Student Learning with Performance-Based, In-Class and Learner-Centered, Online Exams

ERIC Educational Resources Information Center

Greenberg, Katherine; Lester, Jessica N.; Evans, Kathy; Williams, Michele; Hacker, Carolyn; Halic, Olivia

2008-01-01

The purpose of this study was to explore the experience of students with performance-based, in-class and learner-centered, online assessment and the effects of these formats on comprehensive exam scores in an educational psychology course required of participants in a teacher education program. In our quantitative analysis, we investigated the…

Personality Traits and Performance in Online Game-Based Learning: Collaborative versus Individual Settings

ERIC Educational Resources Information Center

Lara, Miguel Angel

2013-01-01

Extant research indicates that, in face-to-face settings, cooperative learning and game-based learning strategies can be effective. However, in online settings (e.g., in distance education), there is a paucity of research in this area. This study was designed to investigate performance and attitudes of university students who played an educational…

Improving Web-Based Student Learning Through Online Video Demonstrations

NASA Astrophysics Data System (ADS)

Miller, Scott; Redman, S.

2010-01-01

Students in online courses continue to lag their peers in comparable face-to-face (F2F) courses (Ury 2004, Slater & Jones 2004). A meta-study of web-based vs. classroom instruction by Sitzmann et al (2006) discovered that the degree of learner control positively influences the effectiveness of instruction: students do better when they are in control of their own learning. In particular, web-based courses are more effective when they incorporate a larger variety of instructional methods. To address this need, we developed a series of online videos to demonstrate various astronomical concepts and provided them to students enrolled in an online introductory astronomy course at Penn State University. We found that the online students performed worse than the F2F students on questions unrelated to the videos (t = -2.84), but that the online students who watched the videos performed better than the F2F students on related examination questions (t = 2.11). We also found that the online students who watched the videos performed significantly better than those who did not (t = 3.43). While the videos in general proved helpful, some videos were more helpful than others. We will discuss our thoughts on why this might be, and future plans to improve upon this study. These videos are freely available on iTunesU, YouTube, and Google Video.

On-Line Mathematics Assessment: The Impact of Mode on Performance and Question Answering Strategies

ERIC Educational Resources Information Center

Johnson, Martin; Green, Sylvia

2006-01-01

The transition from paper-based to computer-based assessment raises a number of important issues about how mode might affect children's performance and question answering strategies. In this project 104 eleven-year-olds were given two sets of matched mathematics questions, one set on-line and the other on paper. Facility values were analyzed to…

Word Recall: Cognitive Performance Within Internet Surveys

PubMed Central

Craig, Benjamin M; Jim, Heather S

2015-01-01

Background The use of online surveys for data collection has increased exponentially, yet it is often unclear whether interview-based cognitive assessments (such as face-to-face or telephonic word recall tasks) can be adapted for use in application-based research settings. Objective The objective of the current study was to compare and characterize the results of online word recall tasks to those of the Health and Retirement Study (HRS) and determine the feasibility and reliability of incorporating word recall tasks into application-based cognitive assessments. Methods The results of the online immediate and delayed word recall assessment, included within the Women’s Health and Valuation (WHV) study, were compared to the results of the immediate and delayed recall tasks of Waves 5-11 (2000-2012) of the HRS. Results Performance on the WHV immediate and delayed tasks demonstrated strong concordance with performance on the HRS tasks (ρc=.79, 95% CI 0.67-0.91), despite significant differences between study populations (P<.001) and study design. Sociodemographic characteristics and self-reported memory demonstrated similar relationships with performance on both the HRS and WHV tasks. Conclusions The key finding of this study is that the HRS word recall tasks performed similarly when used as an online cognitive assessment in the WHV. Online administration of cognitive tests, which has the potential to significantly reduce participant and administrative burden, should be considered in future research studies and health assessments. PMID:26543924

Improving integrity of on-line grammage measurement with traceable basic calibration.

PubMed

Kangasrääsiö, Juha

2010-07-01

The automatic control of grammage (basis weight) in paper and board production is based upon on-line grammage measurement. Furthermore, the automatic control of other quality variables such as moisture, ash content and coat weight, may rely on the grammage measurement. The integrity of Kr-85 based on-line grammage measurement systems was studied, by performing basic calibrations with traceably calibrated plastic reference standards. The calibrations were performed according to the EN ISO/IEC 17025 standard, which is a requirement for calibration laboratories. The observed relative measurement errors were 3.3% in the first time calibrations at the 95% confidence level. With the traceable basic calibration method, however, these errors can be reduced to under 0.5%, thus improving the integrity of on-line grammage measurements. Also a standardised algorithm, based on the experience from the performed calibrations, is proposed to ease the adjustment of the different grammage measurement systems. The calibration technique can basically be applied to all beta-radiation based grammage measurements. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Successful Developmental Math Students in Traditional Format and Online Delivery: A Comparative Study

ERIC Educational Resources Information Center

Thomas, Jeremy Lloyd

2016-01-01

The purpose of this study was to compare student performance in online and traditional classroom based developmental math courses at Texas community colleges. This study specifically examined: (a) student performance in both delivery methods, (b) students who successfully completed the developmental math course, and (c) student performance in the…

Determining the Drivers of Student Performance in Online Business Courses

ERIC Educational Resources Information Center

Estelami, Hooman

2014-01-01

An emerging question in business education is whether all students would benefit from distance learning and if student performance can be predicted prior to enrollment in an online course based on student characteristics. In this paper, the role of student characteristics on academic performance is examined in the context two different online…

Online Graduates in Clinical Laboratory Sciences: Are They Prepared for the Workplace?

ERIC Educational Resources Information Center

Perry, Jennifer D.

2014-01-01

Online programs are increasing in the field of clinical laboratory sciences (CLS), however there is limited research regarding how well prepared online CLS program graduates are for the workplace, given that the field is highly hands-on skills based. Prior research suggests that online CLS graduates perform as well as their traditional graduate…

Student Perceptions of Online Lectures and WebCT in an Introductory Drug Information Course

PubMed Central

Freeman, Maisha Kelly; Schrimsher, Robert H.; Kendrach, Michael G.

2006-01-01

Objectives To determine student perceptions regarding online lectures and quizzes during an introductory drug information course for first-year professional doctor of pharmacy students. Design Formal and online lectures, online quizzes, written semester projects, a practice-based examination, a careers in pharmacy exercise, and a final examination were used to deliver the course content and assess performance. A multiple-choice survey instrument was used to evaluate student perceptions of WebCT and online lectures. Assessment More than 47% of students reported that online lectures helped them learn the material better, 77% reported that lectures would be used to study for the final examination, and 59% reported that they would use WebCT lectures for future classes. Approximately 40% of students agreed that online lectures should be used in future courses. Conclusion Students reported that WebCT was easy to use; however, the majority of students preferred in-class lectures compared to online lectures. A positive correlation was observed for those students who performed well on the online quizzes and those who performed well on the final examination. PMID:17332852

Effects of Online Synchronous Instruction with an Attention Monitoring and Alarm Mechanism on Sustained Attention and Learning Performance

ERIC Educational Resources Information Center

Chen, Chih-Ming; Wang, Jung-Ying

2018-01-01

Many studies have shown that learners' sustained attention strongly affects e-learning performance, particularly during online synchronous instruction. This work thus develops a novel attention monitoring and alarm mechanism (AMAM) based on brainwave signals to improve learning performance via monitoring the attention state of individual learners…

Monitoring the metering performance of an electronic voltage transformer on-line based on cyber-physics correlation analysis

NASA Astrophysics Data System (ADS)

Zhang, Zhu; Li, Hongbin; Tang, Dengping; Hu, Chen; Jiao, Yang

2017-10-01

Metering performance is the key parameter of an electronic voltage transformer (EVT), and it requires high accuracy. The conventional off-line calibration method using a standard voltage transformer is not suitable for the key equipment in a smart substation, which needs on-line monitoring. In this article, we propose a method for monitoring the metering performance of an EVT on-line based on cyber-physics correlation analysis. By the electrical and physical properties of a substation running in three-phase symmetry, the principal component analysis method is used to separate the metering deviation caused by the primary fluctuation and the EVT anomaly. The characteristic statistics of the measured data during operation are extracted, and the metering performance of the EVT is evaluated by analyzing the change in statistics. The experimental results show that the method successfully monitors the metering deviation of a Class 0.2 EVT accurately. The method demonstrates the accurate evaluation of on-line monitoring of the metering performance on an EVT without a standard voltage transformer.

On-Demand Grades: The Effect of Online Grade Book Access on Student Mastery and Performance Goal Orientations, Grade Orientation, Academic Self Efficacy, and Grades

ERIC Educational Resources Information Center

Seldow, Adam Lowell

2010-01-01

With the widespread growth of broadband Internet access, teachers, and in many cases, schools and school districts are transitioning from traditional paper-based grade books to student accessible online (Web-based) grade books. Online grade books offer students 24/7, on demand access to grades and various other student data, and have the potential…

Online energy management strategy of fuel cell hybrid electric vehicles based on data fusion approach

NASA Astrophysics Data System (ADS)

Zhou, Daming; Al-Durra, Ahmed; Gao, Fei; Ravey, Alexandre; Matraji, Imad; Godoy Simões, Marcelo

2017-10-01

Energy management strategy plays a key role for Fuel Cell Hybrid Electric Vehicles (FCHEVs), it directly affects the efficiency and performance of energy storages in FCHEVs. For example, by using a suitable energy distribution controller, the fuel cell system can be maintained in a high efficiency region and thus saving hydrogen consumption. In this paper, an energy management strategy for online driving cycles is proposed based on a combination of the parameters from three offline optimized fuzzy logic controllers using data fusion approach. The fuzzy logic controllers are respectively optimized for three typical driving scenarios: highway, suburban and city in offline. To classify patterns of online driving cycles, a Probabilistic Support Vector Machine (PSVM) is used to provide probabilistic classification results. Based on the classification results of the online driving cycle, the parameters of each offline optimized fuzzy logic controllers are then fused using Dempster-Shafer (DS) evidence theory, in order to calculate the final parameters for the online fuzzy logic controller. Three experimental validations using Hardware-In-the-Loop (HIL) platform with different-sized FCHEVs have been performed. Experimental comparison results show that, the proposed PSVM-DS based online controller can achieve a relatively stable operation and a higher efficiency of fuel cell system in real driving cycles.

Grades, Student Satisfaction and Retention in Online and Face-to-Face Introductory Psychology Units: A Test of Equivalency Theory.

