and model fitting. Results A significant advantage (P=.01) was found in favor of the WOZ training approach. Content type and training audience were not significant. Conclusions This study evaluated the contribution of an integrated teaching environment using a computerized interactive simulator, with an instructor providing immediate Web-based immediate feedback to trainees. Involvement of an instructor in the simulation-based training process provided better learning outcomes that varied training content and trainee populations did not affect the overall learning gains. PMID:28432039

[Distance learning in postgraduate training of professionals. Example of occupational medicine specialization].

PubMed

Marcinkiewicz, Andrzej; Cybart, Adam; Chromińska-Szosland, Dorota

2002-01-01

The rapid development of science, technology, economy and the society has one along with the wide recognition of lifelong education and learning society concepts. Scientific centres worldwide conduct research how the access to the information and multimedia technology could bring about positive changes in our lives including improvement in education and the learning environment. Mankind development in conformity with social progress and sustainable development faces a new educational concept of learning society and open education in the information age, supported with multimedia and data processing technology. Constrains in resources availability for broadening the access to education had led to search for alternative, more time and cost-effective systems of education. One of them is distance learning, applied with success in many countries. The benefits of distance learning are well proven and can be extended to occupational medicine. Major advantages include: the integration of studies with work experience, flexibility, allowing studies to be matched to work requirements, perceived work and leisure timing, continuity of career progression. Likewise is in Poland this form of education becomes more and more popular. The distance education systems have been seen as an investment in human resource development. The vast variety of courses and educational stages makes possible the modern method of knowledge to be easily accessible. Experience of the School of Public Health in Łódź in distance learning had shown remarkable benefits of the method with comparable quality of intramural and distance learning in respect of the knowledge and experience gained by students.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Carob pod insoluble fiber exerts anti-atherosclerotic effects in rabbits through sirtuin-1 and peroxisome proliferator-activated receptor-γ coactivator-1α.

PubMed

Valero-Muñoz, María; Martín-Fernández, Beatriz; Ballesteros, Sandra; Lahera, Vicente; de las Heras, Natalia

2014-09-01

The aim of this study was to evaluate the potential effects of an insoluble dietary fiber from carob pod (IFC) (1 g ⋅ kg(-1) ⋅ d(-1) in the diet) on alterations associated with atherosclerosis in rabbits with dyslipidemia. Male New Zealand rabbits (n = 30) were fed the following diets for 8 wk: 1) a control diet (SF412; Panlab) as a control group representing normal conditions; 2) a control supplemented with 0.5% cholesterol + 14% coconut oil (DL) (SF302; Panlab) for 8 wk as a dyslipidemic group; and 3) a control containing 0.5% cholesterol + 14% coconut oil plus IFC (1 g ⋅ kg(-1) ⋅ d(-1)) (DL+IFC) for 8 wk. IFC was administered in a pellet mixed with the DL diet. The DL-fed group developed mixed dyslipidemia and atherosclerotic lesions, which were associated with endothelial dysfunction, inflammation, and fibrosis. Furthermore, sirtuin-1 (SIRT1) and peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) protein expression in the aorta were reduced to 77% and 63% of the control group, respectively (P < 0.05), in these rabbits. Administration of IFC to DL-fed rabbits reduced the size of the aortic lesion significantly (DL, 15.2% and DL+IFC, 2.6%) and normalized acetylcholine-induced relaxation (maximal response: control, 89.3%; DL, 61.6%; DL+IFC, 87.1%; P < 0.05) and endothelial nitric oxide synthase expression (DL, 52% and DL+IFC, 104% of the control group). IFC administration to DL-fed rabbits also reduced cluster of differentiation 36 (DL, 148% and DL+IFC, 104% of the control group; P < 0.05), plasminogen activator inhibitor-1 (DL, 141% and DL+IFC, 107% of the control group), tumor necrosis factor-α (DL, 166% and DL+IFC, 120% of the control group), vascular cell adhesion molecule-1 (DL, 153% and DL+IFC, 110% of the control group), transforming growth factor-β (DL, 173% and DL+IFC, 99% of the control group), and collagen I (DL, 157% and DL+IFC, 112% of the control group) in the aorta. These effects were accompanied by an enhancement of SIRT1 and PGC-1α (160% and 121% of the control group, respectively; P < 0.05) vascular expression. In summary, we demonstrated for the first time, to our knowledge, that administration of IFC reduces the development of atherosclerosis in rabbits. This effect seems to be related to an improvement in endothelial function and a reduction of inflammation and fibrosis, most probably as a consequence of the reduction of serum concentrations of cholesterol and triglycerides. Increased expression of aortic SIRT1 and PGC-1α could play an important role in the observed effects of IFC in rabbits with dyslipidemia. © 2014 American Society for Nutrition.

