Biofeedback for Better Vision

NASA Technical Reports Server (NTRS)

1990-01-01

Biofeedtrac, Inc.'s Accommotrac Vision Trainer, invented by Dr. Joseph Trachtman, is based on vision research performed by Ames Research Center and a special optometer developed for the Ames program by Stanford Research Institute. In the United States, about 150 million people are myopes (nearsighted), who tend to overfocus when they look at distant objects causing blurry distant vision, or hyperopes (farsighted), whose vision blurs when they look at close objects because they tend to underfocus. The Accommotrac system is an optical/electronic system used by a doctor as an aid in teaching a patient how to contract and relax the ciliary body, the focusing muscle. The key is biofeedback, wherein the patient learns to control a bodily process or function he is not normally aware of. Trachtman claims a 90 percent success rate for correcting, improving or stopping focusing problems. The Vision Trainer has also proved effective in treating other eye problems such as eye oscillation, cross eyes, and lazy eye and in professional sports to improve athletes' peripheral vision and reaction time.

Teacher Leadership: Making Your Voice Count

ERIC Educational Resources Information Center

Singh, Kathryn

2011-01-01

Though principals play an important role in setting the vision for a school, and moving their staffs toward that vision, it is increasingly apparent that teachers must take on active decision-making and problem-solving roles. By sharing these responsibilities, schools can tap into the expertise of those most in tune with teaching and learning, and…

Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Tellaeche, A.; Arana, R.; Ibarguren, A.; Martínez-Otzeta, J. M.

The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

Problem Solved: Middle School Math Instruction Gets a Boost from a Flexible Model for Learning

ERIC Educational Resources Information Center

Jacobs, Jennifer; Koellner, Karen; Funderburk, Joanie

2012-01-01

Education researchers frequently seek out districts, schools, and teachers as partners for professional learning projects. They share their ambitious vision--a new model of professional learning that will support an empowered community, instructional improvement, and student achievement. The authors, along with other members of their research…

An active role for machine learning in drug development

PubMed Central

Murphy, Robert F.

2014-01-01

Due to the complexity of biological systems, cutting-edge machine-learning methods will be critical for future drug development. In particular, machine-vision methods to extract detailed information from imaging assays and active-learning methods to guide experimentation will be required to overcome the dimensionality problem in drug development. PMID:21587249

Maximizing the Impact: The Pivotal Role of Technology in a 21st Century Education System

ERIC Educational Resources Information Center

Vockley, Martha

2007-01-01

All students need a more robust education--and a refreshingly different kind of education--than most are getting today. The vision of learning individuals embrace focuses on teaching students to become critical thinkers, problem solvers and innovators; effective communicators and collaborators; and self-directed learners. This vision responds to…

Relaxations to Sparse Optimization Problems and Applications

NASA Astrophysics Data System (ADS)

Skau, Erik West

Parsimony is a fundamental property that is applied to many characteristics in a variety of fields. Of particular interest are optimization problems that apply rank, dimensionality, or support in a parsimonious manner. In this thesis we study some optimization problems and their relaxations, and focus on properties and qualities of the solutions of these problems. The Gramian tensor decomposition problem attempts to decompose a symmetric tensor as a sum of rank one tensors.We approach the Gramian tensor decomposition problem with a relaxation to a semidefinite program. We study conditions which ensure that the solution of the relaxed semidefinite problem gives the minimal Gramian rank decomposition. Sparse representations with learned dictionaries are one of the leading image modeling techniques for image restoration. When learning these dictionaries from a set of training images, the sparsity parameter of the dictionary learning algorithm strongly influences the content of the dictionary atoms.We describe geometrically the content of trained dictionaries and how it changes with the sparsity parameter.We use statistical analysis to characterize how the different content is used in sparse representations. Finally, a method to control the structure of the dictionaries is demonstrated, allowing us to learn a dictionary which can later be tailored for specific applications. Variations of dictionary learning can be broadly applied to a variety of applications.We explore a pansharpening problem with a triple factorization variant of coupled dictionary learning. Another application of dictionary learning is computer vision. Computer vision relies heavily on object detection, which we explore with a hierarchical convolutional dictionary learning model. Data fusion of disparate modalities is a growing topic of interest.We do a case study to demonstrate the benefit of using social media data with satellite imagery to estimate hazard extents. In this case study analysis we apply a maximum entropy model, guided by the social media data, to estimate the flooded regions during a 2013 flood in Boulder, CO and show that the results are comparable to those obtained using expert information.

Nutrition and Learning.

ERIC Educational Resources Information Center

Goldsmith, Robert H.

Nutritional deficiencies and imbalances can influence learning directly or indirectly. Fatigue, boredom and low motivation may be the result of poor nutrition. Some vision problems, it is known, are related to deficiencies in vitamin A. A number of studies indicate that protein-caloric malnutrition affects intellectual and psychomotor development.…

People with dyslexia and heart, chest, skin, digestive, musculoskeletal, vision, learning, speech and mental disorders were more dissatisfied with neighbourhoods: Scottish Household Survey, 2007-2008.

PubMed

Shiue, Ivy

2016-12-01

Rarely do we know the perception toward neighbourhoods in people specifically with health conditions. Therefore, the aim of the present study was to understand the perception toward neighbourhoods among adults with a series of the existing health conditions in a country-wide and population-based setting. Data were retrieved from and analysed in Scottish Household Survey, 2007-2008. Information on demographics, self-reported health conditions and perception toward neighbourhoods and the surrounding facilities was obtained by household interview. Analysis including chi-square test, t test and logistic regression modelling were performed. Of 19,150 Scottish adults (aged 16-80) included in the study cohort, 1079 (7.7 %) people were dissatisfied with their living areas; particularly for those who experienced harassment (15.4 %), did not recycle or with dyslexia, chest, digestive, mental and musculoskeletal problems. Twenty to forty per cent reported common neighbourhood problems including noise, rubbish, disputes, graffiti, harassment and drug misuse. People with heart or digestive problems were more dissatisfied with the existing parks and open space. People with arthritis, chest or hearing problems were more dissatisfied with the waste management condition. People with dyslexia were more dissatisfied with the existing public transportation. People with heart problems were more dissatisfied with the current street cleaning condition. People with hearing, vision, speech, learning problems or dyslexia were also more dissatisfied with sports and recreational facilities. People with heart, chest, skin, digestive, musculoskeletal, vision, learning, speech and mental disorders and dyslexia were more dissatisfied with their current neighbourhood environments. Upgrading neighbourhood planning to tackle social environment injustice and put pleasant life experience as priorty would be suggested. Graphical abstract interrelations of individual health and neighbourhood health.

The Vision of Children with Learning Difficulties: The Role of the Teacher and Psychologist.

ERIC Educational Resources Information Center

Willis, Marilyn A.

1981-01-01

The role of optometry in the study of learning difficulties and the problems of interpreting research results in the fields of optometry and ophthalmology are discussed. Limitations of school visual screening are described, and it is suggested that many children with learning difficulties should be referred for a full clinical visual examination.…

Online Graph Completion: Multivariate Signal Recovery in Computer Vision.

PubMed

Kim, Won Hwa; Jalal, Mona; Hwang, Seongjae; Johnson, Sterling C; Singh, Vikas

2017-07-01

The adoption of "human-in-the-loop" paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision) and the underlying inference algorithms are closely interwined. While classical work in active learning provides effective solutions when the learning module involves classification and regression tasks, many practical issues such as partially observed measurements, financial constraints and even additional distributional or structural aspects of the data typically fall outside the scope of this treatment. For instance, with sequential acquisition of partial measurements of data that manifest as a matrix (or tensor), novel strategies for completion (or collaborative filtering) of the remaining entries have only been studied recently. Motivated by vision problems where we seek to annotate a large dataset of images via a crowdsourced platform or alternatively, complement results from a state-of-the-art object detector using human feedback, we study the "completion" problem defined on graphs, where requests for additional measurements must be made sequentially. We design the optimization model in the Fourier domain of the graph describing how ideas based on adaptive submodularity provide algorithms that work well in practice. On a large set of images collected from Imgur, we see promising results on images that are otherwise difficult to categorize. We also show applications to an experimental design problem in neuroimaging.

Case-Based Learning in Endocrine Physiology: An Approach toward Self-Directed Learning and the Development of Soft Skills in Medical Students

ERIC Educational Resources Information Center

Gade, Shubhada; Chari, Suresh

2013-01-01

The Medical Council of India, in the recent "Vision 2015" document, recommended curricular reforms for undergraduates. Case-based learning (CBL) is one method where students are motivated toward self-directed learning and to develop analytic and problem-solving skills. An overview of thyroid physiology was given in a didactic lecture. A…

The Effect of Multimedia-Based Learning on the Concept Learning Levels and Attitudes of Students

ERIC Educational Resources Information Center

Beydogan, H. Ömer; Hayran, Zeynel

2015-01-01

Problem Statement: Rich stimuli received by sensory organs such as vision, hearing, and touch are important elements that affect an individual's perception, identification, classification, and conceptualization of the external world. In primary education, since students perform conceptual abstraction based upon concrete characteristics, when they…

Learning Disabilities: The Decade Ahead.

ERIC Educational Resources Information Center

Krasnoff, Margaret J., Ed.

Presented are ten papers given at a 1974 conference focusing on realistic goals for serving learning disabled children in the decade ahead. Papers have the following titles and authors: "Introduction and Overview of the Problem of the Conference" (W. Cruickshank); "Concepts of Vision in Relation to Perception" (G. Getman); "Motor Activities and…

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

PubMed

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

PubMed Central

Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

The Challenge of Educational Technology for Students with Multiple Impairments in the Classroom.

ERIC Educational Resources Information Center

Molloy, Paul; Baskin, Barbara

1995-01-01

Discussion of assistive technologies that help students with multiple impairments focuses on procedures and equipment used by a college student with Usher's Syndrome, involving vision and hearing impairments. Highlights include federal legislation; problems and possible solutions at various educational levels; specific learning problems; and…

Working Together: The Art of Consulting & Communicating.

ERIC Educational Resources Information Center

DeBoer, Anita

Productive learning occurs when educators work together to create new visions, analyze important issues, and evaluate outcomes. This book explores how educators can effectively engage in peer problem solving, focusing on three aspects of the process: (1) models for consulting with colleagues in problem solving; (2) communication skills necessary…

Combining Vision with Voice: A Learning and Implementation Structure Promoting Teachers' Internalization of Practices Based on Self-Determination Theory

ERIC Educational Resources Information Center

Assor, Avi; Kaplan, Haya; Feinberg, Ofra; Tal, Karen

2009-01-01

We propose that self-determination theory's conceptualization of internalization may help school reformers overcome the recurrent problem of "the predictable failure of educational reform" (Sarason, 1993). Accordingly, we present a detailed learning and implementation structure to promote teachers' internalization and application of ideas and…

Creating an Outcomes-Based Tool for Learning Barrier Assessment in an Outpatient Education Program.

ERIC Educational Resources Information Center

Hernandez, Teri L.; Rupnow, Jana M.; Currie, Kristi A.; Procious, James K.; Adams, Jenny

2003-01-01

An outcomes-based assessment instrument was devised to screen patients for learning problems that would impede patient education in cardiac rehabilitation. Criteria for seven barriers were established: hearing, language, cultural, religious, vision, cognitive, emotional). Points of data collection and a rationale for collection were identified.…

The Music Teacher as a Cultural Figure: A Cautionary Note on Globalized Learning as Part of a Technical Conception of Education

ERIC Educational Resources Information Center

Pio, Frederick

2017-01-01

This article is divided into three parts: the problem (globalized learning); the consequences (for general music education); and the vision (the music teacher as a cultural figure). In the first part, I claim that the current learning agenda is being increasingly instrumentalized as a carrier of a global education policy driven by technical…

Warning Signs of Vision Problems in Children

MedlinePlus

... Life Family Life Family Life Medical Home Family Dynamics Media Work & Play Getting Involved in Your Community ... and Urinary Tract Glands & Growth Head Neck & Nervous System Heart Infections Learning Disabilities Obesity Orthopedic Prevention Sexually ...

Computer vision cracks the leaf code

PubMed Central

Wilf, Peter; Zhang, Shengping; Chikkerur, Sharat; Little, Stefan A.; Wing, Scott L.; Serre, Thomas

2016-01-01

Understanding the extremely variable, complex shape and venation characters of angiosperm leaves is one of the most challenging problems in botany. Machine learning offers opportunities to analyze large numbers of specimens, to discover novel leaf features of angiosperm clades that may have phylogenetic significance, and to use those characters to classify unknowns. Previous computer vision approaches have primarily focused on leaf identification at the species level. It remains an open question whether learning and classification are possible among major evolutionary groups such as families and orders, which usually contain hundreds to thousands of species each and exhibit many times the foliar variation of individual species. Here, we tested whether a computer vision algorithm could use a database of 7,597 leaf images from 2,001 genera to learn features of botanical families and orders, then classify novel images. The images are of cleared leaves, specimens that are chemically bleached, then stained to reveal venation. Machine learning was used to learn a codebook of visual elements representing leaf shape and venation patterns. The resulting automated system learned to classify images into families and orders with a success rate many times greater than chance. Of direct botanical interest, the responses of diagnostic features can be visualized on leaf images as heat maps, which are likely to prompt recognition and evolutionary interpretation of a wealth of novel morphological characters. With assistance from computer vision, leaves are poised to make numerous new contributions to systematic and paleobotanical studies. PMID:26951664

Monocular Depth Perception and Robotic Grasping of Novel Objects

DTIC Science & Technology

2009-06-01

resulting algorithm is able to learn monocular vision cues that accurately estimate the relative depths of obstacles in a scene. Reinforcement learning ... learning still make sense in these settings? Since many of the cues that are useful for estimating depth can be re-created in synthetic images, we...supervised learning approach to this problem, and use a Markov Random Field (MRF) to model the scene depth as a function of the image features. We show

The Challenges of Educating the Visually Impaired and Quality Assurance in Tertiary Institutions of Learning in Nigeria

ERIC Educational Resources Information Center

Omede, Andrew A.

2015-01-01

This paper focused on the challenges in educating the visually impaired and modalities for ensuring quality assurance in tertiary institutions of learning in Nigeria. It examined the global challenges in the higher educational system and made it clear that the visually impaired are those with visual problems be it partial, low vision, or total…

Premeds Abroad.

ERIC Educational Resources Information Center

Rossel, Todd

1987-01-01

Foreign study can broaden the undergraduate experience for premedical students and help remedy the problem of on-campus tunnel vision, characterized by too little independent learning and critical thinking, premature specialization, avoidance of social sciences and humanities, and lack of appreciation of cultural heritage. (MSE)

Saliency detection by conditional generative adversarial network

NASA Astrophysics Data System (ADS)

Cai, Xiaoxu; Yu, Hui

2018-04-01

Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

Autonomous Learning in Mobile Cognitive Machines

DTIC Science & Technology

2017-11-25

2016). [18] Liu, Wei, et al. "Ssd: Single shot multibox detector." European conference on computer vision. Springer, Cham, 2016. [19] Vinyals, Oriol...the brain being evolved to support its mobility has been raised. In fact, as the project progressed, the researchers discovered that if one of the...deductive, relies on rule-based programming, and can solve complex problems, however, faces difficulties in learning and adaptability. The latter

Using enquiry in learning: from vision to reality in higher education.

PubMed

Horne, Maria; Woodhead, Kath; Morgan, Liz; Smithies, Lynda; Megson, Denise; Lyte, Geraldine

2007-02-01

This paper reports on the contribution of six nurse educators to embed enquiry-led learning in a pre-registration nursing programme. Their focus was to evaluate student and facilitator perspectives of a hybrid model of problem-based learning, a form of enquiry-based learning and to focus on facilitators' perceptions of its longer-term utility with large student groups. Problem-based learning is an established learning strategy in healthcare internationally; however, insufficient evidence of its effectiveness with large groups of pre-registration students exists. Fourth Generation Evaluation was used, applying the Nominal Group Technique and Focus Group interviews, for data collection. In total, four groups representing different branches of pre-registration students (n = 121) and 15 facilitators participated. Students identified seven strengths and six areas for development related to problem-based learning. Equally, analysis of facilitators' discussions revealed several themes related to strengths and challenges. The consensus was that using enquiry aided the development of independent learning and encouraged deeper exploration of nursing and allied subject material. However, problems and frustrations were identified in relation to large numbers of groups, group dynamics, room and library resources and personal development. The implications of these findings for longer-term utility with large student groups are discussed.

Learning the Digital Way: Evaluating Progress, Tackling Challenges. Technology Counts, 2015. Education Week. Volume 34, Number 35

ERIC Educational Resources Information Center

Edwards, Virginia B., Ed.

2015-01-01

Lofty ed-tech visions are always tempered by reality. Unexpected problems that arose during a launch of a 1-to-1 computing program and ambitious digital curriculum initiative in Los Angeles led to the dialing back of the effort. Financial, legal, and managerial repercussions continue to swirl in the wake. These problems should not prevent schools…

Exceptional Pupils. Special Education Bulletin Number 1.

ERIC Educational Resources Information Center

Indiana State Dept. of Public Instruction, Indianapolis. Div. of Special Education.

An introduction to exceptional children precedes a discussion of each of the following areas of exceptionality; giftedness, mental retardation, physical handicaps and special health problems, blindness and partial vision, aural handicaps, speech handicaps, emotional disturbance, and learning disabilities. Each chapter is followed by a bibliography…

A Starter's Guide to Artificial Intelligence.

ERIC Educational Resources Information Center

McConnell, Barry A.; McConnell, Nancy J.

1988-01-01

Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

Contextual Teaching and Learning: Preparing Teachers to Enhance Student Success in the Workplace and Beyond. Information Series No. 376.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Adult, Career, and Vocational Education, Columbus, OH.

The papers in this volume outline a vision for teacher education based on the concept of contextual teaching, defined as teaching that enables learning in a variety of in- and out-of-school contexts to solve simulated or real-world problems. They are based on the realization that the construction of knowledge is situated within, and greatly…

Metal surface corrosion grade estimation from single image

NASA Astrophysics Data System (ADS)

Chen, Yijun; Qi, Lin; Sun, Huyuan; Fan, Hao; Dong, Junyu

2018-04-01

Metal corrosion can cause many problems, how to quickly and effectively assess the grade of metal corrosion and timely remediation is a very important issue. Typically, this is done by trained surveyors at great cost. Assisting them in the inspection process by computer vision and artificial intelligence would decrease the inspection cost. In this paper, we propose a dataset of metal surface correction used for computer vision detection and present a comparison between standard computer vision techniques by using OpenCV and deep learning method for automatic metal surface corrosion grade estimation from single image on this dataset. The test has been performed by classifying images and calculating the accuracy for the two different approaches.

Discriminatively learning for representing local image features with quadruplet model

NASA Astrophysics Data System (ADS)

Zhang, Da-long; Zhao, Lei; Xu, Duan-qing; Lu, Dong-ming

2017-11-01

Traditional hand-crafted features for representing local image patches are evolving into current data-driven and learning-based image feature, but learning a robust and discriminative descriptor which is capable of controlling various patch-level computer vision tasks is still an open problem. In this work, we propose a novel deep convolutional neural network (CNN) to learn local feature descriptors. We utilize the quadruplets with positive and negative training samples, together with a constraint to restrict the intra-class variance, to learn good discriminative CNN representations. Compared with previous works, our model reduces the overlap in feature space between corresponding and non-corresponding patch pairs, and mitigates margin varying problem caused by commonly used triplet loss. We demonstrate that our method achieves better embedding result than some latest works, like PN-Net and TN-TG, on benchmark dataset.

Machine Learning, deep learning and optimization in computer vision

NASA Astrophysics Data System (ADS)

Canu, Stéphane

2017-03-01

As quoted in the Large Scale Computer Vision Systems NIPS workshop, computer vision is a mature field with a long tradition of research, but recent advances in machine learning, deep learning, representation learning and optimization have provided models with new capabilities to better understand visual content. The presentation will go through these new developments in machine learning covering basic motivations, ideas, models and optimization in deep learning for computer vision, identifying challenges and opportunities. It will focus on issues related with large scale learning that is: high dimensional features, large variety of visual classes, and large number of examples.

Medical examination of school entrants: later school problems and absenteeism of attenders and non-attenders.

PubMed

Mowat, D L; White, C

1985-04-01

Children who were scheduled for medical examination before entering school were followed in school one or two years later. Non-attenders had a two-fold risk of repeating grades, special class placement, referral for speech/language problems, teacher-reported learning or behavior problems, failure of vision or hearing screening, and transfer between schools. Absenteeism was also significantly more common. Children not brought in for preventive health care are at greater risk than others for difficulties in school.

Southwestern Region Deaf-Blind Center Selected Workshop Papers, 1970-1973.

ERIC Educational Resources Information Center

Southwestern Region Deaf-Blind Center, Sacramento, CA.

The document contains 18 presentations from Southwestern Region Deaf-Blind Center workshops held from 1970 to 1973 and covering the areas of assessment, vision, auditory training, communication, learning, family, and problems. Entries included the following titles and authors: "Methods for Assessing the Status and Growth of Preschool Deaf-Blind…

Advanced IT Education for the Vision Impaired via e-Learning

ERIC Educational Resources Information Center

Armstrong, Helen L.

2009-01-01

Lack of accessibility in the design of e-learning courses continues to hinder students with vision impairment. E-learning materials are predominantly vision-centric, incorporating images, animation, and interactive media, and as a result students with acute vision impairment do not have equal opportunity to gain tertiary qualifications or skills…

Emerging Science in TBI Care: Diagnosis and Treatment: The Quadruple Aim: Learning & Growth, Readiness, Experience of Care

DTIC Science & Technology

2011-01-25

Behavioral problems – Emotional problems – “Unexplained“ symptoms TBI-related impairments increase vulnerability to subsequent injury until full...developed specific protocols for management of concussed Service members and those with recurrent concussion  Transition from symptom driven reporting...with early treatment.  VISION: Every Warfighter trained to: – Recognize the signs/ symptoms – Equipped to reduce the effects And in the event of an

The APPL "Learning Map"

NASA Technical Reports Server (NTRS)

2005-01-01

Root Learning, a learning consulting organization with a background in strategic planning, recognizes the knowledge gap that frequently exists between a leadership team and the rest of an organization. Team members supposedly working toward the same goal don't always have the same vision as to where the organization is headed, and they may not understand how the piece they are accountable for fits into the big picture. To address these complex problems, Root Learning utilizes the age-old tools of sarcasm, metaphor and graphics (much in the same way that ASK uses a traditional storytelling format.) The company is best known for creating "Learning Maps" like this one: humorous drawings based on the inner workings of an organization. Their purpose is to put complex topics on the table, to stimulate discussion, and to ultimately give team members a common vision of where the organization is going and what role they personally play in getting there. APPL knows how effective it is to incorporate new and engaging techniques into its knowledge sharing programs. By collaborating with Root Learning, we were able to expand the knowledge of the organization and add one more of these techniques to our repertoire.

Spatial learning while navigating with severely degraded viewing: The role of attention and mobility monitoring

PubMed Central

Rand, Kristina M.; Creem-Regehr, Sarah H.; Thompson, William B.

2015-01-01

The ability to navigate without getting lost is an important aspect of quality of life. In five studies, we evaluated how spatial learning is affected by the increased demands of keeping oneself safe while walking with degraded vision (mobility monitoring). We proposed that safe low-vision mobility requires attentional resources, providing competition for those needed to learn a new environment. In Experiments 1 and 2 participants navigated along paths in a real-world indoor environment with simulated degraded vision or normal vision. Memory for object locations seen along the paths was better with normal compared to degraded vision. With degraded vision, memory was better when participants were guided by an experimenter (low monitoring demands) versus unguided (high monitoring demands). In Experiments 3 and 4, participants walked while performing an auditory task. Auditory task performance was superior with normal compared to degraded vision. With degraded vision, auditory task performance was better when guided compared to unguided. In Experiment 5, participants performed both the spatial learning and auditory tasks under degraded vision. Results showed that attention mediates the relationship between mobility-monitoring demands and spatial learning. These studies suggest that more attention is required and spatial learning is impaired when navigating with degraded viewing. PMID:25706766

The Apollo Experience Lessons Learned for Constellation Lunar Dust Management

NASA Technical Reports Server (NTRS)

Wagner, Sandra

2008-01-01

In 2008, NASA was embarking on its Exploration Vision, knowing that many technical challenges would be encountered. For lunar exploration missions, one challenge was to learn to manage lunar dust. References to problems associated with lunar dust during the Apollo Program were found on many of pages of the mission reports and technical debriefs. All engineers designing hardware that would come into contact with lunar dust had to mitigate its effects in the design.

Patterns and Punctuation: Learning to Question Language

ERIC Educational Resources Information Center

Schlessman, Elizabeth

2011-01-01

As teachers plan instruction--even instruction about punctuation--they have the opportunity to engage students' minds and create new labels: question-asking, problem-solving. How teachers teach embeds a vision of who they think kids are and what they think kids are capable of. Are they destined for a future of critical thinking, questioning,…

The Potential of Artificial Intelligence in Aids for the Disabled.

ERIC Educational Resources Information Center

Boyer, John J.

The paper explores the possibilities for applying the knowledge of artificial intelligence (AI) research to aids for the disabled. Following a definition of artificial intelligence, the paper reviews areas of basic AI research, such as computer vision, machine learning, and planning and problem solving. Among application areas relevant to the…

Whose Voices Will Be Heard? Creating a Vision for the Future.

ERIC Educational Resources Information Center

McGuire, Margit E.

1992-01-01

Discusses society in the future. Expresses concern over social problems and misuse by the media of terms relating to diversity and multiculturalism. Lists themes for effective instruction in social studies as integration of topics and meaningful, challenging, active, and value-based learning. Urges that self-esteem, mutual respect, and cooperative…

Developmental Visual Dysfunction: Models for Assessment and Management.

ERIC Educational Resources Information Center

Erhardt, Rhoda Priest

This book describes transdisciplinary management of multiply disabled children with vision problems and presents four theoretical models of visual assessment and three illustrative case studies in a sequence appropriate to the learning process. The first three models are intended to lead to assessment and management of the child and the last to…

What Did They Take Away?: Examining Newly Qualified U.S. Teachers' Visions of Learning and Teaching Science in K-8 Classrooms

ERIC Educational Resources Information Center

Roberts-Harris, Deborah

2014-01-01

This study investigated newly qualified K-8 teachers' visions of science learning and teaching after they had completed preparation in a science teaching methods course I taught. What visions of science learning and teaching were these newly qualified teachers taking away from my course? How did these visions compare with those advocated by reform…

Learning for autonomous navigation : extrapolating from underfoot to the far field

NASA Technical Reports Server (NTRS)

Matthies, Larry; Turmon, Michael; Howard, Andrew; Angelova, Anelia; Tang, Benyang; Mjolsness, Eric

2005-01-01

Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter. Enabling robots to learn from experience may alleviate both of these problems. We define two paradigms for this, learning from 3-D geometry and learning from proprioception, and describe initial instantiations of them we have developed under DARPA and NASA programs. Field test results show promise for learning traversability of vegetated terrain, learning to extend the lookahead range of the vision system, and learning how slip varies with slope.

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

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

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Large-scale functional models of visual cortex for remote sensing

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

Brumby, Steven P; Kenyon, Garrett; Rasmussen, Craig E

Neuroscience has revealed many properties of neurons and of the functional organization of visual cortex that are believed to be essential to human vision, but are missing in standard artificial neural networks. Equally important may be the sheer scale of visual cortex requiring {approx}1 petaflop of computation. In a year, the retina delivers {approx}1 petapixel to the brain, leading to massively large opportunities for learning at many levels of the cortical system. We describe work at Los Alamos National Laboratory (LANL) to develop large-scale functional models of visual cortex on LANL's Roadrunner petaflop supercomputer. An initial run of a simplemore » region VI code achieved 1.144 petaflops during trials at the IBM facility in Poughkeepsie, NY (June 2008). Here, we present criteria for assessing when a set of learned local representations is 'complete' along with general criteria for assessing computer vision models based on their projected scaling behavior. Finally, we extend one class of biologically-inspired learning models to problems of remote sensing imagery.« less

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

Learning graph matching.

PubMed

Caetano, Tibério S; McAuley, Julian J; Cheng, Li; Le, Quoc V; Smola, Alex J

2009-06-01

As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. Many formulations of this problem can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility and a quadratic term encodes edge compatibility. The main research focus in this theme is about designing efficient algorithms for approximately solving the quadratic assignment problem, since it is NP-hard. In this paper we turn our attention to a different question: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the 'labels' are matches between them. Our experimental results reveal that learning can substantially improve the performance of standard graph matching algorithms. In particular, we find that simple linear assignment with such a learning scheme outperforms Graduated Assignment with bistochastic normalisation, a state-of-the-art quadratic assignment relaxation algorithm.

Distance education but beyond: "meLearning"--what if the impossible isn't?

PubMed

Hodgins, Wayne

2007-01-01

It's not the physical distance between teachers and learners that is the problem but the gap between what all of us as learners need and what those who supply the education, training, and learning have to offer. Mass-produced education for the masses will give way to massively customized learning with contributions from all. While the scope of such an endeavor appears staggering, the dream of adaptive, personalized "meLearning" for every person every day, and thus the brightest future ever imagined, lies immediately in front of us and within our grasp. The vision for a future world state where every person experiences personalized learning every day is clear, but it has arrived prematurely, is inequitably distributed, and remains unseen by most. Moreover, and as has been common in the history of conditions preceding such mass revolutions, the existing organizations and institution stand in stark contrast to this vision and, in many ways, oppose it. All quite predictable and understandable. However, the status quo is no longer an option. The distance between the supply side of the equation (solutions offered) and the demand side (demands and needs) is disproportionately large. Change is inevitable, and is increasingly demanded by all involved. If you have not done so already, it is time to start imagining what our world would be like if we increased the effectiveness of learning for everyone, all the time, by customizing the learning to fit each individual person and situation. Imagine if the impossible isn't! Many others already have. This future is ours for the choosing if we can muster the courage to ignite the transformation from vision to reality by simply imagining that this bright future is now possible and beginning to shape its design and implementation.

Is there a role for a primary health nurse in a learning support team in a disadvantaged high school? Evaluation of a pilot study.

PubMed

Dennis, Sarah; Noon, Ted; Liaw, Siaw Teng

2016-02-01

Disadvantaged children experience more health problems and have poorer educational outcomes compared with students from advantaged backgrounds. This paper presents the quantitative and qualitative findings from a pilot study to determine the impact of the Healthy Learner model, where an experienced primary care nurse was embedded in a learning support team in a disadvantaged high school. Students entering high school with National Assessment Program, Literacy and Numeracy (NAPLAN) scores in the lowest quartile for the school were assessed by the nurse and identified health issues addressed. Thirty-nine students were assessed in 2012-13 and there were up to seven health problems identified per student, ranging from serious neglect to problems such as uncorrected vision or hearing. Many of these problems were having an impact on the student and their ability to engage in learning. Families struggled to navigate the health system, they had difficulty explaining the student's problems to health professionals and costs were a barrier. Adding a nurse to the learning support team in this disadvantaged high school was feasible and identified considerable unmet health needs that affect a student's ability to learn. The families needed extensive support to access any subsequent health care they required.

Learning from vision-to-touch is different than learning from touch-to-vision.

PubMed

Wismeijer, Dagmar A; Gegenfurtner, Karl R; Drewing, Knut

2012-01-01

We studied whether vision can teach touch to the same extent as touch seems to teach vision. In a 2 × 2 between-participants learning study, we artificially correlated visual gloss cues with haptic compliance cues. In two "natural" tasks, we tested whether visual gloss estimations have an influence on haptic estimations of softness and vice versa. In two "novel" tasks, in which participants were either asked to haptically judge glossiness or to visually judge softness, we investigated how perceptual estimates transfer from one sense to the other. Our results showed that vision does not teach touch as efficient as touch seems to teach vision.

Putting the Vision into Practice

ERIC Educational Resources Information Center

Ravenhall, Mark

2010-01-01

It's almost a year since the revolution--the "Learning Revolution," that is. This was the Government's long-term vision for the development of "informal adult learning", as laid out in the White Paper of March 2009. The vision was expansive, embracing informal learning in the workplace, promoting a "new" culture of…

Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

PubMed

Burlina, Philippe; Pacheco, Katia D; Joshi, Neil; Freund, David E; Bressler, Neil M

2017-03-01

When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is often asymptomatic with regard to visual deficit. These individuals are at high risk for progressing to the advanced stage where the often treatable choroidal neovascular form of AMD can occur. Careful monitoring to detect the onset and prompt treatment of the neovascular form as well as dietary supplementation can reduce the risk of vision loss from AMD, therefore, preferred practice patterns recommend identifying individuals with the intermediate stage in a timely manner. Past automated retinal image analysis (ARIA) methods applied on fundus imagery have relied on engineered and hand-designed visual features. We instead detail the novel application of a machine learning approach using deep learning for the problem of ARIA and AMD analysis. We use transfer learning and universal features derived from deep convolutional neural networks (DCNN). We address clinically relevant 4-class, 3-class, and 2-class AMD severity classification problems. Using 5664 color fundus images from the NIH AREDS dataset and DCNN universal features, we obtain values for accuracy for the (4-, 3-, 2-) class classification problem of (79.4%, 81.5%, 93.4%) for machine vs. (75.8%, 85.0%, 95.2%) for physician grading. This study demonstrates the efficacy of machine grading based on deep universal features/transfer learning when applied to ARIA and is a promising step in providing a pre-screener to identify individuals with intermediate AMD and also as a tool that can facilitate identifying such individuals for clinical studies aimed at developing improved therapies. It also demonstrates comparable performance between computer and physician grading. Copyright © 2017 Elsevier Ltd. All rights reserved.

Teacher Educators' Practice and Vision of Good Teaching in Teacher Education Reform Context in Ghana

ERIC Educational Resources Information Center

Akyeampong, Kwame

2017-01-01

Teacher education in sub-Sahara Africa (SSA) has been criticized for the lack of attention to learning to teach in real classrooms, which limits the opportunity for pre-service teachers to successfully introduce learner-centered pedagogy in African primary school classrooms. To address this problem, Ghana has implemented a teacher education reform…

Learning prosthetic vision: a virtual-reality study.

PubMed

Chen, Spencer C; Hallum, Luke E; Lovell, Nigel H; Suaning, Gregg J

2005-09-01

Acceptance of prosthetic vision will be heavily dependent on the ability of recipients to form useful information from such vision. Training strategies to accelerate learning and maximize visual comprehension would need to be designed in the light of the factors affecting human learning under prosthetic vision. Some of these potential factors were examined in a visual acuity study using the Landolt C optotype under virtual-reality simulation of prosthetic vision. Fifteen normally sighted subjects were tested for 10-20 sessions. Potential learning factors were tested at p < 0.05 with regression models. Learning was most evident across-sessions, though 17% of sessions did express significant within-session trends. Learning was highly concentrated toward a critical range of optotype sizes, and subjects were less capable in identifying the closed optotype (a Landolt C with no gap, forming a closed annulus). Training for implant recipients should target these critical sizes and the closed optotype to extend the limit of visual comprehension. Although there was no evidence that image processing affected overall learning, subjects showed varying personal preferences.

Learning from vision-to-touch is different than learning from touch-to-vision

PubMed Central

Wismeijer, Dagmar A.; Gegenfurtner, Karl R.; Drewing, Knut

2012-01-01

We studied whether vision can teach touch to the same extent as touch seems to teach vision. In a 2 × 2 between-participants learning study, we artificially correlated visual gloss cues with haptic compliance cues. In two “natural” tasks, we tested whether visual gloss estimations have an influence on haptic estimations of softness and vice versa. In two “novel” tasks, in which participants were either asked to haptically judge glossiness or to visually judge softness, we investigated how perceptual estimates transfer from one sense to the other. Our results showed that vision does not teach touch as efficient as touch seems to teach vision. PMID:23181012

ATR applications of minimax entropy models of texture and shape

NASA Astrophysics Data System (ADS)

Zhu, Song-Chun; Yuille, Alan L.; Lanterman, Aaron D.

2001-10-01

Concepts from information theory have recently found favor in both the mainstream computer vision community and the military automatic target recognition community. In the computer vision literature, the principles of minimax entropy learning theory have been used to generate rich probabilitistic models of texture and shape. In addition, the method of types and large deviation theory has permitted the difficulty of various texture and shape recognition tasks to be characterized by 'order parameters' that determine how fundamentally vexing a task is, independent of the particular algorithm used. These information-theoretic techniques have been demonstrated using traditional visual imagery in applications such as simulating cheetah skin textures and such as finding roads in aerial imagery. We discuss their application to problems in the specific application domain of automatic target recognition using infrared imagery. We also review recent theoretical and algorithmic developments which permit learning minimax entropy texture models for infrared textures in reasonable timeframes.

Professional Vision of Classroom Management and Learning Support in Science Classrooms--Does Professional Vision Differ across General and Content-Specific Classroom Interactions?

ERIC Educational Resources Information Center

Steffensky, Mirjam; Gold, Bernadette; Holdynski, Manfred; Möller, Kornelia

2015-01-01

The present study investigates the internal structure of professional vision of in-service teachers and student teachers with respect to classroom management and learning support in primary science lessons. Classroom management (including monitoring, managing momentum, and rules and routines) and learning support (including cognitive activation…

Efficacy of vision therapy in children with learning disability and associated binocular vision anomalies.

PubMed

Hussaindeen, Jameel Rizwana; Shah, Prerana; Ramani, Krishna Kumar; Ramanujan, Lalitha

To report the frequency of binocular vision (BV) anomalies in children with specific learning disorders (SLD) and to assess the efficacy of vision therapy (VT) in children with a non-strabismic binocular vision anomaly (NSBVA). The study was carried out at a centre for learning disability (LD). Comprehensive eye examination and binocular vision assessment was carried out for 94 children (mean (SD) age: 15 (2.2) years) diagnosed with specific learning disorder. BV assessment was done for children with best corrected visual acuity of ≥6/9 - N6, cooperative for examination and free from any ocular pathology. For children with a diagnosis of NSBVA (n=46), 24 children were randomized to VT and no intervention was provided to the other 22 children who served as experimental controls. At the end of 10 sessions of vision therapy, BV assessment was performed for both the intervention and non-intervention groups. Binocular vision anomalies were found in 59 children (62.8%) among which 22% (n=13) had strabismic binocular vision anomalies (SBVA) and 78% (n=46) had a NSBVA. Accommodative infacility (AIF) was the commonest of the NSBVA and found in 67%, followed by convergence insufficiency (CI) in 25%. Post-vision therapy, the intervention group showed significant improvement in all the BV parameters (Wilcoxon signed rank test, p<0.05) except negative fusional vergence. Children with specific learning disorders have a high frequency of binocular vision disorders and vision therapy plays a significant role in improving the BV parameters. Children with SLD should be screened for BV anomalies as it could potentially be an added hindrance to the reading difficulty in this special population. Copyright © 2017 Spanish General Council of Optometry. Published by Elsevier España, S.L.U. All rights reserved.

Vision Problems in Homeless Children.

PubMed

Smith, Natalie L; Smith, Thomas J; DeSantis, Diana; Suhocki, Marissa; Fenske, Danielle

2015-08-01

Vision problems in homeless children can decrease educational achievement and quality of life. To estimate the prevalence and specific diagnoses of vision problems in children in an urban homeless shelter. A prospective series of 107 homeless children and teenagers who underwent screening with a vision questionnaire, eye chart screening (if mature enough) and if vision problem suspected, evaluation by a pediatric ophthalmologist. Glasses and other therapeutic interventions were provided if necessary. The prevalence of vision problems in this population was 25%. Common diagnoses included astigmatism, amblyopia, anisometropia, myopia, and hyperopia. Glasses were required and provided for 24 children (22%). Vision problems in homeless children are common and frequently correctable with ophthalmic intervention. Evaluation by pediatric ophthalmologist is crucial for accurate diagnoses and treatment. Our system of screening and evaluation is feasible, efficacious, and reproducible in other homeless care situations.

Toward open set recognition.