PubMed

Garratt-Reed, David; Roberts, Lynne D; Heritage, Brody

2016-01-01

There has been a recent rapid growth in the number of psychology courses offered online through institutions of higher education. The American Psychological Association has highlighted the importance of ensuring the effectiveness of online psychology courses (Halonen et al., 2013). Despite this, there have been inconsistent findings regarding student grades, satisfaction, and retention in online psychology units. Equivalency Theory (Simonson, 1999; Simonson et al., 1999) posits that online and classroom-based learners will attain equivalent learning outcomes when equivalent learning experiences are provided. We present a study of an online introductory psychology unit designed to provide equivalent learning experiences to the pre-existing face-to-face version of the unit. Using quasi-experimental methods, academic performance, student feedback, and retention data from 866 Australian undergraduate psychology students were examined to assess whether the online unit developed to provide equivalent learning experiences produced comparable outcomes to the 'traditional' unit delivered face-to-face. Student grades did not significantly differ between modes of delivery, except for a group-work based assessment where online students performed more poorly. Student satisfaction was generally high in both modes of the unit, with group-work the key source of dissatisfaction in the online unit. The results provide partial support for Equivalency Theory. The group-work based assessment did not provide an equivalent learning experience for students in the online unit highlighting the need for further research to determine effective methods of engaging students in online group activities. Consistent with previous research, retention rates were significantly lower in the online unit, indicating the need to develop effective strategies to increase online retention rates. While this study demonstrates successes in presenting students with an equivalent learning experience, we recommend that future research investigate means of successfully facilitating collaborative group-work assessment, and to explore contributing factors to actual student retention in online units beyond that of non-equivalent learning experiences.

Grades, Student Satisfaction and Retention in Online and Face-to-Face Introductory Psychology Units: A Test of Equivalency Theory

PubMed Central

Garratt-Reed, David; Roberts, Lynne D.; Heritage, Brody

2016-01-01

There has been a recent rapid growth in the number of psychology courses offered online through institutions of higher education. The American Psychological Association has highlighted the importance of ensuring the effectiveness of online psychology courses (Halonen et al., 2013). Despite this, there have been inconsistent findings regarding student grades, satisfaction, and retention in online psychology units. Equivalency Theory (Simonson, 1999; Simonson et al., 1999) posits that online and classroom-based learners will attain equivalent learning outcomes when equivalent learning experiences are provided. We present a study of an online introductory psychology unit designed to provide equivalent learning experiences to the pre-existing face-to-face version of the unit. Using quasi-experimental methods, academic performance, student feedback, and retention data from 866 Australian undergraduate psychology students were examined to assess whether the online unit developed to provide equivalent learning experiences produced comparable outcomes to the ‘traditional’ unit delivered face-to-face. Student grades did not significantly differ between modes of delivery, except for a group-work based assessment where online students performed more poorly. Student satisfaction was generally high in both modes of the unit, with group-work the key source of dissatisfaction in the online unit. The results provide partial support for Equivalency Theory. The group-work based assessment did not provide an equivalent learning experience for students in the online unit highlighting the need for further research to determine effective methods of engaging students in online group activities. Consistent with previous research, retention rates were significantly lower in the online unit, indicating the need to develop effective strategies to increase online retention rates. While this study demonstrates successes in presenting students with an equivalent learning experience, we recommend that future research investigate means of successfully facilitating collaborative group-work assessment, and to explore contributing factors to actual student retention in online units beyond that of non-equivalent learning experiences. PMID:27242587

Evaluating the effect of online data compression on the disk cache of a mass storage system

NASA Technical Reports Server (NTRS)

Pentakalos, Odysseas I.; Yesha, Yelena

1994-01-01

A trace driven simulation of the disk cache of a mass storage system was used to evaluate the effect of an online compression algorithm on various performance measures. Traces from the system at NASA's Center for Computational Sciences were used to run the simulation and disk cache hit ratios, number of files and bytes migrating to tertiary storage were measured. The measurements were performed for both an LRU and a size based migration algorithm. In addition to seeing the effect of online data compression on the disk cache performance measure, the simulation provided insight into the characteristics of the interactive references, suggesting that hint based prefetching algorithms are the only alternative for any future improvements to the disk cache hit ratio.

Identifying web usage behavior of bank customers

NASA Astrophysics Data System (ADS)

Araya, Sandro; Silva, Mariano; Weber, Richard

2002-03-01

The bank Banco Credito e Inversiones (BCI) started its virtual bank in 1996 and its registered customers perform currently more than 10,000 Internet transactions daily, which typically cause les than 10% of traditional transaction costs. Since most of the customers are still not registered for online banking, one of the goals of the virtual bank is to increase then umber of registered customers. Objective of the presented work was to identify customers who are likely to perform online banking but still do not use this medium for their transactions. This objective has been reached by determining profiles of registered customers who perform many transactions online. Based on these profiles the bank's Data Warehouse is explored for twins of these heavy users that are still not registered for online banking. We applied clustering in order to group the registered customers into five classes. One of these classes contained almost 30% of all registered customers and could clearly be identified as class of heavy users. Next a neural network assigned online customers to the previously found five classes. Applying the network trained on online customers to all the bank customers identified twins of heavy users that, however had not performed online transactions so far. A mailing to these candidates informing about the advantages of online banking doubled the number of registrations compared to previous campaigns.

The impact of blended learning on student performance in a cardiovascular pharmacotherapy course.

PubMed

McLaughlin, Jacqueline E; Gharkholonarehe, Nastaran; Khanova, Julia; Deyo, Zach M; Rodgers, Jo E

2015-03-25

To examine student engagement with, perception of, and performance resulting from blended learning for venous thromboembolism in a required cardiovascular pharmacotherapy course for second-year students. In 2013, key foundational content was packaged into an interactive online module for students to access prior to coming to class; class time was dedicated to active-learning exercises. Students who accessed all online module segments participated in more in class clicker questions (p=0.043) and performed better on the examination (p=0.023). There was no difference in clicker participation or examination performance based on time of module access (prior to or after class). The majority of participants agreed or strongly agreed that foundational content learned prior to class, applied activities during class, and content-related questions in the online module greatly enhanced learning. This study highlights the importance of integrating online modules with classroom learning and the role of blended learning in improving academic performance.

Efficacy Enhancing Communication within the Online Courseroom

ERIC Educational Resources Information Center

Kasitz, Christine M.

2013-01-01

Online learning is becoming more prevalent in high schools especially with at-risk students who may need to recover credits to meet graduation requirements. The purpose of this study was to examine the effects of an online courseroom design that delivers performance-based efficacy enhancing feedback at regular intervals, rather than relying on the…

Reflecting on Online Course Evaluations: Five Must-Do's for Faculty and Students

ERIC Educational Resources Information Center

Cicco, Gina

2016-01-01

This article will review the experiences of a graduate counselor educator in teaching and evaluating her online courses. The author will summarize her most effective instructional and assessment mechanisms, based on student performance through achievement of course objectives as well as students' feedback and comments on specific online counseling…

Student performance in computing education: an empirical analysis of online learning in programming education environments

NASA Astrophysics Data System (ADS)

Xia, Belle Selene; Liitiäinen, Elia

2017-11-01

The benefits of using online exercises have been analysed in terms of distance learning, automatic assessment and self-regulated learning. In this study, we have not found a direct proportional relationship between student performance in the course exercises that use online technologies and the exam grades. We see that the average submission rate to these online exercises is not positively correlated with the exercise points. Yet, our results confirm that doing exercises along supports student learning and skill accumulation equipping them with the knowledge of programming. While the student performance in programming courses is affected by factors such as prior background in programming, cognitive skills and the quality of teaching, completing the course exercises via learning-by-doing is an indispensable part of teaching. Based on the student feedback from the course survey, the students are highly satisfied with using online technologies as part of learning.

Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method.

PubMed

Chen, Jian; Yuan, Shenfang; Qiu, Lei; Cai, Jian; Yang, Weibo

2016-03-03

Prognostics and health management techniques have drawn widespread attention due to their ability to facilitate maintenance activities based on need. On-line prognosis of fatigue crack propagation can offer information for optimizing operation and maintenance strategies in real-time. This paper proposes a Lamb wave-particle filter (LW-PF)-based method for on-line prognosis of fatigue crack propagation which takes advantages of the possibility of on-line monitoring to evaluate the actual crack length and uses a particle filter to deal with the crack evolution and monitoring uncertainties. The piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The state space model relating to crack propagation is established by the data-driven and finite element methods. Fatigue experiments performed on hole-edge crack specimens have validated the advantages of the proposed method.

The Relationship between Working Memory Capacity and L2 Oral Performance under Task-Based Careful Online Planning Condition

ERIC Educational Resources Information Center

Ahmadian, Mohammad Javad

2012-01-01

The study reported in this article aimed to investigate the way working memory capacity (WMC) interacts with careful online planning--a task-based implementation variable--to affect second language (L2) speech production. This issue is important to teachers, because it delves into one of the possible task-based implementation variables and thus…

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

PubMed

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

Performance optimization of an online retailer by a unique online resilience engineering algorithm

NASA Astrophysics Data System (ADS)

Azadeh, A.; Salehi, V.; Salehi, R.; Hassani, S. M.

2018-03-01

Online shopping has become more attractive and competitive in electronic markets. Resilience engineering (RE) can help such systems divert to the normal state in case of encountering unexpected events. This study presents a unique online resilience engineering (ORE) approach for online shopping systems and customer service performance. Moreover, this study presents a new ORE algorithm for the performance optimisation of an actual online shopping system. The data are collected by standard questionnaires from both expert employees and customers. The problem is then formulated mathematically using data envelopment analysis (DEA). The results show that the design process which is based on ORE is more efficient than the conventional design approach. Moreover, on-time delivery is the most important factor from the personnel's perspective. In addition, according to customers' view, trust, security and good quality assurance are the most effective factors during transactions. This is the first study that introduces ORE for electronic markets. Second, it investigates impact of RE on online shopping through DEA and statistical methods. Third, a practical approach is employed in this study and it may be used for similar online shops. Fourth, the results are verified and validated through complete sensitivity analysis.