Person re-identification over camera networks using multi-task distance metric learning.

PubMed

Ma, Lianyang; Yang, Xiaokang; Tao, Dacheng

2014-08-01

Person reidentification in a camera network is a valuable yet challenging problem to solve. Existing methods learn a common Mahalanobis distance metric by using the data collected from different cameras and then exploit the learned metric for identifying people in the images. However, the cameras in a camera network have different settings and the recorded images are seriously affected by variability in illumination conditions, camera viewing angles, and background clutter. Using a common metric to conduct person reidentification tasks on different camera pairs overlooks the differences in camera settings; however, it is very time-consuming to label people manually in images from surveillance videos. For example, in most existing person reidentification data sets, only one image of a person is collected from each of only two cameras; therefore, directly learning a unique Mahalanobis distance metric for each camera pair is susceptible to over-fitting by using insufficiently labeled data. In this paper, we reformulate person reidentification in a camera network as a multitask distance metric learning problem. The proposed method designs multiple Mahalanobis distance metrics to cope with the complicated conditions that exist in typical camera networks. We address the fact that these Mahalanobis distance metrics are different but related, and learned by adding joint regularization to alleviate over-fitting. Furthermore, by extending, we present a novel multitask maximally collapsing metric learning (MtMCML) model for person reidentification in a camera network. Experimental results demonstrate that formulating person reidentification over camera networks as multitask distance metric learning problem can improve performance, and our proposed MtMCML works substantially better than other current state-of-the-art person reidentification methods.

Benefits, barriers, and intentions/desires of nurses related to distance learning in rural island communities.

PubMed

Kataoka-Yahiro, Merle R; Richardson, Karol; Mobley, Joseph

2011-03-01

This study assessed distance learning needs among nurses on the Neighbor Islands in Hawaii. An exploratory study was conducted using a descriptive qualitative design. Of the 37 nurses who completed the study, 7 were nurse administrators and 30 were staff nurses. There were 18 focus groups of nurses recruited from six public hospitals on the Neighbor Islands. Three major themes related to distance learning emerged in this study: benefits, barriers, and intentions/desires. Each major theme had several linkages to categories and subcategories. Overall findings were as follows: (1) cost was mentioned more often in three major thematic areas (benefit, barriers, and intentions/desires); (2) the need to revisit and address current curriculum approaches and practices in distance learning programs was identified; and (3) strong recommendations were made for programs and organizational support for distance learning in hospital settings. These findings have implications for nursing research, education, and practice. Copyright 2011, SLACK Incorporated.

Teaching differential diagnosis to nurse practitioner students in a distance program.

PubMed

Colella, Christine L; Beery, Theresa A

2014-08-01

An interactive case study (ICS) is a novel way to enhance the teaching of differential diagnosis to distance learning nurse practitioner students. Distance education renders the use of many teaching strategies commonly used with face-to-face students difficult, if not impossible. To meet this new pedagogical dilemma and to provide excellence in education, the ICS was developed. Kolb's theory of experiential learning supported efforts to follow the utilization of the ICS. This study sought to determine whether learning outcomes for the distance learning students were equivalent to those of on-campus students who engaged in a live-patient encounter. Accuracy of differential diagnosis lists generated by onsite and online students was compared. Equivalency testing assessed clinical, rather than only statistical, significance in data from 291 students. The ICS responses from the distance learning and onsite students differed by 4.9%, which was within the a priori equivalence estimate of 10%. Narrative data supported the findings. Copyright 2014, SLACK Incorporated.

Effects of intrahippocampal aniracetam treatment on Y-maze avoidance learning performance and behavioral long-term potentiation in dentate gyrus in rat.