PubMed

Scheirer, Walter J; de Rezende Rocha, Anderson; Sapkota, Archana; Boult, Terrance E

2013-07-01

To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of "closed set" recognition, whereby all testing classes are known at training time. A more realistic scenario for vision applications is "open set" recognition, where incomplete knowledge of the world is present at training time, and unknown classes can be submitted to an algorithm during testing. This paper explores the nature of open set recognition and formalizes its definition as a constrained minimization problem. The open set recognition problem is not well addressed by existing algorithms because it requires strong generalization. As a step toward a solution, we introduce a novel "1-vs-set machine," which sculpts a decision space from the marginal distances of a 1-class or binary SVM with a linear kernel. This methodology applies to several different applications in computer vision where open set recognition is a challenging problem, including object recognition and face verification. We consider both in this work, with large scale cross-dataset experiments performed over the Caltech 256 and ImageNet sets, as well as face matching experiments performed over the Labeled Faces in the Wild set. The experiments highlight the effectiveness of machines adapted for open set evaluation compared to existing 1-class and binary SVMs for the same tasks.

AN INVESTIGATION OF VISION PROBLEMS AND THE VISION CARE SYSTEM IN RURAL CHINA.

PubMed

Bai, Yunli; Yi, Hongmei; Zhang, Linxiu; Shi, Yaojiang; Ma, Xiaochen; Congdon, Nathan; Zhou, Zhongqiang; Boswell, Matthew; Rozelle, Scott

2014-11-01

This paper examines the prevalence of vision problems and the accessibility to and quality of vision care in rural China. We obtained data from 4 sources: 1) the National Rural Vision Care Survey; 2) the Private Optometrists Survey; 3) the County Hospital Eye Care Survey; and 4) the Rural School Vision Care Survey. The data from each of the surveys were collected by the authors during 2012. Thirty-three percent of the rural population surveyed self-reported vision problems. Twenty-two percent of subjects surveyed had ever had a vision exam. Among those who self-reported having vision problems, 34% did not wear eyeglasses. Fifty-four percent of those with vision problems who had eyeglasses did not have a vision exam prior to receiving glasses. However, having a vision exam did not always guarantee access to quality vision care. Four channels of vision care service were assessed. The school vision examination program did not increase the usage rate of eyeglasses. Each county-hospital was staffed with three eye-doctors having one year of education beyond high school, serving more than 400,000 residents. Private optometrists often had low levels of education and professional certification. In conclusion, our findings shows that the vision care system in rural China is inadequate and ineffective in meeting the needs of the rural population sampled.

Missionary Zeal: Some Problems with the Rhetoric, Vision and Approach of the AHELO Project

ERIC Educational Resources Information Center

Ashwin, Paul

2015-01-01

The OECD's Assessment of Higher Education Learning Outcomes (AHELO) project is an important contribution to discussions of how to define and measure the quality of global higher education. There is a genuine need for quality measures that can help to ensure students have equitable access to high-quality higher education wherever they study but do…

Senge's Learning Organization and Teachers' Perceptions of Leadership at an Elementary School in Urban Ohio

ERIC Educational Resources Information Center

Moore, Robert J.

2010-01-01

Urban public schools in the United States face the problem of failure to reach academic goals of performance mandated by the No Child Left Behind Act. It was hypothesized that use of Senge's leadership model might result in academic performance in one urban elementary school. Based on Senge's shared vision leadership model as the theoretical…

The Prevalence of Alcohol Abuse among Egerton University Students in Njoro-Kenya

ERIC Educational Resources Information Center

Boitt, Richard Kimuge

2016-01-01

The main objective of higher institutions of learning in Kenya is to provide education and growth experiences for its students but alcohol abuse has continued to be a problem in the university campuses that is slowing down their progress and the Kenya vision 2030 that envisages a healthy population free from the impact of alcohol abuse through the…

Academic Difficulty and Vision Symptoms Children with Concussion

PubMed Central

Swanson, Mark W.; Weise, Katherine K.; Dreer, Laura E.; Johnston, James; Davis, Richard D.; Ferguson, Drew; Hale, M. Heath; Gould, Sara J.; Christy, Jennifer; Busettini, Claudio; Lee, Sarah D.; Swanson, Erin

2016-01-01

Purpose Academic difficulty is reported in children with prolonged post-concussive symptoms. Despite growing evidence that vestibular-ocular and vision-specific dysfunction are common in children following concussion, vision is rarely mentioned in return-to-learn protocols. The purpose of this project was to evaluate a cohort of children with prolonged post-concussive symptoms to determine if vision symptoms are associated with those reporting academic difficulty. Methods Data was obtained from the Children’s of Alabama Concussion Clinic REDCap dataset from the period January 2007 to October 2013. From this dataset of 1,033 concussion events, a cohort of 276 children aged 5–18 years with three or more concussion-related symptoms present for 10 days or more was identified. A cross-sectional cohort study was undertaken to evaluate the association of concussion symptoms, SCAT2 scores, demographic and concussion severity markers to reported educational difficulty among children with prolonged post-concussive symptoms. Univariate and multivariate logistic regression techniques were used to model the association of reported educational difficulty to self-reported vision abnormalities. Results Mean age was 13.8 years. Median time since the concussive event was 21 days, with 33% (95/276) reporting their concussion more than thirty days prior to data collection. Academic difficulty was reported by 29% (79/270) and vision abnormalities in 46% (128/274). After model reduction, vision symptoms (OR 2.17, 95% CI 1.02, 4.62), hearing disturbance (OR 2.39, 95% CI 1.06, 5.36) and concentration difficulty (OR 21.62, 95% CI 9.50, 44.47) remained associated with academic difficulty. For those with symptoms 30 days or more after concussion, only vision (OR 3.15, 95% CI 1.06, 9.38) and concentration difficulty (OR 15.33, 95% CI 4.99, 47.05) remained statistically significant. Conclusions Vision problems were commonly reported in children with concussions and were independently associated with those reporting academic difficulty. Comprehensive vision assessment should be considered in children reporting academic difficulty and in the development of return-to-learn protocols. PMID:27668641

Parent, Teacher, and Student Perspectives on how Corrective Lenses Improve Child Wellbeing and School Function

PubMed Central

Dudovitz, Rebecca N; Izadpanah, Nilufar; Chung, Paul J.; Slusser, Wendelin

2015-01-01

Objectives Up to 20% of school-age children have a vision problem identifiable by screening, over 80% of which can be corrected with glasses. While vision problems are associated with poor school performance, few studies describe whether and how corrective lenses affect academic achievement and health. Further, there are virtually no studies exploring how children with correctable visual deficits, their parents, and teachers perceive the connection between vision care and school function. Methods We conducted a qualitative evaluation of Vision to Learn (VTL), a school-based program providing free corrective lenses to low-income students in Los Angeles. Nine focus groups with students, parents, and teachers from three schools served by VTL explored the relationships between poor vision, receipt of corrective lenses, and school performance and health. Results Twenty parents, 25 teachers, and 21 students from three elementary schools participated. Participants described how uncorrected visual deficits reduced students’ focus, perseverance, and class participation, affecting academic functioning and psychosocial stress; how receiving corrective lenses improved classroom attention, task persistence, and willingness to practice academic skills; and how serving students in school rather than in clinics increased both access to and use of corrective lenses. Conclusions for Practice Corrective lenses may positively impact families, teachers, and students coping with visual deficits by improving school function and psychosocial wellbeing. Practices that increase ownership and use of glasses, such as serving students in school, may significantly improve both child health and academic performance. PMID:26649878

Parent, Teacher, and Student Perspectives on How Corrective Lenses Improve Child Wellbeing and School Function.

PubMed

Dudovitz, Rebecca N; Izadpanah, Nilufar; Chung, Paul J; Slusser, Wendelin

2016-05-01

Up to 20 % of school-age children have a vision problem identifiable by screening, over 80 % of which can be corrected with glasses. While vision problems are associated with poor school performance, few studies describe whether and how corrective lenses affect academic achievement and health. Further, there are virtually no studies exploring how children with correctable visual deficits, their parents, and teachers perceive the connection between vision care and school function. We conducted a qualitative evaluation of Vision to Learn (VTL), a school-based program providing free corrective lenses to low-income students in Los Angeles. Nine focus groups with students, parents, and teachers from three schools served by VTL explored the relationships between poor vision, receipt of corrective lenses, and school performance and health. Twenty parents, 25 teachers, and 21 students from three elementary schools participated. Participants described how uncorrected visual deficits reduced students' focus, perseverance, and class participation, affecting academic functioning and psychosocial stress; how receiving corrective lenses improved classroom attention, task persistence, and willingness to practice academic skills; and how serving students in school rather than in clinics increased both access to and use of corrective lenses. for Practice Corrective lenses may positively impact families, teachers, and students coping with visual deficits by improving school function and psychosocial wellbeing. Practices that increase ownership and use of glasses, such as serving students in school, may significantly improve both child health and academic performance.

Innovative intelligent technology of distance learning for visually impaired people

NASA Astrophysics Data System (ADS)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline.

PubMed

Zhang, Jie; Li, Qingyang; Caselli, Richard J; Thompson, Paul M; Ye, Jieping; Wang, Yalin

2017-06-01

Alzheimer's Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms.

Learning to Look: A Handbook for Parents of Low Vision Infants and Young Children.

ERIC Educational Resources Information Center

Heiner, Donna

Specific and understandable suggestions are offered to parents of severely visually impaired children who have or may have the capacity to learn visually. Parents can assist children with even a small amount of vision to develop that vision from an early age. Vision development begins by ensuring that the child receives appropriate medical and…

School Vision of Learning: Urban Setting

ERIC Educational Resources Information Center

Guy, Tiffany A.

2010-01-01

In this paper, the author develops her school vision of learning. She explains the theories she used to help develop the vision. The author then goes into detail on the methods she will use to make her vision for a school that prepares urban students for a successful life after high school. She takes into account all the stakeholders and how they…

Can Humans Fly Action Understanding with Multiple Classes of Actors

DTIC Science & Technology

2015-06-08

recognition using structure from motion point clouds. In European Conference on Computer Vision, 2008. [5] R. Caruana. Multitask learning. Machine Learning...tonomous driving ? the kitti vision benchmark suite. In IEEE Conference on Computer Vision and Pattern Recognition, 2012. [12] L. Gorelick, M. Blank

Self-Assessment in University Assessment of Prior Learning Procedures

ERIC Educational Resources Information Center

Brinke, D. Joosten-Ten; Sluijsmans, D. M. A.; Jochems, W. M. G.

2009-01-01

Competency-based university education, in which lifelong learning and flexible learning are key elements, demands a renewed vision on assessment. Within this vision, Assessment of Prior Learning (APL), in which learners have to show their prior learning in order for their goals to be recognised, becomes an important element. This article focuses…

Innovation in Health Care Delivery.

PubMed

Sharan, Alok D; Schroeder, Gregory D; West, Michael E; Vaccaro, Alexander R

2016-02-01

As reimbursement transitions from a volume-based to a value-based system, innovation in health care delivery will be needed. The process of innovation begins with framing the problem that needs to be solved along with the strategic vision that has to be achieved. Similar to scientific testing, a hypothesis is generated for a new solution to a problem. Innovation requires conducting a disciplined form of experimentation and then learning from the process. This manuscript will discuss the different types of innovation, and the key steps necessary for successful innovation in the health care field.

From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

PubMed

Grossberg, Stephen

2015-09-24

This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.

A self-learning camera for the validation of highly variable and pseudorandom patterns

NASA Astrophysics Data System (ADS)

Kelley, Michael

2004-05-01

Reliable and productive manufacturing operations have depended on people to quickly detect and solve problems whenever they appear. Over the last 20 years, more and more manufacturing operations have embraced machine vision systems to increase productivity, reliability and cost-effectiveness, including reducing the number of human operators required. Although machine vision technology has long been capable of solving simple problems, it has still not been broadly implemented. The reason is that until now, no machine vision system has been designed to meet the unique demands of complicated pattern recognition. The ZiCAM family was specifically developed to be the first practical hardware to meet these needs. To be able to address non-traditional applications, the machine vision industry must include smart camera technology that meets its users" demands for lower costs, better performance and the ability to address applications of irregular lighting, patterns and color. The next-generation smart cameras will need to evolve as a fundamentally different kind of sensor, with new technology that behaves like a human but performs like a computer. Neural network based systems, coupled with self-taught, n-space, non-linear modeling, promises to be the enabler of the next generation of machine vision equipment. Image processing technology is now available that enables a system to match an operator"s subjectivity. A Zero-Instruction-Set-Computer (ZISC) powered smart camera allows high-speed fuzzy-logic processing, without the need for computer programming. This can address applications of validating highly variable and pseudo-random patterns. A hardware-based implementation of a neural network, Zero-Instruction-Set-Computer, enables a vision system to "think" and "inspect" like a human, with the speed and reliability of a machine.

Socio-Demographic Factors Associated with Alcohol Abuse among Egerton University Students in Njoro-Kenya

ERIC Educational Resources Information Center

Boitt, Richard Kimuge; Boitt, Monicah Lydia; Othieno, Caleb; Obondo, Anne

2016-01-01

The main objective of higher institutions of learning in Kenya is to provide education and growth experiences for its students but alcohol abuse has continued to be a problem in the university campuses that is slowing down their progress and the Kenya vision 2030 that envisages a healthy population free from the impact of alcohol abuse through the…

BI-sparsity pursuit for robust subspace recovery

DOE PAGES

Bian, Xiao; Krim, Hamid

2015-09-01

Here, the success of sparse models in computer vision and machine learning in many real-world applications, may be attributed in large part, to the fact that many high dimensional data are distributed in a union of low dimensional subspaces. The underlying structure may, however, be adversely affected by sparse errors, thus inducing additional complexity in recovering it. In this paper, we propose a bi-sparse model as a framework to investigate and analyze this problem, and provide as a result , a novel algorithm to recover the union of subspaces in presence of sparse corruptions. We additionally demonstrate the effectiveness ofmore » our method by experiments on real-world vision data.« less

Dynamic programming and graph algorithms in computer vision.

PubMed

Felzenszwalb, Pedro F; Zabih, Ramin

2011-04-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.

Vision Problems: How Teachers Can Help.

ERIC Educational Resources Information Center

Desrochers, Joyce

1999-01-01

Describes common vision problems in young children such as myopia, strabismus, and amblyopia. Presents suggestions for helping children with vision problems in the early childhood classroom and in outdoor activities. Lists related resources and children's books. (KB)

Implementing Vision Research in Special Needs Education

ERIC Educational Resources Information Center

Wilhelmsen, Gunvor Birkeland; Aanstad, Monica L.; Leirvik, Eva Iren B.

2015-01-01

This article presents experiences from vision research implemented in education and argues for the need for teachers with visual competence and insight into suitable methods for stimulation and learning. A new type of continuing professional development (CPD) focuses on the role of vision in children's learning and development, the consequences of…

a Fully Automated Pipeline for Classification Tasks with AN Application to Remote Sensing

NASA Astrophysics Data System (ADS)

Suzuki, K.; Claesen, M.; Takeda, H.; De Moor, B.

2016-06-01

Nowadays deep learning has been intensively in spotlight owing to its great victories at major competitions, which undeservedly pushed `shallow' machine learning methods, relatively naive/handy algorithms commonly used by industrial engineers, to the background in spite of their facilities such as small requisite amount of time/dataset for training. We, with a practical point of view, utilized shallow learning algorithms to construct a learning pipeline such that operators can utilize machine learning without any special knowledge, expensive computation environment, and a large amount of labelled data. The proposed pipeline automates a whole classification process, namely feature-selection, weighting features and the selection of the most suitable classifier with optimized hyperparameters. The configuration facilitates particle swarm optimization, one of well-known metaheuristic algorithms for the sake of generally fast and fine optimization, which enables us not only to optimize (hyper)parameters but also to determine appropriate features/classifier to the problem, which has conventionally been a priori based on domain knowledge and remained untouched or dealt with naïve algorithms such as grid search. Through experiments with the MNIST and CIFAR-10 datasets, common datasets in computer vision field for character recognition and object recognition problems respectively, our automated learning approach provides high performance considering its simple setting (i.e. non-specialized setting depending on dataset), small amount of training data, and practical learning time. Moreover, compared to deep learning the performance stays robust without almost any modification even with a remote sensing object recognition problem, which in turn indicates that there is a high possibility that our approach contributes to general classification problems.

Dynamic Programming and Graph Algorithms in Computer Vision*

PubMed Central

Felzenszwalb, Pedro F.; Zabih, Ramin

2013-01-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition. PMID:20660950

Fulfilling a European Vision through Flexible Learning and Choice

ERIC Educational Resources Information Center

Harris, Margaret S. G.

2012-01-01

This article considers the value of flexibility and free choice in learning, and examines the increasing recognition of the evolving and wide range of appropriate environments for learning, such as the workplace, the home, the community, and the virtual world. This "Lifeplace Learning" is compared to the requirements and visions of the…

Automatic Satellite Telemetry Analysis for SSA using Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Stottler, R.; Mao, J.

In April 2016, General Hyten, commander of Air Force Space Command, announced the Space Enterprise Vision (SEV) (http://www.af.mil/News/Article-Display/Article/719941/hyten-announces-space-enterprise-vision/). The SEV addresses increasing threats to space-related systems. The vision includes an integrated approach across all mission areas (communications, positioning, navigation and timing, missile warning, and weather data) and emphasizes improved access to data across the entire enterprise and the ability to protect space-related assets and capabilities. "The future space enterprise will maintain our nation's ability to deliver critical space effects throughout all phases of conflict," Hyten said. Satellite telemetry is going to become available to a new audience. While that telemetry information should be valuable for achieving Space Situational Awareness (SSA), these new satellite telemetry data consumers will not know how to utilize it. We were tasked with applying AI techniques to build an infrastructure to process satellite telemetry into higher abstraction level symbolic space situational awareness and to initially populate that infrastructure with useful data analysis methods. We are working with two organizations, Montana State University (MSU) and the Air Force Academy, both of whom control satellites and therefore currently analyze satellite telemetry to assess the health and circumstances of their satellites. The design which has resulted from our knowledge elicitation and cognitive task analysis is a hybrid approach which combines symbolic processing techniques of Case-Based Reasoning (CBR) and Behavior Transition Networks (BTNs) with current Machine Learning approaches. BTNs are used to represent the process and associated formulas to check telemetry values against anticipated problems and issues. CBR is used to represent and retrieve BTNs that represent an investigative process that should be applied to the telemetry in certain circumstances. Machine Learning is used to learn normal patterns of telemetry, learn pre-mission simulated telemetry patterns that represent known problems, and detect both pre-trained known and unknown abnormalities in real-time. The operational system is currently being implemented and applied to real satellite telemetry data. This paper presents the design, examples, and results of the first version as well as planned future work.

Vision and art: an interdisciplinary approach to neuroscience education.

PubMed

Lafer-Sousa, Rosa; Conway, Bevil R

2009-01-01

Undergraduate institutions are increasingly adopting neuroscience within their curricula, although it is unclear how best to implement this material given the interdisciplinary nature of the field, which requires knowledge of basic physics, chemistry, biology and psychology. This difficulty is compounded by declines over recent decades in the amount of physics education that students receive in high school, which hinders students' ability to grasp basic principles of neuroscience. Here we discuss our experiences as teacher (BRC) and student (RLS) with an undergraduate course in Vision and Art. The course capitalizes on students' prior interest in visual art to motivate an understanding of the physiological and computational neural processes that underlie vision; our aim is that the learning strategies that students acquire as a result of the format and interdisciplinary approach of the course will increase students' critical thinking skills and benefit them as they pursue other domains of inquiry. The course includes both expert lectures on central themes of vision along with a problem-based learning (PBL) laboratory component that directly engages the students as empirical scientists. We outline the syllabus, the motivation for using PBL, and describe a number of hands-on laboratory exercises, many of which require only inexpensive and readily available equipment. We have developed a website that we hope will facilitate student-driven inquiry beyond the classroom and foster inter-institutional collaboration in this endeavor. We conclude the paper with a discussion of the potential limitations of the course and how to evaluate the success of the course and the website.

Encouragement for Faculty to Implement Vision and Change

PubMed Central

Harvey, Caylyn; Eshleman, Kristen; Koo, Kyosung; Smith, Kevin G.; Paradise, Christopher J.; Campbell, A. Malcolm

2016-01-01

The seminal report Vision and Change outlined improvements necessary for undergraduate biology courses to accomplish widely recognized learning objectives. Over the past 8 years, we have developed a two-semester introductory biology course that incorporates the core concepts and competencies recommended in Vision and Change. Using published research on how students learn, we focused our efforts on three main areas of change: pedagogy, course content, and technology. We introduced active-learning strategies to improve our classroom environments, wrote an e-textbook that provides students with the tools they need to construct their own knowledge, and employed an online learning hub to assist students who needed extra support. The redesigned courses have been well received by students, and we have seen good student learning outcomes. The purpose of this essay is to demonstrate to faculty that Vision and Change’s recommendations are feasible and students welcome the improvements. PMID:27810871

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline

PubMed Central

Zhang, Jie; Li, Qingyang; Caselli, Richard J.; Thompson, Paul M.; Ye, Jieping; Wang, Yalin

2017-01-01

Alzheimer’s Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms. PMID:28943731

Addressing economic development goals through innovative teaching of university statistics: a case study of statistical modelling in Nigeria

NASA Astrophysics Data System (ADS)

Oseloka Ezepue, Patrick; Ojo, Adegbola

2012-12-01

A challenging problem in some developing countries such as Nigeria is inadequate training of students in effective problem solving using the core concepts of their disciplines. Related to this is a disconnection between their learning and socio-economic development agenda of a country. These problems are more vivid in statistical education which is dominated by textbook examples and unbalanced assessment 'for' and 'of' learning within traditional curricula. The problems impede the achievement of socio-economic development objectives such as those stated in the Nigerian Vision 2020 blueprint and United Nations Millennium Development Goals. They also impoverish the ability of (statistics) graduates to creatively use their knowledge in relevant business and industry sectors, thereby exacerbating mass graduate unemployment in Nigeria and similar developing countries. This article uses a case study in statistical modelling to discuss the nature of innovations in statistics education vital to producing new kinds of graduates who can link their learning to national economic development goals, create wealth and alleviate poverty through (self) employment. Wider implications of the innovations for repositioning mathematical sciences education globally are explored in this article.

Declarative knowledge and professional vision in teacher education: effect of courses in teaching and learning.

PubMed

Stürmer, Kathleen; Könings, Karen D; Seidel, Tina

2013-09-01

Teachers' professional vision includes the ability to apply general pedagogical knowledge about components of effective teaching and learning to reason about significant features of classroom practice. It requires teachers to (a) describe, (b) explain, and (c) predict classroom situations. Although the acquisition of underling knowledge can be considered as a key element of university-based teacher education programmes, to date, there has been little empirical research on teacher candidates' development of professional vision. This study aims to improve understanding of how different university-based courses in teaching and learning impact the development of professional vision. Participants were teacher candidates (N= 53) attending the same teacher education programme at a German university. They were enrolled in one of three different compulsory courses in teaching and learning, lasting one semester. In a pre-test-post-test design, participants' declarative knowledge about teaching and learning was measured with a test, professional vision with the online tool Observer. Analysis of covariance and multivariate analysis of variance were conducted. Teacher candidates in all three courses showed significant gains both in declarative knowledge and professional vision. Patterns of results differed depending on the course attended. A video-based course with a focus on effective teaching resulted in highest gains in prediction of the consequences of observed events for student learning processes, which is the highest level of knowledge transfer. The development of professional vision is a strongly knowledge-guided process. In line with their content and aims, university-based courses can enhance teaching-relevant knowledge for teacher candidates. © 2012 The British Psychological Society.

Case-based learning facilitates critical thinking in undergraduate nutrition education: students describe the big picture.

PubMed

Harman, Tara; Bertrand, Brenda; Greer, Annette; Pettus, Arianna; Jennings, Jill; Wall-Bassett, Elizabeth; Babatunde, Oyinlola Toyin

2015-03-01

The vision of dietetics professions is based on interdependent education, credentialing, and practice. Case-based learning is a method of problem-based learning that is designed to heighten higher-order thinking. Case-based learning can assist students to connect education and specialized practice while developing professional skills for entry-level practice in nutrition and dietetics. This study examined student perspectives of their learning after immersion into case-based learning in nutrition courses. The theoretical frameworks of phenomenology and Bloom's Taxonomy of Educational Objectives triangulated the design of this qualitative study. Data were drawn from 426 written responses and three focus group discussions among 85 students from three upper-level undergraduate nutrition courses. Coding served to deconstruct the essence of respondent meaning given to case-based learning as a learning method. The analysis of the coding was the constructive stage that led to configuration of themes and theoretical practice pathways about student learning. Four leading themes emerged. Story or Scenario represents the ways that students described case-based learning, changes in student thought processes to accommodate case-based learning are illustrated in Method of Learning, higher cognitive learning that was achieved from case-based learning is represented in Problem Solving, and Future Practice details how students explained perceived professional competency gains from case-based learning. The skills that students acquired are consistent with those identified as essential to professional practice. In addition, the common concept of Big Picture was iterated throughout the themes and demonstrated that case-based learning prepares students for multifaceted problems that they are likely to encounter in professional practice. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Vision Therapy News Backgrounder.

ERIC Educational Resources Information Center

American Optometric Association, St. Louis, MO.

The booklet provides an overview on vision therapy to aid writers, editors, and broadcasters help parents, teachers, older adults, and all consumers learn more about vision therapy. Following a description of vision therapy or vision training, information is provided on how and why vision therapy works. Additional sections address providers of…

The Future of Learning Technology: Some Tentative Predictions

ERIC Educational Resources Information Center

Rushby, Nick

2013-01-01

This paper is a snapshot of an evolving vision of what the future may hold for learning technology. It offers three personal visions of the future and raises many questions that need to be explored if learning technology is to realise its full potential.

Prosopagnosia

MedlinePlus

... to memory dysfunction, memory loss, impaired vision, or learning disabilities. Prosopagnosia is thought to be the result of ... to memory dysfunction, memory loss, impaired vision, or learning disabilities. Prosopagnosia is thought to be the result of ...

2020 Vision: Envisioning a New Generation of STEM Learning Research

ERIC Educational Resources Information Center

Dierking, Lynn D.; Falk, John H.

2016-01-01

In this issue, we have compiled six original papers, outcomes from the U.S. National Science Foundation (US-NSF)-funded REESE (Research and Evaluation on Education in Science and Engineering) 2020 Vision: The Next Generation of STEM Learning Research project. The purpose of 2020 Vision was to re-envision the questions and frameworks guiding STEM…

The Non-Instrumental Vision of the Learning Society

ERIC Educational Resources Information Center

Su, Yahui

2010-01-01

This essay considers the non-instrumental vision of the learning society through the analysis of its conceptual logic and meaning based on A. J. Cropley's approach. It outlines a view of the learning society whereby learning is an end in itself rather than a means of achieving other economic or civic purposes, as currently described in relevant…

Rapid and highly resolving associative affective learning: convergent electro- and magnetoencephalographic evidence from vision and audition.

PubMed

Steinberg, Christian; Bröckelmann, Ann-Kathrin; Rehbein, Maimu; Dobel, Christian; Junghöfer, Markus

2013-03-01

Various pathway models for emotional processing suggest early prefrontal contributions to affective stimulus evaluation. Yet, electrophysiological evidence for such rapid modulations is still sparse. In a series of four MEG/EEG studies which investigated associative learning in vision and audition using a novel MultiCS Conditioning paradigm, many different neutral stimuli (faces, tones) were paired with aversive and appetitive events in only two to three learning instances. Electrophysiological correlates of neural activity revealed highly significant amplified processing for conditioned stimuli within distributed prefrontal and sensory cortical networks. In both, vision and audition, affect-specific responses occurred in two successive waves of rapid (vision: 50-80 ms, audition: 25-65 ms) and mid-latency (vision: >130 ms, audition: >100 ms) processing. Interestingly, behavioral measures indicated that MultiCS Conditioning successfully prevented contingency awareness. We conclude that affective processing rapidly recruits highly elaborate and widely distributed networks with substantial capacity for fast learning and excellent resolving power. Copyright © 2012 Elsevier B.V. All rights reserved.

Lighthouse Guild

MedlinePlus

... Contact Us About Us Programs & Services Health Plans eLearning Vision + Health Donate Need Help? Show Menu Hide ... Find a health plan Coping with vision loss eLearning Support for parents of children with visual impairments ...

Web-based learning: pros, cons and controversies.

PubMed

Cook, David A

2007-01-01

Advantages of web-based learning (WBL) in medical education include overcoming barriers of distance and time, economies of scale, and novel instructional methods, while disadvantages include social isolation, up-front costs, and technical problems. Web-based learning is purported to facilitate individualised instruction, but this is currently more vision than reality. More importantly, many WBL instructional designs fail to incorporate principles of effective learning, and WBL is often used for the wrong reasons (e.g., for the sake of technology). Rather than trying to decide whether WBL is superior to or equivalent to other instructional media (research addressing this question will always be confounded), we should accept it as a potentially powerful instructional tool, and focus on learning when and how to use it. Educators should recognise that high fidelity, multimedia, simulations, and even WBL itself will not always be necessary to effectively facilitate learning.

Analytical Cost Metrics : Days of Future Past

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

Prajapati, Nirmal; Rajopadhye, Sanjay; Djidjev, Hristo Nikolov

As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems. These problems arise in almost all areas of computing, ranging from big data analytics, artificial intelligence, search, machine learning, virtual/augmented reality, computer vision, image/signal processing to computational science and bioinformatics. With Moore’s law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency. Therefore the major challenge that we face in computing systems researchmore » is: “how to solve massive-scale computational problems in the most time/power/energy efficient manner?”« less

Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation.

PubMed

Dominguez Veiga, Jose Juan; O'Reilly, Martin; Whelan, Darragh; Caulfield, Brian; Ward, Tomas E

2017-08-04

Inertial sensors are one of the most commonly used sources of data for human activity recognition (HAR) and exercise detection (ED) tasks. The time series produced by these sensors are generally analyzed through numerical methods. Machine learning techniques such as random forests or support vector machines are popular in this field for classification efforts, but they need to be supported through the isolation of a potentially large number of additionally crafted features derived from the raw data. This feature preprocessing step can involve nontrivial digital signal processing (DSP) techniques. However, in many cases, the researchers interested in this type of activity recognition problems do not possess the necessary technical background for this feature-set development. The study aimed to present a novel application of established machine vision methods to provide interested researchers with an easier entry path into the HAR and ED fields. This can be achieved by removing the need for deep DSP skills through the use of transfer learning. This can be done by using a pretrained convolutional neural network (CNN) developed for machine vision purposes for exercise classification effort. The new method should simply require researchers to generate plots of the signals that they would like to build classifiers with, store them as images, and then place them in folders according to their training label before retraining the network. We applied a CNN, an established machine vision technique, to the task of ED. Tensorflow, a high-level framework for machine learning, was used to facilitate infrastructure needs. Simple time series plots generated directly from accelerometer and gyroscope signals are used to retrain an openly available neural network (Inception), originally developed for machine vision tasks. Data from 82 healthy volunteers, performing 5 different exercises while wearing a lumbar-worn inertial measurement unit (IMU), was collected. The ability of the proposed method to automatically classify the exercise being completed was assessed using this dataset. For comparative purposes, classification using the same dataset was also performed using the more conventional approach of feature-extraction and classification using random forest classifiers. With the collected dataset and the proposed method, the different exercises could be recognized with a 95.89% (3827/3991) accuracy, which is competitive with current state-of-the-art techniques in ED. The high level of accuracy attained with the proposed approach indicates that the waveform morphologies in the time-series plots for each of the exercises is sufficiently distinct among the participants to allow the use of machine vision approaches. The use of high-level machine learning frameworks, coupled with the novel use of machine vision techniques instead of complex manually crafted features, may facilitate access to research in the HAR field for individuals without extensive digital signal processing or machine learning backgrounds. ©Jose Juan Dominguez Veiga, Martin O'Reilly, Darragh Whelan, Brian Caulfield, Tomas E Ward. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.08.2017.

Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation

PubMed Central

O'Reilly, Martin; Whelan, Darragh; Caulfield, Brian; Ward, Tomas E

2017-01-01

Background Inertial sensors are one of the most commonly used sources of data for human activity recognition (HAR) and exercise detection (ED) tasks. The time series produced by these sensors are generally analyzed through numerical methods. Machine learning techniques such as random forests or support vector machines are popular in this field for classification efforts, but they need to be supported through the isolation of a potentially large number of additionally crafted features derived from the raw data. This feature preprocessing step can involve nontrivial digital signal processing (DSP) techniques. However, in many cases, the researchers interested in this type of activity recognition problems do not possess the necessary technical background for this feature-set development. Objective The study aimed to present a novel application of established machine vision methods to provide interested researchers with an easier entry path into the HAR and ED fields. This can be achieved by removing the need for deep DSP skills through the use of transfer learning. This can be done by using a pretrained convolutional neural network (CNN) developed for machine vision purposes for exercise classification effort. The new method should simply require researchers to generate plots of the signals that they would like to build classifiers with, store them as images, and then place them in folders according to their training label before retraining the network. Methods We applied a CNN, an established machine vision technique, to the task of ED. Tensorflow, a high-level framework for machine learning, was used to facilitate infrastructure needs. Simple time series plots generated directly from accelerometer and gyroscope signals are used to retrain an openly available neural network (Inception), originally developed for machine vision tasks. Data from 82 healthy volunteers, performing 5 different exercises while wearing a lumbar-worn inertial measurement unit (IMU), was collected. The ability of the proposed method to automatically classify the exercise being completed was assessed using this dataset. For comparative purposes, classification using the same dataset was also performed using the more conventional approach of feature-extraction and classification using random forest classifiers. Results With the collected dataset and the proposed method, the different exercises could be recognized with a 95.89% (3827/3991) accuracy, which is competitive with current state-of-the-art techniques in ED. Conclusions The high level of accuracy attained with the proposed approach indicates that the waveform morphologies in the time-series plots for each of the exercises is sufficiently distinct among the participants to allow the use of machine vision approaches. The use of high-level machine learning frameworks, coupled with the novel use of machine vision techniques instead of complex manually crafted features, may facilitate access to research in the HAR field for individuals without extensive digital signal processing or machine learning backgrounds. PMID:28778851

Septo-Optic Dysplasia

MedlinePlus

... children with SOD have normal intelligence, others have learning disabilities. Most, however, are developmentally delayed due to vision ... children with SOD have normal intelligence, others have learning disabilities. Most, however, are developmentally delayed due to vision ...

Taking Stock: Existing Resources for Assessing a New Vision of Science Learning

ERIC Educational Resources Information Center

Alonzo, Alicia C.; Ke, Li

2016-01-01

A new vision of science learning described in the "Next Generation Science Standards"--particularly the science and engineering practices and their integration with content--pose significant challenges for large-scale assessment. This article explores what might be learned from advances in large-scale science assessment and…

Vision and the Achievement Gap among Urban Minority Youth

ERIC Educational Resources Information Center

Basch, Charles E.

2011-01-01

Objectives: To outline the prevalence and disparities of vision problems among school-aged urban minority youth, causal pathways through which vision problems adversely affects academic achievement, and proven or promising approaches for schools to address these problems. Methods: Literature review. Results: More than 20% of school-aged youth have…

A Vision of E-Learning for America's Workforce: Report of the Commission on Technology and Adult Learning.

ERIC Educational Resources Information Center

American Society for Training and Development, Alexandria, VA.

In 2000, the American Society for Training and Development and the National Governors Association convened the Commission on Technology and Adult Learning. The 31-member commission included representatives of the business, government, and education sectors. They formulated a vision for the future of e-learning in the United States and identified…

The Development of a Robot-Based Learning Companion: A User-Centered Design Approach

ERIC Educational Resources Information Center

Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong

2015-01-01

A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…

Central and peripheral vision loss differentially affects contextual cueing in visual search.

PubMed

Geringswald, Franziska; Pollmann, Stefan

2015-09-01

Visual search for targets in repeated displays is more efficient than search for the same targets in random distractor layouts. Previous work has shown that this contextual cueing is severely impaired under central vision loss. Here, we investigated whether central vision loss, simulated with gaze-contingent displays, prevents the incidental learning of contextual cues or the expression of learning, that is, the guidance of search by learned target-distractor configurations. Visual search with a central scotoma reduced contextual cueing both with respect to search times and gaze parameters. However, when the scotoma was subsequently removed, contextual cueing was observed in a comparable magnitude as for controls who had searched without scotoma simulation throughout the experiment. This indicated that search with a central scotoma did not prevent incidental context learning, but interfered with search guidance by learned contexts. We discuss the role of visuospatial working memory load as source of this interference. In contrast to central vision loss, peripheral vision loss was expected to prevent spatial configuration learning itself, because the restricted search window did not allow the integration of invariant local configurations with the global display layout. This expectation was confirmed in that visual search with a simulated peripheral scotoma eliminated contextual cueing not only in the initial learning phase with scotoma, but also in the subsequent test phase without scotoma. (c) 2015 APA, all rights reserved).

Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments on monocular distance learning

NASA Astrophysics Data System (ADS)

van Hecke, Kevin; de Croon, Guido C. H. E.; Hennes, Daniel; Setterfield, Timothy P.; Saenz-Otero, Alvar; Izzo, Dario

2017-11-01

Although machine learning holds an enormous promise for autonomous space robots, it is currently not employed because of the inherent uncertain outcome of learning processes. In this article we investigate a learning mechanism, Self-Supervised Learning (SSL), which is very reliable and hence an important candidate for real-world deployment even on safety-critical systems such as space robots. To demonstrate this reliability, we introduce a novel SSL setup that allows a stereo vision equipped robot to cope with the failure of one of its cameras. The setup learns to estimate average depth using a monocular image, by using the stereo vision depths from the past as trusted ground truth. We present preliminary results from an experiment on the International Space Station (ISS) performed with the MIT/NASA SPHERES VERTIGO satellite. The presented experiments were performed on October 8th, 2015 on board the ISS. The main goals were (1) data gathering, and (2) navigation based on stereo vision. First the astronaut Kimiya Yui moved the satellite around the Japanese Experiment Module to gather stereo vision data for learning. Subsequently, the satellite freely explored the space in the module based on its (trusted) stereo vision system and a pre-programmed exploration behavior, while simultaneously performing the self-supervised learning of monocular depth estimation on board. The two main goals were successfully achieved, representing the first online learning robotic experiments in space. These results lay the groundwork for a follow-up experiment in which the satellite will use the learned single-camera depth estimation for autonomous exploration in the ISS, and are an advancement towards future space robots that continuously improve their navigation capabilities over time, even in harsh and completely unknown space environments.

Screening for Vision Problems, Including Usher's Syndrome, among Hearing Impaired Students.

ERIC Educational Resources Information Center

Fillman, Robyn D.; And Others

1987-01-01

A screening program for vision problems and Usher's Syndrome (a common cause of deaf-blindness) among 210 hearing-impaired students found 44 percent had significant vision problems and 1 percent had Usher's Syndrome. The program involved an interagency network of school, health care, and support personnel and utilized a dilated ophathalmological…

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

Ithapu, Vamsi K.; Kondor, Risi; Johnson, Sterling C.; Singh, Vikas

2017-01-01

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision. PMID:29416293

Rationale, Design and Implementation of a Computer Vision-Based Interactive E-Learning System

ERIC Educational Resources Information Center

Xu, Richard Y. D.; Jin, Jesse S.

2007-01-01

This article presents a schematic application of computer vision technologies to e-learning that is synchronous, peer-to-peer-based, and supports an instructor's interaction with non-computer teaching equipments. The article first discusses the importance of these focused e-learning areas, where the properties include accurate bidirectional…

Application of DBNs for concerned internet information detecting

NASA Astrophysics Data System (ADS)

Wang, Yanfang; Gao, Song

2017-03-01

In recent years, deep learning has achieved great success in many fields, ranging from voice recognition and image classification to computer vision. In this study we apply DBNs to concerned internet information in Chinese detecting problem, since there are inherent differences between English and Chinese. Contrastive divergence (CD) is employed in the DBNs to learn a multi-layer generative model from numerous unlabeled data. The features obtained by this model are used to initialize the feed-forward neural network, which can be fine-tuned with backpropagation. Experiment results indicate that, the model and training method we proposed can be used to detect the concerned internet information effectively and accurately.