Does Time Spent Online Have an Influence on Student Performance? Evidence for a Large Business Studies Class

ERIC Educational Resources Information Center

Korkofingas, Con; Macri, Joseph

2013-01-01

This paper examines, using regression modelling, whether a statistically significant relationship exists between the time spent by a student using the course website and the student's assessment performance for a large third year university business forecasting course. We utilise the online tracking system in Blackboard, a web-based software…

The Effect of Online Co-Regulated Learning in the Implementation of Team-Based Learning on Improving Students' Involvement

ERIC Educational Resources Information Center

Tsai, Chia-Wen

2015-01-01

Many education institutions and teachers are recognizing and applying online learning and related educational technologies to help students achieve satisfactory learning performance. Due to the free entertainment on the Internet that may distract students' attention from online courses and with the purpose of developing students' teamwork…

An Online Game Approach for Improving Students' Learning Performance in Web-Based Problem-Solving Activities

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Wu, Po-Han; Chen, Chi-Chang

2012-01-01

In this paper, an online game was developed in the form of a competitive board game for conducting web-based problem-solving activities. The participants of the game determined their move by throwing a dice. Each location of the game board corresponds to a gaming task, which could be a web-based information-searching question or a mini-game; the…

Performance-Based Funding & Online Learning: Maximizing Resources for Student Success

ERIC Educational Resources Information Center

Patrick, Susan; Myers, John; Silverstein, Justin; Brown, Amanda; Watson, John

2015-01-01

There is a new conversation taking place in public education on creating systemic incentives through school finance to encourage schools to innovate and be rewarded for positive student outcomes and performance. What if education funding was not based on seat-time, but on rewarding student performance? Performance-based funding is a term that…

The Combined Effects of Online Planning and Task Structure on Complexity, Accuracy and Fluency of L2 Speech

ERIC Educational Resources Information Center

Javad Ahmadian, Mohammad; Tavakoli, Mansoor; Vahid Dastjerdi, Hossein

2015-01-01

This study investigates the combined effects of task-based careful online planning and the storyline structure of a task on second language performance (complexity, accuracy and fluency). Sixty intermediate EFL learners were randomly assigned to four groups (n = 15). Participants were asked to perform two tasks with different degrees of storyline…

A comparison of student performance in human development classes using three different modes of delivery: Online, face-to-face, and combined

NASA Astrophysics Data System (ADS)

Kalsow, Susan Christensen

1999-11-01

The problem. The dual purposes of this research were to determine if there is a difference in student performance in three Human Development classes when the modes of delivery are different and to analyze student perceptions of using Web-based learning as all or part of their course experience. Procedures. Data for this study were collected from three Human Development courses taught at Drake University. Grades from five essays, projects, and overall grades were used in the three classes and analyzed using a single factor analysis of variance to determine if there was a significant difference. Content analysis was used on the evaluation comments of the participants in the online and combined classes to determine their perceptions of Web-based learning. Findings. The single factor analysis of variance measuring student performance showed no significant difference among the online, face-to-face, and combined scores at the .05 level of significance, however, the difference was significant at the .06. The content analysis of the online and combined course showed the three major strengths of learning totally or partly online to be increased comfort in using the computer, the quality of the overall experience, and convenience in terms of increased access to educational opportunities. The barriers included lack of human interaction and access to the professor. Conclusions. The study indicates that Web-based learning is a viable option for postsecondary educational delivery in terms of student performance and learning. On the average, performance is at least as good as performance in traditional face-to-face classrooms. Improved performance, however, is contingent on adequate access to equipment, faculty skill in teaching using a new mode of delivery, and the personality of the student. The convenient access to educational opportunities and becoming more comfortable with technology are benefits that were important to these two groups. Web-based learning is not for everyone, but Web-assisted learning may be. It has the potential to reach a population of students who otherwise would not have access to postsecondary education. Recommendations. Technology in the twenty-first century will continue to explode and impact our lives. Universities and colleges have the potential to reach a more diverse population, but face-to-face learning will always have value. Consideration must be given to how technology and the use of Web-based learning can be used in varying degrees to meet the needs of students. Classes in the future should have some expected component of navigation and productive use of online learning. Web classes vary from totally online to mostly face-to-face, but all students in the twenty-first century should be expected to know and use this powerful educational resource.

Cultural Membership and Web-Based Training: Does Everyone Really Have Equal Access to Programming?

ERIC Educational Resources Information Center

Harris, Nicholas R.

2017-01-01

The purpose of this study was to determine if differences exist in academic performance (grade point average) in online education programs based on cultural group membership at the undergraduate and graduate levels of post-secondary education. Participants consisted of 1,800 online college students recruited from a large midwestern university with…

Online Project-Based Learning: How Collaborative Strategies and Problem Solving Processes Impact Performance

ERIC Educational Resources Information Center

Thomas, W. Randall; Macgregor, S. Kim

2005-01-01

The goal of this study was to gain insights into the interactions that occur in online communications in a project-based learning activity implemented in an undergraduate course. A multi-case study was conducted of six collaborative groups, focusing on the types and frequencies of interactions that occurred within each group and the perceptions…

The Inequivalence of an Online and Classroom Based General Psychology Course

ERIC Educational Resources Information Center

Edmonds, Christopher L.

2006-01-01

One-hundred seventy-five students enrolled in either a traditional classroom lecture section of General Psychology or in an online section of the same course were compared on exam performance. When covariates of high school grade point average and SAT composite scores were entered into the analysis, students enrolled in the classroom based lecture…

SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

2017-10-01

Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

He Asked Me What!?--Using Shared Online Accounts as Training Tools for Distance Learning Librarians

ERIC Educational Resources Information Center

Robinson, Kelly; Casey, Anne Marie; Citro, Kathleen

2017-01-01

This study explores the idea of creating a knowledge base from shared online accounts to use in training librarians who perform distance reference services. Through a survey, follow-up interviews and a case study, the investigators explored current and potential use of shared online accounts as training tools. This study revealed that the…

Student Performance and Success Factors in Learning Business Statistics in Online vs. On-Ground Classes Using a Web-Based Assessment Platform

ERIC Educational Resources Information Center

Shotwell, Mary; Apigian, Charles H.

2015-01-01

This study aimed to quantify the influence of student attributes, coursework resources, and online assessments on student learning in business statistics. Surveys were administered to students at the completion of both online and on-ground classes, covering student perception and utilization of internal and external academic resources, as well as…

The Impact of Blended Learning on Student Performance in a Cardiovascular Pharmacotherapy Course

PubMed Central

McLaughlin, Jacqueline E.; Gharkholonarehe, Nastaran; Khanova, Julia; Deyo, Zach M.

2015-01-01

Objective. To examine student engagement with, perception of, and performance resulting from blended learning for venous thromboembolism in a required cardiovascular pharmacotherapy course for second-year students. Design. In 2013, key foundational content was packaged into an interactive online module for students to access prior to coming to class; class time was dedicated to active-learning exercises. Assessment. Students who accessed all online module segments participated in more in class clicker questions (p=0.043) and performed better on the examination (p=0.023). There was no difference in clicker participation or examination performance based on time of module access (prior to or after class). The majority of participants agreed or strongly agreed that foundational content learned prior to class, applied activities during class, and content-related questions in the online module greatly enhanced learning. Conclusion. This study highlights the importance of integrating online modules with classroom learning and the role of blended learning in improving academic performance. PMID:25861105

Household Everyday Functioning in the Internet Age: Online Shopping and Banking Skills Are Affected in HIV-Associated Neurocognitive Disorders.

PubMed

Woods, Steven Paul; Iudicello, Jennifer E; Morgan, Erin E; Verduzco, Marizela; Smith, Tyler V; Cushman, Clint

2017-08-01

The Internet is a fundamental tool for completing many different instrumental activities of daily living (IADL), including shopping and banking. Persons with HIV-associated Neurocognitive Disorders (HAND) are at heightened risk for IADL problems, but the extent to which HAND interferes with the performance of Internet-based household IADLs is not known. Ninety-three individuals with HIV disease, 43 of whom were diagnosed with HAND, and 42 HIV- comparison participants completed Internet-based tests of shopping and banking. Participants used mock credentials to log in to an experimenter-controlled Web site and independently performed a series of typical online shopping (e.g., purchasing household goods) and banking (e.g., transferring funds between accounts) tasks. Individuals with HAND were significantly more likely to fail the online shopping task than neurocognitively normal HIV+ and HIV- participants. HAND was also associated with poorer overall performance versus HIV+ normals on the online banking task. In the HAND group, Internet-based task scores were correlated with episodic memory, executive functions, motor skills, and numeracy. In the HIV+ sample as a whole, lower Internet-based task scores were uniquely associated with poorer performance-based functional capacity and self-reported declines in shopping and financial management in daily life, but not with global manifest functional status. Findings indicate that HAND is associated with difficulties in using the Internet to complete important household everyday functioning tasks. The development and validation of effective Internet training and compensatory strategies may help to improve the household management of persons with HAND. (JINS, 2017, 23, 605-615).

A comparison of online versus face-to-face teaching delivery in statistics instruction for undergraduate health science students.

PubMed

Lu, Fletcher; Lemonde, Manon

2013-12-01

The objective of this study was to assess if online teaching delivery produces comparable student test performance as the traditional face-to-face approach irrespective of academic aptitude. This study involves a quasi-experimental comparison of student performance in an undergraduate health science statistics course partitioned in two ways. The first partition involves one group of students taught with a traditional face-to-face classroom approach and the other through a completely online instructional approach. The second partition of the subjects categorized the academic aptitude of the students into groups of higher and lower academically performing based on their assignment grades during the course. Controls that were placed on the study to reduce the possibility of confounding variables were: the same instructor taught both groups covering the same subject information, using the same assessment methods and delivered over the same period of time. The results of this study indicate that online teaching delivery is as effective as a traditional face-to-face approach in terms of producing comparable student test performance but only if the student is academically higher performing. For academically lower performing students, the online delivery method produced significantly poorer student test results compared to those lower performing students taught in a traditional face-to-face environment.

Online Soft Sensor of Humidity in PEM Fuel Cell Based on Dynamic Partial Least Squares

PubMed Central

Long, Rong; Chen, Qihong; Zhang, Liyan; Ma, Longhua; Quan, Shuhai

2013-01-01

Online monitoring humidity in the proton exchange membrane (PEM) fuel cell is an important issue in maintaining proper membrane humidity. The cost and size of existing sensors for monitoring humidity are prohibitive for online measurements. Online prediction of humidity using readily available measured data would be beneficial to water management. In this paper, a novel soft sensor method based on dynamic partial least squares (DPLS) regression is proposed and applied to humidity prediction in PEM fuel cell. In order to obtain data of humidity and test the feasibility of the proposed DPLS-based soft sensor a hardware-in-the-loop (HIL) test system is constructed. The time lag of the DPLS-based soft sensor is selected as 30 by comparing the root-mean-square error in different time lag. The performance of the proposed DPLS-based soft sensor is demonstrated by experimental results. PMID:24453923

Adaptive hidden Markov model-based online learning framework for bearing faulty detection and performance degradation monitoring

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2017-01-01

This study proposes an adaptive-learning-based method for machine faulty detection and health degradation monitoring. The kernel of the proposed method is an "evolving" model that uses an unsupervised online learning scheme, in which an adaptive hidden Markov model (AHMM) is used for online learning the dynamic health changes of machines in their full life. A statistical index is developed for recognizing the new health states in the machines. Those new health states are then described online by adding of new hidden states in AHMM. Furthermore, the health degradations in machines are quantified online by an AHMM-based health index (HI) that measures the similarity between two density distributions that describe the historic and current health states, respectively. When necessary, the proposed method characterizes the distinct operating modes of the machine and can learn online both abrupt as well as gradual health changes. Our method overcomes some drawbacks of the HIs (e.g., relatively low comprehensibility and applicability) based on fixed monitoring models constructed in the offline phase. Results from its application in a bearing life test reveal that the proposed method is effective in online detection and adaptive assessment of machine health degradation. This study provides a useful guide for developing a condition-based maintenance (CBM) system that uses an online learning method without considerable human intervention.

Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

Identifying key hospital service quality factors in online health communities.

PubMed

Jung, Yuchul; Hur, Cinyoung; Jung, Dain; Kim, Minki

2015-04-07

The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. We defined social media-based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea's two biggest online portals were used to test the effectiveness of detection of social media-based key quality factors for hospitals. To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and classification performance still has room for improvement, but the extraction results are applicable to more detailed analysis. Further analysis of the extracted information reveals that there are differences in the details of social media-based key quality factors for hospitals according to the regions in Korea, and the patterns of change seem to accurately reflect social events (eg, influenza epidemics). These findings could be used to provide timely information to caregivers, hospital officials, and medical officials for health care policies.

Improving Student Performance through Computer-Based Assessment: Insights from Recent Research.

ERIC Educational Resources Information Center

Ricketts, C.; Wilks, S. J.

2002-01-01

Compared student performance on computer-based assessment to machine-graded multiple choice tests. Found that performance improved dramatically on the computer-based assessment when students were not required to scroll through the question paper. Concluded that students may be disadvantaged by the introduction of online assessment unless care is…

An evaluative case study of online learning for healthcare professionals.

PubMed

Pullen, Darren L

2006-01-01

This evaluation study assessed the pedagogical and instructional design (e-pedagogy) effectiveness of online continuing professional education (CPE) courses offered by a large Australian CPE provider. A naturalistic theory approach and a multilevel evaluation were used to examine the impact of web-based learning on more than 300 healthcare professionals. Participant satisfaction, learning achievement, self-reported practice performance change, and e-pedagogical courseware characteristics were assessed by various qualitative and quantitative data collection methods. Findings revealed that learning online was an effective means for increasing CPE knowledge (p < .05) and improving self-reported practice performance change (p < .05). Courses containing a clinical tool resulted in an increased self-reported practice performance change over courses that did not (Zobs = 3.757). Online CPE offers a convenient format for healthcare professionals from educationally and geographically diverse populations to update their knowledge and view best practice.

Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video.

PubMed

Gunay, Osman; Toreyin, Behçet Ugur; Kose, Kivanc; Cetin, A Enis

2012-05-01

In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.

Intercepting a moving target: On-line or model-based control?

PubMed

Zhao, Huaiyong; Warren, William H

2017-05-01

When walking to intercept a moving target, people take an interception path that appears to anticipate the target's trajectory. According to the constant bearing strategy, the observer holds the bearing direction of the target constant based on current visual information, consistent with on-line control. Alternatively, the interception path might be based on an internal model of the target's motion, known as model-based control. To investigate these two accounts, participants walked to intercept a moving target in a virtual environment. We degraded the target's visibility by blurring the target to varying degrees in the midst of a trial, in order to influence its perceived speed and position. Reduced levels of visibility progressively impaired interception accuracy and precision; total occlusion impaired performance most and yielded nonadaptive heading adjustments. Thus, performance strongly depended on current visual information and deteriorated qualitatively when it was withdrawn. The results imply that locomotor interception is normally guided by current information rather than an internal model of target motion, consistent with on-line control.

MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.

PubMed

Najjar-Khodabakhsh, Abbas; Soltani, Jafar

2016-03-01

In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Assessment of Web-Based Consumer Reviews as a Resource for Drug Performance

PubMed Central

Adusumalli, Swarnaseetha; Lee, HueyTyng; Hoi, Qiangze; Koo, Si-Lin; Tan, Iain Beehuat

2015-01-01

Background Some health websites provide a public forum for consumers to post ratings and reviews on drugs. Drug reviews are easily accessible and comprehensible, unlike clinical trials and published literature. Because the public increasingly uses the Internet as a source of medical information, it is important to know whether such information is reliable. Objective We aim to examine whether Web-based consumer drug ratings and reviews can be used as a resource to compare drug performance. Methods We analyzed 103,411 consumer-generated reviews on 615 drugs used to treat 249 disease conditions from the health website WebMD. Statistical analysis identified 427 drug pairs from 24 conditions for which two drugs treating the same condition had significantly and substantially different satisfaction ratings (with at least a half-point difference between Web-based ratings and P<.01). PubMed and Google Scholar were searched for publications that were assessed for concordance with findings online. Results Scientific literature was found for 77 out of the 427 drug pairs and compared to findings online. Nearly two-thirds (48/77, 62%) of the online drug trends with at least a half-point difference in online ratings were supported by published literature (P=.02). For a 1-point online rating difference, the concordance rate increased to 68% (15/22) (P=.07). The discrepancies between scientific literature and findings online were further examined to obtain more insights into the usability of Web-based consumer-generated reviews. We discovered that (1) drugs with FDA black box warnings or used off-label were rated poorly in Web-based reviews, (2) drugs with addictive properties were rated higher than their counterparts in Web-based reviews, and (3) second-line or alternative drugs were rated higher. In addition, Web-based ratings indicated drug delivery problems. If FDA black box warning labels are used to resolve disagreements between publications and online trends, the concordance rate increases to 71% (55/77) (P<.001) for a half-point rating difference and 82% (18/22) for a 1-point rating difference (P=.002). Our results suggest that Web-based reviews can be used to inform patients’ drug choices, with certain caveats. Conclusions Web-based reviews can be viewed as an orthogonal source of information for consumers, physicians, and drug manufacturers to assess the performance of a drug. However, one should be cautious to rely solely on consumer reviews as ratings can be strongly influenced by the consumer experience. PMID:26319108

The Effectiveness of Volition Support (VoS) in Promoting Students' Effort Regulation and Performance in an Online Mathematics Course

ERIC Educational Resources Information Center

Kim, ChanMin; Bennekin, Kimberly N.

2016-01-01

The purposes of this study were to investigate (a) the effects of volition support (VoS) on students' motivation, effort regulation, and performance as well as (b) the perceptions of students about VoS in an online mathematics course offered at a community college. VoS was developed based on the theories of and research on volition (e.g., Corno…

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

The Effect of Task Planning on L2 Performance and L2 Development in Text-Based Synchronous Computer-Mediated Communication

ERIC Educational Resources Information Center

Hsu, Hsiu-Chen

2017-01-01

This study explored the effect of two planning conditions [the simultaneous use of rehearsal and careful online planning (ROP), and the careful online planning alone (OP)] on L2 production complexity and accuracy and the subsequent development of these two linguistic areas in the context of text-based synchronous computer-mediated communication.…

Efficient Online Learning Algorithms Based on LSTM Neural Networks.

PubMed

Ergen, Tolga; Kozat, Suleyman Serdar

2017-09-13

We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure.

PubMed

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-05-11

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

PubMed Central

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-01-01

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures. PMID:28772879

Making Student Online Teams Work

ERIC Educational Resources Information Center

Olsen, Joel; Kalinski, Ray

2017-01-01

Online professors typically assign teams based on time zones, performance, or alphabet, but are these the best ways to position student virtual teams for success? Personality and task complexity could provide additional direction. Personality and task complexity were used as independent variables related to the depended variable of team…

The Effects of Prior-knowledge and Online Learning Approaches on Students' Inquiry and Argumentation Abilities

NASA Astrophysics Data System (ADS)

Yang, Wen-Tsung; Lin, Yu-Ren; She, Hsiao-Ching; Huang, Kai-Yi

2015-07-01

This study investigated the effects of students' prior science knowledge and online learning approaches (social and individual) on their learning with regard to three topics: science concepts, inquiry, and argumentation. Two science teachers and 118 students from 4 eighth-grade science classes were invited to participate in this research. Students in each class were divided into three groups according to their level of prior science knowledge; they then took either our social- or individual-based online science learning program. The results show that students in the social online argumentation group performed better in argumentation and online argumentation learning. Qualitative analysis indicated that the students' social interactions benefited the co-construction of sound arguments and the accurate understanding of science concepts. In constructing arguments, students in the individual online argumentation group were limited to knowledge recall and self-reflection. High prior-knowledge students significantly outperformed low prior-knowledge students in all three aspects of science learning. However, the difference in inquiry and argumentation performance between low and high prior-knowledge students decreased with the progression of online learning topics.

An adaptive P300-based online brain-computer interface.

PubMed

Lenhardt, Alexander; Kaper, Matthias; Ritter, Helge J

2008-04-01

The P300 component of an event related potential is widely used in conjunction with brain-computer interfaces (BCIs) to translate the subjects intent by mere thoughts into commands to control artificial devices. A well known application is the spelling of words while selection of the letters is carried out by focusing attention to the target letter. In this paper, we present a P300-based online BCI which reaches very competitive performance in terms of information transfer rates. In addition, we propose an online method that optimizes information transfer rates and/or accuracies. This is achieved by an algorithm which dynamically limits the number of subtrial presentations, according to the subject's current online performance in real-time. We present results of two studies based on 19 different healthy subjects in total who participated in our experiments (seven subjects in the first and 12 subjects in the second one). In the first, study peak information transfer rates up to 92 bits/min with an accuracy of 100% were achieved by one subject with a mean of 32 bits/min at about 80% accuracy. The second experiment employed a dynamic classifier which enables the user to optimize bitrates and/or accuracies by limiting the number of subtrial presentations according to the current online performance of the subject. At the fastest setting, mean information transfer rates could be improved to 50.61 bits/min (i.e., 13.13 symbols/min). The most accurate results with 87.5% accuracy showed a transfer rate of 29.35 bits/min.

Online Self-Tracking Groups to Increase Fruit and Vegetable Intake: A Small-Scale Study on Mechanisms of Group Effect on Behavior Change.

PubMed

Meng, Jingbo; Peng, Wei; Shin, Soo Yun; Chung, Minwoong

2017-03-06

Web-based interventions with a self-tracking component have been found to be effective in promoting adults' fruit and vegetable consumption. However, these interventions primarily focus on individual- rather than group-based self-tracking. The rise of social media technologies enables sharing and comparing self-tracking records in a group context. Therefore, we developed an online group-based self-tracking program to promote fruit and vegetable consumption. This study aims to examine (1) the effectiveness of online group-based self-tracking on fruit and vegetable consumption and (2) characteristics of online self-tracking groups that make the group more effective in promoting fruit and vegetable consumption in early young adults. During a 4-week Web-based experiment, 111 college students self-tracked their fruit and vegetable consumption either individually (ie, the control group) or in an online group characterized by a 2 (demographic similarity: demographically similar vs demographically diverse) × 2 (social modeling: incremental change vs ideal change) experimental design. Each online group consisted of one focal participant and three confederates as group members or peers, who had their demographics and fruit and vegetable consumption manipulated to create the four intervention groups. Self-reported fruit and vegetable consumption were assessed using the Food Frequency Questionnaire at baseline and after the 4-week experiment. Participants who self-tracked their fruit and vegetable consumption collectively with other group members consumed more fruits and vegetables than participants who self-tracked individually (P=.01). The results did not show significant main effects of demographic similarity (P=.32) or types of social modeling (P=.48) in making self-tracking groups more effective in promoting fruit and vegetable consumption. However, additional analyses revealed the main effect of performance discrepancy (ie, difference in fruit and vegetable consumption between a focal participant and his/her group members during the experiment), such that participants who had a low performance discrepancy from other group members had greater fruit and vegetable consumption than participants who had a high performance discrepancy from other group members (P=.002). A mediation test showed that low performance discrepancy led to greater downward contrast (b=-0.78, 95% CI -2.44 to -0.15), which in turn led to greater fruit and vegetable consumption. Online self-tracking groups were more effective than self-tracking alone in promoting fruit and vegetable consumption for early young adults. Low performance discrepancy from other group members lead to downward contrast, which in turn increased participants' fruit and vegetable consumption over time. The study highlighted social comparison processes in online groups that allow for sharing personal health information. Lastly, given the small scale of this study, nonsignificant results with small effect sizes might be subject to bias. ©Jingbo Meng, Wei Peng, Soo Yun Shin, Minwoong Chung. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.03.2017.