PubMed

Rao, Y; Xiao, P; Xu, S

2001-02-09

Effects of intrahippocampal treatment of aniracetam, a selective agonist for DL-alpha-amino-3-hydroxy-5-methyl-4-isoxazoleproionic acid (AMPA) receptors, on Y-maze avoidance learning task and behavioral long-term potentiation (LTP) in perforant path-dentate gyrus were studied in freely moving rats by using in vivo electrophysiology combined with behavioral tests. The results were as follows: (1) intrahippocampal treatment of aniracetam reversibly enhanced basal synaptic transmission in perforant path to dentate gyrus in a dosage dependent manner; (2) aniracetam produced improvement in Y-maze learning performance when administration occurred 5 min prior to maze learning; (3) aniracetam administration significantly facilitated behavioral LTP in dentate gyrus, while the maximal amplitude of LTP has no significant difference when compared to saline group. The present results indicate that hippocampal AMPA receptors are involved in learning and memory.

A Security Framework for Online Distance Learning and Training.

ERIC Educational Resources Information Center

Furnell, S. M.; Onions, P. D.; Bleimann, U.; Gojny, U.; Knahl, M.; Roder, H. F.; Sanders, P. W.

1998-01-01

Presents a generic reference model for online distance learning and discusses security issues for each stage (enrollment, study, completion, termination, suspension). Discusses a security framework (authentication and accountability, access control, intrusion detection, network communications, nonrepudiation, learning resources provider…

Convergent Technologies in Distance Learning Delivery.

ERIC Educational Resources Information Center

Wheeler, Steve

1999-01-01

Describes developments in British education in distance learning technologies. Highlights include networking the rural areas; communication, community, and paradigm shifts; digital compression techniques and telematics; Web-based material delivered over the Internet; system flexibility; social support; learning support; videoconferencing; and…

The Experience of a Distance Learning Organization in a Private Higher Educational Institution in the Republic of Tatarastan (Russia): From Idea to Realization

ERIC Educational Resources Information Center

Akhmetova, Daniya; Vorontsova, Liliya; Morozova, Ilona Gennadyevna

2013-01-01

The article is devoted to the unique experience of distance learning development in the conditions of Russian reality. The model of distance learning in the Institute of Economics, Management and Law (Kazan city, Russia) is created on the basis of educational sphere diagnosis taking into account foreign and Russian experience. The specificity of…

Learning Design Implementation for Distance e-Learning: Blending Rapid e-Learning Techniques with Activity-Based Pedagogies to Design and Implement a Socio-Constructivist Environment

ERIC Educational Resources Information Center

Santally, Mohammad Issack; Rajabalee, Yousra; Cooshna-Naik, Dorothy

2012-01-01

This paper discusses how modern technologies are changing the teacher-student-content relationships from the conception to the delivery of so-called "distance" education courses. The concept of Distance Education has greatly evolved in the digital era of 21st Century. With the widespread use and access to the Internet, exponential growth…

The Impact of ICT in Learning through Distance Education Programmes at Zimbabwe Open University (ZOU): Roles of ICT in Learning through Distance Education Programmes

ERIC Educational Resources Information Center

Mpofu, John; Chimhenga, Sylod; Mafa, Onias

2013-01-01

Zimbabwe Distance Open University is enrols students from both urban and rural settings. The majority of students living and working in rural areas have limited or no access to computers and electricity as a result the use of information and communication technology (ICT) in the learning process is very limited. Though government has realized the…

Meeting the Needs of Distance Learners of M.Ed Program: Bangladesh Open University Perspective

ERIC Educational Resources Information Center

Islam, Amirul; Ferdowsi, Sakiba

2014-01-01

This study draws on the experience of a cohort of 22 students from 09 tutorial centers enrolled in a Master of Education (M Ed) distance learning program administered by the Bangladesh Open University (BOU). It's purpose is to locate the aims and philosophies of distance learning within the experiences of actual distance learners in order to see…

Review and Content Analysis of the "International Review of Research in Open and Distance/Distributed Learning" (2000-2015)

ERIC Educational Resources Information Center

Zawacki-Richter, Olaf; Alturki, Uthman; Aldraiweesh, Ahmed

2017-01-01

This paper presents a review of distance education literature published in the "International Review of Research in Open and Distance/Distributed Learning" (IRRODL) to describe the status thereof and to identify gaps and priority areas in distance education research based on a validated classification of research areas. All articles (N =…

Developing Transactional Distance Scale and Examining Transactional Distance Perception of Blended Learning Students in Terms of Different Variables

ERIC Educational Resources Information Center

Horzum, Mehmet Baris

2011-01-01

The first purpose of this study was to develop valid and reliable a scale which measure the transactional distance. Besides, the second purpose of the study was to investigate whether the transactional distance perception differed according to gender, utilized component and number of logins to system, and also blended learning was useful. The…

Reliability and Validity of a Student Scale for Assessing the Quality of Internet-Based Distance Learning

ERIC Educational Resources Information Center

Scanlan, Craig L.