Seeing is believing: effects of visual contextual cues on learning and transfer of locomotor adaptation.

PubMed

Torres-Oviedo, Gelsy; Bastian, Amy J

2010-12-15

Devices such as robots or treadmills are often used to drive motor learning because they can create novel physical environments. However, the learning (i.e., adaptation) acquired on these devices only partially generalizes to natural movements. What determines the specificity of motor learning, and can this be reliably made more general? Here we investigated the effect of visual cues on the specificity of split-belt walking adaptation. We systematically removed vision to eliminate the visual-proprioceptive mismatch that is a salient cue specific to treadmills: vision indicates that we are not moving while leg proprioception indicates that we are. We evaluated the adaptation of temporal and spatial features of gait (i.e., timing and location of foot landing), their transfer to walking over ground, and washout of adaptation when subjects returned to the treadmill. Removing vision during both training (i.e., on the treadmill) and testing (i.e., over ground) strongly improved the transfer of treadmill adaptation to natural walking. Removing vision only during training increased transfer of temporal adaptation, whereas removing vision only during testing increased the transfer of spatial adaptation. This dissociation reveals differences in adaptive mechanisms for temporal and spatial features of walking. Finally training without vision increased the amount that was learned and was linked to the variability in the behavior during adaptation. In conclusion, contextual cues can be manipulated to modulate the magnitude, transfer, and washout of device-induced learning in humans. These results bring us closer to our ultimate goal of developing rehabilitation strategies that improve movements beyond the clinical setting.

Case-based learning in endocrine physiology: an approach toward self-directed learning and the development of soft skills in medical students.

PubMed

Gade, Shubhada; Chari, Suresh

2013-12-01

The Medical Council of India, in the recent Vision 2015 document, recommended curricular reforms for undergraduates. Case-based learning (CBL) is one method where students are motivated toward self-directed learning and to develop analytic and problem-solving skills. An overview of thyroid physiology was given in a didactic lecture. A paper-based case scenario of multinodular goiter was given to phase I Bachelor of Medicine, Bachelor of Surgery students in two sessions. An attitude survey of the students and teachers was done using a Likert scale ranging from strongly disagrees to strongly agree. A pretest and posttest were conducted. The students opined that CBL helped them to better their understanding of a particular topic, gave them better retention of knowledge, helped them to relate clinical conditions to basic sciences, improved soft skills such as communication skills and group dynamics, and promoted a better teacher-student relationship. There was significant improvement in student's performance when pre- and posttest scores were compared (P = 0.018). Furthermore, faculty members opined that CBL promoted self-study and problem-solving abilities of the students. In conclusion, CBL motivates students toward self-directed learning and to develop analytic and problem-solving skills; thus, CBL could be beneficial for students' entry into clinical departments and, finally, in managing patients.

Lessons Learned from the Creation of a Center of Excellence in Low Vision and Vision Rehabilitation in Wenzhou, China

ERIC Educational Resources Information Center

Marinoff, Rebecca; Heilberger, Michael H.

2017-01-01

A model Center of Excellence in Low Vision and Vision Rehabilitation was created in a health care setting in China utilizing an inter-institutional relationship with a United States optometric institution. Accomplishments of, limitations to, and stimuli to the provision of low vision and vision rehabilitation services are shared.

Non-Native Chinese Language Learners' Attitudes towards Online Vision-Based Motion Games

ERIC Educational Resources Information Center

Hao, Yungwei; Hong, Jon-Chao; Jong, Jyh-Tsorng; Hwang, Ming-Yueh; Su, Chao-Ya; Yang, Jin-Shin

2010-01-01

Learning to write Chinese characters is often thought to be a very challenging and laborious task. However, new learning tools are being designed that might reduce learners' tedium. This study explores one such tool, an online program in which learners can learn Chinese characters through vision-based motion games. The learner's gestures are…

Learning from failure in health care: frequent opportunities, pervasive barriers.

PubMed

Edmondson, A C

2004-12-01

The notion that hospitals and medical practices should learn from failures, both their own and others', has obvious appeal. Yet, healthcare organisations that systematically and effectively learn from the failures that occur in the care delivery process, especially from small mistakes and problems rather than from consequential adverse events, are rare. This article explores pervasive barriers embedded in healthcare's organisational systems that make shared or organisational learning from failure difficult and then recommends strategies for overcoming these barriers to learning from failure, emphasising the critical role of leadership. Firstly, leaders must create a compelling vision that motivates and communicates urgency for change; secondly, leaders must work to create an environment of psychological safety that fosters open reporting, active questioning, and frequent sharing of insights and concerns; and thirdly, case study research on one hospital's organisational learning initiative suggests that leaders can empower and support team learning throughout their organisations as a way of identifying, analysing, and removing hazards that threaten patient safety.

Learning from failure in health care: frequent opportunities, pervasive barriers

PubMed Central

Edmondson, A

2004-01-01

The notion that hospitals and medical practices should learn from failures, both their own and others', has obvious appeal. Yet, healthcare organisations that systematically and effectively learn from the failures that occur in the care delivery process, especially from small mistakes and problems rather than from consequential adverse events, are rare. This article explores pervasive barriers embedded in healthcare's organisational systems that make shared or organisational learning from failure difficult and then recommends strategies for overcoming these barriers to learning from failure, emphasising the critical role of leadership. Firstly, leaders must create a compelling vision that motivates and communicates urgency for change; secondly, leaders must work to create an environment of psychological safety that fosters open reporting, active questioning, and frequent sharing of insights and concerns; and thirdly, case study research on one hospital's organisational learning initiative suggests that leaders can empower and support team learning throughout their organisations as a way of identifying, analysing, and removing hazards that threaten patient safety. PMID:15576689

Student performance and appreciation using 3D vs. 2D vision in a virtual learning environment.

PubMed

de Boer, I R; Wesselink, P R; Vervoorn, J M

2016-08-01

The aim of this study was to investigate the differences in the performance and appreciation of students working in a virtual learning environment with two (2D)- or three (3D)-dimensional vision. One hundred and twenty-four randomly divided first-year dental students performed a manual dexterity exercise on the Simodont dental trainer with an automatic assessment. Group 1 practised in 2D vision and Group 2 in 3D. All of the students practised five times for 45 min and then took a test using the vision they had practised in. After test 1, all of the students switched the type of vision to control for the learning curve: Group 1 practised in 3D and took a test in 3D, whilst Group 2 practised in 2D and took the test in 2D. To pass, three of five exercises had to be successfully completed within a time limit. The students filled out a questionnaire after completing test 2. The results show that students working with 3D vision achieved significantly better results than students who worked in 2D. Ninety-five per cent of the students filled out the questionnaire, and over 90 per cent preferred 3D vision. The use of 3D vision in a virtual learning environment has a significant positive effect on the performance of the students as well as on their appreciation of the environment. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Statistical and Variational Methods for Problems in Visual Control

DTIC Science & Technology

2009-03-02

plane curves to round points," /. Differential Geometry 26 (1987), pp. 285-314. 12 [7] S. Haker , G. Sapiro, and A. Tannenbaum, "Knowledge-based...segmentation of SAR data with learned priors," IEEE Trans. Image Processing, vol. 9, pp. 298-302, 2000. [8] S. Haker , L. Zhu, S. Angenent, and A...Tannenbaum, "Optimal mass transport for registration and warping" Int. Journal Computer Vision, vol. 60, pp. 225-240, 2004. [9] S. Haker , G. Sapiro, A

A Vision in Jeopardy: Royal Navy Maritime Autonomous Systems (MAS)

DTIC Science & Technology

2017-03-31

Chapter 6 will propose a new MAS vision for the RN. However, before doing so, a fresh look at the problem is required. Consensus of the Problem, Not the... assessment , the RN has failed to deliver any sustainable MAS operational capability. A vision for MAS finally materialized in 2014. Yet, the vision...continuous investment and assessment , the RN has failed to deliver any sustainable MAS operational capability. A vision for MAS finally materialized in

Analog "neuronal" networks in early vision.

PubMed Central

Koch, C; Marroquin, J; Yuille, A

1986-01-01

Many problems in early vision can be formulated in terms of minimizing a cost function. Examples are shape from shading, edge detection, motion analysis, structure from motion, and surface interpolation. As shown by Poggio and Koch [Poggio, T. & Koch, C. (1985) Proc. R. Soc. London, Ser. B 226, 303-323], quadratic variational problems, an important subset of early vision tasks, can be "solved" by linear, analog electrical, or chemical networks. However, in the presence of discontinuities, the cost function is nonquadratic, raising the question of designing efficient algorithms for computing the optimal solution. Recently, Hopfield and Tank [Hopfield, J. J. & Tank, D. W. (1985) Biol. Cybern. 52, 141-152] have shown that networks of nonlinear analog "neurons" can be effective in computing the solution of optimization problems. We show how these networks can be generalized to solve the nonconvex energy functionals of early vision. We illustrate this approach by implementing a specific analog network, solving the problem of reconstructing a smooth surface from sparse data while preserving its discontinuities. These results suggest a novel computational strategy for solving early vision problems in both biological and real-time artificial vision systems. PMID:3459172

American Academy of Optometry

MedlinePlus

... Publications Contact the Foundation Promoting the Art and Science of Vision Care through lifelong learning Become a ... 07, 2017 View all news Optometry and Vision Science Journal Optometry and Vision Science is the official ...

Nonlinear programming for classification problems in machine learning

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

2016-10-01

We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.

Video based object representation and classification using multiple covariance matrices.

PubMed

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Traveling with Science

ERIC Educational Resources Information Center

Fast, Danene; Wild, Tiffany

2018-01-01

For early elementary students with vision loss, these seemingly simple questions can pose great difficulty, especially when conceptual development is being established. Because students with vision loss are unable to observe non-verbal cues within environmental settings, supplemental learning techniques must be utilized for learning. In science,…

Impact of Project-Based Curriculum Materials on Student Learning in Science: Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Harris, Christopher J.; Penuel, William R.; D'Angelo, Cynthia M.; DeBarger, Angela Haydel; Gallagher, Lawrence P.; Kennedy, Cathleen A.; Cheng, Britte Haugen; Krajcik, Joseph S.

2015-01-01

The "Framework for K-12 Science Education" (National Research Council, 2012) sets an ambitious vision for science learning by emphasizing that for students to achieve proficiency in science they will need to participate in the authentic practices of scientists. To realize this vision, all students will need opportunities to learn from…

2020 Vision: Envisioning a new generation of STEM learning research

NASA Astrophysics Data System (ADS)

Dierking, Lynn D.; Falk, John H.

2016-03-01

In this issue, we have compiled six original papers, outcomes from the U.S. National Science Foundation (US-NSF)-funded REESE (Research and Evaluation on Education in Science and Engineering) 2020 Vision: The Next Generation of STEM Learning Research project. The purpose of 2020 Vision was to re-envision the questions and frameworks guiding STEM research in the twenty-first century, given that notions of learning have changed significantly in the last decade. The papers present diverse research principles that emerged from an initial 2020 Vision conference at Oregon State University (OSU), were then vetted more broadly with the science education community nationally and internationally, and presented in a public 2020 Vision symposium series also at OSU. Individually and as a group, these papers argue that if STEM learning is lifelong, life-wide and life-deep, research designs need to cut across the diverse settings and investigate the multiple contexts and media in which learners live and interact. Authors call for research paradigms that holistically reflect questions of the "what, when, where, why, how and with whom" of STEM learning. Associated Forum papers respond and expand the conversation by critically examining the recommended research principles and in some cases, challenging both authors and editors to think even more broadly. Two Key Contributor pieces highlight the contributions of researchers who have helped to push on these research boundaries, advancing science education research nationally and internationally. A final synthesis paper, a case study of research being conducted in a diverse, under-resourced community in Portland, Oregon provides one example of how the 2020 Vision research principles might be integrated into a comprehensive STEM learning research study.

Riemann tensor of motion vision revisited.

PubMed

Brill, M

2001-07-02

This note shows that the Riemann-space interpretation of motion vision developed by Barth and Watson is neither necessary for their results, nor sufficient to handle an intrinsic coordinate problem. Recasting the Barth-Watson framework as a classical velocity-solver (as in computer vision) solves these problems.

Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.

NASA Astrophysics Data System (ADS)

Battiti, Roberto

1990-01-01

This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from multiple-purpose modules. In the last part of the thesis a well known optimization method (the Broyden-Fletcher-Goldfarb-Shanno memoryless quasi -Newton method) is applied to simple classification problems and shown to be superior to the "error back-propagation" algorithm for numerical stability, automatic selection of parameters, and convergence properties.

Tunnel Vision in Environmental Management.

ERIC Educational Resources Information Center

Miller, Alan

1982-01-01

Discusses problem-solving styles in environmental management and the specific deficiencies in these styles that might be grouped under the label "tunnel vision," a form of selective attention contributing to inadequate problem-formulation, partial solutions to complex problems, and generation of additional problems. Includes educational…

Newly qualified teachers' visions of science learning and teaching

NASA Astrophysics Data System (ADS)

Roberts, Deborah L.

2011-12-01

This study investigated newly qualified teachers' visions of science learning and teaching. The study also documented their preparation in an elementary science methods course. The research questions were: What educational and professional experiences influenced the instructor's visions of science learning and teaching? What visions of science learning and teaching were promoted in the participants' science methods course? What visions of science learning and teaching did these newly qualified teachers bring with them as they graduated from their teacher preparation program? How did these visions compare with those advocated by reform documents? Data sources included participants' assignments, weekly reflections, and multi-media portfolio finals. Semi-structured interviews provided the emic voice of participants, after graduation but before they had begun to teach. These data were interpreted via a combination of qualitative methodologies. Vignettes described class activities. Assertions supported by excerpts from participants' writings emerged from repeated review of their assignments. A case study of a typical participant characterized weekly reflections and final multi-media portfolio. Four strands of science proficiency articulated in a national reform document provided a framework for interpreting activities, assignments, and interview responses. Prior experiences that influenced design of the methods course included an inquiry-based undergraduate physics course, participation in a reform-based teacher preparation program, undergraduate and graduate inquiry-based science teaching methods courses, participation in a teacher research group, continued connection to the university as a beginning teacher, teaching in diverse Title 1 schools, service as the county and state elementary science specialist, participation in the Carnegie Academy for the Scholarship of Teaching and Learning, service on a National Research Council committee, and experience teaching a science methods course. The methods course studied here emphasized reform-based practices, science as inquiry, culturally responsive teaching, scientific discourse, and integration of science with technology and other disciplines. Participants' writings and interview responses articulated visions of science learning and teaching that included aspects of reform-based practices. Some participants intentionally incorporated and implemented reform-based strategies in field placements during the methods course and student teaching. The strands of scientific proficiency were evident in activities, assignments and participants' interviews in varying degrees.

Broad-based visual benefits from training with an integrated perceptual-learning video game.

PubMed

Deveau, Jenni; Lovcik, Gary; Seitz, Aaron R

2014-06-01

Perception is the window through which we understand all information about our environment, and therefore deficits in perception due to disease, injury, stroke or aging can have significant negative impacts on individuals' lives. Research in the field of perceptual learning has demonstrated that vision can be improved in both normally seeing and visually impaired individuals, however, a limitation of most perceptual learning approaches is their emphasis on isolating particular mechanisms. In the current study, we adopted an integrative approach where the goal is not to achieve highly specific learning but instead to achieve general improvements to vision. We combined multiple perceptual learning approaches that have individually contributed to increasing the speed, magnitude and generality of learning into a perceptual-learning based video-game. Our results demonstrate broad-based benefits of vision in a healthy adult population. Transfer from the game includes; improvements in acuity (measured with self-paced standard eye-charts), improvement along the full contrast sensitivity function, and improvements in peripheral acuity and contrast thresholds. The use of this type of this custom video game framework built up from psychophysical approaches takes advantage of the benefits found from video game training while maintaining a tight link to psychophysical designs that enable understanding of mechanisms of perceptual learning and has great potential both as a scientific tool and as therapy to help improve vision. Copyright © 2014 Elsevier B.V. All rights reserved.

Towards a Framework for Modeling Space Systems Architectures

NASA Technical Reports Server (NTRS)

Shames, Peter; Skipper, Joseph

2006-01-01

Topics covered include: 1) Statement of the problem: a) Space system architecture is complex; b) Existing terrestrial approaches must be adapted for space; c) Need a common architecture methodology and information model; d) Need appropriate set of viewpoints. 2) Requirements on a space systems model. 3) Model Based Engineering and Design (MBED) project: a) Evaluated different methods; b) Adapted and utilized RASDS & RM-ODP; c) Identified useful set of viewpoints; d) Did actual model exchanges among selected subset of tools. 4) Lessons learned & future vision.

[Improvement of vision through perceptual learning in the case of refractive errors and presbyopia : A critical valuation].

PubMed

Heinrich, S P

2017-02-01

The idea of compensating or even rectifying refractive errors and presbyopia with the help of vision training is not new. For most approaches, however, scientific evidence is insufficient. A currently promoted method is "perceptual learning", which is assumed to improve stimulus processing in the brain. The basic phenomena of perceptual learning have been demonstrated by a multitude of studies. Some of these specifically address the case of refractive errors and presbyopia. However, many open questions remain, in particular with respect to the transfer of practice effects to every-day vision. At present, the method should therefore be judged with caution.

The Pedagogy of Teaching Educational Vision: A Vision Coach's Field Notes about Leaders as Learners

ERIC Educational Resources Information Center

Schein, Jeffrey

2009-01-01

The emerging field of educational visioning is full of challenges and phenomena worthy of careful analysis and documentation. A relatively neglected phenomenon is the learning curve of the leaders (often lay leaders) involved in the visioning process. This article documents a range of experiences of the author serving as a vision coach to five…

Selecting the Most Appropriate Primary Learning Medium for Students with Functional Vision.

ERIC Educational Resources Information Center

Mangold, S.; Mangold, P.

1989-01-01

Five considerations for determining the most appropriate learning medium for students with functional vision are: (1) working distance from the page; (2) portability of reading skills; (3) reading rates and accuracy; (4) visual fatigue; and (5) interpretation of assessment results. (Author/DB)

Vision and academic performance of learning disabled children.

PubMed

Wharry, R E; Kirkpatrick, S W

1986-02-01

The purpose of this study was to assess difference in academic performance among myopic, hyperopic, and emmetropic children who were learning disabled. More specifically, myopic children were expected to perform better on mathematical and spatial tasks than would hyperopic ones and that hyperopic and emmetropic children would perform better on verbal measures than would myopic ones. For 439 learning disabled students visual anomalies were determined via a Generated Retinal Reflex Image Screening System. Test data were obtained from school files. Partial support for the hypothesis was obtained. Myopic learning disabled children outperformed hyperopic and emmetropic children on the Key Math test. Myopic children scored better than hyperopic children on the WRAT Reading subtest and on the Durrell Analysis of Reading Difficulty Oral Reading Comprehension, Oral Rate, Flashword, and Spelling subtests, and on the Key Math Measurement and Total Scores. Severity of refractive error significantly affected the Wechsler Intelligence Scale for Children--Revised Full Scale, Performance Scale, Verbal Scale, and Digit Span scores but did not affect any academic test scores. Several other findings were also reported. Those with nonametropic problems scored higher than those without problems on the Key Math Time subtest. Implications supportive of the theories of Benbow and Benbow and Geschwind and Behan were stated.

Differences in children and adolescents' ability of reporting two CVS-related visual problems.

PubMed

Hu, Liang; Yan, Zheng; Ye, Tiantian; Lu, Fan; Xu, Peng; Chen, Hao

2013-01-01

The present study examined whether children and adolescents can correctly report dry eyes and blurred distance vision, two visual problems associated with computer vision syndrome. Participants are 913 children and adolescents aged 6-17. They were asked to report their visual problems, including dry eyes and blurred distance vision, and received an eye examination, including tear film break-up time (TFBUT) and visual acuity (VA). Inconsistency was found between participants' reports of dry eyes and TFBUT results among all 913 participants as well as for all of four subgroups. In contrast, consistency was found between participants' reports of blurred distance vision and VA results among 873 participants who had never worn glasses as well as for the four subgroups. It was concluded that children and adolescents are unable to report dry eyes correctly; however, they are able to report blurred distance vision correctly. Three practical implications of the findings were discussed. Little is known about children's ability to report their visual problems, an issue critical to diagnosis and treatment of children's computer vision syndrome. This study compared children's self-reports and clinic examination results and found children can correctly report blurred distance vision but not dry eyes.

Vision Care and the Nation's Children.

ERIC Educational Resources Information Center

American Optometric Association, St. Louis, MO.

Aspects of vision and vision care considered are the following: extent and types of vision defects of American children; importance of vision care in pre-school years, elementary, and secondary school and beyond; and manpower resources in vision care today, the extent of vision testing and care, special problem areas, and governmental support.…

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

PubMed Central

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems. PMID:28079187

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

PubMed

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-12

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

NASA Astrophysics Data System (ADS)

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

Vision Systems with the Human in the Loop

NASA Astrophysics Data System (ADS)

Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

2005-12-01

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

Vision impairment and dual sensory problems in middle age

PubMed Central

Dawes, Piers; Dickinson, Christine; Emsley, Richard; Bishop, Paul; Cruickshanks, Karen; Edmondson-Jones, Mark; McCormack, Abby; Fortnum, Heather; Moore, David R.; Norman, Paul; Munro, Kevin

2014-01-01

Purpose Vision and hearing impairments are known to increase in middle age. In this study we describe the prevalence of vision impairment and dual sensory impairment in UK adults aged 40 to 69 years in a very large and recently ascertained data set. The associations between vision impairment, age, sex, socioeconomic status, and ethnicity are reported. Methods This research was conducted using the UK Biobank Resource, with subsets of UK Biobank data analysed with respect to self-report of eye problems and glasses use. Better-eye visual acuity with habitually worn refractive correction was assessed with a logMAR chart (n = 116,682). Better-ear speech reception threshold was measured with an adaptive speech in noise test, the Digit Triplet Test (n = 164,770). Prevalence estimates were weighted with respect to UK 2001 Census data. Results Prevalence of mild visual impairment and low vision was estimated at 15.2% (95% CI 14.9–15.5%) and 0.9% (95% CI 0.8–1.0%), respectively. Use of glasses was 88.0% (95% CI 87.9–88.1%). The prevalence of dual sensory impairment was 3.1% (95% CI 3.0–3.2%) and there was a nine-fold increase in the prevalence of dual sensory problems between the youngest and oldest age groups. Older adults, those from low socioeconomic and ethnic minority backgrounds were most at risk for vision problems. Conclusions Mild vision impairment is common in middle aged UK adults, despite widespread use of spectacles. Possible barriers to optometric care for those from low socioeconomic and ethnic minority backgrounds may require attention. A higher than expected prevalence of dual impairment suggests that hearing and vision problems share common causes. Optometrists should consider screening for hearing problems, particularly among older adults. PMID:24888710

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

Childhood Vision: What the Research Tells Us

ERIC Educational Resources Information Center

Center for Health and Health Care in Schools, 2004

2004-01-01

While a nationwide study of vision problems in children has not been conducted in over 30 years, the most recent NHIS (National Health Interview Survey) study shows vision problems are common in children, with an estimated 13.5 million children ages 0-17 affected. As of 2002, 30 states plus the District of Columbia "required" vision…

Atoms of recognition in human and computer vision.

PubMed

Ullman, Shimon; Assif, Liav; Fetaya, Ethan; Harari, Daniel

2016-03-08

Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have shown remarkable progress and have begun to rival human performance in some challenging tasks. These models are trained on image examples and learn to extract features and representations and to use them for categorization. It remains unclear, however, whether the representations and learning processes discovered by current models are similar to those used by the human visual system. Here we show, by introducing and using minimal recognizable images, that the human visual system uses features and processes that are not used by current models and that are critical for recognition. We found by psychophysical studies that at the level of minimal recognizable images a minute change in the image can have a drastic effect on recognition, thus identifying features that are critical for the task. Simulations then showed that current models cannot explain this sensitivity to precise feature configurations and, more generally, do not learn to recognize minimal images at a human level. The role of the features shown here is revealed uniquely at the minimal level, where the contribution of each feature is essential. A full understanding of the learning and use of such features will extend our understanding of visual recognition and its cortical mechanisms and will enhance the capacity of computational models to learn from visual experience and to deal with recognition and detailed image interpretation.

Color vision test

MedlinePlus

... present from birth) color vision problems: Achromatopsia -- complete color blindness , seeing only shades of gray Deuteranopia -- difficulty telling ... Vision test - color; Ishihara color vision test Images Color blindness tests References Bowling B. Hereditary fundus dystrophies. In: ...

Learning to perceive differences in solid shape through vision and touch.

PubMed

Norman, J Farley; Clayton, Anna Marie; Norman, Hideko F; Crabtree, Charles E

2008-01-01

A single experiment was designed to investigate perceptual learning and the discrimination of 3-D object shape. Ninety-six observers were presented with naturally shaped solid objects either visually, haptically, or across the modalities of vision and touch. The observers' task was to judge whether the two sequentially presented objects on any given trial possessed the same or different 3-D shapes. The results of the experiment revealed that significant perceptual learning occurred in all modality conditions, both unimodal and cross-modal. The amount of the observers' perceptual learning, as indexed by increases in hit rate and d', was similar for all of the modality conditions. The observers' hit rates were highest for the unimodal conditions and lowest in the cross-modal conditions. Lengthening the inter-stimulus interval from 3 to 15 s led to increases in hit rates and decreases in response bias. The results also revealed the existence of an asymmetry between two otherwise equivalent cross-modal conditions: in particular, the observers' perceptual sensitivity was higher for the vision-haptic condition and lower for the haptic-vision condition. In general, the results indicate that effective cross-modal shape comparisons can be made between the modalities of vision and active touch, but that complete information transfer does not occur.

Stepping on Obstacles with a Sensory Substitution Device on the Lower Leg: Practice without Vision Is More Beneficial than Practice with Vision

PubMed Central

Lobo, Lorena; Travieso, David; Barrientos, Antonio; Jacobs, David M.

2014-01-01

Practice is essential for an adapted use of sensory substitution devices. Understanding the learning process is therefore a fundamental issue in this field of research. This study presents a novel sensory substitution device worn on the lower leg and uses the device to study learning. The device includes 32 vibrotactile actuators that each vibrate as a function of the distance to the nearest surface in a particular direction. Participants wearing the device were asked to approach an object and to step on the object. Two 144-trial practice conditions were compared in a pretest-practice-posttest design. Participants in the first condition practiced with vibrotactile stimulation while blindfolded. Participants in the second condition practiced with vibrotactile stimulation along with normal vision. Performance was relatively successful, both types of practice led to improvements in performance, and practice without vision led to a larger reduction in the number of errors than practice with vision. These results indicate that distance-based sensory substitution is promising in addition to the more traditional light-intensity-based sensory substitution and that providing appropriate sensorimotor couplings is more important than applying the stimulation to highly sensitive body parts. The observed advantage of practice without vision over practice with vision is interpreted in terms of the guidance hypothesis of feedback and learning. PMID:24901843

Creating Thinking Schools through "Knowledge and Inquiry": The Curriculum Challenges for Singapore

ERIC Educational Resources Information Center

Tan, Charlene

2006-01-01

The importance of thinking skills in Singapore was seen in the launch of the "Thinking Schools, Learning Nation" (TSLN) vision in 1997. This vision aims to develop creative thinking skills, a lifelong passion for learning and nationalistic commitment in the young. In elucidating the concept of "thinking schools" the former…

Taking Stock: Implications of a New Vision of Science Learning for State Science Assessment

ERIC Educational Resources Information Center

Wertheim, Jill

2016-01-01

This article presents the author's response to the article "Taking Stock: Existing Resources for Assessing a New Vision of Science Learning" by Alonzo and Ke (this issue), which identifies numerous challenges that the Next Generation Science Standards (NGSS) pose for large-scale assessment. Jill Werthem comments that among those…

The Power of 2: Partnership Paves the Way for Teacher Leadership Academy

ERIC Educational Resources Information Center

Harmon, Jeanne; Herren, Kip; Luke, Rod; Emry, Terese

2012-01-01

A clear vision is the essential foundation for making decisions about precious resources for implementing professional learning: (1) people; (2) time; and (3) money. The Auburn School District in Washington state learned firsthand how a clear vision drives resource allocation to support strategic actions and how effective partnerships can be the…

Post-School Visions and Expectations of Latino Students with Learning Disabilities, Their Parents, and Teachers

ERIC Educational Resources Information Center

Keel, Joanna Mossmond; Cushing, Lisa Sharon; Awsumb, Jessica M.

2018-01-01

This study explored perspectives about the desired components of adult life for 12th-grade Latino students with learning disabilities, their parents, and special education teachers. Focus groups and individual interviews were used to understand the similarities and differences in post-school visions and expectations among participants. Five…

Bi Sparsity Pursuit: A Paradigm for Robust Subspace Recovery

DTIC Science & Technology

2016-09-27

16. SECURITY CLASSIFICATION OF: The success of sparse models in computer vision and machine learning is due to the fact that, high dimensional data...Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Signal recovery, Sparse learning , Subspace modeling REPORT DOCUMENTATION PAGE 11...vision and machine learning is due to the fact that, high dimensional data is distributed in a union of low dimensional subspaces in many real-world

Color Vision Deficiency and Color Blindness: An Introduction to the Problem.

ERIC Educational Resources Information Center

Olsen, Mary Margaret; Harris, Kenneth R.

The paper examines issues concerned with the education and employment of individuals, primarily males, with color vision deficiency. After a brief introduction, the first chapter looks at adult problems such as employment areas in which the disability presents problems. The next chapter considers problems of children, noting the heavy use of color…

Hypothalamic dysfunction

MedlinePlus

... symptoms may include headache or loss of vision. Hypothyroidism symptoms may include feeling cold all the time, ... Vision disorders Problems controlling salt and water balance HYPOTHYROIDISM Heart problems High cholesterol ADRENAL INSUFFICIENCY Inability to ...

Vision Screening of School Children by Teachers as a Community Based Strategy to Address the Challenges of Childhood Blindness.

PubMed

Kaur, Gurvinder; Koshy, Jacob; Thomas, Satish; Kapoor, Harpreet; Zachariah, Jiju George; Bedi, Sahiba

2016-04-01

Early detection and treatment of vision problems in children is imperative to meet the challenges of childhood blindness. Considering the problems of inequitable distribution of trained manpower and limited access of quality eye care services to majority of our population, innovative community based strategies like 'Teachers training in vision screening' need to be developed for effective utilization of the available human resources. To evaluate the effectiveness of introducing teachers as the first level vision screeners. Teacher training programs were conducted for school teachers to educate them about childhood ocular disorders and the importance of their early detection. Teachers from government and semi-government schools located in Ludhiana were given training in vision screening. These teachers then conducted vision screening of children in their schools. Subsequently an ophthalmology team visited these schools for re-evaluation of children identified with low vision. Refraction was performed for all children identified with refractive errors and spectacles were prescribed. Children requiring further evaluation were referred to the base hospital. The project was done in two phases. True positives, false positives, true negatives and false negatives were calculated for evaluation. In phase 1, teachers from 166 schools underwent training in vision screening. The teachers screened 30,205 children and reported eye problems in 4523 (14.97%) children. Subsequently, the ophthalmology team examined 4150 children and confirmed eye problems in 2137 children. Thus, the teachers were able to correctly identify eye problems (true positives) in 47.25% children. Also, only 13.69% children had to be examined by the ophthalmology team, thus reducing their work load. Similarly, in phase 2, 46.22% children were correctly identified to have eye problems (true positives) by the teachers. By random sampling, 95.65% children were correctly identified as normal (true negatives) by the teachers. Considering the high true negative rates and reasonably good true positive rates and the wider coverage provided by the program, vision screening in schools by teachers is an effective method of identifying children with low vision. This strategy is also valuable in reducing the workload of the eye care staff.

Use of 3D vision for fine robot motion

NASA Technical Reports Server (NTRS)

Lokshin, Anatole; Litwin, Todd

1989-01-01

An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.

Mental stress as consequence and cause of vision loss: the dawn of psychosomatic ophthalmology for preventive and personalized medicine.

PubMed

Sabel, Bernhard A; Wang, Jiaqi; Cárdenas-Morales, Lizbeth; Faiq, Muneeb; Heim, Christine

2018-06-01

The loss of vision after damage to the retina, optic nerve, or brain has often grave consequences in everyday life such as problems with recognizing faces, reading, or mobility. Because vision loss is considered to be irreversible and often progressive, patients experience continuous mental stress due to worries, anxiety, or fear with secondary consequences such as depression and social isolation. While prolonged mental stress is clearly a consequence of vision loss, it may also aggravate the situation. In fact, continuous stress and elevated cortisol levels negatively impact the eye and brain due to autonomous nervous system (sympathetic) imbalance and vascular dysregulation; hence stress may also be one of the major causes of visual system diseases such as glaucoma and optic neuropathy. Although stress is a known risk factor, its causal role in the development or progression of certain visual system disorders is not widely appreciated. This review of the literature discusses the relationship of stress and ophthalmological diseases. We conclude that stress is both consequence and cause of vision loss. This creates a vicious cycle of a downward spiral, in which initial vision loss creates stress which further accelerates vision loss, creating even more stress and so forth. This new psychosomatic perspective has several implications for clinical practice. Firstly, stress reduction and relaxation techniques (e.g., meditation, autogenic training, stress management training, and psychotherapy to learn to cope) should be recommended not only as complementary to traditional treatments of vision loss but possibly as preventive means to reduce progression of vision loss. Secondly, doctors should try their best to inculcate positivity and optimism in their patients while giving them the information the patients are entitled to, especially regarding the important value of stress reduction. In this way, the vicious cycle could be interrupted. More clinical studies are now needed to confirm the causal role of stress in different low vision diseases to evaluate the efficacy of different anti-stress therapies for preventing progression and improving vision recovery and restoration in randomized trials as a foundation of psychosomatic ophthalmology.

Revolutionary Learning, Biodiversity, and Transformative Action. Essay Review of "Learning in Social Action: A Contribution To Understanding Informal Education" by Griff Foley; "Transformative Learning: Educational Vision for the Twenty-First Century" by Edmund O'Sullivan; and "Che Guevara, Paulo Freire and the Pedagogy of Revolution" by Peter McLaren.

ERIC Educational Resources Information Center

Mayo, Peter

2001-01-01

Three books, published 1999-2000, map out a vision of education as a vehicle for human emancipation and global transformation. Their approaches to presenting the "big picture" differ, focusing on case studies of learning through local social action; the impact of Che Guevara and Paulo Freire on liberation discourse worldwide; and comprehensive…

Acting to gain information

NASA Technical Reports Server (NTRS)

Rosenchein, Stanley J.; Burns, J. Brian; Chapman, David; Kaelbling, Leslie P.; Kahn, Philip; Nishihara, H. Keith; Turk, Matthew

1993-01-01

This report is concerned with agents that act to gain information. In previous work, we developed agent models combining qualitative modeling with real-time control. That work, however, focused primarily on actions that affect physical states of the environment. The current study extends that work by explicitly considering problems of active information-gathering and by exploring specialized aspects of information-gathering in computational perception, learning, and language. In our theoretical investigations, we analyzed agents into their perceptual and action components and identified these with elements of a state-machine model of control. The mathematical properties of each was developed in isolation and interactions were then studied. We considered the complexity dimension and the uncertainty dimension and related these to intelligent-agent design issues. We also explored active information gathering in visual processing. Working within the active vision paradigm, we developed a concept of 'minimal meaningful measurements' suitable for demand-driven vision. We then developed and tested an architecture for ongoing recognition and interpretation of visual information. In the area of information gathering through learning, we explored techniques for coping with combinatorial complexity. We also explored information gathering through explicit linguistic action by considering the nature of conversational rules, coordination, and situated communication behavior.

A comparison of algorithms for inference and learning in probabilistic graphical models.

PubMed

Frey, Brendan J; Jojic, Nebojsa

2005-09-01

Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.

ACE [Adult and Community Education] into the 21st Century: A Vision.

ERIC Educational Resources Information Center

Adult, Community, and Further Education Board, Melbourne (Australia).

This document outlines a vision for adult and community education (ACE) in Victoria for the next 3 years and provides a broad map of how to reach that vision. A description of the context is followed by the ACE vision statement: ACE delivers accessible, quality, and timely learning in autonomous, community settings as a valued and essential…

Strategic thinking for radiology.

PubMed

Schilling, R B

1997-08-01

We have now analyzed the use and benefits of four Strategic Thinking Tools for Radiology: the Vision Statement, the High Five, the Two-by-Two, and Real-Win-Worth. Additional tools will be provided during the tutorial. The tools provided above should be considered as examples. They all contain the 10 benefits outlined earlier to varying degrees. It is extremely important that the tools be used in a manner consistent with the Vision Statement of the organization. The specific situation, the effectiveness of the team, and the experience developed with the tools over time will determine the true benefits of the process. It has also been shown that with active use of the types of tools provided above, teams have learned to modify the tools for increased effectiveness and have created additional tools for specific purposes. Once individuals in the organization become committed to improving communication and to using tools/frameworks for solving problems as a team, effectiveness becomes boundless.

Encouragement for Faculty to Implement "Vision and Change"

ERIC Educational Resources Information Center

Harvey, Caylyn; Eshleman, Kristen; Koo, Kyosung; Smith, Kevin G.; Paradise, Christopher J.; Campbell, A. Malcolm

2016-01-01

The seminal report "Vision and Change" outlined improvements necessary for undergraduate biology courses to accomplish widely recognized learning objectives. Over the past 8 years, we have developed a two-semester introductory biology course that incorporates the core concepts and competencies recommended in "Vision and…

Lifelong Learning and the Pursuit of a Vision for Sustainable Development in Botswana

ERIC Educational Resources Information Center

Maruatona, Tonic

2011-01-01

This paper analyses Botswana's commitment to lifelong learning policy and discusses how it can help the state achieve its vision for sustainable development. First, it argues that while Botswana is renowned for its economic success, it still fails to address positively such traditional challenges as poverty, unemployment and income inequality,…

Visions of Mobile Learning

ERIC Educational Resources Information Center

T.H.E. Journal, 2011

2011-01-01

It is almost a foregone conclusion that the mobile device will become an indispensable tool for learning in the future. That's why "T.H.E. Journal" asked a number of educators to let their imaginations go wild and conjure up visions of the future of the device in the classroom. This paper presents the views of educators who conjure up the mobile…

Inspiration and Intellect: Significant Learning in Musical Forms and Analysis

ERIC Educational Resources Information Center

Kelley, Bruce C.

2009-01-01

In his book "Creating Significant Learning Experiences" (2003), Dee Fink challenges professors to create a deep vision for the courses they teach. Educators often have a vision for what their courses could be, but often lack a model for instituting change. Fink's book provides that model. In this article, the author describes how this model helped…

A "Vision and Change" Reform of Introductory Biology Shifts Faculty Perceptions and Use of Active Learning

ERIC Educational Resources Information Center

Auerbach, Anna Jo; Schussler, Elisabeth

2017-01-01

Increasing faculty use of active-learning (AL) pedagogies in college classrooms is a persistent challenge in biology education. A large research-intensive university implemented changes to its biology majors' two-course introductory sequence as outlined by the "Vision and Change in Undergraduate Biology Education" final report. One goal…

Increasing Accessibility to Advanced Education for Under-Represented Albertans. A Discussion Document

ERIC Educational Resources Information Center

Online Submission, 2005

2005-01-01

In 2005, Alberta's Minister of Advanced Education initiated a comprehensive exercise to establish a new vision for the province's advanced education system. Through the A Learning Alberta initiative, a revised vision and new policy outcomes for Alberta's advanced education system will be articulated. A key question of A Learning Alberta is how to…

What Is Mathematics? An Exploration of Teachers' Philosophies of Mathematics during a Time of Curriculum Reform

ERIC Educational Resources Information Center

White-Fredette, Kimberly

2009-01-01

Current reform in mathematics teaching and learning is rooted in a changing vision of school mathematics, one that includes constructivist learning, student-centered pedagogy, and the use of worthwhile tasks (National Council of Teachers of Mathematics, 1989, 1991, 2000). This changing vision not only challenges teachers' beliefs about mathematics…

Vision and Vestibular System Dysfunction Predicts Prolonged Concussion Recovery in Children.

