Combination of inquiry learning model and computer simulation to improve mastery concept and the correlation with critical thinking skills (CTS)

NASA Astrophysics Data System (ADS)

Nugraha, Muhamad Gina; Kaniawati, Ida; Rusdiana, Dadi; Kirana, Kartika Hajar

2016-02-01

Among the purposes of physics learning at high school is to master the physics concepts and cultivate scientific attitude (including critical attitude), develop inductive and deductive reasoning skills. According to Ennis et al., inductive and deductive reasoning skills are part of critical thinking. Based on preliminary studies, both of the competence are lack achieved, it is seen from student learning outcomes is low and learning processes that are not conducive to cultivate critical thinking (teacher-centered learning). One of learning model that predicted can increase mastery concepts and train CTS is inquiry learning model aided computer simulations. In this model, students were given the opportunity to be actively involved in the experiment and also get a good explanation with the computer simulations. From research with randomized control group pretest-posttest design, we found that the inquiry learning model aided computer simulations can significantly improve students' mastery concepts than the conventional (teacher-centered) method. With inquiry learning model aided computer simulations, 20% of students have high CTS, 63.3% were medium and 16.7% were low. CTS greatly contribute to the students' mastery concept with a correlation coefficient of 0.697 and quite contribute to the enhancement mastery concept with a correlation coefficient of 0.603.

Computer Numerical Control: Instructional Manual. The North Dakota High Technology Mobile Laboratory Project.

ERIC Educational Resources Information Center

Sinn, John W.

This instructional manual contains five learning activity packets for use in a workshop on computer numerical control for computer-aided manufacturing. The lessons cover the following topics: introduction to computer-aided manufacturing, understanding the lathe, using the computer, computer numerically controlled part programming, and executing a…

Learning and Optimization of Cognitive Capabilities. Final Project Report.

ERIC Educational Resources Information Center

Lumsdaine, A.A.; And Others

The work of a three-year series of experimental studies of human cognition is summarized in this report. Proglem solving and learning in man-machine interaction was investigated, as well as relevant variables and processes. The work included four separate projects: (1) computer-aided problem solving, (2) computer-aided instruction techniques, (3)…

Teaching Neuroanatomy Using Computer-Aided Learning: What Makes for Successful Outcomes?

ERIC Educational Resources Information Center

Svirko, Elena; Mellanby, Jane

2017-01-01

Computer-aided learning (CAL) is an integral part of many medical courses. The neuroscience course at Oxford University for medical students includes CAL course of neuroanatomy. CAL is particularly suited to this since neuroanatomy requires much detailed three-dimensional visualization, which can be presented on screen. The CAL course was…

Computer Aided Learning of Mathematics: Software Evaluation

ERIC Educational Resources Information Center

Yushau, B.; Bokhari, M. A.; Wessels, D. C. J.

2004-01-01

Computer Aided Learning of Mathematics (CALM) has been in use for some time in the Prep-Year Mathematics Program at King Fahd University of Petroleum & Minerals. Different kinds of software (both locally designed and imported) have been used in the quest of optimizing the recitation/problem session hour of the mathematics classes. This paper…

Teaching Computer-Aided Design of Fluid Flow and Heat Transfer Engineering Equipment.

ERIC Educational Resources Information Center

Gosman, A. D.; And Others

1979-01-01

Describes a teaching program for fluid mechanics and heat transfer which contains both computer aided learning (CAL) and computer aided design (CAD) components and argues that the understanding of the physical and numerical modeling taught in the CAL course is essential to the proper implementation of CAD. (Author/CMV)

Relationships among Learning Styles and Motivation with Computer-Aided Instruction in an Agronomy Course

ERIC Educational Resources Information Center

McAndrews, Gina M.; Mullen, Russell E.; Chadwick, Scott A.

2005-01-01

Multi-media learning tools were developed to enhance student learning for an introductory agronomy course at Iowa State University. During fall 2002, the new interactive computer program, called Computer Interactive Multimedia Program for Learning Enhancement (CIMPLE) was incorporated into the teaching, learning, and assessment processes of the…

The Effects of Cooperative and Individualistic Learning Structures on Achievement in a College-Level Computer-Aided Drafting Course

ERIC Educational Resources Information Center

Swab, A. Geoffrey

2012-01-01

This study of cooperative learning in post-secondary engineering education investigated achievement of engineering students enrolled in two intact sections of a computer-aided drafting (CAD) course. Quasi-experimental and qualitative methods were employed in comparing student achievement resulting from out-of-class cooperative and individualistic…

Computer Support of Operator Training: Constructing and Testing a Prototype of a CAL (Computer Aided Learning) Supported Simulation Environment.

ERIC Educational Resources Information Center

Zillesen, P. G. van Schaick; And Others

Instructional feedback given to the learners during computer simulation sessions may be greatly improved by integrating educational computer simulation programs with hypermedia-based computer-assisted learning (CAL) materials. A prototype of a learning environment of this type called BRINE PURIFICATION was developed for use in corporate training…

Adaptive Device Context Based Mobile Learning Systems

ERIC Educational Resources Information Center

Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

2011-01-01

Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

Using Microcomputers To Help Learning Disabled Student with Arithmetic Difficulties.

ERIC Educational Resources Information Center

Brevil, Margarette

The use of microcomputers to help the learning disabled increase their arithmetic skills is examined. The microcomputer should be used to aid the learning disabled student to practice the concepts taught by the teacher. Computer-aided instruction such as drill and practice may help the learning disabled student because it gives immediate feedback…

Implementation and Evaluation of Computer-Aided Mandarin Phonemes Training System for Hearing-Impaired Students

ERIC Educational Resources Information Center

Yang, Hui-Jen; Lay, Yun-Long

2005-01-01

A computer-aided Mandarin phonemes training (CAMPT) system was developed and evaluated for training hearing-impaired students in their pronunciation of Mandarin phonemes. Deaf or hearing-impaired people have difficulty hearing their own voice, hence most of them cannot learn how to speak. Phonemes are the basis for learning to read and speak in…

Ten years of CLIVE (Computer-Aided Learning in Veterinary Education) in the United Kingdom.

PubMed

Dale, Vicki H M; McConnell, Gill; Short, Andrew; Sullivan, Martin

2005-01-01

This paper outlines the work of the CLIVE (Computer-Aided Learning in Veterinary Education) project over a 10-year period, set against the backdrop of changes in education policy and learning technology developments. The consortium of six UK veterinary schools and 14 international Associate Member Schools has been very successful. Sustaining these partnerships requires that the project redefine itself and adapt to cater to the diverse learning needs of today's students and to changing professional and societal needs on an international scale.

Computers in medical education 1: evaluation of a problem-orientated learning package.

PubMed

Devitt, P; Palmer, E

1998-04-01

A computer-based learning package has been developed, aimed at expanding students' knowledge base, as well as improving data-handling abilities and clinical problem-solving skills. The program was evaluated by monitoring its use by students, canvassing users' opinions and measuring its effectiveness as a learning tool compared to tutorials on the same material. Evaluation was undertaken using three methods: initially, by a questionnaire on computers as a learning tool and the applicability of the content: second, through monitoring by the computer of student use, decisions and performance; finally, through pre- and post-test assessment of fifth-year students who either used a computer package or attended a tutorial on equivalent material. Most students provided positive comments on the learning material and expressed a willingness to see computer-aided learning (CAL) introduced into the curriculum. Over a 3-month period, 26 modules in the program were used on 1246 occasions. Objective measurement showed a significant gain in knowledge, data handling and problem-solving skills. Computer-aided learning is a valuable learning resource that deserves better attention in medical education. When used appropriately, the computer can be an effective learning resource, not only for the delivery of knowledge. but also to help students develop their problem-solving skills.

Computer-Based Aids for Learning, Job Performance, and Decision Making in Military Applications: Emergent Technology and Challenges

DTIC Science & Technology

2003-10-01

paper, which addresses the following questions: Is it worth it? What do we know about the value of technology applications in learning ( education and......fax) fletcher@ida.org SUMMARY Technology -based systems for education , training, and performance aiding (including decision aiding) may pose the

Computer Programmed Milling Machine Operations. High-Technology Training Module.

ERIC Educational Resources Information Center

Leonard, Dennis

This learning module for a high school metals and manufacturing course is designed to introduce the concept of computer-assisted machining (CAM). Through it, students learn how to set up and put data into the controller to machine a part. They also become familiar with computer-aided manufacturing and learn the advantages of computer numerical…

Computer-Assisted Instruction: One Aid for Teachers of Reading.

ERIC Educational Resources Information Center

Rauch, Margaret; Samojeden, Elizabeth

Computer assisted instruction (CAI), an instructional system with direct interaction between the student and the computer, can be a valuable aid for presenting new concepts, for reinforcing of selective skills, and for individualizing instruction. The advantages CAI provides include self-paced learning, more efficient allocation of classroom time,…

Development of an Interactive Computer-Based Learning Strategy to Assist in Teaching Water Quality Modelling

ERIC Educational Resources Information Center

Zigic, Sasha; Lemckert, Charles J.

2007-01-01

The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a…

Computer Aided Instruction: A Study of Student Evaluations and Academic Performance

ERIC Educational Resources Information Center

Collins, David; Deck, Alan; McCrickard, Myra

2008-01-01

Computer aided instruction (CAI) encompasses a broad range of computer technologies that supplement the classroom learning environment and can dramatically increase a student's access to information. Criticism of CAI generally focuses on two issues: it lacks an adequate foundation in educational theory and the software is difficult to implement…

Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

PubMed

Frost, Mary E; Derby, Dustin C; Haan, Andrea G

2013-01-01

Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

PubMed

Frost, Mary E; Derby, Dustin C; Haan, Andrea G

2013-06-27

Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

Virtual Bioinformatics Distance Learning Suite

ERIC Educational Resources Information Center

Tolvanen, Martti; Vihinen, Mauno

2004-01-01

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

The Use of Help Options in Multimedia Listening Environments to Aid Language Learning: A Review

ERIC Educational Resources Information Center

Mohsen, Mohammed Ali

2016-01-01

This paper provides a comprehensive review on the use of help options (HOs) in the multimedia listening context to aid listening comprehension (LC) and improve incidental vocabulary learning. The paper also aims to synthesize the research findings obtained from the use of HOs in Computer-Assisted Language Learning (CALL) literature and reveals the…

An Infrastructure for Web-Based Computer Assisted Learning

ERIC Educational Resources Information Center

Joy, Mike; Muzykantskii, Boris; Rawles, Simon; Evans, Michael

2002-01-01

We describe an initiative under way at Warwick to provide a technical foundation for computer aided learning and computer-assisted assessment tools, which allows a rich dialogue sensitive to individual students' response patterns. The system distinguishes between dialogues for individual problems and the linking of problems. This enables a subject…

Implementing Computer Algebra Enabled Questions for the Assessment and Learning of Mathematics

ERIC Educational Resources Information Center

Sangwin, Christopher J.; Naismith, Laura

2008-01-01

We present principles for the design of an online system to support computer algebra enabled questions for use within the teaching and learning of mathematics in higher education. The introduction of a computer algebra system (CAS) into a computer aided assessment (CAA) system affords sophisticated response processing of student provided answers.…

Computer Aided Self-Instruction Training with Impulsive Deaf Students and Learning Disabled Students: A Study on Teaching Reflective Thought. Education and Technology Series.

ERIC Educational Resources Information Center

Campbell, Donald S.; And Others

Two studies examined the effectiveness of self-instruction training via a specially developed computer program to modify the impulsive problem-solving behavior of 16 deaf and 10 learning disabled (aphasic) adolescents attending two special residential schools in Canada. In the control condition, students learned the Apple LOGO computing language…

Does Computer-Aided Formative Assessment Improve Learning Outcomes?

ERIC Educational Resources Information Center

Hannah, John; James, Alex; Williams, Phillipa

2014-01-01

Two first-year engineering mathematics courses used computer-aided assessment (CAA) to provide students with opportunities for formative assessment via a series of weekly quizzes. Most students used the assessment until they achieved very high (>90%) quiz scores. Although there is a positive correlation between these quiz marks and the final…

Computer-Aided Instruction.

ERIC Educational Resources Information Center

Hunt, Graham

This report discusses the impact of and presents guidelines for developing a computer-aided instructional (CAI) system. The first section discusses CAI in terms of the need for the countries of Asia to increase their economic self-sufficiency. The second section examines various theories on the nature of learning with special attention to the role…

A Model for Intelligent Computer-Aided Education Systems.

ERIC Educational Resources Information Center

Du Plessis, Johan P.; And Others

1995-01-01

Proposes a model for intelligent computer-aided education systems that is based on cooperative learning, constructive problem-solving, object-oriented programming, interactive user interfaces, and expert system techniques. Future research is discussed, and a prototype for teaching mathematics to 10- to 12-year-old students is appended. (LRW)

Computer-Aided Corrosion Program Management

NASA Technical Reports Server (NTRS)

MacDowell, Louis

2010-01-01

This viewgraph presentation reviews Computer-Aided Corrosion Program Management at John F. Kennedy Space Center. The contents include: 1) Corrosion at the Kennedy Space Center (KSC); 2) Requirements and Objectives; 3) Program Description, Background and History; 4) Approach and Implementation; 5) Challenges; 6) Lessons Learned; 7) Successes and Benefits; and 8) Summary and Conclusions.

INDIVIDUALIZING UNIVERSITY INSTRUCTION, EXPLORING COMPUTER POTENTIAL TO AID COLLEGE TEACHERS BY DIRECTING THE LEARNING PROCESS. INTER-UNIVERSITY PROJECT ONE, PUBLICATIONS SERIES.

ERIC Educational Resources Information Center

FALL, CHARLES R.

THIS DOCUMENT CONCLUDES THAT INSTRUCTION BY COMPUTER-BASED RESOURCE UNITS CAN FACILITATE LEARNING AND PROVIDE THE INSTRUCTOR WITH VALUABLE ASSISTANCE. BY PRE-PLANNING THE TEACHING-LEARNING SITUATION, RESOURCE UNITS CAN FREE THE INSTRUCTOR FOR DECISION-MAKING TASKS. RESOURCE UNITS CAN ALSO PROVIDE APPROPRIATE LEARNING GOALS AND STUDY GUIDES TO EACH…

On the convergence of nanotechnology and Big Data analysis for computer-aided diagnosis.

PubMed

Rodrigues, Jose F; Paulovich, Fernando V; de Oliveira, Maria Cf; de Oliveira, Osvaldo N

2016-04-01

An overview is provided of the challenges involved in building computer-aided diagnosis systems capable of precise medical diagnostics based on integration and interpretation of data from different sources and formats. The availability of massive amounts of data and computational methods associated with the Big Data paradigm has brought hope that such systems may soon be available in routine clinical practices, which is not the case today. We focus on visual and machine learning analysis of medical data acquired with varied nanotech-based techniques and on methods for Big Data infrastructure. Because diagnosis is essentially a classification task, we address the machine learning techniques with supervised and unsupervised classification, making a critical assessment of the progress already made in the medical field and the prospects for the near future. We also advocate that successful computer-aided diagnosis requires a merge of methods and concepts from nanotechnology and Big Data analysis.

The Impact of Microtechnology. A Case for Reassessing the Role of Computers in Learning.

ERIC Educational Resources Information Center

Alty, J. L.

1982-01-01

Reviews recent advances in microtechnology and describes the impact they will have on computer aided instruction and learning. It is suggested that distributed systems based on network technology will become widespread, and computer assisted guidance systems will be developed to assist new unskilled users. Eight references are given. (CHC)

A Computer-Aided Writing Program for Learning Disabled Adolescents.

ERIC Educational Resources Information Center

Fais, Laurie; Wanderman, Richard

The paper describes the application of a computer-assisted writing program in a special high school for learning disabled and dyslexic students and reports on a study of the program's effectiveness. Particular advantages of the Macintosh Computer for such a program are identified including use of the mouse pointing tool, graphic icons to identify…

A Functional Specification for a Programming Language for Computer Aided Learning Applications.

ERIC Educational Resources Information Center

National Research Council of Canada, Ottawa (Ontario).

In 1972 there were at least six different course authoring languages in use in Canada with little exchange of course materials between Computer Assisted Learning (CAL) centers. In order to improve facilities for producing "transportable" computer based course materials, a working panel undertook the definition of functional requirements of a user…

Microcomputers in Schools as a Teaching and Learning Aid.

ERIC Educational Resources Information Center

Trotman-Dickenson, D. I.

1986-01-01

Presents the findings of a survey of comprehensive and independent schools' use of microcomputers as teaching and learning aids in economics. Results suggest that use is wide spread but not intensive. Teachers allocate few hours to computer programs per year, have difficulty finding suitable software, and fail to encourage use by girls. (JDH)

A Course Which Used Programming to Aid Learning Various Mathematical Concepts.

ERIC Educational Resources Information Center

Day, Jane M.

A three unit mathematics course entitled Introduction to Computing evaluated the effectiveness of programing as an aid to learning math concepts and to developing student self-reliance. Sixteen students enrolled in the course at the College of Notre Dame in Belmont, California; one terminal was available, connected to the Stanford Computation…

CNC Programming I.

ERIC Educational Resources Information Center

Casey, Joe

This document contains five units for a course in computer numerical control (CNC) for computer-aided manufacturing. It is intended to familiarize students with the principles and techniques necessary to create proper CNC programs manually. Each unit consists of an introduction, instructional objectives, learning materials, learning activities,…

The Impact of Machine Translation and Computer-aided Translation on Translators

NASA Astrophysics Data System (ADS)

Peng, Hao

2018-03-01

Under the context of globalization, communications between countries and cultures are becoming increasingly frequent, which make it imperative to use some techniques to help translate. This paper is to explore the influence of computer-aided translation on translators, which is derived from the field of the computer-aided translation (CAT) and machine translation (MT). Followed by an introduction to the development of machine and computer-aided translation, it then depicts the technologies practicable to translators, which are trying to analyze the demand of designing the computer-aided translation so far in translation practice, and optimize the designation of computer-aided translation techniques, and analyze its operability in translation. The findings underline the advantages and disadvantages of MT and CAT tools, and the serviceability and future development of MT and CAT technologies. Finally, this thesis probes into the impact of these new technologies on translators in hope that more translators and translation researchers can learn to use such tools to improve their productivity.

A Study of the Use of Ontologies for Building Computer-Aided Control Engineering Self-Learning Educational Software

ERIC Educational Resources Information Center

García, Isaías; Benavides, Carmen; Alaiz, Héctor; Alonso, Angel

2013-01-01

This paper describes research on the use of knowledge models (ontologies) for building computer-aided educational software in the field of control engineering. Ontologies are able to represent in the computer a very rich conceptual model of a given domain. This model can be used later for a number of purposes in different software applications. In…

The Effects of Computer-Aided Instruction on Learning and Attitudes in Economic Principles Courses: Revised Results.

ERIC Educational Resources Information Center

Henry, Mark

1979-01-01

Recounts statistical inaccuracies in an article on computer-aided instruction in economics courses on the college level. The article, published in the J. Econ. Ed (Fall 1978), erroneously placed one student in the TIPS group instead of the control group. Implications of this alteration are discussed. (DB)

Computer-Aided Drafting. Education for Technology Employment.

ERIC Educational Resources Information Center

Northern Illinois Univ., De Kalb. Dept. of Technology.

This computer-aided drafting (CAD) curriculum was developed to provide drafting instructors in Illinois with a useful guide for relating an important new technological advance to the vocational classroom. The competency-based learning activity guides are written to be used with any CAD system being used at the secondary and postsecondary levels.…

A Visual Tool for Computer Supported Learning: The Robot Motion Planning Example

ERIC Educational Resources Information Center

Elnagar, Ashraf; Lulu, Leena

2007-01-01

We introduce an effective computer aided learning visual tool (CALVT) to teach graph-based applications. We present the robot motion planning problem as an example of such applications. The proposed tool can be used to simulate and/or further to implement practical systems in different areas of computer science such as graphics, computational…

Teaching Arabic with Technology at BYU: Learning from the Past to Bridge to the Future

ERIC Educational Resources Information Center

Bush, Michael D.; Browne, Jeremy M.

2004-01-01

Reporting in 1971 on research related to computer-based methods for teaching the Arabic writing system, Bunderson and Abboud cited the potential that computers have for language learning, a largely unfulfilled potential even in 2004. After a review of the relevant historical background for the justification of computer-aided language learning…

Aids to Computer-Based Multimedia Learning.

ERIC Educational Resources Information Center

Mayer, Richard E.; Moreno, Roxana

2002-01-01

Presents a cognitive theory of multimedia learning that draws on dual coding theory, cognitive load theory, and constructivist learning theory and derives some principles of instructional design for fostering multimedia learning. These include principles of multiple representation, contiguity, coherence, modality, and redundancy. (SLD)

How Can We Aid the Learning of Young Children with Computers

ERIC Educational Resources Information Center

Bork, Alfred

2004-01-01

A very important part of the learning process occurs during early childhood, before preschool and the first few grades. Teachers need to understand the characteristics of this early learning, and ask if they can be extended to later education. While the author's concern here is with computers, the results of such a study might also tell teachers…

The Effectiveness of Computer-Aid, Self-Instructional Programs in Dental Education: A Systematic Review of the Literature.

ERIC Educational Resources Information Center

Rosenberg, Harold; Grad, Helen A.; Matear, David W.

2003-01-01

Performed a systematic review of the published literature comparing computer-aided learning (CAL) with other teaching methods in dental education. Concluded that CAL is as effective as other methods of teaching and can be used as an adjunct to traditional education or as a means of self-instruction. (EV)

A Design Science Research Methodology for Developing a Computer-Aided Assessment Approach Using Method Marking Concept

ERIC Educational Resources Information Center

Genemo, Hussein; Miah, Shah Jahan; McAndrew, Alasdair

2016-01-01

Assessment has been defined as an authentic method that plays an important role in evaluating students' learning attitude in acquiring lifelong knowledge. Traditional methods of assessment including the Computer-Aided Assessment (CAA) for mathematics show limited ability to assess students' full work unless multi-step questions are sub-divided…

Computer-aided classification of lung nodules on computed tomography images via deep learning technique

PubMed Central

Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

2015-01-01

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. PMID:26346558

Computer-aided classification of lung nodules on computed tomography images via deep learning technique.

PubMed

Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

2015-01-01

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain.

An Instructor's Diagnostic Aid for Feedback in Training.

ERIC Educational Resources Information Center

Andrews, Dee H.; Uliano, Kevin C.

1988-01-01

Instructor's Diagnostic Aid for Feedback in Training (IDAFT) is a computer-assisted method based on error analysis, domains of learning, and events of instruction. Its use with Navy team instructors is currently being explored. (JOW)

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

PubMed

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

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 Use of an Online Learning and Teaching System for Monitoring Computer Aided Design Student Participation and Predicting Student Success

ERIC Educational Resources Information Center

Akhtar, S.; Warburton, S.; Xu, W.

2017-01-01

In this paper we report on the use of a purpose built Computer Support Collaborative learning environment designed to support lab-based CAD teaching through the monitoring of student participation and identified predictors of success. This was carried out by analysing data from the interactive learning system and correlating student behaviour with…

Assessment of the Effectiveness of the Educational Environment Supported by Computer Aided Presentations at Primary School Level

ERIC Educational Resources Information Center

Kose, Erdogan

2009-01-01

The objective of this study is to assess the effectiveness of the educational environment supported by computer aided presentations at primary school. The effectiveness of the environment has been evaluated in terms of students' learning and remembering what they have learnt. In the study, we have compared experimental group and control group in…

A novel approach to malignant-benign classification of pulmonary nodules by using ensemble learning classifiers.

PubMed

Tartar, A; Akan, A; Kilic, N

2014-01-01

Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this paper, a novel Computer-Aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. The proposed CAD system using ensemble learning classifiers, provides an important support to radiologists at the diagnosis process of the disease, achieves high classification performance. The proposed approach with bagging classifier results in 94.7 %, 90.0 % and 77.8 % classification sensitivities for benign, malignant and undetermined classes (89.5 % accuracy), respectively.

The Negotiation Model in Asynchronous Computer-Mediated Communication (CMC): Negotiation in Task-Based Email Exchanges

ERIC Educational Resources Information Center

Kitade, Keiko

2006-01-01

Based on recent studies, computer-mediated communication (CMC) has been considered a tool to aid in language learning on account of its distinctive interactional features. However, most studies have referred to "synchronous" CMC and neglected to investigate how "asynchronous" CMC contributes to language learning. Asynchronous CMC possesses…

Students’ Spatial Ability through Open-Ended Approach Aided by Cabri 3D

NASA Astrophysics Data System (ADS)

Priatna, N.

2017-09-01

The use of computer software such as Cabri 3D for learning activities is very unlimited. Students can adjust their learning speed according to their level of ability. Open-ended approach strongly supports the use of computer software in learning, because the goal of open-ended learning is to help developing creative activities and mathematical mindset of students through problem solving simultaneously. In other words, creative activities and mathematical mindset of students should be developed as much as possible in accordance with the ability of spatial ability of each student. Spatial ability is the ability of students in constructing and representing geometry models. This study aims to determine the improvement of spatial ability of junior high school students who obtained learning with open-ended approach aided by Cabri 3D. It adopted a quasi-experimental method with the non-randomized control group pretest-posttest design and the 2×3 factorial model. The instrument of the study is spatial ability test. Based on analysis of the data, it is found that the improvement of spatial ability of students who received open-ended learning aided by Cabri 3D was greater than students who received expository learning, both as a whole and based on the categories of students’ initial mathematical ability.

Effect of computer-aided instruction versus traditional modes on student PT's learning musculoskeletal special tests

NASA Astrophysics Data System (ADS)

Ford, Gregory Scott

2007-12-01

Title. Effect of computer-aided instruction versus traditional modes on student PT's learning musculoskeletal special tests. Problem. Lack of quantitative evidence to support the use of computer-aided instruction (CAI) in PT education for both the cognitive and psychomotor domains and lack of qualitative support as to an understanding why CAI may or may not be effective. Design. 3 group single-blind pre-test, immediate post-test, final post-test repeated measures with qualitative survey for the CAI group. Methods. Subjects were randomly assigned to CAI, live demonstration or textbook learning groups. Three novel special tests were instructed. Analysis of performance on written and practical examinations was conducted across the 3 repeated measures. A qualitative survey was completed by the CAI group post intervention. Results. CAI is equally as effective as live demonstration and textbook learning of musculoskeletal special tests in the cognitive domain, however, CAI was superior to live demonstration and textbook instruction at final post-testing. Significance. The significance of this research is that a gap in the literature of PT education needs to be bridged as it pertains to the effect of CAI on learning in both the cognitive and psychomotor domains as well as attempt to understand why CAI results in certain student performance. The methods of this study allowed for a wide range of generalizability to any and all PT programs across the country.

Applying Learning Diagnosis Diagram in Computer Aided Instructions: Research, Practice and Evaluation

ERIC Educational Resources Information Center

Wu, YuLung

2010-01-01

In Taiwan, when students learn in experiment-related courses, they are often grouped into several teams. The familiar method of grouping learning is "Cooperative Learning". A well-organized grouping strategy improves cooperative learning and increases the number of activities. This study proposes a novel pedagogical method by adopting…

Exploring Moodle Functionality for Managing Open Distance Learning E-Assessments

ERIC Educational Resources Information Center

Koneru, Indira

2017-01-01

Current and emerging technologies enable Open Distance Learning (ODL) institutions integrate e-Learning in innovative ways and add value to the existing teaching-learning and assessment processes. ODL e-Assessment systems have evolved from Computer Assisted/Aided Assessment (CAA) systems through intelligent assessment and feedback systems.…

How Learning Mathematics Can Be Made More Enjoyable

ERIC Educational Resources Information Center

D'Apice, Ciro; Manzo, Rosanna

2004-01-01

New information technologies can act as a Trojan horse offering activities that will require major changes in the teaching-learning process. Computer aided learning applications are able to offer advanced students the opportunity to improve their skills and to maintain their motivation. In the spirit of "learning by doing", they are…

Do pre-trained deep learning models improve computer-aided classification of digital mammograms?

NASA Astrophysics Data System (ADS)

Aboutalib, Sarah S.; Mohamed, Aly A.; Zuley, Margarita L.; Berg, Wendie A.; Luo, Yahong; Wu, Shandong

2018-02-01

Digital mammography screening is an important exam for the early detection of breast cancer and reduction in mortality. False positives leading to high recall rates, however, results in unnecessary negative consequences to patients and health care systems. In order to better aid radiologists, computer-aided tools can be utilized to improve distinction between image classifications and thus potentially reduce false recalls. The emergence of deep learning has shown promising results in the area of biomedical imaging data analysis. This study aimed to investigate deep learning and transfer learning methods that can improve digital mammography classification performance. In particular, we evaluated the effect of pre-training deep learning models with other imaging datasets in order to boost classification performance on a digital mammography dataset. Two types of datasets were used for pre-training: (1) a digitized film mammography dataset, and (2) a very large non-medical imaging dataset. By using either of these datasets to pre-train the network initially, and then fine-tuning with the digital mammography dataset, we found an increase in overall classification performance in comparison to a model without pre-training, with the very large non-medical dataset performing the best in improving the classification accuracy.

Author Languages, Authoring Systems, and Their Relation to the Changing Focus of Computer-Aided Language Learning.

ERIC Educational Resources Information Center

Sussex, Roland

1991-01-01

Considers how the effectiveness of computer-assisted language learning (CALL) has been hampered by language teachers who lack programing and software engineering expertise, and explores the limitations and potential contributions of author languages, programs, and environments in increasing the range of options for language teachers who are not…

Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

PubMed

van Ginneken, Bram

2017-03-01

Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

Enhancing a Multi-body Mechanism with Learning-Aided Cues in an Augmented Reality Environment

NASA Astrophysics Data System (ADS)

Singh Sidhu, Manjit

2013-06-01

Augmented Reality (AR) is a potential area of research for education, covering issues such as tracking and calibration, and realistic rendering of virtual objects. The ability to augment real world with virtual information has opened the possibility of using AR technology in areas such as education and training as well. In the domain of Computer Aided Learning (CAL), researchers have long been looking into enhancing the effectiveness of the teaching and learning process by providing cues that could assist learners to better comprehend the materials presented. Although a number of works were done looking into the effectiveness of learning-aided cues, but none has really addressed this issue for AR-based learning solutions. This paper discusses the design and model of an AR based software that uses visual cues to enhance the learning process and the outcome perception results of the cues.

E-Learning - best Practice in Photogrammetry, Remote Sensing and GIS - Status and Challenges

NASA Astrophysics Data System (ADS)

König, G.; Shih, P. T. Y.; Katterfeld, C.

2012-07-01

In addition to professional training, computer aided teaching has long tradition. The difficult economic situation, however, forced many customers to take drastic austerity measures in the field of learning. Cost pressure encouraged a new openness to innovative and tailored learning concepts. As a result e-learning gained more interest and importance promising great benefit to the user. Around the world a variety of well-designed e-learning products exist. The web pages of Commission VI/2 (http://www.igg.tuberlin. de/ISPRS/) provide a decision aid to locate relevant material. Links to websites known to the authors are listed; a search function allows selective access, taking account of quality criteria. This article describes best practice e-learning applications in photogrammetry, remote sensing and GIS. The rating is based on results of the Computer Assisted Teaching CONtest (CATCON) initiated by ISPRS, and on observation of recent developments.

Deep learning aided decision support for pulmonary nodules diagnosing: a review

PubMed Central

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping

2018-01-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing. PMID:29780633

Pedagogical effectiveness of innovative teaching methods initiated at the Department of Physiology, Government Medical College, Chandigarh.

PubMed

Nageswari, K Sri; Malhotra, Anita S; Kapoor, Nandini; Kaur, Gurjit

2004-12-01

Modern teaching trends in medical education exhibit a paradigm shift from the conventional classroom teaching methods adopted in the past to nonconventional teaching aids so as to encourage interactive forms of learning in medical students through active participation and integrative reasoning where the relationship of the teacher and the taught has undergone tremendous transformation. Some of the nonconventional teaching methods adopted at our department are learning through active participation by the students through computer-assisted learning (CD-ROMs), Web-based learning (undergraduate projects), virtual laboratories, seminars, audiovisual aids (video-based demonstrations), and "physioquiz."

Can Blended Learning Aid Foreign Language Learning?

ERIC Educational Resources Information Center

Genís Pedra, Marta; Martín de Lama, Mª Teresa

2013-01-01

There has always been a debate around the issue of what it is that improves learning: the instruction itself or the media used for it (Clark 1983; Kozma 1994). It has also been said (Kulik and Kulik 1991; Andrewartha & Wilmot 2001) that computer mediated learning, as opposed to traditional instruction, positively influences the students'…

Flipped Learning in TESOL: Definitions, Approaches, and Implementation

ERIC Educational Resources Information Center

Bauer-Ramazani, Christine; Graney, John M.; Marshall, Helaine W.; Sabieh, Christine

2016-01-01

As the use of flipped learning spreads throughout educational disciplines, TESOL educators need to consider its potential for our field. This article, based on a computer-aided language learning (CALL) interest session at TESOL 2015, first looks at how best to describe and define flipped learning and examines the factors needed to make it…

Using Pre-test/Post-test Data To Evaluate the Effectiveness of Computer Aided Instruction (A Study of CAI and Its Use with Developmental Reading Students).

ERIC Educational Resources Information Center

Lansford, Carl E.

As computer aided instruction (CAI) and distance learning become more popular, a model for easily evaluating these teaching methods must be developed, one which will enable replication of the study each year. This paper discusses the results of a study using existing dependent and independent variables to evaluate CAI for developmental reading…

The Burn Medical Assistant: Developing Machine Learning Algorithms to Aid in the Estimation of Burn Wound Size

DTIC Science & Technology

2017-10-01

hypothesis that a computer machine learning algorithm can analyze and classify burn injures using multispectral imaging within 5% of an expert clinician...morbidity. In response to these challenges, the USAISR developed and obtained FDA 510(k) clearance of the Burn Navigator™, a computer decision support... computer decision support software (CDSS), can significantly change the CDSS algorithm’s recommendations and thus the total fluid administered to a

Computer Aided Braille Trainer

PubMed Central

Sibert, Thomas W.

1984-01-01

The problems involved in teaching visually impaired persons to Braille are numerous. Training while the individual is still sighted and using a computer to assist is one way of shortening the learning curve. Such a solution is presented here.

Labeled Postings for Asynchronous Interaction

ERIC Educational Resources Information Center

ChanLin, Lih-Juan; Chen, Yong-Ting; Chan, Kung-Chi

2009-01-01

The Internet promotes computer-mediated communications, and so asynchronous learning network systems permit more flexibility in time, space, and interaction than synchronous mode of learning. The key point of asynchronous learning is the materials for web-aided teaching and the flow of knowledge. This research focuses on improving online…

Early Identification of Ineffective Cooperative Learning Teams

ERIC Educational Resources Information Center

Hsiung, C .M.; Luo, L. F.; Chung, H. C.

2014-01-01

Cooperative learning has many pedagogical benefits. However, if the cooperative learning teams become ineffective, these benefits are lost. Accordingly, this study developed a computer-aided assessment method for identifying ineffective teams at their early stage of dysfunction by using the Mahalanobis distance metric to examine the difference…

Multiple neural network approaches to clinical expert systems

NASA Astrophysics Data System (ADS)

Stubbs, Derek F.

1990-08-01

We briefly review the concept of computer aided medical diagnosis and more extensively review the the existing literature on neural network applications in the field. Neural networks can function as simple expert systems for diagnosis or prognosis. Using a public database we develop a neural network for the diagnosis of a major presenting symptom while discussing the development process and possible approaches. MEDICAL EXPERTS SYSTEMS COMPUTER AIDED DIAGNOSIS Biomedicine is an incredibly diverse and multidisciplinary field and it is not surprising that neural networks with their many applications are finding more and more applications in the highly non-linear field of biomedicine. I want to concentrate on neural networks as medical expert systems for clinical diagnosis or prognosis. Expert Systems started out as a set of computerized " ifthen" rules. Everything was reduced to boolean logic and the promised land of computer experts was said to be in sight. It never came. Why? First the computer code explodes as the number of " ifs" increases. All the " ifs" have to interact. Second experts are not very good at reducing expertise to language. It turns out that experts recognize patterns and have non-verbal left-brain intuition decision processes. Third learning by example rather than learning by rule is the way natural brains works and making computers work by rule-learning is hideously labor intensive. Neural networks can learn from example. They learn the results

Evaluation of Sports Trainers Perceptions on Computer Aided Education Related to the Attitudes toward Learning

ERIC Educational Resources Information Center

Murathan, Talha; Kaya, Oktay

2016-01-01

Technologic developments have--the same as they have done it in every sector--influenced the education system. These influences have forced to use the computer in the education-training applications within the education system. The aim of this research is to determine, compare, and examine the influences on the conduct for learning of sport…

The Computer as an Aid to Reading Instruction. Learning Package No. 27.

ERIC Educational Resources Information Center

Simic, Marge, Comp.; Smith, Carl, Ed.

Originally developed for the Department of Defense Schools (DoDDS) system, this learning package on computer use in reading is designed for teachers who wish to upgrade or expand their teaching skills on their own. The package includes an overview of the project; a comprehensive search of the ERIC database; a lecture giving an overview on the…

The Use of Computer-Based Simulation to Aid Comprehension and Incidental Vocabulary Learning

ERIC Educational Resources Information Center

Mohsen, Mohammed Ali

2016-01-01

One of the main issues in language learning is to find ways to enable learners to interact with the language input in an involved task. Given that computer-based simulation allows learners to interact with visual modes, this article examines how the interaction of students with an online video simulation affects their second language video…

Aids to Computer-Based Multimedia Learning: A Comparison of Human Tutoring and Computer Support

ERIC Educational Resources Information Center

Rodicio, H. Garcia; Sanchez, E.

2012-01-01

Learners are usually provided with support devices because they find it difficult to learn from multimedia presentations. A key question, with no clear answer so far, is how best to present these support devices. One possibility is to insert them into the multimedia presentation (canned support), while another is to have a human agent provide them…

A cross-sectional evaluation of computer literacy among medical students at a tertiary care teaching hospital in Mumbai, Bombay.

PubMed

Panchabhai, T S; Dangayach, N S; Mehta, V S; Patankar, C V; Rege, N N

2011-01-01

Computer usage capabilities of medical students for introduction of computer-aided learning have not been adequately assessed. Cross-sectional study to evaluate computer literacy among medical students. Tertiary care teaching hospital in Mumbai, India. Participants were administered a 52-question questionnaire, designed to study their background, computer resources, computer usage, activities enhancing computer skills, and attitudes toward computer-aided learning (CAL). The data was classified on the basis of sex, native place, and year of medical school, and the computer resources were compared. The computer usage and attitudes toward computer-based learning were assessed on a five-point Likert scale, to calculate Computer usage score (CUS - maximum 55, minimum 11) and Attitude score (AS - maximum 60, minimum 12). The quartile distribution among the groups with respect to the CUS and AS was compared by chi-squared tests. The correlation between CUS and AS was then tested. Eight hundred and seventy-five students agreed to participate in the study and 832 completed the questionnaire. One hundred and twenty eight questionnaires were excluded and 704 were analyzed. Outstation students had significantly lesser computer resources as compared to local students (P<0.0001). The mean CUS for local students (27.0±9.2, Mean±SD) was significantly higher than outstation students (23.2±9.05). No such difference was observed for the AS. The means of CUS and AS did not differ between males and females. The CUS and AS had positive, but weak correlations for all subgroups. The weak correlation between AS and CUS for all students could be explained by the lack of computer resources or inadequate training to use computers for learning. Providing additional resources would benefit the subset of outstation students with lesser computer resources. This weak correlation between the attitudes and practices of all students needs to be investigated. We believe that this gap can be bridged with a structured computer learning program.