Development of On-Line High Performance Liquid Chromatography (HPLC)-Biochemical Detection Methods as Tools in the Identification of Bioactives

PubMed Central

Malherbe, Christiaan J.; de Beer, Dalene; Joubert, Elizabeth

2012-01-01

Biochemical detection (BCD) methods are commonly used to screen plant extracts for specific biological activities in batch assays. Traditionally, bioactives in the most active extracts were identified through time-consuming bio-assay guided fractionation until single active compounds could be isolated. Not only are isolation procedures often tedious, but they could also lead to artifact formation. On-line coupling of BCD assays to high performance liquid chromatography (HPLC) is gaining ground as a high resolution screening technique to overcome problems associated with pre-isolation by measuring the effects of compounds post-column directly after separation. To date, several on-line HPLC-BCD assays, applied to whole plant extracts and mixtures, have been published. In this review the focus will fall on enzyme-based, receptor-based and antioxidant assays. PMID:22489144

Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

Improving General Chemistry Course Performance through Online Homework-Based Metacognitive Training

ERIC Educational Resources Information Center

Casselman, Brock L.; Atwood, Charles H.

2017-01-01

In a first-semester general chemistry course, metacognitive training was implemented as part of an online homework system. Students completed weekly quizzes and multiple practice tests to regularly assess their abilities on the chemistry principles. Before taking these assessments, students predicted their score, receiving feedback after…

An Ecological Approach to the On-Line Assessment of Problem-Solving Paths: Principles and Applications.

ERIC Educational Resources Information Center

Shaw, Robert E.; And Others

1997-01-01

Proposes a theoretical framework for designing online-situated assessment tools for multimedia instructional systems. Uses a graphic method based on ecological psychology to monitor student performance through a learning activity. Explores the method's feasibility in case studies describing instructional systems teaching critical-thinking and…

Quality assurance for online adapted treatment plans: Benchmarking and delivery monitoring simulation

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

Li, Taoran, E-mail: taoran.li.duke@gmail.com; Wu, Qiuwen; Yang, Yun

Purpose: An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. Methods: The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system wasmore » designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system’s performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.« less

Quality assurance for online adapted treatment plans: benchmarking and delivery monitoring simulation.

PubMed

Li, Taoran; Wu, Qiuwen; Yang, Yun; Rodrigues, Anna; Yin, Fang-Fang; Jackie Wu, Q

2015-01-01

An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system was designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system's performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system's ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

NASA Astrophysics Data System (ADS)

Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai

2014-05-01

We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.

PubMed

Spüler, Martin; Rosenstiel, Wolfgang; Bogdan, Martin

2012-01-01

The goal of a Brain-Computer Interface (BCI) is to control a computer by pure brain activity. Recently, BCIs based on code-modulated visual evoked potentials (c-VEPs) have shown great potential to establish high-performance communication. In this paper we present a c-VEP BCI that uses online adaptation of the classifier to reduce calibration time and increase performance. We compare two different approaches for online adaptation of the system: an unsupervised method and a method that uses the detection of error-related potentials. Both approaches were tested in an online study, in which an average accuracy of 96% was achieved with adaptation based on error-related potentials. This accuracy corresponds to an average information transfer rate of 144 bit/min, which is the highest bitrate reported so far for a non-invasive BCI. In a free-spelling mode, the subjects were able to write with an average of 21.3 error-free letters per minute, which shows the feasibility of the BCI system in a normal-use scenario. In addition we show that a calibration of the BCI system solely based on the detection of error-related potentials is possible, without knowing the true class labels.

Recruiting migrants for health research through social network sites: an online survey among chinese migrants in australia.

PubMed

Hu, Jie; Wong, Kam Cheong; Wang, Zhiqiang

2015-04-27

Traditionally, postal surveys or face to face interviews are the main approaches for health researchers to obtain essential research data. However, with the prevalence of information technology and Internet, Web-based surveys are gaining popularity in health research. This study aims to report the process and outcomes of recruiting Chinese migrants through social network sites in Australia and to examine the sample characteristics of online recruitment by comparing the sample which was recruited by an online survey to a sample of Australian Chinese migrants collected by a postal survey. Descriptive analyses were performed to describe and compare the process and outcomes of online recruitment with postal survey questionnaires. Chi square tests and t tests were performed to assess the differences between the two samples for categorical and continuous variables respectively. In total, 473 Chinese migrants completed the online health survey from July to October 2013. Out of 426 participants recruited through the three Chinese social network sites in Australia, over 86.6% (369/426) were recruited within six weeks. Participants of the Web-based survey were younger, with a higher education level or had resided in Australia for less time compared to those recruited via a postal survey. However, there was no significant difference in gender, marital status, and professional occupation. The recruitment of Chinese migrants through social network sites in our online survey was feasible. Compared to a postal survey of Chinese migrants, the online survey attracted different group of Chinese migrants who may have diverse health needs and concerns. Our findings provided insightful information for researchers who are considering employing a Web-based approach to recruit migrants and ethnic minority participants.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Making Online Learning Personal: Evolution, Evidentiary Reasoning, and Self-Regulation in an Online Curriculum

NASA Astrophysics Data System (ADS)

Marsteller, Robert B.

An online curriculum about biological evolution was designed according to the Promoting Evidentiary Reasoning and Self-regulation Online (PERSON) theoretical framework. PERSON is an attempt to develop online science instruction focused on supporting evidentiary reasoning and self-regulation. An efficacy study was conducted with 80 suburban high school biology students using a design-based research approach to develop a curriculum to promote biological evolution understandings, evidentiary reasoning, and self-regulation. Data sources and instruments included (1) the Biological Evolution Assessment Measurement (BEAM); (2) the modified Motivated Strategies for Learning Questionnaire (MSLQ); (3) discussion forum posts; (4) formative assessments of evidence based reasoning; (5) Prediction, Monitoring, and Reflection forms (PMR); (6) the Online Instruction Questionnaire; and (7) field notes. Findings revealed that BEAM posttest scores were significantly greater than pretest scores for items designed to measure biological evolution content knowledge and evidentiary reasoning. Students tracked in a lower level biology course showed improvement in biological evolution understandings and evidentiary reasoning. It was found that performance on daily evidentiary reasoning tasks strongly predicted BEAM posttest scores. However, findings revealed that students did not meet local standards for performance on items designed to measure evidentiary reasoning. Students expressed a variety of opinions about their learning experiences with the online curriculum. Some students expressed a definite preference for traditional learning environments, while others expressed a definite preference for online learning. Self-regulatory ability did not significantly predict BEAM gain scores. Further, self-regulatory ability was not demonstrably improved as a result of this intervention. Implications for designing science instruction in asynchronous online learning environments to support evidentiary reasoning and self-regulation are discussed.

Effect of online formative assessment on summative performance in integrated musculoskeletal system module.

PubMed

Mitra, Nilesh Kumar; Barua, Ankur

2015-03-03

The impact of web-based formative assessment practices on performance of undergraduate medical students in summative assessments is not widely studied. This study was conducted among third-year undergraduate medical students of a designated university in Malaysia to compare the effect, on performance in summative assessment, of repeated computer-based formative assessment with automated feedback with that of single paper-based formative assessment with face-to face feedback. This quasi-randomized trial was conducted among two groups of undergraduate medical students who were selected by stratified random technique from a cohort undertaking the Musculoskeletal module. The control group C (n = 102) was subjected to a paper-based formative MCQ test. The experimental group E (n = 65) was provided three online formative MCQ tests with automated feedback. The summative MCQ test scores for both these groups were collected after the completion of the module. In this study, no significant difference was observed between the mean summative scores of the two groups. However, Band 1 students from group E with higher entry qualification showed higher mean score in the summative assessment. A trivial, but significant and positive correlation (r(2) = +0.328) was observed between the online formative test scores and summative assessment scores of group E. The proportionate increase of performance in group E was found to be almost double than group C. The use of computer based formative test with automated feedback improved the performance of the students with better academic background in the summative assessment. Computer-based formative test can be explored as an optional addition to the curriculum of pre-clinical integrated medical program to improve the performance of the students with higher academic ability.

Identifying Key Hospital Service Quality Factors in Online Health Communities

PubMed Central

Jung, Yuchul; Hur, Cinyoung; Jung, Dain

2015-01-01

Background The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. Objective As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. Methods We defined social media–based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea’s two biggest online portals were used to test the effectiveness of detection of social media–based key quality factors for hospitals. Results To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and classification performance still has room for improvement, but the extraction results are applicable to more detailed analysis. Further analysis of the extracted information reveals that there are differences in the details of social media–based key quality factors for hospitals according to the regions in Korea, and the patterns of change seem to accurately reflect social events (eg, influenza epidemics). Conclusions These findings could be used to provide timely information to caregivers, hospital officials, and medical officials for health care policies. PMID:25855612

The effect of content delivery style on student performance in anatomy.

PubMed

White, Lloyd J; McGowan, Heath W; McDonald, Aaron C

2018-04-12

The development of new technologies and ensuing pedagogical research has led many tertiary institutions to integrate and adopt online learning strategies. The authors of this study have incorporated online learning strategies into existing educational practices of a second year anatomy course, resulting in half of the course content delivered via face-to-face lectures, and half delivered online via tailored video vignettes, with accompanying worksheets and activities. The effect of the content delivery mode on student learning was analyzed by tailoring questions to content presented either face-to-face or online. Four practical tests were conducted across the semester with each consisting of four questions. Within each test, two questions were based on content delivered face-to-face, and two questions were based on content delivered online. Examination multiple choice questions were similarly divided and assessed. Findings indicate that student learning is consistent regardless of the mode of content delivery. However, student viewing habits had a significant impact on learning, with students who viewed videos multiple times achieving higher marks than those less engaged with the online content. Student comments also indicated that content delivery mode was not an influence on learning. Therefore student engagement, rather than the mode of content delivery, is a determinant of student learning and performance in human anatomy. Anat Sci Educ. © 2018 American Association of Anatomists. © 2018 American Association of Anatomists.