2003-01-01

U.S. universities and colleges offering distance education courses have increased immensely since 1998, and by 2004 it was expected that distance learners will constitute about 14% of all those enrolled in degree programs. In its preliminary review of distance learning, the Institute for Higher Education Policy (1998) emphasized the need for…

The impact of rigorous mathematical thinking as learning method toward geometry understanding

NASA Astrophysics Data System (ADS)

Nugraheni, Z.; Budiyono, B.; Slamet, I.

2018-05-01

To reach higher order thinking skill, needed to be mastered the conceptual understanding. RMT is a unique realization of the cognitive conceptual construction approach based on Mediated Learning Experience (MLE) theory by Feurstein and Vygotsky’s sociocultural theory. This was quasi experimental research which was comparing the experimental class that was given Rigorous Mathematical Thinking (RMT) as learning method and control class that was given Direct Learning (DL) as the conventional learning activity. This study examined whether there was different effect of two learning method toward conceptual understanding of Junior High School students. The data was analyzed by using Independent t-test and obtained a significant difference of mean value between experimental and control class on geometry conceptual understanding. Further, by semi-structure interview known that students taught by RMT had deeper conceptual understanding than students who were taught by conventional way. By these result known that Rigorous Mathematical Thinking (RMT) as learning method have positive impact toward Geometry conceptual understanding.

A Review of Benefits and Limitations of Online Learning in the Context of the Student, the Instructor, and the Tenured Faculty

ERIC Educational Resources Information Center

Appana, Subhashni

2008-01-01

Distance education is a formal learning activity, which occurs when students and instructors are separated by geographic distance or by time. Learning is supported by communications technology such as television, videotape, computers, e-mail, and mail. Online learning is any learning experience or environment that relies upon the Internet/World…

Pervasive, Lifestyle-Integrated Mobile Learning for Distance Learners: An Analysis and Unexpected Results from a Podcasting Study

ERIC Educational Resources Information Center

Lee, Mark J. W.; Chan, Anthony

2007-01-01

This article opens with a discussion of how and why mobile learning (m-learning) is purported to be the next step in the evolution of distance education, before looking at various perspectives on what m-learning constitutes. It critically examines the degree to which "true" m-learning has been achieved, by offering pedagogical value…

Building the Capability of Non-Formal Education Teachers to Develop a Learning Society for Promoting Lifelong Education in Thailand

ERIC Educational Resources Information Center

Sungsri, Sumalee

2018-01-01

This study aims to study Thai non-formal education teachers' perceptions of their opportunities to obtain knowledge about the learning society; identify the knowledge of non-formal education teachers need about the learning society which could be obtained through a distance learning package; and to develop and evaluate distance learning package on…

Three Generations of Distance Education Pedagogy

ERIC Educational Resources Information Center

Anderson, Terry; Dron, Jon

2011-01-01

This paper defines and examines three generations of distance education pedagogy. Unlike earlier classifications of distance education based on the technology used, this analysis focuses on the pedagogy that defines the learning experiences encapsulated in the learning design. The three generations of cognitive-behaviourist, social constructivist,…

Face-to-Face versus Distance Learning: Psychological Consequences and Practical Implications.

ERIC Educational Resources Information Center

Kahl, Thomas N.; Cropley, Arthur J.