An Optimum Strategy for Learning to Read Foreign Scientific and Technical Literature.

ERIC Educational Resources Information Center

Alford, M.H.T.

A report on a series of computer programs being written to make frequency counts designed to indicate the learning problems to be encountered in any approach to a target literature discusses how these programs can be used to aid in foreign language vocabulary learning. (Author/AF)

The Computer as a Teaching Aid for Eleventh Grade Mathematics: A Comparison Study.

ERIC Educational Resources Information Center

Kieren, Thomas Ervin

To determine the effect of learning computer programming and the use of a computer on mathematical achievement of eleventh grade students, for each of two years, average and above average students were randomly assigned to an experimental and control group. The experimental group wrote computer programs and used the output from the computer in…

A Study of the Use of Ontologies for Building Computer-Aided Control Engineering Self-Learning Educational Software

NASA Astrophysics Data System (ADS)

García, Isaías; Benavides, Carmen; Alaiz, Héctor; Alonso, Angel

2013-08-01

This paper describes research on the use of knowledge models (ontologies) for building computer-aided educational software in the field of control engineering. Ontologies are able to represent in the computer a very rich conceptual model of a given domain. This model can be used later for a number of purposes in different software applications. In this study, domain ontology about the field of lead-lag compensator design has been built and used for automatic exercise generation, graphical user interface population and interaction with the user at any level of detail, including explanations about why things occur. An application called Onto-CELE (ontology-based control engineering learning environment) uses the ontology for implementing a learning environment that can be used for self and lifelong learning purposes. The experience has shown that the use of knowledge models as the basis for educational software applications is capable of showing students the whole complexity of the analysis and design processes at any level of detail. A practical experience with postgraduate students has shown the mentioned benefits and possibilities of the approach.

Computer-aided drug discovery research at a global contract research organization

NASA Astrophysics Data System (ADS)

Kitchen, Douglas B.

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

Computer-aided drug discovery research at a global contract research organization.

PubMed

Kitchen, Douglas B

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

Computer-Based Tutoring of Visual Concepts: From Novice to Experts.

ERIC Educational Resources Information Center

Sharples, Mike

1991-01-01

Description of ways in which computers might be used to teach visual concepts discusses hypermedia systems; describes computer-generated tutorials; explains the use of computers to create learning aids such as concept maps, feature spaces, and structural models; and gives examples of visual concept teaching in medical education. (10 references)…

Development of Computer-Based Resources for Textile Education.

ERIC Educational Resources Information Center

Hopkins, Teresa; Thomas, Andrew; Bailey, Mike

1998-01-01

Describes the production of computer-based resources for students of textiles and engineering in the United Kingdom. Highlights include funding by the Teaching and Learning Technology Programme (TLTP), courseware author/subject expert interaction, usage test and evaluation, authoring software, graphics, computer-aided design simulation, self-test…

Design of Intelligent Robot as A Tool for Teaching Media Based on Computer Interactive Learning and Computer Assisted Learning to Improve the Skill of University Student

NASA Astrophysics Data System (ADS)

Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.

2018-01-01

The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.

Attitudes of health care students about computer-aided neuroanatomy instruction.

PubMed

McKeough, D Michael; Bagatell, Nancy

2009-01-01

This study examined students' attitudes toward computer-aided instruction (CAI), specifically neuroanatomy learning modules, to assess which components were primary in establishing these attitudes and to discuss the implications of these attitudes for successfully incorporating CAI in the preparation of health care providers. Seventy-seven masters degree, entry-level, health care professional students matriculated in an introductory neuroanatomy course volunteered as subjects for this study. Students independently reviewed the modules as supplements to lecture and completed a survey to evaluate teaching effectiveness. Responses to survey statements were compared across the learning modules to determine if students viewed the modules differently. Responses to individual survey statements were averaged to measure the strength of agreement or disagreement with the statement. Responses to open-ended questions were theme coded, and frequencies and percentages were calculated for each. Students saw no differences between the learning modules. Students perceived the learning modules as valuable; they enjoyed using the modules but did not prefer CAI over traditional lecture format. The modules were useful in learning or reinforcing neuroanatomical concepts and improving clinical problem-solving skills. Students reported that the visual representation of the neuroanatomical systems, computer animation, ability to control the use of the modules, and navigational fidelity were key factors in determining attitudes. The computer-based learning modules examined in this study were effective as adjuncts to lecture in helping entry-level health care students learn and make clinical applications of neuroanatomy information.

Application of Adaptive Decision Aiding Systems to Computer-Assisted Instruction. Final Report, January-December 1974.

ERIC Educational Resources Information Center

May, Donald M.; And Others

The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

Advanced CNC Programming (EZ-CAM). 439-366.

ERIC Educational Resources Information Center

Casey, Joe

This document contains two units for an advanced course in computer numerical control (CNC) for computer-aided manufacturing. It is intended to familiarize students with the principles and techniques necessary to create proper CNC programs using computer software. Each unit consists of an introduction, instructional objectives, learning materials,…

Traditional Engineering Graphics versus Computer-Aided Drafting: A View from Academe.

ERIC Educational Resources Information Center

Foster, Robert J.

1987-01-01

Argues for a legitimate role of manually expressed engineering graphics within engineering education as a needed support for computer-assisted drafting work. Discusses what and how students should learn as well as trends in engineering graphics education. Compares and contrasts manual and computer drafting methods. (CW)

Presentation Software and the Single Computer.

ERIC Educational Resources Information Center

Brown, Cindy A.

1998-01-01

Shows how the "Kid Pix" software and a single multimedia computer can aid classroom instruction for kindergarten through second grade. Topics include using the computer as a learning center for small groups of students; making a "Kid Pix" slide show; using it as an electronic chalkboard; and creating curriculum-related…

Modeling the User for Education, Training, and Performance Aiding

DTIC Science & Technology

2003-11-01

Eds.) Technology applications in education : A learning view (pp. 79–99). Hillsdale, NJ: Lawrence Erlbaum Associates. Fletcher, J.D. and Johnston, R...2003 symposium on Advanced Technologies for Military Training. v CONTENTS MODELING THE USER FOR EDUCATION , TRAINING, AND PERFORMANCE AIDING EXECUTIVE...using computer technology for education , training, decision-making, and performance aiding. Our focus is on the digital representation of these users

Affordances and Limitations of Learning Analytics for Computer-Assisted Language Learning: A Case Study of the VITAL Project

ERIC Educational Resources Information Center

Gelan, Anouk; Fastré, Greet; Verjans, Martine; Martin, Niels; Janssenswillen, Gert; Creemers, Mathijs; Lieben, Jonas; Depaire, Benoît; Thomas, Michael

2018-01-01

Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…

The Magnitude Response Learning Tool for DSP Education: A Case Study

ERIC Educational Resources Information Center

Kulmer, Florian; Wurzer, Christian Gun; Geiger, Bernhard C.

2016-01-01

Many concepts in digital signal processing are intuitive, despite being mathematically challenging. The lecturer not only has to teach the complicated math but should also help students develop intuition about the concept. To aid the lecturer in this task, the Magnitude Response Learning Tool has been introduced, a computer-based learning game…

Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey

PubMed Central

Zhang, Fan; Li, Xuelong

2018-01-01

The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system. PMID:29687000

Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey.

PubMed

Huang, Qinghua; Zhang, Fan; Li, Xuelong

2018-01-01

The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system.

BACLAB: A Computer Simulation of a Medical Bacteriology Laboratory--An Aid for Teaching Tertiary Level Microbiology.

ERIC Educational Resources Information Center

Lewington, J.; And Others

1985-01-01

Describes a computer simulation program which helps students learn the main biochemical tests and profiles for identifying medically important bacteria. Also discusses the advantages and applications of this type of approach. (ML)

Teaching Advance Care Planning to Medical Students with a Computer-Based Decision Aid

PubMed Central

Levi, Benjamin H.

2013-01-01

Discussing end-of-life decisions with cancer patients is a crucial skill for physicians. This article reports findings from a pilot study evaluating the effectiveness of a computer-based decision aid for teaching medical students about advance care planning. Second-year medical students at a single medical school were randomized to use a standard advance directive or a computer-based decision aid to help patients with advance care planning. Students' knowledge, skills, and satisfaction were measured by self-report; their performance was rated by patients. 121/133 (91%) of students participated. The Decision-Aid Group (n=60) outperformed the Standard Group (n=61) in terms of students´ knowledge (p<0.01), confidence in helping patients with advance care planning (p<0.01), knowledge of what matters to patients (p=0.05), and satisfaction with their learning experience (p<0.01). Likewise, patients in the Decision Aid Group were more satisfied with the advance care planning method (p<0.01) and with several aspects of student performance. Use of a computer-based decision aid may be an effective way to teach medical students how to discuss advance care planning with cancer patients. PMID:20632222

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

"Let's get physical": advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy.

PubMed

Preece, Daniel; Williams, Sarah B; Lam, Richard; Weller, Renate

2013-01-01

Three-dimensional (3D) information plays an important part in medical and veterinary education. Appreciating complex 3D spatial relationships requires a strong foundational understanding of anatomy and mental 3D visualization skills. Novel learning resources have been introduced to anatomy training to achieve this. Objective evaluation of their comparative efficacies remains scarce in the literature. This study developed and evaluated the use of a physical model in demonstrating the complex spatial relationships of the equine foot. It was hypothesized that the newly developed physical model would be more effective for students to learn magnetic resonance imaging (MRI) anatomy of the foot than textbooks or computer-based 3D models. Third year veterinary medicine students were randomly assigned to one of three teaching aid groups (physical model; textbooks; 3D computer model). The comparative efficacies of the three teaching aids were assessed through students' abilities to identify anatomical structures on MR images. Overall mean MRI assessment scores were significantly higher in students utilizing the physical model (86.39%) compared with students using textbooks (62.61%) and the 3D computer model (63.68%) (P < 0.001), with no significant difference between the textbook and 3D computer model groups (P = 0.685). Student feedback was also more positive in the physical model group compared with both the textbook and 3D computer model groups. Our results suggest that physical models may hold a significant advantage over alternative learning resources in enhancing visuospatial and 3D understanding of complex anatomical architecture, and that 3D computer models have significant limitations with regards to 3D learning. © 2013 American Association of Anatomists.

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…

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions.

PubMed

Loh, Brian C S; Then, Patrick H H

2017-01-01

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

PubMed Central

Then, Patrick H. H.

2017-01-01

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications. PMID:29184897

The Use of Errorless Learning Strategies for Patients with Alzheimer's Disease: A Literature Review

ERIC Educational Resources Information Center

Li, Ruijie; Liu, Karen P. Y.

2012-01-01

The aim of this article was to review the evidence of errorless learning on learning outcomes in patients with early-stage Alzheimer's disease. A computer-aided literature search from 1999 to 2011 was carried out using MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO and PsycArticles. Keywords included…

Analysis of problem solving on project based learning with resource based learning approach computer-aided program

NASA Astrophysics Data System (ADS)

Kuncoro, K. S.; Junaedi, I.; Dwijanto

2018-03-01

This study aimed to reveal the effectiveness of Project Based Learning with Resource Based Learning approach computer-aided program and analyzed problem-solving abilities in terms of problem-solving steps based on Polya stages. The research method used was mixed method with sequential explanatory design. The subject of this research was the students of math semester 4. The results showed that the S-TPS (Strong Top Problem Solving) and W-TPS (Weak Top Problem Solving) had good problem-solving abilities in each problem-solving indicator. The problem-solving ability of S-MPS (Strong Middle Problem Solving) and (Weak Middle Problem Solving) in each indicator was good. The subject of S-BPS (Strong Bottom Problem Solving) had a difficulty in solving the problem with computer program, less precise in writing the final conclusion and could not reflect the problem-solving process using Polya’s step. While the Subject of W-BPS (Weak Bottom Problem Solving) had not been able to meet almost all the indicators of problem-solving. The subject of W-BPS could not precisely made the initial table of completion so that the completion phase with Polya’s step was constrained.

Computer aided lung cancer diagnosis with deep learning algorithms

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Zheng, Bin; Qian, Wei

2016-03-01

Deep learning is considered as a popular and powerful method in pattern recognition and classification. However, there are not many deep structured applications used in medical imaging diagnosis area, because large dataset is not always available for medical images. In this study we tested the feasibility of using deep learning algorithms for lung cancer diagnosis with the cases from Lung Image Database Consortium (LIDC) database. The nodules on each computed tomography (CT) slice were segmented according to marks provided by the radiologists. After down sampling and rotating we acquired 174412 samples with 52 by 52 pixel each and the corresponding truth files. Three deep learning algorithms were designed and implemented, including Convolutional Neural Network (CNN), Deep Belief Networks (DBNs), Stacked Denoising Autoencoder (SDAE). To compare the performance of deep learning algorithms with traditional computer aided diagnosis (CADx) system, we designed a scheme with 28 image features and support vector machine. The accuracies of CNN, DBNs, and SDAE are 0.7976, 0.8119, and 0.7929, respectively; the accuracy of our designed traditional CADx is 0.7940, which is slightly lower than CNN and DBNs. We also noticed that the mislabeled nodules using DBNs are 4% larger than using traditional CADx, this might be resulting from down sampling process lost some size information of the nodules.

Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.

PubMed

Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira

2016-04-01

This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

Computers in the Classroom: The School of the Future, The Future of the School.

ERIC Educational Resources Information Center

Tapia, Ivan, Ed.

1995-01-01

Computer uses in the classroom is the theme topic of this journal issue. Contents include: "Emo Welzl: 1995 Leibniz Laureate" (Hartmut Wewetzer); "Learning to Read with the Aid of a Computer: Research Project with Children Starting School" (Horst Meermann); "The Multimedia School: The Comenius Pilot Project" (Tom Sperlich); "A Very Useful Piece of…

Teaching Business Statistics in a Computer Lab: Benefit or Distraction?

ERIC Educational Resources Information Center

Martin, Linda R.

2011-01-01

Teaching in a classroom configured with computers has been heralded as an aid to learning. Students receive the benefits of working with large data sets and real-world problems. However, with the advent of network and wireless connections, students can now use the computer for alternating tasks, such as emailing, web browsing, and social…

The Dinosaurs Didn't See It Coming, But Historians Had Better: Computer Aided Activities in the History Classroom.

ERIC Educational Resources Information Center

Phillips, Julieanne

2001-01-01

States that in ninety percent of colleges across the United States, some or most classrooms are wired for technology integration. Posits that to facilitate student learning and prepare students for future technological advances, instructors must use effective teaching activities that include computers. Provides a sample computer assisted history…

A Journey from the Sun to the Earth

ERIC Educational Resources Information Center

Psycharis, Sarantos; Daflos, Athanasios

2005-01-01

Computer-aided modelling and investigations can bring the real world into classrooms and facilitate its exploration, in contrast to acquiring factual knowledge from textbooks. Computer modelling puts a whole new "spin" on science education, redefining and reshaping the classroom learning experience. The authors used information and…

Microcomputers in the Curriculum: Micros and the First R.

ERIC Educational Resources Information Center

Balajthy, Ernest; Reinking, David

1985-01-01

Introduces the range of computer software currently available to aid in developing children's basic skills in reading, including programs for reading readiness, word recognition, vocabulary development, reading comprehension, and learning motivation. Additional information on software and computer use is provided in sidebars by Gwen Solomon and…

A Computer-aided Learning Exercise in Spectrophotometry.

ERIC Educational Resources Information Center

Pamula, Frederick

1994-01-01

Discusses the use of a computer simulation program in teaching the concepts of spectrophotometry. Introduces several parts of the program and program usage. Presents an assessment activity to evaluate students' mastery of material. Concludes with the advantages of this approach to the student and to the assessor. (ASK)

Enhancement of Teaching and Learning of the Fundamentals of Nuclear Engineering Using Multimedia Courseware.

ERIC Educational Resources Information Center

Keyvan, Shahla A.; Pickard, Rodney; Song, Xiaolong

1997-01-01

Computer-aided instruction incorporating interactive multimedia and network technologies can boost teaching effectiveness and student learning. This article describes the development and implementation of network server-based interactive multimedia courseware for a fundamental course in nuclear engineering. A student survey determined that 80% of…

Web-Based Learning and Instruction Support System for Pneumatics

ERIC Educational Resources Information Center

Yen, Chiaming; Li, Wu-Jeng

2003-01-01

This research presents a Web-based learning and instructional system for Pneumatics. The system includes course material, remote data acquisition modules, and a pneumatic laboratory set. The course material is in the HTML format accompanied with text, still and animated images, simulation programs, and computer aided design tools. The data…

WINDS: A Web-Based Intelligent Interactive Course on Data-Structures

ERIC Educational Resources Information Center

Sirohi, Vijayalaxmi

2007-01-01

The Internet has opened new ways of learning and has brought several advantages to computer-aided education. Global access, self-paced learning, asynchronous teaching, interactivity, and multimedia usage are some of these. Along with the advantages comes the challenge of designing the software using the available facilities. Integrating online…

Interactivity of Visual Mathematical Representations: Factors Affecting Learning and Cognitive Processes

ERIC Educational Resources Information Center

Sedig, Kamran; Liang, Hai-Ning

2006-01-01

Computer-based mathematical cognitive tools (MCTs) are a category of external aids intended to support and enhance learning and cognitive processes of learners. MCTs often contain interactive visual mathematical representations (VMRs), where VMRs are graphical representations that encode properties and relationships of mathematical concepts. In…

Learning with On-Line and Hardcopy Tutorials. A Final Report. CDC Technical Report No. 32.

ERIC Educational Resources Information Center

Duffy, T. M.; And Others

Intended to aid in the design of computer systems that promote efficient learning and performance, this study compared the effects of using hard copy and online format tutorials on the learning activities of 48 undergraduate students in either design or engineering. The tutorials, which provided instruction on the use of the equipment and basic…

Effects of Computer-Aided and Blended Teaching Strategies on Students' Achievement in Civic Education Concepts in Mountain Learning Ecologies

ERIC Educational Resources Information Center

Ige, Olugbenga Adedayo; Hlalele, Dipane Joseph

2017-01-01

The need to enhance students' learning outcomes has become integral in secondary schools in developing countries due to increased students enrollment. Research has shown that the strategies utilized in teaching secondary school students have significant influence on their learning outcomes. At present in Nigeria, public secondary schools have not…

A Silent Revolution: From Sketching to Coding--A Case Study on Code-Based Design Tool Learning

ERIC Educational Resources Information Center

Xu, Song; Fan, Kuo-Kuang

2017-01-01

Along with the information technology rising, Computer Aided Design activities are becoming more modern and more complex. But learning how to operation these new design tools has become the main problem lying in front of each designer. This study was purpose on finding problems encountered during code-based design tools learning period of…

Applications of Speech-to-Text Recognition and Computer-Aided Translation for Facilitating Cross-Cultural Learning through a Learning Activity: Issues and Their Solutions

ERIC Educational Resources Information Center

Shadiev, Rustam; Wu, Ting-Ting; Sun, Ai; Huang, Yueh-Min

2018-01-01

In this study, 21 university students, who represented thirteen nationalities, participated in an online cross-cultural learning activity. The participants were engaged in interactions and exchanges carried out on Facebook® and Skype® platforms, and their multilingual communications were supported by speech-to-text recognition (STR) and…

Utilizing computerized entertainment education in the development of decision aids for lower literate and naïve computer users.

PubMed

Jibaja-Weiss, Maria L; Volk, Robert J

2007-01-01

Decision aids have been developed by using various delivery methods, including interactive computer programs. Such programs, however, still rely heavily on written information, health and digital literacy, and reading ease. We describe an approach to overcome these potential barriers for low-literate, underserved populations by making design considerations for poor readers and naïve computer users and by using concepts from entertainment education to engage the user and to contextualize the content for the user. The system design goals are to make the program both didactic and entertaining and the navigation and graphical user interface as simple as possible. One entertainment education strategy, the soap opera, is linked seamlessly to interactive learning modules to enhance the content of the soap opera episodes. The edutainment decision aid model (EDAM) guides developers through the design process. Although designing patient decision aids that are educational, entertaining, and targeted toward poor readers and those with limited computer skills is a complex task, it is a promising strategy for aiding this population. Entertainment education may be a highly effective approach to promoting informed decision making for patients with low health literacy.

38 CFR 64.6 - Permissible uses of RVCP grants.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., devices, appliances, and assistive technology. (3) Providing assistance to families of transitioning... schools and/or child care programs; securing learning aids such as textbooks, computers and laboratory...

38 CFR 64.6 - Permissible uses of RVCP grants.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., devices, appliances, and assistive technology. (3) Providing assistance to families of transitioning... schools and/or child care programs; securing learning aids such as textbooks, computers and laboratory...

SnapAnatomy, a computer-based interactive tool for independent learning of human anatomy.

PubMed

Yip, George W; Rajendran, Kanagasuntheram

2008-06-01

Computer-aided instruction materials are becoming increasing popular in medical education and particularly in the teaching of human anatomy. This paper describes SnapAnatomy, a new interactive program that the authors designed for independent learning of anatomy. SnapAnatomy is primarily tailored for the beginner student to encourage the learning of anatomy by developing a three-dimensional visualization of human structure that is essential to applications in clinical practice and the understanding of function. The program allows the student to take apart and to accurately put together body components in an interactive, self-paced and variable manner to achieve the learning outcome.

Computer-Aided Authoring of Programmed Instruction for Teaching Symbol Recognition. Final Report.

ERIC Educational Resources Information Center

Braby, Richard; And Others

This description of AUTHOR, a computer program for the automated authoring of programmed texts designed to teach symbol recognition, includes discussions of the learning strategies incorporated in the design of the instructional materials, hardware description and the algorithm for the software, and current and future developments. Appendices…

IPAD: A unique approach to government/industry cooperation for technology development and transfer

NASA Technical Reports Server (NTRS)

Fulton, Robert E.; Salley, George C.

1985-01-01

A key element to improved industry productivity is effective management of Computer Aided Design / Computer Aided Manufacturing (CAD/CAM) information. To stimulate advancement, a unique joint government/industry project designated Integrated Programs for Aerospace-Vehicle Design (IPAD) was carried out from 1971 to 1984. The goal was to raise aerospace industry productivity through advancement of computer based technology to integrate and manage information involved in the design and manufacturing process. IPAD research was guided by an Industry Technical Advisory Board (ITAB) composed of over 100 representatives from aerospace and computer companies. The project complemented traditional NASA/DOD research to develop aerospace design technology and the Air Force's Integrated Computer Aided Manufacturing (ICAM) program to advance CAM technology. IPAD had unprecedented industry support and involvement and served as a unique approach to government industry cooperation in the development and transfer of advanced technology. The IPAD project background, approach, accomplishments, industry involvement, technology transfer mechanisms and lessons learned are summarized.

Quantification of Hepatorenal Index for Computer-Aided Fatty Liver Classification with Self-Organizing Map and Fuzzy Stretching from Ultrasonography.

PubMed

Kim, Kwang Baek; Kim, Chang Won

2015-01-01

Accurate measures of liver fat content are essential for investigating hepatic steatosis. For a noninvasive inexpensive ultrasonographic analysis, it is necessary to validate the quantitative assessment of liver fat content so that fully automated reliable computer-aided software can assist medical practitioners without any operator subjectivity. In this study, we attempt to quantify the hepatorenal index difference between the liver and the kidney with respect to the multiple severity status of hepatic steatosis. In order to do this, a series of carefully designed image processing techniques, including fuzzy stretching and edge tracking, are applied to extract regions of interest. Then, an unsupervised neural learning algorithm, the self-organizing map, is designed to establish characteristic clusters from the image, and the distribution of the hepatorenal index values with respect to the different levels of the fatty liver status is experimentally verified to estimate the differences in the distribution of the hepatorenal index. Such findings will be useful in building reliable computer-aided diagnostic software if combined with a good set of other characteristic feature sets and powerful machine learning classifiers in the future.

Quantification of Hepatorenal Index for Computer-Aided Fatty Liver Classification with Self-Organizing Map and Fuzzy Stretching from Ultrasonography

PubMed Central

Kim, Kwang Baek

2015-01-01

Accurate measures of liver fat content are essential for investigating hepatic steatosis. For a noninvasive inexpensive ultrasonographic analysis, it is necessary to validate the quantitative assessment of liver fat content so that fully automated reliable computer-aided software can assist medical practitioners without any operator subjectivity. In this study, we attempt to quantify the hepatorenal index difference between the liver and the kidney with respect to the multiple severity status of hepatic steatosis. In order to do this, a series of carefully designed image processing techniques, including fuzzy stretching and edge tracking, are applied to extract regions of interest. Then, an unsupervised neural learning algorithm, the self-organizing map, is designed to establish characteristic clusters from the image, and the distribution of the hepatorenal index values with respect to the different levels of the fatty liver status is experimentally verified to estimate the differences in the distribution of the hepatorenal index. Such findings will be useful in building reliable computer-aided diagnostic software if combined with a good set of other characteristic feature sets and powerful machine learning classifiers in the future. PMID:26247023

Deep Learning in Medical Image Analysis.

PubMed

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

Assess/Mitigate Risk through the Use of Computer-Aided Software Engineering (CASE) Tools

NASA Technical Reports Server (NTRS)

Aguilar, Michael L.

2013-01-01

The NASA Engineering and Safety Center (NESC) was requested to perform an independent assessment of the mitigation of the Constellation Program (CxP) Risk 4421 through the use of computer-aided software engineering (CASE) tools. With the cancellation of the CxP, the assessment goals were modified to capture lessons learned and best practices in the use of CASE tools. The assessment goal was to prepare the next program for the use of these CASE tools. The outcome of the assessment is contained in this document.

Courseware Integration into Task-Based Learning: A Case Study of Multimedia Courseware-Supported Oral Presentations for Non-English Major Students

ERIC Educational Resources Information Center

Tsai, Shu-Chiao

2011-01-01

This study reports on the integration of English for Specific Purposes (ESP) multimedia courseware for oral presentations into a self-learning and elective program for non-English major students in an English as a Foreign Language (EFL) setting. A computer-aided instruction approach, combined with a task-based learning approach, was adopted.…

Can Computer-Based Visual-Spatial Aids Lead to Increased Student Performance in Anatomy & Physiology?

ERIC Educational Resources Information Center

Kesner, Michael H.; Linzey, Alicia V.

2005-01-01

InterActive Physiology (IAP) is one of a new generation of anatomy and physiology learning aids with a broader range of sensory inputs than is possible from a static textbook or moderately dynamic lecture. This best-selling software has modules covering the muscular, respiratory, urinary, cardiovascular, and nervous systems plus a module on fluids…

CAL-laborate: A Collaborative Publication on the Use of Computer Aided Learning for Tertiary Level Physical Sciences and Geosciences.

ERIC Educational Resources Information Center

Fernandez, Anne, Ed.; Sproats, Lee, Ed.; Sorensen, Stacey, Ed.

2000-01-01

The science community has been trying to use computers in teaching for many years. There has been much conformity in how this was to be achieved, and the wheel has been re-invented again and again as enthusiast after enthusiast has "done their bit" towards getting computers accepted. Computers are now used by science undergraduates (as well as…

Role of computer-based learning in tooth carving in dentistry: An Indian perspective.

PubMed

Juneja, Saurabh; Juneja, Manjushree

2016-01-01

Tooth carving is an important practical preclinical exercise in the curriculum in Indian dental education setup. It forms the basis of introduction to tooth anatomy, morphology and occlusion of primary and permanent teeth through practical approach. It requires enormous time and manpower to master the skill. Therefore, there is an imminent necessity to incorporate computer-based learning of the art of tooth carving for effective teaching and efficient student learning. This will ensure quality time to be spent on other academic and research activities by students and faculty in addition to adding value as a teaching aid.

Factors Influencing Undergraduate Students' Acceptance of a Haptic Interface for Learning Gross Anatomy

ERIC Educational Resources Information Center

Yeom, Soonja; Choi-Lundberg, Derek L.; Fluck, Andrew Edward; Sale, Arthur

2017-01-01

Purpose: This study aims to evaluate factors influencing undergraduate students' acceptance of a computer-aided learning resource using the Phantom Omni haptic stylus to enable rotation, touch and kinaesthetic feedback and display of names of three-dimensional (3D) human anatomical structures on a visual display. Design/methodology/approach: The…

Meaning-Making in Online Language Learner Interactions via Desktop Videoconferencing

ERIC Educational Resources Information Center

Satar, H. Müge

2016-01-01

Online language learning and teaching in multimodal contexts has been identified as one of the key research areas in computer-aided learning (CALL) (Lamy, 2013; White, 2014). This paper aims to explore meaning-making in online language learner interactions via desktop videoconferencing (DVC) and in doing so illustrate multimodal transcription and…

Effect of Animated Graphic Annotations and Immediate Visual Feedback in Aiding Japanese Pronunciation Learning: A Comparative Study

ERIC Educational Resources Information Center

Hew, Soon-Hin; Ohki, Mitsuru

2004-01-01

This study examines the effectiveness of imagery and electronic visual feedback in facilitating students' acquisition of Japanese pronunciation skills. The independent variables, animated graphic annotation (AGA) and immediate visual feedback (IVF) were integrated into a Japanese computer-assisted language learning (JCALL) program focused on the…

A Cross-National CAI Tool To Support Learning Operations Decision-Making and Market Analysis.

ERIC Educational Resources Information Center

Mockler, Robert J.; Afanasiev, Mikhail Y.; Dologite, Dorothy G.

1999-01-01

Describes bicultural (United States and Russia) development of a computer-aided instruction (CAI) tool to learn management decision-making using information systems technologies. The program has been used with undergraduate and graduate students in both countries; it integrates free and controlled market concepts and combines traditional computer…

Implementation and Evaluation of a Course Concept Based on Reusable Learning Objects

ERIC Educational Resources Information Center

Van Zele, Els; Vandaele, Pieter; Botteldooren, Dick; Lenaerts, Josephina

2003-01-01

This article describes the implementation and evaluation of a learning objects based computer aided system for an advanced engineering course at Ghent University, Belgium. A new syllabus concept was introduced: students had access to a Web-delivered component and received an identical printed component as two sources of information additional to…

Working with Students Who Are Late-Deafened. NETAC Teacher Tipsheet.

ERIC Educational Resources Information Center

Clark, Mary

This tipsheet provides suggestions to help teachers work more effectively with students who are late-deafened. Suggestions include: (1) allow time for the student to introduce himself and discuss possible needs; (2) learn the basics of CART (Computer-Aided Realtime Translation) and other communication options; (3) learn the basics of using…

Intelligent Image Based Computer Aided Education (IICAE)

NASA Astrophysics Data System (ADS)

David, Amos A.; Thiery, Odile; Crehange, Marion

1989-03-01

Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.

Computer-aided vs. tutor-delivered teaching of exposure therapy for phobia/panic: randomized controlled trial with pre-registration nursing students.

PubMed

Gega, L; Norman, I J; Marks, I M

2007-03-01

Exposure therapy is effective for phobic anxiety disorders (specific phobias, agoraphobia, social phobia) and panic disorder. Despite their high prevalence in the community, sufferers often get no treatment or if they do, it is usually after a long delay. This is largely due to the scarcity of healthcare professionals trained in exposure therapy, which is due, in part, to the high cost of training. Traditional teaching methods employed are labour intensive, being based mainly on role-play in small groups with feedback and coaching from experienced trainers. In an attempt to increase knowledge and skills in exposure therapy, there is now some interest in providing relevant teaching as part of pre-registration nurse education. Computers have been developed to teach terminology and simulate clinical scenarios for health professionals, and offer a potentially cost effective alternative to traditional teaching methods. To test whether student nurses would learn about exposure therapy for phobia/panic as well by computer-aided self-instruction as by face-to-face teaching, and to compare the individual and combined effects of two educational methods, traditional face-to-face teaching comprising a presentation with discussion and questions/answers by a specialist cognitive behaviour nurse therapist, and a computer-aided self-instructional programme based on a self-help programme for patients with phobia/panic called FearFighter, on students' knowledge, skills and satisfaction. Randomised controlled trial, with a crossover, completed in 2 consecutive days over a period of 4h per day. Ninety-two mental health pre-registration nursing students, of mixed gender, age and ethnic origin, with no previous training in cognitive behaviour therapy studying at one UK university. The two teaching methods led to similar improvements in knowledge and skills, and to similar satisfaction, when used alone. Using them in tandem conferred no added benefit. Computer-aided self-instruction was more efficient as it saved teacher preparation and delivery time, and needed no specialist tutor. Computer-aided self-instruction saved almost all preparation time and delivery effort for the expert teacher. When added to past results in medical students, the present results in nurses justify the use of computer-aided self-instruction for learning about exposure therapy and phobia/panic and of research into its value for other areas of health education.

Interactive and Multimedia Contents Associated with a System for Computer-Aided Assessment

ERIC Educational Resources Information Center

Paiva, Rui C.; Ferreira, Milton S.; Mendes, Ana G.; Eusébio, Augusto M. J.

2015-01-01

This article presents a research study addressing the development, implementation, evaluation, and use of Interactive Modules for Online Training (MITO) of mathematics in higher education. This work was carried out in the context of the MITO project, which combined several features of the learning and management system Moodle, the computer-aided…

An Interaction of Screen Colour and Lesson Task in CAL

ERIC Educational Resources Information Center

Clariana, Roy B.

2004-01-01

Colour is a common feature in computer-aided learning (CAL), though the instructional effects of screen colour are not well understood. This investigation considers the effects of different CAL study tasks with feedback on posttest performance and on posttest memory of the lesson colour scheme. Graduate students (n=68) completed a computer-based…

Use of an Automatic Problem Generator to Teach Basic Skills in a First Course in Assembly Language.

ERIC Educational Resources Information Center

Benander, Alan; And Others

1989-01-01

Discussion of the use of computer aided instruction (CAI) and instructional software in college level courses highlights an automatic problem generator, AUTOGEN, that was written for computer science students learning assembly language. Design of the software is explained, and student responses are reported. (nine references) (LRW)

Comparative use of podcasts vs. lecture transcripts as learning aids for dental students.

PubMed

Allen, Kenneth L; Katz, Ralph V

2011-06-01

The purpose of this project was to describe dental students' use of lecture podcasts versus written lecture transcripts as learning aids under three different circumstances: studying for an exam, reviewing an attended lecture, and reviewing a missed lecture. Additional analyses were performed to see whether demographic differences (e.g., age, gender, language skills, and computer skills) or grade differences were associated with preferences for using podcast versus written lecture transcripts of class notes. Fifty-one percent (n=171) of the second-year dental students at the New York University College of Dentistry voluntarily participated in this survey. The major findings were that 1) a high percentage of students (70-92 percent) used one or both aids in all three utilization circumstances with a consistent preference for podcast use, especially when reviewing a missed lecture; 2) course grades were not associated with the preferred use of either lecture aid; and 3) over half the students listened to the podcasts at speeds that were one and one-half or two times faster than normal speech, especially younger students. Further studies are warranted to delve into the current student generation's preferred learning styles and the resultant learning outcomes associated with those preferences.

Computer Aided Teaching in Photogrammetry, Remote Sensing, and Geomatics - A Status Review

NASA Astrophysics Data System (ADS)

Vyas, A.; Koenig, G.

2014-04-01

Education and training play vital role in the utilization of the technology. Shared and coordinated knowledge that geospatial technology and GIS deliver provides a deeper understanding of our present and will also help to better understand our future development. But it is not enough to explain new technological developments during congresses or workshops; it is also necessary to promote these new ideas and to distribute the knowledge by applying new learning strategies. This paper will review the status of computer aided teaching advances during the last decade, with a particular emphasis on photogrammetry, remote sensing, and geomatics. Some best practise examples will be presented featuring prominently recent Massive Open Online Courses (MOOCs) related to our fields. The consideration of mainly free online learning resources will include a commentary on quality and perceived effectiveness.

Improved Computer-Aided Instruction by the Use of Interfaced Random-Access Audio-Visual Equipment. Report on Research Project No. P/24/1.

ERIC Educational Resources Information Center

Bryce, C. F. A.; Stewart, A. M.

A brief review of the characteristics of computer assisted instruction and the attributes of audiovisual media introduces this report on a project designed to improve the effectiveness of computer assisted learning through the incorporation of audiovisual materials. A discussion of the implications of research findings on the design and layout of…

Ermittlung von Wortstaemmen in russischen wissenschaftlichen Fachsprachen mit Hilfe des Computers (Establishing Word Stems in Scientific Russian With the Aid of a Computer)

ERIC Educational Resources Information Center

Halbauer, Siegfried

1976-01-01

It was considered that students of intensive scientific Russian courses could learn vocabulary more efficiently if they were taught word stems and how to combine them with prefixes and suffixes to form scientific words. The computer programs developed to identify the most important stems is discussed. (Text is in German.) (FB)

Evaluating Imaging and Computer-aided Detection and Diagnosis Devices at the FDA

PubMed Central

Gallas, Brandon D.; Chan, Heang-Ping; D’Orsi, Carl J.; Dodd, Lori E.; Giger, Maryellen L.; Gur, David; Krupinski, Elizabeth A.; Metz, Charles E.; Myers, Kyle J.; Obuchowski, Nancy A.; Sahiner, Berkman; Toledano, Alicia Y.; Zuley, Margarita L.

2017-01-01

This report summarizes the Joint FDA-MIPS Workshop on Methods for the Evaluation of Imaging and Computer-Assist Devices. The purpose of the workshop was to gather information on the current state of the science and facilitate consensus development on statistical methods and study designs for the evaluation of imaging devices to support US Food and Drug Administration submissions. Additionally, participants expected to identify gaps in knowledge and unmet needs that should be addressed in future research. This summary is intended to document the topics that were discussed at the meeting and disseminate the lessons that have been learned through past studies of imaging and computer-aided detection and diagnosis device performance. PMID:22306064

ICADx: interpretable computer aided diagnosis of breast masses

NASA Astrophysics Data System (ADS)

Kim, Seong Tae; Lee, Hakmin; Kim, Hak Gu; Ro, Yong Man

2018-02-01

In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has been successfully applied to medical image analysis including CADx. Existing deep learning based CADx approaches, however, have a limitation in explaining the diagnostic decision. In real clinical practice, clinical decisions could be made with reasonable explanation. So current deep learning approaches in CADx are limited in real world deployment. In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework. The proposed framework is devised with a generative adversarial network, which consists of interpretable diagnosis network and synthetic lesion generative network to learn the relationship between malignancy and a standardized description (BI-RADS). The lesion generative network and the interpretable diagnosis network compete in an adversarial learning so that the two networks are improved. The effectiveness of the proposed method was validated on public mammogram database. Experimental results showed that the proposed ICADx framework could provide the interpretability of mass as well as mass classification. It was mainly attributed to the fact that the proposed method was effectively trained to find the relationship between malignancy and interpretations via the adversarial learning. These results imply that the proposed ICADx framework could be a promising approach to develop the CADx system.