Transcranial direct current stimulation versus user training on improving online myoelectric control for amputees

NASA Astrophysics Data System (ADS)

Pan, Lizhi; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Zhu, Xiangyang

2017-08-01

Objective. Transcranial direct current stimulation (tDCS) and user training (UT) are two types of methods to improve myoelectric control performance for amputees. In this study, we compared the independent effect between tDCS and UT, and investigated the combined effect of tDCS and UT. Approach. An online paradigm of simultaneous and proportional control (SPC) based on electromyography (EMG) was adopted. The proposed experiments were conducted on six naïve unilateral trans-radial amputees. The subjects each received three types of 20 min interventions: active tDCS with motor training (tDCS  +  UT), active tDCS with quiet sitting (tDCS), and sham tDCS with motor training (UT). The interventions were applied at one week intervals in a randomized order. The subjects performed online control of a feedback arrow with two degrees of freedom (DoFs) to accomplish target reaching motor tasks in pre-sessions and post-sessions. We compared the performance, measured by completion rate, completion time, and efficiency coefficient, between pre-sessions and post-sessions. Main results. The results showed that the intervention tDCS  +  UT and tDCS significantly improved the online SPC performance (i.e. improved the completion rate; reduced the completion time; and improved the efficiency coefficient), while intervention UT did not significantly change the performance. The results also showed that the online SPC performance after intervention tDCS  +  UT and tDCS was not significantly different, but both were significantly better than that after intervention UT. Significance. tDCS could be an effective intervention to improve the online SPC performance in a short time.

An Investigation of Personality Traits in Relation to Job Performance of Online Instructors

ERIC Educational Resources Information Center

Holmes, Charles; Kirwan, Jeral R.; Bova, Mark; Belcher, Trevor

2015-01-01

This quantitative study examined the relationship between the Big 5 personality traits and how they relate to online teacher effectiveness. The primary method of data collection for this study was through the use of surveys primarily building upon the Personality Style Inventory (PSI) (Lounsbury & Gibson, 2010), a work-based personality…

The New Literacies of Online Research and Comprehension: Rethinking the Reading Achievement Gap

ERIC Educational Resources Information Center

Leu, Donald J.; Forzani, Elena; Rhoads, Chris; Maykel, Cheryl; Kennedy, Clint; Timbrell, Nicole

2015-01-01

Is there an achievement gap for online reading ability based on income inequality that is separate from the achievement gap in traditional, offline reading? This possibility was examined between students in two pseudonymous school districts: West Town (economically advantaged) and East Town (economically challenged; N = 256). Performance-based…

On-Line vs. Face-to-Face Delivery of Information Technology Courses: Students' Assessment

ERIC Educational Resources Information Center

Said, Hazem; Kirgis, Lauren; Verkamp, Brian; Johnson, Lawrence

2015-01-01

This paper investigates students' assessment of on-line vs face-to-face delivery of lecture-based information technology courses. The study used end-of-course surveys to examine students' ratings of five course quality indicators: Course Organization, Assessment and Grading Procedures, Instructor Performance, Positive Learning Experience, and…

Profiling Students Who Take Online Courses Using Data Mining Methods

ERIC Educational Resources Information Center

Yu, Chong Ho; Digangi, Samuel; Jannasch-Pennell, Angel Kay; Kaprolet, Charles

2008-01-01

The efficacy of online learning programs is tied to the suitability of the program in relation to the target audience. Based on the dataset that provides information on student enrollment, academic performance, and demographics extracted from a data warehouse of a large Southwest institution, this study explored the factors that could distinguish…

Adaptive control based on an on-line parameter estimation of an upper limb exoskeleton.

PubMed

Riani, Akram; Madani, Tarek; Hadri, Abdelhafid El; Benallegue, Abdelaziz

2017-07-01

This paper presents an adaptive control strategy for an upper-limb exoskeleton based on an on-line dynamic parameter estimator. The objective is to improve the control performance of this system that plays a critical role in assisting patients for shoulder, elbow and wrist joint movements. In general, the dynamic parameters of the human limb are unknown and differ from a person to another, which degrade the performances of the exoskeleton-human control system. For this reason, the proposed control scheme contains a supplementary loop based on a new efficient on-line estimator of the dynamic parameters. Indeed, the latter is acting upon the parameter adaptation of the controller to ensure the performances of the system in the presence of parameter uncertainties and perturbations. The exoskeleton used in this work is presented and a physical model of the exoskeleton interacting with a 7 Degree of Freedom (DoF) upper limb model is generated using the SimMechanics library of MatLab/Simulink. To illustrate the effectiveness of the proposed approach, an example of passive rehabilitation movements is performed using multi-body dynamic simulation. The aims is to maneuver the exoskeleton that drive the upper limb to track desired trajectories in the case of the passive arm movements.

Adaptive control of nonlinear system using online error minimum neural networks.

PubMed

Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

2016-11-01

In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A qualitative and quantitative assessment for a bone marrow harvest simulator.

PubMed

Machado, Liliane S; Moraes, Ronei M

2009-01-01

Several approaches to perform assessment in training simulators based on virtual reality have been proposed. There are two kinds of assessment methods: offline and online. The main requirements related to online training assessment methodologies applied to virtual reality systems are the low computational complexity and the high accuracy. In the literature it can be found several approaches for general cases which can satisfy such requirements. An inconvenient about those approaches is related to an unsatisfactory solution for specific cases, as in some medical procedures, where there are quantitative and qualitative information available to perform the assessment. In this paper, we present an approach to online training assessment based on a Modified Naive Bayes which can manipulate qualitative and quantitative variables simultaneously. A special medical case was simulated in a bone marrow harvest simulator. The results obtained were satisfactory and evidenced the applicability of the method.

Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

PubMed

Meng, Jianjun; Mundahl, John; Streitz, Taylor; Maile, Kaitlin; Gulachek, Nicholas; He, Jeffrey; He, Bin

2017-01-01

Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.

Needle Steering in Biological Tissue using Ultrasound-based Online Curvature Estimation

PubMed Central

Moreira, Pedro; Patil, Sachin; Alterovitz, Ron; Misra, Sarthak

2014-01-01

Percutaneous needle insertions are commonly performed for diagnostic and therapeutic purposes. Accurate placement of the needle tip is important to the success of many needle procedures. The current needle steering systems depend on needle-tissue-specific data, such as maximum curvature, that is unavailable prior to an interventional procedure. In this paper, we present a novel three-dimensional adaptive steering method for flexible bevel-tipped needles that is capable of performing accurate tip placement without previous knowledge about needle curvature. The method steers the needle by integrating duty-cycled needle steering, online curvature estimation, ultrasound-based needle tracking, and sampling-based motion planning. The needle curvature estimation is performed online and used to adapt the path and duty cycling. We evaluated the method using experiments in a homogenous gelatin phantom, a two-layer gelatin phantom, and a biological tissue phantom composed of a gelatin layer and in vitro chicken tissue. In all experiments, virtual obstacles and targets move in order to represent the disturbances that might occur due to tissue deformation and physiological processes. The average targeting error using our new adaptive method is 40% lower than using the conventional non-adaptive duty-cycled needle steering method. PMID:26229729

Online physician ratings fail to predict actual performance on measures of quality, value, and peer review.

PubMed

Daskivich, Timothy J; Houman, Justin; Fuller, Garth; Black, Jeanne T; Kim, Hyung L; Spiegel, Brennan

2018-04-01

Patients use online consumer ratings to identify high-performing physicians, but it is unclear if ratings are valid measures of clinical performance. We sought to determine whether online ratings of specialist physicians from 5 platforms predict quality of care, value of care, and peer-assessed physician performance. We conducted an observational study of 78 physicians representing 8 medical and surgical specialties. We assessed the association of consumer ratings with specialty-specific performance scores (metrics including adherence to Choosing Wisely measures, 30-day readmissions, length of stay, and adjusted cost of care), primary care physician peer-review scores, and administrator peer-review scores. Across ratings platforms, multivariable models showed no significant association between mean consumer ratings and specialty-specific performance scores (β-coefficient range, -0.04, 0.04), primary care physician scores (β-coefficient range, -0.01, 0.3), and administrator scores (β-coefficient range, -0.2, 0.1). There was no association between ratings and score subdomains addressing quality or value-based care. Among physicians in the lowest quartile of specialty-specific performance scores, only 5%-32% had consumer ratings in the lowest quartile across platforms. Ratings were consistent across platforms; a physician's score on one platform significantly predicted his/her score on another in 5 of 10 comparisons. Online ratings of specialist physicians do not predict objective measures of quality of care or peer assessment of clinical performance. Scores are consistent across platforms, suggesting that they jointly measure a latent construct that is unrelated to performance. Online consumer ratings should not be used in isolation to select physicians, given their poor association with clinical performance.

A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance

PubMed Central

Meng, Jianjun; Edelman, Bradley J.; Olsoe, Jaron; Jacobs, Gabriel; Zhang, Shuying; Beyko, Angeliki; He, Bin

2018-01-01

Motor imagery–based brain–computer interface (BCI) using electroencephalography (EEG) has demonstrated promising applications by directly decoding users' movement related mental intention. The selection of control signals, e.g., the channel configuration and decoding algorithm, plays a vital role in the online performance and progressing of BCI control. While several offline analyses report the effect of these factors on BCI accuracy for a single session—performance increases asymptotically by increasing the number of channels, saturates, and then decreases—no online study, to the best of our knowledge, has yet been performed to compare for a single session or across training. The purpose of the current study is to assess, in a group of forty-five subjects, the effect of channel number and decoding method on the progression of BCI performance across multiple training sessions and the corresponding neurophysiological changes. The 45 subjects were divided into three groups using Laplacian Filtering (LAP/S) with nine channels, Common Spatial Pattern (CSP/L) with 40 channels and CSP (CSP/S) with nine channels for online decoding. At the first training session, subjects using CSP/L displayed no significant difference compared to CSP/S but a higher average BCI performance over those using LAP/S. Despite the average performance when using the LAP/S method was initially lower, but LAP/S displayed improvement over first three sessions, whereas the other two groups did not. Additionally, analysis of the recorded EEG during BCI control indicates that the LAP/S produces control signals that are more strongly correlated with the target location and a higher R-square value was shown at the fifth session. In the present study, we found that subjects' average online BCI performance using a large EEG montage does not show significantly better performance after the first session than a smaller montage comprised of a common subset of these electrodes. The LAP/S method with a small EEG montage allowed the subjects to improve their skills across sessions, but no improvement was shown for the CSP method. PMID:29681792

A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance.