1986-01-01

Summarizes differences between face-to-face and distance learners at Fernuniversitat (West Germany) in terms of demographics, motivation, study conditions, and personal consequences, in order to provide some empirically derived insights into the psychological consequences of distance learning for learners. (MBR)

The Relationships between Cognitive Style of Field Dependence and Learner Variables in E-Learning Instruction

ERIC Educational Resources Information Center

Sozcu, Omer Faruk

2014-01-01

This study examines the relationships between cognitive styles of field dependent learners with their attitudes towards e-learning (distance education) and instructional behavior in e-learning instruction. The Group Embedded Figures Test (GEFT) and the attitude survey (for students' preferences) towards e-learning instruction as distance education…

Validation of a Spanish Version of the Distance Education Learning Environments Survey (DELES) in Spain

ERIC Educational Resources Information Center

Fernández-Pascual, Maria Dolores; Ferrer-Cascales, Rosario; Reig-Ferrer, Abilio; Albaladejo-Blázquez, Natalia; Walker, Scott L.

2015-01-01

The aim of this study was to examine the validity of the Spanish version of the Distance Education Learning Environments Survey (Sp-DELES). This instrument assesses students' perceptions of virtual learning environments using six scales: Instructor Support, Student Interaction and Collaboration, Personal Relevance, Authentic Learning, Active…

The Use of Open Educational Resources in Online Learning: A Study of Students' Perception

ERIC Educational Resources Information Center

Harsasi, Meirani

2015-01-01

Universitas Terbuka (UT) is Indonesia's higher education institution which implements distance education system. The term distance implies that learning is not performed face-to-face but there is geographically separation between students and teacher. Therefore, UT must provide many kinds of learning modes and learning support. To facilitate…

Developing an International Distance Education Program: A Blended Learning Approach

ERIC Educational Resources Information Center

Mathur, Ravisha; Oliver, Lisa

2007-01-01

Building a dynamic international distance education program can be a complex operation. The purpose of this paper is to discuss a model for global learning that utilizes a blended learning approach. This paper will describe how a blended learning approach was implemented in an international instructional technology Master's program to the benefit…

Synchronous and Asynchronous Communication in Distance Learning: A Review of the Literature

ERIC Educational Resources Information Center

Watts, Lynette

2016-01-01

Distance learning is commonplace in higher education, with increasing numbers of students enjoying the flexibility e-learning provides. Keeping students connected with peers and instructors has been a challenge with e-learning, but as technology has advanced, the methods by which educators keep students engaged, synchronously and asynchronously,…

Rich Media e-Compendiums: A New Tool for Enhanced Learning in Higher Education

ERIC Educational Resources Information Center

Foss, Brynjar; Oftedal, Bjorg F.; Lokken, Atle

2013-01-01

Electronically supported learning has increasingly been introduced and accepted into the academic community over recent decades, and a variety of new digital learning tools have been developed to serve students both for distance education and on-campus blended learning. To serve our distance education nursing students, we recently developed unique…

Researching Mobile-Assisted Chinese-Character Learning Strategies among Adult Distance Learners

ERIC Educational Resources Information Center

Qian, Kan; Owen, Nathaniel; Bax, Stephen

2018-01-01

In the field of teaching and learning Chinese as a foreign language (CFL), most studies investigate Chinese character learning strategies in pen-and-paper study by campus-based students. With the increase in distance-learning, and expanding popularity of smartphones and tablets and widespread availability of mobile applications for language…

E-Learning in Engineering Education: Design of a Collaborative Advanced Remote Access Laboratory

ERIC Educational Resources Information Center

Chandra A. P., Jagadeesh; Samuel, R. D. Sudhaker

2010-01-01

Attaining excellence in technical education is a worthy challenge to any life goal. Distance learning opportunities make these goals easier to reach with added quality. Distance learning in engineering education is possible only through successful implementations of remote laboratories in a learning-by-doing environment. This paper presents one…

Successful Students in an Open and Distance Learning System

ERIC Educational Resources Information Center

Puspitasari, Kristanti Ambar; Oetoyo, Boedhi

2018-01-01

Learning in a higher education institution that applies an open and distance learning system requires the students to study as independent learners. This research is a survey research with the purpose of exploring the characteristics, habits and learning motivation of high-achiever students or those who obtained a high level of Grade Point Average…

The Relation between Distance Students' Motivation, Their Use of Learning Strategies, and Academic Success

ERIC Educational Resources Information Center

Radovan, Marko

2011-01-01

The aim of this study was to discover possible relationships between self-regulated learning dimensions and students' success in a distance-learning programme. The sample consisted of 319 students: 83 males and 236 females. They completed the "Motivated Strategies for Learning Questionnaire" (Pintrich, Smith, Garcia & McKeachie,…