Dissecting Sequences of Regulation and Cognition: Statistical Discourse Analysis of Primary School Children's Collaborative Learning

ERIC Educational Resources Information Center

Molenaar, Inge; Chiu, Ming Ming

2014-01-01

Extending past research showing that regulative activities (metacognitive and relational) can aid learning, this study tests whether sequences of cognitive, metacognitive and relational activities affect subsequent cognition. Scaffolded by a computer avatar, 54 primary school students (working in 18 groups of 3) discussed writing a report about a…

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.

PubMed

Shin, Hoo-Chang; Roth, Holger R; Gao, Mingchen; Lu, Le; Xu, Ziyue; Nogues, Isabella; Yao, Jianhua; Mollura, Daniel; Summers, Ronald M

2016-05-01

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models pre-trained from natural image dataset to medical image tasks. In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computer-aided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks.

Modelling of Molecular Structures and Properties. Proceedings of the International Meeting of Physical Chemistry on Modeling of Molecular Structures and Properties in Physical Chemistry and Biophysics Organized by the Division de Chimie Physique of the Societe Francaise de Chimie Held in Nancy, France on 11-15 September 1989

DTIC Science & Technology

1990-01-01

expert systems, "intelligent" computer-aided instruction , symbolic learning . These aspects will be discussed, focusing on the specific problems the...VLSI chips) according to preliminary specifications. Finally ES are also used in computer-aided instruction (CAI) due to their ability of... instructions to process controllers), academic teaching (for mathematics , physics, foreign language, etc.). Domains of application The different

[The Meaning of "Understanding the Brain": Peeking into the Brain of a Computational Neuroscientist].

PubMed

Tanaka, Hirokazu

2016-11-01

What does "understanding the brain" mean? Here, I review how computational neuroscience, a theoretical approach to the brain, can aid our understanding of the brain. First, I illustrate the study of reinforcement learning and dopamine neurons and argue its success in the light of Marr's three levels of computation. Second, I discuss how Marr's program has led to a computational understanding of the brain, and present computational models of the motor cortex and of a spiking neural network as illustrative examples.

Understanding Mathematics and Logic Using BASIC Computer Games.

ERIC Educational Resources Information Center

Ahl, David H.

This combination teacher's guide and student workbook serves as a companion volume to 101 BASIC Computer Games (EM 011 681). It presents ideas, exercises and supplemental projects which will aid the teaching and learning of a wide variety of academic subjects in grades 7 through 12, although the emphasis is upon mathematics and logic. In addition,…

Adaptive Decision Aiding in Computer-Assisted Instruction: Adaptive Computerized Training System (ACTS).

ERIC Educational Resources Information Center

Hopf-Weichel, Rosemarie; And Others

This report describes results of the first year of a three-year program to develop and evaluate a new Adaptive Computerized Training System (ACTS) for electronics maintenance training. (ACTS incorporates an adaptive computer program that learns the student's diagnostic and decision value structure, compares it to that of an expert, and adapts the…

Using Maple to Implement eLearning Integrated with Computer Aided Assessment

ERIC Educational Resources Information Center

Blyth, Bill; Labovic, Aleksandra

2009-01-01

Advanced mathematics courses have been developed and refined by the first author, using an action research methodology, for more than a decade. These courses use the computer algebra system (CAS) Maple in an "immersion mode" where all presentations and student work are done using Maple. Assignments and examinations are Maple files downloaded from…

EduSpeak[R]: A Speech Recognition and Pronunciation Scoring Toolkit for Computer-Aided Language Learning Applications

ERIC Educational Resources Information Center

Franco, Horacio; Bratt, Harry; Rossier, Romain; Rao Gadde, Venkata; Shriberg, Elizabeth; Abrash, Victor; Precoda, Kristin

2010-01-01

SRI International's EduSpeak[R] system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology. Automatic pronunciation scoring allows the computer to provide feedback on the overall quality of pronunciation and to point to…

Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions.

PubMed

Mulfari, Davide; Palla, Alessandro; Fanucci, Luca

2017-01-01

In the field of deep learning, this paper presents the design of a wearable computer vision system for visually impaired users. The Assistive Technology solution exploits a powerful single board computer and smart glasses with a camera in order to allow its user to explore the objects within his surrounding environment, while it employs Google TensorFlow machine learning framework in order to real time classify the acquired stills. Therefore the proposed aid can increase the awareness of the explored environment and it interacts with its user by means of audio messages.

A Survey and Analysis of Military Computer-Based Training Systems: A Two Part Study. Volume I: A Survey and Annotated Bibliography of Authoring Aids for Instructional Systems Development.

ERIC Educational Resources Information Center

Logan, Robert S.

The authoring process and authoring aids which facilitate development of instructional materials have recently emerged as an area of concern in the field of instructional systems development (ISD). This process includes information gathering, its conversion to learning packages, its revision, and its formal publication. The purpose of this…

Utilization of Educationally Oriented Microcomputer Based Laboratories

ERIC Educational Resources Information Center

Fitzpatrick, Michael J.; Howard, James A.

1977-01-01

Describes one approach to supplying engineering and computer science educators with an economical portable digital systems laboratory centered around microprocessors. Expansion of the microcomputer based laboratory concept to include Learning Resource Aided Instruction (LRAI) systems is explored. (Author)

Virtual reality for the treatment of autism.

PubMed

Strickland, D

1997-01-01

Autism is a mental disorder which has received attention in several unrelated studies using virtual reality. One of the first attempts was to diagnose children with special needs at Tokyo University using a sandbox playing technique. Although operating the computer controls proved to be too difficult for the individuals with autism in the Tokyo study, research at the University of Nottingham, UK, is successful in using VR as a learning aid for children with a variety of disorders including autism. Both centers used flat screen computer systems with virtual scenes. Another study which concentrated on using VR as a learning aid with an immersive headset system is described in detail in this chapter. Perhaps because of the seriousness of the disorder and the lack of effective treatments, autism has received more study than attention deficit disorders, although both would appear to benefit from many of the same technology features.

[Medical computer-aided detection method based on deep learning].

PubMed

Tao, Pan; Fu, Zhongliang; Zhu, Kai; Wang, Lili

2018-03-01

This paper performs a comprehensive study on the computer-aided detection for the medical diagnosis with deep learning. Based on the region convolution neural network and the prior knowledge of target, this algorithm uses the region proposal network, the region of interest pooling strategy, introduces the multi-task loss function: classification loss, bounding box localization loss and object rotation loss, and optimizes it by end-to-end. For medical image it locates the target automatically, and provides the localization result for the next stage task of segmentation. For the detection of left ventricular in echocardiography, proposed additional landmarks such as mitral annulus, endocardial pad and apical position, were used to estimate the left ventricular posture effectively. In order to verify the robustness and effectiveness of the algorithm, the experimental data of ultrasonic and nuclear magnetic resonance images are selected. Experimental results show that the algorithm is fast, accurate and effective.

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

PubMed

Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

2017-11-01

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

Implementation of Web-Based Education in Egypt through Cloud Computing Technologies and Its Effect on Higher Education

ERIC Educational Resources Information Center

El-Seoud, M. Samir Abou; El-Sofany, Hosam F.; Taj-Eddin, Islam A. T. F.; Nosseir, Ann; El-Khouly, Mahmoud M.

2013-01-01

The information technology educational programs at most universities in Egypt face many obstacles that can be overcome using technology enhanced learning. An open source Moodle eLearning platform has been implemented at many public and private universities in Egypt, as an aid to deliver e-content and to provide the institution with various…

Stop Talking and Type: Comparing Virtual and Face-to-Face Mentoring in an Epistemic Game

ERIC Educational Resources Information Center

Bagley, E. A.; Shaffer, D. W.

2015-01-01

Research has shown that computer games and other virtual environments can support significant learning gains because they allow young people to explore complex concepts in simulated form. However, in complex problem-solving domains, complex thinking is learned not only by taking action, but also with the aid of mentors who provide guidance in the…

HYPER-­TVT: Development and Implementation of an Interactive Learning Environment for Students of Chemical and Process Engineering

ERIC Educational Resources Information Center

Santoro, Marina; Mazzotti, Marco

2006-01-01

Hyper-TVT is a computer-aided education system that has been developed at the Institute of Process Engineering at the ETH Zurich. The aim was to create an interactive learning environment for chemical and process engineering students. The topics covered are the most important multistage separation processes, i.e. fundamentals of separation…

Significant Increase in Factual Knowledge with Web-Assisted Problem-Based Learning as Part of an Undergraduate Cardio-Respiratory Curriculum

ERIC Educational Resources Information Center

Raupach, T.; Munscher, C.; Pukrop, T.; Anders, S.; Harendza, S.

2010-01-01

In recent years, increasing attention has been paid to web-based learning although the advantages of computer-aided instruction over traditional teaching formats still need to be confirmed. This study examined whether participation in an online module on the differential diagnosis of dyspnoea impacts on student performance in a multiple choice…

Dental students' preferences and performance in crown design: conventional wax-added versus CAD.

PubMed

Douglas, R Duane; Hopp, Christa D; Augustin, Marcus A

2014-12-01

The purpose of this study was to evaluate dental students' perceptions of traditional waxing vs. computer-aided crown design and to determine the effectiveness of either technique through comparative grading of the final products. On one of twoidentical tooth preparations, second-year students at one dental school fabricated a wax pattern for a full contour crown; on the second tooth preparation, the same students designed and fabricated an all-ceramic crown using computer-aided design (CAD) and computer-aided manufacturing (CAM) technology. Projects were graded for occlusion and anatomic form by three faculty members. On completion of the projects, 100 percent of the students (n=50) completed an eight-question, five-point Likert scalesurvey, designed to assess their perceptions of and learning associated with the two design techniques. The average grades for the crown design projects were 78.3 (CAD) and 79.1 (wax design). The mean numbers of occlusal contacts were 3.8 (CAD) and 2.9(wax design), which was significantly higher for CAD (p=0.02). The survey results indicated that students enjoyed designing afull contour crown using CAD as compared to using conventional wax techniques and spent less time designing the crown using CAD. From a learning perspective, students felt that they learned more about position and the size/strength of occlusal contacts using CAD. However, students recognized that CAD technology has limits in terms of representing anatomic contours and excursive occlusion compared to conventional wax techniques. The results suggest that crown design using CAD could be considered as an adjunct to conventional wax-added techniques in preclinical fixed prosthodontic curricula.

Teaching Guide and Problem Supplement. A Publication of the Exemplary Project Problem Solving Computer Style 1969-1970.

ERIC Educational Resources Information Center

New Orleans Public Schools, LA.

Secondary school teachers incorporating the use of a computer in algebra, trigonometry, advanced mathematics, chemistry, or physics classes are the individuals for whom this book is intended. The content included in it is designed to aid the learning of programing techniques and basic scientific or mathematical principles, and to offer some…

The Use and Benefits of Computer Aided Learning in the Assessment of the Laboratory Exercise "Enzyme Induction in Escherichia coli".

ERIC Educational Resources Information Center

Pamula, F.; And Others

1995-01-01

Describes an interactive computer program written to provide accurate and immediate feedback to students while they are processing experimental data. Discusses the problems inherent in laboratory courses that led to the development of this program. Advantages of the software include allowing students to work at their own pace in a nonthreatening…

Design Principles and First Educational Experiments of pR, a Platform to Infer Geo-Referenced Itineraries from Travel Stories

ERIC Educational Resources Information Center

Loustau, Pierre; Nodenot, Thierry; Gaio, Mauro

2009-01-01

Purpose: The purpose of this paper is to present a computational approach and a toolset to infer spatial displacements as they occur in route narrative documents and report on first experiments done to produce computer-aided learning (CAL) applications and instructional design editors that exploit the inferred georeferenced itineraries.…

Do Computers Improve the Drawing of a Geometrical Figure for 10 Year-Old Children?

ERIC Educational Resources Information Center

Martin, Perrine; Velay, Jean-Luc

2012-01-01

Nowadays, computer aided design (CAD) is widely used by designers. Would children learn to draw more easily and more efficiently if they were taught with computerised tools? To answer this question, we made an experiment designed to compare two methods for children to do the same drawing: the classical "pen and paper" method and a CAD…

Meaningful learning: The essential factor for conceptual change in limited or inappropriate propositional hierarchies leading to empowerment of learners

NASA Astrophysics Data System (ADS)

Novak, Joseph D.

2002-07-01

The construction and reconstruction of meanings by learners requires that they actively seek to integrate new knowledge with knowledge already in their cognitive structure. Ausubel's assimilation theory of cognitive learning has been shown to be effective in guiding research and instructional design to facilitate meaningful learning (Ausubel, The psychology of meaningful verbal learning, New York: Grune and Stratton, 1963; Educational psychology: A cognitive view, New York: Holt, Rinehart and Winston, 1968; The acquisition and retention of knowledge, Dordrecht: Kluwer, 2000). Gowin's Vee heuristic has been employed effectively to aid teachers and students in understanding the constructed nature of knowledge (Gowin, Educating, Ithaca, NY: Cornell University Press, 1981). Situated learning occurs when learning is by rote or at a lower level of meaningful learning. Concept mapping has been used effectively to aid meaningful learning with resulting modification of student's knowledge structures. When these knowledge structures are limited or faulty in some way, they may be referred to as Limited or Inappropriate Propositional Hierarchies (LIPH's). Conceptual change, or more accurately conceptual reconstrution, requires meaningful learning to modify LIPH's. Collaborative group learning facilitates meaningful learning and new knowledge construction. World-wide economic changes are forcing major changes in business and industry placing a premium on the power and value of knowledge and new knowledge production. These changes require changes in school and university education that centers on the nature and power of meaningful learning. New computer tools are available to facilitate teaching activities targeted at modifying LIPH's, and aiding meaningful learning in general.

Factors associated with parent-child communication about HIV/AIDS in the United States and Kenya: a cross-cultural comparison.

PubMed

Poulsen, Melissa N; Miller, Kim S; Lin, Carol; Fasula, Amy; Vandenhoudt, Hilde; Wyckoff, Sarah C; Ochura, Juliet; Obong'o, Christopher O; Forehand, Rex

2010-10-01

This study explored parent-child communication about HIV/AIDS among two populations disproportionately affected by HIV. Similar computer-assisted surveys were completed by parents of pre-teens, including 1,115 African American parents of 9-12-year-old children in southeastern US and 403 parents of 10-12-year-old children in Nyanza Province, Kenya. Multivariate analyses identified factors associated with parental report of ever talking to their child about HIV/AIDS. Twenty-nine percent of US parents and 40% in Kenya had never talked to their pre-teen about HIV/AIDS. In both countries, communication was more likely if parents perceived their child to be ready to learn about sex topics, had gotten information to educate their child about sex, and had greater sexual communication responsiveness (skill, comfort, and confidence communicating about sexuality). Programs are needed that help parents assess children's readiness to learn about sexual issues; access accurate information about adolescent sexual risks; and acquire the responsiveness needed to discuss sexual issues, including HIV/AIDS.

TRAD or CAD? A Comparison.

ERIC Educational Resources Information Center

Resetarits, Paul J.

1989-01-01

Studies whether traditional drafting equipment (TRAD) or computer aided drafting equipment (CAD) is more effective. Proposes that students using only CAD can learn principles of drafting as well as students using only TRAD. Reports no significant difference either on achievement or attitude. (MVL)

Using CASE Software to Teach Undergraduates Systems Analysis and Design.

ERIC Educational Resources Information Center

Wilcox, Russell E.

1988-01-01

Describes the design and delivery of a college course for information system students utilizing a Computer-Aided Software Engineering program. Discusses class assignments, cooperative learning, student attitudes, and the advantages of using this software in the course. (CW)

Medicine's Life Inside the Body

MedlinePlus

... Science > A Medicine's Life Inside the Body Inside Life Science View All Articles | Inside Life Science Home Page A Medicine's Life Inside the Body ... Medicines Work Computation Aids Drug Discovery This Inside Life Science article also appears on LiveScience . Learn about related ...

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

Measurement of information and communication technology experience and attitudes to e-learning of students in the healthcare professions: integrative review.

PubMed

Wilkinson, Ann; While, Alison E; Roberts, Julia

2009-04-01

This paper is a report of a review to describe and discuss the psychometric properties of instruments used in healthcare education settings measuring experience and attitudes of healthcare students regarding their information and communication technology skills and their use of computers and the Internet for education. Healthcare professionals are expected to be computer and information literate at registration. A previous review of evaluative studies of computer-based learning suggests that methods of measuring learners' attitudes to computers and computer aided learning are problematic. A search of eight health and social science databases located 49 papers, the majority published between 1995 and January 2007, focusing on the experience and attitudes of students in the healthcare professions towards computers and e-learning. An integrative approach was adopted, with narrative description of findings. Criteria for inclusion were quantitative studies using survey tools with samples of healthcare students and concerning computer and information literacy skills, access to computers, experience with computers and use of computers and the Internet for education purposes. Since the 1980s a number of instruments have been developed, mostly in the United States of America, to measure attitudes to computers, anxiety about computer use, information and communication technology skills, satisfaction and more recently attitudes to the Internet and computers for education. The psychometric properties are poorly described. Advances in computers and technology mean that many earlier tools are no longer valid. Measures of the experience and attitudes of healthcare students to the increased use of e-learning require development in line with computer and technology advances.

Transforming information for computer-aided instruction: using a Socratic Dialogue method to teach gross anatomy.

PubMed

Constantinou, P; Daane, S; Dev, P

1994-01-01

Traditional teaching of anatomy can be a difficult process of rote memorization. Computers allow information presentation to be much more dynamic, and interactive; the same information can be presented in multiple organizations. Using this idea, we have implemented a new pedagogy for computer-assisted instruction in The Anatomy Lesson, an interactive digital teacher which uses a "Socratic Dialogue" metaphor, as well as a textbook-like approach, to facilitate conceptual learning in anatomy.

Developing a Computer Touch-Screen Interactive Colorectal Screening Decision Aid for a Low-Literacy African American Population: Lessons Learned

PubMed Central

Bass, Sarah Bauerle; Gordon, Thomas F.; Ruzek, Sheryl Burt; Wolak, Caitlin; Ruggieri, Dominique; Mora, Gabriella; Rovito, Michael J.; Britto, Johnson; Parameswaran, Lalitha; Abedin, Zainab; Ward, Stephanie; Paranjape, Anuradha; Lin, Karen; Meyer, Brian; Pitts, Khaliah

2017-01-01

African Americans have higher colorectal cancer (CRC) mortality than White Americans and yet have lower rates of CRC screening. Increased screening aids in early detection and higher survival rates. Coupled with low literacy rates, the burden of CRC morbidity and mortality is exacerbated in this population, making it important to develop culturally and literacy appropriate aids to help low-literacy African Americans make informed decisions about CRC screening. This article outlines the development of a low-literacy computer touch-screen colonoscopy decision aid using an innovative marketing method called perceptual mapping and message vector modeling. This method was used to mathematically model key messages for the decision aid, which were then used to modify an existing CRC screening tutorial with different messages. The final tutorial was delivered through computer touch-screen technology to increase access and ease of use for participants. Testing showed users were not only more comfortable with the touch-screen technology but were also significantly more willing to have a colonoscopy compared with a “usual care group.” Results confirm the importance of including participants in planning and that the use of these innovative mapping and message design methods can lead to significant CRC screening attitude change. PMID:23132838

Problem-Solving Models for Computer Literacy: Getting Smarter at Solving Problems. Student Lessons.

ERIC Educational Resources Information Center

Moursund, David

This book is intended for use as a student guide. It is about human problem solving and provides information on how the mind works, placing a major emphasis on the role of computers as an aid in problem solving. The book is written with the underlying philosophy of discovery-based learning based on two premises: first, through the appropriate…

Effects of MicroCAD on Learning Fundamental Engineering Graphical Concepts: A Qualitative Study.

ERIC Educational Resources Information Center

Leach, James A.; Gull, Randall L.

1990-01-01

Students' reactions and performances were examined when taught engineering geometry concepts using a standard microcomputer-aided drafting software package. Two sample groups were compared based on their computer experience. Included are the methodology, data analysis, and conclusions. (KR)

Alternatives for Saving and Viewing CAD Graphics for the Web.

ERIC Educational Resources Information Center

Harris, La Verne Abe; Sadowski, Mary A.

2001-01-01

Introduces some alternatives for preparing and viewing computer aided design (CAD) graphics for Internet output on a budget, without the fear of copyright infringement, and without having to go back to college to learn a complex graphic application. (Author/YDS)

The community FabLab platform: applications and implications in biomedical engineering.

PubMed

Stephenson, Makeda K; Dow, Douglas E

2014-01-01

Skill development in science, technology, engineering and math (STEM) education present one of the most formidable challenges of modern society. The Community FabLab platform presents a viable solution. Each FabLab contains a suite of modern computer numerical control (CNC) equipment, electronics and computing hardware and design, programming, computer aided design (CAD) and computer aided machining (CAM) software. FabLabs are community and educational resources and open to the public. Development of STEM based workforce skills such as digital fabrication and advanced manufacturing can be enhanced using this platform. Particularly notable is the potential of the FabLab platform in STEM education. The active learning environment engages and supports a diversity of learners, while the iterative learning that is supported by the FabLab rapid prototyping platform facilitates depth of understanding, creativity, innovation and mastery. The product and project based learning that occurs in FabLabs develops in the student a personal sense of accomplishment, self-awareness, command of the material and technology. This helps build the interest and confidence necessary to excel in STEM and throughout life. Finally the introduction and use of relevant technologies at every stage of the education process ensures technical familiarity and a broad knowledge base needed for work in STEM based fields. Biomedical engineering education strives to cultivate broad technical adeptness, creativity, interdisciplinary thought, and an ability to form deep conceptual understanding of complex systems. The FabLab platform is well designed to enhance biomedical engineering education.

An evaluation of consensus techniques for diagnostic interpretation

NASA Astrophysics Data System (ADS)

Sauter, Jake N.; LaBarre, Victoria M.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Learning diagnostic labels from image content has been the standard in computer-aided diagnosis. Most computer-aided diagnosis systems use low-level image features extracted directly from image content to train and test machine learning classifiers for diagnostic label prediction. When the ground truth for the diagnostic labels is not available, reference truth is generated from the experts diagnostic interpretations of the image/region of interest. More specifically, when the label is uncertain, e.g. when multiple experts label an image and their interpretations are different, techniques to handle the label variability are necessary. In this paper, we compare three consensus techniques that are typically used to encode the variability in the experts labeling of the medical data: mean, median and mode, and their effects on simple classifiers that can handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees). Given that the NIH/NCI Lung Image Database Consortium (LIDC) data provides interpretations for lung nodules by up to four radiologists, we leverage the LIDC data to evaluate and compare these consensus approaches when creating computer-aided diagnosis systems for lung nodules. First, low-level image features of nodules are extracted and paired with their radiologists semantic ratings (1= most likely benign, , 5 = most likely malignant); second, machine learning multi-class classifiers that handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees) are built to predict the lung nodules semantic ratings. We show that the mean-based consensus generates the most robust classi- fier overall when compared to the median- and mode-based consensus. Lastly, the results of this study show that, when building CAD systems with uncertain diagnostic interpretation, it is important to evaluate different strategies for encoding and predicting the diagnostic label.

The use of computer-aided learning in chemistry laboratory instruction

NASA Astrophysics Data System (ADS)

Allred, Brian Robert Tracy

This research involves developing and implementing computer software for chemistry laboratory instruction. The specific goal is to design the software and investigate whether it can be used to introduce concepts and laboratory procedures without a lecture format. This would allow students to conduct an experiment even though they may not have been introduced to the chemical concept in their lecture course. This would also allow for another type of interaction for those students who respond more positively to a visual approach to instruction. The first module developed was devoted to using computer software to help introduce students to the concepts related to thin-layer chromatography and setting up and running an experiment. This was achieved through the use of digitized pictures and digitized video clips along with written information. A review quiz was used to help reinforce the learned information. The second module was devoted to the concept of the "dry lab". This module presented students with relevant information regarding the chemical concepts and then showed them the outcome of mixing solutions. By these observations, they were to determine the composition of unknown solutions based on provided descriptions and comparison with their written observations. The third piece of the software designed was a computer game. This program followed the first two modules in providing information the students were to learn. The difference here, though, was incorporating a game scenario for students to use to help reinforce the learning. Students were then assessed to see how much information they retained after playing the game. In each of the three cases, a control group exposed to the traditional lecture format was used. Their results were compared to the experimental group using the computer modules. Based upon the findings, it can be concluded that using technology to aid in the instructional process is definitely of benefit and students were more successful in learning. It is important to note, though, that one single type of instructional method is not the best way to inspire learning. It seems multiple methods provide the best educational experience for all.

Student Assistant for Learning from Text (SALT): a hypermedia reading aid.

PubMed

MacArthur, C A; Haynes, J B

1995-03-01

Student Assistant for Learning from Text (SALT) is a software system for developing hypermedia versions of textbooks designed to help students with learning disabilities and other low-achieving students to compensate for their reading difficulties. In the present study, 10 students with learning disabilities (3 young women and 7 young men ages 15 to 17) in Grades 9 and 10 read passages from a science textbook using a basic computer version and an enhanced computer version. The basic version included the components found in the printed textbook (text, graphics, outline, and questions) and a notebook. The enhanced version added speech synthesis, an on-line glossary, links between questions and text, highlighting of main ideas, and supplementary explanations that summarized important ideas. Students received significantly higher comprehension scores using the enhanced version. Furthermore, students preferred the enhanced version and thought it helped them learn the material better.

Transforming information for computer-aided instruction: using a Socratic Dialogue method to teach gross anatomy.

PubMed Central

Constantinou, P.; Daane, S.; Dev, P.

1994-01-01

Traditional teaching of anatomy can be a difficult process of rote memorization. Computers allow information presentation to be much more dynamic, and interactive; the same information can be presented in multiple organizations. Using this idea, we have implemented a new pedagogy for computer-assisted instruction in The Anatomy Lesson, an interactive digital teacher which uses a "Socratic Dialogue" metaphor, as well as a textbook-like approach, to facilitate conceptual learning in anatomy. Images Figure 1 PMID:7949881

Computer-based visual communication in aphasia.

PubMed

Steele, R D; Weinrich, M; Wertz, R T; Kleczewska, M K; Carlson, G S

1989-01-01

The authors describe their recently developed Computer-aided VIsual Communication (C-VIC) system, and report results of single-subject experimental designs probing its use with five chronic, severely impaired aphasic individuals. Studies replicate earlier results obtained with a non-computerized system, demonstrate patient competence with the computer implementation, extend the system's utility, and identify promising areas of application. Results of the single-subject experimental designs clarify patients' learning, generalization, and retention patterns, and highlight areas of performance difficulties. Future directions for the project are indicated.

The TI-99/4A Software.

ERIC Educational Resources Information Center

Wrege, Rachael; And Others

1982-01-01

Describes the software modules produced by Texas Instruments for use with the TI-99/4A home computer. Among the modules described are: Personal Real Estate, Programing Aids, Home Financial Decisions, Music Maker, Weight Control and Nutrition, Early Learning Fun, and Tax/Investment Record Keeping. (JL)

Smart Networking Decisions: A Kase Study.

ERIC Educational Resources Information Center

Sturgeon, Julie

1999-01-01

Describes one decision-making approach for quickly implementing a communications network into a school district. The use of volunteer labor for wiring installation, computer selection focusing on standardization to aid in troubleshooting, and an intranet system to achieve efficiency and learning opportunities for teachers and administrative…

Lessons learned from the design of chemical space networks and opportunities for new applications.

PubMed

Vogt, Martin; Stumpfe, Dagmar; Maggiora, Gerald M; Bajorath, Jürgen

2016-03-01

The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer-Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.

Lessons learned from the design of chemical space networks and opportunities for new applications

NASA Astrophysics Data System (ADS)

Vogt, Martin; Stumpfe, Dagmar; Maggiora, Gerald M.; Bajorath, Jürgen

2016-03-01

The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer- Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.

Educational Technology in the 21st Century. Joint Hearing before the Committee on Science and the Committee on Economic and Educational Opportunities. House of Representatives, One Hundred Fourth Congress, First Session.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science and Technology.

This document presents witness testimony and supplemental materials from a Congressional hearing addressing the potential as well as the affordability of educational technology and the classroom of the future, where computers and computer networks will increasingly aid teachers and facilitate learning. Those presenting prepared statements are…

Instructional design in mathematics for undergraduate students based on learning by mistakes approach utilizing scilab assistance

NASA Astrophysics Data System (ADS)

Kartika, H.

2018-03-01

The issue related to making mistake while learning such as negative emotion is found while students learn mathematics with the aid of a computer. When the computer output showed a mistake message, the students considered it as a computer software malfunction. Based on this issue, the writer designs an instructional model based on learning by mistake approach and which is Scilab assisted. The method used in this research is research design involving undergraduate students in matrix algebra courses. The data collected throught survey with questionnaire to gain feedback about the approach implemented. The data analyzed using quantitative descriptive. The instructional design proposed is the student act as a mistake corrector while the teacher acts as a mistake maker. Teacher deliberately makes mistakes with the help of Scilab software. On the other hand, students correct, analyze and explain errors resulting from Scilab software. The result of this research is an ICT based instructional design which is expected to be applicable as an alternative learning in directing students to think positively about mistakes in learning. Furthermore, students are also expected to improve their ability in understanding and thinking critically while solving problems and improving themselves in learning mathematics.

Learning Reverse Engineering and Simulation with Design Visualization

NASA Technical Reports Server (NTRS)

Hemsworth, Paul J.

2018-01-01

The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing metrology data with Computer-Aided Design (CAD) models and simulations to provide accurate visual representations that aid in decision-making. The capability to measure and simulate objects in real time helps to predict and avoid potential problems before they become expensive in addition to facilitating the planning of operations. I had the opportunity to work on existing and new models and simulations in support of DV and NASA’s Exploration Ground Systems (EGS).

Towards Building a Computer Aided Education System for Special Students Using Wearable Sensor Technologies

PubMed Central

Mehmood, Raja Majid; Lee, Hyo Jong

2017-01-01

Human computer interaction is a growing field in terms of helping people in their daily life to improve their living. Especially, people with some disability may need an interface which is more appropriate and compatible with their needs. Our research is focused on similar kinds of problems, such as students with some mental disorder or mood disruption problems. To improve their learning process, an intelligent emotion recognition system is essential which has an ability to recognize the current emotional state of the brain. Nowadays, in special schools, instructors are commonly use some conventional methods for managing special students for educational purposes. In this paper, we proposed a novel computer aided method for instructors at special schools where they can teach special students with the support of our system using wearable technologies. PMID:28208734

Organisational aspects and benchmarking of e-learning initiatives: a case study with South African community health workers.

PubMed

Reisach, Ulrike; Weilemann, Mitja

2016-06-01

South Africa desperately needs a comprehensive approach to fight HIV/AIDS. Education is crucial to reach this goal and Internet and e-learning could offer huge opportunities to broaden and deepen the knowledge basis. But due to the huge societal and digital divide between rich and poor areas, e-learning is difficult to realize in the townships. Community health workers often act as mediators and coaches for people seeking medical and personal help. They could give good advice regarding hygiene, nutrition, protection of family members in case of HIV/AIDS and finding legal ways to earn one's living if they were trained to do so. Therefore they need to have a broader general knowledge. Since learning opportunities in the townships are scarce, a system for e-learning has to be created in order to overcome the lack of experience with computers or the Internet and to enable them to implement a network of expertise. The article describes how the best international resources on basic medical knowledge, HIV/AIDS as well as on basic economic and entrepreneurial skills were benchmarked to be integrated into an e-learning system. After tests with community health workers, researchers developed recommendations on building a self-sustaining system for learning, including a network of expertise and best practice sharing. The article explains the opportunities and challenges for community health workers, which could provide information for other parts of the world with similar preconditions of rural poverty. © The Author(s) 2015.

Scientists at Work. Final Report.

ERIC Educational Resources Information Center

Education Turnkey Systems, Inc., Falls Church, VA.

This report summarizes activities related to the development, field testing, evaluation, and marketing of the "Scientists at Work" program which combines computer assisted instruction with database tools to aid cognitively impaired middle and early high school children in learning and applying thinking skills to science. The brief report reviews…

A New Approach to Develop Computer-aided Diagnosis Scheme of Breast Mass Classification Using Deep Learning Technology

PubMed Central

Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

2017-01-01

PURPOSE To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. METHODS An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. RESULTS The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. CONCLUSIONS This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process. PMID:28436410

A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.

PubMed

Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

2017-01-01

To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process.

A Response Evaluation Approach: An Aid for Computer Assisted Instruction Lesson Writing.

DTIC Science & Technology

1980-09-01

Arnheim, Rudolph, Visual Thinking, Berkeley and Los Angeles, California: UniversiEy of California Press, 1969. Bruner , Jerome S., Goodnow, Jacqueline J...describing a further path for each student, which would optimize his learning experience, must be at the machine’s disposal. In the student-directed...approach, the sequence of the material presented is altered only at the request of the student. The approach uses the aspect of learning by dis

Comparison of three aids for teaching lumbar surgical anatomy.

PubMed

Das, S; Mitchell, P

2013-08-01

Reduced surgeons' training time has resulted in a need to increase the speed of learning. Currently, anatomy education involves traditional (textbooks, physical models, cadaveric dissection/prosection) and recent (electronic) techniques. As yet there are no available data comparing their performance. The performance of three anatomical training aids at teaching the surgical anatomy of the lumbar spinal was compared. The aids used were paper-based images, a three-dimensional plastic model and a semitransparent computer model. Fifty one study subjects were recruited from a population of junior doctors, nurses, medical and nursing students. Three study groups were created which differed in the order of presenting the aids. For each subject, spinal anatomy was revised by the investigator, teaching them the anatomy using each aid. They were specifically taught the locations of the intervertebral disc, pedicles and nerve roots in the lateral recesses. They then drew these structures on a response sheet (three response sheets per subject). The computer model was the best at allowing subjects accurately to determine structure location followed by the paper-based images, the plastic model was the worst. Accuracy improved with successive models used but this trend was not significant. Subjects were not versed in spinal anatomy beforehand, so meaningful baseline measures were not available. The educational performance of surgical anatomical training aids can be measured and compared. A computer generated 3 dimensional model gave the best results with paper-based images second and the plastic model third.

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

PubMed

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

2018-01-01

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

Computer-aided diagnosis of early knee osteoarthritis based on MRI T2 mapping.

PubMed

Wu, Yixiao; Yang, Ran; Jia, Sen; Li, Zhanjun; Zhou, Zhiyang; Lou, Ting

2014-01-01

This work was aimed at studying the method of computer-aided diagnosis of early knee OA (OA: osteoarthritis). Based on the technique of MRI (MRI: Magnetic Resonance Imaging) T2 Mapping, through computer image processing, feature extraction, calculation and analysis via constructing a classifier, an effective computer-aided diagnosis method for knee OA was created to assist doctors in their accurate, timely and convenient detection of potential risk of OA. In order to evaluate this method, a total of 1380 data from the MRI images of 46 samples of knee joints were collected. These data were then modeled through linear regression on an offline general platform by the use of the ImageJ software, and a map of the physical parameter T2 was reconstructed. After the image processing, the T2 values of ten regions in the WORMS (WORMS: Whole-organ Magnetic Resonance Imaging Score) areas of the articular cartilage were extracted to be used as the eigenvalues in data mining. Then,a RBF (RBF: Radical Basis Function) network classifier was built to classify and identify the collected data. The classifier exhibited a final identification accuracy of 75%, indicating a good result of assisting diagnosis. Since the knee OA classifier constituted by a weights-directly-determined RBF neural network didn't require any iteration, our results demonstrated that the optimal weights, appropriate center and variance could be yielded through simple procedures. Furthermore, the accuracy for both the training samples and the testing samples from the normal group could reach 100%. Finally, the classifier was superior both in time efficiency and classification performance to the frequently used classifiers based on iterative learning. Thus it was suitable to be used as an aid to computer-aided diagnosis of early knee OA.

PCACE-Personal-Computer-Aided Cabling Engineering

NASA Technical Reports Server (NTRS)

Billitti, Joseph W.

1987-01-01

PCACE computer program developed to provide inexpensive, interactive system for learning and using engineering approach to interconnection systems. Basically database system that stores information as files of individual connectors and handles wiring information in circuit groups stored as records. Directly emulates typical manual engineering methods of handling data, thus making interface between user and program very natural. Apple version written in P-Code Pascal and IBM PC version of PCACE written in TURBO Pascal 3.0

Information Retention and Overload in First-Time Hearing Aid Users: An Interactive Multimedia Educational Solution.

PubMed

Ferguson, Melanie; Brandreth, Marian; Brassington, William; Wharrad, Heather

2015-09-01

An educational intervention to improve knowledge of hearing aids and communication in first-time hearing aid users was assessed. This intervention was based on the concept of reusable learning objects (RLOs). A randomized controlled trial was conducted. One group received the educational intervention, and the other acted as a control group. RLOs were delivered online and through DVD for television and personal computer. Knowledge of both practical and psychosocial aspects of hearing aids and communication was assessed using a free-recall method 6 weeks postfitting. Knowledge of both practical and psychosocial issues was significantly higher in the group that received the RLOs than in the control group. Moderate to large effect sizes indicated that these differences were clinically significant. An educational intervention that supplements clinical practice results in improved knowledge in first-time hearing aid users.

Where Are the Quadratic's Complex Roots?

ERIC Educational Resources Information Center

Páll-Szabó, Ágnes Orsolya

2015-01-01

A picture is worth more than a thousand words--in mathematics too. Many students fail in learning mathematics because, in some cases, teachers do not offer the necessary visualization. Nowadays technology overcomes this problem: computer aided instruction is one of the most efficients methods in teaching mathematics. In this article we try to…

Calculus Courses' Assessment Data

ERIC Educational Resources Information Center

Pauna, Matti

2017-01-01

In this paper we describe computer-aided assessment methods used in online Calculus courses and the data they produce. The online learning environment collects a lot of time-stamped data about every action a student makes. Assessment data can be harnessed into use as a feedback, predictor, and recommendation facility for students and instructors.…

Broadcasting a Lab Measurement over Existing Conductor Networks

ERIC Educational Resources Information Center

Knipp, Peter A.