PubMed

Meng, Jianjun; Edelman, Bradley J; Olsoe, Jaron; Jacobs, Gabriel; Zhang, Shuying; Beyko, Angeliki; He, Bin

2018-01-01

Motor imagery-based brain-computer interface (BCI) using electroencephalography (EEG) has demonstrated promising applications by directly decoding users' movement related mental intention. The selection of control signals, e.g., the channel configuration and decoding algorithm, plays a vital role in the online performance and progressing of BCI control. While several offline analyses report the effect of these factors on BCI accuracy for a single session-performance increases asymptotically by increasing the number of channels, saturates, and then decreases-no online study, to the best of our knowledge, has yet been performed to compare for a single session or across training. The purpose of the current study is to assess, in a group of forty-five subjects, the effect of channel number and decoding method on the progression of BCI performance across multiple training sessions and the corresponding neurophysiological changes. The 45 subjects were divided into three groups using Laplacian Filtering (LAP/S) with nine channels, Common Spatial Pattern (CSP/L) with 40 channels and CSP (CSP/S) with nine channels for online decoding. At the first training session, subjects using CSP/L displayed no significant difference compared to CSP/S but a higher average BCI performance over those using LAP/S. Despite the average performance when using the LAP/S method was initially lower, but LAP/S displayed improvement over first three sessions, whereas the other two groups did not. Additionally, analysis of the recorded EEG during BCI control indicates that the LAP/S produces control signals that are more strongly correlated with the target location and a higher R-square value was shown at the fifth session. In the present study, we found that subjects' average online BCI performance using a large EEG montage does not show significantly better performance after the first session than a smaller montage comprised of a common subset of these electrodes. The LAP/S method with a small EEG montage allowed the subjects to improve their skills across sessions, but no improvement was shown for the CSP method.

Laboratory and field based evaluation of chromatography related performance of the Monitor for Aerosols and Gases in Ambient Air (MARGA)

EPA Science Inventory

The Monitor for AeRosols and GAses in ambient air (MARGA) is an on-line ion-chromatography-based instrument designed for speciation of the inorganic gas and aerosol ammonium-nitrate-sulfate system. Previous work to characterize the performance of the MARGA has been primarily base...

Instructional strategies for online introductory college physics based on learning styles

NASA Astrophysics Data System (ADS)

Ekwue, Eleazer U.

The practical nature of physics and its reliance on mathematical presentations and problem solving pose a challenge toward presentation of the course in an online environment for effective learning experience. Most first-time introductory college physics students fail to grasp the basic concepts of the course and the problem solving skills if the instructional strategy used to deliver the course is not compatible with the learners' preferred learning styles. This study investigates the effect of four instructional strategies based on four learning styles (listening, reading, iconic, and direct-experience) to improve learning for introductory college physics in an online environment. Learning styles of 146 participants were determined with Canfield Learning Style inventory. Of the 85 learners who completed the study, research results showed a statistically significant increase in learning performance following the online instruction in all four learning style groups. No statistically significant differences in learning were found among the four groups. However, greater significant academic improvement was found among learners with iconic and direct-experience modes of learning. Learners in all four groups expressed that the design of the unit presentation to match their individual learning styles contributed most to their learning experience. They were satisfied with learning a new physics concept online that, in their opinion, is either comparable or better than an instructor-led classroom experience. Findings from this study suggest that learners' performance and satisfaction in an online introductory physics course could be improved by using instructional designs that are tailored to learners' preferred ways of learning. It could contribute toward the challenge of providing viable online physics instruction in colleges and universities.

Mnemonic anosognosia in Alzheimer's disease is caused by a failure to transfer online evaluations of performance: Evidence from memory training programs.

PubMed

Silva, Ana Rita; Pinho, Maria Salomé; Macedo, Luís; Souchay, Céline; Moulin, Christopher

2017-06-01

There is a debate about the ability of patients with Alzheimer's disease to build an up-to-date representation of their memory function, which has been termed mnemonic anosognosia. This form of anosognosia is typified by accurate online evaluations of performance, but dysfunctional or outmoded representations of function more generally. We tested whether people with Alzheimer's disease could adapt or change their representations of memory performance across three different six-week memory training programs using global judgements of learning. We showed that whereas online assessments of performance were accurate, patients continued to make inaccurate overestimations of their memory performance. This was despite the fact that the magnitude of predictions shifted according to the memory training. That is, on some level patients showed an ability to change and retain a representation of performance over time, but it was a dysfunctional one. For the first time in the literature we were able to use an analysis using correlations to support this claim, based on a large heterogeneous sample of 51 patients with Alzheimer's disease. The results point not to a failure to retain online metamemory information, but rather that this information is never used or incorporated into longer term representations, supporting but refining the mnemonic anosognosia hypothesis.

A Study of the Metacognition Performance in Online Inquiry Learning

ERIC Educational Resources Information Center

Huang, Ya-Ping; Chang, Chiung-Sui

2013-01-01

The purpose of this study is to probe into the effect of metacognitive thinking strategies with different teaching strategies in an online inquiry-based junior high course. Two types of teaching strategies were applied in classes with totally 69 students of 9th graders in New Taipei City. Among participants, 34 students were in the experimental…

Title I Schools: The Student-Based Impact of Online, On-Demand Professional Development on Educators

ERIC Educational Resources Information Center

Shaha, Steven; Glassett, Kelly; Copas, Aimee; Ellsworth, Heather

2015-01-01

Title I students remain among the most challenging population for achieving significant gains in academic performance and standardized test scores. This multi-state, quasi-experimental, pre-versus-post study reflects the comparative Title I gains for math and reading scores for teachers participating in an online, on-demand professional…

Asynchronous Knowledge Sharing and Conversation Interaction Impact on Grade in an Online Business Course

ERIC Educational Resources Information Center

Strang, Kenneth David

2011-01-01

Student knowledge sharing and conversation theory interactions were coded from asynchronous discussion forums to measure the effect of learning-oriented utterances on academic performance. The sample was 3 terms of an online business course (in an accredited MBA program) at a U.S.-based university. Correlation, stepwise regression, and multiple…

Examining a Web-Based Peer Feedback System in an Introductory Computer Literacy Course

ERIC Educational Resources Information Center

Adiguzel, Tufan; Varank, Ilhan; Erkoç, Mehmet Fatih; Buyukimdat, Meryem Koskeroglu

2017-01-01

This study focused on formative use of peer feedback in an online system that was used in basic computer literacy for word processing assignment-related purposes. Specifically, the effect of quantity, modality and satisfaction of peer feedback provided through the online system on students' performance, self-efficacy, and technology acceptance was…

Characteristics and Performance of Students in an Online Section of Business Statistics

ERIC Educational Resources Information Center

Dutton, John; Dutton, Marilyn

2005-01-01

We compare students in online and lecture sections of a business statistics class taught simultaneously by the same instructor using the same content, assignments, and exams in the fall of 2001. Student data are based on class grades, registration records, and two surveys. The surveys asked for information on preparedness, reasons for section…

On-Line Modal State Monitoring of Slowly Time-Varying Structures

NASA Technical Reports Server (NTRS)

Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

1997-01-01

Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring

PubMed Central

Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Objective Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Methods Six MSPE algorithms—derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis—were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. Results CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. Conclusions MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales. PMID:27723803

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.

PubMed

Su, Cui; Liang, Zhenhu; Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Six MSPE algorithms-derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis-were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales.

Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF).

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2018-01-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

NASA Astrophysics Data System (ADS)

Nguyen, T. K. T.; Navratilova, Z.; Cabral, H.; Wang, L.; Gielen, G.; Battaglia, F. P.; Bartic, C.

2014-08-01

Objective. Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach. Approach. The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats. Main results. Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals. Significance. A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

Off-lexicon online Arabic handwriting recognition using neural network

NASA Astrophysics Data System (ADS)

Yahia, Hamdi; Chaabouni, Aymen; Boubaker, Houcine; Alimi, Adel M.

2017-03-01

This paper highlights a new method for online Arabic handwriting recognition based on graphemes segmentation. The main contribution of our work is to explore the utility of Beta-elliptic model in segmentation and features extraction for online handwriting recognition. Indeed, our method consists in decomposing the input signal into continuous part called graphemes based on Beta-Elliptical model, and classify them according to their position in the pseudo-word. The segmented graphemes are then described by the combination of geometric features and trajectory shape modeling. The efficiency of the considered features has been evaluated using feed forward neural network classifier. Experimental results using the benchmarking ADAB Database show the performance of the proposed method.

Assessing the feasibility of online SSVEP decoding in human walking using a consumer EEG headset.

PubMed

Lin, Yuan-Pin; Wang, Yijun; Jung, Tzyy-Ping

2014-08-09

Bridging the gap between laboratory brain-computer interface (BCI) demonstrations and real-life applications has gained increasing attention nowadays in translational neuroscience. An urgent need is to explore the feasibility of using a low-cost, ease-of-use electroencephalogram (EEG) headset for monitoring individuals' EEG signals in their natural head/body positions and movements. This study aimed to assess the feasibility of using a consumer-level EEG headset to realize an online steady-state visual-evoked potential (SSVEP)-based BCI during human walking. This study adopted a 14-channel Emotiv EEG headset to implement a four-target online SSVEP decoding system, and included treadmill walking at the speeds of 0.45, 0.89, and 1.34 meters per second (m/s) to initiate the walking locomotion. Seventeen participants were instructed to perform the online BCI tasks while standing or walking on the treadmill. To maintain a constant viewing distance to the visual targets, participants held the hand-grip of the treadmill during the experiment. Along with online BCI performance, the concurrent SSVEP signals were recorded for offline assessment. Despite walking-related attenuation of SSVEPs, the online BCI obtained an information transfer rate (ITR) over 12 bits/min during slow walking (below 0.89 m/s). SSVEP-based BCI systems are deployable to users in treadmill walking that mimics natural walking rather than in highly-controlled laboratory settings. This study considerably promotes the use of a consumer-level EEG headset towards the real-life BCI applications.

Architecture for knowledge-based and federated search of online clinical evidence.

PubMed

Coiera, Enrico; Walther, Martin; Nguyen, Ken; Lovell, Nigel H

2005-10-24

It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Clinicians performed 1662 searches over the trial. The average search duration was 4.9 +/- 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the capabilities of each individual source (to improve the quality of search results), system maintenance requires only a small additional overhead.

An MFC-Based Online Monitoring and Alert System for Activated Sludge Process

PubMed Central

Xu, Gui-Hua; Wang, Yun-Kun; Sheng, Guo-Ping; Mu, Yang; Yu, Han-Qing

2014-01-01

In this study, based on a simple, compact and submersible microbial fuel cell (MFC), a novel online monitoring and alert system with self-diagnosis function was established for the activated sludge (AS) process. Such a submersible MFC utilized organic substrates and oxygen in the AS reactor as the electron donor and acceptor respectively, and could provide an evaluation on the status of the AS reactor and thus give a reliable early warning of potential risks. In order to evaluate the reliability and sensitivity of this online monitoring and alert system, a series of tests were conducted to examine the response of this system to various shocks imposed on the AS reactor. The results indicate that this online monitoring and alert system was highly sensitive to the performance variations of the AS reactor. The stability, sensitivity and repeatability of this online system provide feasibility of being incorporated into current control systems of wastewater treatment plants to real-time monitor, diagnose, alert and control the AS process. PMID:25345502

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

PubMed

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

SOTXTSTREAM: Density-based self-organizing clustering of text streams.