Seamless Support: Technology Enhanced Learning in Open Distance Learning at NWU

ERIC Educational Resources Information Center

Esterhuizen, Hennie

2015-01-01

Frantic attempts of investing in technology to demonstrate willingness to educate for the knowledge society may result in failure to address the real requirements. This paper presents the main features of a framework for integrating Technology Enhanced Learning in Open Distance Learning at North-West University, South Africa. Support towards…

E-Learning--Long-Distance and Lifelong Perspectives

ERIC Educational Resources Information Center

Pontes, Elvis, Ed.; Silva, Anderson, Ed.; Guelfi, Adilson, Ed.; Kofuji, Sergio Takeo, Ed.

2012-01-01

Chapters in this book include: (1) Adaptive Model for E-Learning in Secondary School (Todorka Glushkova); (2) Electronic- and Mobile-Learning in Electronics Courses Focused on FPGA (Giovanni Vito Persiano and Sergio Rapuano); (3) Promoting E-Learning in Distance Education Programs in an African Country (Kenneth Addah, Desmond Kpebu and Olivia A.…

Dialogue and Structure: Enabling Learner Self-Regulation in Technology-Enhanced Learning Environments

ERIC Educational Resources Information Center

Andrade, Maureen Snow

2014-01-01

Distance learning that incorporates technology-enhanced learning environments provides a solution to the ever-increasing global demand for higher education. To be successful in these contexts, learners must be self-regulated, or have the ability to control the factors affecting their learning. Based on the theories of transactional distance,…

7 CFR 1703.101 - Policy.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.101 Policy... rural Americans. To further this objective, RUS will provide financial assistance to distance learning... educational, learning, training, and health care services. (b) In providing financial assistance, RUS will...

Preparation, characterization, and stereochemistry of binuclear vanadyl(IV) monomethyl- and dimethyltartrate(4-) complexes and the crystal structure of tetrasodium (. mu. -(+)-dimethyltartrato(4-))-(. mu. -(-)-dimethyltartrato(4-))-bis(oxovanadate(IV)) dodecahydrate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hahs, S.K.; Ortega, R.B.; Tapscott, R.E.

1982-02-01

The syntheses and characterizations (by ESR, IR, and electronic spectroscopies) of the sodium salts of the DL and DD (or LL) binuclear complexes of vanadyl(IV) with dimethyltartrate(4-), dmt, and with monomethyltartrate(4-), mmt, are described. Na/sub 4/((VO)/sub 22/((+)-dmt)((-)-dmt)) exists in two crystal forms - a blue dodecahydrate and a pink hexahydrate. An x-ray diffraction study of the former shows that the V-V distance (3.429 (3) A) of the binuclear anion is decreased relative to that of the unsubstituted tartrate(4-), tart, complex, as predicted from earlier ESR studies, and that this decrease is due in part to a dropping of the vanadiummore » atom into the plane of the four coordinating equatorial oxygen atoms. A sixth oxygen atom is weakly coordinated (2.377 (3) A) trans to the vanadyl oxygen atom. A purple tetradecahydrate also obtained with racenic dmt contains a mixture of ((VO)/sub 2/ ((+)-dmt)/sub 2/)/sup 4 -/ and ((VO)/sub 2/((-)-dmt)/sub 2/)/sup 4 -/). The aqueous solution ligand-exchange reaction between the DD and LL complexes of this salt to give the more stable DL isomer is remarkably slow (several hours at room temperature). Stereoselective effects allow the production of mixed-ligand species containing two of the three ligands tart, dmt, and mmt, and potentiometric titrations indicate a decreasing stability of the DL isomer (relative to the DD and LL isomers) as methyl substitution increases.« less

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

PubMed Central

Lu, Hongyang; Wei, Jingbo; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values. PMID:27110235

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

PubMed

Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Effectiveness of Learning with 3D-Lab on Omani Basic Education Students' Achievement, Attitudes and Scientific Thinking

ERIC Educational Resources Information Center

Musawi, Ali Al; Ambusaidi, Abdullah; Al-Balushi, Sulaiman; Al-Sinani, Mohamed; Al-Balushi, Kholoud

2017-01-01

This paper aims to measure the effectiveness of the 3DL on Omani students' acquisition of practical abilities and skills. It examines the effectiveness of the 3D-lab in science education and scientific thinking acquisition as part of a national project funded by The Research Council. Four research tools in a Pre-Post Test Control Group Design,…

Manifold Learning by Preserving Distance Orders.