2009-01-01

Students learn about physical laws and the scientific method when they analyze experimental data in a laboratory setting. Three common sources exist for the experimental data that they analyze: (1) "hands-on" measurements by the students themselves, (2) electronic transfer (by downloading a spreadsheet, video, or computer-aided data-acquisition…

Case-Based Learning for Orofacial Pain and Temporomandibular Disorders.

ERIC Educational Resources Information Center

Clark, Glenn T.; And Others

1993-01-01

The use of interactive computer-based simulation of cases of chronic orofacial pain and temporomandibular joint disfunction patients for clinical dental education is described. Its application as a voluntary study aid in a third-year dental course is evaluated for effectiveness and for time factors in case completion. (MSE)

Interaction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments

ERIC Educational Resources Information Center

Eagle, Michael; Hicks, Drew; Barnes, Tiffany

2015-01-01

Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…

NATAL-74; Towards a Common Programming Language for CAL.

ERIC Educational Resources Information Center

Brahan, J. W.; Colpitts, B. A.

NATAL-74 is a programing language designed for Canadian computer aided learning (CAL) programs. The language has two fundamental elements: the UNIT provides the interface between the student and the subject matter, and the PROCEDURE element embodies teaching strategy. Desirable features of several programing languages have been adapted to cope…

E-Assessment Data Compatibility Resolution Methodology with Bidirectional Data Transformation

ERIC Educational Resources Information Center

Malik, Kaleem Razzaq; Ahmad, Tauqir

2017-01-01

Electronic Assessment (E-Assessment) also known as computer aided assessment for the purposes involving diagnostic, formative or summative examining using data analysis. Digital assessments come commonly from social, academic, and adaptive learning in machine readable forms to deliver the machine scoring function. To achieve real-time and smart…

Melanges Pedagogiques (Pedagogical Mixture), 1983.

ERIC Educational Resources Information Center

Melanges Pedagogiques, 1983

1983-01-01

The 1983 issue of the journal on second language teaching and learning contains six articles in French. These include the following: "E.A.O.: Expression avec ordinateur (E.A.O.: Computer-Aided Expression)" (Daniele Abe, Michele Cembalo); "Ou suis-je? De la relation apprenant/environnement (Where Am I? On the Learner/Environment…

How Can Intelligent CAL Better Adapt to Learners?

ERIC Educational Resources Information Center

Boyd, Gary McI.; Mitchell, P. David

1992-01-01

Discusses intelligent computer-aided learning (ICAL) support systems and considers learner characteristics as elements of ICAL student models. Cybernetic theory and attribute-treatment results are discussed, six components of a student model for tutoring are described, and methods for determining the student's model of the tutor are examined. (22…

Inquiry-Based Learning in Remote Sensing: A Space Balloon Educational Experiment

ERIC Educational Resources Information Center

Mountrakis, Giorgos; Triantakonstantis, Dimitrios

2012-01-01

Teaching remote sensing in higher education has been traditionally restricted in lecture and computer-aided laboratory activities. This paper presents and evaluates an engaging inquiry-based educational experiment. The experiment was incorporated in an introductory remote sensing undergraduate course to bridge the gap between theory and…

Practicality in Virtuality: Finding Student Meaning in Video Game Education

NASA Astrophysics Data System (ADS)

Barko, Timothy; Sadler, Troy D.

2013-04-01

This paper looks at the conceptual differences between video game learning and traditional classroom and laboratory learning. It explores the notion of virtual experience by comparing a commonly used high school laboratory protocol on DNA extraction with a similar experience provided by a biotechnology themed video game. When considered conceptually, the notion of virtual experience is not limited to those experiences generated by computer aided technology, as with a video game or computer simulation. The notion of virtuality can apply to many real world experiences as well. It is proposed that the medium of the learning experience, be it video game or classroom, is not an important distinction to consider; instead, we should seek to determine what kinds of meaningful experiences apply for both classrooms and video games.

Deep learning in mammography and breast histology, an overview and future trends.

PubMed

Hamidinekoo, Azam; Denton, Erika; Rampun, Andrik; Honnor, Kate; Zwiggelaar, Reyer

2018-07-01

Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promising results reported by deep learning based methods in breast imaging, an overview of the recent state-of-the-art deep learning based CAD systems developed for mammography and breast histopathology images is presented. In this study, the relationship between mammography and histopathology phenotypes is described, which takes biological aspects into account. We propose a computer based breast cancer modelling approach: the Mammography-Histology-Phenotype-Linking-Model, which develops a mapping of features/phenotypes between mammographic abnormalities and their histopathological representation. Challenges are discussed along with the potential contribution of such a system to clinical decision making and treatment management. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Providing Formative Feedback From a Summative Computer-aided Assessment

PubMed Central

Sewell, Robert D. E.

2007-01-01

Objectives To examine the effectiveness of providing formative feedback for summative computer-aided assessment. Design Two groups of first-year undergraduate life science students in pharmacy and neuroscience who were studying an e-learning package in a common pharmacology module were presented with a computer-based summative assessment. A sheet with individualized feedback derived from each of the 5 results sections of the assessment was provided to each student. Students were asked via a questionnaire to evaluate the form and method of feedback. Assessment The students were able to reflect on their performance and use the feedback provided to guide their future study or revision. There was no significant difference between the responses from pharmacy and neuroscience students. Students' responses on the questionnaire indicated a generally positive reaction to this form of feedback. Conclusions Findings suggest that additional formative assessment conveyed by this style and method would be appreciated and valued by students. PMID:17533442

Interactive Visualization of Infrared Spectral Data: Synergy of Computation, Visualization, and Experiment for Learning Spectroscopy

NASA Astrophysics Data System (ADS)

Lahti, Paul M.; Motyka, Eric J.; Lancashire, Robert J.

2000-05-01

A straightforward procedure is described to combine computation of molecular vibrational modes using commonly available molecular modeling programs with visualization of the modes using advanced features of the MDL Information Systems Inc. Chime World Wide Web browser plug-in. Minor editing of experimental spectra that are stored in the JCAMP-DX format allows linkage of IR spectral frequency ranges to Chime molecular display windows. The spectra and animation files can be combined by Hypertext Markup Language programming to allow interactive linkage between experimental spectra and computationally generated vibrational displays. Both the spectra and the molecular displays can be interactively manipulated to allow the user maximum control of the objects being viewed. This procedure should be very valuable not only for aiding students through visual linkage of spectra and various vibrational animations, but also by assisting them in learning the advantages and limitations of computational chemistry by comparison to experiment.

Recent development on computer aided tissue engineering--a review.

PubMed

Sun, Wei; Lal, Pallavi

2002-02-01

The utilization of computer-aided technologies in tissue engineering has evolved in the development of a new field of computer-aided tissue engineering (CATE). This article reviews recent development and application of enabling computer technology, imaging technology, computer-aided design and computer-aided manufacturing (CAD and CAM), and rapid prototyping (RP) technology in tissue engineering, particularly, in computer-aided tissue anatomical modeling, three-dimensional (3-D) anatomy visualization and 3-D reconstruction, CAD-based anatomical modeling, computer-aided tissue classification, computer-aided tissue implantation and prototype modeling assisted surgical planning and reconstruction.

Saving Strokes with Space Technology

NASA Technical Reports Server (NTRS)

1980-01-01

Inventor Dave Pelz developed a space spinoff Teacher Alignment Computer for Sunmark Preceptor Golf Ltd. which helps golfers learn proper putting aim. The light beam, reflected into the computer, measures putter alignment and lights atop the box tell the golfer he is on target or off to either side and how much. A related putting aid idea is to stroke the ball at the putter's "sweet spot," which is bracketed by metal prongs. Regular practice develops solid impacts for better putting.

Development of Ideas in a GeoGebra-Aided Mathematics Instruction

ERIC Educational Resources Information Center

Ljajko, Eugen; Ibro, Vait

2013-01-01

With GeoGebra introduced into mathematics instruction the teaching/learning process is not improved in terms of speed and quality only. Mathematical concepts, rules and procedures must be adjusted to the new environment. On the other hand, characteristics of the computer and the educational software in use must be thoroughly examined and a…

The Effect of Three-Dimensional Simulations on the Understanding of Chemical Structures and Their Properties

ERIC Educational Resources Information Center

Urhahne, Detlef; Nick, Sabine; Schanze, Sascha

2009-01-01

In a series of three experimental studies, the effectiveness of three-dimensional computer simulations to aid the understanding of chemical structures and their properties was investigated. Arguments for the usefulness of three-dimensional simulations were derived from Mayer's generative theory of multimedia learning. Simulations might lead to a…

A Group-Decision Approach for Evaluating Educational Web Sites

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Huanga, Tony C. K.; Tseng, Judy C. R.

2004-01-01

With the advent of network technologies, many educational web sites have been developed to assist students in the learning of subjects on computer networks. However, without proper aid, students may have difficulty in selecting appropriate web sites, that are of benefit to them; hence, studying, evaluating and recommending educational web sites…

Learning through Plastic Filament Extrusion

ERIC Educational Resources Information Center

Orr, Taylor; Flowers, Jim

2015-01-01

3D printing is becoming ever more popular in both the manufacturing world as well as in technology and engineering education classrooms all over the United States. 3D printing is an additive manufacturing process in which successive layers of material are built up to produce three-dimensional objects from computer-aided design (CAD) files, making…

The Potential Impact of Computer-Aided Assessment Technology in Higher Education

ERIC Educational Resources Information Center

Tshibalo, A. E.

2007-01-01

Distance learning generally separates students from educators, and demands that interventions be put in place to counter the constraints that this distance poses to learners and educators. Furthermore "Increased number of students in Higher Education and the corresponding increase in time spent by staff on assessment has encouraged interest…

An Interactive Computer Aided Electrical Engineering Education Package.

ERIC Educational Resources Information Center

Cavati, Cicero Romao

This paper describes an educational package to help the learning process. A case study is presented of an energy distribution course in the Electrical Engineering Department at the Federal University of Espirito Santo (UFES). The advantages of the developed package are shown by comparing it with the traditional academic book. This package presents…

The Spread of ICT Innovation in Accounting Education

ERIC Educational Resources Information Center

Jebeile, Sam; Abeysekera, Indra

2010-01-01

This paper conveys the findings of a study conducted to evaluate the initiation of an interactive online computer-assisted learning module, called WEBLEARN, in an undergraduate introductory accounting course at an Australian university. The purpose was to aid students in the preparation of cash flow statements, a topic that from the student…

Tips on Creating Complex Geometry Using Solid Modeling Software

ERIC Educational Resources Information Center

Gow, George

2008-01-01

Three-dimensional computer-aided drafting (CAD) software, sometimes referred to as "solid modeling" software, is easy to learn, fun to use, and becoming the standard in industry. However, many users have difficulty creating complex geometry with the solid modeling software. And the problem is not entirely a student problem. Even some teachers and…

Technology-Supported Orchestration Matters: Outperforming Paper-Based Scripting in a Jigsaw Classroom

ERIC Educational Resources Information Center

Balestrini, Mara; Hernandez-Leo, Davinia; Nieves, Raul; Blat, Josep

2014-01-01

Under the umbrella of ubiquitous technologies, many computational artifacts have been designed to enhance the learning experience in physical settings such as classrooms or playgrounds, but few of them focus on aiding orchestration. This paper presents a systematic evaluation of the signal orchestration system (SOS) used by students for a jigsaw…

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

NASA Astrophysics Data System (ADS)

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

PubMed

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-15

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

PubMed Central

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-01-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features. PMID:27079888

Hierarchical kernel mixture models for the prediction of AIDS disease progression using HIV structural gp120 profiles

PubMed Central

2010-01-01

Changes to the glycosylation profile on HIV gp120 can influence viral pathogenesis and alter AIDS disease progression. The characterization of glycosylation differences at the sequence level is inadequate as the placement of carbohydrates is structurally complex. However, no structural framework is available to date for the study of HIV disease progression. In this study, we propose a novel machine-learning based framework for the prediction of AIDS disease progression in three stages (RP, SP, and LTNP) using the HIV structural gp120 profile. This new intelligent framework proves to be accurate and provides an important benchmark for predicting AIDS disease progression computationally. The model is trained using a novel HIV gp120 glycosylation structural profile to detect possible stages of AIDS disease progression for the target sequences of HIV+ individuals. The performance of the proposed model was compared to seven existing different machine-learning models on newly proposed gp120-Benchmark_1 dataset in terms of error-rate (MSE), accuracy (CCI), stability (STD), and complexity (TBM). The novel framework showed better predictive performance with 67.82% CCI, 30.21 MSE, 0.8 STD, and 2.62 TBM on the three stages of AIDS disease progression of 50 HIV+ individuals. This framework is an invaluable bioinformatics tool that will be useful to the clinical assessment of viral pathogenesis. PMID:21143806

Computer-Based Technologies in Dentistry: Types and Applications

PubMed Central

Albuha Al-Mussawi, Raja’a M.; Farid, Farzaneh

2016-01-01

During dental education, dental students learn how to examine patients, make diagnosis, plan treatment and perform dental procedures perfectly and efficiently. However, progresses in computer-based technologies including virtual reality (VR) simulators, augmented reality (AR) and computer aided design/computer aided manufacturing (CAD/CAM) systems have resulted in new modalities for instruction and practice of dentistry. Virtual reality dental simulators enable repeated, objective and assessable practice in various controlled situations. Superimposition of three-dimensional (3D) virtual images on actual images in AR allows surgeons to simultaneously visualize the surgical site and superimpose informative 3D images of invisible regions on the surgical site to serve as a guide. The use of CAD/CAM systems for designing and manufacturing of dental appliances and prostheses has been well established. This article reviews computer-based technologies, their application in dentistry and their potentials and limitations in promoting dental education, training and practice. Practitioners will be able to choose from a broader spectrum of options in their field of practice by becoming familiar with new modalities of training and practice. PMID:28392819

Computer-Based Technologies in Dentistry: Types and Applications.

PubMed

Albuha Al-Mussawi, Raja'a M; Farid, Farzaneh

2016-06-01

During dental education, dental students learn how to examine patients, make diagnosis, plan treatment and perform dental procedures perfectly and efficiently. However, progresses in computer-based technologies including virtual reality (VR) simulators, augmented reality (AR) and computer aided design/computer aided manufacturing (CAD/CAM) systems have resulted in new modalities for instruction and practice of dentistry. Virtual reality dental simulators enable repeated, objective and assessable practice in various controlled situations. Superimposition of three-dimensional (3D) virtual images on actual images in AR allows surgeons to simultaneously visualize the surgical site and superimpose informative 3D images of invisible regions on the surgical site to serve as a guide. The use of CAD/CAM systems for designing and manufacturing of dental appliances and prostheses has been well established. This article reviews computer-based technologies, their application in dentistry and their potentials and limitations in promoting dental education, training and practice. Practitioners will be able to choose from a broader spectrum of options in their field of practice by becoming familiar with new modalities of training and practice.

Enabling an Integrated Rate-temporal Learning Scheme on Memristor

NASA Astrophysics Data System (ADS)

He, Wei; Huang, Kejie; Ning, Ning; Ramanathan, Kiruthika; Li, Guoqi; Jiang, Yu; Sze, Jiayin; Shi, Luping; Zhao, Rong; Pei, Jing

2014-04-01

Learning scheme is the key to the utilization of spike-based computation and the emulation of neural/synaptic behaviors toward realization of cognition. The biological observations reveal an integrated spike time- and spike rate-dependent plasticity as a function of presynaptic firing frequency. However, this integrated rate-temporal learning scheme has not been realized on any nano devices. In this paper, such scheme is successfully demonstrated on a memristor. Great robustness against the spiking rate fluctuation is achieved by waveform engineering with the aid of good analog properties exhibited by the iron oxide-based memristor. The spike-time-dependence plasticity (STDP) occurs at moderate presynaptic firing frequencies and spike-rate-dependence plasticity (SRDP) dominates other regions. This demonstration provides a novel approach in neural coding implementation, which facilitates the development of bio-inspired computing systems.

Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students.

PubMed

Khumrin, Piyapong; Ryan, Anna; Judd, Terry; Verspoor, Karin

2017-01-01

Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is both critical and challenging. In this paper, we describe the development of a machine learning model to support medical students' diagnostic decisions. Machine learning models were trained on 208 clinical cases presenting with abdominal pain, to predict five diagnoses. We assessed which of these models are likely to be most effective for use in an e-learning tool that allows students to interact with a virtual patient. The broader goal is to utilise these models to generate personalised feedback based on the specific patient information requested by students and their active diagnostic hypotheses.

The Computer as a Tool for Learning

PubMed Central

Starkweather, John A.

1986-01-01

Experimenters from the beginning recognized the advantages computers might offer in medical education. Several medical schools have gained experience in such programs in automated instruction. Television images and graphic display combined with computer control and user interaction are effective for teaching problem solving. The National Board of Medical Examiners has developed patient-case simulation for examining clinical skills, and the National Library of Medicine has experimented with combining media. Advances from the field of artificial intelligence and the availability of increasingly powerful microcomputers at lower cost will aid further development. Computers will likely affect existing educational methods, adding new capabilities to laboratory exercises, to self-assessment and to continuing education. PMID:3544511

WINPEPI updated: computer programs for epidemiologists, and their teaching potential

PubMed Central

2011-01-01

Background The WINPEPI computer programs for epidemiologists are designed for use in practice and research in the health field and as learning or teaching aids. The programs are free, and can be downloaded from the Internet. Numerous additions have been made in recent years. Implementation There are now seven WINPEPI programs: DESCRIBE, for use in descriptive epidemiology; COMPARE2, for use in comparisons of two independent groups or samples; PAIRSetc, for use in comparisons of paired and other matched observations; LOGISTIC, for logistic regression analysis; POISSON, for Poisson regression analysis; WHATIS, a "ready reckoner" utility program; and ETCETERA, for miscellaneous other procedures. The programs now contain 122 modules, each of which provides a number, sometimes a large number, of statistical procedures. The programs are accompanied by a Finder that indicates which modules are appropriate for different purposes. The manuals explain the uses, limitations and applicability of the procedures, and furnish formulae and references. Conclusions WINPEPI is a handy resource for a wide variety of statistical routines used by epidemiologists. Because of its ready availability, portability, ease of use, and versatility, WINPEPI has a considerable potential as a learning and teaching aid, both with respect to practical procedures in the planning and analysis of epidemiological studies, and with respect to important epidemiological concepts. It can also be used as an aid in the teaching of general basic statistics. PMID:21288353

Toward the detection of abnormal chest radiographs the way radiologists do it

NASA Astrophysics Data System (ADS)

Alzubaidi, Mohammad; Patel, Ameet; Panchanathan, Sethuraman; Black, John A., Jr.

2011-03-01

Computer Aided Detection (CADe) and Computer Aided Diagnosis (CADx) are relatively recent areas of research that attempt to employ feature extraction, pattern recognition, and machine learning algorithms to aid radiologists in detecting and diagnosing abnormalities in medical images. However, these computational methods are based on the assumption that there are distinct classes of abnormalities, and that each class has some distinguishing features that set it apart from other classes. However, abnormalities in chest radiographs tend to be very heterogeneous. The literature suggests that thoracic (chest) radiologists develop their ability to detect abnormalities by developing a sense of what is normal, so that anything that is abnormal attracts their attention. This paper discusses an approach to CADe that is based on a technique called anomaly detection (which aims to detect outliers in data sets) for the purpose of detecting atypical regions in chest radiographs. However, in order to apply anomaly detection to chest radiographs, it is necessary to develop a basis for extracting features from corresponding anatomical locations in different chest radiographs. This paper proposes a method for doing this, and describes how it can be used to support CADe.

The electronic stethoscope.

PubMed

Leng, Shuang; Tan, Ru San; Chai, Kevin Tshun Chuan; Wang, Chao; Ghista, Dhanjoo; Zhong, Liang

2015-07-10

Most heart diseases are associated with and reflected by the sounds that the heart produces. Heart auscultation, defined as listening to the heart sound, has been a very important method for the early diagnosis of cardiac dysfunction. Traditional auscultation requires substantial clinical experience and good listening skills. The emergence of the electronic stethoscope has paved the way for a new field of computer-aided auscultation. This article provides an in-depth study of (1) the electronic stethoscope technology, and (2) the methodology for diagnosis of cardiac disorders based on computer-aided auscultation. The paper is based on a comprehensive review of (1) literature articles, (2) market (state-of-the-art) products, and (3) smartphone stethoscope apps. It covers in depth every key component of the computer-aided system with electronic stethoscope, from sensor design, front-end circuitry, denoising algorithm, heart sound segmentation, to the final machine learning techniques. Our intent is to provide an informative and illustrative presentation of the electronic stethoscope, which is valuable and beneficial to academics, researchers and engineers in the technical field, as well as to medical professionals to facilitate its use clinically. The paper provides the technological and medical basis for the development and commercialization of a real-time integrated heart sound detection, acquisition and quantification system.

Computer-Aided Diagnosis of Anterior Segment Eye Abnormalities using Visible Wavelength Image Analysis Based Machine Learning.

PubMed

S V, Mahesh Kumar; R, Gunasundari

2018-06-02

Eye disease is a major health problem among the elderly people. Cataract and corneal arcus are the major abnormalities that exist in the anterior segment eye region of aged people. Hence, computer-aided diagnosis of anterior segment eye abnormalities will be helpful for mass screening and grading in ophthalmology. In this paper, we propose a multiclass computer-aided diagnosis (CAD) system using visible wavelength (VW) eye images to diagnose anterior segment eye abnormalities. In the proposed method, the input VW eye images are pre-processed for specular reflection removal and the iris circle region is segmented using a circular Hough Transform (CHT)-based approach. The first-order statistical features and wavelet-based features are extracted from the segmented iris circle and used for classification. The Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO) algorithm was used for the classification. In experiments, we used 228 VW eye images that belong to three different classes of anterior segment eye abnormalities. The proposed method achieved a predictive accuracy of 96.96% with 97% sensitivity and 99% specificity. The experimental results show that the proposed method has significant potential for use in clinical applications.

Pulmonary lobar volumetry using novel volumetric computer-aided diagnosis and computed tomography

PubMed Central

Iwano, Shingo; Kitano, Mariko; Matsuo, Keiji; Kawakami, Kenichi; Koike, Wataru; Kishimoto, Mariko; Inoue, Tsutomu; Li, Yuanzhong; Naganawa, Shinji

2013-01-01

OBJECTIVES To compare the accuracy of pulmonary lobar volumetry using the conventional number of segments method and novel volumetric computer-aided diagnosis using 3D computed tomography images. METHODS We acquired 50 consecutive preoperative 3D computed tomography examinations for lung tumours reconstructed at 1-mm slice thicknesses. We calculated the lobar volume and the emphysematous lobar volume < −950 HU of each lobe using (i) the slice-by-slice method (reference standard), (ii) number of segments method, and (iii) semi-automatic and (iv) automatic computer-aided diagnosis. We determined Pearson correlation coefficients between the reference standard and the three other methods for lobar volumes and emphysematous lobar volumes. We also compared the relative errors among the three measurement methods. RESULTS Both semi-automatic and automatic computer-aided diagnosis results were more strongly correlated with the reference standard than the number of segments method. The correlation coefficients for automatic computer-aided diagnosis were slightly lower than those for semi-automatic computer-aided diagnosis because there was one outlier among 50 cases (2%) in the right upper lobe and two outliers among 50 cases (4%) in the other lobes. The number of segments method relative error was significantly greater than those for semi-automatic and automatic computer-aided diagnosis (P < 0.001). The computational time for automatic computer-aided diagnosis was 1/2 to 2/3 than that of semi-automatic computer-aided diagnosis. CONCLUSIONS A novel lobar volumetry computer-aided diagnosis system could more precisely measure lobar volumes than the conventional number of segments method. Because semi-automatic computer-aided diagnosis and automatic computer-aided diagnosis were complementary, in clinical use, it would be more practical to first measure volumes by automatic computer-aided diagnosis, and then use semi-automatic measurements if automatic computer-aided diagnosis failed. PMID:23526418

Deep Learning in Gastrointestinal Endoscopy.

PubMed

Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

2016-01-01

Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

(I Learned It) through the Grapevine: Hypermedia at Work in the Classroom.

ERIC Educational Resources Information Center

Campbell, Robert

1989-01-01

Describes a project that was intended to aid students researching "The Grapes of Wrath" and that resulted in a program that uses the Apple Macintosh computer with HyperCard and a videodisk to put users in touch with the sights, sounds, issues, and events of the United States in the 1930s. (three references) (CLB)

A Focus on Students' Use of Twitter--Their Interactions with Each Other, Content and Interface

ERIC Educational Resources Information Center

Prestridge, Sarah

2014-01-01

In their advertising campaigns, universities depict students using computers, laptops, mobile phones, iPads and tablets as learning devices. Regardless of the marketing used, there is value in enlisting the advantages of any medium that can aid deep thinking and increase student engagement. This study offers new knowledge about conceptualising…

Design Features of a Friendly Software Environment for Novice Programmers. Technical Report No. 3.

ERIC Educational Resources Information Center

Eisenstadt, Marc

This paper describes the results of a 6-year period of design, implementation, testing, and iterative redesign of a programming language, user aids, and curriculum materials for use by psychology students learning how to write simple computer programs. The SOLO language, which was the resulting product, is primarily a simple, database…

Teaching CAD at the University: Specifically Written or Commercial Software?

ERIC Educational Resources Information Center

Garcia, Ramon Rubio; Quiros, Javier Suarez; Santos, Ramon Gallego; Penin, Pedro I. Alvarez

2007-01-01

At most universities throughout the world Computer Aided Design is taught using commercial programs more suitable for business and industry than for teaching. This led us to write our own design program (GIcad) starting from the best-known standards on the market, but always avoiding unnecessary commands in the first steps of the learning process.…

A Simple Computer-Aided Three-Dimensional Molecular Modeling for the Octant Rule

ERIC Educational Resources Information Center

Kang, Yinan; Kang, Fu-An

2011-01-01

The Moffitt-Woodward-Moscowitz-Klyne-Djerassi octant rule is one of the most successful empirical rules in organic chemistry. However, the lack of a simple effective modeling method for the octant rule in the past 50 years has posed constant difficulties for researchers, teachers, and students, particularly the young generations, to learn and…

Failed State: A New (Old) Definition

DTIC Science & Technology

2010-04-21

school curriculum into CD-ROMs so students can learn interactively with the aid of computers. Programa Escuelas de Calidad, or quality schools program...12 Ibid., 133. 13 David Hume, Treatise on Human Nature (London: Longmans, 1874), 415. 14 Charles de Secondat Montesquieu, The...category political legitimacy and the sub-categories of regime inclusions , factionalism, political salience of elite ethnicity, polity fragmentation

Exploiting the Potential of CD-ROM Databases: Staff Induction at the University of East Anglia.

ERIC Educational Resources Information Center

Guillot, Marie-Noelle; Kenning, Marie-Madeleine

1995-01-01

Overviews a project exploring the possibility of using CD-ROM applications and the design of exploratory didactic materials to introduce academic staff to the field of computer-assisted instruction. The project heightened the staff's awareness of electronic resources and their potential as research, teaching, and learning aids, with particular…

EssayCritic: Writing to Learn with a Knowledge-Based Design Critiquing System

ERIC Educational Resources Information Center

Mørch, Anders I.; Engeness, Irina; Cheng, Victor C.; Cheung, William K.; Wong, Kelvin C.

2017-01-01

This article presents a study of EssayCritic, a computer-based writing aid for English as a foreign language (EFL) that provides feedback on the content of English essays. We compared two feedback conditions: automated feedback from EssayCritic (target class) and feedback from collaborating peers (comparison class). We used a mixed methods…

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

PubMed

Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

2016-07-01

Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

Effectiveness of a computer-based tutorial for teaching how to make a blood smear.

PubMed

Preast, Vanessa; Danielson, Jared; Bender, Holly; Bousson, Maury

2007-09-01

Computer-aided instruction (CAI) was developed to teach veterinary students how to make blood smears. This instruction was intended to replace the traditional instructional method in order to promote efficient use of faculty resources while maintaining learning outcomes and student satisfaction. The purpose of this study was to evaluate the effect of a computer-aided blood smear tutorial on 1) instructor's teaching time, 2) students' ability to make blood smears, and 3) students' ability to recognize smear quality. Three laboratory sessions for senior veterinary students were taught using traditional methods (control group) and 4 sessions were taught using the CAI tutorial (experimental group). Students in the control group received a short demonstration and lecture by the instructor at the beginning of the laboratory and then practiced making blood smears. Students in the experimental group received their instruction through the self-paced, multimedia tutorial on a laptop computer and then practiced making blood smears. Data was collected from observation, interview, survey questionnaires, and smear evaluation by students and experts using a scoring rubric. Students using the CAI made better smears and were better able to recognize smear quality. The average time the instructor spent in the room was not significantly different between groups, but the quality of the instructor time was improved with the experimental instruction. The tutorial implementation effectively provided students and instructors with a teaching and learning experience superior to the traditional method of instruction. Using CAI is a viable method of teaching students to make blood smears.

Two adults with multiple disabilities use a computer-aided telephone system to make phone calls independently.

PubMed

Lancioni, Giulio E; O'Reilly, Mark F; Singh, Nirbhay N; Sigafoos, Jeff; Oliva, Doretta; Alberti, Gloria; Lang, Russell

2011-01-01

This study extended the assessment of a newly developed computer-aided telephone system with two participants (adults) who presented with blindness or severe visual impairment and motor or motor and intellectual disabilities. For each participant, the study was carried out according to an ABAB design, in which the A represented baseline phases and the B represented intervention phases, during which the special telephone system was available. The system involved among others a net-book computer provided with specific software, a global system for mobile communication modem, and a microswitch. Both participants learned to use the system very rapidly and managed to make phone calls independently to a variety of partners such as family members, friends and staff personnel. The results were discussed in terms of the technology under investigation (its advantages, drawbacks, and need of improvement) and the social-communication impact it can make for persons with multiple disabilities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Perceptions of the roles of social networking in simulation augmented medical education and training.

PubMed

Martin, Rob; Rojas, David; Cheung, Jeffrey J H; Weber, Bryce; Kapralos, Bill; Dubrowski, Adam

2013-01-01

Simulation-augmented education and training (SAET) is an expensive educational tool that may be facilitated through social networking technologies or Computer Supported Collaborative Learning (CSCL). This study examined the perceptions of medical undergraduates participating in SAET for knot tying skills to identify perceptions and barriers to implementation of social networking technologies within a broader medical education curriculum. The majority of participants (89%) found CSCL aided their learning of the technical skill and identified privacy and accessibility as major barriers to the tools implementation.

Emerging CAE technologies and their role in Future Ambient Intelligence Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2011-03-01

Dramatic improvements are on the horizon in Computer Aided Engineering (CAE) and various simulation technologies. The improvements are due, in part, to the developments in a number of leading-edge technologies and their synergistic combinations/convergence. The technologies include ubiquitous, cloud, and petascale computing; ultra high-bandwidth networks, pervasive wireless communication; knowledge based engineering; networked immersive virtual environments and virtual worlds; novel human-computer interfaces; and powerful game engines and facilities. This paper describes the frontiers and emerging simulation technologies, and their role in the future virtual product creation and learning/training environments. The environments will be ambient intelligence environments, incorporating a synergistic combination of novel agent-supported visual simulations (with cognitive learning and understanding abilities); immersive 3D virtual world facilities; development chain management systems and facilities (incorporating a synergistic combination of intelligent engineering and management tools); nontraditional methods; intelligent, multimodal and human-like interfaces; and mobile wireless devices. The Virtual product creation environment will significantly enhance the productivity and will stimulate creativity and innovation in future global virtual collaborative enterprises. The facilities in the learning/training environment will provide timely, engaging, personalized/collaborative and tailored visual learning.

Developments in Computer Aided Software Maintenance

DTIC Science & Technology

1974-09-01

thinks in terms of one sub- division until one happens to move to another one. Another study ( Tulving & Pearlstone , 1966) showed that failure to...them directions. (Wortman & Greenberg, 1971; Tulving & Pearlstone , 1966) In either case, hierarchical category formation is an economi- cal...1969.) Tulving , E., and Pearlstone , Z. "Availability Versus Accessibility of Information in Memory for Words." Journal of Verbal Learning and

Blending Video Games with Learning: Issues and Challenges with Classroom Implementations in the Turkish Context

ERIC Educational Resources Information Center

Tuzun, Hakan

2007-01-01

The research design for this study focuses on examining the core issues and challenges when video games are used in the classroom. For this purpose three naturalistic contexts in Turkey were examined in which educational video games were used as the basis for teaching units on world continents and countries, first aid, and basic computer hardware…

Final Report of the Computer Assisted Learning Test Project. Report No. 19.

ERIC Educational Resources Information Center

Van der Drift, K. D.; And Others

A pilot project was conducted to gain information to advise the Board of Directors at the University of Leyden as to the feasibility of using a computerized system to aid in instructional programs in the social sciences, law, medicine, arts, mathematics, and natural sciences at a low cost. The pilot project is divided into four parts which are…

The Complementary Use of Audience Response Systems and Online Tests to Implement Repeat Testing: A Case Study

ERIC Educational Resources Information Center

Stratling, Rebecca

2017-01-01

Although learning theories suggest that repeat testing can be highly beneficial for students' retention and understanding of material, there is, so far, little guidance on how to implement repeat testing in higher education. This paper introduces one method for implementing a three-stage model of repeat testing via computer-aided formative…

Simple and Inexpensive 3D Printed Filter Fluorometer Designs: User-Friendly Instrument Models for Laboratory Learning and Outreach Activities

ERIC Educational Resources Information Center

Porter, Lon A., Jr.; Chapman, Cole A.; Alaniz, Jacob A.

2017-01-01

In this work, a versatile and user-friendly selection of stereolithography (STL) files and computer-aided design (CAD) models are shared to assist educators and students in the production of simple and inexpensive 3D printed filter fluorometer instruments. These devices are effective resources for supporting active learners in the exploration of…

The Effects of a Chemistry Course with Integrated Information Communication Technologies on University Students' Learning and Attitudes

ERIC Educational Resources Information Center

Su, King-Dow

2008-01-01

The purpose of this study was to evaluate the instructional effects of using animations, static figures, PowerPoint bulletins, and e-plus software as chemistry texts with the aid of computer-based technology. This study analyzed the characteristics of students involved in three multimedia courses and their achievement and attitude toward chemistry…

A Switching-Mode Power Supply Design Tool to Improve Learning in a Power Electronics Course

ERIC Educational Resources Information Center

Miaja, P. F.; Lamar, D. G.; de Azpeitia, M.; Rodriguez, A.; Rodriguez, M.; Hernando, M. M.

2011-01-01

The static design of ac/dc and dc/dc switching-mode power supplies (SMPS) relies on a simple but repetitive process. Although specific spreadsheets, available in various computer-aided design (CAD) programs, are widely used, they are difficult to use in educational applications. In this paper, a graphic tool programmed in MATLAB is presented,…

The Effectiveness of a Virtual Field Trip (VFT) Module in Learning Biology

ERIC Educational Resources Information Center

Haris, Norbaizura; Osman, Kamisah

2015-01-01

Virtual Field Trip is a computer aided module of science developed to study the Colonisation and Succession in Mangrove Swamps, as an alternative to the real field trip in Form for Biology. This study is to identify the effectiveness of the Virtual Field Trip (VFT) module towards the level of achievement in the formative test for this topic. This…

A Review. A Real-Time Microcomputer-Assisted System for Translating Aural, Monophonic Tones into Music Notation as an Aid in Sight-Singing.

ERIC Educational Resources Information Center

Higgins, William R.

1987-01-01

Reviews a dissertation in which the problems of real-time pitch detection by computer were studied in an attempt to develop a learning tool for sightsinging students. Specialized hardware and software were developed to discriminate aural pitches and to display them in real-time using standard notation. (BSR)

Exploring Perceptions and Attitudes towards Teaching and Learning Manual Technical Drawing in a Digital Age

ERIC Educational Resources Information Center

McLaren, Susan Valerie

2008-01-01

This paper examines the place of manual technical drawing in the 21st century by discussing the perceived value and relevance of teaching school students how to draw using traditional instruments, in a world of computer aided drafting (CAD). Views were obtained through an e-survey, questionnaires and structured interviews. The sample groups…

Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.

PubMed

Yassin, Nisreen I R; Omran, Shaimaa; El Houby, Enas M F; Allam, Hemat

2018-03-01

The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer. The SR was conducted using a comprehensive selection of scientific databases as reference sources, allowing access to diverse publications in the field. The scientific databases used are Springer Link (SL), Science Direct (SD), IEEE Xplore Digital Library, and PubMed. Inclusion and exclusion criteria were defined and applied to each retrieved work to select those of interest. From 320 studies retrieved, 154 studies were included. However, the scope of this research is limited to scientific and academic works and excludes commercial interests. This survey provides a general analysis of the current status of CAD systems according to the used image modalities and the machine learning based classifiers. Potential research studies have been discussed to create a more objective and efficient CAD systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Teaching neuroanatomy using computer-aided learning: What makes for successful outcomes?

PubMed

Svirko, Elena; Mellanby, Jane

2017-11-01

Computer-aided learning (CAL) is an integral part of many medical courses. The neuroscience course at Oxford University for medical students includes CAL course of neuroanatomy. CAL is particularly suited to this since neuroanatomy requires much detailed three-dimensional visualization, which can be presented on screen. The CAL course was evaluated using the concept of approach to learning. The aims of university teaching are congruent with the deep approach-seeking meaning and relating new information to previous knowledge-rather than to the surface approach of concentrating on rote learning of detail. Seven cohorts of medical students (N = 869) filled in approach to learning scale and a questionnaire investigating their engagement with the CAL course. The students' scores on CAL-course-based neuroanatomy assessment and later university examinations were obtained. Although the students reported less use of the deep approach for the neuroanatomy CAL course than for the rest of their neuroanatomy course (mean = 24.99 vs. 31.49, P < 0.001), deep approach for CAL was positively correlated with neuroanatomy assessment performance (r = 0.12, P < 0.001). Time spent on the CAL course, enjoyment of it, the amount of CAL videos watched and quizzes completed were each significantly positively related to deep approach. The relationship between deep approach and enjoyment was particularly notable (25.5% shared variance). Reported relationships between deep approach and academic performance support the desirability of deep approach in university students. It is proposed that enjoyment of the course and the deep approach could be increased by incorporation of more clinical material which is what the students liked most. Anat Sci Educ 10: 560-569. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

PubMed

Ahmad, Asif; Asif, Amina; Rajpoot, Nasir; Arif, Muhammad; Minhas, Fayyaz Ul Amir Afsar

2017-11-21

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist .

Multiple kernel learning using single stage function approximation for binary classification problems

NASA Astrophysics Data System (ADS)

Shiju, S.; Sumitra, S.

2017-12-01

In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Mobile computing initiatives within pharmacy education.