PubMed

Master, Christina L; Master, Stephen R; Wiebe, Douglas J; Storey, Eileen P; Lockyer, Julia E; Podolak, Olivia E; Grady, Matthew F

2018-03-01

Up to one-third of children with concussion have prolonged symptoms lasting beyond 4 weeks. Vision and vestibular dysfunction is common after concussion. It is unknown whether such dysfunction predicts prolonged recovery. We sought to determine which vision or vestibular problems predict prolonged recovery in children. A retrospective cohort of pediatric patients with concussion. A subspecialty pediatric concussion program. Four hundred thirty-two patient records were abstracted. Presence of vision or vestibular dysfunction upon presentation to the subspecialty concussion program. The main outcome of interest was time to clinical recovery, defined by discharge from clinical follow-up, including resolution of acute symptoms, resumption of normal physical and cognitive activity, and normalization of physical examination findings to functional levels. Study subjects were 5 to 18 years (median = 14). A total of 378 of 432 subjects (88%) presented with vision or vestibular problems. A history of motion sickness was associated with vestibular dysfunction. Younger age, public insurance, and presence of headache were associated with later presentation for subspecialty concussion care. Vision and vestibular problems were associated within distinct clusters. Provocable symptoms with vestibulo-ocular reflex (VOR) and smooth pursuits and abnormal balance and accommodative amplitude (AA) predicted prolonged recovery time. Vision and vestibular problems predict prolonged concussion recovery in children. A history of motion sickness may be an important premorbid factor. Public insurance status may represent problems with disparities in access to concussion care. Vision assessments in concussion must include smooth pursuits, saccades, near point of convergence (NPC), and accommodative amplitude (AA). A comprehensive, multidomain assessment is essential to predict prolonged recovery time and enable active intervention with specific school accommodations and targeted rehabilitation.

Encouragement for Faculty to Implement Vision and Change.

PubMed

Harvey, Caylyn; Eshleman, Kristen; Koo, Kyosung; Smith, Kevin G; Paradise, Christopher J; Campbell, A Malcolm

2016-01-01

The seminal report Vision and Change outlined improvements necessary for undergraduate biology courses to accomplish widely recognized learning objectives. Over the past 8 years, we have developed a two-semester introductory biology course that incorporates the core concepts and competencies recommended in Vision and Change Using published research on how students learn, we focused our efforts on three main areas of change: pedagogy, course content, and technology. We introduced active-learning strategies to improve our classroom environments, wrote an e-textbook that provides students with the tools they need to construct their own knowledge, and employed an online learning hub to assist students who needed extra support. The redesigned courses have been well received by students, and we have seen good student learning outcomes. The purpose of this essay is to demonstrate to faculty that Vision and Change's recommendations are feasible and students welcome the improvements. © 2016 C. Harvey et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Genetics Home Reference: renal coloboma syndrome

MedlinePlus

... the back of the eye ( the retina ). The vision problems caused by these abnormalities can vary depending ... visual problems, while others may have severely impaired vision. Less common features of renal coloboma syndrome include ...

IEEE 1982. Proceedings of the international conference on cybernetics and society

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

Not Available

1982-01-01

The following topics were dealt with: knowledge-based systems; risk analysis; man-machine interactions; human information processing; metaphor, analogy and problem-solving; manual control modelling; transportation systems; simulation; adaptive and learning systems; biocybernetics; cybernetics; mathematical programming; robotics; decision support systems; analysis, design and validation of models; computer vision; systems science; energy systems; environmental modelling and policy; pattern recognition; nuclear warfare; technological forecasting; artificial intelligence; the Turin shroud; optimisation; workloads. Abstracts of individual papers can be found under the relevant classification codes in this or future issues.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.

PubMed

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝ d , and the dictionary is learned from the training data using the vector space structure of ℝ d and its Euclidean L 2 -metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning

PubMed Central

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝd, and the dictionary is learned from the training data using the vector space structure of ℝd and its Euclidean L2-metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis. PMID:24129583

Do problem-solving interventions improve psychosocial outcomes in vision impaired adults: a systematic review and meta-analysis.

PubMed

Holloway, Edith E; Xie, Jing; Sturrock, Bonnie A; Lamoureux, Ecosse L; Rees, Gwyneth

2015-05-01

To evaluate the effectiveness of problem-solving interventions on psychosocial outcomes in vision impaired adults. A systematic search of randomised controlled trials (RCTs), published between 1990 and 2013, that investigated the impact of problem-solving interventions on depressive symptoms, emotional distress, quality of life (QoL) and functioning was conducted. Two reviewers independently selected and appraised study quality. Data permitting, intervention effects were statistically pooled and meta-analyses were performed, otherwise summarised descriptively. Eleven studies (reporting on eight trials) met inclusion criteria. Pooled analysis showed problem-solving interventions improved vision-related functioning (standardised mean change [SMC]: 0.15; 95% CI: 0.04-0.27) and emotional distress (SMC: -0.36; 95% CI: -0.54 to -0.19). There was no evidence to support improvements in depressive symptoms (SMC: -0.27, 95% CI: -0.66 to 0.12) and insufficient evidence to determine the effectiveness of problem-solving interventions on QoL. The small number of well-designed studies and narrow inclusion criteria limit the conclusions drawn from this review. However, problem-solving skills may be important for nurturing daily functioning and reducing emotional distress for adults with vision impairment. Given the empirical support for the importance of effective problem-solving skills in managing chronic illness, more well-designed RCTs are needed with diverse vision impaired samples. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Economics of Adult Learning: The Role of Government. A Series of 29 Booklets Documenting Workshops Held at the Fifth International Conference on Adult Education (Hamburg, Germany, July 14-18, 1997).

ERIC Educational Resources Information Center

United Nations Educational, Scientific, and Cultural Organization, Hamburg (Germany). Inst. for Education.

The booklet reports on a new vision of the economics of adult learning. The vision considers adult learning to be not an expense but an investment that can be analyzed and managed as such. According to the booklet, governments in many countries, therefore, are adopting a steering role and are giving more direct responsibilities to institutions at…

Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion

PubMed Central

Hamsici, Onur C.; Gotardo, Paulo F.U.; Martinez, Aleix M.

2013-01-01

Non-rigid structure from motion (NRSFM) is a classical underconstrained problem in computer vision. A common approach to make NRSFM more tractable is to constrain 3D shape deformation to be smooth over time. This constraint has been used to compress the deformation model and reduce the number of unknowns that are estimated. However, temporal smoothness cannot be enforced when the data lacks temporal ordering and its benefits are less evident when objects undergo abrupt deformations. This paper proposes a new NRSFM method that addresses these problems by considering deformations as spatial variations in shape space and then enforcing spatial, rather than temporal, smoothness. This is done by modeling each 3D shape coefficient as a function of its input 2D shape. This mapping is learned in the feature space of a rotation invariant kernel, where spatial smoothness is intrinsically defined by the mapping function. As a result, our model represents shape variations compactly using custom-built coefficient bases learned from the input data, rather than a pre-specified set such as the Discrete Cosine Transform. The resulting kernel-based mapping is a by-product of the NRSFM solution and leads to another fundamental advantage of our approach: for a newly observed 2D shape, its 3D shape is recovered by simply evaluating the learned function. PMID:23946937

Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion.

PubMed

Hamsici, Onur C; Gotardo, Paulo F U; Martinez, Aleix M

2012-01-01

Non-rigid structure from motion (NRSFM) is a classical underconstrained problem in computer vision. A common approach to make NRSFM more tractable is to constrain 3D shape deformation to be smooth over time. This constraint has been used to compress the deformation model and reduce the number of unknowns that are estimated. However, temporal smoothness cannot be enforced when the data lacks temporal ordering and its benefits are less evident when objects undergo abrupt deformations. This paper proposes a new NRSFM method that addresses these problems by considering deformations as spatial variations in shape space and then enforcing spatial, rather than temporal, smoothness. This is done by modeling each 3D shape coefficient as a function of its input 2D shape. This mapping is learned in the feature space of a rotation invariant kernel, where spatial smoothness is intrinsically defined by the mapping function. As a result, our model represents shape variations compactly using custom-built coefficient bases learned from the input data, rather than a pre-specified set such as the Discrete Cosine Transform. The resulting kernel-based mapping is a by-product of the NRSFM solution and leads to another fundamental advantage of our approach: for a newly observed 2D shape, its 3D shape is recovered by simply evaluating the learned function.

Teacher Justice and Parent Support as Predictors of Learning Motivation and Visions of a Just World

ERIC Educational Resources Information Center

Berti, Chiara; Mameli, Consuelo; Speltini, Giuseppina; Molinari, Luisa

2016-01-01

In this study we explore teacher justice and parent support in learning motivation and visions of a just world. The study sample was 509 Italian secondary school students, 163 males and 346 females. Regression analyses investigated the impact of teacher justice, parental involvement and factors of school choice (one's interests and parental…

Education for All: An Expanded Vision. World Conference on Education for All (Jomtien, Thailand, March 5-9, 1990). Monograph II. Roundtable Themes II.

ERIC Educational Resources Information Center

Fordham, Paul

This seven-chapter monograph elaborates on five components of an expanded vision of basic education. It presents material that deals with aspects of these components: universalizing access and promoting equity, focusing on learning, broadening the means and scope of basic education, enhancing the environment for learning, and strengthening…

The Role of Prototype Learning in Hierarchical Models of Vision

ERIC Educational Resources Information Center

Thomure, Michael David

2014-01-01

I conduct a study of learning in HMAX-like models, which are hierarchical models of visual processing in biological vision systems. Such models compute a new representation for an image based on the similarity of image sub-parts to a number of specific patterns, called prototypes. Despite being a central piece of the overall model, the issue of…

Vision-based Detection of Acoustic Timed Events: a Case Study on Clarinet Note Onsets

NASA Astrophysics Data System (ADS)

Bazzica, A.; van Gemert, J. C.; Liem, C. C. S.; Hanjalic, A.

2017-05-01

Acoustic events often have a visual counterpart. Knowledge of visual information can aid the understanding of complex auditory scenes, even when only a stereo mixdown is available in the audio domain, \\eg identifying which musicians are playing in large musical ensembles. In this paper, we consider a vision-based approach to note onset detection. As a case study we focus on challenging, real-world clarinetist videos and carry out preliminary experiments on a 3D convolutional neural network based on multiple streams and purposely avoiding temporal pooling. We release an audiovisual dataset with 4.5 hours of clarinetist videos together with cleaned annotations which include about 36,000 onsets and the coordinates for a number of salient points and regions of interest. By performing several training trials on our dataset, we learned that the problem is challenging. We found that the CNN model is highly sensitive to the optimization algorithm and hyper-parameters, and that treating the problem as binary classification may prevent the joint optimization of precision and recall. To encourage further research, we publicly share our dataset, annotations and all models and detail which issues we came across during our preliminary experiments.

Egocentric daily activity recognition via multitask clustering.

PubMed

Yan, Yan; Ricci, Elisa; Liu, Gaowen; Sebe, Nicu

2015-10-01

Recognizing human activities from videos is a fundamental research problem in computer vision. Recently, there has been a growing interest in analyzing human behavior from data collected with wearable cameras. First-person cameras continuously record several hours of their wearers' life. To cope with this vast amount of unlabeled and heterogeneous data, novel algorithmic solutions are required. In this paper, we propose a multitask clustering framework for activity of daily living analysis from visual data gathered from wearable cameras. Our intuition is that, even if the data are not annotated, it is possible to exploit the fact that the tasks of recognizing everyday activities of multiple individuals are related, since typically people perform the same actions in similar environments, e.g., people working in an office often read and write documents). In our framework, rather than clustering data from different users separately, we propose to look for clustering partitions which are coherent among related tasks. In particular, two novel multitask clustering algorithms, derived from a common optimization problem, are introduced. Our experimental evaluation, conducted both on synthetic data and on publicly available first-person vision data sets, shows that the proposed approach outperforms several single-task and multitask learning methods.

Neural system applied on an invariant industrial character recognition

NASA Astrophysics Data System (ADS)

Lecoeuche, Stephane; Deguillemont, Denis; Dubus, Jean-Paul

1997-04-01

Besides the variety of fonts, character recognition systems for the industrial world are confronted with specific problems like: the variety of support (metal, wood, paper, ceramics . . .) as well as the variety of marking (printing, engraving, . . .) and conditions of lighting. We present a system that is able to solve a part of this problem. It implements a collaboration between two neural networks. The first network specialized in vision allows the system to extract the character from an image. Besides this capability, we have equipped our system with characteristics allowing it to obtain an invariant model from the presented character. Thus, whatever the position, the size and the orientation of the character during the capture are, the model presented to the input of the second network will be identical. The second network, thanks to a learning phase, permits us to obtain a character recognition system independent of the type of fonts used. Furthermore, its capabilities of generalization permit us to recognize degraded and/or distorted characters. A feedback loop between the two networks permits the first one to modify the quality of vision.The cooperation between these two networks allows us to recognize characters whatever the support and the marking.

A convolutional neural network neutrino event classifier

DOE PAGES

Aurisano, A.; Radovic, A.; Rocco, D.; ...

2016-09-01

Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

Relevance feedback-based building recognition

NASA Astrophysics Data System (ADS)

Li, Jing; Allinson, Nigel M.

2010-07-01

Building recognition is a nontrivial task in computer vision research which can be utilized in robot localization, mobile navigation, etc. However, existing building recognition systems usually encounter the following two problems: 1) extracted low level features cannot reveal the true semantic concepts; and 2) they usually involve high dimensional data which require heavy computational costs and memory. Relevance feedback (RF), widely applied in multimedia information retrieval, is able to bridge the gap between the low level visual features and high level concepts; while dimensionality reduction methods can mitigate the high-dimensional problem. In this paper, we propose a building recognition scheme which integrates the RF and subspace learning algorithms. Experimental results undertaken on our own building database show that the newly proposed scheme appreciably enhances the recognition accuracy.

A convolutional neural network neutrino event classifier

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

Aurisano, A.; Radovic, A.; Rocco, D.

Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

Systematic construction and control of stereo nerve vision network in intelligent manufacturing

NASA Astrophysics Data System (ADS)

Liu, Hua; Wang, Helong; Guo, Chunjie; Ding, Quanxin; Zhou, Liwei

2017-10-01

A system method of constructing stereo vision by using neural network is proposed, and the operation and control mechanism in actual operation are proposed. This method makes effective use of the neural network in learning and memory function, by after training with samples. Moreover, the neural network can learn the nonlinear relationship in the stereoscopic vision system and the internal and external orientation elements. These considerations are Worthy of attention, which includes limited constraints, the scientific of critical group, the operating speed and the operability in technical aspects. The results support our theoretical forecast.

Cognitive Tutoring based on Intelligent Decision Support in the PENTHA Instructional Design Model

NASA Astrophysics Data System (ADS)

dall'Acqua, Luisa

2010-06-01

The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.

Building a Global Learning Organization: Lessons from the World's Top Corporations.

ERIC Educational Resources Information Center

Marquardt, Michael J.

1995-01-01

Research on 50 organizations elicited 19 attributes of learning organizations: individual learning, group learning, streamlined structure, corporate learning culture, empowerment, environmental scanning, knowledge creation/transfer, learning technology, quality, learning strategy, supportive atmosphere, teamwork/networking, vision, acculturation,…

Conjunctive patches subspace learning with side information for collaborative image retrieval.

PubMed

Zhang, Lining; Wang, Lipo; Lin, Weisi

2012-08-01

Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.

Towards Open-World Person Re-Identification by One-Shot Group-Based Verification.

PubMed

Zheng, Wei-Shi; Gong, Shaogang; Xiang, Tao

2016-03-01

Solving the problem of matching people across non-overlapping multi-camera views, known as person re-identification (re-id), has received increasing interests in computer vision. In a real-world application scenario, a watch-list (gallery set) of a handful of known target people are provided with very few (in many cases only a single) image(s) (shots) per target. Existing re-id methods are largely unsuitable to address this open-world re-id challenge because they are designed for (1) a closed-world scenario where the gallery and probe sets are assumed to contain exactly the same people, (2) person-wise identification whereby the model attempts to verify exhaustively against each individual in the gallery set, and (3) learning a matching model using multi-shots. In this paper, a novel transfer local relative distance comparison (t-LRDC) model is formulated to address the open-world person re-identification problem by one-shot group-based verification. The model is designed to mine and transfer useful information from a labelled open-world non-target dataset. Extensive experiments demonstrate that the proposed approach outperforms both non-transfer learning and existing transfer learning based re-id methods.

Effects of Learning on Performance When Computerized Dynamic Posturography Assessments Are Repeated

NASA Technical Reports Server (NTRS)

Taylor, Laura C.; Paloski, William H.; Wood, Scott J.

2008-01-01

Background: Computerized dynamic posturography is widely used to measure balance control performance. Clinically, performance is assessed by comparing individual data against standards obtained from a normative population. When performing repeated assessments to track performance changes, one must be concerned with the influence of learning effects. Subjects do not have the opportunity to practice before the first session, and often a second session is not performed prior to an experiment. Thus, the objective of this activity was to examine learning effects on balance control performance. We hypothesize that subjects will perform better on the second session when compared to the first, and that the difference will be greater for more difficult conditions. Methods: Data were collected from 204 subjects using the NeuroCom Equitest system during quiet stance with arms crossed at the chest on up to two sessions. All subjects performed standard sensory organization tests (SOTs) including 1) normal vision, fixed support; 2) absent vision, fixed support; 3) sway-referenced vision, fixed support; 4) normal vision, swayreferenced support; 5) absent vision, sway-referenced support; and 6) sway-referenced vision, sway-referenced support. 120 of these subjects performed modified sensory organization tests (mSOTs 2 and 5) which included static (20 back) and dynamic (20, 0.33Hz) head tilts. Median equilibrium scores (mEQ) were calculated from peak-to-peak anterior-posterior sway across trials. Data collected on the first session were then compared with the second to examine learning effect. Results: There were no differences in mEQ scores between the first and second sessions for SOTs 1, 2, and 4, while mEQ scores were higher for the second session when compared to the first for SOTs 3, 5, and 6 and for all mSOTs. Discussion: An additional familiarization session or practice trials prior to the first session may be necessary for more challenging SOT and mSOT conditions to minimize learning effect.

A Fast Optimization Method for General Binary Code Learning.

PubMed

Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng

2016-09-22

Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.

The effects of deep network topology on mortality prediction.

PubMed

Hao Du; Ghassemi, Mohammad M; Mengling Feng

2016-08-01

Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attention only in recent years, and it's ultimate place at the bedside remains a topic of skeptical discussion. While there is a growing academic interest in the application of Machine Learning (ML) techniques to clinical problems, many in the clinical community see little incentive to upgrade from simpler methods, such as logistic regression, to deep learning. Logistic regression, after all, provides odds ratios, p-values and confidence intervals that allow for ease of interpretation, while deep nets are often seen as `black-boxes' which are difficult to understand and, as of yet, have not demonstrated performance levels far exceeding their simpler counterparts. If deep learning is to ever take a place at the bedside, it will require studies which (1) showcase the performance of deep-learning methods relative to other approaches and (2) interpret the relationships between network structure, model performance, features and outcomes. We have chosen these two requirements as the goal of this study. In our investigation, we utilized a publicly available EMR dataset of over 32,000 intensive care unit patients and trained a Deep Belief Network (DBN) to predict patient mortality at discharge. Utilizing an evolutionary algorithm, we demonstrate automated topology selection for DBNs. We demonstrate that with the correct topology selection, DBNs can achieve better prediction performance compared to several bench-marking methods.

Two-stage perceptual learning to break visual crowding.

PubMed

Zhu, Ziyun; Fan, Zhenzhi; Fang, Fang

2016-01-01

When a target is presented with nearby flankers in the peripheral visual field, it becomes harder to identify, which is referred to as crowding. Crowding sets a fundamental limit of object recognition in peripheral vision, preventing us from fully appreciating cluttered visual scenes. We trained adult human subjects on a crowded orientation discrimination task and investigated whether crowding could be completely eliminated by training. We discovered a two-stage learning process with this training task. In the early stage, when the target and flankers were separated beyond a certain distance, subjects acquired a relatively general ability to break crowding, as evidenced by the fact that the breaking of crowding could transfer to another crowded orientation, even a crowded motion stimulus, although the transfer to the opposite visual hemi-field was weak. In the late stage, like many classical perceptual learning effects, subjects' performance gradually improved and showed specificity to the trained orientation. We also found that, when the target and flankers were spaced too finely, training could only reduce, rather than completely eliminate, the crowding effect. This two-stage learning process illustrates a learning strategy for our brain to deal with the notoriously difficult problem of identifying peripheral objects in clutter. The brain first learned to solve the "easy and general" part of the problem (i.e., improving the processing resolution and segmenting the target and flankers) and then tackle the "difficult and specific" part (i.e., refining the representation of the target).

Optical needs of students with low vision in integrated schools of Nepal.

PubMed

Gnyawali, Subodh; Shrestha, Jyoti Baba; Bhattarai, Dipesh; Upadhyay, Madan

2012-12-01

To identify the optical needs of students with low vision studying in the integrated schools for the blind in Nepal. A total of 779 blind and vision-impaired students studying in 67 integrated schools for the blind across Nepal were examined using the World Health Organization/Prevention of Blindness Eye Examination Record for Children with Blindness and Low Vision. Glasses and low-vision devices were provided to the students with low vision who showed improvement in visual acuity up to a level that was considered sufficient for classroom learning. Follow-up on the use and maintenance of device provided was done after a year. Almost 78% of students studying in the integrated schools for the blind were not actually blind; they had low vision. Five students were found to be wrongly enrolled. Avoidable causes of blindness were responsible for 41% of all blindness. Among 224 students who had visual acuity 1/60 or better, distance vision could be improved in 18.7% whereas near vision could be improved in 41.1% students. Optical intervention provided improved vision in 48.2% of students who were learning braille. Only 34.8% students were found to be using the devices regularly after assessment 1 year later; the most common causes for nonuse were damage or misplacement of the device. A high proportion of students with low vision in integrated schools could benefit from optical intervention. A system of comprehensive eye examination at the time of school enrollment would allow students with low vision to use their available vision to the fullest, encourage print reading over braille, ensure appropriate placement, and promote timely adoption and proper usage of optical device.

Global Trend in Education: Shifting from a Teaching-Focus to a Learning-Focus.

ERIC Educational Resources Information Center

Montgomery, Joel R.

Today a global shift in education is taking place, moving from a teaching focus to a learning focus. The new vision of education centers on the learner and how teachers can assist the learner in mastering needed competencies and processes required for success in the workplace and in life. This vision looks at the learner as a decision maker,…

Accelerated Schools as Learning Organizations: Cases from the University of New Orleans Accelerated School Network.

ERIC Educational Resources Information Center

Brunner, Ilse; And Others

Organizations are the product of the ideas and interactions of those who work in them. The challenge for learning in organizations is to have a shared purpose and vision of the organization, to develop new ideas arising out of the vision and purpose, to test the ideas in the organizational reality, and to communicate that knowledge to other…

"Looking Good" and "Good Looking" in School: Beauty Ideals, Appearance, and Enskilled Vision among Girls in a London Secondary School

ERIC Educational Resources Information Center

Winkler-Reid, Sarah

2017-01-01

This article explores the enskillment of vision through which girls in a London school learn to see bodies and selves in particular ways. Dominant body and beauty ideals inform these processes but cannot be reduced to them. Drawing from the anthropological literature on situated learning and the senses, I propose an anthropological approach to…

Post-Traumatic Stress Disorder and the Earnings of Military Reservists

DTIC Science & Technology

2013-01-01

such as back pain, fever , rash, and vision problems. After controlling 1 The fact that the PDHA PTSD screen differs from that used by Savoca and...problems Back pain –306**   (100) Chest pain –1,018**   (147) Chronic cough –341*   (136) Diarrhea 48   (107) Fever 538**   (149) Joint problems 108...problems associated with PTSD (for example, fevers and vision problems). However, conditions that tend to co-occur with PTSD, such as memory problems

[Learning together for working together: interprofessionalism in simulation training for collaborative skills development].

PubMed

Policard, Florence

2014-06-01

The use of simulation as an educational tool is becoming more widespread in healthcare. Such training gathers doctors and nurses together, which is a rare opportunity in such a sector. The present research focuses on the contribution of inter-professional training to the development of collaborative skills when managing an emergency situation in the context of anesthesia or intensive care. From direct observations of post-simulation debriefing sessions and interviews held with learners in post graduate or in-service training, either in single or multi-professional groups, this study shows that these sessions, based on experiential learning and reflective practice, help to build a shared vision of the problem and of common operative patterns, supporting better communication and the "ability to work in a team".

Cost-Sensitive Local Binary Feature Learning for Facial Age Estimation.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2015-12-01

In this paper, we propose a cost-sensitive local binary feature learning (CS-LBFL) method for facial age estimation. Unlike the conventional facial age estimation methods that employ hand-crafted descriptors or holistically learned descriptors for feature representation, our CS-LBFL method learns discriminative local features directly from raw pixels for face representation. Motivated by the fact that facial age estimation is a cost-sensitive computer vision problem and local binary features are more robust to illumination and expression variations than holistic features, we learn a series of hashing functions to project raw pixel values extracted from face patches into low-dimensional binary codes, where binary codes with similar chronological ages are projected as close as possible, and those with dissimilar chronological ages are projected as far as possible. Then, we pool and encode these local binary codes within each face image as a real-valued histogram feature for face representation. Moreover, we propose a cost-sensitive local binary multi-feature learning method to jointly learn multiple sets of hashing functions using face patches extracted from different scales to exploit complementary information. Our methods achieve competitive performance on four widely used face aging data sets.

Learning a Mahalanobis Distance-Based Dynamic Time Warping Measure for Multivariate Time Series Classification.

PubMed

Mei, Jiangyuan; Liu, Meizhu; Wang, Yuan-Fang; Gao, Huijun

2016-06-01

Multivariate time series (MTS) datasets broadly exist in numerous fields, including health care, multimedia, finance, and biometrics. How to classify MTS accurately has become a hot research topic since it is an important element in many computer vision and pattern recognition applications. In this paper, we propose a Mahalanobis distance-based dynamic time warping (DTW) measure for MTS classification. The Mahalanobis distance builds an accurate relationship between each variable and its corresponding category. It is utilized to calculate the local distance between vectors in MTS. Then we use DTW to align those MTS which are out of synchronization or with different lengths. After that, how to learn an accurate Mahalanobis distance function becomes another key problem. This paper establishes a LogDet divergence-based metric learning with triplet constraint model which can learn Mahalanobis matrix with high precision and robustness. Furthermore, the proposed method is applied on nine MTS datasets selected from the University of California, Irvine machine learning repository and Robert T. Olszewski's homepage, and the results demonstrate the improved performance of the proposed approach.

Vision Screening For Head Starters.

ERIC Educational Resources Information Center

Foley, Celia

To determine which children in the Head Start program may have vision problems, Head Start teachers and staff do vision "screening." This booklet demonstrates how to do the screening using the Snellen "E Chart." Trouble signs that the test administrator should be aware of are listed, and vision scores are explained simply.…

The Impact of Providing Vision Screening and Free Eyeglasses on Academic Outcomes: Evidence from a Randomized Trial in Title I Elementary Schools in Florida

PubMed Central

West, Kristine L.; Lee, Jongwook

2018-01-01

More than 20 percent of all school-aged children in the United States have vision problems, and low-income and minority children are disproportionately likely to have unmet vision care needs. Vision screening is common in U.S. schools, but it remains an open question whether screening alone is sufficient to improve student outcomes. We implemented a multi-armed randomized controlled trial to evaluate the impact of vision screening, and of vision screening accompanied by eye exams and eyeglasses, provided by a non-profit organization to Title I elementary schools in three large central Florida school districts. We find that providing additional/enhanced screening alone is generally insufficient to improve student achievement in math and reading. In contrast, providing screening along with free eye exams and free eyeglasses to students with vision problems improved student achievement as measured by standardized test scores. We find, averaging over all students (including those without vision problems), that this more comprehensive intervention increased the probability of passing the Florida Comprehensive Achievement Tests (FCAT) in reading and math by approximately 2.0 percentage points. We also present evidence that indicates that this impact fades out over time, indicating that follow-up actions after the intervention may be necessary to sustain these estimated achievement gains. PMID:29693366

Assistive peripheral phosphene arrays deliver advantages in obstacle avoidance in simulated end-stage retinitis pigmentosa: a virtual-reality study

NASA Astrophysics Data System (ADS)

Zapf, Marc Patrick H.; Boon, Mei-Ying; Lovell, Nigel H.; Suaning, Gregg J.

2016-04-01

Objective. The prospective efficacy of peripheral retinal prostheses for guiding orientation and mobility in the absence of residual vision, as compared to an implant for the central visual field (VF), was evaluated using simulated prosthetic vision (SPV). Approach. Sighted volunteers wearing a head-mounted display performed an obstacle circumvention task under SPV. Mobility and orientation performance with three layouts of prosthetic vision were compared: peripheral prosthetic vision of higher visual acuity (VA) but limited VF, of wider VF but limited VA, as well as centrally restricted prosthetic vision. Learning curves using these layouts were compared fitting an exponential model to the mobility and orientation measures. Main results. Using peripheral layouts, performance was superior to the central layout. Walking speed with both higher-acuity and wider-angle layouts was 5.6% higher, and mobility errors reduced by 46.4% and 48.6%, respectively, as compared to the central layout. The wider-angle layout yielded the least number of collisions, 63% less than the higher-acuity and 73% less than the central layout. Using peripheral layouts, the number of visual-scanning related head movements was 54.3% (higher-acuity) and 60.7% (wider-angle) lower, as compared to the central layout, and the ratio of time standing versus time walking was 51.9% and 61.5% lower, respectively. Learning curves did not differ between layouts, except for time standing versus time walking, where both peripheral layouts achieved significantly lower asymptotic values compared to the central layout. Significance. Beyond complementing residual vision for an improved performance, peripheral prosthetic vision can effectively guide mobility in the later stages of retinitis pigmentosa (RP) without residual vision. Further, the temporal dynamics of learning peripheral and central prosthetic vision are similar. Therefore, development of a peripheral retinal prosthesis and early implantation to alleviate VF constriction in RP should be considered to extend the target group and the time of benefit for potential retinal prosthesis implantees.

Perceptual learning in a non-human primate model of artificial vision

PubMed Central

Killian, Nathaniel J.; Vurro, Milena; Keith, Sarah B.; Kyada, Margee J.; Pezaris, John S.

2016-01-01

Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation. PMID:27874058

Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi

1989-01-01

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.

Cross-Modal Correspondence Among Vision, Audition, and Touch in Natural Objects: An Investigation of the Perceptual Properties of Wood.

PubMed

Kanaya, Shoko; Kariya, Kenji; Fujisaki, Waka

2016-10-01

Certain systematic relationships are often assumed between information conveyed from multiple sensory modalities; for instance, a small figure and a high pitch may be perceived as more harmonious. This phenomenon, termed cross-modal correspondence, may result from correlations between multi-sensory signals learned in daily experience of the natural environment. If so, we would observe cross-modal correspondences not only in the perception of artificial stimuli but also in perception of natural objects. To test this hypothesis, we reanalyzed data collected previously in our laboratory examining perceptions of the material properties of wood using vision, audition, and touch. We compared participant evaluations of three perceptual properties (surface brightness, sharpness of sound, and smoothness) of the wood blocks obtained separately via vision, audition, and touch. Significant positive correlations were identified for all properties in the audition-touch comparison, and for two of the three properties regarding in the vision-touch comparison. By contrast, no properties exhibited significant positive correlations in the vision-audition comparison. These results suggest that we learn correlations between multi-sensory signals through experience; however, the strength of this statistical learning is apparently dependent on the particular combination of sensory modalities involved. © The Author(s) 2016.

Shaping the First-Year Experience: Assessment of the Vision Planning Seminar at Nagoya University of Commerce and Business in Japan

ERIC Educational Resources Information Center

Ito, Hiroshi

2014-01-01

Learning assessments of the First-Year Experience (FYE) at universities have drawn increasing attention. Despite its current popularity, few pieces of literature on the FYE learning assessment exist in Japan. To present a case of FYE in the context of Japan, this paper examines the FYE course called the Vision Planning Seminar (VPS) at the Nagoya…

Resources and Information for Parents about Braille

MedlinePlus

... Vision Loss Eye Conditions Losing Your Sight? Using Technology For Parents of Blind Children For Job Seekers For Seniors Braille Video Description Programs & Services Technology Evaluation Center on Vision Loss Learning Center Professional ...

Vision Based Autonomous Robotic Control for Advanced Inspection and Repair

NASA Technical Reports Server (NTRS)

Wehner, Walter S.

2014-01-01

The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.

Bringing Vision to Practice: Planning and Provisioning the New Library Resource Center

ERIC Educational Resources Information Center

Wilson, Lisa

2004-01-01

The most critical factor in creating a successful school library is the development of a clear vision of the mission and functionality of this integral learning space. However, the process of bringing a vision to realization involves harsh realities and sensible planning. The budget will determine many purchasing decisions and therefore it is…

Student Writing, Teacher Feedback, and Working Online: Launching the Drive to Write Program

ERIC Educational Resources Information Center

Balu, Rekha; Alterman, Emma; Haider, Zeest; Quinn, Kelly

2018-01-01

The Drive to Write program was organized by New Visions for Public Schools (a New York City school support network that helps schools with professional development, data infrastructure, leadership training, certification, and more), and New Visions hopes it will lead to a new standard in writing instruction and student learning. New Visions is…

Visions for Space Exploration: ILS Issues and Approaches

NASA Technical Reports Server (NTRS)

Watson, Kevin

2005-01-01

This viewgraph presentation reviews some of the logistic issues that the Vision for Space Exploration will entail. There is a review of the vision and the timeline for the return to the moon that will lead to the first human exploration of Mars. The lessons learned from the International Space Station (ISS) and other such missions are also reviewed.

INCREASED VISUAL BEHAVIOR IN LOW VISION CHILDREN.

ERIC Educational Resources Information Center

BARRAGA, NATALIE

TEN PAIRS OF BLIND CHILDREN AGED SIX TO 13 YEARS WHO HAD SOME VISION WERE MATCHED BY PRETEST SCORES ON A TEST OF VISUAL DISCRIMINATION. A CRITERION GROUP, DESIGNATED THE PRINT COMPARISON GROUP, HAD SLIGHLY HIGHER RECORDED DISTANCE ACUITIES AND USED VISION AS THE PRIMARY MEANS OF LEARNING. PAIRS OF EXPERIMENTAL SUBJECTS DAILY RECEIVED 45 MINUTES OF…

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

A Clear Vision for Equity and Opportunity.

ERIC Educational Resources Information Center

Gould, Marge Christensen; Gould, Herman

2003-01-01

Describes undetected and uncorrected vision problems for children in poverty associated with juvenile delinquency and poor academic performance. Discusses success of a project offering vision screening and free glasses for at-risk students in Tucson, Arizona. (PKP)

Integrated Imaging and Vision Techniques for Industrial Inspection: A Special Issue on Machine Vision and Applications

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

Liu, Zheng; Ukida, H.; Ramuhalli, Pradeep

2010-06-05

Imaging- and vision-based techniques play an important role in industrial inspection. The sophistication of the techniques assures high- quality performance of the manufacturing process through precise positioning, online monitoring, and real-time classification. Advanced systems incorporating multiple imaging and/or vision modalities provide robust solutions to complex situations and problems in industrial applications. A diverse range of industries, including aerospace, automotive, electronics, pharmaceutical, biomedical, semiconductor, and food/beverage, etc., have benefited from recent advances in multi-modal imaging, data fusion, and computer vision technologies. Many of the open problems in this context are in the general area of image analysis methodologies (preferably in anmore » automated fashion). This editorial article introduces a special issue of this journal highlighting recent advances and demonstrating the successful applications of integrated imaging and vision technologies in industrial inspection.« less

Accomplishing the Visions for Teacher Education Programs Advocated in the National Science Education Standards

NASA Astrophysics Data System (ADS)

Akcay, Hakan; Yager, Robert

2010-10-01

The purpose of this study was to investigate the advantages of an approach to instruction using current problems and issues as curriculum organizers and illustrating how teaching must change to accomplish real learning. The study sample consisted of 41 preservice science teachers (13 males and 28 females) in a model science teacher education program. Both qualitative and quantitative research methods were used to determine success with science discipline-specific “Societal and Educational Applications” courses as one part of a total science teacher education program at a large Midwestern university. Students were involved with idea generation, consideration of multiple points of views, collaborative inquiries, and problem solving. All of these factors promoted grounded instruction using constructivist perspectives that situated science with actual experiences in the lives of students.

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

NASA Astrophysics Data System (ADS)

Gil, Pablo

2017-10-01

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

Find Services for People Who Are Blind or Visually Impaired

MedlinePlus

... Vision Loss Eye Conditions Losing Your Sight? Using Technology For Parents of Blind Children For Job Seekers For Seniors Braille Video Description Programs & Services Technology Evaluation Center on Vision Loss Learning Center Professional ...

Psychological Adjustment in Adolescents with Vision Impairment

ERIC Educational Resources Information Center

Pinquart, Martin; Pfeiffer, Jens P.

2012-01-01

The present study compared psychological adjustment of 158 adolescents with vision impairment and 158 sighted adolescents with a matched-pair design using the Strengths and Difficulties Questionnaire. Adolescent self-reports and teacher reports on emotional problems, peer problems, and total difficulties showed higher scores in students with…

Low Vision Aids in Glaucoma

PubMed Central

Khanna, Anjani

2012-01-01

A large number of glaucoma patients suffer from vision impairments that qualify as low vision. Additional difficulties associated with low vision include problems with glare, lighting, and contrast, which can make daily activities extremely challenging. This article elaborates on how low vision aids can help with various tasks that visually impaired glaucoma patients need to do each day, to take care of themselves and to lead an independent life. PMID:27990068

Perspectives on leadership: moving out of the corner of our room.

PubMed

Ferguson-Paré, Mary

2011-10-01

Perspectives on leadership developed through a career as a nurse leader are shared, including the author's guiding vision, a valuing of nursing as knowledge work, how to create a learning organization that supports professional practice, and other lessons learned through experience. Readers are urged to find the leadership voice within, be courageous, engage surrounding opportunities, and be guided by their vision of what nursing should be in the future.

A Feasibility Study of View-independent Gait Identification

DTIC Science & Technology

2012-03-01

ice skates . For walking, the footprint records for single pixels form clusters that are well separated in space and time. (Any overlap of contact...Pattern Recognition 2007, 1-8. Cheng M-H, Ho M-F & Huang C-L (2008), "Gait Analysis for Human Identification Through Manifold Learning and HMM... Learning and Cybernetics 2005, 4516-4521 Moeslund T B & Granum E (2001), "A Survey of Computer Vision-Based Human Motion Capture", Computer Vision

The manipulation of vision during the powerlift squat: exploring the boundaries of the specificity of learning hypothesis.

PubMed

Bennett, S; Davids, K

1995-09-01

The available information for controlling a multidegree-of-freedom sport action was manipulated in 2 experiments. In the first, 10 intermediate lifters were participants; for the second, 8 skilled and 8 less skilled lifters were observed. Three single repetitions of a powerlift squat were performed under 3 vision conditions (i.e., full, ambient, no vision). The less skilled and intermediate lifters' technical performance decreased significantly with the removal of visual information. There was no detrimental effect in the skilled group. Despite the differing information constraints, skilled lifters exhibited a high level of positioning accuracy and timing consistency across conditions. These data fail to support the theoretical predictions of the specificity of learning hypothesis. The differences between the task constraints in this study and those in manual aiming investigations may represent a boundary to the current propositions of the specificity of learning hypothesis.

Learning multimodal dictionaries.