PubMed

Ataer-Cansizoglu, Esra; Akcakaya, Murat; Orhan, Umut; Erdogmus, Deniz

2014-03-01

Nonlinear dimensionality reduction is essential for the analysis and the interpretation of high dimensional data sets. In this manuscript, we propose a distance order preserving manifold learning algorithm that extends the basic mean-squared error cost function used mainly in multidimensional scaling (MDS)-based methods. We develop a constrained optimization problem by assuming explicit constraints on the order of distances in the low-dimensional space. In this optimization problem, as a generalization of MDS, instead of forcing a linear relationship between the distances in the high-dimensional original and low-dimensional projection space, we learn a non-decreasing relation approximated by radial basis functions. We compare the proposed method with existing manifold learning algorithms using synthetic datasets based on the commonly used residual variance and proposed percentage of violated distance orders metrics. We also perform experiments on a retinal image dataset used in Retinopathy of Prematurity (ROP) diagnosis.

Distance Education in European Higher Education--The Offer. Report 1 (of 3) of the IDEAL (Impact of Distance Education on Adult Learning) Project

ERIC Educational Resources Information Center

Schneller, Chripa; Holmberg, Carl

2014-01-01

This report is the first in a series published by the IDEAL (Impact of Distance Education on Adult Learning) project. The IDEAL project ran from October 2013 to September 2015 with financial support from the EU Lifelong Learning Programme. The project aims to: (1) offer insights on the needs of adult learners to both policymakers and distance…

Educational Satellite Loan Guarantee Program Act, and Distance Learning. Hearing before the Subcommittee on Science, Technology, and Space of the Committee on Commerce, Science, and Transportation. United States Senate. One Hundred Fourth Congress, Second Session.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Senate Committee on Commerce, Science, and Transportation.

This document presents witness testimony and supplemental materials from a Congressional hearing focused on the role of technology in promoting distance learning in the United States. Distance learning programs make educational resources available to citizens, regardless of socioeconomic status or geographic location, and enable citizens to remain…

Distance Education in European Higher Education--The Potential. Report 3 (of 3) of the IDEAL (Impact of Distance Education on Adult Learning Project. Extended Version

ERIC Educational Resources Information Center

Owusu-Boampong, Angela; Holmberg, Carl

2015-01-01

This report is the third in a series published by the IDEAL (Impact of Distance Education on Adult Learning) project. The IDEAL project ran from October 2013 to September 2015 with financial support from the EU Lifelong Learning Programme. The project aims to: (1) offer insights on the needs of adult learners to both policymakers and distance…

An Approach for the Distance Delivery of AFIT/LS Resident Degree Curricula

DTIC Science & Technology

1991-12-01

minimal (least complex) distance education technologies appropriate for each learning topic or task. This may be the most time-consuming step in the...34 represents the least complex distance education technology that could be used to deliver the educational material for a particular learning objective. Careful...minimal technology needed to accomplish the learning objective. Look at question Q2.1 (Figure 5.15). Since the lecture offers an essential educational

Cocrystallization out of the blue: DL-mandelic acid/ethyl-DL-mandelate cocrystal

NASA Astrophysics Data System (ADS)

Tumanova, Natalia; Payen, Ricky; Springuel, Géraldine; Norberg, Bernadette; Robeyns, Koen; Le Duff, Cécile; Wouters, Johan; Leyssens, Tom

2017-01-01

This work focuses on a peculiar behavior of racemic mandelic acid in ethanol solution. Dissolution of racemic mandelic acid in ethanol followed by evaporation to dryness results in a DL-mandelic acid/ethyl-DL-mandelate cocrystal. This behavior indicates that racemic mandelic acid tends not only to transform into an ester in ethanol, but also to cocrystallize with untransformed acid molecules. Cocrystal formation for mandelic acid in ethanol was found to be reproducible under various conditions. DL-tropic acid and DL-phenyllactic acid that contain similar functional groups and that were tested as well, on the other hand, showed no cocrystal formation: DL-phenyllactic acid partly converted into an ester, whereas DL-tropic acid mostly recrystallized.