PubMed

Cain, Jeff; Bird, Eleanora R; Jones, Mikael

2008-08-15

To identify mobile computing initiatives within pharmacy education, including how devices are obtained, supported, and utilized within the curriculum. An 18-item questionnaire was developed and delivered to academic affairs deans (or closest equivalent) of 98 colleges and schools of pharmacy. Fifty-four colleges and schools completed the questionnaire for a 55% completion rate. Thirteen of those schools have implemented mobile computing requirements for students. Twenty schools reported they were likely to formally consider implementing a mobile computing initiative within 5 years. Numerous models of mobile computing initiatives exist in terms of device obtainment, technical support, infrastructure, and utilization within the curriculum. Responders identified flexibility in teaching and learning as the most positive aspect of the initiatives and computer-aided distraction as the most negative, Numerous factors should be taken into consideration when deciding if and how a mobile computing requirement should be implemented.

Intelligent computer-aided training authoring environment

NASA Technical Reports Server (NTRS)

Way, Robert D.

1994-01-01

Although there has been much research into intelligent tutoring systems (ITS), there are few authoring systems available that support ITS metaphors. Instructional developers are generally obliged to use tools designed for creating on-line books. We are currently developing an authoring environment derived from NASA's research on intelligent computer-aided training (ICAT). The ICAT metaphor, currently in use at NASA has proven effective in disciplines from satellite deployment to high school physics. This technique provides a personal trainer (PT) who instructs the student using a simulated work environment (SWE). The PT acts as a tutor, providing individualized instruction and assistance to each student. Teaching in an SWE allows the student to learn tasks by doing them, rather than by reading about them. This authoring environment will expedite ICAT development by providing a tool set that guides the trainer modeling process. Additionally, this environment provides a vehicle for distributing NASA's ICAT technology to the private sector.

The use of porcine corrosion casts for teaching human anatomy.

PubMed

Eberlova, Lada; Liska, Vaclav; Mirka, Hynek; Tonar, Zbynek; Haviar, Stanislav; Svoboda, Milos; Benes, Jan; Palek, Richard; Emingr, Michal; Rosendorf, Jachym; Mik, Patrik; Leupen, Sarah; Lametschwandtner, Alois

2017-09-01

In teaching and learning human anatomy, anatomical autopsy and prosected specimens have always been indispensable. However, alternative methods must often be used to demonstrate particularly delicate structures. Corrosion casting of porcine organs with Biodur E20 ® Plus is valuable for teaching and learning both gross anatomy and, uniquely, the micromorphology of cardiovascular, respiratory, digestive, and urogenital systems. Assessments of casts with a stereomicroscope and/or scanning electron microscope as well as highlighting cast structures using color coding help students to better understand how the structures that they have observed as two-dimensional images actually exist in three dimensions, and students found using the casts to be highly effective in their learning. Reconstructions of cast hollow structures from (micro-)computed tomography scans and videos facilitate detailed analyses of branching patterns and spatial arrangements in cast structures, aid in the understanding of clinically relevant structures and provide innovative visual aids. The casting protocol and teaching manual we offer can be adjusted to different technical capabilities and might also be found useful for veterinary or other biological science classes. Copyright © 2017 Elsevier GmbH. All rights reserved.

The Impact of a Language Learning Task on Instructional Outcomes in Two Student Populations: High-Ability and Average-Ability Students.

ERIC Educational Resources Information Center

Nikolova, Ofelia; Taylor, Gregory

2003-01-01

High-ability (n=97) and average-ability students (n=84) were asked to read a Spanish passage on a computer and use glosses provided for certain words to aid in comprehension or create glosses using a Spanish-English dictionary and annotation software (experimental task). High-ability students performed significantly better after the experimental…

Netbook - A Toolset in Support of a Collaborative Learning.

DTIC Science & Technology

1997-01-31

Netbook is a software development research project being conducted for the DARPA Computer Aided Training Initiative (CEATI). As a part of the Smart...Navigators to Access and Integrated Resources (SNAIR) division of CEATI, Netbook concerns itself with the management of Internet resources. More...specifically, Netbook is a toolset that enables students, teachers, and administrators to navigate the World Wide Web, collect resources found there, index

An investigative study into the effectiveness of using computer-aided instruction (CAI) as a laboratory component of college-level biology: A case study

NASA Astrophysics Data System (ADS)

Barrett, Joan Beverly

Community colleges serve the most diverse student populations in higher education. They consist of non-traditional, part-time, older, intermittent, and mobile students of different races, ethnic backgrounds, language preferences, physical and mental abilities, and learning style preferences. Students who are academically challenged may have diverse learning characteristics that are not compatible with the more traditional approaches to the delivery of instruction. With this need come new ways of solving the dilemma, such as Computer-aided Instruction (CAI). This case study investigated the use of CAI as a laboratory component of college-level biology in a small, rural community college setting. The intent was to begin to fill a void that seems to exist in the literature regarding the role of the faculty in the development and use of CAI. In particular, the investigator was seeking to understand the practice and its effectiveness, especially in helping the under prepared student. The case study approach was chosen to examine a specific phenomenon within a single institution. Ethnographic techniques, such as interviewing, documentary analysis, life's experiences, and participant observations were used to collect data about the phenomena being studied. Results showed that the faculty was primarily self-motivated and self-taught in their use of CAI as a teaching and learning tool. The importance of faculty leadership and collegiality was evident. Findings showed the faculty confident that expectations of helping students who have difficulties with mathematical concepts have been met and that CAI is becoming the most valuable of learning tools. In a traditional college classroom, or practice, time is the constant (semesters) and competence is the variable. In the CAI laboratory time became the variable and competence the constant. The use of CAI also eliminated hazardous chemicals that were routinely used in the more traditional lab. Outcomes showed that annual savings from operations were realized after the initial capital investment for computer hardware and software were made.

Computer-assisted versus conventional free fibula flap technique for craniofacial reconstruction: an outcomes comparison.

PubMed

Seruya, Mitchel; Fisher, Mark; Rodriguez, Eduardo D

2013-11-01

There has been rising interest in computer-aided design/computer-aided manufacturing for preoperative planning and execution of osseous free flap reconstruction. The purpose of this study was to compare outcomes between computer-assisted and conventional fibula free flap techniques for craniofacial reconstruction. A two-center, retrospective review was carried out on patients who underwent fibula free flap surgery for craniofacial reconstruction from 2003 to 2012. Patients were categorized by the type of reconstructive technique: conventional (between 2003 and 2009) or computer-aided design/computer-aided manufacturing (from 2010 to 2012). Demographics, surgical factors, and perioperative and long-term outcomes were compared. A total of 68 patients underwent microsurgical craniofacial reconstruction: 58 conventional and 10 computer-aided design and manufacturing fibula free flaps. By demographics, patients undergoing the computer-aided design/computer-aided manufacturing method were significantly older and had a higher rate of radiotherapy exposure compared with conventional patients. Intraoperatively, the median number of osteotomies was significantly higher (2.0 versus 1.0, p=0.002) and the median ischemia time was significantly shorter (120 minutes versus 170 minutes, p=0.004) for the computer-aided design/computer-aided manufacturing technique compared with conventional techniques; operative times were shorter for patients undergoing the computer-aided design/computer-aided manufacturing technique, although this did not reach statistical significance. Perioperative and long-term outcomes were equivalent for the two groups, notably, hospital length of stay, recipient-site infection, partial and total flap loss, and rate of soft-tissue and bony tissue revisions. Microsurgical craniofacial reconstruction using a computer-assisted fibula flap technique yielded significantly shorter ischemia times amidst a higher number of osteotomies compared with conventional techniques. Therapeutic, III.

Computer-Aided Facilities Management Systems (CAFM).

ERIC Educational Resources Information Center

Cyros, Kreon L.

Computer-aided facilities management (CAFM) refers to a collection of software used with increasing frequency by facilities managers. The six major CAFM components are discussed with respect to their usefulness and popularity in facilities management applications: (1) computer-aided design; (2) computer-aided engineering; (3) decision support…

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

PubMed

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of rhythm in acquisition of a computer-generated tracking task.

PubMed

Fulop, A C; Kirby, R H; Coates, G D

1992-08-01

This research assessed whether rhythm aids acquisition of motor skills by providing cues for the timing of those skills. Rhythms were presented to participants visually or visually with auditory cues. It was hypothesized that the auditory cues would facilitate recognition and learning of the rhythms. The three timing principles of rhythms were also explored. It was hypothesized that rhythms that satisfied all three timing principles would be more beneficial in learning a skill than rhythms that did not satisfy the principles. Three groups learned three different rhythms by practicing a tracking task. After training, participants attempted to reproduce the tracks from memory. Results suggest that rhythms do help in learning motor skills but different sets of timing principles explain perception of rhythm in different modalities.

On-line integration of computer controlled diagnostic devices and medical information systems in undergraduate medical physics education for physicians.

PubMed

Hanus, Josef; Nosek, Tomas; Zahora, Jiri; Bezrouk, Ales; Masin, Vladimir

2013-01-01

We designed and evaluated an innovative computer-aided-learning environment based on the on-line integration of computer controlled medical diagnostic devices and a medical information system for use in the preclinical medical physics education of medical students. Our learning system simulates the actual clinical environment in a hospital or primary care unit. It uses a commercial medical information system for on-line storage and processing of clinical type data acquired during physics laboratory classes. Every student adopts two roles, the role of 'patient' and the role of 'physician'. As a 'physician' the student operates the medical devices to clinically assess 'patient' colleagues and records all results in an electronic 'patient' record. We also introduced an innovative approach to the use of supportive education materials, based on the methods of adaptive e-learning. A survey of student feedback is included and statistically evaluated. The results from the student feedback confirm the positive response of the latter to this novel implementation of medical physics and informatics in preclinical education. This approach not only significantly improves learning of medical physics and informatics skills but has the added advantage that it facilitates students' transition from preclinical to clinical subjects. Copyright © 2011 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

On the Value of Computer-aided Instruction: Thoughts after Teaching Sales Writing in a Computer Classroom.

ERIC Educational Resources Information Center

Hagge, John

1986-01-01

Focuses on problems encountered with computer-aided writing instruction. Discusses conflicts caused by the computer classroom concept, some general paradoxes and ethical implications of computer-aided instruction. (EL)

Wind-US Flow Calculations for the M2129 S-Duct Using Structured and Unstructured Grids

NASA Technical Reports Server (NTRS)

Mohler, Stanley R., Jr.

2003-01-01

Computational Fluid Dynamics (CFD) flow solutions for the M2129 diffusing S-duct with and without vane effectors were computed by the Wind-US flow solver. Both structured and unstructured 3-D grids were used. Without vane effectors, the duct exhibited massive flow separation in both experiment and CFD. With vane effectors installed, the flow remained attached and aerodynamic losses were reduced. Total pressure recovery and distortion near the duct outlet were computed from the solutions and compared favorably to experimental values. These calculations are part of a validation effort for the Wind-US code. They also provide an example case to aid engineers in learning to use the Wind-US software.

LLNL Partners with IBM on Brain-Like Computing Chip

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

Van Essen, Brian

Lawrence Livermore National Laboratory (LLNL) will receive a first-of-a-kind brain-inspired supercomputing platform for deep learning developed by IBM Research. Based on a breakthrough neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing aid battery – a mere 2.5 watts of power. The brain-like, neural network design of the IBM Neuromorphic System is able to infer complex cognitive tasks such as pattern recognition and integrated sensory processing far more efficiently than conventional chips.

LLNL Partners with IBM on Brain-Like Computing Chip

ScienceCinema

Van Essen, Brian

2018-06-25

Lawrence Livermore National Laboratory (LLNL) will receive a first-of-a-kind brain-inspired supercomputing platform for deep learning developed by IBM Research. Based on a breakthrough neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing aid battery – a mere 2.5 watts of power. The brain-like, neural network design of the IBM Neuromorphic System is able to infer complex cognitive tasks such as pattern recognition and integrated sensory processing far more efficiently than conventional chips.

Learning-based image preprocessing for robust computer-aided detection

NASA Astrophysics Data System (ADS)

Raghupathi, Laks; Devarakota, Pandu R.; Wolf, Matthias

2013-03-01

Recent studies have shown that low dose computed tomography (LDCT) can be an effective screening tool to reduce lung cancer mortality. Computer-aided detection (CAD) would be a beneficial second reader for radiologists in such cases. Studies demonstrate that while iterative reconstructions (IR) improve LDCT diagnostic quality, it however degrades CAD performance significantly (increased false positives) when applied directly. For improving CAD performance, solutions such as retraining with newer data or applying a standard preprocessing technique may not be suffice due to high prevalence of CT scanners and non-uniform acquisition protocols. Here, we present a learning-based framework that can adaptively transform a wide variety of input data to boost an existing CAD performance. This not only enhances their robustness but also their applicability in clinical workflows. Our solution consists of applying a suitable pre-processing filter automatically on the given image based on its characteristics. This requires the preparation of ground truth (GT) of choosing an appropriate filter resulting in improved CAD performance. Accordingly, we propose an efficient consolidation process with a novel metric. Using key anatomical landmarks, we then derive consistent feature descriptors for the classification scheme that then uses a priority mechanism to automatically choose an optimal preprocessing filter. We demonstrate CAD prototype∗ performance improvement using hospital-scale datasets acquired from North America, Europe and Asia. Though we demonstrated our results for a lung nodule CAD, this scheme is straightforward to extend to other post-processing tools dedicated to other organs and modalities.

Using the theory of planned behaviour to understand the motivation to learn about HIV/AIDS prevention among adolescents in Tigray, Ethiopia.

PubMed

Gebreeyesus Hadera, H; Boer, H; Kuiper, W A J M

2007-08-01

Various studies indicate that school- or university-based HIV prevention curricula can reduce the prevalence of sexual risk behaviour among adolescent youth in Sub-Saharan Africa. However, effective HIV/AIDS prevention education may be problematic, if the needs of youth are not served adequately. To date, little attention has been given to the motivation of youth to learn about HIV/AIDS and about their preferences for HIV/AIDS curriculum design options. The aim of this study was to get insight into the determinants of the motivation of youth to learn about HIV/AIDS prevention and to assess their curriculum design preferences. Students from a university in Tigray, Ethiopia, filled out a structured questionnaire, which assessed demographics, variables that according to the Theory of Planned Behaviour are related to the motivation to learn, and their preferences for independent, carrier and integrated HIV/AIDS curriculum designs. On average, participants were highly motivated to learn about HIV/AIDS. Motivation to learn was primarily related to social norms and was not related to self-efficacy to discuss HIV/AIDS in class. The often discussed reluctance to discuss sexuality and condom use in curricula in Sub-Saharan Africa, seems to be more related to existing negative social norms, than to lack of self-efficacy. Participants revealed a high preference for the independent, carrier and integrated curriculum design options. However, students with a higher motivation to learn about HIV/AIDS were more attracted to the independent course design.

CD-ROM-aided Databases

NASA Astrophysics Data System (ADS)

Sano, Tomoyuki; Suzuki, Masataka; Nishida, Hideo

The Development of CAI system using CD-ROM and NAPLPS (North American Presentation Level Protocol Syntax) was taken place by Himeji Dokkyo University. The characteristics of CAI using CD-ROM as information processing series for the department of liberal arts student are described. The system is that the computer program, vast amount of voice data and graphics data are stored in a CD-ROM. It is very effective to improve learning ability of student.

Netbook - A Toolset in Support of a Collaborative and Cooperative Learning Environment.

DTIC Science & Technology

1996-04-26

Netbook is a software development/research project being conducted for the DARPA computer aided training initiative (CEATI). As a part of the SNAIR...division of CEATI, Netbook concerns itself with the management of Internet resources. More specifically, Netbook is a toolset that allows students...a meaningful way. In addition Netbook provides the capacity for communication with peers and teachers, enabling students to collaborate while engaged

The Improvement and Individualization of Computer-Assisted Instruction

DTIC Science & Technology

1975-09-15

Spanish experiments had studied at least one Romance language and con- sequently were able to learn some of +he Spanish wordo by using cognates...Involved the acquisition of foreign- language vocabulary Items. The first (using Geraan vocabulary) concerned Itself with optimizing the selection of...method. Experiments with Spanish and Russian items showed that the method could be a powerful aid in building and retaining a large vocabulary of

Use of Automated Testing to Facilitate Affordable Design of Military Systems

DTIC Science & Technology

2015-04-30

momentum across the Navy and DoD. This initiative is no new big bang /silver bullet; it simply focuses on lowering the cost and risk of government...University of Minnesota. He has developed several specification languages, software tools for computer-aided software design, and fundamental theory ...review of lessons learned and recommendations for further enhancements are discussed. Overview: The Testing Challenge Infinity Is a Big Place The

Machine Learning in Medical Imaging.

PubMed

Giger, Maryellen L

2018-03-01

Advances in both imaging and computers have synergistically led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks, such as risk assessment, detection, diagnosis, prognosis, and therapy response, as well as in multi-omics disease discovery. A brief overview of the field is given here, allowing the reader to recognize the terminology, the various subfields, and components of machine learning, as well as the clinical potential. Radiomics, an expansion of computer-aided diagnosis, has been defined as the conversion of images to minable data. The ultimate benefit of quantitative radiomics is to (1) yield predictive image-based phenotypes of disease for precision medicine or (2) yield quantitative image-based phenotypes for data mining with other -omics for discovery (ie, imaging genomics). For deep learning in radiology to succeed, note that well-annotated large data sets are needed since deep networks are complex, computer software and hardware are evolving constantly, and subtle differences in disease states are more difficult to perceive than differences in everyday objects. In the future, machine learning in radiology is expected to have a substantial clinical impact with imaging examinations being routinely obtained in clinical practice, providing an opportunity to improve decision support in medical image interpretation. The term of note is decision support, indicating that computers will augment human decision making, making it more effective and efficient. The clinical impact of having computers in the routine clinical practice may allow radiologists to further integrate their knowledge with their clinical colleagues in other medical specialties and allow for precision medicine. Copyright © 2018. Published by Elsevier Inc.

Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Bao, Hang; Yang, Jinzhu; Zhao, Dazhe

2015-01-01

The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these challenges, we propose oversampling and semi-supervised learning methods based on the restricted Boltzmann machines (RBMs) to solve the classification of imbalanced data with a few labeled samples. To evaluate the proposed method, we conducted a comprehensive performance study and compared its results with the commonly used techniques. Experiments on benchmark dataset of DDSM demonstrate the effectiveness of the RBMs based oversampling and semi-supervised learning method in terms of geometric mean (G-mean) for false positive reduction in Breast CAD.

Do medical students watch video clips in eLearning and do these facilitate learning?

PubMed

Romanov, Kalle; Nevgi, Anne

2007-06-01

There is controversial evidence of the impact of individual learning style on students' performance in computer-aided learning. We assessed the association between the use of multimedia materials, such as video clips, and collaborative communication tools with learning outcome among medical students. One hundred and twenty-one third-year medical students attended a course in medical informatics (0.7 credits) consisting of lectures, small group sessions and eLearning material. The eLearning material contained six learning modules with integrated video clips and collaborative learning tools in WebCT. Learning outcome was measured with a course exam. Approximately two-thirds of students (68.6%) viewed two or more videos. Female students were significantly more active video-watchers. No significant associations were found between video-watching and self-test scores or the time used in eLearning. Video-watchers were more active in WebCT; they loaded more pages and more actively participated in discussion forums. Video-watching was associated with a better course grade. Students who watched video clips were more active in using collaborative eLearning tools and achieved higher course grades.

Mental health first aid training by e-learning: a randomized controlled trial.

PubMed

Jorm, Anthony F; Kitchener, Betty A; Fischer, Julie-Anne; Cvetkovski, Stefan

2010-12-01

Mental Health First Aid training is a course for the public that teaches how to give initial help to a person developing a mental health problem or in a mental health crisis. The present study evaluated the effects of Mental Health First Aid training delivered by e-learning on knowledge about mental disorders, stigmatizing attitudes and helping behaviour. A randomized controlled trial was carried out with 262 members of the Australian public. Participants were randomly assigned to complete an e-learning CD, read a Mental Health First Aid manual or be in a waiting list control group. The effects of the interventions were evaluated using online questionnaires pre- and post-training and at 6-months follow up. The questionnaires covered mental health knowledge, stigmatizing attitudes, confidence in providing help to others, actions taken to implement mental health first aid and participant mental health. Both e-learning and the printed manual increased aspects of knowledge, reduced stigma and increased confidence compared to waiting list. E-learning also improved first aid actions taken more than waiting list, and was superior to the printed manual in reducing stigma and disability due to mental ill health. Mental Health First Aid information received by either e-learning or printed manual had positive effects, but e-learning was better at reducing stigma.

Engineering Technology Programs Courses Guide for Computer Aided Design and Computer Aided Manufacturing.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Div. of Vocational Education.

This guide describes the requirements for courses in computer-aided design and computer-aided manufacturing (CAD/CAM) that are part of engineering technology programs conducted in vocational-technical schools in Georgia. The guide is organized in five sections. The first section provides a rationale for occupations in design and in production,…

Employment Opportunities for the Handicapped in Programmable Automation.

ERIC Educational Resources Information Center

Swift, Richard; Leneway, Robert

A Computer Integrated Manufacturing System may make it possible for severely disabled people to custom design, machine, and manufacture either wood or metal parts. Programmable automation merges computer aided design, computer aided manufacturing, computer aided engineering, and computer integrated manufacturing systems with automated production…

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

PubMed

Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

2018-04-30

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

Lessons Learned from Ares I Upper Stage Structures and Thermal Design

NASA Technical Reports Server (NTRS)

Ahmed, Rafiq

2012-01-01

The Ares 1 Upper Stage was part of the vehicle intended to succeed the Space Shuttle as the United States manned spaceflight vehicle. Although the Upper Stage project was cancelled, there were many lessons learned that are applicable to future vehicle design. Lessons learned that are briefly detailed in this Technical Memorandum are for specific technical areas such as tank design, common bulkhead design, thrust oscillation, control of flight and slosh loads, purge and hazardous gas system. In addition, lessons learned from a systems engineering and vehicle integration perspective are also included, such as computer aided design and engineering, scheduling, and data management. The need for detailed systems engineering in the early stages of a project is emphasized throughout this report. The intent is that future projects will be able to apply these lessons learned to keep costs down, schedules brief, and deliver products that perform to the expectations of their customers.

A Student Response System in an Electronic Classroom: Technology Aids for Large Classroom Instruction

NASA Astrophysics Data System (ADS)

Ober, D.; Errington, P.; Islam, S.; Robertson, T.; Watson, J.

1997-10-01

In the fall of 1996, thirteen (13) classrooms on the Ball State campus were equipped with technological aids to enhance learning in large classrooms (for typically 100 students or larger). Each classroom was equipped with the following built-in equipment: computer, zip drive, laser disc player, VCR, LAN and Internet connection, TV monitors, and Elmo overhead camera with large-screen projection system. This past fall semester a student response system was added to a 108-seat classroom in the Physics and Astronomy department for use with large General Education courses. Each student seat was equipped with a hardwired hand-held unit possessing input capabilities and LCD feedback for the student. The introduction of the student response system was added in order enhance more active learning by students in the large classroom environment. Attendance, quizzes, hour exams, and in-class surveys are early uses for the system; initial reactions by student and faculty users will be given.

Back to the Bedside: Developing a Bedside Aid for Concussion and Brain Injury Decisions in the Emergency Department

PubMed Central

Melnick, Edward R.; Lopez, Kevin; Hess, Erik P.; Abujarad, Fuad; Brandt, Cynthia A.; Shiffman, Richard N.; Post, Lori A.

2015-01-01

Context: Current information-rich electronic health record (EHR) interfaces require large, high-resolution screens running on desktop computers. This interface compromises the provider’s already limited time at the bedside by physically separating the patient from the doctor. The case study presented here describes a patient-centered clinical decision support (CDS) design process that aims to bring the physician back to the bedside by integrating a patient decision aid with CDS for shared use by the patient and provider on a touchscreen tablet computer for deciding whether or not to obtain a CT scan for minor head injury in the emergency department, a clinical scenario that could benefit from CDS but has failed previous implementation attempts. Case Description: This case study follows the user-centered design (UCD) approach to build a bedside aid that is useful and usable, and that promotes shared decision-making between patients and their providers using a tablet computer at the bedside. The patient-centered decision support design process focuses on the prototype build using agile software development, but also describes the following: (1) the requirement gathering phase including triangulated qualitative research (focus groups and cognitive task analysis) to understand current challenges, (2) features for patient education, the physician, and shared decision-making, (3) system architecture and technical requirements, and (4) future plans for formative usability testing and field testing. Lessons Learned: We share specific lessons learned and general recommendations from critical insights gained in the patient-centered decision support design process about early stakeholder engagement, EHR integration, external expert feedback, challenges to two users on a single device, project management, and accessibility. Conclusions: Successful implementation of this tool will require seamless integration into the provider’s workflow. This protocol can create an effective interface for shared decision-making and safe resource reduction at the bedside in the austere and dynamic clinical environment of the ED and is generalizable for these purposes in other clinical environments as well. PMID:26290885

CAD/CAM (Computer Aided Design/Computer Aided Manufacture). A Brief Guide to Materials in the Library of Congress.

ERIC Educational Resources Information Center

Havas, George D.

This brief guide to materials in the Library of Congress (LC) on computer aided design and/or computer aided manufacturing lists reference materials and other information sources under 13 headings: (1) brief introductions; (2) LC subject headings used for such materials; (3) textbooks; (4) additional titles; (5) glossaries and handbooks; (6)…

System Re-engineering Project Executive Summary

DTIC Science & Technology

1991-11-01

Management Information System (STAMIS) application. This project involved reverse engineering, evaluation of structured design and object-oriented design, and re- implementation of the system in Ada. This executive summary presents the approach to re-engineering the system, the lessons learned while going through the process, and issues to be considered in future tasks of this nature.... Computer-Aided Software Engineering (CASE), Distributed Software, Ada, COBOL, Systems Analysis, Systems Design, Life Cycle Development, Functional Decomposition, Object-Oriented

Dictionary learning-based CT detection of pulmonary nodules

NASA Astrophysics Data System (ADS)

Wu, Panpan; Xia, Kewen; Zhang, Yanbo; Qian, Xiaohua; Wang, Ge; Yu, Hengyong

2016-10-01

Segmentation of lung features is one of the most important steps for computer-aided detection (CAD) of pulmonary nodules with computed tomography (CT). However, irregular shapes, complicated anatomical background and poor pulmonary nodule contrast make CAD a very challenging problem. Here, we propose a novel scheme for feature extraction and classification of pulmonary nodules through dictionary learning from training CT images, which does not require accurately segmented pulmonary nodules. Specifically, two classification-oriented dictionaries and one background dictionary are learnt to solve a two-category problem. In terms of the classification-oriented dictionaries, we calculate sparse coefficient matrices to extract intrinsic features for pulmonary nodule classification. The support vector machine (SVM) classifier is then designed to optimize the performance. Our proposed methodology is evaluated with the lung image database consortium and image database resource initiative (LIDC-IDRI) database, and the results demonstrate that the proposed strategy is promising.

Dynamics of list-server discussion on genetically modified foods.

PubMed

Triunfol, Marcia L; Hines, Pamela J

2004-04-01

Computer-mediated discussion lists, or list-servers, are popular tools in settings ranging from professional to personal to educational. A discussion list on genetically modified food (GMF) was created in September 2000 as part of the Forum on Genetically Modified Food developed by Science Controversies: Online Partnerships in Education (SCOPE), an educational project that uses computer resources to aid research and learning around unresolved scientific questions. The discussion list "GMF-Science" was actively supported from January 2001 to May 2002. The GMF-Science list welcomed anyone interested in discussing the controversies surrounding GMF. Here, we analyze the dynamics of the discussions and how the GMF-Science list may contribute to learning. Activity on the GMF-Science discussion list reflected some but not all the controversies that were appearing in more traditional publication formats, broached other topics not well represented in the published literature, and tended to leave undiscussed the more technical research developments.

Silicon Wafer Advanced Packaging (SWAP). Multichip Module (MCM) Foundry Study. Version 2

DTIC Science & Technology

1991-04-08

Next Layer Dielectric Spacing - Additional Metal Thickness Impact on Dielectric Uniformity/Adhiesion. The first step in .!Ie EPerimental design would be... design CAM - computer aided manufacturing CAE - computer aided engineering CALCE - computer aided life cycle engineering center CARMA - computer aided...expansion 5 j- CVD - chemical vapor deposition J . ..- j DA - design automation J , DEC - Digital Equipment Corporation --- DFT - design for testability

The application of computer-aided technologies in automotive styling design

NASA Astrophysics Data System (ADS)

Zheng, Ze-feng; Zhang, Ji; Zheng, Ying

2012-04-01

In automotive industry, outline design is its life and creative design is its soul indeed. Computer-aided technology has been widely used in the automotive industry and more and more attention has been paid. This paper chiefly introduce the application of computer-aided technologies including CAD, CAM and CAE, analyses the process of automotive structural design and describe the development tendency of computer-aided design.

PLM in the context of the maritime virtual education

NASA Astrophysics Data System (ADS)

Raicu, Alexandra; Oanta, Emil M.

2016-12-01

This paper presents new approaches regarding the use of Product Lifecycle Management concept to achieve knowledge integration of the academic disciplines in the maritime education context. The philosophy of the educational system is now changing faster worldwide and it is in a continuous developing process. There is a demand to develop modern educational facilities for CAD/CAE/CAM training of the future maritime engineers, which offers collaborative environments between the academic disciplines and the teachers. It is well known that the students must understand the importance of the connectivity between the academic disciplines and the computer aided methods to interface them. Thus, besides the basic knowledge and competences acquired from the CAD courses, students learn how to increase the design productivity, to create a parametric design, the original instruments of automatic design, 3D printing methods, how to interface the CAD/CAE/CAM applications. As an example, the Strength of Materials discipline briefly presents alternate computer aided methods to compute the geometrical characteristics of the cross sections using the CAD geometry, creation the free body diagrams and presentation the deflected shapes of various educational models, including the rotational effect when the forces are not applied in the shear center, using the results of the FEM applications. During the computer aided engineering academic disciplines, after the students design and analyze a virtual 3D model they can convert it into a physical object using 3D printing method. Constanta Maritime University offers a full understanding of the concept of Product Lifecycle Management, collaborative creation, management and dissemination.

Toward Usable Interactive Analytics: Coupling Cognition and Computation

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

Endert, Alexander; North, Chris; Chang, Remco

Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analyticsmore » that will ultimately increase the effectiveness for both humans and computers to produce insights.« less

Vehicle Sketch Pad: a Parametric Geometry Modeler for Conceptual Aircraft Design

NASA Technical Reports Server (NTRS)

Hahn, Andrew S.

2010-01-01

The conceptual aircraft designer is faced with a dilemma, how to strike the best balance between productivity and fidelity? Historically, handbook methods have required only the coarsest of geometric parameterizations in order to perform analysis. Increasingly, there has been a drive to upgrade analysis methods, but these require considerably more precise and detailed geometry. Attempts have been made to use computer-aided design packages to fill this void, but their cost and steep learning curve have made them unwieldy at best. Vehicle Sketch Pad (VSP) has been developed over several years to better fill this void. While no substitute for the full feature set of computer-aided design packages, VSP allows even novices to quickly become proficient in defining three-dimensional, watertight aircraft geometries that are adequate for producing multi-disciplinary meta-models for higher order analysis methods, wind tunnel and display models, as well as a starting point for animation models. This paper will give an overview of the development and future course of VSP.

Model–Free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning

PubMed Central

Twellmann, Thorsten; Meyer-Baese, Anke; Lange, Oliver; Foo, Simon; Nattkemper, Tim W.

2008-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important tool in breast cancer diagnosis, but evaluation of multitemporal 3D image data holds new challenges for human observers. To aid the image analysis process, we apply supervised and unsupervised pattern recognition techniques for computing enhanced visualizations of suspicious lesions in breast MRI data. These techniques represent an important component of future sophisticated computer-aided diagnosis (CAD) systems and support the visual exploration of spatial and temporal features of DCE-MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogeneity of cancerous tissue, these techniques reveal signals with malignant, benign and normal kinetics. They also provide a regional subclassification of pathological breast tissue, which is the basis for pseudo-color presentations of the image data. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging. PMID:19255616

An integrated classifier for computer-aided diagnosis of colorectal polyps based on random forest and location index strategies

NASA Astrophysics Data System (ADS)

Hu, Yifan; Han, Hao; Zhu, Wei; Li, Lihong; Pickhardt, Perry J.; Liang, Zhengrong

2016-03-01

Feature classification plays an important role in differentiation or computer-aided diagnosis (CADx) of suspicious lesions. As a widely used ensemble learning algorithm for classification, random forest (RF) has a distinguished performance for CADx. Our recent study has shown that the location index (LI), which is derived from the well-known kNN (k nearest neighbor) and wkNN (weighted k nearest neighbor) classifier [1], has also a distinguished role in the classification for CADx. Therefore, in this paper, based on the property that the LI will achieve a very high accuracy, we design an algorithm to integrate the LI into RF for improved or higher value of AUC (area under the curve of receiver operating characteristics -- ROC). Experiments were performed by the use of a database of 153 lesions (polyps), including 116 neoplastic lesions and 37 hyperplastic lesions, with comparison to the existing classifiers of RF and wkNN, respectively. A noticeable gain by the proposed integrated classifier was quantified by the AUC measure.

Effects of External Learning Aids on Learning with Ill-Structured Hypertext.

ERIC Educational Resources Information Center

Astleitner, Hermann

1997-01-01

Describes three experiments with high school and college students concerning learning with ill-structured hypertext; in each study, one different kind of external learning aid (memo pads, learning time, and teaching objectives) was manipulated and examined for its effect on intentional and incidental knowledge acquisition. Findings are discussed…

Computer-assisted education and interdisciplinary breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Whatmough, Pamela; Gale, Alastair G.; Wilson, A. R. M.

1996-04-01

The diagnosis of breast disease for screening or symptomatic women is largely arrived at by a multi-disciplinary team. We report work on the development and assessment of an inter- disciplinary computer based learning system to support the diagnosis of this disease. The diagnostic process is first modelled from different viewpoints and then appropriate knowledge structures pertinent to the domains of radiologist, pathologist and surgeon are depicted. Initially the underlying inter-relationships of the mammographic diagnostic approach were detailed which is largely considered here. Ultimately a system is envisaged which will link these specialties and act as a diagnostic aid as well as a multi-media educational system.

Enhancing an appointment diary on a pocket computer for use by people after brain injury.

PubMed

Wright, P; Rogers, N; Hall, C; Wilson, B; Evans, J; Emslie, H

2001-12-01

People with memory loss resulting from brain injury benefit from purpose-designed memory aids such as appointment diaries on pocket computers. The present study explores the effects of extending the range of memory aids and including games. For 2 months, 12 people who had sustained brain injury were loaned a pocket computer containing three purpose-designed memory aids: diary, notebook and to-do list. A month later they were given another computer with the same memory aids but a different method of text entry (physical keyboard or touch-screen keyboard). Machine order was counterbalanced across participants. Assessment was by interviews during the loan periods, rating scales, performance tests and computer log files. All participants could use the memory aids and ten people (83%) found them very useful. Correlations among the three memory aids were not significant, suggesting individual variation in how they were used. Games did not increase use of the memory aids, nor did loan of the preferred pocket computer (with physical keyboard). Significantly more diary entries were made by people who had previously used other memory aids, suggesting that a better understanding of how to use a range of memory aids could benefit some people with brain injury.

Significances of Multimedia Technologies Training

NASA Astrophysics Data System (ADS)

Zhang, Fulei

The use of multimedia technologies in education has enabled teachers to simulate final outcomes and assist s-tudents in applying knowledge learned from textbooks, thereby compensating for the deficiency of traditional teach- ing methods. It is important to examine how effective these technologies are in practical use. This study developed online learning-teaching resource platforms using Flash multimedia, providing interactive and integrated features in an easy-to-use user interface, in order to discuss Computer-Aided Drawing (CAD). The study utilized a teaching experiment with a non-equivalent pretest-posttest control group design to test and discuss students' professional cognition, operating skill cognition, and level of learning satisfaction during the learning process. No significant differences emerged between the groups in regards to professional cognition or operation skills cognition. However, a significant difference in learning satisfaction was noted, indicating that the coursework with multimedia Flash produced greater satisfaction than with traditional learning methods. Results are explained in detail and recommendations for further research provided.

The use of errorless learning strategies for patients with Alzheimer's disease: a literature review.

PubMed

Li, Ruijie; Liu, Karen P Y

2012-12-01

The aim of this article was to review the evidence of errorless learning on learning outcomes in patients with early-stage Alzheimer's disease. A computer-aided literature search from 1999 to 2011 was carried out using MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO and PsycArticles. Keywords included 'errorless learning or practice' and 'Alzheimer's disease'. Four studies that fulfilled the inclusion criteria were selected and reviewed. Two of the studies were clinical controlled trials: one was a single-group pretest-post-test trial and the other was a multiple single-participant study. Demographic variables, design, treatment and outcome measures were summarized. Recall trials were used as the primary outcome measure. Results indicate that the use of errorless learning promotes better retention of specific types of information. Errorless learning is effective in memory rehabilitation of older adults with Alzheimer's disease. However, it would require more studies with unified outcome measures to allow for the formulation of standardized clinical protocol and recommendations.

Vibration control of building structures using self-organizing and self-learning neural networks

NASA Astrophysics Data System (ADS)

Madan, Alok

2005-11-01

Past research in artificial intelligence establishes that artificial neural networks (ANN) are effective and efficient computational processors for performing a variety of tasks including pattern recognition, classification, associative recall, combinatorial problem solving, adaptive control, multi-sensor data fusion, noise filtering and data compression, modelling and forecasting. The paper presents a potentially feasible approach for training ANN in active control of earthquake-induced vibrations in building structures without the aid of teacher signals (i.e. target control forces). A counter-propagation neural network is trained to output the control forces that are required to reduce the structural vibrations in the absence of any feedback on the correctness of the output control forces (i.e. without any information on the errors in output activations of the network). The present study shows that, in principle, the counter-propagation network (CPN) can learn from the control environment to compute the required control forces without the supervision of a teacher (unsupervised learning). Simulated case studies are presented to demonstrate the feasibility of implementing the unsupervised learning approach in ANN for effective vibration control of structures under the influence of earthquake ground motions. The proposed learning methodology obviates the need for developing a mathematical model of structural dynamics or training a separate neural network to emulate the structural response for implementation in practice.

An application of computer aided requirements analysis to a real time deep space system

NASA Technical Reports Server (NTRS)

Farny, A. M.; Morris, R. V.; Hartsough, C.; Callender, E. D.; Teichroew, D.; Chikofsky, E.

1981-01-01

The entire procedure of incorporating the requirements and goals of a space flight project into integrated, time ordered sequences of spacecraft commands, is called the uplink process. The Uplink Process Control Task (UPCT) was created to examine the uplink process and determine ways to improve it. The Problem Statement Language/Problem Statement Analyzer (PSL/PSA) designed to assist the designer/analyst/engineer in the preparation of specifications of an information system is used as a supporting tool to aid in the analysis. Attention is given to a definition of the uplink process, the definition of PSL/PSA, the construction of a PSA database, the value of analysis to the study of the uplink process, and the PSL/PSA lessons learned.