PubMed

Monaci, Gianluca; Jost, Philippe; Vandergheynst, Pierre; Mailhé, Boris; Lesage, Sylvain; Gribonval, Rémi

2007-09-01

Real-world phenomena involve complex interactions between multiple signal modalities. As a consequence, humans are used to integrate at each instant perceptions from all their senses in order to enrich their understanding of the surrounding world. This paradigm can be also extremely useful in many signal processing and computer vision problems involving mutually related signals. The simultaneous processing of multimodal data can, in fact, reveal information that is otherwise hidden when considering the signals independently. However, in natural multimodal signals, the statistical dependencies between modalities are in general not obvious. Learning fundamental multimodal patterns could offer deep insight into the structure of such signals. In this paper, we present a novel model of multimodal signals based on their sparse decomposition over a dictionary of multimodal structures. An algorithm for iteratively learning multimodal generating functions that can be shifted at all positions in the signal is proposed, as well. The learning is defined in such a way that it can be accomplished by iteratively solving a generalized eigenvector problem, which makes the algorithm fast, flexible, and free of user-defined parameters. The proposed algorithm is applied to audiovisual sequences and it is able to discover underlying structures in the data. The detection of such audio-video patterns in audiovisual clips allows to effectively localize the sound source on the video in presence of substantial acoustic and visual distractors, outperforming state-of-the-art audiovisual localization algorithms.

Blending Community Service and Teaching to Open Vision Care and Eye Health Awareness to University Students

ERIC Educational Resources Information Center

Do, Chi-wai; Chan, Lily Y. L.; Wong, Horace H. Y.; Chu, Geoffrey; Yu, Wing Yan; Pang, Peter C. K.; Cheong, Allen M. Y.; Ting, Patrick Wai-ki; Lam, Thomas Chuen; Kee, Chea-su; Lam, Andrew; Chan, Henry H. L.

2016-01-01

A vision care-based community service subject is offered to general university students for fulfillment of a service-learning compulsory credit requirement. Here, a professional health subject is taught in a way that caters to generalist learners. Students gain basic skills they can apply to provide vision screenings for the needy population. All…

Visioning the Centre for Place and Sustainability Studies through an Embodied Aesthetic Wholeness

ERIC Educational Resources Information Center

Sameshima, Pauline; Greenwood, David A.

2015-01-01

In the context of research universities, what kind of places and spaces can we create for ourselves that foster a holistic vision of learning and community, a vision that is responsive to the shifting social and ecological landscapes of the Anthropocene? How can these spaces simultaneously address the need to nurture both personal and cultural…

A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation

NASA Astrophysics Data System (ADS)

Cruz-Roa, Angel; Arevalo, John; Basavanhally, Ajay; Madabhushi, Anant; González, Fabio

2015-01-01

Learning data representations directly from the data itself is an approach that has shown great success in different pattern recognition problems, outperforming state-of-the-art feature extraction schemes for different tasks in computer vision, speech recognition and natural language processing. Representation learning applies unsupervised and supervised machine learning methods to large amounts of data to find building-blocks that better represent the information in it. Digitized histopathology images represents a very good testbed for representation learning since it involves large amounts of high complex, visual data. This paper presents a comparative evaluation of different supervised and unsupervised representation learning architectures to specifically address open questions on what type of learning architectures (deep or shallow), type of learning (unsupervised or supervised) is optimal. In this paper we limit ourselves to addressing these questions in the context of distinguishing between anaplastic and non-anaplastic medulloblastomas from routine haematoxylin and eosin stained images. The unsupervised approaches evaluated were sparse autoencoders and topographic reconstruct independent component analysis, and the supervised approach was convolutional neural networks. Experimental results show that shallow architectures with more neurons are better than deeper architectures without taking into account local space invariances and that topographic constraints provide useful invariant features in scale and rotations for efficient tumor differentiation.

Transformational Teaching: Theoretical Underpinnings, Basic Principles, and Core Methods

PubMed Central

Slavich, George M.; Zimbardo, Philip G.

2012-01-01

Approaches to classroom instruction have evolved considerably over the past 50 years. This progress has been spurred by the development of several learning principles and methods of instruction, including active learning, student-centered learning, collaborative learning, experiential learning, and problem-based learning. In the present paper, we suggest that these seemingly different strategies share important underlying characteristics and can be viewed as complimentary components of a broader approach to classroom instruction called transformational teaching. Transformational teaching involves creating dynamic relationships between teachers, students, and a shared body of knowledge to promote student learning and personal growth. From this perspective, instructors are intellectual coaches who create teams of students who collaborate with each other and with their teacher to master bodies of information. Teachers assume the traditional role of facilitating students’ acquisition of key course concepts, but do so while enhancing students’ personal development and attitudes toward learning. They accomplish these goals by establishing a shared vision for a course, providing modeling and mastery experiences, challenging and encouraging students, personalizing attention and feedback, creating experiential lessons that transcend the boundaries of the classroom, and promoting ample opportunities for preflection and reflection. We propose that these methods are synergistically related and, when used together, maximize students’ potential for intellectual and personal growth. PMID:23162369

Launching Professional Learning Communities: Beginning Actions.

ERIC Educational Resources Information Center

Leo, Tara; Cowan, D'Ette

2000-01-01

A Professional Learning Community (PLC) is a school where administrators and teachers continuously seek and share learning to increase their effectiveness for students and act on what they learn. PLCs are characterized by five dimensions: shared and supportive leadership, shared values and vision, collective learning and application of learning,…

Vision Guided Intelligent Robot Design And Experiments

NASA Astrophysics Data System (ADS)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

PlantCV v2: Image analysis software for high-throughput plant phenotyping

PubMed Central

Abbasi, Arash; Berry, Jeffrey C.; Callen, Steven T.; Chavez, Leonardo; Doust, Andrew N.; Feldman, Max J.; Gilbert, Kerrigan B.; Hodge, John G.; Hoyer, J. Steen; Lin, Andy; Liu, Suxing; Lizárraga, César; Lorence, Argelia; Miller, Michael; Platon, Eric; Tessman, Monica; Sax, Tony

2017-01-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning. PMID:29209576

PlantCV v2: Image analysis software for high-throughput plant phenotyping.

PubMed

Gehan, Malia A; Fahlgren, Noah; Abbasi, Arash; Berry, Jeffrey C; Callen, Steven T; Chavez, Leonardo; Doust, Andrew N; Feldman, Max J; Gilbert, Kerrigan B; Hodge, John G; Hoyer, J Steen; Lin, Andy; Liu, Suxing; Lizárraga, César; Lorence, Argelia; Miller, Michael; Platon, Eric; Tessman, Monica; Sax, Tony

2017-01-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

PlantCV v2: Image analysis software for high-throughput plant phenotyping

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

Gehan, Malia A.; Fahlgren, Noah; Abbasi, Arash

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here in this paper we present the details andmore » rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.« less

PlantCV v2: Image analysis software for high-throughput plant phenotyping

DOE PAGES

Gehan, Malia A.; Fahlgren, Noah; Abbasi, Arash; ...

2017-12-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here in this paper we present the details andmore » rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.« less

Topographic Mapping of Residual Vision by Computer

ERIC Educational Resources Information Center

MacKeben, Manfred

2008-01-01

Many persons with low vision have diseases that damage the retina only in selected areas, which can lead to scotomas (blind spots) in perception. The most frequent of these diseases is age-related macular degeneration (AMD), in which foveal vision is often impaired by a central scotoma that impairs vision of fine detail and causes problems with…

Healthier students are better learners: a missing link in school reforms to close the achievement gap.

PubMed

Basch, Charles E

2011-10-01

This article provides an introduction to the October 2011 special issue of the Journal of School Health on "Healthier Students Are Better Learners." Literature was reviewed and synthesized to identify health problems affecting school-aged youth that are highly prevalent, disproportionately affect urban minority youth, directly and indirectly causally affect academic achievement, and can be feasibly and effectively addressed through school health programs and services. Based on these criteria, 7 educationally relevant health disparities were selected as strategic priorities to help close the achievement gap: (1) vision, (2) asthma, (3) teen pregnancy, (4) aggression and violence, (5) physical activity, (6) breakfast, and (7) inattention and hyperactivity. Research clearly shows that these health problems influence students' motivation and ability to learn. Disparities among urban minority youth are outlined, along with the causal pathways through which each adversely affects academic achievement, including sensory perceptions, cognition, school connectedness, absenteeism, and dropping out. Evidence-based approaches that schools can implement to address these problems are presented. These health problems and the causal pathways they influence have interactive and a synergistic effect, which is why they must be addressed collectively using a coordinated approach. No matter how well teachers are prepared to teach, no matter what accountability measures are put in place, no matter what governing structures are established for schools, educational progress will be profoundly limited if students are not motivated and able to learn. Particular health problems play a major role in limiting the motivation and ability to learn of urban minority youth. This is why reducing these disparities through a coordinated approach warrants validation as a cohesive school improvement initiative to close the achievement gap. Local, state, and national policies for implementing this recommendation are suggested. © 2011, American School Health Association.

Teaching organization theory for healthcare management: three applied learning methods.

PubMed

Olden, Peter C

2006-01-01

Organization theory (OT) provides a way of seeing, describing, analyzing, understanding, and improving organizations based on patterns of organizational design and behavior (Daft 2004). It gives managers models, principles, and methods with which to diagnose and fix organization structure, design, and process problems. Health care organizations (HCOs) face serious problems such as fatal medical errors, harmful treatment delays, misuse of scarce nurses, costly inefficiency, and service failures. Some of health care managers' most critical work involves designing and structuring their organizations so their missions, visions, and goals can be achieved-and in some cases so their organizations can survive. Thus, it is imperative that graduate healthcare management programs develop effective approaches for teaching OT to students who will manage HCOs. Guided by principles of education, three applied teaching/learning activities/assignments were created to teach OT in a graduate healthcare management program. These educationalmethods develop students' competency with OT applied to HCOs. The teaching techniques in this article may be useful to faculty teaching graduate courses in organization theory and related subjects such as leadership, quality, and operation management.

Classification Objects, Ideal Observers & Generative Models

ERIC Educational Resources Information Center

Olman, Cheryl; Kersten, Daniel

2004-01-01

A successful vision system must solve the problem of deriving geometrical information about three-dimensional objects from two-dimensional photometric input. The human visual system solves this problem with remarkable efficiency, and one challenge in vision research is to understand how neural representations of objects are formed and what visual…

Non-Rigid Structure Estimation in Trajectory Space from Monocular Vision

PubMed Central

Wang, Yaming; Tong, Lingling; Jiang, Mingfeng; Zheng, Junbao

2015-01-01

In this paper, the problem of non-rigid structure estimation in trajectory space from monocular vision is investigated. Similar to the Point Trajectory Approach (PTA), based on characteristic points’ trajectories described by a predefined Discrete Cosine Transform (DCT) basis, the structure matrix was also calculated by using a factorization method. To further optimize the non-rigid structure estimation from monocular vision, the rank minimization problem about structure matrix is proposed to implement the non-rigid structure estimation by introducing the basic low-rank condition. Moreover, the Accelerated Proximal Gradient (APG) algorithm is proposed to solve the rank minimization problem, and the initial structure matrix calculated by the PTA method is optimized. The APG algorithm can converge to efficient solutions quickly and lessen the reconstruction error obviously. The reconstruction results of real image sequences indicate that the proposed approach runs reliably, and effectively improves the accuracy of non-rigid structure estimation from monocular vision. PMID:26473863

Group learning capacity: the roles of open-mindedness and shared vision

PubMed Central

Lord, Mimi

2015-01-01

Open-mindedness (OPM) is a construct that is considered a key foundational aspect of learning in individuals, groups and organizations. Also known as critical inquiry or reflection, OPM is believed to increase learning through examination of prior beliefs, decisions and mistakes, and also through openness to new ideas. Renowned theorists including Dewey and Argyris have emphasized the relationship between OPM and learning, yet little quantitative research has tested it or examined moderators of the linkage. The setting for the current study is that of endowment investment committees at U.S. universities and colleges who need to make knowledgeable and well-reasoned decisions about the composition of investment portfolios. Findings indicate that OPM has a positive, significant effect on group learning capacity (LCAP) and also that shared vision, which represents the group's collective purpose and direction, moderates that relationship. The literature review and discussion offer insights about how OPM is related to the research on group conflict, and how shared vision (SHV) differs from concepts such as interpersonal cohesiveness and conformity that have been associated with groupthink. A review of relevant research from the fields of organizational learning, group dynamics, and absorptive capacity provides context for the development of the hypotheses and the discussion of findings. PMID:25774141

A case of learning to teach elementary science: Investigating beliefs, experiences, and tensions

NASA Astrophysics Data System (ADS)

Bryan, Lynn Ann

This study examines how preservice elementary teacher beliefs and experiences within the context of reflective science teacher education influence the development of professional knowledge. From a cognitive constructivist theoretical perspective, I conducted a case analysis to investigate the beliefs about science teaching and learning held by a preservice teacher (Barbara), identify the tensions she encountered in learning to teach elementary science, understand the frames from which she identified problems of practice, and discern how her experiences influenced the process of reflecting on her own science teaching. From an analysis of interviews, observation, and written documents, I constructed a profile of Barbara's beliefs that consisted of three foundational and three dualistic beliefs about science teaching and learning. Her foundational beliefs concerned: (a) the value of science and science teaching, (b) the nature of scientific concepts and goals of science instruction, and (c) control in the science classroom. Barbara held dualistic beliefs about: (a) how children learn science, (b) the science students' role, and (c) the science teacher's role. The dualistic beliefs formed two contradictory nests of beliefs. One nest, grounded in life-long science learner experiences, reflected a didactic teaching orientation and predominantly guided her practice. The second nest, not well-grounded in experience, embraced a hands-on approach and predominantly guided her vision of practice. Barbara encountered tensions in thinking about science teaching and learning as a result of inconsistencies between her vision of science teaching and her actual practice. Confronting these tensions prompted Barbara to rethink the connections between her classroom actions and students' learning, create new perspectives for viewing her practice, and consider alternative practices more resonant with her visionary beliefs. However, the self-reinforcing belief system created by her didactic nest of beliefs, control beliefs, and belief about the goals of science instruction prevented Barbara from enacting new frames in practice. The findings contribute to an understanding of the relationship between beliefs and experiences in learning to teach and indicate that reframing is crucial in developing professional knowledge. Furthermore, the findings underscore the significance of (a) identifying prospective teachers' beliefs for designing teacher preparation programs, and (b) offering experiences as professionals early in the careers of prospective teachers.

Active Learning in Engineering Education: A (Re)Introduction

ERIC Educational Resources Information Center

Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth

2017-01-01

The informal network "Active Learning in Engineering Education" (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE are centred on the vision that learners…

Lightness modification of color image for protanopia and deuteranopia

NASA Astrophysics Data System (ADS)

Tanaka, Go; Suetake, Noriaki; Uchino, Eiji

2010-01-01

In multimedia content, colors play important roles in conveying visual information. However, color information cannot always be perceived uniformly by all people. People with a color vision deficiency, such as dichromacy, cannot recognize and distinguish certain color combinations. In this paper, an effective lightness modification method, which enables barrier-free color vision for people with dichromacy, especially protanopia or deuteranopia, while preserving the color information in the original image for people with standard color vision, is proposed. In the proposed method, an optimization problem concerning lightness components is first defined by considering color differences in an input image. Then a perceptible and comprehensible color image for both protanopes and viewers with no color vision deficiency or both deuteranopes and viewers with no color vision deficiency is obtained by solving the optimization problem. Through experiments, the effectiveness of the proposed method is illustrated.

A visual tracking method based on improved online multiple instance learning

NASA Astrophysics Data System (ADS)

He, Xianhui; Wei, Yuxing

2016-09-01

Visual tracking is an active research topic in the field of computer vision and has been well studied in the last decades. The method based on multiple instance learning (MIL) was recently introduced into the tracking task, which can solve the problem that template drift well. However, MIL method has relatively poor performance in running efficiency and accuracy, due to its strong classifiers updating strategy is complicated, and the speed of the classifiers update is not always same with the change of the targets' appearance. In this paper, we present a novel online effective MIL (EMIL) tracker. A new update strategy for strong classifier was proposed to improve the running efficiency of MIL method. In addition, to improve the t racking accuracy and stability of the MIL method, a new dynamic mechanism for learning rate renewal of the classifier and variable search window were proposed. Experimental results show that our method performs good performance under the complex scenes, with strong stability and high efficiency.

Keep Your Vision Healthy: Learn About Comprehensive Dilated Eye Exams

MedlinePlus

... risk for glaucoma, age-related macular degeneration, and diabetic retinopathy—the most common cause of vision loss from ... to these areas may be a sign of diabetic retinopathy, glaucoma, or age-related macular degeneration. Tonometry measures ...

Smart vision chips: An overview

NASA Technical Reports Server (NTRS)

Koch, Christof

1994-01-01

This viewgraph presentation presents four working analog VLSI vision chips: (1) time-derivative retina, (2) zero-crossing chip, (3) resistive fuse, and (4) figure-ground chip; work in progress on computing motion and neuromorphic systems; and conceptual and practical lessons learned.

Quaternions in computer vision and robotics

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

Pervin, E.; Webb, J.A.

1982-01-01

Computer vision and robotics suffer from not having good tools for manipulating three-dimensional objects. Vectors, coordinate geometry, and trigonometry all have deficiencies. Quaternions can be used to solve many of these problems. Many properties of quaternions that are relevant to computer vision and robotics are developed. Examples are given showing how quaternions can be used to simplify derivations in computer vision and robotics.

Computer-assisted learning in human and dental medicine.

PubMed

Höhne, S; Schumann, R R

2004-04-01

This article describes the development and application of new didactic methods for use in computer-assisted teaching and learning systems for training doctors and dentists. Taking the Meducase project as an example, didactic models and their technological implementation are explained, together with the limitations of imparting knowledge with the "new media". In addition, legal concepts for a progressive, pragmatic, and innovative distribution of knowledge to undergraduate students are presented. In conclusion, potential and visions for the wide use of electronic learning in the German and European universities in the future are discussed. Self-directed learning (SDL) is a key component in both undergraduate education and lifelong learning for medical practitioners. E-learning can already be used to promote SDL at undergraduate level. The Meducase project uses self-directed, constructive, case- and problem-oriented learning within a learning platform for medical and dental students. In the long run, e-learning programs can only be successful in education if there is consistent analysis and implementation of value-added factors and the development and use of media-didactic concepts matched to electronic learning. The use of innovative forms of licensing - open source licenses for software and similar licenses for content - facilitates continuous, free access to these programs for all students and teachers. These legal concepts offer the possibility of innovative knowledge distribution, quality assurance and standardization across specializations, university departments, and possibly even national borders.

The Music of Mathematics: Toward a New Problem Typology

NASA Astrophysics Data System (ADS)

Quarfoot, David

Halmos (1980) once described problems and their solutions as "the heart of mathematics". Following this line of thinking, one might naturally ask: "What, then, is the heart of problems?". In this work, I attempt to answer this question using techniques from statistics, information visualization, and machine learning. I begin the journey by cataloging the features of problems delineated by the mathematics and mathematics education communities. These dimensions are explored in a large data set of students working thousands of problems at the Art of Problem Solving, an online company that provides adaptive mathematical training for students around the world. This analysis is able to concretely show how the fabric of mathematical problems changes across different subjects, difficulty levels, and students. Furthermore, it locates problems that stand out in the crowd -- those that synergize cognitive engagement, learning, and difficulty. This quantitatively-heavy side of the dissertation is partnered with a qualitatively-inspired portion that involves human scoring of 105 problems and their solutions. In this setting, I am able to capture elusive features of mathematical problems and derive a fuller picture of the space of mathematical problems. Using correlation matrices, principal components analysis, and clustering techniques, I explore the relationships among those features frequently discussed in mathematics problems (e.g., difficulty, creativity, novelty, affective engagement, authenticity). Along the way, I define a new set of uncorrelated features in problems and use these as the basis for a New Mathematical Problem Typology (NMPT). Grounded in the terminology of classical music, the NMPT works to quickly convey the essence and value of a problem, just as terms like "etude" and "mazurka" do for musicians. Taken together, these quantitative and qualitative analyses seek to terraform the landscape of mathematical problems and, concomitantly, the current thinking about that world. Most importantly, this work highlights and names the panoply of problems that exist, expanding the myopic vision of contemporary mathematical problem solving.

Reliable vision-guided grasping

NASA Technical Reports Server (NTRS)

Nicewarner, Keith E.; Kelley, Robert B.

1992-01-01

Automated assembly of truss structures in space requires vision-guided servoing for grasping a strut when its position and orientation are uncertain. This paper presents a methodology for efficient and robust vision-guided robot grasping alignment. The vision-guided grasping problem is related to vision-guided 'docking' problems. It differs from other hand-in-eye visual servoing problems, such as tracking, in that the distance from the target is a relevant servo parameter. The methodology described in this paper is hierarchy of levels in which the vision/robot interface is decreasingly 'intelligent,' and increasingly fast. Speed is achieved primarily by information reduction. This reduction exploits the use of region-of-interest windows in the image plane and feature motion prediction. These reductions invariably require stringent assumptions about the image. Therefore, at a higher level, these assumptions are verified using slower, more reliable methods. This hierarchy provides for robust error recovery in that when a lower-level routine fails, the next-higher routine will be called and so on. A working system is described which visually aligns a robot to grasp a cylindrical strut. The system uses a single camera mounted on the end effector of a robot and requires only crude calibration parameters. The grasping procedure is fast and reliable, with a multi-level error recovery system.

Problems with vision associated with limitations or avoidance of driving in older populations.

PubMed

Satariano, William A; MacLeod, Kara E; Cohn, Theodore E; Ragland, David R

2004-09-01

This report examines the role of (a) disease processes affecting vision, (b) reported troubles with vision, (c) physical symptoms affecting the eyes, and (d) objective measures in reported driving limitation due to problems with eyesight among older drivers. Data for this study (N = 1,840) were obtained from participants in a community-based study of aging and physical performance in people age 55 or older in the city of Sonoma, California. Each of 16 visual conditions was assessed for impact on reported driving limitation due to eyesight by calculating a "risk" ratio. Then, prevalence of the condition was combined with the ratio to generate an attributable risk for that condition for vision-related limitations in driving. Each condition was significantly associated with reported limitations in driving due to eyesight. "Avoiding physical activity due to vision" (ratio = 3.4) and "trouble seeing steps up/down stairs" (ratio = 2.9) had the strongest association. However, "glasses/contacts required for driving" and "trouble with glare from sun/lights" had the highest attributable risks (35.8 and 29.4). The risk ratio is relevant for evaluating individuals; the attributable risk is relevant to planning countermeasures in populations. Addressing specific problems related to vision should substantially reduce driving limitations due to eyesight.

Indirect iterative learning control for a discrete visual servo without a camera-robot model.

PubMed

Jiang, Ping; Bamforth, Leon C A; Feng, Zuren; Baruch, John E F; Chen, YangQuan

2007-08-01

This paper presents a discrete learning controller for vision-guided robot trajectory imitation with no prior knowledge of the camera-robot model. A teacher demonstrates a desired movement in front of a camera, and then, the robot is tasked to replay it by repetitive tracking. The imitation procedure is considered as a discrete tracking control problem in the image plane, with an unknown and time-varying image Jacobian matrix. Instead of updating the control signal directly, as is usually done in iterative learning control (ILC), a series of neural networks are used to approximate the unknown Jacobian matrix around every sample point in the demonstrated trajectory, and the time-varying weights of local neural networks are identified through repetitive tracking, i.e., indirect ILC. This makes repetitive segmented training possible, and a segmented training strategy is presented to retain the training trajectories solely within the effective region for neural network approximation. However, a singularity problem may occur if an unmodified neural-network-based Jacobian estimation is used to calculate the robot end-effector velocity. A new weight modification algorithm is proposed which ensures invertibility of the estimation, thus circumventing the problem. Stability is further discussed, and the relationship between the approximation capability of the neural network and the tracking accuracy is obtained. Simulations and experiments are carried out to illustrate the validity of the proposed controller for trajectory imitation of robot manipulators with unknown time-varying Jacobian matrices.

How Does My Child's Vision Affect His Reading?

ERIC Educational Resources Information Center

Eberly, Donald W.

Various eye problems and the effects they can have on children's reading abilities are explored in this pamphlet, which is one of a series designed to answer parents' questions about their children's reading development. Topics discussed are the demands on vision made by reading, problems that affect visual acuity (nearsightedness, farsightedness,…

The role of vision processing in prosthetic vision.

PubMed

Barnes, Nick; He, Xuming; McCarthy, Chris; Horne, Lachlan; Kim, Junae; Scott, Adele; Lieby, Paulette

2012-01-01

Prosthetic vision provides vision which is reduced in resolution and dynamic range compared to normal human vision. This comes about both due to residual damage to the visual system from the condition that caused vision loss, and due to limitations of current technology. However, even with limitations, prosthetic vision may still be able to support functional performance which is sufficient for tasks which are key to restoring independent living and quality of life. Here vision processing can play a key role, ensuring that information which is critical to the performance of key tasks is available within the capability of the available prosthetic vision. In this paper, we frame vision processing for prosthetic vision, highlight some key areas which present problems in terms of quality of life, and present examples where vision processing can help achieve better outcomes.

Education Research in Physical Therapy: Visions of the Possible.

PubMed

Jensen, Gail M; Nordstrom, Terrence; Segal, Richard L; McCallum, Christine; Graham, Cecilia; Greenfield, Bruce

2016-12-01

Education research has been labeled the "hardest science" of all, given the challenges of teaching and learning in an environment encompassing a mixture of social interactions, events, and problems coupled with a persistent belief that education depends more on common sense than on disciplined knowledge and skill. The American Educational Research Association specifies that education research-as a scientific field of study-examines teaching and learning processes that shape educational outcomes across settings and that a learning process takes place throughout a person's life. The complexity of learning and learning environments requires not only a diverse array of research methods but also a community of education researchers committed to exploring critical questions in the education of physical therapists. Although basic science research and clinical research in physical therapy have continued to expand through growth in the numbers of funded physical therapist researchers, the profession still lacks a robust and vibrant community of education researchers. In this perspective article, the American Council of Academic Physical Therapy Task Force on Education Research proposes a compelling rationale for building a much-needed foundation for education research in physical therapy, including a set of recommendations for immediate action. © 2016 American Physical Therapy Association.

Measuring the learning capacity of organisations: development and factor analysis of the Questionnaire for Learning Organizations.

PubMed

Oudejans, S C C; Schippers, G M; Schramade, M H; Koeter, M W J; van den Brink, W

2011-04-01

To investigate internal consistency and factor structure of a questionnaire measuring learning capacity based on Senge's theory of the five disciplines of a learning organisation: Personal Mastery, Mental Models, Shared Vision, Team Learning, and Systems Thinking. Cross-sectional study. Substance-abuse treatment centres (SATCs) in The Netherlands. A total of 293 SATC employees from outpatient and inpatient treatment departments, financial and human resources departments. Psychometric properties of the Questionnaire for Learning Organizations (QLO), including factor structure, internal consistency, and interscale correlations. A five-factor model representing the five disciplines of Senge showed good fit. The scales for Personal Mastery, Shared Vision and Team Learning had good internal consistency, but the scales for Systems Thinking and Mental Models had low internal consistency. The proposed five-factor structure was confirmed in the QLO, which makes it a promising instrument to assess learning capacity in teams. The Systems Thinking and the Mental Models scales have to be revised. Future research should be aimed at testing criterion and discriminatory validity.

Object recognition based on Google's reverse image search and image similarity

NASA Astrophysics Data System (ADS)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

Resources for Adapting Low Vision Training Materials for the Adult with Low Literacy Skills. Practice Report

ERIC Educational Resources Information Center

Tucker, Laurel A.

2004-01-01

Adults with low vision who seek clinical low vision services need to be able to read (that is, to interpret or understand words, numbers, and symbols in print meaningfully). Reading difficulties that adults encounter during low vision therapy may be directly connected to a visual impairment or may be related to other reading problems, such as…

Implementation of a Campuswide Distributed Mass Storage Service: the Dream Versus Reality

NASA Technical Reports Server (NTRS)

Prahst, Stephen; Armstead, Betty Jo

1996-01-01

In 1990, a technical team at NASA Lewis Research Center, Cleveland, Ohio, began defining a Mass Storage Service to pro- wide long-term archival storage, short-term storage for very large files, distributed Network File System access, and backup services for critical data dw resides on workstations and personal computers. Because of software availability and budgets, the total service was phased in over dm years. During the process of building the service from the commercial technologies available, our Mass Storage Team refined the original vision and learned from the problems and mistakes that occurred. We also enhanced some technologies to better meet the needs of users and system administrators. This report describes our team's journey from dream to reality, outlines some of the problem areas that still exist, and suggests some solutions.

Height Measuring System On Video Using Otsu Method

NASA Astrophysics Data System (ADS)

Sandy, C. L. M.; Meiyanti, R.

2017-01-01

A measurement of height is comparing the value of the magnitude of an object with a standard measuring tool. The problems that exist in the measurement are still the use of a simple apparatus in which one of them is by using a meter. This method requires a relatively long time. To overcome these problems, this research aims to create software with image processing that is used for the measurement of height. And subsequent that image is tested, where the object captured by the video camera can be known so that the height of the object can be measured using the learning method of Otsu. The system was built using Delphi 7 of Vision Lab VCL 4.5 component. To increase the quality of work of the system in future research, the developed system can be combined with other methods.

Self-Taught Low-Rank Coding for Visual Learning.

PubMed

Li, Sheng; Li, Kang; Fu, Yun

2018-03-01

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

Transforming American Education

ERIC Educational Resources Information Center

Horn, Michael B.; Mackey, Katherine

2011-01-01

In this article the authors accept as a given the National Education Technology Plan's vision of a transformed education system powered by technology such that learners receive personalized and engaging learning experiences, and where assessment, teaching, infrastructure, and productivity are redefined. The article analyzes this vision of a…

Assessing the Future.

ERIC Educational Resources Information Center

Berger, Allen

A review of the past, the present, and the future offers an enlightening view of literacy in America. A 1967 issue of the "Illinois Journal of Education" has articles on phonics, linguistics, spelling, modalities of learning, disadvantaged children, vision screening and vision training, readiness, Montessori, partnerships between…

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

NASA Technical Reports Server (NTRS)

Knasel, T. Michael

1996-01-01

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Degas: Vision and Perception.

ERIC Educational Resources Information Center

Kendall, Richard

1988-01-01

The art of Edgar Degas is discussed in relation to his impaired vision, including amblyopia, later blindness in one eye, corneal scarring, and photophobia. Examined are ways in which Degas compensated for vision problems, and dominant themes of his art such as the process of perception and spots of brilliant light. (Author/JDD)

State of Learning in Canada: A Year in Review, 2009-2010. Executive Summary

ERIC Educational Resources Information Center

Canadian Council on Learning, 2010

2010-01-01

The 2009-2010 "State of Learning in Canada" provides the most current information on the Canadian learning landscape, contributing to a comprehensive understanding of how Canadians are faring as lifelong learners. As in previous "State of Learning" reports, this update reflects CCL's vision of learning as a lifelong process.…

Machine vision for various manipulation tasks

NASA Astrophysics Data System (ADS)

Domae, Yukiyasu

2017-03-01

Bin-picking, re-grasping, pick-and-place, kitting, etc. There are many manipulation tasks in the fields of automation of factory, warehouse and so on. The main problem of the automation is that the target objects (items/parts) have various shapes, weights and surface materials. In my talk, I will show latest machine vision systems and algorithms against the problem.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

PubMed

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Effects of Colored Filters on Visual Function

DTIC Science & Technology

2008-05-01

normal vision, yellow filters have been reported to reduce glare and improve overall visual performance.4-9 The claims of improved vision in dyslexia ...use of tinted lenses and colored overlays for the treatment of dyslexia and other related reading and learning disorders. American Optometric

Learning discriminative features from RGB-D images for gender and ethnicity identification

NASA Astrophysics Data System (ADS)

Azzakhnini, Safaa; Ballihi, Lahoucine; Aboutajdine, Driss

2016-11-01

The development of sophisticated sensor technologies gave rise to an interesting variety of data. With the appearance of affordable devices, such as the Microsoft Kinect, depth-maps and three-dimensional data became easily accessible. This attracted many computer vision researchers seeking to exploit this information in classification and recognition tasks. In this work, the problem of face classification in the context of RGB images and depth information (RGB-D images) is addressed. The purpose of this paper is to study and compare some popular techniques for gender recognition and ethnicity classification to understand how much depth data can improve the quality of recognition. Furthermore, we investigate which combination of face descriptors, feature selection methods, and learning techniques is best suited to better exploit RGB-D images. The experimental results show that depth data improve the recognition accuracy for gender and ethnicity classification applications in many use cases.

Computer use and vision-related problems among university students in ajman, United arab emirate.

PubMed

Shantakumari, N; Eldeeb, R; Sreedharan, J; Gopal, K

2014-03-01

The extensive use of computers as medium of teaching and learning in universities necessitates introspection into the extent of computer related health disorders among student population. This study was undertaken to assess the pattern of computer usage and related visual problems, among University students in Ajman, United Arab Emirates. A total of 500 Students studying in Gulf Medical University, Ajman and Ajman University of Science and Technology were recruited into this study. Demographic characteristics, pattern of usage of computers and associated visual symptoms were recorded in a validated self-administered questionnaire. Chi-square test was used to determine the significance of the observed differences between the variables. The level of statistical significance was at P < 0.05. The crude odds ratio (OR) was determined using simple binary logistic regression and adjusted OR was calculated using the multiple logistic regression. The mean age of participants was 20.4 (3.2) years. The analysis of racial data reveals that 50% (236/471) students were from Middle East, 32% (151/471) from other parts of Asia, 11% (52/471) from Africa, 4% (19/471) from America and 3% (14/471) from Europe. The most common visual problems reported among computer users were headache - 53.3% (251/471), burning sensation in the eyes - 54.8% (258/471) and tired eyes - 48% (226/471). Female students were found to be at a higher risk. Nearly 72% of students reported frequent interruption of computer work. Headache caused interruption of work in 43.85% (110/168) of the students while tired eyes caused interruption of work in 43.5% (98/168) of the students. When the screen was viewed at distance more than 50 cm, the prevalence of headaches decreased by 38% (50-100 cm - OR: 0.62, 95% of the confidence interval [CI]: 0.42-0.92). Prevalence of tired eyes increased by 89% when screen filters were not used (OR: 1.894, 95% CI: 1.065-3.368). High prevalence of vision related problems was noted among university students. Sustained periods of close screen work without screen filters were found to be associated with occurrence of the symptoms and increased interruptions of work of the students. There is a need to increase the ergonomic awareness among students and corrective measures need to be implemented to reduce the impact of computer related vision problems.

Plan of Work 2010: Towards True Student-Centered Learning

ERIC Educational Resources Information Center

European Students' Union (NJ1), 2010

2010-01-01

The European Students' Union's (ESU's) vision regarding the Student Centered Learning concept stems from the fundamental belief that the learning process should have at its core learning objectives as they are prioritized by each individual students, also that each (potential) student should be empowered to define those objectives and progress…

Evidence for E-Learning Policy

ERIC Educational Resources Information Center

Pittard, Vanessa

2004-01-01

E-learning is becoming an increasingly mainstream feature of educational delivery. The launch of a national e-learning strategy in England signals the Government's commitment to maximising the potential benefits of investment in information and communications technology (ICT). The vision for e-learning set out in this strategy is ambitious. At…

Predicting problems in school performance from preschool health, developmental and behavioural assessments.

PubMed Central

Cadman, D; Walter, S D; Chambers, L W; Ferguson, R; Szatmari, P; Johnson, N; McNamee, J

1988-01-01

To determine the accuracy of various predictors of school problems, we conducted a 3-year prospective study of 1999 children who began school in the Niagara region of Ontario in 1980. During the year before school entry the parents gave a health, developmental and behavioural history during an interview with a community health nurse, and the children underwent vision and hearing screening tests and the Denver Developmental Screening Test (DDST). At the end of the 1980-81 school year the kindergarten teachers rated the children's learning problems. At the end of the 1982-83 school year the presence of school problems was ascertained, and the predictive accuracy of items from the preschool history and examination and of the kindergarten teachers' ratings was calculated. The health, developmental and behavioural history with or without the DDST was found to predict later school problems with acceptable accuracy. The kindergarten teachers' ratings gave slightly more accurate predictions. We conclude that in communities where prompt diagnostic evaluation and effective therapeutic or preventive help can be provided to children identified as being at high risk, health professionals may play a useful role in screening for future school problems. PMID:3383038

Historical Controversy as an Educational Tool: Evaluating Elements of a Teaching-Learning Sequence Conducted with the Text "Dialogue on the Ways that Vision Operates"

ERIC Educational Resources Information Center

de Hosson, Cecile; Kaminski, Wanda

2007-01-01

This paper describes the development, use, and analysis, of an educational tool inspired by the history of the optical mechanism of vision. We investigated 12-year-old students' reasoning about vision. Most of them explain it as the result of something coming either from the object or from the eye. Moreover, some of them think that light…

The Glenn A. Fry Award Lecture 2012: Plasticity of the visual system following central vision loss.

PubMed

Chung, Susana T L

2013-06-01

Following the onset of central vision loss, most patients develop an eccentric retinal location outside the affected macular region, the preferred retinal locus (PRL), as their new reference for visual tasks. The first goal of this article is to present behavioral evidence showing the presence of experience-dependent plasticity in people with central vision loss. The evidence includes the presence of oculomotor re-referencing of fixational saccades to the PRL; the characteristics of the shape of the crowding zone (spatial region within which the presence of other objects affects the recognition of a target) at the PRL are more "foveal-like" instead of resembling those of the normal periphery; and the change in the shape of the crowding zone at a para-PRL location that includes a component referenced to the PRL. These findings suggest that there is a shift in the referencing locus of the oculomotor and the sensory visual system from the fovea to the PRL for people with central vision loss, implying that the visual system for these individuals is still plastic and can be modified through experiences. The second goal of the article is to demonstrate the feasibility of applying perceptual learning, which capitalizes on the presence of plasticity, as a tool to improve functional vision for people with central vision loss. Our finding that visual function could improve with perceptual learning presents an exciting possibility for the development of an alternative rehabilitative strategy for people with central vision loss.

A Retrospective on the Vision for Progress in Community Health Partnerships: Research, Education, and Action.

PubMed

Eder, Milton Mickey; Holzer, Jessica; Calhoun, Karen; Strong, Larkin L

2017-01-01

The organizers founded Progress in Community Health Partnerships with a commitment to improving our understanding of community-based participatory research (CBPR) and its use in community-academic/institutional health partnerships. Following Rogers's Diffusion of Innovations, they reasoned that expanded adoption would occur through academic and community partner recognition of CBPR's relative advantage over previous approaches; its compatibility with the values, past experience and needs of potential adopters; its ease of understanding and use; its capacity for experimentation and refinement; and its production of observable results. We now assess the journal's progress toward realizing the vision, as well as issues and problems the organizers identified. We map the journal's content over its first decade onto the initial vision by examining the record of submissions and publications across the eight types of articles and the journal's record of rejections and publications. In remembering that Rogers's study of innovations requires both technical and social change, we discuss the difference between understanding how to do something and actually putting an innovation into action that becomes standard practice at both individual and systemic levels. We observe that the large number of Original Research and Works-in-Progress/Lessons Learned manuscripts, submitted and published, reflect traditional expectations for faculty research productivity. We suggest that sustainability, which rated of lower importance within the initial vision, has gained in importance among community and academic partners; however, it will gain added attention only with changed university expectations of researchers. We further suggest that the study of partnerships involved in researching and improving public health should be expanded beyond the current focus on CBPR.

Learning to see again: Biological constraints on cortical plasticity and the implications for sight restoration technologies

PubMed Central

Beyeler, Michael; Rokem, Ariel; Boynton, Geoffrey M.; Fine, Ione

2018-01-01

The “bionic eye” – so long a dream of the future – is finally becoming a reality with retinal prostheses available to patients in both the US and Europe. However, clinical experience with these implants has made it apparent that the vision provided by these devices differs substantially from normal sight. Consequently, the ability to learn to make use of this abnormal retinal input plays a critical role in whether or not some functional vision is successfully regained. The goal of the present review is to summarize the vast basic science literature on developmental and adult cortical plasticity with an emphasis on how this literature might relate to the field of prosthetic vision. We begin with describing the distortion and information loss likely to be experienced by visual prosthesis users. We then define cortical plasticity and perceptual learning, and describe what is known, and what is unknown, about visual plasticity across the hierarchy of brain regions involved in visual processing, and across different stages of life. We close by discussing what is known about brain plasticity in sight restoration patients and discuss biological mechanisms that might eventually be harnessed to improve visual learning in these patients. PMID:28612755

Vision and Oral Health Needs of Individuals with Intellectual Disability

ERIC Educational Resources Information Center

Owens, Pamela L.; Kerker, Bonnie D.; Zigler, Edward; Horwitz, Sarah M.