From research to self-reflection: learning about ourselves as academics through a support group's resistance to our intervention.

PubMed

Scherr, Courtney Lynam; Mattson, Marifran

2012-01-01

Purdue University's Center for Healthcare Engineering developed a computer-assisted technology hub (CATHUB) designed to aid individuals with disabilities. Upon realizing the lack of input from the very individuals they were trying to help, Marifran approached the developers of CATHUB and offered to engage a group of amputees to aid in the design and implementation of the hub. In this essay, Courtney and Marifran recount, each from their own perspective, their experiences working with Amputees in Action as participants in their research project. Ultimately the researchers discovered their research agenda was not compatible with the amputees' needs, resulting in enlightened self-reflection by the researchers and abandonment of the research project.

Computer-aided design and computer science technology

NASA Technical Reports Server (NTRS)

Fulton, R. E.; Voigt, S. J.

1976-01-01

A description is presented of computer-aided design requirements and the resulting computer science advances needed to support aerospace design. The aerospace design environment is examined, taking into account problems of data handling and aspects of computer hardware and software. The interactive terminal is normally the primary interface between the computer system and the engineering designer. Attention is given to user aids, interactive design, interactive computations, the characteristics of design information, data management requirements, hardware advancements, and computer science developments.

Computer Instructional Aids for Undergraduate Control Education.

ERIC Educational Resources Information Center

Volz, Richard A.; And Others

Engineering is coming to rely more and more heavily upon the computer for computations, analyses, and graphic displays which aid the design process. A general purpose simulation system, the Time-shared Automatic Control Laboratory (TACL), and a set of computer-aided design programs, Control Oriented Interactive Graphic Analysis and Design…

Overview of deep learning in medical imaging.

PubMed

Suzuki, Kenji

2017-09-01

The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a lesser number of training cases than did CNNs. "Deep learning", or ML with image input, in medical imaging is an explosively growing, promising field. It is expected that ML with image input will be the mainstream area in the field of medical imaging in the next few decades.

Automated assessment of joint synovitis activity from medical ultrasound and power doppler examinations using image processing and machine learning methods.

PubMed

Cupek, Rafal; Ziębiński, Adam

2016-01-01

Rheumatoid arthritis is the most common rheumatic disease with arthritis, and causes substantial functional disability in approximately 50% patients after 10 years. Accurate measurement of the disease activity is crucial to provide an adequate treatment and care to the patients. The aim of this study is focused on a computer aided diagnostic system that supports an assessment of synovitis severity. This paper focus on a computer aided diagnostic system that was developed within joint Polish-Norwegian research project related to the automated assessment of the severity of synovitis. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Synovitis is estimated by ultrasound examiner using the scoring system graded from 0 to 3. Activity score is estimated on the basis of the examiner's experience or standardized ultrasound atlases. The method needs trained medical personnel and the result can be affected by a human error. The porotype of a computer-aided diagnostic system and algorithms essential for an analysis of ultrasonic images of finger joints are main scientific output of the MEDUSA project. Medusa Evaluation System prototype uses bone, skin, joint and synovitis area detectors for mutual structural model based evaluation of synovitis. Finally, several algorithms that support the semi-automatic or automatic detection of the bone region were prepared as well as a system that uses the statistical data processing approach in order to automatically localize the regions of interest. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Activity score is estimated on the basis of the examiner's experience and the result can be affected by a human error. In this paper we presented the MEDUSA project which is focused on a computer aided diagnostic system that supports an assessment of synovitis severity.

Evaluation of Microcomputer-Based Operation and Maintenance Management Systems for Army Water/Wastewater Treatment Plant Operation.

DTIC Science & Technology

1986-07-01

COMPUTER-AIDED OPERATION MANAGEMENT SYSTEM ................. 29 Functions of an Off-Line Computer-Aided Operation Management System Applications of...System Comparisons 85 DISTRIBUTION 5V J. • 0. FIGURES Number Page 1 Hardware Components 21 2 Basic Functions of a Computer-Aided Operation Management System...Plant Visits 26 4 Computer-Aided Operation Management Systems Reviewed for Analysis of Basic Functions 29 5 Progress of Software System Installation and

How to build better memory training games

PubMed Central

Deveau, Jenni; Jaeggi, Susanne M.; Zordan, Victor; Phung, Calvin; Seitz, Aaron R.

2015-01-01

Can we create engaging training programs that improve working memory (WM) skills? While there are numerous procedures that attempt to do so, there is a great deal of controversy regarding their efficacy. Nonetheless, recent meta-analytic evidence shows consistent improvements across studies on lab-based tasks generalizing beyond the specific training effects (Au et al., 2014; Karbach and Verhaeghen, 2014), however, there is little research into how WM training aids participants in their daily life. Here we propose that incorporating design principles from the fields of Perceptual Learning (PL) and Computer Science might augment the efficacy of WM training, and ultimately lead to greater learning and transfer. In particular, the field of PL has identified numerous mechanisms (including attention, reinforcement, multisensory facilitation and multi-stimulus training) that promote brain plasticity. Also, computer science has made great progress in the scientific approach to game design that can be used to create engaging environments for learning. We suggest that approaches integrating knowledge across these fields may lead to a more effective WM interventions and better reflect real world conditions. PMID:25620916

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information

NASA Astrophysics Data System (ADS)

Melendez, Jaime; Sánchez, Clara I.; Philipsen, Rick H. H. M.; Maduskar, Pragnya; Dawson, Rodney; Theron, Grant; Dheda, Keertan; van Ginneken, Bram

2016-04-01

Lack of human resources and radiological interpretation expertise impair tuberculosis (TB) screening programmes in TB-endemic countries. Computer-aided detection (CAD) constitutes a viable alternative for chest radiograph (CXR) reading. However, no automated techniques that exploit the additional clinical information typically available during screening exist. To address this issue and optimally exploit this information, a machine learning-based combination framework is introduced. We have evaluated this framework on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa. Each record comprised a CAD score, automatically computed from a CXR, and 12 clinical features. Comparisons with strategies relying on either CAD scores or clinical information alone were performed. Our results indicate that the combination framework outperforms the individual strategies in terms of the area under the receiving operating characteristic curve (0.84 versus 0.78 and 0.72), specificity at 95% sensitivity (49% versus 24% and 31%) and negative predictive value (98% versus 95% and 96%). Thus, it is believed that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.

Exploring the color feature power for psoriasis risk stratification and classification: A data mining paradigm.

PubMed

Shrivastava, Vimal K; Londhe, Narendra D; Sonawane, Rajendra S; Suri, Jasjit S

2015-10-01

A large percentage of dermatologist׳s decision in psoriasis disease assessment is based on color. The current computer-aided diagnosis systems for psoriasis risk stratification and classification lack the vigor of color paradigm. The paper presents an automated psoriasis computer-aided diagnosis (pCAD) system for classification of psoriasis skin images into psoriatic lesion and healthy skin, which solves the two major challenges: (i) fulfills the color feature requirements and (ii) selects the powerful dominant color features while retaining high classification accuracy. Fourteen color spaces are discovered for psoriasis disease analysis leading to 86 color features. The pCAD system is implemented in a support vector-based machine learning framework where the offline image data set is used for computing machine learning offline color machine learning parameters. These are then used for transformation of the online color features to predict the class labels for healthy vs. diseased cases. The above paradigm uses principal component analysis for color feature selection of dominant features, keeping the original color feature unaltered. Using the cross-validation protocol, the above machine learning protocol is compared against the standalone grayscale features with 60 features and against the combined grayscale and color feature set of 146. Using a fixed data size of 540 images with equal number of healthy and diseased, 10 fold cross-validation protocol, and SVM of polynomial kernel of type two, pCAD system shows an accuracy of 99.94% with sensitivity and specificity of 99.93% and 99.96%. Using a varying data size protocol, the mean classification accuracies for color, grayscale, and combined scenarios are: 92.85%, 93.83% and 93.99%, respectively. The reliability of the system in these three scenarios are: 94.42%, 97.39% and 96.00%, respectively. We conclude that pCAD system using color space alone is compatible to grayscale space or combined color and grayscale spaces. We validated our pCAD system against facial color databases and the results are consistent in accuracy and reliability. Copyright © 2015 Elsevier Ltd. All rights reserved.

How the strengths of Lisp-family languages facilitate building complex and flexible bioinformatics applications

PubMed Central

Khomtchouk, Bohdan B; Weitz, Edmund; Karp, Peter D; Wahlestedt, Claes

2018-01-01

Abstract We present a rationale for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Put simply, Lisp-family languages enable programmers to more quickly write programs that run faster than in other languages. Languages such as Common Lisp, Scheme and Clojure facilitate the creation of powerful and flexible software that is required for complex and rapidly evolving domains like biology. We will point out several important key features that distinguish languages of the Lisp family from other programming languages, and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSLs): languages that are specialized to a particular area, and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the ‘programmable programming language’. We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and artificial intelligence research in bioinformatics and computational biology. PMID:28040748

How the strengths of Lisp-family languages facilitate building complex and flexible bioinformatics applications.

PubMed

Khomtchouk, Bohdan B; Weitz, Edmund; Karp, Peter D; Wahlestedt, Claes

2018-05-01

We present a rationale for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Put simply, Lisp-family languages enable programmers to more quickly write programs that run faster than in other languages. Languages such as Common Lisp, Scheme and Clojure facilitate the creation of powerful and flexible software that is required for complex and rapidly evolving domains like biology. We will point out several important key features that distinguish languages of the Lisp family from other programming languages, and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSLs): languages that are specialized to a particular area, and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the 'programmable programming language'. We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and artificial intelligence research in bioinformatics and computational biology.

The Feasibility of Classifying Breast Masses Using a Computer-Assisted Diagnosis (CAD) System Based on Ultrasound Elastography and BI-RADS Lexicon.

PubMed

Fleury, Eduardo F C; Gianini, Ana Claudia; Marcomini, Karem; Oliveira, Vilmar

2018-01-01

To determine the applicability of a computer-aided diagnostic system strain elastography system for the classification of breast masses diagnosed by ultrasound and scored using the criteria proposed by the breast imaging and reporting data system ultrasound lexicon and to determine the diagnostic accuracy and interobserver variability. This prospective study was conducted between March 1, 2016, and May 30, 2016. A total of 83 breast masses subjected to percutaneous biopsy were included. Ultrasound elastography images before biopsy were interpreted by 3 radiologists with and without the aid of computer-aided diagnostic system for strain elastography. The parameters evaluated by each radiologist results were sensitivity, specificity, and diagnostic accuracy, with and without computer-aided diagnostic system for strain elastography. Interobserver variability was assessed using a weighted κ test and an intraclass correlation coefficient. The areas under the receiver operating characteristic curves were also calculated. The areas under the receiver operating characteristic curve were 0.835, 0.801, and 0.765 for readers 1, 2, and 3, respectively, without computer-aided diagnostic system for strain elastography, and 0.900, 0.926, and 0.868, respectively, with computer-aided diagnostic system for strain elastography. The intraclass correlation coefficient between the 3 readers was 0.6713 without computer-aided diagnostic system for strain elastography and 0.811 with computer-aided diagnostic system for strain elastography. The proposed computer-aided diagnostic system for strain elastography system has the potential to improve the diagnostic performance of radiologists in breast examination using ultrasound associated with elastography.

Identification of lesion images from gastrointestinal endoscope based on feature extraction of combinational methods with and without learning process.

PubMed

Liu, Ding-Yun; Gan, Tao; Rao, Ni-Ni; Xing, Yao-Wen; Zheng, Jie; Li, Sang; Luo, Cheng-Si; Zhou, Zhong-Jun; Wan, Yong-Li

2016-08-01

The gastrointestinal endoscopy in this study refers to conventional gastroscopy and wireless capsule endoscopy (WCE). Both of these techniques produce a large number of images in each diagnosis. The lesion detection done by hand from the images above is time consuming and inaccurate. This study designed a new computer-aided method to detect lesion images. We initially designed an algorithm named joint diagonalisation principal component analysis (JDPCA), in which there are no approximation, iteration or inverting procedures. Thus, JDPCA has a low computational complexity and is suitable for dimension reduction of the gastrointestinal endoscopic images. Then, a novel image feature extraction method was established through combining the algorithm of machine learning based on JDPCA and conventional feature extraction algorithm without learning. Finally, a new computer-aided method is proposed to identify the gastrointestinal endoscopic images containing lesions. The clinical data of gastroscopic images and WCE images containing the lesions of early upper digestive tract cancer and small intestinal bleeding, which consist of 1330 images from 291 patients totally, were used to confirm the validation of the proposed method. The experimental results shows that, for the detection of early oesophageal cancer images, early gastric cancer images and small intestinal bleeding images, the mean values of accuracy of the proposed method were 90.75%, 90.75% and 94.34%, with the standard deviations (SDs) of 0.0426, 0.0334 and 0.0235, respectively. The areas under the curves (AUCs) were 0.9471, 0.9532 and 0.9776, with the SDs of 0.0296, 0.0285 and 0.0172, respectively. Compared with the traditional related methods, our method showed a better performance. It may therefore provide worthwhile guidance for improving the efficiency and accuracy of gastrointestinal disease diagnosis and is a good prospect for clinical application. Copyright © 2016 Elsevier B.V. All rights reserved.

Toward Medical Documentation That Enhances Situational Awareness Learning

PubMed Central

Lenert, Leslie A.

2016-01-01

The purpose of writing medical notes in a computer system goes beyond documentation for medical-legal purposes or billing. The structure of documentation is a checklist that serves as a cognitive aid and a potential index to retrieve information for learning from the record. For the past 50 years, one of the primary organizing structures for physicians’ clinical documentation have been the SOAP note (Subjective, Objective, Assessment, Plan). The cognitive check list is well-suited to differential diagnosis but may not support detection of changes in systems and/or learning from cases. We describe an alternative cognitive checklist called the OODA Loop (Observe, Orient, Decide, Act. Through incorporation of projections of anticipated course events with and without treatment and by making “Decisions” an explicit category of documentation in the medical record in the context of a variable temporal cycle for observations, OODA may enhance opportunities to learn from clinical care. PMID:28269872

A transfer learning approach for classification of clinical significant prostate cancers from mpMRI scans

NASA Astrophysics Data System (ADS)

Chen, Quan; Xu, Xiang; Hu, Shiliang; Li, Xiao; Zou, Qing; Li, Yunpeng

2017-03-01

Deep learning has shown a great potential in computer aided diagnosis. However, in many applications, large dataset is not available. This makes the training of a sophisticated deep learning neural network (DNN) difficult. In this study, we demonstrated that with transfer learning, we can quickly retrain start-of-the-art DNN models with limited data provided by the prostateX challenge. The training data consists of 330 lesions, only 78 were clinical significant. Efforts were made to balance the data during training. We used ImageNet pre-trained inceptionV3 and Vgg-16 model and obtained AUC of 0.81 and 0.83 respectively on the prostateX test data, good for a 4th place finish. We noticed that models trained for different prostate zone has different sensitivity. Applying scaling factors before merging the result improves the AUC for the final result.

Transforming the advanced lab: Part I - Learning goals

NASA Astrophysics Data System (ADS)

Zwickl, Benjamin; Finkelstein, Noah; Lewandowski, H. J.

2012-02-01

Within the physics education research community relatively little attention has been given to laboratory courses, especially at the upper-division undergraduate level. As part of transforming our senior-level Optics and Modern Physics Lab at the University of Colorado Boulder we are developing learning goals, revising curricula, and creating assessments. In this paper, we report on the establishment of our learning goals and a surrounding framework that have emerged from discussions with a wide variety of faculty, from a review of the literature on labs, and from identifying the goals of existing lab courses. Our goals go beyond those of specific physics content and apparatus, allowing instructors to personalize them to their contexts. We report on four broad themes and associated learning goals: Modeling (math-physics-data connection, statistical error analysis, systematic error, modeling of engineered "black boxes"), Design (of experiments, apparatus, programs, troubleshooting), Communication, and Technical Lab Skills (computer-aided data analysis, LabVIEW, test and measurement equipment).

Machine Learning and Radiology

PubMed Central

Wang, Shijun; Summers, Ronald M.

2012-01-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

Do we need dissection in an integrated problem-based learning medical course? Perceptions of first- and second-year students.

PubMed

Azer, Samy A; Eizenberg, Norm

2007-03-01

The introduction of a problem-based learning (PBL) curriculum at the School of Medicine of the University of Melbourne has necessitated a reduction in the number of lectures and limited the use of dissection in teaching anatomy. In the new curriculum, students learn the anatomy of different body systems using PBL tutorials, practical classes, pre-dissected specimens, computer-aided learning multimedia and a few dissection classes. The aims of this study are: (1) to assess the views of first- and second-year medical students on the importance of dissection in learning about the anatomy, (2) to assess if students' views have been affected by demographic variables such as gender, academic background and being a local or an international student, and (3) to assess which educational tools helped them most in learning the anatomy and whether dissection sessions have helped them in better understanding anatomy. First- and second-year students enrolled in the medical course participated in this study. Students were asked to fill out a 5-point Likert scale questionnaire. Data was analysed using Mann-Whitney's U test, Wilcoxon's signed-ranks or the calculation of the Chi-square value. The response rates were 89% for both first- and second-year students. Compared to second-year students, first-year students perceived dissection to be important for deep understanding of anatomy (P < 0.001), making learning interesting (P < 0.001) and introducing them to emergency procedures (P < 0.001). Further, they preferred dissection over any other approach (P < 0.001). First-year students ranked dissection (44%), textbooks (23%), computer-aided learning (CAL), multimedia (10%), self-directed learning (6%) and lectures (5%) as the most valuable resources for learning anatomy, whereas second-year students found textbooks (38%), dissection (18%), pre-dissected specimens (11%), self-directed learning (9%), lectures (7%) and CAL programs (7%) as most useful. Neither of the groups showed a significant preference for pre-dissected specimens, CAL multimedia or lectures over dissection. Both first- and second-year students, regardless of their gender, academic background, or citizenship felt that the time devoted to dissection classes were not adequate. Students agreed that dissection deepened their understanding of anatomical structures, provided them with a three-dimensional perspective of structures and helped them recall what they learnt. Although their perception about the importance of dissection changed as they progressed in the course, good anatomy textbooks were perceived as an excellent resource for learning anatomy. Interestingly, innovations used in teaching anatomy, such as interactive multimedia resources, have not replaced students' perceptions about the importance of dissection.

Motivation in computer-assisted instruction.

PubMed

Hu, Amanda; Shewokis, Patricia A; Ting, Kimberly; Fung, Kevin

2016-08-01

Computer-aided instruction (CAI) is defined as instruction in which computers play a central role as the means of information delivery and direct interaction with learners. Computer-aided instruction has become mainstream in medical school curricula. For example, a three-dimensional (3D) computer module of the larynx has been created to teach laryngeal anatomy. Although the novelty and educational potential of CAI has garnered much attention, these new technologies have been plagued with low utilization rates. Several experts attribute this problem to lack of motivation in students. Motivation is defined as the desire and action toward goal-oriented behavior. Psychologist Dr. John Keller developed the ARCS theory of motivational learning, which proposed four components: attention (A), relevance (R), concentration (C), and satisfaction (S). Keller believed that motivation is not only an innate characteristic of the pupil; it can also be influenced by external factors, such as the instructional design of the curriculum. Thus, understanding motivation is an important step to designing CAI appropriately. Keller also developed a 36-item validated instrument called the Instructional Materials Motivation Survey (IMMS) to measure motivation. The objective of this study was to study motivation in CAI. Medical students learning anatomy with the 3D computer module will have higher laryngeal anatomy test scores and higher IMMS motivation scores. Higher anatomy test scores will be positively associated with higher IMMS scores. Prospective, randomized, controlled trial. After obtaining institutional review board approval, 100 medical students (mean age 25.5 ± 2.5, 49% male) were randomized to either the 3D computer module (n = 49) or written text (n = 51). Information content was identical in both arms. Students were given 30 minutes to study laryngeal anatomy and then completed the laryngeal anatomy test and IMMS. Students were categorized as either junior (year 1 and 2) or senior (year 3 and 4). There were no significant differences in anatomy scores based on educational modality. There was significant interaction of educational modality by year [F(1,96) = 4.12, P = 0.045, ω(2)  = 0.031]. For the total score, there was a significant effect of year [F(1,96) = 22.28, P < 0.001, ω(2)  = 0.178], with seniors (15.4 ± 2.6) scoring significantly higher than juniors (12.8 ± 3.1). For the motivational score, the total IMMS score had two significant effects. With educational modality [F(1,96) = 5.18, P = 0.025, ω(2)  = 0.041], the 3D group (12.4 ± 2.8) scored significantly higher than the written text group (11.7 ± 3.2). With year [F(1,96) = 25.31, P < 0.001, ω(2)  = 0.198], seniors (13.4 ± 3.0) scored significantly higher than juniors (10.8 ± 2.5). Pearson's correlation showed positive associations (r = 0.22-0.91) between anatomy scores and IMMS motivation scores (P < 0.05). Computer-aided instruction conferred no measurable educational benefit over traditional written text in medical students; however, CAI was associated with higher motivational levels. Computer-aided instruction was found to have a greater positive impact on senior medical students with higher anatomy and motivational scores. Higher anatomy scores were positively associated with higher motivational scores. Computer-aided instruction may be better targeted toward senior students. N/A. Laryngoscope, 126:S5-S13, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Information Systems for NASA's Aeronautics and Space Enterprises

NASA Technical Reports Server (NTRS)

Kutler, Paul

1998-01-01

The aerospace industry is being challenged to reduce costs and development time as well as utilize new technologies to improve product performance. Information technology (IT) is the key to providing revolutionary solutions to the challenges posed by the increasing complexity of NASA's aeronautics and space missions and the sophisticated nature of the systems that enable them. The NASA Ames vision is to develop technologies enabling the information age, expanding the frontiers of knowledge for aeronautics and space, improving America's competitive position, and inspiring future generations. Ames' missions to accomplish that vision include: 1) performing research to support the American aviation community through the unique integration of computation, experimentation, simulation and flight testing, 2) studying the health of our planet, understanding living systems in space and the origins of the universe, developing technologies for space flight, and 3) to research, develop and deliver information technologies and applications. Information technology may be defined as the use of advance computing systems to generate data, analyze data, transform data into knowledge and to use as an aid in the decision-making process. The knowledge from transformed data can be displayed in visual, virtual and multimedia environments. The decision-making process can be fully autonomous or aided by a cognitive processes, i.e., computational aids designed to leverage human capacities. IT Systems can learn as they go, developing the capability to make decisions or aid the decision making process on the basis of experiences gained using limited data inputs. In the future, information systems will be used to aid space mission synthesis, virtual aerospace system design, aid damaged aircraft during landing, perform robotic surgery, and monitor the health and status of spacecraft and planetary probes. NASA Ames through the Center of Excellence for Information Technology Office is leading the effort in pursuit of revolutionary, IT-based approaches to satisfying NASA's aeronautics and space requirements. The objective of the effort is to incorporate information technologies within each of the Agency's four Enterprises, i.e., Aeronautics and Space Transportation Technology, Earth, Science, Human Exploration and Development of Space and Space Sciences. The end results of these efforts for Enterprise programs and projects should be reduced cost, enhanced mission capability and expedited mission completion.

Using Chemistry Teaching Aids Based Local Wisdom as an Alternative Media for Chemistry Teaching and Learning

ERIC Educational Resources Information Center

Priyambodo, Erfan; Wulaningrum, Safira

2017-01-01

Students have difficulties in relating the chemistry phenomena they learned and the life around them. It is necessary to have teaching aids which can help them to relate between chemistry with the phenomena occurred in everyday life, which is chemistry's teaching aids based on local wisdom. There are 3 teaching aids which used in chemistry…

Comparison of Two Modes of Delivery of First Aid Training Including Basic Life Support

ERIC Educational Resources Information Center

Lippmann, John; Livingston, Patricia; Craike, Melinda J.

2011-01-01

Aims: Flexible-learning first aid courses are increasingly common due to reduced classroom contact time. This study compared retention of first aid knowledge and basic life support (BLS) skills three months after a two-day, classroom-based first aid course (STD) to one utilizing on-line theory learning at home followed by one day of classroom…

Chile: educational game, "Learning about AIDS: the Responsibility of All".

PubMed

1993-01-01

For more than 10 years, People's Health Education (EPES) has developed educational materials which call upon target audiences to integrate their practical experiences into a collective learning process based upon games. The methodology and materials aim to meet the needs of the most underprivileged sections of the population. EPES produced "Learning about AIDS: the responsibility of all," a game which can be used as it is or adapted to meet the needs of differing groups. The objectives of the game are to provide basic information on AIDS; to facilitate the expression of ideas, beliefs, and myths about AIDS; to promote forums for discussion in order to exchange opinions and views on sexuality and AIDS; to create awareness on how AIDS affects the community; and to create awareness of the need to prevent the disease. Played in couples to strengthen the level of interpersonal communication on such issues, the game is played because AIDS is a fact of everyday life which is affecting the community, because learning about AIDS will help people to protect themselves and their communities from the disease and groundless associated fears, and because open discussion is needed to help prevent more people from becoming infected with HIV.

Imagery as an aid to retrieval for Korsakoff patients.

PubMed

Cermak, L S

1975-06-01

Six Korsakoff patients and six alcoholic controls learned a five item P-A task under each of the following three learning conditions; Rote, Imagery, and Cued learning. Under all conditions the Korsakoff patients took more trials to learn than did the control patients. However, both imagery learning and cued learning were easier than rote learning for the Korsakoff patients when recall was used as the learning index. When a recognition measure was used instead of the recall, imagery learning proved easiest with no difference existing between cued and rote learning. In a second experiment, the patients were given the cue (a mediating link) during presentation, but not during retrieval. Under this condition the Korsakoff patients learned no more rapidly than they did by rote regardless which response measure was required. It was concluded that imagery can aid both storage and retrieval of verbal information for Korsakoff patients, while cuing aids only the retrieval process.

Computer-aided classification of breast masses using contrast-enhanced digital mammograms

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Aghaei, Faranak; Heidari, Morteza; Wu, Teresa; Patel, Bhavika; Zheng, Bin

2018-02-01

By taking advantages of both mammography and breast MRI, contrast-enhanced digital mammography (CEDM) has emerged as a new promising imaging modality to improve efficacy of breast cancer screening and diagnosis. The primary objective of study is to develop and evaluate a new computer-aided detection and diagnosis (CAD) scheme of CEDM images to classify between malignant and benign breast masses. A CEDM dataset consisting of 111 patients (33 benign and 78 malignant) was retrospectively assembled. Each case includes two types of images namely, low-energy (LE) and dual-energy subtracted (DES) images. First, CAD scheme applied a hybrid segmentation method to automatically segment masses depicting on LE and DES images separately. Optimal segmentation results from DES images were also mapped to LE images and vice versa. Next, a set of 109 quantitative image features related to mass shape and density heterogeneity was initially computed. Last, four multilayer perceptron-based machine learning classifiers integrated with correlationbased feature subset evaluator and leave-one-case-out cross-validation method was built to classify mass regions depicting on LE and DES images, respectively. Initially, when CAD scheme was applied to original segmentation of DES and LE images, the areas under ROC curves were 0.7585+/-0.0526 and 0.7534+/-0.0470, respectively. After optimal segmentation mapping from DES to LE images, AUC value of CAD scheme significantly increased to 0.8477+/-0.0376 (p<0.01). Since DES images eliminate overlapping effect of dense breast tissue on lesions, segmentation accuracy was significantly improved as compared to regular mammograms, the study demonstrated that computer-aided classification of breast masses using CEDM images yielded higher performance.

Rubber airplane: Constraint-based component-modeling for knowledge representation in computer-aided conceptual design

NASA Technical Reports Server (NTRS)

Kolb, Mark A.

1990-01-01

Viewgraphs on Rubber Airplane: Constraint-based Component-Modeling for Knowledge Representation in Computer Aided Conceptual Design are presented. Topics covered include: computer aided design; object oriented programming; airfoil design; surveillance aircraft; commercial aircraft; aircraft design; and launch vehicles.

[Development of computer aided forming techniques in manufacturing scaffolds for bone tissue engineering].

PubMed

Wei, Xuelei; Dong, Fuhui

2011-12-01

To review recent advance in the research and application of computer aided forming techniques for constructing bone tissue engineering scaffolds. The literature concerning computer aided forming techniques for constructing bone tissue engineering scaffolds in recent years was reviewed extensively and summarized. Several studies over last decade have focused on computer aided forming techniques for bone scaffold construction using various scaffold materials, which is based on computer aided design (CAD) and bone scaffold rapid prototyping (RP). CAD include medical CAD, STL, and reverse design. Reverse design can fully simulate normal bone tissue and could be very useful for the CAD. RP techniques include fused deposition modeling, three dimensional printing, selected laser sintering, three dimensional bioplotting, and low-temperature deposition manufacturing. These techniques provide a new way to construct bone tissue engineering scaffolds with complex internal structures. With rapid development of molding and forming techniques, computer aided forming techniques are expected to provide ideal bone tissue engineering scaffolds.

Multi-stage learning aids applied to hands-on software training.

PubMed

Rother, Kristian; Rother, Magdalena; Pleus, Alexandra; Upmeier zu Belzen, Annette

2010-11-01

Delivering hands-on tutorials on bioinformatics software and web applications is a challenging didactic scenario. The main reason is that trainees have heterogeneous backgrounds, different previous knowledge and vary in learning speed. In this article, we demonstrate how multi-stage learning aids can be used to allow all trainees to progress at a similar speed. In this technique, the trainees can utilize cards with hints and answers to guide themselves self-dependently through a complex task. We have successfully conducted a tutorial for the molecular viewer PyMOL using two sets of learning aid cards. The trainees responded positively, were able to complete the task, and the trainer had spare time to respond to individual questions. This encourages us to conclude that multi-stage learning aids overcome many disadvantages of established forms of hands-on software training.

Studies of Learning and Self-Contained Educational Systems, 1973-1976

DTIC Science & Technology

1976-03-01

ISTKIW WORDS fCondnu» on reverse aide // neceeeary ««’ ’-dtntlly by block numb«; Leirning, teaching, memory, tutorial instruction. 20. AB ^RACT...poorly acquired or because the learner might have missed exposi -e to that part of the material, then the rest of the structure is weakened and may...War in the computer data bsnt, including the causal structure of the actions during the war. We are ab ]^ to use the data base to interact with a

FEQinput—An editor for the full equations (FEQ) hydraulic modeling system

USGS Publications Warehouse

Ancalle, David S.; Ancalle, Pablo J.; Domanski, Marian M.

2017-10-30

IntroductionThe Full Equations Model (FEQ) is a computer program that solves the full, dynamic equations of motion for one-dimensional unsteady hydraulic flow in open channels and through control structures. As a result, hydrologists have used FEQ to design and operate flood-control structures, delineate inundation maps, and analyze peak-flow impacts. To aid in fighting floods, hydrologists are using the software to develop a system that uses flood-plain models to simulate real-time streamflow.Input files for FEQ are composed of text files that contain large amounts of parameters, data, and instructions that are written in a format exclusive to FEQ. Although documentation exists that can aid in the creation and editing of these input files, new users face a steep learning curve in order to understand the specific format and language of the files.FEQinput provides a set of tools to help a new user overcome the steep learning curve associated with creating and modifying input files for the FEQ hydraulic model and the related utility tool, Full Equations Utilities (FEQUTL).

Original Science-Based Music and Student Learning

ERIC Educational Resources Information Center

Smolinski, Keith

2010-01-01

American middle school student science scores have been stagnating for several years, demonstrating a need for better learning strategies to aid teachers in instruction and students in content learning. It has also been suggested by researchers that music can be used to aid students in their learning and memory. Employing the theoretical framework…

Design and validation of a computer-aided learning program to enhance students' ability to recognize lameness in the horse.

PubMed

Barstow, Amy; Pfau, Thilo; Bolt, David M; Smith, Roger K; Weller, Renate

2014-01-01

The ability to recognize lameness in the horse is an important skill for veterinary graduates; however, opportunities to develop this skill at the undergraduate level are limited. Computer-aided learning programs (CALs) have been successful in supplementing practical skills teaching. The aim of this study was to design and validate a CAL for the teaching of equine lameness recognition (CAL1). A control CAL was designed to simulate learning by experience (CAL2). Student volunteers were randomly assigned to either CAL and tested to establish their current ability to recognize lameness. Retesting occurred both immediately following exposure and 1 week later. At each test point, the number of correct responses for forelimb and hind limb cases was determined. Student confidence was assessed before and after CAL exposure, with previous opportunities to recognize lameness taken into account. Immediately following exposure, the number of correct responses was significantly higher for CAL1 than for CAL2, both overall and for forelimb cases but not for hind limb cases. After 1 week, the CAL1 group performed significantly better overall compared to the CAL2 group, with no significant difference between forelimb and hind limb cases. Student confidence and ability to recognize lameness were significantly improved following exposure to CAL1. When considered as one category, students in years 4 and 5 performed significantly better than year 3 students. Gender did not significantly affect performance. CAL1 could be used to supplement current lameness recognition opportunities. CAL1 is, however, limited in its ability to improve lameness recognition, especially in relation to hind limb lameness where it was unable to attain a significant difference from CAL2.

Effectiveness of a computer-aided neuroanatomy program for entry-level physical therapy students: anatomy and clinical examination of the dorsal column-medial lemniscal system.

PubMed

McKeough, D Michael; Mattern-Baxter, Katrin; Barakatt, Edward

2010-01-01

The purpose of this study was to determine if a computer-aided instruction learning module improves students' knowledge of the neuroanatomy/physiology and clinical examination of the dorsal column-medial lemniscal (DCML) system. Sixty-one physical therapy students enrolled in a clinical neurology course in entry-level PT educational programs at two universities participated in the study. Students from University-1 (U1;) had not had a previous neuroanatomy course, while students from University-2 (U2;) had taken a neuroanatomy course in the previous semester. Before and after working with the learning module, students took a paper-and-pencil test on the neuroanatomy/physiology and clinical examination of the DCML system. Kruskal-Wallis one-way ANOVA and Mann-Whitney tests were used to determine if differences existed between neuroanatomy/physiology examination scores and clinical examination scores before and after taking the learning module, and between student groups based on university attended. For students from U1, neuroanatomy/physiology post-test scores improved significantly over pre-test scores (p < 0.001), while post-test scores of students from U2 did not (p = 0.60). Neuroanatomy/physiology pre-test scores from U2 were significantly better than those from U1 (p < 0.001); there was no significant difference in post-test scores (p = 0.062). Clinical examination pre-test and post-test scores from U2 were significantly better than those from U1 (p < 0.001). Clinical examination post-test scores improved significantly from the pre-test scores for both U1 (p < 0.001) and U2 (p < 0.001).

Attributes Affecting Computer-Aided Decision Making--A Literature Survey.

ERIC Educational Resources Information Center

Moldafsky, Neil I; Kwon, Ik-Whan

1994-01-01

Reviews current literature about personal, demographic, situational, and cognitive attributes that affect computer-aided decision making. The effectiveness of computer-aided decision making is explored in relation to decision quality, effectiveness, and confidence. Studies of the effects of age, anxiety, cognitive type, attitude, gender, and prior…

Hearing Impairments. Tech Use Guide: Using Computer Technology.

ERIC Educational Resources Information Center

Council for Exceptional Children, Reston, VA. Center for Special Education Technology.

One of nine brief guides for special educators on using computer technology, this guide focuses on advances in electronic aids, computers, telecommunications, and videodiscs to assist students with hearing impairments. Electronic aids include hearing aids, telephone devices for the deaf, teletypes, closed captioning systems for television, and…

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

PubMed

Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

2017-02-27

The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

Metrics in method engineering

NASA Astrophysics Data System (ADS)

Brinkkemper, S.; Rossi, M.

1994-12-01

As customizable computer aided software engineering (CASE) tools, or CASE shells, have been introduced in academia and industry, there has been a growing interest into the systematic construction of methods and their support environments, i.e. method engineering. To aid the method developers and method selectors in their tasks, we propose two sets of metrics, which measure the complexity of diagrammatic specification techniques on the one hand, and of complete systems development methods on the other hand. Proposed metrics provide a relatively fast and simple way to analyze the technique (or method) properties, and when accompanied with other selection criteria, can be used for estimating the cost of learning the technique and the relative complexity of a technique compared to others. To demonstrate the applicability of the proposed metrics, we have applied them to 34 techniques and 15 methods.

Computer Aided Design in Engineering Education.

ERIC Educational Resources Information Center

Gobin, R.

1986-01-01

Discusses the use of Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) systems in an undergraduate engineering education program. Provides a rationale for CAD/CAM use in the already existing engineering program. Describes the methods used in choosing the systems, some initial results, and warnings for first-time users. (TW)

Prosthetic rehabilitation with an implant-supported fixed prosthesis using computer-aided design and computer-aided manufacturing dental technology for a patient with a mandibulectomy: A clinical report.

PubMed

Yoon, Hyung-In; Han, Jung-Suk

2016-02-01

The fabrication of dental prostheses with computer-aided design and computer-aided manufacturing shows acceptable marginal fits and favorable treatment outcomes. This clinical report describes the management of a patient who had undergone a mandibulectomy and received an implant-supported fixed prosthesis by using additive manufacturing for the framework and subtractive manufacturing for the monolithic zirconia restorations. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

PubMed Central

Hoo-Chang, Shin; Roth, Holger R.; Gao, Mingchen; Lu, Le; Xu, Ziyue; Nogues, Isabella; Yao, Jianhua; Mollura, Daniel

2016-01-01

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets (i.e. ImageNet) and the revival of deep convolutional neural networks (CNN). CNNs enable learning data-driven, highly representative, layered hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models (supervised) pre-trained from natural image dataset to medical image tasks (although domain transfer between two medical image datasets is also possible). In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computeraided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, with 85% sensitivity at 3 false positive per patient, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks. PMID:26886976

Computers in Manufacturing.

ERIC Educational Resources Information Center

Hudson, C. A.

1982-01-01

Advances in factory computerization (computer-aided design and computer-aided manufacturing) are reviewed, including discussions of robotics, human factors engineering, and the sociological impact of automation. (JN)

Bilateral symmetry aspects in computer-aided Alzheimer's disease diagnosis by single-photon emission-computed tomography imaging.

PubMed

Illán, Ignacio Alvarez; Górriz, Juan Manuel; Ramírez, Javier; Lang, Elmar W; Salas-Gonzalez, Diego; Puntonet, Carlos G

2012-11-01

This paper explores the importance of the latent symmetry of the brain in computer-aided systems for diagnosing Alzheimer's disease (AD). Symmetry and asymmetry are studied from two points of view: (i) the development of an effective classifier within the scope of machine learning techniques, and (ii) the assessment of its relevance to the AD diagnosis in the early stages of the disease. The proposed methodology is based on eigenimage decomposition of single-photon emission-computed tomography images, using an eigenspace extension to accommodate odd and even eigenvectors separately. This feature extraction technique allows for support-vector-machine classification and image analysis. Identification of AD patterns is improved when the latent symmetry of the brain is considered, with an estimated 92.78% accuracy (92.86% sensitivity, 92.68% specificity) using a linear kernel and a leave-one-out cross validation strategy. Also, asymmetries may be used to define a test for AD that is very specific (90.24% specificity) but not especially sensitive. Two main conclusions are derived from the analysis of the eigenimage spectrum. Firstly, the recognition of AD patterns is improved when considering only the symmetric part of the spectrum. Secondly, asymmetries in the hypo-metabolic patterns, when present, are more pronounced in subjects with AD. Copyright © 2012 Elsevier B.V. All rights reserved.