2006-01-01

Over the past 20 years, there has been an increased emphasis on health promotion, including prevention activities related to vision and oral health, for the general population, but not for individuals with intellectual disability (ID). This review explores what is known about the prevalence of vision problems and oral health conditions among…

Benefit from NASA

NASA Image and Video Library

1985-01-01

The NASA imaging processing technology, an advanced computer technique to enhance images sent to Earth in digital form by distant spacecraft, helped develop a new vision screening process. The Ocular Vision Screening system, an important step in preventing vision impairment, is a portable device designed especially to detect eye problems in children through the analysis of retinal reflexes.

Access to Microsoft Windows 95 for Persons with Low Vision: An Overview.

ERIC Educational Resources Information Center

Shragai, Y.

1995-01-01

This article examines Windows 95, pointing out differences and improvements from Windows 3.1 for persons with low vision. Windows 95 is seen as providing substantially greater accessibility than Windows 3.1, though the graphical user interface may still pose serious problems for some users with low vision. (DB)

Robust Spatial Autoregressive Modeling for Hardwood Log Inspection

Treesearch

Dongping Zhu; A.A. Beex

1994-01-01

We explore the application of a stochastic texture modeling method toward a machine vision system for log inspection in the forest products industry. This machine vision system uses computerized tomography (CT) imaging to locate and identify internal defects in hardwood logs. The application of CT to such industrial vision problems requires efficient and robust image...

Envisioning a Literacy Partnership: The University of Nebraska at Omaha's Criss Library and Girls Inc.

ERIC Educational Resources Information Center

Neujahr, Joyce; Hillyer, Nora; Cast-Brede, Melissa

2013-01-01

The history of academic library involvement in service learning is varied. This paper provides an overview of service learning and the literature on academic libraries' participation in service-learning activities. A vision of service-learning participation is described, as well as the implementation of service-learning activities in two library…

Assessing Student Behaviors and Motivation for Actively Learning Biology

ERIC Educational Resources Information Center

Moore, Michael Edward

2017-01-01

Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is…

Vision rehabilitation in the case of blindness.

PubMed

Veraart, Claude; Duret, Florence; Brelén, Marten; Oozeer, Medhy; Delbeke, Jean

2004-09-01

This article examines the various vision rehabilitation procedures that are available for early and late blindness. Depending on the pathology involved, several vision rehabilitation procedures exist, or are in development. Visual aids are available for low vision individuals, as are sensory aids for blind persons. Most noninvasive sensory substitution prostheses as well as implanted visual prostheses in development are reviewed. Issues dealing with vision rehabilitation are also discussed, such as problems of biocompatibility, electrical safety, psychosocial aspects, and ethics. Basic studies devoted to vision rehabilitation such as simulation in mathematical models and simulation of artificial vision are also presented. Finally, the importance of accurate rehabilitation assessment is addressed, and tentative market figures are given.

Artificial intelligence, expert systems, computer vision, and natural language processing

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

The Impact of Providing Vision Screening and Free Eyeglasses on Academic Outcomes: Evidence from a Randomized Trial in Title I Elementary Schools in Florida

ERIC Educational Resources Information Center

Glewwe, Paul; West, Kristine L.; Lee, Jongwook

2018-01-01

More than 20 percent of all school-aged children in the United States have vision problems, and low-income and minority children are disproportionately likely to have unmet vision care needs. Vision screening is common in U.S. schools, but it remains an open question whether screening alone is sufficient to improve student outcomes. We implemented…

Advanced helmet vision system (AHVS) integrated night vision helmet mounted display (HMD)

NASA Astrophysics Data System (ADS)

Ashcraft, Todd W.; Atac, Robert

2012-06-01

Gentex Corporation, under contract to Naval Air Systems Command (AIR 4.0T), designed the Advanced Helmet Vision System to provide aircrew with 24-hour, visor-projected binocular night vision and HMD capability. AHVS integrates numerous key technologies, including high brightness Light Emitting Diode (LED)-based digital light engines, advanced lightweight optical materials and manufacturing processes, and innovations in graphics processing software. This paper reviews the current status of miniaturization and integration with the latest two-part Gentex modular helmet, highlights the lessons learned from previous AHVS phases, and discusses plans for qualification and flight testing.

The Medawar Lecture 2001 Knowledge for vision: vision for knowledge

PubMed Central

Gregory, Richard L

2005-01-01

An evolutionary development of perception is suggested—from passive reception to active perception to explicit conception—earlier stages being largely retained and incorporated in later species. A key is innate and then individually learned knowledge, giving meaning to sensory signals. Inappropriate or misapplied knowledge produces rich cognitive phenomena of illusions, revealing normally hidden processes of vision, tentatively classified here in a ‘peeriodic table’. Phenomena of physiology are distinguished from phenomena of general rules and specific object knowledge. It is concluded that vision uses implicit knowledge, and provides knowledge for intelligent behaviour and for explicit conceptual understanding including science. PMID:16147519

Convolutional neural network guided blue crab knuckle detection for autonomous crab meat picking machine

NASA Astrophysics Data System (ADS)

Wang, Dongyi; Vinson, Robert; Holmes, Maxwell; Seibel, Gary; Tao, Yang

2018-04-01

The Atlantic blue crab is among the highest-valued seafood found in the American Eastern Seaboard. Currently, the crab processing industry is highly dependent on manual labor. However, there is great potential for vision-guided intelligent machines to automate the meat picking process. Studies show that the back-fin knuckles are robust features containing information about a crab's size, orientation, and the position of the crab's meat compartments. Our studies also make it clear that detecting the knuckles reliably in images is challenging due to the knuckle's small size, anomalous shape, and similarity to joints in the legs and claws. An accurate and reliable computer vision algorithm was proposed to detect the crab's back-fin knuckles in digital images. Convolutional neural networks (CNNs) can localize rough knuckle positions with 97.67% accuracy, transforming a global detection problem into a local detection problem. Compared to the rough localization based on human experience or other machine learning classification methods, the CNN shows the best localization results. In the rough knuckle position, a k-means clustering method is able to further extract the exact knuckle positions based on the back-fin knuckle color features. The exact knuckle position can help us to generate a crab cutline in XY plane using a template matching method. This is a pioneering research project in crab image analysis and offers advanced machine intelligence for automated crab processing.

Making time for learning-oriented leadership in multidisciplinary hospital management groups.

PubMed

Singer, Sara J; Hayes, Jennifer E; Gray, Garry C; Kiang, Mathew V

2015-01-01

Although the clinical requirements of health care delivery imply the need for interdisciplinary management teams to work together to promote frontline learning, such interdisciplinary, learning-oriented leadership is atypical. We designed this study to identify behaviors enabling groups of diverse managers to perform as learning-oriented leadership teams on behalf of quality and safety. We randomly selected 12 of 24 intact groups of hospital managers from one hospital to participate in a Safety Leadership Team Training program. We collected primary data from March 2008 to February 2010 including pre- and post-staff surveys, multiple interviews, observations, and archival data from management groups. We examined the level and trend in frontline perceptions of managers' learning-oriented leadership following the intervention and ability of management groups to achieve objectives on targeted improvement projects. Among the 12 intervention groups, we identified higher- and lower-performing intervention groups and behaviors that enabled higher performers to work together more successfully. Management groups that achieved more of their performance goals and whose staff perceived more and greater improvement in their learning-oriented leadership after participation in Safety Leadership Team Training invested in structures that created learning capacity and conscientiously practiced prescribed learning-oriented management and problem-solving behaviors. They made the time to do these things because they envisioned the benefits of learning, valued the opportunity to learn, and maintained an environment of mutual respect and psychological safety within their group. Learning in management groups requires vision of what learning can accomplish; will to explore, practice, and build learning capacity; and mutual respect that sustains a learning environment.

Refractive Errors

MedlinePlus

... and lens of your eye helps you focus. Refractive errors are vision problems that happen when the shape ... cornea, or aging of the lens. Four common refractive errors are Myopia, or nearsightedness - clear vision close up ...

Inspiring a Life Full of Learning

ERIC Educational Resources Information Center

Ludlam, John

2012-01-01

The Secrets and Words films had everything one would expect from a BBC drama--great writing, acting and directing allied with high production values. But the dramas were also powerful learning tools, co-commissioned by BBC Learning and aimed at inspiring people who have difficulty with reading and writing to seek help. The BBC's learning vision is…

Learning in the Digital Age: Control or Connection?

ERIC Educational Resources Information Center

Van Galen, Jane

2013-01-01

In October 2011, 200 state school officers and legislators gathered at a hotel in San Francisco to learn how to "revolutionize" learning by "personalizing" instruction. The occasion was former Florida Gov. Jeb Bush's second annual National Summit on Education Reform. The topic was digital learning. The vision of digitally managed curriculum and…

Higher Education Civic Learning and Engagement: A Massachusetts Case Study. Promising Practices

ERIC Educational Resources Information Center

Brennan, Jan

2017-01-01

This Promising Practices report explores the civic learning and engagement efforts of Massachusetts' public higher education system in five areas: vision of Preparing Citizens as a core educational commitment, development of a state higher education Policy on Civic Learning, creation of civic engagement and service-learning course designations,…

Exploring Potentialities for Cosmopolitan Learning in Swedish Teacher Education

ERIC Educational Resources Information Center

Scheja, Max

2015-01-01

This study aimed to explore student teachers' experiences of learning in teacher education, with a focus on how students describe their ways of thinking about their own learning in relation to their future professional role as teachers and how these descriptions relate to emerging cosmopolitan visions for student learning in teacher education.…

Creating Strategic Visions

DTIC Science & Technology

1990-10-15

3010 o, AuTOVON 242-3010. - =n~m~m i ma ll lil~ m mm m i mii FOREWORD This futures study presents an analysis and discussion of a program used at the U.S...Operations Research Society, and The Planning Forum . iv CREATING STRATEGIC VISIONS 1 Introduction. The United States Army War College (USAWC) prepares its...consideration and time must be given to a program that attempts to help these potential leaders learn how to create strategic visions. In this paper

Smart in Everything Except School.

ERIC Educational Resources Information Center

Getman, G. N.

This book focuses on the prevention of academic failure through focus on developmental processes (especially development of essential visual skills) within the individual learner. A distinction is made between sight and vision with vision involving the entire person and his/her learning experiences The first chapter examines "The Dynamics of the…

The Noticing of Physical Education Teachers: A Comparison of Groups with Different Expertise

ERIC Educational Resources Information Center

Reuker, Sabine

2017-01-01

Background: Teachers' important diagnostic abilities include noticing and interpreting students' behaviors and learning processes. By focusing on noticing, I refer to the theoretical framework of professional vision. Professional vision includes the ability to notice what is occurring in complex classroom situations (selective attention) and the…

Seizing Opportunity: "Opportunity as Transformation"

ERIC Educational Resources Information Center

Williams, Michael; Muller, Esther

2012-01-01

Opportunity creates conditions for achievement. We learn daily of the success of others that resulted from conditions they created through opportunity. Often these conditions of opportunity are the product of a compelling vision of a future steeped in possibility and rich in reward. These visions, however, must be operationalized in order to be…

Perceptions Matter: Administrators' Vision of Instruction for Students with Severe Disabilities

ERIC Educational Resources Information Center

Roberts, Carly A.; Ruppar, Andrea L.; Olson, Amy J.

2018-01-01

School administrators play an important role in shaping teaching and learning. However, very little is known regarding how school administrators perceive instruction for students with severe disabilities and how those perceptions shape expectations and visions for instruction. Semistructured interviews were used to interview 12 administrators…

Living Mathematx: Towards a Vision for the Future

ERIC Educational Resources Information Center

Gutiérrez, Rochelle

2017-01-01

This paper offers specific implications for teaching and learning and brings into conversation ideas from ethnomathematics (including Western mathematics), postcolonial theory, aesthetics, biology, and Indigenous knowledge in order to propose a new vision for practicing mathematics, what I call mathematx. I build upon the work of sustainability in…

Recent CESAR (Center for Engineering Systems Advanced Research) research activities in sensor based reasoning for autonomous machines

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

Pin, F.G.; de Saussure, G.; Spelt, P.F.

1988-01-01

This paper describes recent research activities at the Center for Engineering Systems Advanced Research (CESAR) in the area of sensor based reasoning, with emphasis being given to their application and implementation on our HERMIES-IIB autonomous mobile vehicle. These activities, including navigation and exploration in a-priori unknown and dynamic environments, goal recognition, vision-guided manipulation and sensor-driven machine learning, are discussed within the framework of a scenario in which an autonomous robot is asked to navigate through an unknown dynamic environment, explore, find and dock at the panel, read and understand the status of the panel's meters and dials, learn the functioningmore » of a process control panel, and successfully manipulate the control devices of the panel to solve a maintenance emergency problems. A demonstration of the successful implementation of the algorithms on our HERMIES-IIB autonomous robot for resolution of this scenario is presented. Conclusions are drawn concerning the applicability of the methodologies to more general classes of problems and implications for future work on sensor-driven reasoning for autonomous robots are discussed. 8 refs., 3 figs.« less

Face sketch recognition based on edge enhancement via deep learning

NASA Astrophysics Data System (ADS)

Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

Sensory Changes with Age: Implications for Learning and Research.

ERIC Educational Resources Information Center

Carter, Phillip Dean

1982-01-01

Hearing loss, vision loss, and other physical impairments which are natural parts of the aging process can be compensated for in planning learning for older adults. Such impairments should not be taken as restrictions on the older adult's ability or desire to learn. (SK)

Vision-based semi-autonomous outdoor robot system to reduce soldier workload

NASA Astrophysics Data System (ADS)

Richardson, Al; Rodgers, Michael H.

2001-09-01

Sensors and computational capability have not reached the point to enable small robots to navigate autonomously in unconstrained outdoor environments at tactically useful speeds. This problem is greatly reduced, however, if a soldier can lead the robot through terrain that he knows it can traverse. An application of this concept is a small pack-mule robot that follows a foot soldier over outdoor terrain. The solder would be responsible to avoid situations beyond the robot's limitations when encountered. Having learned the route, the robot could autonomously retrace the path carrying supplies and munitions. This would greatly reduce the soldier's workload under normal conditions. This paper presents a description of a developmental robot sensor system using low-cost commercial 3D vision and inertial sensors to address this application. The robot moves at fast walking speed and requires only short-range perception to accomplish its task. 3D-feature information is recorded on a composite route map that the robot uses to negotiate its local environment and retrace the path taught by the soldier leader.

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

PubMed

Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

2017-01-01

Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

Building a patient-centered hospital web site: best practices in china.

PubMed

Huang, Edgar

2015-01-01

In this case study, based on six criteria, four Chinese hospitals were chosen from a national sample to showcase, through content analysis and in-depth interviews, the best practices of serving patients online. The extensive findings have addressed the following three questions: what these hospitals have in common in their Web development, what problems and challenges they are facing, and how they have excelled in serving their patients online. The study concludes that, like larger hospitals, smaller hospitals can also excel in creating an outstanding Web site to serve their patients so long as they truly care about their patients, have a clear vision and strong expertise in IT development. The study also concludes that Chinese private hospitals can learn from these state-owned hospitals in establishing a good reputation through professional and responsible interaction with patients. The four hospitals studied may shed light on the Web development in many other Chinese hospitals that are going through the same healthcare new media adoption. The findings from this study can also help Chinese hospitals form their visions in serving patients online.

Participatory research towards co-management: lessons from artisanal fisheries in coastal Uruguay.

PubMed

Trimble, Micaela; Berkes, Fikret

2013-10-15

Participatory research has become increasingly common in natural resources management. Even though participatory research is considered a strategy to facilitate co-management, there is little empirical evidence supporting this. The objective of the present paper is to analyze the contributions of participatory research to help encourage the emergence of co-management, based on a case study in Piriápolis artisanal fishery in coastal Uruguay (where management has been top-down). We argue that participatory research involving artisanal fishers, government, and other stakeholders (university scientists and NGOs) can be a key stimulus towards co-management. We build this argument by considering "seven faces" by which co-management can be analyzed: (1) as power sharing; (2) as institution building; (3) as trust building; (4) as process; (5) as learning and knowledge co-production; (6) as problem solving; and (7) as governance. Our findings show that participatory research had an impact on these various faces: (1) power was shared when making research decisions; (2) a multi-stakeholder group (POPA), with a common vision and goals, was created; (3) trust among participants increased; (4) the process of group formation was valued by participants; (5) stakeholders learned skills for participation; (6) two problem-solving exercises were conducted; and (7) a diversity of stakeholders of the initial problem identified by fishers (sea lions' impact on long-line fishery) participated in the process. The case shows that participatory research functions as a platform which enhances learning and knowledge co-production among stakeholders, paving the way towards future co-management. Copyright © 2013 Elsevier Ltd. All rights reserved.

Stability Training for Convolutional Neural Nets in LArTPC

NASA Astrophysics Data System (ADS)

Lindsay, Matt; Wongjirad, Taritree

2017-01-01

Convolutional Neural Nets (CNNs) are the state of the art for many problems in computer vision and are a promising method for classifying interactions in Liquid Argon Time Projection Chambers (LArTPCs) used in neutrino oscillation experiments. Despite the good performance of CNN's, they are not without drawbacks, chief among them is vulnerability to noise and small perturbations to the input. One solution to this problem is a modification to the learning process called Stability Training developed by Zheng et al. We verify existing work and demonstrate volatility caused by simple Gaussian noise and also that the volatility can be nearly eliminated with Stability Training. We then go further and show that a traditional CNN is also vulnerable to realistic experimental noise and that a stability trained CNN remains accurate despite noise. This further adds to the optimism for CNNs for work in LArTPCs and other applications.

Novel Descattering Approach for Stereo Vision in Dense Suspended Scatterer Environments

PubMed Central

Nguyen, Chanh D. Tr.; Park, Jihyuk; Cho, Kyeong-Yong; Kim, Kyung-Soo; Kim, Soohyun

2017-01-01

In this paper, we propose a model-based scattering removal method for stereo vision for robot manipulation in indoor scattering media where the commonly used ranging sensors are unable to work. Stereo vision is an inherently ill-posed and challenging problem. It is even more difficult in the case of images of dense fog or dense steam scenes illuminated by active light sources. Images taken in such environments suffer attenuation of object radiance and scattering of the active light sources. To solve this problem, we first derive the imaging model for images taken in a dense scattering medium with a single active illumination close to the cameras. Based on this physical model, the non-uniform backscattering signal is efficiently removed. The descattered images are then utilized as the input images of stereo vision. The performance of the method is evaluated based on the quality of the depth map from stereo vision. We also demonstrate the effectiveness of the proposed method by carrying out the real robot manipulation task. PMID:28629139

Enhanced computer vision with Microsoft Kinect sensor: a review.

PubMed

Han, Jungong; Shao, Ling; Xu, Dong; Shotton, Jamie

2013-10-01

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.

Social capital and knowledge sharing: effects on patient safety.

PubMed

Chang, Chia-Wen; Huang, Heng-Chiang; Chiang, Chi-Yun; Hsu, Chiu-Ping; Chang, Chia-Chen

2012-08-01

This article is a report on a study that empirically examines the influence of social capital on knowledge sharing and the impact of knowledge sharing on patient safety. Knowledge sharing is linked to many desirable managerial outcomes, including learning and problem-solving, which are essential for patient safety. Rather than studying the tangible effects of rewards, this study examines whether social capital (including social interaction, trust and shared vision) directly supports individual knowledge sharing in an organization. This cross-sectional study analysed data collected through a questionnaire survey of nurses from a major medical centre in northern Taiwan. The data were collected over a 9-month period from 2008 to 2009. The data analysis was conducted using the Partial Least Squares Graph v3.0 program to evaluate the measurement properties and the structural relationships specified in the research model. Based on a large-scale survey, empirical results indicate that Registered Nurses' perceptions of trust and shared vision have statistically significant and direct effects on knowledge sharing. In addition, knowledge sharing is significantly and positively associated with patient safety. The findings suggest that hospital administrators should foster group trust and initiate a common vision among Registered Nurses. In addition, administrators and chief knowledge officers of hospitals should encourage positive intentions towards knowledge sharing. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.

Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm.

PubMed

Ren, Fulong; Cao, Peng; Li, Wei; Zhao, Dazhe; Zaiane, Osmar

2017-01-01

Diabetic retinopathy (DR) is a progressive disease, and its detection at an early stage is crucial for saving a patient's vision. An automated screening system for DR can help in reduce the chances of complete blindness due to DR along with lowering the work load on ophthalmologists. Among the earliest signs of DR are microaneurysms (MAs). However, current schemes for MA detection appear to report many false positives because detection algorithms have high sensitivity. Inevitably some non-MAs structures are labeled as MAs in the initial MAs identification step. This is a typical "class imbalance problem". Class imbalanced data has detrimental effects on the performance of conventional classifiers. In this work, we propose an ensemble based adaptive over-sampling algorithm for overcoming the class imbalance problem in the false positive reduction, and we use Boosting, Bagging, Random subspace as the ensemble framework to improve microaneurysm detection. The ensemble based over-sampling methods we proposed combine the strength of adaptive over-sampling and ensemble. The objective of the amalgamation of ensemble and adaptive over-sampling is to reduce the induction biases introduced from imbalanced data and to enhance the generalization classification performance of extreme learning machines (ELM). Experimental results show that our ASOBoost method has higher area under the ROC curve (AUC) and G-mean values than many existing class imbalance learning methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

A model of traffic signs recognition with convolutional neural network

NASA Astrophysics Data System (ADS)

Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

2016-10-01

In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.

3-D Signal Processing in a Computer Vision System

Treesearch

Dongping Zhu; Richard W. Conners; Philip A. Araman

1991-01-01

This paper discusses the problem of 3-dimensional image filtering in a computer vision system that would locate and identify internal structural failure. In particular, a 2-dimensional adaptive filter proposed by Unser has been extended to 3-dimension. In conjunction with segmentation and labeling, the new filter has been used in the computer vision system to...

The Eye and Learning Disabilities

ERIC Educational Resources Information Center

Sight-Saving Review, 1971

1971-01-01

A joint organizational statement on vision and therapy for learning disabilities and dyslexia is presented by the American Academy of Pediatrics, the American Academy of Ophthalmology and Otolaryngology, and the American Association of Ophthalmology. (CB)

Learning context-sensitive shape similarity by graph transduction.

PubMed

Bai, Xiang; Yang, Xingwei; Latecki, Longin Jan; Liu, Wenyu; Tu, Zhuowen

2010-05-01

Shape similarity and shape retrieval are very important topics in computer vision. The recent progress in this domain has been mostly driven by designing smart shape descriptors for providing better similarity measure between pairs of shapes. In this paper, we provide a new perspective to this problem by considering the existing shapes as a group, and study their similarity measures to the query shape in a graph structure. Our method is general and can be built on top of any existing shape similarity measure. For a given similarity measure, a new similarity is learned through graph transduction. The new similarity is learned iteratively so that the neighbors of a given shape influence its final similarity to the query. The basic idea here is related to PageRank ranking, which forms a foundation of Google Web search. The presented experimental results demonstrate that the proposed approach yields significant improvements over the state-of-art shape matching algorithms. We obtained a retrieval rate of 91.61 percent on the MPEG-7 data set, which is the highest ever reported in the literature. Moreover, the learned similarity by the proposed method also achieves promising improvements on both shape classification and shape clustering.

Exploration of the functions of health impact assessment in real-world policymaking in the field of social health inequality: towards a conception of conceptual learning.

PubMed

Feyaerts, Gille; Deguerry, Murielle; Deboosere, Patrick; De Spiegelaere, Myriam

2017-06-01

With the implementation of health impact assessment (HIA)'s conceptual model into real-world policymaking, a number of fundamental issues arise concerning its decision-support function. Rooted in a rational vision of the decision-making process, focus regarding both conceptualisation and evaluation has been mainly on the function of instrumental policy-learning. However, in the field of social health inequalities, this function is strongly limited by the intrinsic 'wickedness' of the policy issue. Focusing almost exclusively on this instrumental function, the real influence HIA can have on policymaking in the longer term is underestimated and remains largely unexploited. Drawing insights from theoretical models developed in the field of political science and sociology, we explore the different decision-support functions HIA can fulfill and identify conceptual learning as potentially the most important. Accordingly, dominant focus on the technical engineering function, where knowledge is provided in order to 'rationalise' the policy process and to tackle 'tame' problems, should be complemented with an analysis of the conditions for conceptual learning, where knowledge introduces new information and perspectives and, as such, contributes in the longer term to a paradigm change.

Comparison on testability of visual acuity, stereo acuity and colour vision tests between children with learning disabilities and children without learning disabilities in government primary schools.

PubMed

Abu Bakar, Nurul Farhana; Chen, Ai-Hong

2014-02-01

Children with learning disabilities might have difficulties to communicate effectively and give reliable responses as required in various visual function testing procedures. The purpose of this study was to compare the testability of visual acuity using the modified Early Treatment Diabetic Retinopathy Study (ETDRS) and Cambridge Crowding Cards, stereo acuity using Lang Stereo test II and Butterfly stereo tests and colour perception using Colour Vision Test Made Easy (CVTME) and Ishihara's Test for Colour Deficiency (Ishihara Test) between children in mainstream classes and children with learning disabilities in special education classes in government primary schools. A total of 100 primary school children (50 children from mainstream classes and 50 children from special education classes) matched in age were recruited in this cross-sectional comparative study. The testability was determined by the percentage of children who were able to give reliable respond as required by the respective tests. 'Unable to test' was defined as inappropriate response or uncooperative despite best efforts of the screener. The testability of the modified ETDRS, Butterfly stereo test and Ishihara test for respective visual function tests were found lower among children in special education classes ( P < 0.001) but not in Cambridge Crowding Cards, Lang Stereo test II and CVTME. Non verbal or "matching" approaches were found to be more superior in testing visual functions in children with learning disabilities. Modifications of vision testing procedures are essential for children with learning disabilities.

A multidisciplinary approach to solving computer related vision problems.

PubMed

Long, Jennifer; Helland, Magne

2012-09-01

This paper proposes a multidisciplinary approach to solving computer related vision issues by including optometry as a part of the problem-solving team. Computer workstation design is increasing in complexity. There are at least ten different professions who contribute to workstation design or who provide advice to improve worker comfort, safety and efficiency. Optometrists have a role identifying and solving computer-related vision issues and in prescribing appropriate optical devices. However, it is possible that advice given by optometrists to improve visual comfort may conflict with other requirements and demands within the workplace. A multidisciplinary approach has been advocated for solving computer related vision issues. There are opportunities for optometrists to collaborate with ergonomists, who coordinate information from physical, cognitive and organisational disciplines to enact holistic solutions to problems. This paper proposes a model of collaboration and examples of successful partnerships at a number of professional levels including individual relationships between optometrists and ergonomists when they have mutual clients/patients, in undergraduate and postgraduate education and in research. There is also scope for dialogue between optometry and ergonomics professional associations. A multidisciplinary approach offers the opportunity to solve vision related computer issues in a cohesive, rather than fragmented way. Further exploration is required to understand the barriers to these professional relationships. © 2012 The College of Optometrists.

The effect of normal aging and age-related macular degeneration on perceptual learning.

PubMed

Astle, Andrew T; Blighe, Alan J; Webb, Ben S; McGraw, Paul V

2015-01-01

We investigated whether perceptual learning could be used to improve peripheral word identification speed. The relationship between the magnitude of learning and age was established in normal participants to determine whether perceptual learning effects are age invariant. We then investigated whether training could lead to improvements in patients with age-related macular degeneration (AMD). Twenty-eight participants with normal vision and five participants with AMD trained on a word identification task. They were required to identify three-letter words, presented 10° from fixation. To standardize crowding across each of the letters that made up the word, words were flanked laterally by randomly chosen letters. Word identification performance was measured psychophysically using a staircase procedure. Significant improvements in peripheral word identification speed were demonstrated following training (71% ± 18%). Initial task performance was correlated with age, with older participants having poorer performance. However, older adults learned more rapidly such that, following training, they reached the same level of performance as their younger counterparts. As a function of number of trials completed, patients with AMD learned at an equivalent rate as age-matched participants with normal vision. Improvements in word identification speed were maintained at least 6 months after training. We have demonstrated that temporal aspects of word recognition can be improved in peripheral vision with training across a range of ages and these learned improvements are relatively enduring. However, training targeted at other bottlenecks to peripheral reading ability, such as visual crowding, may need to be incorporated to optimize this approach.

The effect of normal aging and age-related macular degeneration on perceptual learning

PubMed Central

Astle, Andrew T.; Blighe, Alan J.; Webb, Ben S.; McGraw, Paul V.

2015-01-01

We investigated whether perceptual learning could be used to improve peripheral word identification speed. The relationship between the magnitude of learning and age was established in normal participants to determine whether perceptual learning effects are age invariant. We then investigated whether training could lead to improvements in patients with age-related macular degeneration (AMD). Twenty-eight participants with normal vision and five participants with AMD trained on a word identification task. They were required to identify three-letter words, presented 10° from fixation. To standardize crowding across each of the letters that made up the word, words were flanked laterally by randomly chosen letters. Word identification performance was measured psychophysically using a staircase procedure. Significant improvements in peripheral word identification speed were demonstrated following training (71% ± 18%). Initial task performance was correlated with age, with older participants having poorer performance. However, older adults learned more rapidly such that, following training, they reached the same level of performance as their younger counterparts. As a function of number of trials completed, patients with AMD learned at an equivalent rate as age-matched participants with normal vision. Improvements in word identification speed were maintained at least 6 months after training. We have demonstrated that temporal aspects of word recognition can be improved in peripheral vision with training across a range of ages and these learned improvements are relatively enduring. However, training targeted at other bottlenecks to peripheral reading ability, such as visual crowding, may need to be incorporated to optimize this approach. PMID:26605694

The reliability of a VISION COACH task as a measure of psychomotor skills.

PubMed

Xi, Yubin; Rosopa, Patrick J; Mossey, Mary; Crisler, Matthew C; Drouin, Nathalie; Kopera, Kevin; Brooks, Johnell O

2014-10-01

The VISION COACH™ interactive light board is designed to test and enhance participants' psychomotor skills. The primary goal of this study was to examine the test-retest reliability of the Full Field 120 VISION COACH task. One hundred eleven male and 131 female adult participants completed six trials where they responded to 120 randomly distributed lights displayed on the VISION COACH interactive light board. The mean time required for a participant to complete a trial was 101 seconds. Intraclass correlation coefficients, ranging from 0.962 to 0.987 suggest the VISION COACH Full Field 120 task was a reliable task. Cohen's d's of adjacent pairs of trials suggest learning effects did not negatively affect reliability after the third trial.

Computer Vision and Machine Learning for Autonomous Characterization of AM Powder Feedstocks

NASA Astrophysics Data System (ADS)

DeCost, Brian L.; Jain, Harshvardhan; Rollett, Anthony D.; Holm, Elizabeth A.

2017-03-01

By applying computer vision and machine learning methods, we develop a system to characterize powder feedstock materials for metal additive manufacturing (AM). Feature detection and description algorithms are applied to create a microstructural scale image representation that can be used to cluster, compare, and analyze powder micrographs. When applied to eight commercial feedstock powders, the system classifies powder images into the correct material systems with greater than 95% accuracy. The system also identifies both representative and atypical powder images. These results suggest the possibility of measuring variations in powders as a function of processing history, relating microstructural features of powders to properties relevant to their performance in AM processes, and defining objective material standards based on visual images. A significant advantage of the computer vision approach is that it is autonomous, objective, and repeatable.

An inquiry-based approach to the Franck-Hertz experiment

NASA Astrophysics Data System (ADS)

Persano Adorno, Dominique; Pizzolato, Nicola

2016-05-01

The practice of scientists and engineers is today exerted within interdisciplinary contexts, placed at the intersections of different research fields, including nanoscale science. The development of the required competences is based on an effective science and engineering instruction, which should be able to drive the students towards a deeper understanding of quantum mechanics fundamental concepts and, at the same time, strengthen their reasoning skills and transversal abilities. In this study we report the results of an inquiry-driven learning path experienced by a sample of 12 electronic engineering undergraduates engaged to perform the Franck-Hertz experiment. Before being involved in this experimental activity, the students received a traditional lecture-based instruction on the fundamental concepts of quantum mechanics, but their answers to an open-ended questionnaire, administered at the beginning of the inquiry activity, demonstrated that the acquired knowledge was characterized by a strictly theoretical vision of quantum science, basically in terms of an artificial mathematical framework having very poor connections with the real world. The Franck Hertz experiment was introduced to the students by starting from the problem of finding an experimental confirmation of the Bohr's postulates asserting that atoms can absorb energy only in quantum portions. The whole activity has been videotaped and this allowed us to deeply analyse the student perception's change about the main concepts of quantum mechanics. We have found that the active participation to this learning experience favored the building of cognitive links among student theoretical perceptions of quantum mechanics and their vision of quantum phenomena, within an everyday context of knowledge. Furthermore, our findings confirm the benefits of integrating traditional lecture-based instruction on quantum mechanics with learning experiences driven by inquiry-based teaching strategies.

The Future of Informal Learning

ERIC Educational Resources Information Center

Taylor, Richard

2008-01-01

"Informal Adult Learning: Shaping the Way Ahead," the Government's consultation on the future of informal adult learning in England, was launched by Secretary of State for Innovation, Universities and Skills, John Denham, on January 15, 2007. The consultation invites respondents to help shape "a new vision for informal adult…

Impacts of Learning Orientation on Product Innovation Performance

ERIC Educational Resources Information Center

Calisir, Fethi; Gumussoy, Cigdem Altin; Guzelsoy, Ezgi

2013-01-01

Purpose: The present study aims to examine the effect of learning orientation (commitment to learning, shared vision, open-mindedness) on the product innovation performance (product innovation efficacy and efficiency) of companies in Turkey. Design/methodology/approach: A structural equation-modeling approach was applied to identify the variables…

Family Caregiver Social Problem-Solving Abilities and Adjustment to Caring for a Relative with Vision Loss

PubMed Central

Bambara, Jennifer K.; Owsley, Cynthia; Wadley, Virginia; Martin, Roy; Porter, Chebon; Dreer, Laura E.

2009-01-01

Purpose To examine the prevalence of persons at risk for depression among family caregivers of visually impaired persons and the extent to which social problem-solving abilities are associated with caregiver depressive symptomatology and life satisfaction. Methods Family caregivers were defined as adults who accompanied their adult relative to an appointment at a low-vision rehabilitation clinic and self-identified themselves as the primary family caregiver responsible for providing some form of assistance for their relative due to vision impairment. Demographic variables, depressive symptoms, life satisfaction, caregiver burden, and social problem-solving abilities were assessed in caregivers. The patient’s visual acuity and depressive symptoms and their relationship to the caregiver’s depressive symptoms and life satisfaction were also examined. Results Ninety-six family caregivers were enrolled. Of those, 35.4% were identified as at risk for depression. Among caregivers, dysfunctional or ineffective social problem-solving abilities were significantly associated with greater depressive symptomatology and decreased life satisfaction after adjustment for caregiver burden and demographic and medical variables for both the caregiver and the visually impaired patient. Problem orientation or motivation to solving problems was also significantly associated with caregiver depression and satisfaction with life. Conclusions A substantial number of caregivers of visually impaired adults experience psychosocial distress, particularly among those who possess poor social problem-solving abilities. These results underscore the need for routine screening and treatment of emotional distress among individuals caring for relatives with vision impairments. Future research should examine the extent to which psychosocial interventions targeting caregiver social problem-solving skills may be useful not only in improving caregiver quality of life but also in subsequently enhancing rehabilitation outcomes for the visually impaired care recipient. PMID:19060279

Family caregiver social problem-solving abilities and adjustment to caring for a relative with vision loss.

PubMed

Bambara, Jennifer K; Owsley, Cynthia; Wadley, Virginia; Martin, Roy; Porter, Chebon; Dreer, Laura E

2009-04-01

To examine the prevalence of persons at risk for depression among family caregivers of visually impaired persons and the extent to which social problem-solving abilities are associated with caregiver depressive symptomatology and life satisfaction. Family caregivers were defined as adults who accompanied their adult relative to an appointment at a low-vision rehabilitation clinic and self-identified themselves as the primary family caregiver responsible for providing some form of assistance for their relative due to vision impairment. Demographic variables, depressive symptoms, life satisfaction, caregiver burden, and social problem-solving abilities were assessed in caregivers. The patient's visual acuity and depressive symptoms and their relationship to the caregiver's depressive symptoms and life satisfaction were also examined. Ninety-six family caregivers were enrolled. Of those, 35.4% were identified as at risk for depression. Among caregivers, dysfunctional or ineffective social problem-solving abilities were significantly associated with greater depressive symptomatology and decreased life satisfaction after adjustment for caregiver burden and demographic and medical variables for both the caregiver and the visually impaired patient. Problem orientation or motivation to solving problems was also significantly associated with caregiver depression and satisfaction with life. A substantial number of caregivers of visually impaired adults experience psychosocial distress, particularly among those who possess poor social problem-solving abilities. These results underscore the need for routine screening and treatment of emotional distress among individuals caring for relatives with vision impairments. Future research should examine the extent to which psychosocial interventions targeting caregiver social problem-solving skills may be useful not only in improving caregiver quality of life but also in subsequently enhancing rehabilitation outcomes for the visually impaired care recipient.

Contour-based object orientation estimation

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel

2016-04-01

Real-time object orientation estimation is an actual problem of computer vision nowadays. In this paper we propose an approach to estimate an orientation of objects lacking axial symmetry. Proposed algorithm is intended to estimate orientation of a specific known 3D object, so 3D model is required for learning. The proposed orientation estimation algorithm consists of 2 stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. It minimizes the training image set. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy (mean error value less than 6°) in all case studies. The real-time performance of the algorithm was also demonstrated.

A Retrospective Look at 20 Years of ASM Education Programs (1990-2010) and a Prospective Look at the Next 20 Years (2011-2030).

PubMed

Chang, Amy

2011-01-01

Professional societies provide visibility and legitimacy to the work of their post secondary educator members, advocate best practices in courses and sponsored student research, and establish deep networks and communities that catalyze members to collectively engage in undergraduate teaching and learning scholarship. Within the American Society for Microbiology (ASM), the Education Board, established in the mid-1970s, assumes this role. I have been fortunate enough to watch several pivotal programs support our growth and change the status quo by providing opportunities for biology educators to flourish. In this retrospective review, the background and details I offer about each initiative help explain ASM Education offerings, how our growth has been supported and how the status quo has changed. In this prospective look, I offer my vision of the future in post secondary education where classroom learning is student-centered and focused on global problems affecting our health and environment. For the profession to proliferate, the ASM must provide members as many opportunities in learning biology as they do with advancing biology to new frontiers.

Visual function and color vision in adults with Attention-Deficit/Hyperactivity Disorder.

PubMed

Kim, Soyeon; Chen, Samantha; Tannock, Rosemary

2014-01-01

Color vision and self-reported visual function in everyday life in young adults with Attention-Deficit/Hyperactivity Disorder (ADHD) were investigated. Participants were 30 young adults with ADHD and 30 controls matched for age and gender. They were tested individually and completed the Visual Activities Questionnaire (VAQ), Farnsworth-Munsell 100 Hue Test (FMT) and A Quick Test of Cognitive Speed (AQT). The ADHD group reported significantly more problems in 4 of 8 areas on the VAQ: depth perception, peripheral vision, visual search and visual processing speed. Further analyses of VAQ items revealed that the ADHD group endorsed more visual problems associated with driving than controls. Color perception difficulties on the FMT were restricted to the blue spectrum in the ADHD group. FMT and AQT results revealed slower processing of visual stimuli in the ADHD group. A comprehensive investigation of mechanisms underlying visual function and color vision in adults with ADHD is warranted, along with the potential impact of these visual problems on driving performance. Copyright © 2013 Spanish General Council of Optometry. Published by Elsevier Espana. All rights reserved.

Getting a Bigger Bang for Your Buck: A Collaborative Approach to Enhancing Dementia Education Planning in Long-Term Care Homes

PubMed Central

McAiney, Carrie A.; Hillier, Loretta M.; Ringland, Margaret; Cooper, Nancy

2009-01-01

A collaborative of Ontario-based long-term care associations, researchers, clinicians and educators representing various education initiatives related to dementia care and challenging behaviours used existing research evidence on adult learning principles, knowledge transfer and performance improvement to develop an evidence-based approach to support practice change and improvement in long-term care. The collaborative was led by the two provincial long-term care associations with no external funds to support its activities. This effort illustrates how people with common challenges, visions and goals can work together to share their intellectual and physical resources to address pervasive problems. PMID:21037817

Deep hierarchies in the primate visual cortex: what can we learn for computer vision?

PubMed

Krüger, Norbert; Janssen, Peter; Kalkan, Sinan; Lappe, Markus; Leonardis, Ales; Piater, Justus; Rodríguez-Sánchez, Antonio J; Wiskott, Laurenz

2013-08-01

Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Organized for a computer vision audience, we present functional principles of the processing hierarchies present in the primate visual system considering recent discoveries in neurophysiology. The hierarchical processing in the primate visual system is characterized by a sequence of different levels of processing (on the order of 10) that constitute a deep hierarchy in contrast to the flat vision architectures predominantly used in today's mainstream computer vision. We hope that the functional description of the deep hierarchies realized in the primate visual system provides valuable insights for the design of computer vision algorithms, fostering increasingly productive interaction between biological and computer vision research.

Composition of a Vision Screen for Servicemembers With Traumatic Brain Injury: Consensus Using a Modified Nominal Group Technique

PubMed Central

Finkelstein, Marsha; Llanos, Imelda; Scheiman, Mitchell; Wagener, Sharon Gowdy

2014-01-01

Vision impairment is common in the first year after traumatic brain injury (TBI), including among service members whose brain injuries occurred during deployment in Iraq and Afghanistan. Occupational therapy practitioners provide routine vision screening to inform treatment planning and referral to vision specialists, but existing methods are lacking because many tests were developed for children and do not screen for vision dysfunction typical of TBI. An expert panel was charged with specifying the composition of a vision screening protocol for servicemembers with TBI. A modified nominal group technique fostered discussion and objective determinations of consensus. After considering 29 vision tests, the panel recommended a nine-test vision screening that examines functional performance, self-reported problems, far–near acuity, reading, accommodation, convergence, eye alignment and binocular vision, saccades, pursuits, and visual fields. Research is needed to develop reliable, valid, and clinically feasible vision screening protocols to identify TBI-related vision disorders in adults. PMID:25005505

The Glenn A. Fry Award Lecture 2012: Plasticity of the Visual System Following Central Vision Loss

PubMed Central

Chung, Susana T. L.

2013-01-01

Following the onset of central vision loss, most patients develop an eccentric retinal location outside the affected macular region, the preferred retinal locus (PRL), as their new reference for visual tasks. The first goal of this paper is to present behavioral evidence showing the presence of experience-dependent plasticity in people with central vision loss. The evidence includes (1) the presence of oculomotor re-referencing of fixational saccades to the PRL; (2) the characteristics of the shape of the crowding zone (spatial region within which the presence of other objects affects the recognition of a target) at the PRL are more “foveal-like” instead of resembling those of the normal periphery; and (3) the change in the shape of the crowding zone at a para-PRL location that includes a component referenced to the PRL. These findings suggest that there is a shift in the referencing locus of the oculomotor and the sensory visual system from the fovea to the PRL for people with central vision loss, implying that the visual system for these individuals is still plastic and can be modified through experiences. The second goal of the paper is to demonstrate the feasibility of applying perceptual learning, which capitalizes on the presence of plasticity, as a tool to improve functional vision for people with central vision loss. Our finding that visual function could improve with perceptual learning presents an exciting possibility for the development of an alternative rehabilitative strategy for people with central vision loss. PMID:23670125

Dual Sensory Loss: Overview of Problems, Visual Assessment, and Rehabilitation

PubMed Central

Brabyn, John A.; Schneck, Marilyn E.; Haegerstrom-Portnoy, Gunilla; Lott, Lori A.

2007-01-01

This article provides an overview of some of the problems and possible solutions surrounding the neglected issue of combined vision and hearing deficits. The subject is treated by considering each subpopulation, ranging from those who have no residual vision or hearing to those with mild coexisting vision and hearing losses. An attempt is made to relate the different types of visual deficit to the likely problems encountered in real-life activities, such as communication and travel, among individuals who also have a hearing impairment. The assessment and appropriate referral of patients with these combined deficits is discussed, including the interpretation of visual test results and the importance of factors other than standard visual acuity. Speculation is offered on potential strategies and solutions for rehabilitation as well as the need for future research and improvements in service delivery. PMID:18003865

Comparing deep neural network and other machine learning algorithms for stroke prediction in a large-scale population-based electronic medical claims database.

PubMed

Chen-Ying Hung; Wei-Chen Chen; Po-Tsun Lai; Ching-Heng Lin; Chi-Chun Lee

2017-07-01

Electronic medical claims (EMCs) can be used to accurately predict the occurrence of a variety of diseases, which can contribute to precise medical interventions. While there is a growing interest in the application of machine learning (ML) techniques to address clinical problems, the use of deep-learning in healthcare have just gained attention recently. Deep learning, such as deep neural network (DNN), has achieved impressive results in the areas of speech recognition, computer vision, and natural language processing in recent years. However, deep learning is often difficult to comprehend due to the complexities in its framework. Furthermore, this method has not yet been demonstrated to achieve a better performance comparing to other conventional ML algorithms in disease prediction tasks using EMCs. In this study, we utilize a large population-based EMC database of around 800,000 patients to compare DNN with three other ML approaches for predicting 5-year stroke occurrence. The result shows that DNN and gradient boosting decision tree (GBDT) can result in similarly high prediction accuracies that are better compared to logistic regression (LR) and support vector machine (SVM) approaches. Meanwhile, DNN achieves optimal results by using lesser amounts of patient data when comparing to GBDT method.

Walking Problems

MedlinePlus

... as Parkinson's disease Diseases such as arthritis or multiple sclerosis Vision or balance problems Treatment of walking problems depends on the cause. Physical therapy, surgery, or mobility aids may help.

Learning to Be a Community: Schools Need Adaptable Models to Create Successful Programs

ERIC Educational Resources Information Center

Ermeling, Bradley A.; Gallimore, Ronald

2013-01-01

Making schools learning places for teachers as well as students is a timeless and appealing vision. The growing number of professional learning communities is a hopeful sign that profound change is on the way. This is the challenge learning communities face: Schools and districts need implementation models flexible enough to adapt to local…

Professional Learning in Initial Teacher Education: Vision in the Constructivist Conception of Teaching and Learning

ERIC Educational Resources Information Center

Tang, Sylvia Y. F.; Wong, Angel K. Y.; Cheng, May M. H.

2012-01-01

With the constructivist view of learning as a conceptual lens, this paper examines student teachers' professional learning in initial teacher education (ITE). A mixed-method study was conducted with student teachers of a Bachelor of Education Programme in Hong Kong. The quantitative element of the study reveals that student teachers held a…

Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

ERIC Educational Resources Information Center

Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

2014-01-01

This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

Report on the National Learning Roundtable (Edmonton, Alberta, Canada, March 19-20, 2001).

ERIC Educational Resources Information Center

Lowe, Graham S.

Forty-five individuals from a wide range of organizations and backgrounds participated in a national roundtable on learning in Canada. Working in small groups and plenaries, participants proposed a vision for learning as a way to address the widely expressed concern that Canada is not moving fast enough to increase learning opportunities and to…

A Critical Appraisal of the Performance of Royal Dutch Shell as a Learning Organisation in the 1990s.

ERIC Educational Resources Information Center

Boyle, Emily

2002-01-01

Although Royal Dutch Shell had been identified as a "premiere learning organization," it had its worst results in 1998. Reasons included loss of commitment and community, leadership complacency, and inability to create a shared vision. Although management espoused learning organization principles, learning was not used for communal…

Machine Learning Techniques in Clinical Vision Sciences.

PubMed

Caixinha, Miguel; Nunes, Sandrina

2017-01-01

This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration, and diabetic retinopathy, these ocular pathologies being the major causes of irreversible visual impairment.

The Aging Eye

MedlinePlus

... Search Search the NEI Website search NEI on Social Media | Search A-Z | en español | Text size S M ... Outreach Tools and Tips Watch, Listen, and Learn Social Media Glaucoma Glaucoma Learn About Glaucoma Keep Vision in ...

Computer vision for microscopy diagnosis of malaria.

PubMed

Tek, F Boray; Dempster, Andrew G; Kale, Izzet

2009-07-13

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Manifold learning in machine vision and robotics

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-02-01

Smart algorithms are used in Machine vision and Robotics to organize or extract high-level information from the available data. Nowadays, Machine learning is an essential and ubiquitous tool to automate extraction patterns or regularities from data (images in Machine vision; camera, laser, and sonar sensors data in Robotics) in order to solve various subject-oriented tasks such as understanding and classification of images content, navigation of mobile autonomous robot in uncertain environments, robot manipulation in medical robotics and computer-assisted surgery, and other. Usually such data have high dimensionality, however, due to various dependencies between their components and constraints caused by physical reasons, all "feasible and usable data" occupy only a very small part in high dimensional "observation space" with smaller intrinsic dimensionality. Generally accepted model of such data is manifold model in accordance with which the data lie on or near an unknown manifold (surface) of lower dimensionality embedded in an ambient high dimensional observation space; real-world high-dimensional data obtained from "natural" sources meet, as a rule, this model. The use of Manifold learning technique in Machine vision and Robotics, which discovers a low-dimensional structure of high dimensional data and results in effective algorithms for solving of a large number of various subject-oriented tasks, is the content of the conference plenary speech some topics of which are in the paper.

A Vision of the Future: A School for Running.

ERIC Educational Resources Information Center

Spino, Mike

1979-01-01

Presents a vision of how a school of running could provide young people with learning experiences encompassing body and mind. The school would have four tracks: running, body work, inner space development, and academic subjects. Sea Pines Resort in South Carolina will be ideal for the kind of education described here. (Author/BEF)

Preparing Mathematics Teachers for Elementary High-Poverty Schools: Perceptions and Suggestions from Preservice Teachers

ERIC Educational Resources Information Center

McKinney, Sueanne E.; Berry, Robert Q., III; Jackson, Joan M.

2007-01-01

The National Council of Teachers of Mathematics articulates an ambitious vision of a high-quality mathematics program. Achieving this vision requires competent and knowledgeable teachers who can support all students in learning mathematics concepts with understanding. Effective mathematics teachers are especially needed for high-poverty schools…

Effective Science Instruction: What Does Research Tell Us? Second Edition

ERIC Educational Resources Information Center

Banilower, Eric; Cohen, Kim; Pasley, Joan; Weiss, Iris

2010-01-01

This brief distills the research on science learning to inform a common vision of science instruction and to describe the extent to which K-12 science education currently reflects this vision. A final section on implications for policy makers and science education practitioners describes actions that could integrate the findings from research into…

A Hypermedia System To Aid in Preservice Teacher Education: Instructional Design and Evaluation.

ERIC Educational Resources Information Center

Lambdin, Diana V.; And Others

This research investigated how use of an interactive videodisk information system, the Strategic Teaching Framework (STF), helped preservice teachers expand their visions of teaching, learning, and assessment in mathematics, and helped develop their skills in translating that vision into action in the classroom. STF consisted of videos of…

How Small Schools Grew Up and Got Serious (but Didn't Lose Their Spunk)

ERIC Educational Resources Information Center

Oxley, Diana; Luers, Katie Whitney

2011-01-01

After providing technical assistance to the federal Smaller Learning Community Program grantees, the authors developed five lessons for successful programs: 1) A strong vision of improved instruction needs to drive high school reorganization; 2) A strong vision of improved instruction focuses on strengthening the instructional core; 3)…

Promoting Socialization in Distance Education

ERIC Educational Resources Information Center

Tucker, Shelia Y.

2012-01-01

Learners enjoy the convenience of being able to take online courses, yet many reports missing the face-to-face contact with their peers. This researcher has sought to tap into the vision of Ferratt & Hall (2009) whereby educators and technology designers are encouraged to extend the vision of online learning to "virtually being there and…

Visions for Literacy: Parents' Aspirations for Reading in Children with Down Syndrome

ERIC Educational Resources Information Center

Ricci, Leila; Osipova, Anna

2012-01-01

Although children with Down syndrome (DS) can learn to read, few studies have explored parental perspectives on the reading development of this group of children. This article, written by Leila Ricci and Anna Osipova, from California State University, explores visions and expectations regarding reading held by parents of children with Down…

Understanding the Graphical Challenges Faced by Vision-Impaired Students in Australian Universities

ERIC Educational Resources Information Center

Butler, Matthew; Holloway, Leona; Marriott, Kim; Goncu, Cagatay

2017-01-01

Information graphics such as plots, maps, plans, charts, tables and diagrams form an integral part of the student learning experience in many disciplines. However, for a vision impaired student accessing such graphical materials can be problematic. This research seeks to understand the current state of accessible graphics provision in Australian…

A (Super) Heroic Vision of Leader Self

ERIC Educational Resources Information Center

Linn, Genie Bingham

2011-01-01

This study leads the reader on a learning journey with the heroic metaphors derived from heroic myths of today's pop culture to the views shared by aspiring administrators. Viewing the students' leadership vision of self as hero provided insight to guiding students in their personal leadership journey. By naming and describing self as hero, future…

Range Image Flow using High-Order Polynomial Expansion

DTIC Science & Technology

2013-09-01

included as a default algorithm in the OpenCV library [2]. The research of estimating the motion between range images, or range flow, is much more...Journal of Computer Vision, vol. 92, no. 1, pp. 1‒31. 2. G. Bradski and A. Kaehler. 2008. Learning OpenCV : Computer Vision with the OpenCV Library

The General College Vision: Integrating Intellectual Growth, Multicultural Perspectives, and Student Development

ERIC Educational Resources Information Center

Higbee, Jeanne L., Ed.; Lundell, Dana B., Ed.; Arendale, David R., Ed.

2005-01-01

This book explores the vision and contributions of the former General College, a program existing 74 years in the University of Minnesota, highlighting its history, mission, programs, research, and student services. This includes an evolving and dynamic program for teaching, learning, and research for student success in higher education. Following…

Deep Learning: A Primer for Radiologists.

PubMed

Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

2017-01-01

Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

To See Anew: New Technologies Are Moving Rapidly Toward Restoring or Enabling Vision in the Blind.

PubMed

Grifantini, Kristina

2017-01-01

Humans have been using technology to improve their vision for many decades. Eyeglasses, contact lenses, and, more recently, laser-based surgeries are commonly employed to remedy vision problems, both minor and major. But options are far fewer for those who have not seen since birth or who have reached stages of blindness in later life.

"Better" People, Better Teaching: The Vision of the National Teacher Corps, 1965-1968

ERIC Educational Resources Information Center

Rogers, Bethany

2009-01-01

This article focuses on the period between 1966 and 1968, when the original vision of the policymakers of the National Teacher Corps (NTC) and the federal staffers who created the NTC initiative held sway. In their vision, the "best and brightest" (according to their criteria) could better solve the problems of educating so-called disadvantaged…

Temporal Properties of Liquid Crystal Displays: Implications for Vision Science Experiments

PubMed Central

Elze, Tobias; Tanner, Thomas G.

2012-01-01

Liquid crystal displays (LCD) are currently replacing the previously dominant cathode ray tubes (CRT) in most vision science applications. While the properties of the CRT technology are widely known among vision scientists, the photometric and temporal properties of LCDs are unfamiliar to many practitioners. We provide the essential theory, present measurements to assess the temporal properties of different LCD panel types, and identify the main determinants of the photometric output. Our measurements demonstrate that the specifications of the manufacturers are insufficient for proper display selection and control for most purposes. Furthermore, we show how several novel display technologies developed to improve fast transitions or the appearance of moving objects may be accompanied by side–effects in some areas of vision research. Finally, we unveil a number of surprising technical deficiencies. The use of LCDs may cause problems in several areas in vision science. Aside from the well–known issue of motion blur, the main problems are the lack of reliable and precise onsets and offsets of displayed stimuli, several undesirable and uncontrolled components of the photometric output, and input lags which make LCDs problematic for real–time applications. As a result, LCDs require extensive individual measurements prior to applications in vision science. PMID:22984458

Light Vision Color

NASA Astrophysics Data System (ADS)

Valberg, Arne

2005-04-01

Light Vision Color takes a well-balanced, interdisciplinary approach to our most important sensory system. The book successfully combines basics in vision sciences with recent developments from different areas such as neuroscience, biophysics, sensory psychology and philosophy. Originally published in 1998 this edition has been extensively revised and updated to include new chapters on clinical problems and eye diseases, low vision rehabilitation and the basic molecular biology and genetics of colour vision. Takes a broad interdisciplinary approach combining basics in vision sciences with the most recent developments in the area Includes an extensive list of technical terms and explanations to encourage student understanding Successfully brings together the most important areas of the subject in to one volume

The global problem of blindness and visual dysfunction

NASA Astrophysics Data System (ADS)

Lakshminarayanan, Vasudevan

2012-10-01

According to World Health Organization statistics there are approximately 285 million people who are blind, have severe low vision, or are near-blind. Of these, 39 million are blind, and 246 million have low vision problems. About 90% of these live in developing countries. The major causes are uncorrected refractive errors (42%), and cataracts (38%). In the US, there are about 6 million people over the age of 65 who have age-related macular degeneration which is the leading cause of blindness. For each decade after age 40, it is found that there is a three-fold increase in the prevalence of blindness and low vision. This paper will address the question of what can we, as optical physicists and engineers, do? There is a need for efficient methods to detect problems, investigate function, provide solutions, and develop rehabilitation devices for the visually impaired. Here I will sketch out the magnitude and variety of the problem, examples and future research directions.

The early evolution of southwestern Pennsylvania's regional math/science collaborative from the leadership perspective

NASA Astrophysics Data System (ADS)

Bunt, Nancy R.

Designed as a regional approach to the coordination of efforts and focusing of resources in fragmented southwestern Pennsylvania, the Collaborative's story is narrated by its founding director. Drawing from office archives, including letters of invitation, meeting notes, and participant evaluations of each event, the study describes the genesis of the Collaborative. It begins with identification of the problem and the resulting charge by a founding congress. It details the building of an organizational framework, the creation of a shared vision, the development of a blueprint for action, and the decision-making involved in determining how to strengthen mathematics and science education in the region. The study notes several influences on the Collaborative's leadership. Considering the role of other collaboratives, the study notes that knowledge of the Los Angeles Educational Partnership's LA SMART jump-started the Collaborative's initial planning process. Knowledge of San Francisco's SEABA influenced the size and naming of the Collaborative's Journal. Fred Newmann's definition of authentic instruction, learning and assessment are reflected in the shared vision and belief statements of the Collaborative. The five disciplines of Peter Senge influenced the nature of the organizational framework as well as the day-to-day operations of the Collaborative. The study also notes that the five organizational tensions identified in Ann Lieberman's work on "intentional learning communities" were present in every aspect of the evolution of the Collaborative. The study suggests that leaders of evolving collaboratives: (1) engage all relevant stakeholders in assessing the current situation and defining a desired future state, (2) take advantage of the lessons learned by others and the resources available at the state and national levels to design strategies and build action plans, (3) model the practices to be inspired in the learning community, (4) constantly gather feedback on process and content--and act on the recommendations as soon as possible, and (5) keep the focus of efforts on achieving the desired future--and measure progress toward it.

Neural correlates of virtual route recognition in congenital blindness.

PubMed

Kupers, Ron; Chebat, Daniel R; Madsen, Kristoffer H; Paulson, Olaf B; Ptito, Maurice

2010-07-13

Despite the importance of vision for spatial navigation, blind subjects retain the ability to represent spatial information and to move independently in space to localize and reach targets. However, the neural correlates of navigation in subjects lacking vision remain elusive. We therefore used functional MRI (fMRI) to explore the cortical network underlying successful navigation in blind subjects. We first trained congenitally blind and blindfolded sighted control subjects to perform a virtual navigation task with the tongue display unit (TDU), a tactile-to-vision sensory substitution device that translates a visual image into electrotactile stimulation applied to the tongue. After training, participants repeated the navigation task during fMRI. Although both groups successfully learned to use the TDU in the virtual navigation task, the brain activation patterns showed substantial differences. Blind but not blindfolded sighted control subjects activated the parahippocampus and visual cortex during navigation, areas that are recruited during topographical learning and spatial representation in sighted subjects. When the navigation task was performed under full vision in a second group of sighted participants, the activation pattern strongly resembled the one obtained in the blind when using the TDU. This suggests that in the absence of vision, cross-modal plasticity permits the recruitment of the same cortical network used for spatial navigation tasks in sighted subjects.

Post-vision and change: do we know how to change?

PubMed

D'Avanzo, Charlene

2013-01-01

The scale and importance of Vision and Change in Undergraduate Biology Education: A Call to Action challenges us to ask fundamental questions about widespread transformation of college biology instruction. I propose that we have clarified the "vision" but lack research-based models and evidence needed to guide the "change." To support this claim, I focus on several key topics, including evidence about effective use of active-teaching pedagogy by typical faculty and whether certain programs improve students' understanding of the Vision and Change core concepts. Program evaluation is especially problematic. While current education research and theory should inform evaluation, several prominent biology faculty-development programs continue to rely on self-reporting by faculty and students. Science, technology, engineering, and mathematics (STEM) faculty-development overviews can guide program design. Such studies highlight viewing faculty members as collaborators, embedding rewards faculty value, and characteristics of effective faculty-development learning communities. A recent National Research Council report on discipline-based STEM education research emphasizes the need for long-term faculty development and deep conceptual change in teaching and learning as the basis for genuine transformation of college instruction. Despite the progress evident in Vision and Change, forward momentum will likely be limited, because we lack evidence-based, reliable models for actually realizing the desired "change."

Lifelong Learning or Learning for Life? South Africa Provides Some Lessons.

ERIC Educational Resources Information Center

Thompson, Jane

2000-01-01

Reflects on an adult education conference in South Africa, noting that as the nation focuses on neoliberal economic policies, the education agenda may shift to vocationalism. Considers how the vision of Mandela and the needs expressed by local women for learning for life will be lost. (SK)

HRD in a Multicultural Workplace: The Need for Lifelong Learning.

ERIC Educational Resources Information Center

Ogisu-Kamiya, Motoyo

Advocating the development of a new vision and strategies for lifelong learning in the multicultural workplace, this paper describes the influences of cultural issues on the human resource development (HRD) interface at a Japanese multinational firm operating in Canada. Following an introduction defining lifelong learning and related terms,…

Keeping Current: Feng Shui and the School Library Media Specialist.

ERIC Educational Resources Information Center

Barron, Daniel D.

2000-01-01

Discusses the changing shift in education, including learning resources centers, from a production to a consumer mind-set, focusing on the activity of learning rather than teaching. Highlights include learning communities; personal mastery; developing a vision; the interconnectedness of organizations; harmony and balance, similar to feng shui; and…

Alignment between Principal and Teacher Beliefs about Technology Use

ERIC Educational Resources Information Center

Alghamdi, Abdulmajeed; Prestridge, Sarah

2015-01-01

This paper explores the link between principals' and teachers' beliefs regarding technology use in teaching and learning. Principals who have a clear vision for carrying out the pedagogical requirements for technological change in teaching and learning approaches can direct the use of technology to enhance the school learning environment.…

Evaluation of the Implementation of Professional Learning Communities and the Impact on Student Achievement

ERIC Educational Resources Information Center

Bostic, Cristi M.

2013-01-01

This dissertation evaluated the implementation of professional learning communities in a large suburban school district in North Carolina. The presence of shared and supportive leadership, shared values and vision, collective learning and application, shared personal practice, supportive conditions for relationships, and supportive conditions for…

Village Voices, Global Visions: Digital Video as a Transformative Foreign Language Learning Tool

ERIC Educational Resources Information Center

Goulah, Jason

2007-01-01

This instrumental case study examines how adolescent high-intermediate Japanese language learners enrolled in a one-month credited abroad program used video as a mediational tool for (1) learning foreign language, content, and technology skills, (2) cultivating critical multiliteracies and transformative learning regarding geopolitics and the…

Supporting Three-Dimensional Science Learning: The Role of Curiosity-Driven Classroom Discourse

ERIC Educational Resources Information Center

Johnson, Wendy Renae

2017-01-01

The National Research Council's "Framework for K-12 Science Education" (2011) presents a new vision for science education that calls for the integration of the three dimensions of science learning: science and engineering practices, crosscutting concepts, and disciplinary core ideas. Unlike previous conceptions of science learning that…

Learning and Active Aging

ERIC Educational Resources Information Center

Boulton-Lewis, Gillian M.; Buys, Laurie; Lovie-Kitchin, Jan

2006-01-01

Learning is an important aspect of aging productively. This paper describes results from 2645 respondents (aged from 50 to 74+ years) to a 165-variable postal survey in Australia. The focus is on learning and its relation to work; social, spiritual, and emotional status; health; vision; home; life events; and demographic details. Clustering…

Five Cities, One Vision. CORAL: Linking Communities, Children and Learning.

ERIC Educational Resources Information Center

James G. Irvine Foundation, San Francisco, CA.

This booklet describes the CORAL (Communities Organizing Resources To Advance Learning) program within five California communities: Pasadena, Long Beach, San Jose, Fresno, and Sacramento. This initiative, begun in 1999, is committed to a community-based and community-building approach to supporting learning and focuses on improving academic…

Transformative Professional Learning: A System to Enhance Teacher and Student Motivation

ERIC Educational Resources Information Center

Ginsberg, Margery B.

2011-01-01

This book's bold new vision for professional learning emphasizes the importance of intrinsic motivation and respect for cultural diversity to create a transformative approach to school improvement. Knowing that culture and motivation are inseparable influences on learning, Margery B. Ginsberg provides practical steps that focus on teaching and…

ICPR-2016 - International Conference on Pattern Recognition

Science.gov Websites

Learning for Scene Understanding" Speakers ICPR2016 PAPER AWARDS Best Piero Zamperoni Student Paper -Paced Dictionary Learning for Cross-Domain Retrieval and Recognition Xu, Dan; Song, Jingkuan; Alameda discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and

Vision rehabilitation for visual-vestibular dysfunction: the role of the neuro-optometrist.

PubMed

Cohen, Allen H

2013-01-01

This article discusses, in a clinically relevant format, the importance of including a neuro-optometrist as a member of the management team for patients with balance disorders. To review the importance of vision and visual processing for maintaining a sense of balance and equilibrium and the role of the neuro-optometrist in the overall rehabilitation of patients with balance disorders Dizziness, balance problems and the sensation that the space world is moving (vertigo) are one of the most commonly reported problems in general medical practice. Persons with a central nervous system injury or other idiopathic causes of visual processing problems or who have functional vision problems that are not adequately managed, often experience extreme difficulty with balance and movement, as well as with their perception of space. Consequently, the patient often experiences difficulty functioning in an environment with excessive visual stimulation such as a grocery store or shopping mall. Symptoms of disequilibrium, vestibular and balance problems are commonly a result of VOR disturbance secondary to an inner ear problem and an unstable binocularity. The combination of neuro-optomertic rehabilitative therapy and balance therapy will result in a is an effective treatment for reducing or resolving these symptoms.

A Practical Solution Using A New Approach To Robot Vision

NASA Astrophysics Data System (ADS)

Hudson, David L.

1984-01-01

Up to now, robot vision systems have been designed to serve both application development and operational needs in inspection, assembly and material handling. This universal approach to robot vision is too costly for many practical applications. A new industrial vision system separates the function of application program development from on-line operation. A Vision Development System (VDS) is equipped with facilities designed to simplify and accelerate the application program development process. A complimentary but lower cost Target Application System (TASK) runs the application program developed with the VDS. This concept is presented in the context of an actual robot vision application that improves inspection and assembly for a manufacturer of electronic terminal keyboards. Applications developed with a VDS experience lower development cost when compared with conventional vision systems. Since the TASK processor is not burdened with development tools, it can be installed at a lower cost than comparable "universal" vision systems that are intended to be used for both development and on-line operation. The VDS/TASK approach opens more industrial applications to robot vision that previously were not practical because of the high cost of vision systems. Although robot vision is a new technology, it has been applied successfully to a variety of industrial needs in inspection, manufacturing, and material handling. New developments in robot vision technology are creating practical, cost effective solutions for a variety of industrial needs. A year or two ago, researchers and robot manufacturers interested in implementing a robot vision application could take one of two approaches. The first approach was to purchase all the necessary vision components from various sources. That meant buying an image processor from one company, a camera from another and lens and light sources from yet others. The user then had to assemble the pieces, and in most instances he had to write all of his own software to test, analyze and process the vision application. The second and most common approach was to contract with the vision equipment vendor for the development and installation of a turnkey inspection or manufacturing system. The robot user and his company paid a premium for their vision system in an effort to assure the success of the system. Since 1981, emphasis on robotics has skyrocketed. New groups have been formed in many manufacturing companies with the charter to learn about, test and initially apply new robot and automation technologies. Machine vision is one of new technologies being tested and applied. This focused interest has created a need for a robot vision system that makes it easy for manufacturing engineers to learn about, test, and implement a robot vision application. A newly developed vision system addresses those needs. Vision Development System (VDS) is a complete hardware and software product for the development and testing of robot vision applications. A complimentary, low cost Target Application System (TASK) runs the application program developed with the VDS. An actual robot vision application that demonstrates inspection and pre-assembly for keyboard manufacturing is used to illustrate the VDS/TASK approach.

Vision impairment and nutritional status among older assisted living residents.

PubMed

Muurinen, Seija M; Soini, Helena H; Suominen, Merja H; Saarela, Riitta K T; Savikko, Niina M; Pitkälä, Kaisu H

2014-01-01

Vision impairment is common among older persons. It is a risk factor for disability, and it may be associated with nutritional status via decline in functional status. However, only few studies have examined the relationship between vision impairment and nutritional status, which was investigated in this cross-sectional study. The study included all residents living in the assisted living facilities in Helsinki and Espoo in 2007. Residents in temporary respite care were excluded (5%). Of permanent residents (N=2214), 70% (N=1475) consented. Trained nurses performed a personal interview and assessment of each resident including the Mini Nutritional Assessment (MNA), functional and health status. Patient records were used to confirm demographic data and medical history. Mortality in 2010 was retrieved from central registers. Of the residents, 17.5% (N=245) had vision impairment and they were not able to read regular print. Those with vision impairment were older, more often females, and malnourished according to MNA. They had lower BMI, and suffered more often from dementia and chewing problems than those without vision impairment. In logistic regression analysis controlling for age, gender, chewing problems and dementia, vision impairment was independently associated with resident's malnutrition (OR 2.51, 95% CI 1.80-3.51). According to our results older residents in assisted living with vision impairment are at high risk for malnutrition. Therefore it is important to assess nutritional status of persons with vision impairment. It would be beneficial to repeat this kind of a study also in elderly community population. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Psychology and Optometry: Interaction and Collaboration.

ERIC Educational Resources Information Center

Biaggio, Mary Kay; Bittner, Erika

1990-01-01

Because a number of vision conditions have psychological components and some psychological conditions may be complicated by vision difficulties, interdisciplinary cooperation between clinical psychology and optometry should prove fruitful for the diagnosis, treatment, and management of health problems. (EVL)

Component Pin Recognition Using Algorithms Based on Machine Learning

NASA Astrophysics Data System (ADS)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

From spectral information to animal colour vision: experiments and concepts.

PubMed

Kelber, Almut; Osorio, Daniel

2010-06-07

Many animals use the spectral distribution of light to guide behaviour, but whether they have colour vision has been debated for over a century. Our strong subjective experience of colour and the fact that human vision is the paradigm for colour science inevitably raises the question of how we compare with other species. This article outlines four grades of 'colour vision' that can be related to the behavioural uses of spectral information, and perhaps to the underlying mechanisms. In the first, even without an (image-forming) eye, simple organisms can compare photoreceptor signals to locate a desired light environment. At the next grade, chromatic mechanisms along with spatial vision guide innate preferences for objects such as food or mates; this is sometimes described as wavelength-specific behaviour. Here, we compare the capabilities of di- and trichromatic vision, and ask why some animals have more than three spectral types of receptors. Behaviours guided by innate preferences are then distinguished from a grade that allows learning, in part because the ability to learn an arbitrary colour is evidence for a neural representation of colour. The fourth grade concerns colour appearance rather than colour difference: for instance, the distinction between hue and saturation, and colour categorization. These higher-level phenomena are essential to human colour perception but poorly known in animals, and we suggest how they can be studied. Finally, we observe that awareness of colour and colour qualia cannot be easily tested in animals.

The handicap of abnormal colour vision.

PubMed

Cole, Barry L

2004-07-01

All people with abnormal colour vision, except for a few mildly affected deuteranomals, report that they experience problems with colour in everyday life and at work. Contemporary society presents them with increasing problems because colour is now so widely used in printed materials and in computer displays. Equal opportunity law gives them protection against unfair discrimination in employment, so a decision to exclude a person from employment on the grounds of abnormal colour vision must now be well supported by good evidence and sound argument. This paper reviews the investigations that have contributed to understanding the nature and consequences of the problems they have. All those with abnormal colour vision are at a disadvantage with comparative colour tasks that involve precise matching of colours or discrimination of fine colour differences either because of their loss of colour discrimination or anomalous perception of metamers. The majority have problems when colour is used to code information, in man-made colour codes and in naturally occurring colour codes that signal ripeness of fruit, freshness of meat or illness. They can be denied the benefit of colour to mark out objects and organise complex visual displays. They may be unreliable when a colour name is used as an identifier. They are slower and less successful in search when colour is an attribute of the target object or is used to organise the visual display. Because those with the more severe forms of abnormal colour vision perceive a very limited gamut of colours, they are at a disadvantage in the pursuit and appreciation of those forms of art that use colour.

A Retrospective on the Vision for Progress in Community Health Partnerships: Research, Education, and Action

PubMed Central

Eder, Milton “Mickey”; Holzer, Jessica; Calhoun, Karen; Strong, Larkin L.

2017-01-01

The organizers founded Progress in Community Health Partnerships with a commitment to improving our understanding of community-based participatory research (CBPR) and its use in community–academic/institutional health partnerships. Following Rogers’s Diffusion of Innovations, they reasoned that expanded adoption would occur through academic and community partner recognition of CBPR’s relative advantage over previous approaches; its compatibility with the values, past experience and needs of potential adopters; its ease of understanding and use; its capacity for experimentation and refinement; and its production of observable results. We now assess the journal’s progress toward realizing the vision, as well as issues and problems the organizers identified. We map the journal’s content over its first decade onto the initial vision by examining the record of submissions and publications across the eight types of articles and the journal’s record of rejections and publications. In remembering that Rogers’s study of innovations requires both technical and social change, we discuss the difference between understanding how to do something and actually putting an innovation into action that becomes standard practice at both individual and systemic levels. We observe that the large number of Original Research and Works-in-Progress/Lessons Learned manuscripts, submitted and published, reflect traditional expectations for faculty research productivity. We suggest that sustainability, which rated of lower importance within the initial vision, has gained in importance among community and academic partners; however, it will gain added attention only with changed university expectations of researchers. We further suggest that the study of partnerships involved in researching and improving public health should be expanded beyond the current focus on CBPR. PMID:28603145

Convolutional Dictionary Learning: Acceleration and Convergence

NASA Astrophysics Data System (ADS)

Chun, Il Yong; Fessler, Jeffrey A.

2018-04-01

Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM). When their parameters are properly tuned, AL methods have shown fast convergence in CDL. However, the parameter tuning process is not trivial due to its data dependence and, in practice, the convergence of AL methods depends on the AL parameters for nonconvex CDL problems. To moderate these problems, this paper proposes a new practically feasible and convergent Block Proximal Gradient method using a Majorizer (BPG-M) for CDL. The BPG-M-based CDL is investigated with different block updating schemes and majorization matrix designs, and further accelerated by incorporating some momentum coefficient formulas and restarting techniques. All of the methods investigated incorporate a boundary artifacts removal (or, more generally, sampling) operator in the learning model. Numerical experiments show that, without needing any parameter tuning process, the proposed BPG-M approach converges more stably to desirable solutions of lower objective values than the existing state-of-the-art ADMM algorithm and its memory-efficient variant do. Compared to the ADMM approaches, the BPG-M method using a multi-block updating scheme is particularly useful in single-threaded CDL algorithm handling large datasets, due to its lower memory requirement and no polynomial computational complexity. Image denoising experiments show that, for relatively strong additive white Gaussian noise, the filters learned by BPG-M-based CDL outperform those trained by the ADMM approach.

Drosophila learn efficient paths to a food source.

PubMed

Navawongse, Rapeechai; Choudhury, Deepak; Raczkowska, Marlena; Stewart, James Charles; Lim, Terrence; Rahman, Mashiur; Toh, Alicia Guek Geok; Wang, Zhiping; Claridge-Chang, Adam

2016-05-01

Elucidating the genetic, and neuronal bases for learned behavior is a central problem in neuroscience. A leading system for neurogenetic discovery is the vinegar fly Drosophila melanogaster; fly memory research has identified genes and circuits that mediate aversive and appetitive learning. However, methods to study adaptive food-seeking behavior in this animal have lagged decades behind rodent feeding analysis, largely due to the challenges presented by their small scale. There is currently no method to dynamically control flies' access to food. In rodents, protocols that use dynamic food delivery are a central element of experimental paradigms that date back to the influential work of Skinner. This method is still commonly used in the analysis of learning, memory, addiction, feeding, and many other subjects in experimental psychology. The difficulty of microscale food delivery means this is not a technique used in fly behavior. In the present manuscript we describe a microfluidic chip integrated with machine vision and automation to dynamically control defined liquid food presentations and sensory stimuli. Strikingly, repeated presentations of food at a fixed location produced improvements in path efficiency during food approach. This shows that improved path choice is a learned behavior. Active control of food availability using this microfluidic system is a valuable addition to the methods currently available for the analysis of learned feeding behavior in flies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A Projection free method for Generalized Eigenvalue Problem with a nonsmooth Regularizer.

PubMed

Hwang, Seong Jae; Collins, Maxwell D; Ravi, Sathya N; Ithapu, Vamsi K; Adluru, Nagesh; Johnson, Sterling C; Singh, Vikas

2015-12-01

Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation. Few other linear algebra problems have a more mature set of numerical routines available and many computer vision libraries leverage such tools extensively. However, the ability to call the underlying solver only as a "black box" can often become restrictive. Many 'human in the loop' settings in vision frequently exploit supervision from an expert, to the extent that the user can be considered a subroutine in the overall system. In other cases, there is additional domain knowledge, side or even partial information that one may want to incorporate within the formulation. In general, regularizing a (generalized) eigenvalue problem with such side information remains difficult. Motivated by these needs, this paper presents an optimization scheme to solve generalized eigenvalue problems (GEP) involving a (nonsmooth) regularizer. We start from an alternative formulation of GEP where the feasibility set of the model involves the Stiefel manifold. The core of this paper presents an end to end stochastic optimization scheme for the resultant problem. We show how this general algorithm enables improved statistical analysis of brain imaging data where the regularizer is derived from other 'views' of the disease pathology, involving clinical measurements and other image-derived representations.