Semi-supervised protein subcellular localization.

PubMed

Xu, Qian; Hu, Derek Hao; Xue, Hong; Yu, Weichuan; Yang, Qiang

2009-01-30

Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data. In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions. Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.

A conceptual cognitive architecture for robots to learn behaviors from demonstrations in robotic aid area.

PubMed

Tan, Huan; Liang, Chen

2011-01-01

This paper proposes a conceptual hybrid cognitive architecture for cognitive robots to learn behaviors from demonstrations in robotic aid situations. Unlike the current cognitive architectures, this architecture puts concentration on the requirements of the safety, the interaction, and the non-centralized processing in robotic aid situations. Imitation learning technologies for cognitive robots have been integrated into this architecture for rapidly transferring the knowledge and skills between human teachers and robots.

Advanced engineering environment collaboration project.

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

Lamph, Jane Ann; Pomplun, Alan R.; Kiba, Grant W.

2008-12-01

The Advanced Engineering Environment (AEE) is a model for an engineering design and communications system that will enhance project collaboration throughout the nuclear weapons complex (NWC). Sandia National Laboratories and Parametric Technology Corporation (PTC) worked together on a prototype project to evaluate the suitability of a portion of PTC's Windchill 9.0 suite of data management, design and collaboration tools as the basis for an AEE. The AEE project team implemented Windchill 9.0 development servers in both classified and unclassified domains and used them to test and evaluate the Windchill tool suite relative to the needs of the NWC using weaponsmore » project use cases. A primary deliverable was the development of a new real time collaborative desktop design and engineering process using PDMLink (data management tool), Pro/Engineer (mechanical computer aided design tool) and ProductView Lite (visualization tool). Additional project activities included evaluations of PTC's electrical computer aided design, visualization, and engineering calculations applications. This report documents the AEE project work to share information and lessons learned with other NWC sites. It also provides PTC with recommendations for improving their products for NWC applications.« less

A multimedia adult literacy program: Combining NASA technology, instructional design theory, and authentic literacy concepts

NASA Technical Reports Server (NTRS)

Willis, Jerry W.

1993-01-01

For a number of years, the Software Technology Branch of the Information Systems Directorate has been involved in the application of cutting edge hardware and software technologies to instructional tasks related to NASA projects. The branch has developed intelligent computer aided training shells, instructional applications of virtual reality and multimedia, and computer-based instructional packages that use fuzzy logic for both instructional and diagnostic decision making. One outcome of the work on space-related technology-supported instruction has been the creation of a significant pool of human talent in the branch with current expertise on the cutting edges of instructional technologies. When the human talent is combined with advanced technologies for graphics, sound, video, CD-ROM, and high speed computing, the result is a powerful research and development group that both contributes to the applied foundations of instructional technology and creates effective instructional packages that take advantage of a range of advanced technologies. Several branch projects are currently underway that combine NASA-developed expertise to significant instructional problems in public education. The branch, for example, has developed intelligent computer aided software to help high school students learn physics and staff are currently working on a project to produce educational software for young children with language deficits. This report deals with another project, the adult literacy tutor. Unfortunately, while there are a number of computer-based instructional packages available for adult literacy instruction, most of them are based on the same instructional models that failed these students when they were in school. The teacher-centered, discrete skill and drill-oriented, instructional strategies, even when they are supported by color computer graphics and animation, that form the foundation for most of the computer-based literacy packages currently on the market may not be the most effective or most desirable way to use computer technology in literacy programs. This project is developing a series of instructional packages that are based on a different instructional model - authentic instruction. The instructional development model used to create these packages is also different. Instead of using the traditional five stage linear, sequential model based on behavioral learning theory, the project uses the recursive, reflective design and development model (R2D2) that is based on cognitive learning theory, particularly the social constructivism of Vygotsky, and an epistemology based on critical theory. Using alternative instructional and instructional development theories, the result of the summer faculty fellowship is LiteraCity, a multimedia adult literacy instructional package that is a simulation of finding and applying for a job. The program, which is about 120 megabytes, is distributed on CD-ROM.

The Effects of Computer-Aided Design Software on Engineering Students' Spatial Visualisation Skills

ERIC Educational Resources Information Center

Kösa, Temel; Karakus, Fatih

2018-01-01

The purpose of this study was to determine the influence of computer-aided design (CAD) software-based instruction on the spatial visualisation skills of freshman engineering students in a computer-aided engineering drawing course. A quasi-experimental design was applied, using the Purdue Spatial Visualization Test-Visualization of Rotations…

Computer-Presented Organizational/Memory Aids as Instruction for Solving Pico-Fomi Problems.

ERIC Educational Resources Information Center

Steinberg, Esther R.; And Others

1985-01-01

Describes investigation of effectiveness of computer-presented organizational/memory aids (matrix and verbal charts controlled by computer or learner) as instructional technique for solving Pico-Fomi problems, and the acquisition of deductive inference rules when such aids are present. Results indicate chart use control should be adapted to…

DeepInfer: open-source deep learning deployment toolkit for image-guided therapy

NASA Astrophysics Data System (ADS)

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-03-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research work ows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy.

PubMed

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A; Kapur, Tina; Wells, William M; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-02-11

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy

PubMed Central

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-01-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose “DeepInfer” – an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections. PMID:28615794

Computer-aided design development transition for IPAD environment

NASA Technical Reports Server (NTRS)

Owens, H. G.; Mock, W. D.; Mitchell, J. C.

1980-01-01

The relationship of federally sponsored computer-aided design/computer-aided manufacturing (CAD/CAM) programs to the aircraft life cycle design process, an overview of NAAD'S CAD development program, an evaluation of the CAD design process, a discussion of the current computing environment within which NAAD is developing its CAD system, some of the advantages/disadvantages of the NAAD-IPAD approach, and CAD developments during transition into the IPAD system are discussed.

CAD/CAE Integration Enhanced by New CAD Services Standard

NASA Technical Reports Server (NTRS)

Claus, Russell W.

2002-01-01

A Government-industry team led by the NASA Glenn Research Center has developed a computer interface standard for accessing data from computer-aided design (CAD) systems. The Object Management Group, an international computer standards organization, has adopted this CAD services standard. The new standard allows software (e.g., computer-aided engineering (CAE) and computer-aided manufacturing software to access multiple CAD systems through one programming interface. The interface is built on top of a distributed computing system called the Common Object Request Broker Architecture (CORBA). CORBA allows the CAD services software to operate in a distributed, heterogeneous computing environment.

Investigations in Computer-Aided Instruction and Computer-Aided Controls. Final Report.

ERIC Educational Resources Information Center

Rosenberg, R.C.; And Others

These research projects, designed to delve into certain relationships between humans and computers, are focused on computer-assisted instruction and on man-computer interaction. One study demonstrates that within the limits of formal engineering theory, a computer simulated laboratory (Dynamic Systems Laboratory) can be built in which freshmen…

Software and resources for computational medicinal chemistry

PubMed Central

Liao, Chenzhong; Sitzmann, Markus; Pugliese, Angelo; Nicklaus, Marc C

2011-01-01

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools. PMID:21707404

Using machine learning classifiers to assist healthcare-related decisions: classification of electronic patient records.

PubMed

Pollettini, Juliana T; Panico, Sylvia R G; Daneluzzi, Julio C; Tinós, Renato; Baranauskas, José A; Macedo, Alessandra A

2012-12-01

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Microscopic medical image classification framework via deep learning and shearlet transform.

PubMed

Rezaeilouyeh, Hadi; Mollahosseini, Ali; Mahoor, Mohammad H

2016-10-01

Cancer is the second leading cause of death in US after cardiovascular disease. Image-based computer-aided diagnosis can assist physicians to efficiently diagnose cancers in early stages. Existing computer-aided algorithms use hand-crafted features such as wavelet coefficients, co-occurrence matrix features, and recently, histogram of shearlet coefficients for classification of cancerous tissues and cells in images. These hand-crafted features often lack generalizability since every cancerous tissue and cell has a specific texture, structure, and shape. An alternative approach is to use convolutional neural networks (CNNs) to learn the most appropriate feature abstractions directly from the data and handle the limitations of hand-crafted features. A framework for breast cancer detection and prostate Gleason grading using CNN trained on images along with the magnitude and phase of shearlet coefficients is presented. Particularly, we apply shearlet transform on images and extract the magnitude and phase of shearlet coefficients. Then we feed shearlet features along with the original images to our CNN consisting of multiple layers of convolution, max pooling, and fully connected layers. Our experiments show that using the magnitude and phase of shearlet coefficients as extra information to the network can improve the accuracy of detection and generalize better compared to the state-of-the-art methods that rely on hand-crafted features. This study expands the application of deep neural networks into the field of medical image analysis, which is a difficult domain considering the limited medical data available for such analysis.

Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings.

PubMed

Mordang, Jan-Jurre; Gubern-Mérida, Albert; Bria, Alessandro; Tortorella, Francesco; den Heeten, Gerard; Karssemeijer, Nico

2017-04-01

Computer-aided detection (CADe) systems for mammography screening still mark many false positives. This can cause radiologists to lose confidence in CADe, especially when many false positives are obviously not suspicious to them. In this study, we focus on obvious false positives generated by microcalcification detection algorithms. We aim at reducing the number of obvious false-positive findings by adding an additional step in the detection method. In this step, a multiclass machine learning method is implemented in which dedicated classifiers learn to recognize the patterns of obvious false-positive subtypes that occur most frequently. The method is compared to a conventional two-class approach, where all false-positive subtypes are grouped together in one class, and to the baseline CADe system without the new false-positive removal step. The methods are evaluated on an independent dataset containing 1,542 screening examinations of which 80 examinations contain malignant microcalcifications. Analysis showed that the multiclass approach yielded a significantly higher sensitivity compared to the other two methods (P < 0.0002). At one obvious false positive per 100 images, the baseline CADe system detected 61% of the malignant examinations, while the systems with the two-class and multiclass false-positive reduction step detected 73% and 83%, respectively. Our study showed that by adding the proposed method to a CADe system, the number of obvious false positives can decrease significantly (P < 0.0002). © 2017 American Association of Physicists in Medicine.

A deep-learning based automatic pulmonary nodule detection system

NASA Astrophysics Data System (ADS)

Zhao, Yiyuan; Zhao, Liang; Yan, Zhennan; Wolf, Matthias; Zhan, Yiqiang

2018-02-01

Lung cancer is the deadliest cancer worldwide. Early detection of lung cancer is a promising way to lower the risk of dying. Accurate pulmonary nodule detection in computed tomography (CT) images is crucial for early diagnosis of lung cancer. The development of computer-aided detection (CAD) system of pulmonary nodules contributes to making the CT analysis more accurate and with more efficiency. Recent studies from other groups have been focusing on lung cancer diagnosis CAD system by detecting medium to large nodules. However, to fully investigate the relevance between nodule features and cancer diagnosis, a CAD that is capable of detecting nodules with all sizes is needed. In this paper, we present a deep-learning based automatic all size pulmonary nodule detection system by cascading two artificial neural networks. We firstly use a U-net like 3D network to generate nodule candidates from CT images. Then, we use another 3D neural network to refine the locations of the nodule candidates generated from the previous subsystem. With the second sub-system, we bring the nodule candidates closer to the center of the ground truth nodule locations. We evaluate our system on a public CT dataset provided by the Lung Nodule Analysis (LUNA) 2016 grand challenge. The performance on the testing dataset shows that our system achieves 90% sensitivity with an average of 4 false positives per scan. This indicates that our system can be an aid for automatic nodule detection, which is beneficial for lung cancer diagnosis.

Building capacity for skilled birth attendance: An evaluation of the Maternal and Child Health Aides training programme in Sierra Leone.

PubMed

Jones, Susan; Ameh, Charles A; Gopalakrishnan, Somasundari; Sam, Betty; Bull, Florence; Labicane, Roderick R; Dabo, Fatmata; van den Broek, Nynke

2015-12-01

Maternal and Child Health Aides (MCH Aide) in Sierra Leone provide the majority of maternity services at primary care level. To formulate recommendations for improving the quality and scale-up of MCH Aides training an evaluation of all schools across Sierra Leone was undertaken. Structured, direct observation of two randomly selected teaching sessions per school using pre-tested standardised review forms. Event sampling with random selection of timetabled sessions across all 14 MCH Aide Training Schools. All MCH Aide training schools across Sierra Leone. Tutors across 14 MCH Aide training schools observed in August 2013. Assessment of four key elements of teaching and learning: (1) teaching style, (2) use of visual aids, (3) teaching environment and (4) student involvement. In the majority of teaching schools there was over-crowding (11/14), lack of furniture and inconsistent electricity supply. Ten of 26 tutors used lesson plans and teaching was mostly tutor- rather than student-focused. Majority of tutors use a didactic approach rather than active learning methods. Teaching aides were rarely available (15% of lessons). Tutors were knowledgeable in their subject area and there was evidence of an excellent tutor-student relationship. Training for Maternal and Child health Aides relies on teacher focused didactic methods, which may hinder student learning. Teaching and learning within the schools needs to be enhanced by a combination of tutor development and improvements in the learning environment. Interventions to improve the quality of teaching are urgently needed and should include training on teaching techniques and student assessment for tutors, provision of audio visual equipment and teaching aides such as posters and mannequins. Monitoring and Evaluation of interventions is critical to be able to amend the programmes approach and address further challenges at an early stage. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Key points for esthetic rehabilitation of anterior teeth using chair-side computer aided design and computer aided manufacture technique].

PubMed

Yang, J; Feng, H L

2018-04-09

With the rapid development of the chair-side computer aided design and computer aided manufacture (CAD/CAM) technology, its accuracy and operability of have been greatly improved in recent years. Chair-side CAD/CAM system may produce all kinds of indirect restorations, and has the advantages of rapid, accurate and stable production. It has become the future development direction of Stomatology. This paper describes the clinical application of the chair-side CAD/CAM technology for anterior aesthetic restorations from the aspects of shade and shape.

[Clinical skills and outcomes of chair-side computer aided design and computer aided manufacture system].

PubMed

Yu, Q

2018-04-09

Computer aided design and computer aided manufacture (CAD/CAM) technology is a kind of oral digital system which is applied to clinical diagnosis and treatment. It overturns the traditional pattern, and provides a solution to restore defect tooth quickly and efficiently. In this paper we mainly discuss the clinical skills of chair-side CAD/CAM system, including tooth preparation, digital impression, the three-dimensional design of prosthesis, numerical control machining, clinical bonding and so on, and review the outcomes of several common kinds of materials at the same time.

Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

PubMed

De Looze, Céline; Beausang, Alan; Cryan, Jane; Loftus, Teresa; Buckley, Patrick G; Farrell, Michael; Looby, Seamus; Reilly, Richard; Brett, Francesca; Kearney, Hugh

2018-05-16

Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a glioma. The aim of this study is to devise a machine learning algorithm that may be used by radiologists in routine practice to aid diagnosis of both: WHO grade and IDH mutation status in de novo gliomas. To evaluate the status quo, we interrogated the accuracy of neuroradiology reports in relation to WHO grade: grade II 96.49% (95% confidence intervals [CI] 0.88, 0.99); III 36.51% (95% CI 0.24, 0.50); IV 72.9% (95% CI 0.67, 0.78). We derived five MRI parameters from the same diagnostic brain scans, in under two minutes per case, and then supplied these data to a random forest algorithm. Machine learning resulted in a high level of accuracy in prediction of tumour grade: grade II/III; area under the receiver operating characteristic curve (AUC) = 98%, sensitivity = 0.82, specificity = 0.94; grade II/IV; AUC = 100%, sensitivity = 1.0, specificity = 1.0; grade III/IV; AUC = 97%, sensitivity = 0.83, specificity = 0.97. Furthermore, machine learning also facilitated the discrimination of IDH status: AUC of 88%, sensitivity = 0.81, specificity = 0.77. These data demonstrate the ability of machine learning to accurately classify diffuse gliomas by both WHO grade and IDH status from routine MRI alone-without significant image processing, which may facilitate usage as a diagnostic adjunct in clinical practice.

Petascale supercomputing to accelerate the design of high-temperature alloys

DOE PAGES

Shin, Dongwon; Lee, Sangkeun; Shyam, Amit; ...

2017-10-25

Recent progress in high-performance computing and data informatics has opened up numerous opportunities to aid the design of advanced materials. Herein, we demonstrate a computational workflow that includes rapid population of high-fidelity materials datasets via petascale computing and subsequent analyses with modern data science techniques. We use a first-principles approach based on density functional theory to derive the segregation energies of 34 microalloying elements at the coherent and semi-coherent interfaces between the aluminium matrix and the θ'-Al 2Cu precipitate, which requires several hundred supercell calculations. We also perform extensive correlation analyses to identify materials descriptors that affect the segregation behaviourmore » of solutes at the interfaces. Finally, we show an example of leveraging machine learning techniques to predict segregation energies without performing computationally expensive physics-based simulations. As a result, the approach demonstrated in the present work can be applied to any high-temperature alloy system for which key materials data can be obtained using high-performance computing.« less

Petascale supercomputing to accelerate the design of high-temperature alloys

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

Shin, Dongwon; Lee, Sangkeun; Shyam, Amit

Recent progress in high-performance computing and data informatics has opened up numerous opportunities to aid the design of advanced materials. Herein, we demonstrate a computational workflow that includes rapid population of high-fidelity materials datasets via petascale computing and subsequent analyses with modern data science techniques. We use a first-principles approach based on density functional theory to derive the segregation energies of 34 microalloying elements at the coherent and semi-coherent interfaces between the aluminium matrix and the θ'-Al 2Cu precipitate, which requires several hundred supercell calculations. We also perform extensive correlation analyses to identify materials descriptors that affect the segregation behaviourmore » of solutes at the interfaces. Finally, we show an example of leveraging machine learning techniques to predict segregation energies without performing computationally expensive physics-based simulations. As a result, the approach demonstrated in the present work can be applied to any high-temperature alloy system for which key materials data can be obtained using high-performance computing.« less

Petascale supercomputing to accelerate the design of high-temperature alloys

NASA Astrophysics Data System (ADS)

Shin, Dongwon; Lee, Sangkeun; Shyam, Amit; Haynes, J. Allen

2017-12-01

Recent progress in high-performance computing and data informatics has opened up numerous opportunities to aid the design of advanced materials. Herein, we demonstrate a computational workflow that includes rapid population of high-fidelity materials datasets via petascale computing and subsequent analyses with modern data science techniques. We use a first-principles approach based on density functional theory to derive the segregation energies of 34 microalloying elements at the coherent and semi-coherent interfaces between the aluminium matrix and the θ‧-Al2Cu precipitate, which requires several hundred supercell calculations. We also perform extensive correlation analyses to identify materials descriptors that affect the segregation behaviour of solutes at the interfaces. Finally, we show an example of leveraging machine learning techniques to predict segregation energies without performing computationally expensive physics-based simulations. The approach demonstrated in the present work can be applied to any high-temperature alloy system for which key materials data can be obtained using high-performance computing.

The Abnormal vs. Normal ECG Classification Based on Key Features and Statistical Learning

NASA Astrophysics Data System (ADS)

Dong, Jun; Tong, Jia-Fei; Liu, Xia

As cardiovascular diseases appear frequently in modern society, the medicine and health system should be adjusted to meet the new requirements. Chinese government has planned to establish basic community medical insurance system (BCMIS) before 2020, where remote medical service is one of core issues. Therefore, we have developed the "remote network hospital system" which includes data server and diagnosis terminal by the aid of wireless detector to sample ECG. To improve the efficiency of ECG processing, in this paper, abnormal vs. normal ECG classification approach based on key features and statistical learning is presented, and the results are analyzed. Large amount of normal ECG could be filtered by computer automatically and abnormal ECG is left to be diagnosed specially by physicians.

[Investigation on level and influencing factors of first aid knowledge among dentists in Sichuan province].

PubMed

Qiu, Yu; Li, Yuan-Yuan; Li, Tian-Guo; Chen, Yi-Ge; Kong, Jing-Jun; Pan, Jian

2018-04-01

The study aims to investigate the cognition degree and influencing factors of first aid knowledge among dentists in Sichuan province, and to provide suggestions for the training of oral clinician. A questionnaire was designed for this study. It included the basic situation of population, first aid knowledge level, emergency situation often encountered in stomatology clinic, first aid training situation, learning approach and attitude of first aid knowledge, etc. This questionnaire was used to investigate the dentists of medical institutions in various cities in Sichuan province. The survey results was statistical analyzed. There were 245 valid questionnaires. 1) The level of first aid knowledge of dentists was generally lower in Sichuan province. Work department and other departments work experience were the influencing factors of knowledge level of first aid knowledge among dentists. 2) 87.3% of dentists believed that it was very necessary to master the knowledge of first aid, but in the event of an emergency situation, 73.5% of dentists only can find other doctors to guide themselves to help. 3) The most common way to learn first aid knowledge was through work experience and medical school's first aid course. Dentists should strengthen the learning and training to improve the first aid skill.

Machine Learning in Computer-Aided Synthesis Planning.

PubMed

Coley, Connor W; Green, William H; Jensen, Klavs F

2018-05-15

Computer-aided synthesis planning (CASP) is focused on the goal of accelerating the process by which chemists decide how to synthesize small molecule compounds. The ideal CASP program would take a molecular structure as input and output a sorted list of detailed reaction schemes that each connect that target to purchasable starting materials via a series of chemically feasible reaction steps. Early work in this field relied on expert-crafted reaction rules and heuristics to describe possible retrosynthetic disconnections and selectivity rules but suffered from incompleteness, infeasible suggestions, and human bias. With the relatively recent availability of large reaction corpora (such as the United States Patent and Trademark Office (USPTO), Reaxys, and SciFinder databases), consisting of millions of tabulated reaction examples, it is now possible to construct and validate purely data-driven approaches to synthesis planning. As a result, synthesis planning has been opened to machine learning techniques, and the field is advancing rapidly. In this Account, we focus on two critical aspects of CASP and recent machine learning approaches to both challenges. First, we discuss the problem of retrosynthetic planning, which requires a recommender system to propose synthetic disconnections starting from a target molecule. We describe how the search strategy, necessary to overcome the exponential growth of the search space with increasing number of reaction steps, can be assisted through a learned synthetic complexity metric. We also describe how the recursive expansion can be performed by a straightforward nearest neighbor model that makes clever use of reaction data to generate high quality retrosynthetic disconnections. Second, we discuss the problem of anticipating the products of chemical reactions, which can be used to validate proposed reactions in a computer-generated synthesis plan (i.e., reduce false positives) to increase the likelihood of experimental success. While we introduce this task in the context of reaction validation, its utility extends to the prediction of side products and impurities, among other applications. We describe neural network-based approaches that we and others have developed for this forward prediction task that can be trained on previously published experimental data. Machine learning and artificial intelligence have revolutionized a number of disciplines, not limited to image recognition, dictation, translation, content recommendation, advertising, and autonomous driving. While there is a rich history of using machine learning for structure-activity models in chemistry, it is only now that it is being successfully applied more broadly to organic synthesis and synthesis design. As reported in this Account, machine learning is rapidly transforming CASP, but there are several remaining challenges and opportunities, many pertaining to the availability and standardization of both data and evaluation metrics, which must be addressed by the community at large.

Lesion classification using clinical and visual data fusion by multiple kernel learning

NASA Astrophysics Data System (ADS)

Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf

2014-03-01

To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.

Machine learning and radiology.

PubMed

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Smartphone-Based System for Learning and Inferring Hearing Aid Settings.

PubMed

Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J

2016-10-01

Previous research has shown that hearing aid wearers can successfully self-train their instruments' gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the "untrained system," that is, the manufacturer's algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The "trained system" first learned each individual's preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. An experimental within-participants study. Participants used a prototype hearing system-comprising two hearing aids, Android smartphone, and body-worn gateway device-for ∼6 weeks. Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Participants were fitted and instructed to perform daily comparisons of settings ("listening evaluations") through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase, HALIC recorded individual listening preferences along with sensor data from the smartphone-including environmental sound classification, sound level, and location-to build trained models. In the subsequent two-week-long validation phase, participants performed blinded listening evaluations comparing settings predicted by the trained system ("trained settings") to those suggested by the hearing aids' untrained system ("untrained settings"). We analyzed data collected on the smartphone and hearing aids during the study. We also obtained audiometric and demographic information. Overall, the 15 participants with valid data significantly preferred trained settings to untrained settings (paired-samples t test). Seven participants had a significant preference for trained settings, while one had a significant preference for untrained settings (binomial test). The remaining seven participants had nonsignificant preferences. Pooling data across participants, the proportion of times that each setting was chosen in a given environmental sound class was on average very similar. However, breaking down the data by participant revealed strong and idiosyncratic individual preferences. Fourteen participants reported positive feelings of clarity, competence, and mastery when training via HALIC. The obtained data, as well as subjective participant feedback, indicate that smartphones could become viable tools to train hearing aids. Individuals who are tech savvy and have milder HL seem well suited to take advantages of the benefits offered by training with a smartphone. American Academy of Audiology

Enhancing Engineering Computer-Aided Design Education Using Lectures Recorded on the PC

ERIC Educational Resources Information Center

McGrann, Roy T. R.

2006-01-01

Computer-Aided Engineering (CAE) is a course that is required during the third year in the mechanical engineering curriculum at Binghamton University. The primary objective of the course is to educate students in the procedures of computer-aided engineering design. The solid modeling and analysis program Pro/Engineer[TM] (PTC[R]) is used as the…

Key Issues in Instructional Computer Graphics.

ERIC Educational Resources Information Center

Wozny, Michael J.

1981-01-01

Addresses key issues facing universities which plan to establish instructional computer graphics facilities, including computer-aided design/computer aided manufacturing systems, role in curriculum, hardware, software, writing instructional software, faculty involvement, operations, and research. Thirty-seven references and two appendices are…

AIDS: What Young Adults Should Know. Instructor's Guide and Student Guide.

ERIC Educational Resources Information Center

Yarber, William L.

This curriculum allows students to learn about Acquired Immune Deficiency Syndrome (AIDS) at their own pace. The Instructor's manual presents the goals of AIDS education in a three-session lesson plan. The manual also outlines eight learning opportunities to reinforce in students the personal health behaviors and attitudes emphasized in the guide.…

A Model Human Sexuality--HIV/AIDS Prevention and Intervention Service-Learning Program

ERIC Educational Resources Information Center

Stewart, Clarence, M., Jr.

2005-01-01

This article deals with a service-learning program focused on human sexuality and HIV/AIDS prevention and intervention at the Howard University Department of Health, Human Performance and Leisure Studies. Topics discussed include how this program was created, an overview of peer education, HIV/AIDS peer education training, and services provided to…

Nurses' perceptions of online continuing education

PubMed Central

2011-01-01

Background There is increasing attention to online learning as a convenient way of getting professional training. The number and popularity of online nursing continuing education programs are increasing rapidly in many countries. Understanding these may contribute to designing these programs to maximize success. Also, knowing the perceptions and preferences in online learning aids development and orientation of online programs. The aims of this study are to show nurses' perceptions of online continuing education and to determine perceptions of various groups; area groups, working companies, frequency of computer usage and age. Methods The survey method was used in this quantitative study to reveal perception levels and relationship with related variables. Data were collected through an online instrument from a convenience sample of 1041 Registered Nurses (RNs) at an online bachelor's degree program. Descriptive and inferential analysis techniques were performed. Results Nurses generally have positive perceptions about online learning (X = 3.86; SD = 0.48). A significant difference was seen between nurses who used computers least and those with the highest computer usage [F (3, 1033) = 3.040; P < .05]. Neither nurses' ages nor lengths of working experience are significantly related to perceptions of online programs (r = -.013; P > .05 and r = -.036; P > .05, respectively). Nurses' perceptions are significantly different depending on the settings where they work [F (3,989) = 3.193; P < .05]. The difference between perceptions of nurses living in urban areas (X = 3.82; SD = .51) and those living in rural areas (X = 3.88; SD = .47) was not significant [t (994) = -1.570, P > .05]. Conclusions We found that nurses regard online learning opportunities as suitable for their working conditions and needs. Nurses should be provided with continued training through online learning alternatives, regardless of age, working experience or area of residence. PMID:22013974

Computer Programming Languages and Expertise Needed by Practicing Engineers.

ERIC Educational Resources Information Center

Doelling, Irvin

1980-01-01

Discussed is the present engineering computer environment of a large aerospace company recognized as a leader in the application and development of computer-aided design and computer-aided manufacturing techniques. A review is given of the exposure spectrum of engineers to the world of computing, the computer languages used, and the career impacts…

Multi-Instance Learning Models for Automated Support of Analysts in Simulated Surveillance Environments

NASA Technical Reports Server (NTRS)

Birisan, Mihnea; Beling, Peter

2011-01-01

New generations of surveillance drones are being outfitted with numerous high definition cameras. The rapid proliferation of fielded sensors and supporting capacity for processing and displaying data will translate into ever more capable platforms, but with increased capability comes increased complexity and scale that may diminish the usefulness of such platforms to human operators. We investigate methods for alleviating strain on analysts by automatically retrieving content specific to their current task using a machine learning technique known as Multi-Instance Learning (MIL). We use MIL to create a real time model of the analysts' task and subsequently use the model to dynamically retrieve relevant content. This paper presents results from a pilot experiment in which a computer agent is assigned analyst tasks such as identifying caravanning vehicles in a simulated vehicle traffic environment. We compare agent performance between MIL aided trials and unaided trials.

Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.

PubMed

Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M

2012-05-01

In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.

Seeing is Believing: Video Classification for Computed Tomographic Colonography Using Multiple-Instance Learning

PubMed Central

Wang, Shijun; McKenna, Matthew T.; Nguyen, Tan B.; Burns, Joseph E.; Petrick, Nicholas; Sahiner, Berkman

2012-01-01

In this paper we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods. PMID:22552333

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer

NASA Astrophysics Data System (ADS)

Vandenberghe, Michel E.; Scott, Marietta L. J.; Scorer, Paul W.; Söderberg, Magnus; Balcerzak, Denis; Barker, Craig

2017-04-01

Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a computational approach based on deep learning that automatically scores HER2, a biomarker that defines patient eligibility for anti-HER2 targeted therapies in breast cancer. In a cohort of 71 breast tumour resection samples, automated scoring showed a concordance of 83% with a pathologist. The twelve discordant cases were then independently reviewed, leading to a modification of diagnosis from initial pathologist assessment for eight cases. Diagnostic discordance was found to be largely caused by perceptual differences in assessing HER2 expression due to high HER2 staining heterogeneity. This study provides evidence that deep learning aided diagnosis can facilitate clinical decision making in breast cancer by identifying cases at high risk of misdiagnosis.

Computer-aided detection systems to improve lung cancer early diagnosis: state-of-the-art and challenges

NASA Astrophysics Data System (ADS)

Traverso, A.; Lopez Torres, E.; Fantacci, M. E.; Cerello, P.

2017-05-01

Lung cancer is one of the most lethal types of cancer, because its early diagnosis is not good enough. In fact, the detection of pulmonary nodule, potential lung cancers, in Computed Tomography scans is a very challenging and time-consuming task for radiologists. To support radiologists, researchers have developed Computer-Aided Diagnosis (CAD) systems for the automated detection of pulmonary nodules in chest Computed Tomography scans. Despite the high level of technological developments and the proved benefits on the overall detection performance, the usage of Computer-Aided Diagnosis in clinical practice is far from being a common procedure. In this paper we investigate the causes underlying this discrepancy and present a solution to tackle it: the M5L WEB- and Cloud-based on-demand Computer-Aided Diagnosis. In addition, we prove how the combination of traditional imaging processing techniques with state-of-art advanced classification algorithms allows to build a system whose performance could be much larger than any Computer-Aided Diagnosis developed so far. This outcome opens the possibility to use the CAD as clinical decision support for radiologists.

Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

ERIC Educational Resources Information Center

Russell, Daniel M.; Pirolli, Peter

Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

A review of computer-aided oral and maxillofacial surgery: planning, simulation and navigation.

PubMed

Chen, Xiaojun; Xu, Lu; Sun, Yi; Politis, Constantinus

2016-11-01

Currently, oral and maxillofacial surgery (OMFS) still poses a significant challenge for surgeons due to the anatomic complexity and limited field of view of the oral cavity. With the great development of computer technologies, he computer-aided surgery has been widely used for minimizing the risks and improving the precision of surgery. Areas covered: The major goal of this paper is to provide a comprehensive reference source of current and future development of computer-aided OMFS including surgical planning, simulation and navigation for relevant researchers. Expert commentary: Compared with the traditional OMFS, computer-aided OMFS overcomes the disadvantage that the treatment on the region of anatomically complex maxillofacial depends almost exclusively on the experience of the surgeon.

Software For Computer-Aided Design Of Control Systems

NASA Technical Reports Server (NTRS)

Wette, Matthew

1994-01-01

Computer Aided Engineering System (CAESY) software developed to provide means to evaluate methods for dealing with users' needs in computer-aided design of control systems. Interpreter program for performing engineering calculations. Incorporates features of both Ada and MATLAB. Designed to be flexible and powerful. Includes internally defined functions, procedures and provides for definition of functions and procedures by user. Written in C language.

NREL Kicks Off Next Phase of Advanced Computer-Aided Battery Engineering |

Science.gov Websites

lithium-ion (Li-ion) batteries, known as a multi-scale multi-domain (GH-MSMD) model framework, was News | NREL Kicks Off Next Phase of Advanced Computer-Aided Battery Engineering NREL Kicks Off Next Phase of Advanced Computer-Aided Battery Engineering March 16, 2016 NREL researcher looks across

Defense Acquisitions Acronyms and Terms

DTIC Science & Technology

2012-12-01

Computer-Aided Design CADD Computer-Aided Design and Drafting CAE Component Acquisition Executive; Computer-Aided Engineering CAIV Cost As an...Radiation to Ordnance HFE Human Factors Engineering HHA Health Hazard Assessment HNA Host-Nation Approval HNS Host-Nation Support HOL High -Order...Engineering Change Proposal VHSIC Very High Speed Integrated Circuit VLSI Very Large Scale Integration VOC Volatile Organic Compound W WAN Wide

[The automatic iris map overlap technology in computer-aided iridiagnosis].

PubMed

He, Jia-feng; Ye, Hu-nian; Ye, Miao-yuan

2002-11-01

In the paper, iridology and computer-aided iridiagnosis technologies are briefly introduced and the extraction method of the collarette contour is then investigated. The iris map can be overlapped on the original iris image based on collarette contour extraction. The research on collarette contour extraction and iris map overlap is of great importance to computer-aided iridiagnosis technologies.

New Paradigms for Computer Aids to Invention.

ERIC Educational Resources Information Center

Langston, M. Diane

Many people are interested in computer aids to rhetorical invention and want to know how to evaluate an invention aid, what the criteria are for a good one, and how to assess the trade-offs involved in buying one product or another. The frame of reference for this evaluation is an "old paradigm," which treats the computer as if it were…

Multimedia Image Technology and Computer Aided Manufacturing Engineering Analysis

NASA Astrophysics Data System (ADS)

Nan, Song

2018-03-01

Since the reform and opening up, with the continuous development of science and technology in China, more and more advanced science and technology have emerged under the trend of diversification. Multimedia imaging technology, for example, has a significant and positive impact on computer aided manufacturing engineering in China. From the perspective of scientific and technological advancement and development, the multimedia image technology has a very positive influence on the application and development of computer-aided manufacturing engineering, whether in function or function play. Therefore, this paper mainly starts from the concept of multimedia image technology to analyze the application of multimedia image technology in computer aided manufacturing engineering.

Usability and User Satisfaction of Multimedia Instructional Message (MIM) for Packet Tracer Simulation

ERIC Educational Resources Information Center

Elias, Mohd Syahrizad; Mohamad Ali, Ahmad Zamzuri

2016-01-01

Simulation-aided learning has capability in improving student's learning performance. However, the positive effect of simulation-aided learning still being discussed, which at times has not played the purported role expected. To address these problems, Multimedia Instructional Message (MIM) appeared to be an essential supporting tool in ensuring…

Smartphones Usage in the Classrooms: Learning Aid or Interference?

ERIC Educational Resources Information Center

Anshari, Muhammad; Almunawar, Mohammad Nabil; Shahrill, Masitah; Wicaksono, Danang Kuncoro; Huda, Miftachul

2017-01-01

Many educational institutions, especially higher education institutions, are considering to embrace smartphones as part of learning aids in classes as most students (in many cases all students) not only own them but also are also attached to them. The main question is whether embracing smartphones in classroom teaching enhances the learning or…

The Film as Visual Aided Learning Tool in Classroom Management Course

ERIC Educational Resources Information Center

Altinay Gazi, Zehra; Altinay Aksal, Fahriye

2011-01-01

This research aims to investigate the impact of the visual aided learning on pre-service teachers' co-construction of subject matter knowledge in teaching practice. The study revealed the examination of film as an active cognizing and learning tool in classroom management course within teacher education programme. Within the framework of action…

Three-Dimensional Computational Fluid Dynamics

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

Haworth, D.C.; O'Rourke, P.J.; Ranganathan, R.

1998-09-01

Computational fluid dynamics (CFD) is one discipline falling under the broad heading of computer-aided engineering (CAE). CAE, together with computer-aided design (CAD) and computer-aided manufacturing (CAM), comprise a mathematical-based approach to engineering product and process design, analysis and fabrication. In this overview of CFD for the design engineer, our purposes are three-fold: (1) to define the scope of CFD and motivate its utility for engineering, (2) to provide a basic technical foundation for CFD, and (3) to convey how CFD is incorporated into engineering product and process design.

Computer Aided Manufacturing.

ERIC Educational Resources Information Center

Insolia, Gerard

This document contains course outlines in computer-aided manufacturing developed for a business-industry technology resource center for firms in eastern Pennsylvania by Northampton Community College. The four units of the course cover the following: (1) introduction to computer-assisted design (CAD)/computer-assisted manufacturing (CAM); (2) CAM…

Buying CAM.

ERIC Educational Resources Information Center

Meloy, Jim; And Others

1990-01-01

The relationship between computer-aided design (CAD), computer-aided manufacturing (CAM), and computer numerical control (CNC) computer applications is described. Tips for helping educate the CAM buyer on what to look for and what to avoid when searching for the most appropriate instructional CAM package are provided. (KR)

Computer-Aided Design and Computer-Aided Manufacturing Hydroxyapatite/Epoxide Acrylate Maleic Compound Construction for Craniomaxillofacial Bone Defects.