Testing meta tagger

DTIC Science & Technology

2017-12-21

rank , and computer vision. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on...Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.[1] Arthur Samuel...an American pioneer in the field of computer gaming and artificial intelligence, coined the term "Machine Learning " in 1959 while at IBM[2]. Evolved

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Kernelized Locality-Sensitive Hashing for Fast Image Landmark Association

DTIC Science & Technology

2011-03-24

based Simultaneous Localization and Mapping ( SLAM ). The problem, however, is that vision-based navigation techniques can re- quire excessive amounts of...up and optimizing the data association process in vision-based SLAM . Specifically, this work studies the current methods that algorithms use to...required for location identification than that of other methods. This work can then be extended into a vision- SLAM implementation to subsequently

A 3D terrain reconstruction method of stereo vision based quadruped robot navigation system

NASA Astrophysics Data System (ADS)

Ge, Zhuo; Zhu, Ying; Liang, Guanhao

2017-01-01

To provide 3D environment information for the quadruped robot autonomous navigation system during walking through rough terrain, based on the stereo vision, a novel 3D terrain reconstruction method is presented. In order to solve the problem that images collected by stereo sensors have large regions with similar grayscale and the problem that image matching is poor at real-time performance, watershed algorithm and fuzzy c-means clustering algorithm are combined for contour extraction. Aiming at the problem of error matching, duel constraint with region matching and pixel matching is established for matching optimization. Using the stereo matching edge pixel pairs, the 3D coordinate algorithm is estimated according to the binocular stereo vision imaging model. Experimental results show that the proposed method can yield high stereo matching ratio and reconstruct 3D scene quickly and efficiently.

Mobile phone related-hazards and subjective hearing and vision symptoms in the Saudi population.

PubMed

Meo, Sultan A; Al-Drees, Abdul M

2005-01-01

Over the past decade utilization of mobile phones has dramatically increased. They are now an essential part of business, commerce, and communication, however, their use may lead to health problems. Therefore, the present study was designed to investigate a link between the use of mobile phones and hearing and vision symptoms in the Saudi population and also to contribute to the increase in social awareness of health problems associated with the use of these devices. A total of 873 (57.04% of males and 39.86% of females) subjects using mobile phones were invited to participate in the presented study. A structured questionnaire was distributed among them to collect a detailed medical history. The Chi-square test was employed to observe the relationship between duration of calls and hearing and vision complaints. The present study showed an association between the use of mobile phones and hearing and vision complaints. About 34.59% of problems were related with impaired hearing, ear ache and/or warmth on the ear, and 5.04% of complaints with the decreased and/or blurred vision. It is concluded that the use of mobile phone is a health risk factor, and thus it is suggested that excessive use of mobile phones should be avoided and social awareness increased through health promotion activities, such as group discussions or public presentations and via electronic and printed media sources.

Work-Based Curriculum to Broaden Learners' Participation in Science: Insights for Designers

NASA Astrophysics Data System (ADS)

Bopardikar, Anushree; Bernstein, Debra; Drayton, Brian; McKenney, Susan

2018-05-01

Around the globe, science education during compulsory schooling is envisioned for all learners regardless of their educational and career aspirations, including learners bound to the workforce upon secondary school completion. Yet, a major barrier in attaining this vision is low learner participation in secondary school science. Because curricula play a major role in shaping enacted learning, this study investigated how designers developed a high school physics curriculum with positive learning outcomes in learners with varied inclinations. Qualitative analysis of documents and semistructured interviews with the designers focused on the curriculum in different stages—from designers' ideas about learning goals to their vision for enactment to the printed materials—and on the design processes that brought them to fruition. This revealed designers' emphases on fostering workplace connections via learning goals and activities, and printed supports. The curriculum supported workplace-inspired, hands-on design-and-build projects, developed to address deeply a limited set of standards aligned learning goals. The curriculum also supported learners' interactions with relevant workplace professionals. To create these features, the designers reviewed other curricula to develop vision and printed supports, tested activities internally to assess content coverage, surveyed states in the USA receiving federal school-to-work grants and reviewed occupational information to choose unit topics and career contexts, and visited actual workplaces to learn about authentic praxis. Based on the worked example, this paper offers guidelines for designing work-based science curriculum products and processes that can serve the work of other designers, as well as recommendations for research serving designers and policymakers.

Comparison on testability of visual acuity, stereo acuity and colour vision tests between children with learning disabilities and children without learning disabilities in government primary schools

PubMed Central

Abu Bakar, Nurul Farhana; Chen, Ai-Hong

2014-01-01

Context: Children with learning disabilities might have difficulties to communicate effectively and give reliable responses as required in various visual function testing procedures. Aims: The purpose of this study was to compare the testability of visual acuity using the modified Early Treatment Diabetic Retinopathy Study (ETDRS) and Cambridge Crowding Cards, stereo acuity using Lang Stereo test II and Butterfly stereo tests and colour perception using Colour Vision Test Made Easy (CVTME) and Ishihara's Test for Colour Deficiency (Ishihara Test) between children in mainstream classes and children with learning disabilities in special education classes in government primary schools. Materials and Methods: A total of 100 primary school children (50 children from mainstream classes and 50 children from special education classes) matched in age were recruited in this cross-sectional comparative study. The testability was determined by the percentage of children who were able to give reliable respond as required by the respective tests. ‘Unable to test’ was defined as inappropriate response or uncooperative despite best efforts of the screener. Results: The testability of the modified ETDRS, Butterfly stereo test and Ishihara test for respective visual function tests were found lower among children in special education classes (P < 0.001) but not in Cambridge Crowding Cards, Lang Stereo test II and CVTME. Conclusion: Non verbal or “matching” approaches were found to be more superior in testing visual functions in children with learning disabilities. Modifications of vision testing procedures are essential for children with learning disabilities. PMID:24008790

Disparities in access to medical care for individuals with vision impairment.

PubMed

Spencer, Christine; Frick, Kevin; Gower, Emily W; Kempen, John H; Wolff, Jennifer L

2009-01-01

We investigated the relationship between blindness and vision impairment and access to medical care. Pooled data from the Medical Expenditure Panel Survey (MEPS) years 2002-2004 were used to identify non-institutionalized individuals over the age of 40 with either self-reported blindness, vision impairment, or no vision impairment (n = 40,643). Differences in access to care measures by vision status were assessed, after adjusting for the complex sampling design of the MEPS, using either two-sided z-tests or two-sided t-tests. Individuals with blindness and vision impairment report having more access problems related to cost of care, availability of insurance coverage, transportation issues, and refusal of services by providers, although they do not report lower rates of having a usual source of care compared to those without vision impairment. The results suggest that access to care for individuals with blindness and vision impairment is problematic, for reasons that are amenable to policy interventions.

The Practical Aspects of the Visual Act in Studying.

ERIC Educational Resources Information Center

Robinson, Bernard N.

This paper explores the role of vision in reading and studying. "How Vision Occurs" discusses the functions of rods, cones, the cerebral cortex, and the receptor senses. "The Optometrist and the Educator" views the role of the optometrist in relation to student learning. "Eye Anatomy Terms" defines the ciliary muscle, optic disc and nerve, macula…

Group Active Engagement Exercises: Pursuing the Recommendations of "Vision and Change" in an Introductory Undergraduate Science Course

ERIC Educational Resources Information Center

Jardine, Hannah E.; Levin, Daniel M.; Quimby, B. Booth; Cooke, Todd J.

2017-01-01

"Vision and Change in Undergraduate Education: A Call to Action," published by the American Association for the Advancement of Science in 2011, suggested cultivating biological literacy and practicing more student-centered learning in undergraduate life sciences education. We report here on the use of Group Active Engagement (GAE)…

Visions 2020.2: Student Views on Transforming Education and Training through Advanced Technologies

ERIC Educational Resources Information Center

US Department of Education, 2004

2004-01-01

The U.S. Departments of Commerce and Education (who co-chair the NSTC Working Group) and NetDay formed a partnership aimed at analyzing K-12 student views about technology for learning. These views are analyzed in this second report, "Visions 2020.2: Student Views on Transforming Education and Training Through Advanced Technologies." In…

What Mathematics Education Can Learn from Art: The Assumptions, Values, and Vision of Mathematics Education

ERIC Educational Resources Information Center

Dietiker, Leslie

2015-01-01

Elliot Eisner proposed that educational challenges can be met by applying an artful lens. This article draws from Eisner's proposal to consider the assumptions, values, and vision of mathematics education by theorizing mathematics curriculum as an art form. By conceptualizing mathematics curriculum (both in written and enacted forms) as stories…

Vision and Reality in Electronic Textbooks: What Publishers Need to Do to Survive

ERIC Educational Resources Information Center

Brown, Byron W.

2012-01-01

Today's electronic textbooks (e-texts) are technologically backward and over-priced. Yet publishers continue to press for contracts with colleges and universities that move toward the mandatory purchase by students of e-texts instead of printed books. The author lays out his vision for digital learning materials, explains the details of the…

Using "Competing Visions of Human Rights" in an International IB World School

ERIC Educational Resources Information Center

Tolley, William J.

2013-01-01

William Tolley, a teaching fellow with the Choices Program, is the Learning and Innovation Coach and head of history at the International School of Curitiba, Brazil (IB). He writes in this article that he has found that the "Competing Visions of Human Rights" teaching unit, developed by Brown University's Choices Program, provides a…

Small Boats in an Ocean of School Activities: Towards a European Vision on Education

ERIC Educational Resources Information Center

Villalba, Ernesto

2008-01-01

The paper discusses the concept of schools as "multi-purpose learning centres", proposed by the European Commission in the year 2000 as part of the Lisbon Strategy to improve competitiveness. This concept was arguably the "European vision" for school education and was meant to drive the modernization of school education.…

Leadership, Development and Diversity: In the Learning and Skills Sector in England

ERIC Educational Resources Information Center

Lumby, Jacky

2005-01-01

The White Paper Success for All set out a vision to transform post compulsory education in the United Kingdom. A key theme was "Developing the leaders, teachers, trainers and support staff of the future," reflecting a belief that leadership is one of the key elements in achieving the national vision. Alongside this positive affirmation…

Fair Student Funding and Other Reforms: Baltimore's Plan for Equity, Empowerment, Accountability and Improvement

ERIC Educational Resources Information Center

Frank, Stephen

2012-01-01

Superintendent Andres A. Alonso arrived in Baltimore in 2007 with a vision for improving the city's struggling schools. His vision included empowering school leaders and creating accountability for student learning through a series of reforms that center around a new system for giving resources to schools, called Fair Student Funding (FSF). FSF…

Sjogren's Syndrome

MedlinePlus

... symptoms. Symptoms The two main symptoms of Sjogren's syndrome are: Dry eyes. Your eyes might burn, itch or feel gritty — ... mouth is dry. Yeast infections. People with Sjogren's syndrome are much ... Vision problems. Dry eyes can lead to light sensitivity, blurred vision and ...

Learning to Share: A Vision of Leadership Practice

ERIC Educational Resources Information Center

Moller, Jorunn

2009-01-01

This article aims at providing insight into ways of constructing leadership for learning within a Norwegian context. The focus is on how a Norwegian principal talks about educational leadership and learning. The principal's story is juxtaposed with references to how her deputies and a group of teachers frame their experiences about leadership for…

Ensuring Good Character and Civic Education: Connecting through Service Learning

ERIC Educational Resources Information Center

Shumer, Robert; Lam, Carolina; Laabs, Bonnie

2012-01-01

Character and citizenship education are part of the vision of many countries, including Singapore. Ensuring they are implemented in academic environments, service learning has been shown to be a natural bridge between the two. Research has shown that service learning, when done well, produces outcomes related to character development and…

Making the Vision Work

ERIC Educational Resources Information Center

Plant, Helen; Ravenhall, Mark

2008-01-01

One of the successes of the Learning and Skills Council (LSC) has been to recognize the importance of advice and guidance to adults on courses as well as those wanting to access provision. Information, advice and guidance (IAG) matters: it helps people to overcome barriers to learning. It enables adults to identify what learning is right for them.…

ReVisioning the Public Library as an Oasis of Learning

ERIC Educational Resources Information Center

Cassell, Mary A.; Bamdas, Jo Ann M.; Bryan, Valerie C.

2012-01-01

Culturally diverse older adult learners are among the fastest growing age groups for which public libraries promote the needs of lifelong learning today. This article explores the past, present, and future of informal and non-formal public learning environments as safe and welcoming, with supportive educational programming provided by librarians…

Using a Scholarly Approach to Improve Teaching and Learning in Biochemistry Higher Education

ERIC Educational Resources Information Center

Loertscher, Jennifer

2012-01-01

Although the biochemistry education community is far from avoiding conversations about improving teaching and learning, reexamining individual and community teaching practices through the lens of the scholarship of teaching and learning (SoTL) is critical for continued growth and improvement. The contemporary vision of SoTL, which has been…

A Learning Community Focus for Christian Education

ERIC Educational Resources Information Center

Littleton, John

2008-01-01

The vision statement of St. Saviour's Anglican Church in the Parish of Glen Osmon reads, "We aim to be a worshipping, caring, learning and serving Christian Community." These four aspects of Christian Community are essential and inter-related. The intention in the first part of this article is to explore the "learning" aspects…

Discourses on Empowerment in Adult Learning: A View on Renewed Learning

ERIC Educational Resources Information Center

Daniele, Luisa

2017-01-01

The paper examines critically the dimension of empowerment in the European discourse, starting from some operational definitions used in official documents. The author analyses the shift in the European documents from 2000 to recent years, from a lifelong learning vision to an adult education approach, basically labour market-oriented, thus…

Individual and Collective Reflection: How to Meet the Needs of Development in Teaching

ERIC Educational Resources Information Center

Nissila, Sade-Pirkko

2005-01-01

The following five core ideas explain how learning organizations function as wholes. The core ideas are central when school is examined as a learning organization. Personal mastery, mental models, team learning, shared visions and system thinking offer different angles to examine the organization. (1) Personal mastery. Without personal commitment,…

Future Ready Learning: Reimagining the Role of Technology in Education. 2016 National Education Technology Plan

ERIC Educational Resources Information Center

Thomas, Susan

2016-01-01

The National Education Technology Plan is the flagship educational technology policy document for the United States. The 2016 Plan, "Future Ready Learning: Reimagining the Role of Technology in Education," articulates a vision of equity, active use, and collaborative leadership to make everywhere, all-the-time learning possible. While…

Closed Circuit? Flow, Influence and the Liquid Management of Learning and Skills

ERIC Educational Resources Information Center

Beighton, Christian

2017-01-01

A new discourse is being deployed by the English learning and skills sector's new professional body, the Education and Training Foundation (ETF). This discourse repositions learning within a specific vision of corporate expectations. With a focus on deregulation in the sector and employer engagement, this repositioning deploys the terminology and…

Agriscience Teachers' Implementation of Digital Game-Based Learning in an Introductory Animal Science Course

ERIC Educational Resources Information Center

Webb, Angela W.; Bunch, J. C.; Wallace, Maria F.

2015-01-01

In today's technological age, visions for technology integration in the classroom continue to be explored and examined. Digital game-based learning is one way to purposefully integrate technology while maintaining a focus on learning objectives. This case study sought to understand agriscience teachers' experiences implementing digital game-based…

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…

Merlin C. Wittrock's Enduring Contributions to the Science of Learning

ERIC Educational Resources Information Center

Mayer, Richard E.

2010-01-01

Among his many accomplishments in educational psychology, Merlin C. Wittrock is perhaps best remembered for his enduring contributions to the science of learning. His vision of how learning works is best explicated in articles published in "Educational Psychologist" (Wittrock, 1974, 1978, 1989, 1991, 1992), beginning with his classic 1974 article,…

Strategy Approach for eLearning 2.0 Deployment in Universities

ERIC Educational Resources Information Center

Casquero, Oskar; Portillo, Javier; Ovelar, Ramon; Romo, Jesus; Benito, Manuel

2010-01-01

The institutionally powered Personal Learning Environment (iPLE) constitutes our vision of how Web 2.0 technologies, people arrangement and data sharing could be applied for delivering open, flexible, distributed and learner-centred learning environments to university members. Based on the iPLE, this paper explores a strategy approach that…

"In Loco Communitas": Service-Learning and the Liberal Arts.

ERIC Educational Resources Information Center

Schwartzman, Roy; Phelps, Greg A.

This essay places service-learning within the liberal arts tradition of empowering others to help themselves. Such a contextualization departs from visions of the student as consumer or customer and education as a means to gain economic advantage in a competitive market. Attention then turns to how even well-intentioned service-learning projects…

The Impact of a Sports Vision Training Program in Youth Field Hockey Players

PubMed Central

Schwab, Sebastian; Memmert, Daniel

2012-01-01

The aim of this study was to investigate whether a sports vision training program improves the visual performance of youth male field hockey players, ages 12 to 16 years, after an intervention of six weeks compared to a control group with no specific sports vision training. The choice reaction time task at the D2 board (Learning Task I), the functional field of view task (Learning Task II) and the multiple object tracking (MOT) task (Transfer Task) were assessed before and after the intervention and again six weeks after the second test. Analyzes showed significant differences between the two groups for the choice reaction time task at the D2 board and the functional field of view task, with significant improvements for the intervention group and none for the control group. For the transfer task, we could not find statistically significant improvements for either group. The results of this study are discussed in terms of theoretical and practical implications. Key pointsPerceptual training with youth field hockey playersCan a sports vision training program improve the visual performance of youth male field hockey players, ages 12 to 16 years, after an intervention of six weeks compared to a control group with no specific sports vision training?The intervention was performed in the “VisuLab” as DynamicEye® SportsVision Training at the German Sport University Cologne.We ran a series of 3 two-factor univariate analysis of variance (ANOVA) with repeated measures on both within subject independent variables (group; measuring point) to examine the effects on central perception, peripheral perception and choice reaction time.The present study shows an improvement of certain visual abilities with the help of the sports vision training program. PMID:24150071

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.

Computer vision

NASA Technical Reports Server (NTRS)

Gennery, D.; Cunningham, R.; Saund, E.; High, J.; Ruoff, C.

1981-01-01

The field of computer vision is surveyed and assessed, key research issues are identified, and possibilities for a future vision system are discussed. The problems of descriptions of two and three dimensional worlds are discussed. The representation of such features as texture, edges, curves, and corners are detailed. Recognition methods are described in which cross correlation coefficients are maximized or numerical values for a set of features are measured. Object tracking is discussed in terms of the robust matching algorithms that must be devised. Stereo vision, camera control and calibration, and the hardware and systems architecture are discussed.

Screening for Physical Problems in Classrooms for Severely Handicapped Students.

ERIC Educational Resources Information Center

Dever, Richard; Knapczyk, Dennis

1980-01-01

The authors present a screening device with which teachers of severely handicapped students may detect the presence of a physical problem. The screening approach covers vision, auditory problems, seizures, orthopedic problems, and pain. (CL)

Computer Use and Vision-Related Problems Among University Students In Ajman, United Arab Emirate

PubMed Central

Shantakumari, N; Eldeeb, R; Sreedharan, J; Gopal, K

2014-01-01

Background: The extensive use of computers as medium of teaching and learning in universities necessitates introspection into the extent of computer related health disorders among student population. Aim: This study was undertaken to assess the pattern of computer usage and related visual problems, among University students in Ajman, United Arab Emirates. Materials and Methods: A total of 500 Students studying in Gulf Medical University, Ajman and Ajman University of Science and Technology were recruited into this study. Demographic characteristics, pattern of usage of computers and associated visual symptoms were recorded in a validated self-administered questionnaire. Chi-square test was used to determine the significance of the observed differences between the variables. The level of statistical significance was at P < 0.05. The crude odds ratio (OR) was determined using simple binary logistic regression and adjusted OR was calculated using the multiple logistic regression. Results: The mean age of participants was 20.4 (3.2) years. The analysis of racial data reveals that 50% (236/471) students were from Middle East, 32% (151/471) from other parts of Asia, 11% (52/471) from Africa, 4% (19/471) from America and 3% (14/471) from Europe. The most common visual problems reported among computer users were headache - 53.3% (251/471), burning sensation in the eyes - 54.8% (258/471) and tired eyes - 48% (226/471). Female students were found to be at a higher risk. Nearly 72% of students reported frequent interruption of computer work. Headache caused interruption of work in 43.85% (110/168) of the students while tired eyes caused interruption of work in 43.5% (98/168) of the students. When the screen was viewed at distance more than 50 cm, the prevalence of headaches decreased by 38% (50-100 cm – OR: 0.62, 95% of the confidence interval [CI]: 0.42-0.92). Prevalence of tired eyes increased by 89% when screen filters were not used (OR: 1.894, 95% CI: 1.065-3.368). Conclusion: High prevalence of vision related problems was noted among university students. Sustained periods of close screen work without screen filters were found to be associated with occurrence of the symptoms and increased interruptions of work of the students. There is a need to increase the ergonomic awareness among students and corrective measures need to be implemented to reduce the impact of computer related vision problems. PMID:24761249

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

Colour vision deficiency and physics teaching

NASA Astrophysics Data System (ADS)

Maule, Louise; Featonby, David

2016-05-01

1 in 12 males suffer from some form of colour vision deficiency (CVD) which in the present colour dominated world of education presentation can be a severe disadvantage. Although aware of ‘colourblindness’ most teachers make little or no adjustment for these pupils for whom tasks may be more difficult. This article examines colour vision deficiency and looks at ways in which we can help the many students who have this problem.

Learning of perceptual grouping for object segmentation on RGB-D data☆

PubMed Central

Richtsfeld, Andreas; Mörwald, Thomas; Prankl, Johann; Zillich, Michael; Vincze, Markus

2014-01-01

Object segmentation of unknown objects with arbitrary shape in cluttered scenes is an ambitious goal in computer vision and became a great impulse with the introduction of cheap and powerful RGB-D sensors. We introduce a framework for segmenting RGB-D images where data is processed in a hierarchical fashion. After pre-clustering on pixel level parametric surface patches are estimated. Different relations between patch-pairs are calculated, which we derive from perceptual grouping principles, and support vector machine classification is employed to learn Perceptual Grouping. Finally, we show that object hypotheses generation with Graph-Cut finds a globally optimal solution and prevents wrong grouping. Our framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. We also tackle the problem of segmenting objects when they are partially occluded. The work is evaluated on publicly available object segmentation databases and also compared with state-of-the-art work of object segmentation. PMID:24478571

Image Segmentation for Connectomics Using Machine Learning

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

Tasdizen, Tolga; Seyedhosseini, Mojtaba; Liu, TIng

Reconstruction of neural circuits at the microscopic scale of individual neurons and synapses, also known as connectomics, is an important challenge for neuroscience. While an important motivation of connectomics is providing anatomical ground truth for neural circuit models, the ability to decipher neural wiring maps at the individual cell level is also important in studies of many neurodegenerative diseases. Reconstruction of a neural circuit at the individual neuron level requires the use of electron microscopy images due to their extremely high resolution. Computational challenges include pixel-by-pixel annotation of these images into classes such as cell membrane, mitochondria and synaptic vesiclesmore » and the segmentation of individual neurons. State-of-the-art image analysis solutions are still far from the accuracy and robustness of human vision and biologists are still limited to studying small neural circuits using mostly manual analysis. In this chapter, we describe our image analysis pipeline that makes use of novel supervised machine learning techniques to tackle this problem.« less

Proactive learning for artificial cognitive systems

NASA Astrophysics Data System (ADS)

Lee, Soo-Young

2010-04-01

The Artificial Cognitive Systems (ACS) will be developed for human-like functions such as vision, auditory, inference, and behavior. Especially, computational models and artificial HW/SW systems will be devised for Proactive Learning (PL) and Self-Identity (SI). The PL model provides bilateral interactions between robot and unknown environment (people, other robots, cyberspace). For the situation awareness in unknown environment it is required to receive audiovisual signals and to accumulate knowledge. If the knowledge is not enough, the PL should improve by itself though internet and others. For human-oriented decision making it is also required for the robot to have self-identify and emotion. Finally, the developed models and system will be mounted on a robot for the human-robot co-existing society. The developed ACS will be tested against the new Turing Test for the situation awareness. The Test problems will consist of several video clips, and the performance of the ACSs will be compared against those of human with several levels of cognitive ability.

Critical Response Protocol

ERIC Educational Resources Information Center

Ellingson, Charlene; Roehrig, Gillian; Bakkum, Kris; Dubinsky, Janet M.

2016-01-01

This article introduces the Critical Response Protocol (CRP), an arts-based technique that engages students in equitable critical discourse and aligns with the "Next Generation Science Standards" vision for providing students opportunities for language learning while advancing science learning (NGSS Lead States 2013). CRP helps teachers…

Starting in School

ERIC Educational Resources Information Center

Albertine, Susan

2012-01-01

Through its signature initiative, Liberal Education and America's Promise (LEAP), the Association of American Colleges and Universities (AAC&U) is promoting a vision for learning that begins in school: Starting in School . . . Rigorous and rich curriculum focused on the essential learning outcomes; comprehensive, individualized, and…

Resources for the Visually Impaired.

ERIC Educational Resources Information Center

Oseroff, Andrew; And Others

1987-01-01

Suggestions for resource room teachers working with visually impaired learning disabled students include: consideration of students' unique learning needs; assessment of functional vision; use of assistive devices (such as closed-circuit television); classroom arrangement that facilitates organization and movement; and basic skills instruction…

A nationwide population-based study of low vision and blindness in South Korea.

PubMed

Park, Shin Hae; Lee, Ji Sung; Heo, Hwan; Suh, Young-Woo; Kim, Seung-Hyun; Lim, Key Hwan; Moon, Nam Ju; Lee, Sung Jin; Park, Song Hee; Baek, Seung-Hee

2014-12-18

To investigate the prevalence and associated risk factors of low vision and blindness in the Korean population. This cross-sectional, population-based study examined the ophthalmologic data of 22,135 Koreans aged ≥5 years from the fifth Korea National Health and Nutrition Examination Survey (KNHANES V, 2010-2012). According to the World Health Organization criteria, blindness was defined as visual acuity (VA) less than 20/400 in the better-seeing eye, and low vision as VA of 20/60 or worse but 20/400 or better in the better-seeing eye. The prevalence rates were calculated from either presenting VA (PVA) or best-corrected VA (BCVA). Multivariate regression analysis was conducted for adults aged ≥20 years. The overall prevalence rates of PVA-defined low vision and blindness were 4.98% and 0.26%, respectively, and those of BCVA-defined low vision and blindness were 0.46% and 0.05%, respectively. Prevalence increased rapidly above the age of 70 years. For subjects aged ≥70 years, the population-weighted prevalence rates of low vision, based on PVA and BCVA, were 12.85% and 3.87%, respectively, and the corresponding rates of blindness were 0.49% and 0.42%, respectively. The presenting vision problems were significantly associated with age (younger adults or elderly subjects), female sex, low educational level, and lowest household income, whereas the best-corrected vision problems were associated with age ≥ 70 years, a low educational level, and rural residence. This population-based study provides useful information for planning optimal public eye health care services in South Korea. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

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…

Changing Visions of Excellence in Ontario School Policy: The Cases of "Living and Learning" and "For the Love of Learning"

ERIC Educational Resources Information Center

Bruno-Jofre, Rosa; Hills, George

2011-01-01

In this essay, Rosa Bruno-Jofre and George Hills examine two major Ontario policy documents: 1968's "Living and Learning" and 1994's "For the Love of Learning." The purpose is, first, to gain insight into the uses of the term "excellence" in the context of discourse about educational aims and evaluation, and, second,…

Vision-based coaching: optimizing resources for leader development

PubMed Central

Passarelli, Angela M.

2015-01-01

Leaders develop in the direction of their dreams, not in the direction of their deficits. Yet many coaching interactions intended to promote a leader’s development fail to leverage the benefits of the individual’s personal vision. Drawing on intentional change theory, this article postulates that coaching interactions that emphasize a leader’s personal vision (future aspirations and core identity) evoke a psychophysiological state characterized by positive emotions, cognitive openness, and optimal neurobiological functioning for complex goal pursuit. Vision-based coaching, via this psychophysiological state, generates a host of relational and motivational resources critical to the developmental process. These resources include: formation of a positive coaching relationship, expansion of the leader’s identity, increased vitality, activation of learning goals, and a promotion–orientation. Organizational outcomes as well as limitations to vision-based coaching are discussed. PMID:25926803

A prospective investigation of physical health outcomes in abused and neglected children: new findings from a 30-year follow-up.

PubMed

Widom, Cathy Spatz; Czaja, Sally J; Bentley, Tyrone; Johnson, Mark S

2012-06-01

We investigated whether abused and neglected children are at risk for negative physical health outcomes in adulthood. Using a prospective cohort design, we matched children (aged 0-11 years) with documented cases of physical and sexual abuse and neglect from a US Midwestern county during 1967 through 1971 with nonmaltreated children. Both groups completed a medical status examination (measured health outcomes and blood tests) and interview during 2003 through 2005 (mean age=41.2 years). After adjusting for age, gender, and race, child maltreatment predicted above normal hemoglobin, lower albumin levels, poor peak airflow, and vision problems in adulthood. Physical abuse predicted malnutrition, albumin, blood urea nitrogen, and hemoglobin A1C. Neglect predicted hemoglobin A1C, albumin, poor peak airflow, and oral health and vision problems, Sexual abuse predicted hepatitis C and oral health problems. Additional controls for childhood socioeconomic status, adult socioeconomic status, unhealthy behaviors, smoking, and mental health problems play varying roles in attenuating or intensifying these relationships. Child abuse and neglect affect long-term health status-increasing risk for diabetes, lung disease, malnutrition, and vision problems-and support the need for early health care prevention.

A neural network based artificial vision system for licence plate recognition.

PubMed

Draghici, S

1997-02-01

This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

Application of Crack Identification Techniques for an Aging Concrete Bridge Inspection Using an Unmanned Aerial Vehicle.

PubMed

Kim, In-Ho; Jeon, Haemin; Baek, Seung-Chan; Hong, Won-Hwa; Jung, Hyung-Jo

2018-06-08

Bridge inspection using unmanned aerial vehicles (UAV) with high performance vision sensors has received considerable attention due to its safety and reliability. As bridges become obsolete, the number of bridges that need to be inspected increases, and they require much maintenance cost. Therefore, a bridge inspection method based on UAV with vision sensors is proposed as one of the promising strategies to maintain bridges. In this paper, a crack identification method by using a commercial UAV with a high resolution vision sensor is investigated in an aging concrete bridge. First, a point cloud-based background model is generated in the preliminary flight. Then, cracks on the structural surface are detected with the deep learning algorithm, and their thickness and length are calculated. In the deep learning method, region with convolutional neural networks (R-CNN)-based transfer learning is applied. As a result, a new network for the 384 collected crack images of 256 × 256 pixel resolution is generated from the pre-trained network. A field test is conducted to verify the proposed approach, and the experimental results proved that the UAV-based bridge inspection is effective at identifying and quantifying the cracks on the structures.

Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision.

PubMed

Wolff, J Gerard

2014-01-01

The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

Impact of computer use on children's vision.

PubMed

Kozeis, N

2009-10-01

Today, millions of children use computers on a daily basis. Extensive viewing of the computer screen can lead to eye discomfort, fatigue, blurred vision and headaches, dry eyes and other symptoms of eyestrain. These symptoms may be caused by poor lighting, glare, an improper work station set-up, vision problems of which the person was not previously aware, or a combination of these factors. Children can experience many of the same symptoms related to computer use as adults. However, some unique aspects of how children use computers may make them more susceptible than adults to the development of these problems. In this study, the most common eye symptoms related to computer use in childhood, the possible causes and ways to avoid them are reviewed.

Helicopter flights with night-vision goggles: Human factors aspects

NASA Technical Reports Server (NTRS)

Brickner, Michael S.

1989-01-01

Night-vision goggles (NVGs) and, in particular, the advanced, helmet-mounted Aviators Night-Vision-Imaging System (ANVIS) allows helicopter pilots to perform low-level flight at night. It consists of light intensifier tubes which amplify low-intensity ambient illumination (star and moon light) and an optical system which together produce a bright image of the scene. However, these NVGs do not turn night into day, and, while they may often provide significant advantages over unaided night flight, they may also result in visual fatigue, high workload, and safety hazards. These problems reflect both system limitations and human-factors issues. A brief description of the technical characteristics of NVGs and of human night-vision capabilities is followed by a description and analysis of specific perceptual problems which occur with the use of NVGs in flight. Some of the issues addressed include: limitations imposed by a restricted field of view; problems related to binocular rivalry; the consequences of inappropriate focusing of the eye; the effects of ambient illumination levels and of various types of terrain on image quality; difficulties in distance and slope estimation; effects of dazzling; and visual fatigue and superimposed symbology. These issues are described and analyzed in terms of their possible consequences on helicopter pilot performance. The additional influence of individual differences among pilots is emphasized. Thermal imaging systems (forward looking infrared (FLIR)) are described briefly and compared to light intensifier systems (NVGs). Many of the phenomena which are described are not readily understood. More research is required to better understand the human-factors problems created by the use of NVGs and other night-vision aids, to enhance system design, and to improve training methods and simulation techniques.

Six years of vision screening tests in pre-school children in kindergartens of Wroclaw

NASA Astrophysics Data System (ADS)

Szmigiel, Marta; Geniusz, Malwina; Szmigiel, Ireneusz

2017-09-01

Detection of vision defects of a child without professional knowledge is not easy. Very often, the parents of a small child does not know that their child sees incorrect. Also the youngster, not knowing any other way of seeing, does not know that it is not the best. While the vision of a small child is not yet fully formed, it is worth checking them very early. Defects detected early gives opportunity for the correction of anomalies, which might give the effect of the normal development of vision. According to the indications, the American Optometric Association (AOA) control eye examination should be performed between the ages of 6 months to 3 years, before going to school and then every two years. Members of SPIE Student Chapter, in cooperation with the Visual Optics Group working on the Department of Optics and Photonics (Faculty of Fundamental Problems, Wroclaw University of Science and Technology) for 6 years offer selected kindergartens of Wroclaw participation in project "Screening vision tests in pre-school children". Depending on the number of involved members of the student chapter and willing to cooperate students of Ophthalmology and Optometry, vision screening test was carried out in up to eight kindergartens every year. The basic purpose of screening vision test is to detect visual defects to start the correction so early in life as possible, while increasing the efficiency of the child's visual potential. The surrounding community is in fact more than enough examples of late diagnose vision problems, which resulted in lack of opportunity or treatment failure

Inhabiting Culture: Spanish Anarchists' Vision of Cultural Learning through Aesthetics in the Nineteenth and Early Twentieth Centuries

ERIC Educational Resources Information Center

Collelldemont, Eulàlia; Vilanou, Conrad

2017-01-01

Revisions of textual and audio-visual materials reveal the educational vision of Spanish anarchists. Through research, we have discovered the importance of aesthetical education and art in general for this protest political party. By studying the three key historical moments of the movement (1868-1939/1901-1910/1910-1936-1939) we have traced the…

The Self-Concepts of Spanish Children and Adolescents with Low Vision and Their Sighted Peers.

ERIC Educational Resources Information Center

Lopez-Justicia, Maria Dolores; Pichardo, Maria Carmen; Amezcua, Juan Antonio; Fernandez, Eduardo

2001-01-01

Three studies of Spanish students with low vision, aged 4-7, 8-11, and 12-17, found that, overall, the participants' scores for some dimensions of self-concept were lower than those of comparison groups of sighted students. Teaching strategies such as cooperative learning are suggested to help improve the self-concept and academic performance of…

Developing the Vision: An L4L Job Description for the 21st Century

ERIC Educational Resources Information Center

Ballard, Susan

2009-01-01

The release of AASL's "Standards for the 21st-Century Learner" and "Empowering Learners: Guidelines for School Library Media Programs" has provided school library media specialists with the opportunity to "develop new visions for learning" (AASL 2009), and to rethink what their roles are, and what skills and characteristics are required of them to…

Transformation to a Customer-Oriented Perspective through Action Learning in Product and Service Development

ERIC Educational Resources Information Center

Olsson, Annika

2007-01-01

Customer orientation is strongly visible in the visions and strategies of most organizations, but how do these visions and strategies move from intentions to practice? This question provides the focus for this research which aims to acquire deeper insights into this process. The point of departure is the change in perspective from a product to a…

From Spoke to Hub: Transforming Organizational Vision and Strategy With Story and Visual Art

ERIC Educational Resources Information Center

Tyler, Jo A.

2015-01-01

This article reports on a case study at an inner-city nonprofit service agency that inquired into the ways integration of storytelling and visual art as a method of adult learning and way of knowing might influence the process of strategic visioning and planning in a nonprofit organization. The case study focuses on data collected through…

Instructional Partnerships to Extend Learning in Urban High Schools: Lessons from New York City and Boston

ERIC Educational Resources Information Center

Foley, Eileen M.; Allender, Sara; Cooc, North; Edwards, Sara; Riley, Derek R.; Reisner, Elizabeth R.

2009-01-01

Late in 2007 New Visions for Public Schools, a New York City reform organization, received a grant from the C.S. Mott Foundation to organize select high schools and community partners into delivery systems that could improve student achievement. New Visions asked Policy Studies Associates, Inc. to provide research support for this effort in the…

Attribute-based classification for zero-shot visual object categorization.

PubMed

Lampert, Christoph H; Nickisch, Hannes; Harmeling, Stefan

2014-03-01

We study the problem of object recognition for categories for which we have no training examples, a task also called zero--data or zero-shot learning. This situation has hardly been studied in computer vision research, even though it occurs frequently; the world contains tens of thousands of different object classes, and image collections have been formed and suitably annotated for only a few of them. To tackle the problem, we introduce attribute-based classification: Objects are identified based on a high-level description that is phrased in terms of semantic attributes, such as the object's color or shape. Because the identification of each such property transcends the specific learning task at hand, the attribute classifiers can be prelearned independently, for example, from existing image data sets unrelated to the current task. Afterward, new classes can be detected based on their attribute representation, without the need for a new training phase. In this paper, we also introduce a new data set, Animals with Attributes, of over 30,000 images of 50 animal classes, annotated with 85 semantic attributes. Extensive experiments on this and two more data sets show that attribute-based classification indeed is able to categorize images without access to any training images of the target classes.

Figure-Ground Segmentation Using Factor Graphs

PubMed Central

Shen, Huiying; Coughlan, James; Ivanchenko, Volodymyr

2009-01-01

Foreground-background segmentation has recently been applied [26,12] to the detection and segmentation of specific objects or structures of interest from the background as an efficient alternative to techniques such as deformable templates [27]. We introduce a graphical model (i.e. Markov random field)-based formulation of structure-specific figure-ground segmentation based on simple geometric features extracted from an image, such as local configurations of linear features, that are characteristic of the desired figure structure. Our formulation is novel in that it is based on factor graphs, which are graphical models that encode interactions among arbitrary numbers of random variables. The ability of factor graphs to express interactions higher than pairwise order (the highest order encountered in most graphical models used in computer vision) is useful for modeling a variety of pattern recognition problems. In particular, we show how this property makes factor graphs a natural framework for performing grouping and segmentation, and demonstrate that the factor graph framework emerges naturally from a simple maximum entropy model of figure-ground segmentation. We cast our approach in a learning framework, in which the contributions of multiple grouping cues are learned from training data, and apply our framework to the problem of finding printed text in natural scenes. Experimental results are described, including a performance analysis that demonstrates the feasibility of the approach. PMID:20160994

On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

PubMed Central

Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

2015-01-01

Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration.

PubMed

Chen, Yunjin; Pock, Thomas

2017-06-01

Image restoration is a long-standing problem in low-level computer vision with many interesting applications. We describe a flexible learning framework based on the concept of nonlinear reaction diffusion models for various image restoration problems. By embodying recent improvements in nonlinear diffusion models, we propose a dynamic nonlinear reaction diffusion model with time-dependent parameters (i.e., linear filters and influence functions). In contrast to previous nonlinear diffusion models, all the parameters, including the filters and the influence functions, are simultaneously learned from training data through a loss based approach. We call this approach TNRD-Trainable Nonlinear Reaction Diffusion. The TNRD approach is applicable for a variety of image restoration tasks by incorporating appropriate reaction force. We demonstrate its capabilities with three representative applications, Gaussian image denoising, single image super resolution and JPEG deblocking. Experiments show that our trained nonlinear diffusion models largely benefit from the training of the parameters and finally lead to the best reported performance on common test datasets for the tested applications. Our trained models preserve the structural simplicity of diffusion models and take only a small number of diffusion steps, thus are highly efficient. Moreover, they are also well-suited for parallel computation on GPUs, which makes the inference procedure extremely fast.

Steeped in Study: Remote Canadian School District Approaches Professional Learning with a Passion

ERIC Educational Resources Information Center

Richardson, Joan

2005-01-01

Relationships and leadership, that, in a nutshell, is the vision of professional learning in the remote Northern Lights School Division in Alberta, Canada. This article describes the professional learning provided by Northern Lights, which has been building its capacity for teacher and leadership growth for more than 13 years. The division: (1)…