PubMed

Zhang, Lei; Shen, Shunyao; Yu, Hongbo; Shen, Steve Guofang; Wang, Xudong

2015-07-01

The aim of this study was to investigate the use of computer-aided design and computer-aided manufacturing hydroxyapatite (HA)/epoxide acrylate maleic (EAM) compound construction artificial implants for craniomaxillofacial bone defects. Computed tomography, computer-aided design/computer-aided manufacturing and three-dimensional reconstruction, as well as rapid prototyping were performed in 12 patients between 2008 and 2013. The customized HA/EAM compound artificial implants were manufactured through selective laser sintering using a rapid prototyping machine into the exact geometric shapes of the defect. The HA/EAM compound artificial implants were then implanted during surgical reconstruction. Color-coded superimpositions demonstrated the discrepancy between the virtual plan and achieved results using Geomagic Studio. As a result, the HA/EAM compound artificial bone implants were perfectly matched with the facial areas that needed reconstruction. The postoperative aesthetic and functional results were satisfactory. The color-coded superimpositions demonstrated good consistency between the virtual plan and achieved results. The three-dimensional maximum deviation is 2.12 ± 0.65  mm and the three-dimensional mean deviation is 0.27 ± 0.07  mm. No facial nerve weakness or pain was observed at the follow-up examinations. Only 1 implant had to be removed 2 months after the surgery owing to severe local infection. No other complication was noted during the follow-up period. In conclusion, computer-aided, individually fabricated HA/EAM compound construction artificial implant was a good craniomaxillofacial surgical technique that yielded improved aesthetic results and functional recovery after reconstruction.

Effect of HIV/AIDS on Children's Attitudes toward Learning: Voices of Teachers and Caregivers in Western Kenya

ERIC Educational Resources Information Center

Jepkemboi, Grace; Aldridge, Jerry

2014-01-01

The well-being of children orphaned by HIV/AIDS is often significantly compromised, as they are prone to discrimination, victimization, and exclusion from social and familial structures. The present study examines the effect of HIV/AIDS on children's attitudes toward learning, as perceived by teachers and caregivers. Teachers and caregivers from…

Intelligent hearing aids: the next revolution.

PubMed

Tao Zhang; Mustiere, Fred; Micheyl, Christophe

2016-08-01

The first revolution in hearing aids came from nonlinear amplification, which allows better compensation for both soft and loud sounds. The second revolution stemmed from the introduction of digital signal processing, which allows better programmability and more sophisticated algorithms. The third revolution in hearing aids is wireless, which allows seamless connectivity between a pair of hearing aids and with more and more external devices. Each revolution has fundamentally transformed hearing aids and pushed the entire industry forward significantly. Machine learning has received significant attention in recent years and has been applied in many other industries, e.g., robotics, speech recognition, genetics, and crowdsourcing. We argue that the next revolution in hearing aids is machine intelligence. In fact, this revolution is already quietly happening. We will review the development in at least three major areas: applications of machine learning in speech enhancement; applications of machine learning in individualization and customization of signal processing algorithms; applications of machine learning in improving the efficiency and effectiveness of clinical tests. With the advent of the internet of things, the above developments will accelerate. This revolution will bring patient satisfactions to a new level that has never been seen before.

Accuracy evaluation of metal copings fabricated by computer-aided milling and direct metal laser sintering systems

PubMed Central

Lee, Wan-Sun; Kim, Woong-Chul

2015-01-01

PURPOSE To assess the marginal and internal gaps of the copings fabricated by computer-aided milling and direct metal laser sintering (DMLS) systems in comparison to casting method. MATERIALS AND METHODS Ten metal copings were fabricated by casting, computer-aided milling, and DMLS. Seven mesiodistal and labiolingual positions were then measured, and each of these were divided into the categories; marginal gap (MG), cervical gap (CG), axial wall at internal gap (AG), and incisal edge at internal gap (IG). Evaluation was performed by a silicone replica technique. A digital microscope was used for measurement of silicone layer. Statistical analyses included one-way and repeated measure ANOVA to test the difference between the fabrication methods and categories of measured points (α=.05), respectively. RESULTS The mean gap differed significantly with fabrication methods (P<.001). Casting produced the narrowest gap in each of the four measured positions, whereas CG, AG, and IG proved narrower in computer-aided milling than in DMLS. Thus, with the exception of MG, all positions exhibited a significant difference between computer-aided milling and DMLS (P<.05). CONCLUSION Although the gap was found to vary with fabrication methods, the marginal and internal gaps of the copings fabricated by computer-aided milling and DMLS fell within the range of clinical acceptance (<120 µm). However, the statistically significant difference to conventional casting indicates that the gaps in computer-aided milling and DMLS fabricated restorations still need to be further reduced. PMID:25932310

Accuracy evaluation of metal copings fabricated by computer-aided milling and direct metal laser sintering systems.

PubMed

Park, Jong-Kyoung; Lee, Wan-Sun; Kim, Hae-Young; Kim, Woong-Chul; Kim, Ji-Hwan

2015-04-01

To assess the marginal and internal gaps of the copings fabricated by computer-aided milling and direct metal laser sintering (DMLS) systems in comparison to casting method. Ten metal copings were fabricated by casting, computer-aided milling, and DMLS. Seven mesiodistal and labiolingual positions were then measured, and each of these were divided into the categories; marginal gap (MG), cervical gap (CG), axial wall at internal gap (AG), and incisal edge at internal gap (IG). Evaluation was performed by a silicone replica technique. A digital microscope was used for measurement of silicone layer. Statistical analyses included one-way and repeated measure ANOVA to test the difference between the fabrication methods and categories of measured points (α=.05), respectively. The mean gap differed significantly with fabrication methods (P<.001). Casting produced the narrowest gap in each of the four measured positions, whereas CG, AG, and IG proved narrower in computer-aided milling than in DMLS. Thus, with the exception of MG, all positions exhibited a significant difference between computer-aided milling and DMLS (P<.05). Although the gap was found to vary with fabrication methods, the marginal and internal gaps of the copings fabricated by computer-aided milling and DMLS fell within the range of clinical acceptance (<120 µm). However, the statistically significant difference to conventional casting indicates that the gaps in computer-aided milling and DMLS fabricated restorations still need to be further reduced.

The Design and Production of a Procedure Training Aid Using the Procedure Learning Format and the Computer Automated Page Layout (PLA) Routine.

DTIC Science & Technology

1983-12-01

AS REnITIR 6. Rotarywing.hea ...... ................ ..... cRR( PnPR mOVmIENT 7. Drop tank pumps and indicators (SH--3H...POSE the rotor head. 9. ACTION: Watch forn Captain_ fr sigPlan Catain.lean 10. RESPONSE: Stycycin contrl andk checks for__retonse clea and the____...cyclic forward and to the left ’- and slowly pump te collec z v. 2. RESPONSE: watch for 1/8 revolution of rotary wing- 1. ACTION: Check head area clear1

Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections

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

Morton, April M; Omitaomu, Olufemi A; Kotikot, Susan

A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.

A learning apprentice for software parts composition

NASA Technical Reports Server (NTRS)

Allen, Bradley P.; Holtzman, Peter L.

1987-01-01

An overview of the knowledge acquisition component of the Bauhaus, a prototype computer aided software engineering (CASE) workstation for the development of domain-specific automatic programming systems (D-SAPS) is given. D-SAPS use domain knowledge in the refinement of a description of an application program into a compilable implementation. The approach to the construction of D-SAPS was to automate the process of refining a description of a program, expressed in an object-oriented domain language, into a configuration of software parts that implement the behavior of the domain objects.

Financial Aid for Prior Learning Assessment: Early Successes and Lessons from the U.S. Department of Education's Experimental Sites Initiative

ERIC Educational Resources Information Center

Plumlee, Tucker; Klein-Collins, Rebecca

2017-01-01

In 2015, the U.S. Department of Labor invited postsecondary institutions to participate in an experiment to learn how federal financial aid might be used to cover the costs of prior learning assessment (PLA). PLA is the process of evaluating a student's prior workplace and experiential learning for academic credit. While the experiment is still…

Person Authentication Using Learned Parameters of Lifting Wavelet Filters

NASA Astrophysics Data System (ADS)

Niijima, Koichi

2006-10-01

This paper proposes a method for identifying persons by the use of the lifting wavelet parameters learned by kurtosis-minimization. Our learning method uses desirable properties of kurtosis and wavelet coefficients of a facial image. Exploiting these properties, the lifting parameters are trained so as to minimize the kurtosis of lifting wavelet coefficients computed for the facial image. Since this minimization problem is an ill-posed problem, it is solved by the aid of Tikhonov's regularization method. Our learning algorithm is applied to each of the faces to be identified to generate its feature vector whose components consist of the learned parameters. The constructed feature vectors are memorized together with the corresponding faces in a feature vectors database. Person authentication is performed by comparing the feature vector of a query face with those stored in the database. In numerical experiments, the lifting parameters are trained for each of the neutral faces of 132 persons (74 males and 58 females) in the AR face database. Person authentication is executed by using the smile and anger faces of the same persons in the database.

Evolution of technology in teaching: Blackboard and beyond in Medical Education

PubMed Central

Mendis, Susirith; John, Lisha Jenny; Shanthakumari, Nisha; Sreedharan, Jayadevan; Shaikh, Rizwana B

2016-01-01

Teaching and learning the passing of knowledge from one generation to another - has been in existence from the earliest times of human civilization. It began in 1801, with a large piece of slate hung on the wall in a school in Scotland to provide information to a large audience at one time. In the US by mid-19th century, every class room had a blackboard to teach students. The modern version of the blackboard is either green or brown board. This was introduced in late 1960s. The whiteboards came into use during the late 1980s. Projected aids have been used since 1420. The various devices used are the epidiascope, slide projector, overhead projector for transparencies and the micro projector. An instrument to project images from a horizontal surface onto a vertical screen was invented in the 1870s. By the 1960s, transparencies were in use in classrooms. The ‘Hyalotype’, a transparent image of a photograph using actual black and white photographs on a glass slide that could be projected was invented in 1851. By 1916, the German company Agfa started producing colored lantern slides. The first version of PowerPoint was released by Microsoft in the year 1990. Cell phones, palmtops, and handheld computers; tablets, laptops, and media players are included under mobile learning devices. With the evolution of technology, students achieved competence and interested in interactive learning. The education industry has moved from distance learning to e-learning and finally to m-learning as knowledge expanded exponentially and the demand escalated. While using teaching aids with advanced technology, we must not forget the lessons from the past, striking a balance between embracing new methods of teaching and learning while upholding the timeless principles of education. The newer educational technology can be part of a comprehensive system for lifelong education. Conclusion: Use of technology in education has come a long way since the earliest times of human civilization. While embarking on aids with advanced technology, we need to take full cognizance of the lessons from the past, striking a balance between embracing new methods of teaching and learning while holding on to the timeless principles of education. Thus, the newer educational technology can be effective tools of teaching and learning in this rapidly changing technological world and be part of a comprehensive system for lifelong education. Acknowledgements: The authors wish to acknowledge Prof. Raja Bandaranayake for his valuable suggestions and editing this manuscript. PMID:27822404

A Review of Developments in Computer-Based Systems to Image Teeth and Produce Dental Restorations

PubMed Central

Rekow, E. Dianne; Erdman, Arthur G.; Speidel, T. Michael

1987-01-01

Computer-aided design and manufacturing (CAD/CAM) make it possible to automate the creation of dental restorations. Currently practiced techniques are described. Three automated systems currently under development are described and compared. Advances in computer-aided design and computer-aided manufacturing (CAD/CAM) provide a new option for dentistry, creating an alternative technique for producing dental restorations. It is possible to create dental restorations that are automatically produced and meet or exceed current requirements for fit and occlusion.

Photogrammetry and computer-aided piping design

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

Keneflick, J.F.; Chirillo, R.D.

1985-02-18

Three-dimensional measurements taken from photographs of a plant model can be digitized and linked with computer-aided piping design. This can short-cut the design and construction of new plants and expedite repair and retrofitting projects. Some designers bridge the gap between model and computer by digitizing from orthographic prints obtained via orthography or the laser scanning of model sections. Such valve or fitting then processed is described in this paper. The marriage of photogrammetry and computer-aided piping design can economically produce such numerical drawings.

Integration of the Execution Support System for the Computer-Aided Prototyping System (CAPS)

DTIC Science & Technology

1990-09-01

SUPPORT SYSTEM FOR THE COMPUTER -AIDED PROTOTYPING SYSTEM (CAPS) by Frank V. Palazzo September 1990 Thesis Advisor: Luq± Approved for public release...ZATON REPOR ,,.VBE (, 6a NAME OF PERPORMING ORGAN ZAT7ON 6b OFF:CE SYVBOL 7a NAME OF MONITORINC O0-CA’Za- ON Computer Science Department (if applicable...Include Security Classification) Integration of the Execution Support System for the Computer -Aided Prototyping System (C S) 12 PERSONAL AUTHOR(S) Frank V

Influence of Computer-Aided Detection on Performance of Screening Mammography

PubMed Central

Fenton, Joshua J.; Taplin, Stephen H.; Carney, Patricia A.; Abraham, Linn; Sickles, Edward A.; D'Orsi, Carl; Berns, Eric A.; Cutter, Gary; Hendrick, R. Edward; Barlow, William E.; Elmore, Joann G.

2011-01-01

Background Computer-aided detection identifies suspicious findings on mammograms to assist radiologists. Since the Food and Drug Administration approved the technology in 1998, it has been disseminated into practice, but its effect on the accuracy of interpretation is unclear. Methods We determined the association between the use of computer-aided detection at mammography facilities and the performance of screening mammography from 1998 through 2002 at 43 facilities in three states. We had complete data for 222,135 women (a total of 429,345 mammograms), including 2351 women who received a diagnosis of breast cancer within 1 year after screening. We calculated the specificity, sensitivity, and positive predictive value of screening mammography with and without computer-aided detection, as well as the rates of biopsy and breast-cancer detection and the overall accuracy, measured as the area under the receiver-operating-characteristic (ROC) curve. Results Seven facilities (16%) implemented computer-aided detection during the study period. Diagnostic specificity decreased from 90.2% before implementation to 87.2% after implementation (P<0.001), the positive predictive value decreased from 4.1% to 3.2% (P = 0.01), and the rate of biopsy increased by 19.7% (P<0.001). The increase in sensitivity from 80.4% before implementation of computer-aided detection to 84.0% after implementation was not significant (P = 0.32). The change in the cancer-detection rate (including invasive breast cancers and ductal carcinomas in situ) was not significant (4.15 cases per 1000 screening mammograms before implementation and 4.20 cases after implementation, P = 0.90). Analyses of data from all 43 facilities showed that the use of computer-aided detection was associated with significantly lower overall accuracy than was nonuse (area under the ROC curve, 0.871 vs. 0.919; P = 0.005). Conclusions The use of computer-aided detection is associated with reduced accuracy of interpretation of screening mammograms. The increased rate of biopsy with the use of computer-aided detection is not clearly associated with improved detection of invasive breast cancer. PMID:17409321

Redesigning the Quantum Mechanics Curriculum to Incorporate Problem Solving Using a Computer Algebra System

NASA Astrophysics Data System (ADS)

Roussel, Marc R.

1999-10-01

One of the traditional obstacles to learning quantum mechanics is the relatively high level of mathematical proficiency required to solve even routine problems. Modern computer algebra systems are now sufficiently reliable that they can be used as mathematical assistants to alleviate this difficulty. In the quantum mechanics course at the University of Lethbridge, the traditional three lecture hours per week have been replaced by two lecture hours and a one-hour computer-aided problem solving session using a computer algebra system (Maple). While this somewhat reduces the number of topics that can be tackled during the term, students have a better opportunity to familiarize themselves with the underlying theory with this course design. Maple is also available to students during examinations. The use of a computer algebra system expands the class of feasible problems during a time-limited exercise such as a midterm or final examination. A modern computer algebra system is a complex piece of software, so some time needs to be devoted to teaching the students its proper use. However, the advantages to the teaching of quantum mechanics appear to outweigh the disadvantages.

How Do Professional Learning Communities Aid and Hamper Professional Learning of Beginning Teachers Related to Differentiated Instruction?

ERIC Educational Resources Information Center

De Neve, Debbie; Devos, Geert

2017-01-01

Research has shown that adequate support from the school environment is necessary to help beginning teachers in applying differentiated instruction (DI), but how schools can aid in this process remains unclear. This qualitative study explores how professional learning communities (PLCs), an indicator of a supportive school environment, can enhance…

Learning to Learn: Lessons from a Collaboration

ERIC Educational Resources Information Center

Chadha, Anita

2017-01-01

E-learning has become one of the primary ways to deliver education around the globe. Research is keeping pace with the use of various techno-aids as educators evaluate how to effectively use these aids in an ever-changing e-classroom. Adding to this body of work, and in assessing the effectiveness of techno-tools, this study evaluates meaningful…

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Introduction of e-learning in dental radiology reveals significantly improved results in final examination.

PubMed

Meckfessel, Sandra; Stühmer, Constantin; Bormann, Kai-Hendrik; Kupka, Thomas; Behrends, Marianne; Matthies, Herbert; Vaske, Bernhard; Stiesch, Meike; Gellrich, Nils-Claudius; Rücker, Martin

2011-01-01

Because a traditionally instructed dental radiology lecture course is very time-consuming and labour-intensive, online courseware, including an interactive-learning module, was implemented to support the lectures. The purpose of this study was to evaluate the perceptions of students who have worked with web-based courseware as well as the effect on their results in final examinations. Users (n(3+4)=138) had access to the e-program from any networked computer at any time. Two groups (n(3)=71, n(4)=67) had to pass a final exam after using the e-course. Results were compared with two groups (n(1)=42, n(2)=48) who had studied the same content by attending traditional lectures. In addition a survey of the students was statistically evaluated. Most of the respondents reported a positive attitude towards e-learning and would have appreciated more access to computer-assisted instruction. Two years after initiating the e-course the failure rate in the final examination dropped significantly, from 40% to less than 2%. The very positive response to the e-program and improved test scores demonstrated the effectiveness of our e-course as a learning aid. Interactive modules in step with clinical practice provided learning that is not achieved by traditional teaching methods alone. To what extent staff savings are possible is part of a further study. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Investigating the Language of Engineering Education

NASA Astrophysics Data System (ADS)

Variawa, Chirag

A significant part of professional communication development in engineering is the ability to learn and understand technical vocabulary. Mastering such vocabulary is often a desired learning outcome of engineering education. In promoting this goal, this research investigates the development of a tool that creates wordlists of characteristic discipline-specific vocabulary for a given course. These wordlists explicitly highlight requisite vocabulary learning and, when used as a teaching aid, can promote greater accessibility in the learning environment. Literature, including work in higher education, diversity and language learning, suggest that designing accessible learning environments can increase the quality of instruction and learning for all students. Studying the student/instructor interface using the framework of Universal Instructional Design identified vocabulary learning as an invisible barrier in engineering education. A preliminary investigation of this barrier suggested that students have difficulty assessing their understanding of technical vocabulary. Subsequently, computing word frequency on engineering course material was investigated as an approach for characterizing this barrier. However, it was concluded that a more nuanced method was necessary. This research program was built on previous work in the fields of linguistics and computer science, and lead to the design of an algorithm. The developed algorithm is based on a statistical technique called, Term Frequency-Inverse Document Frequency. Comparator sets of documents are used to hierarchically identify characteristic terms on a target document, such as course materials from a previous term of study. The approach draws on a standardized artifact of the engineering learning environment as its dataset; a repository of 2254 engineering final exams from the University of Toronto, to process the target material. After producing wordlists for ten courses, with the goal of highlighting characteristic discipline-specific terms, the effectiveness of the approach was evaluated by comparing the computed results to the judgment of subject-matter experts. The overall data show a good correlation between the program and the subject-matter experts. The results indicated a balance between accuracy and feasibility, and suggested that this approach could mimic subject-matter expertise to create a list discipline-specific vocabulary from course materials.

Computer-assisted concept mapping: Visual aids for knowledge construction

PubMed Central

Mammen, Jennifer R.

2016-01-01

Background Concept mapping is a visual representation of ideas that facilitates critical thinking and is applicable to many areas of nursing education. Computer-Assisted Concept Maps are more flexible and less constrained than traditional paper methods, allowing for analysis and synthesis of complex topics and larger amounts of data. Ability to iteratively revise and collaboratively create computerized maps can contribute to enhanced interpersonal learning. However, there is limited awareness of free software that can support these types of applications. Discussion This educational brief examines affordances and limitations of Computer-Assisted Concept Maps and reviews free software for development of complex, collaborative malleable maps. Free software such as VUE, Xmind, MindMaple, and others can substantially contribute to utility of concept-mapping for nursing education. Conclusions Computerized concept-mapping is an important tool for nursing and is likely to hold greater benefit for students and faculty than traditional pen and paper methods alone. PMID:27351610

Modeling reality

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1990-01-01

Although powerful computers have allowed complex physical and manmade hardware systems to be modeled successfully, we have encountered persistent problems with the reliability of computer models for systems involving human learning, human action, and human organizations. This is not a misfortune; unlike physical and manmade systems, human systems do not operate under a fixed set of laws. The rules governing the actions allowable in the system can be changed without warning at any moment, and can evolve over time. That the governing laws are inherently unpredictable raises serious questions about the reliability of models when applied to human situations. In these domains, computers are better used, not for prediction and planning, but for aiding humans. Examples are systems that help humans speculate about possible futures, offer advice about possible actions in a domain, systems that gather information from the networks, and systems that track and support work flows in organizations.

Occupational risk identification using hand-held or laptop computers.

PubMed

Naumanen, Paula; Savolainen, Heikki; Liesivuori, Jyrki

2008-01-01

This paper describes the Work Environment Profile (WEP) program and its use in risk identification by computer. It is installed into a hand-held computer or a laptop to be used in risk identification during work site visits. A 5-category system is used to describe the identified risks in 7 groups, i.e., accidents, biological and physical hazards, ergonomic and psychosocial load, chemicals, and information technology hazards. Each group contains several qualifying factors. These 5 categories are colour-coded at this stage to aid with visualization. Risk identification produces visual summary images the interpretation of which is facilitated by colours. The WEP program is a tool for risk assessment which is easy to learn and to use both by experts and nonprofessionals. It is especially well adapted to be used both in small and in larger enterprises. Considerable time is saved as no paper notes are needed.

Computer-aided Instructional System for Transmission Line Simulation.

ERIC Educational Resources Information Center

Reinhard, Erwin A.; Roth, Charles H., Jr.

A computer-aided instructional system has been developed which utilizes dynamic computer-controlled graphic displays and which requires student interaction with a computer simulation in an instructional mode. A numerical scheme has been developed for digital simulation of a uniform, distortionless transmission line with resistive terminations and…

Proceedings of the Workshop on Computational Aspects in the Control of Flexible Systems, part 1

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr. (Compiler)

1989-01-01

Control/Structures Integration program software needs, computer aided control engineering for flexible spacecraft, computer aided design, computational efficiency and capability, modeling and parameter estimation, and control synthesis and optimization software for flexible structures and robots are among the topics discussed.

Computer aided field editing in the DHS context: the Turkey experiment.

PubMed

Cushing, J; Loaiza, E

1994-01-01

"In this study two types of field editing used during the Turkey Demographic and Health Survey are compared. These two types of editing are computer aided field editing and manual editing. It is known that manual editing by field editors is a tedious job in which errors especially on skip questions can be missed; however, with the aid of computers field editors could quickly find all occasions on which an interviewer incorrectly followed a skip instruction. At the end of the experiment it has been found...that the field editing done with the aid of a notebook computer was consistently better than that done in the standard manual manner." (SUMMARY IN TUR) excerpt

The Speech Intelligibility Index and the pure-tone average as predictors of lexical ability in children fit with hearing AIDS.

PubMed

Stiles, Derek J; Bentler, Ruth A; McGregor, Karla K

2012-06-01

To determine whether a clinically obtainable measure of audibility, the aided Speech Intelligibility Index (SII; American National Standards Institute, 2007), is more sensitive than the pure-tone average (PTA) at predicting the lexical abilities of children who wear hearing aids (CHA). School-age CHA and age-matched children with normal hearing (CNH) repeated words and nonwords, learned novel words, and completed a standardized receptive vocabulary test. Analyses of covariance allowed comparison of the 2 groups. For CHA, regression analyses determined whether SII held predictive value over and beyond PTA. CHA demonstrated poorer performance than CNH on tests of word and nonword repetition and receptive vocabulary. Groups did not differ on word learning. Aided SII was a stronger predictor of word and nonword repetition and receptive vocabulary than PTA. After accounting for PTA, aided SII remained a significant predictor of nonword repetition and receptive vocabulary. Despite wearing hearing aids, CHA performed more poorly on 3 of 4 lexical measures. Individual differences among CHA were predicted by aided SII. Unlike PTA, aided SII incorporates hearing aid amplification characteristics and speech-frequency weightings and may provide a more valid estimate of the child's access to and ability to learn from auditory input in real-world environments.

Quality indexing with computer-aided lexicography

NASA Technical Reports Server (NTRS)

Buchan, Ronald L.

1992-01-01

Indexing with computers is a far cry from indexing with the first indexing tool, the manual card sorter. With the aid of computer-aided lexicography, both indexing and indexing tools can provide standardization, consistency, and accuracy, resulting in greater quality control than ever before. A brief survey of computer activity in indexing is presented with detailed illustrations from NASA activity. Applications from techniques mentioned, such as Retrospective Indexing (RI), can be made to many indexing systems. In addition to improving the quality of indexing with computers, the improved efficiency with which certain tasks can be done is demonstrated.

COMPUTER-AIDED DATA ACQUISITION FOR COMBUSTION EXPERIMENTS

EPA Science Inventory

The article describes the use of computer-aided data acquisition techniques to aid the research program of the Combustion Research Branch (CRB) of the U.S. EPA's Air and Energy Engineering Research Laboratory (AEERL) in Research Triangle Park, NC, in particular on CRB's bench-sca...

Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review.

PubMed

Liedlgruber, Michael; Uhl, Andreas

2011-01-01

Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the human body. The advent of endoscopic imaging techniques-allowing the acquisition of images or videos-created the possibility for the development of the whole new branch of computer-aided decision support systems. Such systems aim at helping physicians to identify possibly malignant abnormalities more accurately. At the beginning of this paper, we give a brief introduction to the history of endoscopy, followed by introducing the main types of endoscopes which emerged so far (flexible endoscope, wireless capsule endoscope, and confocal laser endomicroscope). We then give a brief introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract. Then we present general facts and figures concerning computer-aided decision support systems and summarize work specifically targeted at computer-aided decision support in the gastrointestinal tract. This summary is followed by a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.

Smartphone-Based System for Learning and Inferring Hearing Aid Settings

PubMed Central

Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J.

2017-01-01

Background Previous research has shown that hearing aid wearers can successfully self-train their instruments’ gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the “untrained system,” that is, the manufacturer’s algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The “trained system” first learned each individual’s preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). Purpose To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. Research Design An experimental within-participants study. Participants used a prototype hearing system—comprising two hearing aids, Android smartphone, and body-worn gateway device—for ~6 weeks. Study Sample Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Intervention Participants were fitted and instructed to perform daily comparisons of settings (“listening evaluations”) through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase, HALIC recorded individual listening preferences along with sensor data from the smartphone—including environmental sound classification, sound level, and location—to build trained models. In the subsequent two-week-long validation phase, participants performed blinded listening evaluations comparing settings predicted by the trained system (“trained settings”) to those suggested by the hearing aids’ untrained system (“untrained settings”). Data Collection and Analysis We analyzed data collected on the smartphone and hearing aids during the study. We also obtained audiometric and demographic information. Results Overall, the 15 participants with valid data significantly preferred trained settings to untrained settings (paired-samples t test). Seven participants had a significant preference for trained settings, while one had a significant preference for untrained settings (binomial test). The remaining seven participants had nonsignificant preferences. Pooling data across participants, the proportion of times that each setting was chosen in a given environmental sound class was on average very similar. However, breaking down the data by participant revealed strong and idiosyncratic individual preferences. Fourteen participants reported positive feelings of clarity, competence, and mastery when training via HALIC. Conclusions The obtained data, as well as subjective participant feedback, indicate that smartphones could become viable tools to train hearing aids. Individuals who are tech savvy and have milder HL seem well suited to take advantages of the benefits offered by training with a smartphone. PMID:27718350

In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

NASA Astrophysics Data System (ADS)

Singla, Neeru; Srivastava, Vishal; Singh Mehta, Dalip

2018-02-01

We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.

Manipulating the Geometric Computer-aided Design of the Operational Requirements-based Casualty Assessment Model within BRL-CAD

DTIC Science & Technology

2018-03-30

ARL-TR-8336 ● MAR 2018 US Army Research Laboratory Manipulating the Geometric Computer-aided Design of the Operational...so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an official endorsement or approval of...Army Research Laboratory Manipulating the Geometric Computer-aided Design of the Operational Requirements-based Casualty Assessment Model within

Increasing productivity of the McAuto CAD/CAE system by user-specific applications programming

NASA Technical Reports Server (NTRS)

Plotrowski, S. M.; Vu, T. H.

1985-01-01

Significant improvements in the productivity of the McAuto Computer-Aided Design/Computer-Aided Engineering (CAD/CAE) system were achieved by applications programming using the system's own Graphics Interactive Programming language (GRIP) and the interface capabilities with the main computer on which the system resides. The GRIP programs for creating springs, bar charts, finite element model representations and aiding management planning are presented as examples.

Possible Computer Vision Systems and Automated or Computer-Aided Edging and Trimming

Treesearch

Philip A. Araman

1990-01-01

This paper discusses research which is underway to help our industry reduce costs, increase product volume and value recovery, and market more accurately graded and described products. The research is part of a team effort to help the hardwood sawmill industry automate with computer vision systems, and computer-aided or computer controlled processing. This paper...

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.

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

PubMed

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

Computer Skill Acquisition and Retention: The Effects of Computer-Aided Self-Explanation

ERIC Educational Resources Information Center

Chi, Tai-Yin

2016-01-01

This research presents an experimental study to determine to what extent computer skill learners can benefit from generating self-explanation with the aid of different computer-based visualization technologies. Self-explanation was stimulated with dynamic visualization (Screencast), static visualization (Screenshot), or verbal instructions only,…

What's your relationship with computerized manufacturing technologies -- functional, dysfunctional or non-existent?

Treesearch

Jan Wiedenbeck; Jeff Parsons; Bruce Beeken

2009-01-01

Computer-aided manufacturing (CAM), in which computer-aided design (CAD) and computer numerically controlled (CNC) machining are integrated for the production of parts, became a viable option for the woodworking industry in the 1980s.

WINCADRE (COMPUTER-AIDED DATA REVIEW AND EVALUATION)

EPA Science Inventory

WinCADRE (Computer-Aided Data Review and Evaluation) is a Windows -based program designed for computer-assisted data validation. WinCADRE is a powerful tool which significantly decreases data validation turnaround time. The electronic-data-deliverable format has been designed ...

Growing of the mathematical thinking imaginative to students in designing of the teaching aids for CWD towards to joyful learning

NASA Astrophysics Data System (ADS)

Sugiman; Sugiharti, E.; Kurniawati, N. F.

2018-03-01

Government and the private parties had also organized of Special School (SS) and Inclusive School. SS requires of math teachers who were professional in the material, but also master the needs of Children with Disabilities (CwD) in teaching-learning process. The problem: How to design the Teaching Aids for CwD through Extra-Curriculum Training (ECT) activities to Joyful Learning? The purposes of this research: (1) To find new ways how to grow the imaginative in mathematical thinking for students of Mathematics Education. (2) To find a Teaching Aids Design that suitable for CwD who studying in SS. (3) In order to create a Teaching Aids for CwD through activities based on ECT to Joyful Learning. The research method was done by qualitative approach. The research subjects were 6 students of Mathematics Education Study Program of FMIPA UNNES who were interested in attending of the training activities based on ECT. The results: (1) ECT can be a place to grow an Imaginative in Mathematical Thinking of students, (2) created the design of the teaching aids for CwD through activities based on ECT to Joyful Learning as a mirror of the imaginative growth in mathematical thinking for students.

A new 3D texture feature based computer-aided diagnosis approach to differentiate pulmonary nodules

NASA Astrophysics Data System (ADS)

Han, Fangfang; Wang, Huafeng; Song, Bowen; Zhang, Guopeng; Lu, Hongbing; Moore, William; Zhao, Hong; Liang, Zhengrong

2013-02-01

To distinguish malignant pulmonary nodules from benign ones is of much importance in computer-aided diagnosis of lung diseases. Compared to many previous methods which are based on shape or growth assessing of nodules, this proposed three-dimensional (3D) texture feature based approach extracted fifty kinds of 3D textural features from gray level, gradient and curvature co-occurrence matrix, and more derivatives of the volume data of the nodules. To evaluate the presented approach, the Lung Image Database Consortium public database was downloaded. Each case of the database contains an annotation file, which indicates the diagnosis results from up to four radiologists. In order to relieve partial-volume effect, interpolation process was carried out to those volume data with image slice thickness more than 1mm, and thus we had categorized the downloaded datasets to five groups to validate the proposed approach, one group of thickness less than 1mm, two types of thickness range from 1mm to 1.25mm and greater than 1.25mm (each type contains two groups, one with interpolation and the other without). Since support vector machine is based on statistical learning theory and aims to learn for predicting future data, so it was chosen as the classifier to perform the differentiation task. The measure on the performance was based on the area under the curve (AUC) of Receiver Operating Characteristics. From 284 nodules (122 malignant and 162 benign ones), the validation experiments reported a mean of 0.9051 and standard deviation of 0.0397 for the AUC value on average over 100 randomizations.

Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

PubMed

Lu, Shen; Xia, Yong; Cai, Tom Weidong; Feng, David Dagan

2015-01-01

Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine learning based dementia classification methods using medical imaging have been proposed and most of them achieve accurate results. However, most of these methods make use of supervised learning requiring fully labeled image dataset, which usually is not practical in real clinical environment. Using large amount of unlabeled images can improve the dementia classification performance. In this study we propose a new semi-supervised dementia classification method based on random manifold learning with affinity regularization. Three groups of spatial features are extracted from positron emission tomography (PET) images to construct an unsupervised random forest which is then used to regularize the manifold learning objective function. The proposed method, stat-of-the-art Laplacian support vector machine (LapSVM) and supervised SVM are applied to classify AD and normal controls (NC). The experiment results show that learning with unlabeled images indeed improves the classification performance. And our method outperforms LapSVM on the same dataset.

Introducing e-learning/teaching in a physiology course for medical students: acceptance by students and subjective effect on learning.

PubMed

Felder, E; Fauler, M; Geiler, S

2013-12-01

Retrieval of information has substantially changed within the last two decades. Naturally, this has also affected learning/teaching techniques, and methods that are commonly referred to as "e-learning" have become an important part in modern education. Institutions have to decide if (and how) to implement this new form of teaching but face the problem that little subject-specific research has been published for different teaching modes and methods. The present study compares a course module of the physiology laboratory course for medical students in the preclinical phase before and after the introduction of computer-aided course instructions (CACI). Students were provided with an online questionnaire containing Likert items evaluating workspace redesign, acceptance of course instructions, incentive to actively participate in the course, and subjective gain of knowledge. CACI was clearly preferred over the previously used paper workbook. However, the questionnaire also revealed that the gain in knowledge, as subjectively perceived by the students, had not improved, which is in agreement with several studies that neglected a beneficial effect of e-learning on learning success. We conclude that the CACI meet today's student's expectations and that introducing this system seems justified from this perspective.

Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field.

PubMed

Wójcikowski, Maciej; Zielenkiewicz, Piotr; Siedlecki, Pawel

2015-01-01

There has been huge progress in the open cheminformatics field in both methods and software development. Unfortunately, there has been little effort to unite those methods and software into one package. We here describe the Open Drug Discovery Toolkit (ODDT), which aims to fulfill the need for comprehensive and open source drug discovery software. The Open Drug Discovery Toolkit was developed as a free and open source tool for both computer aided drug discovery (CADD) developers and researchers. ODDT reimplements many state-of-the-art methods, such as machine learning scoring functions (RF-Score and NNScore) and wraps other external software to ease the process of developing CADD pipelines. ODDT is an out-of-the-box solution designed to be easily customizable and extensible. Therefore, users are strongly encouraged to extend it and develop new methods. We here present three use cases for ODDT in common tasks in computer-aided drug discovery. Open Drug Discovery Toolkit is released on a permissive 3-clause BSD license for both academic and industrial use. ODDT's source code, additional examples and documentation are available on GitHub (https://github.com/oddt/oddt).

Helical gears with circular arc teeth: Generation, geometry, precision and adjustment to errors, computer aided simulation of conditions of meshing and bearing contact

NASA Technical Reports Server (NTRS)

Litvin, Faydor L.; Tsay, Chung-Biau

1987-01-01

The authors have proposed a method for the generation of circular arc helical gears which is based on the application of standard equipment, worked out all aspects of the geometry of the gears, proposed methods for the computer aided simulation of conditions of meshing and bearing contact, investigated the influence of manufacturing and assembly errors, and proposed methods for the adjustment of gears to these errors. The results of computer aided solutions are illustrated with computer graphics.

Computer-aided drug discovery.

PubMed

Bajorath, Jürgen

2015-01-01

Computational approaches are an integral part of interdisciplinary drug discovery research. Understanding the science behind computational tools, their opportunities, and limitations is essential to make a true impact on drug discovery at different levels. If applied in a scientifically meaningful way, computational methods improve the ability to identify and evaluate potential drug molecules, but there remain weaknesses in the methods that preclude naïve applications. Herein, current trends in computer-aided drug discovery are reviewed, and selected computational areas are discussed. Approaches are highlighted that aid in the identification and optimization of new drug candidates. Emphasis is put on the presentation and discussion of computational concepts and methods, rather than case studies or application examples. As such, this contribution aims to provide an overview of the current methodological spectrum of computational drug discovery for a broad audience.

Rethinking Skin Lesion Segmentation in a Convolutional Classifier.

PubMed

Burdick, Jack; Marques, Oge; Weinthal, Janet; Furht, Borko

2017-10-18

Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powered by convolutional neural networks (CNNs) can improve diagnostic accuracy and save lives. CNNs have been successfully used in both skin lesion segmentation and classification. For reasons heretofore unclear, previous works have found image segmentation to be, conflictingly, both detrimental and beneficial to skin lesion classification. We investigate the effect of expanding the segmentation border to include pixels surrounding the target lesion. Ostensibly, segmenting a target skin lesion will remove inessential information, non-lesion skin, and artifacts to aid in classification. Our results indicate that segmentation border enlargement produces, to a certain degree, better results across all metrics of interest when using a convolutional based classifier built using the transfer learning paradigm. Consequently, preprocessing methods which produce borders larger than the actual lesion can potentially improve classifier performance, more than both perfect segmentation, using dermatologist created ground truth masks, and no segmentation altogether.