PubMed

Bryant, Avory C; Cios, Krzysztof J

2017-01-01

A streaming data clustering algorithm is presented building upon the density-based self-organizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets.

Evaluating user reputation in online rating systems via an iterative group-based ranking method

NASA Astrophysics Data System (ADS)

Gao, Jian; Zhou, Tao

2017-05-01

Reputation is a valuable asset in online social lives and it has drawn increased attention. Due to the existence of noisy ratings and spamming attacks, how to evaluate user reputation in online rating systems is especially significant. However, most of the previous ranking-based methods either follow a debatable assumption or have unsatisfied robustness. In this paper, we propose an iterative group-based ranking method by introducing an iterative reputation-allocation process into the original group-based ranking method. More specifically, the reputation of users is calculated based on the weighted sizes of the user rating groups after grouping all users by their rating similarities, and the high reputation users' ratings have larger weights in dominating the corresponding user rating groups. The reputation of users and the user rating group sizes are iteratively updated until they become stable. Results on two real data sets with artificial spammers suggest that the proposed method has better performance than the state-of-the-art methods and its robustness is considerably improved comparing with the original group-based ranking method. Our work highlights the positive role of considering users' grouping behaviors towards a better online user reputation evaluation.

A Novel Approach to Practice-Based Learning and Improvement Using a Web-Based Audit and Feedback Module.

PubMed

Boggan, Joel C; Cheely, George; Shah, Bimal R; Heffelfinger, Randy; Springall, Deanna; Thomas, Samantha M; Zaas, Aimee; Bae, Jonathan

2014-09-01

Systematically engaging residents in large programs in quality improvement (QI) is challenging. To coordinate a shared QI project in a large residency program using an online tool. A web-based QI tool guided residents through a 2-phase evaluation of performance of foot examinations in patients with diabetes. In phase 1, residents completed reviews of health records with online data entry. Residents were then presented with personal performance data relative to peers and were prompted to develop improvement plans. In phase 2, residents again reviewed personal performance. Rates of performance were compared at the program and clinic levels for each phase, with data presented for residents. Acceptability was measured by the number of residents completing each phase. Feasibility was measured by estimated faculty, programmer, and administrator time and costs. Seventy-nine of 86 eligible residents (92%) completed improvement plans and reviewed 1471 patients in phase 1, whereas 68 residents (79%) reviewed 1054 patient charts in phase 2. Rates of performance of examination increased significantly between phases (from 52% to 73% for complete examination, P < .001). Development of the tool required 130 hours of programmer time. Project analysis and management required 6 hours of administrator and faculty time monthly. An online tool developed and implemented for program-wide QI initiatives successfully engaged residents to participate in QI activities. Residents using this tool demonstrated improvement in a selected quality target. This tool could be adapted by other graduate medical education programs or for faculty development.

Mobile Formative Assessment Tool Based on Data Mining Techniques for Supporting Web-Based Learning

ERIC Educational Resources Information Center

Chen, Chih-Ming; Chen, Ming-Chuan

2009-01-01

Current trends clearly indicate that online learning has become an important learning mode. However, no effective assessment mechanism for learning performance yet exists for e-learning systems. Learning performance assessment aims to evaluate what learners learned during the learning process. Traditional summative evaluation only considers final…

Second Language Incidental Vocabulary Learning: The Effect of Online Textual, Pictorial, and Textual Pictorial Glosses

ERIC Educational Resources Information Center

Shahrokni, Seyyed Abdollah

2009-01-01

This empirical study investigates the effect of online textual, pictorial, and textual pictorial glosses on the incidental vocabulary learning of 90 adult elementary Iranian EFL learners. The participants were selected from a pool of 140 volunteers based on their performance on an English placement test as well as a knowledge test of the target…

Integrating Digital Technology in an Intensive, Fully Online College Course for Japanese Beginning Learners: A Standards-Based, Performance-Driven Approach

ERIC Educational Resources Information Center

Sato, Eriko; Chen, Julian Cheng Chiang; Jourdain, Sarah

2017-01-01

The development of distance learning courses for less commonly taught languages (LCTLs) often meets with instructional challenges, especially for Asian LCTLs with their distinct non-Roman characters and structures. This study documents the implementation of a fully online, elementary Japanese course at Stony Brook University. The curriculum was…

Bridging the Virtual Gap in Internet Based Music Instruction: A Feasibility Study in Trombone Performance Education

ERIC Educational Resources Information Center

Wilson, Aaron James

2013-01-01

Since being introduced into classrooms in the late 1990s, online instruction has grown substantially both in student enrollment and the number of programs offered at state, district, and multi-district levels. Although having been applied liberally to all core subjects and many supplemental subjects, online instruction has yet to be utilized…

Maximizing the Use of a Web-Based Soils Module: Targeting Diverse Populations

ERIC Educational Resources Information Center

Lippert, Robert

2006-01-01

This article deals with an on-line soils module project. The two goals for this part of the project were to determine if an on-line soils module could be successfully used for asynchronous instruction of two diverse populations and to determine which demographic factors are related to test performance. The module was presented to an eighth-grade…

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis.

PubMed

Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

2016-12-13

In untargeted metabolomics analysis, several factors (e.g., unwanted experimental &biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data.

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis

PubMed Central

Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

2016-01-01

In untargeted metabolomics analysis, several factors (e.g., unwanted experimental & biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data. PMID:27958387

Which Are the Determinants of Online Students' Efficiency in Higher Education?

NASA Astrophysics Data System (ADS)

Castillo-Merino, David; Serradell-Lopez, Enric; González-González, Inés

International literature shows that the positive effect on students performance from the adoption of innovations in the technology of teaching and learning do not affect all teaching methods and learning styles equally, as it depends on university strategy and policy towards Information and Communication Technologies (ICT) adoption, students abilities, technology uses in the educational process by teachers and students, or the selection of a methodology that matches with digital uses. This paper provides empirical answers to these questions with data from online students at the Open University of Catalonia (UOC). An empirical model based on structural equations has been defined to explain complex relationships between variables. Our results show that motivation is the main variable affecting online students' performance. It appears as a latent variable influenced by students' perception of efficiency, a driver for indirect positive and significant effect on students' performance from students' ability in ICT uses.

Online Teaching Tool Simplifies Faculty Use of Multimedia and Improves Student Interest and Knowledge in Science

PubMed Central

Walsh, John P.; Chih-Yuan Sun, Jerry; Riconscente, Michelle

2011-01-01

Digital technologies can improve student interest and knowledge in science. However, researching the vast number of websites devoted to science education and integrating them into undergraduate curricula is time-consuming. We developed an Adobe ColdFusion– and Adobe Flash–based system for simplifying the construction, use, and delivery of electronic educational materials in science. The Online Multimedia Teaching Tool (OMTT) in Neuroscience was constructed from a ColdFusion-based online interface, which reduced the need for programming skills and the time for curriculum development. The OMTT in Neuroscience was used by faculty to enhance their lectures in existing curricula. Students had unlimited online access to encourage user-centered exploration. We found the OMTT was rapidly adapted by multiple professors, and its use by undergraduate students was consistent with the interpretation that the OMTT improved performance on exams and increased interest in the field of neuroscience. PMID:21885826

Online teaching tool simplifies faculty use of multimedia and improves student interest and knowledge in science.

PubMed

Walsh, John P; Chih-Yuan Sun, Jerry; Riconscente, Michelle

2011-01-01

Digital technologies can improve student interest and knowledge in science. However, researching the vast number of websites devoted to science education and integrating them into undergraduate curricula is time-consuming. We developed an Adobe ColdFusion- and Adobe Flash-based system for simplifying the construction, use, and delivery of electronic educational materials in science. The Online Multimedia Teaching Tool (OMTT) in Neuroscience was constructed from a ColdFusion-based online interface, which reduced the need for programming skills and the time for curriculum development. The OMTT in Neuroscience was used by faculty to enhance their lectures in existing curricula. Students had unlimited online access to encourage user-centered exploration. We found the OMTT was rapidly adapted by multiple professors, and its use by undergraduate students was consistent with the interpretation that the OMTT improved performance on exams and increased interest in the field of neuroscience.

Information retrieval and terminology extraction in online resources for patients with diabetes.

PubMed

Seljan, Sanja; Baretić, Maja; Kucis, Vlasta

2014-06-01

Terminology use, as a mean for information retrieval or document indexing, plays an important role in health literacy. Specific types of users, i.e. patients with diabetes need access to various online resources (on foreign and/or native language) searching for information on self-education of basic diabetic knowledge, on self-care activities regarding importance of dietetic food, medications, physical exercises and on self-management of insulin pumps. Automatic extraction of corpus-based terminology from online texts, manuals or professional papers, can help in building terminology lists or list of "browsing phrases" useful in information retrieval or in document indexing. Specific terminology lists represent an intermediate step between free text search and controlled vocabulary, between user's demands and existing online resources in native and foreign language. The research aiming to detect the role of terminology in online resources, is conducted on English and Croatian manuals and Croatian online texts, and divided into three interrelated parts: i) comparison of professional and popular terminology use ii) evaluation of automatic statistically-based terminology extraction on English and Croatian texts iii) comparison and evaluation of extracted terminology performed on English manual using statistical and hybrid approaches. Extracted terminology candidates are evaluated by comparison with three types of reference lists: list created by professional medical person, list of highly professional vocabulary contained in MeSH and list created by non-medical persons, made as intersection of 15 lists. Results report on use of popular and professional terminology in online diabetes resources, on evaluation of automatically extracted terminology candidates in English and Croatian texts and on comparison of statistical and hybrid extraction methods in English text. Evaluation of automatic and semi-automatic terminology extraction methods is performed by recall, precision and f-measure.

Performance Assessment Links in Science.

ERIC Educational Resources Information Center

Quellmalz, Edys; Schank, Patricia; Hinojosa, Thomas; Padilla, Christine

1999-01-01

Describes work in progress at SRI International in the Performance Assessment Links in Science (PALS) project, which is developing an online, standards-based, interactive resource bank of science performance assessments. Coupled with the development of the resource bank is a program of research on effective use of these resources. (SLD)

Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

PubMed

Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

2013-12-01

This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

Intelligent on-line fault tolerant control for unanticipated catastrophic failures.

PubMed

Yen, Gary G; Ho, Liang-Wei

2004-10-01

As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.

Developing and providing an online (web-based) clinical research design course in Japan: lessons learned.

PubMed

Clark, Glenn T; Mulligan, Roseann; Baba, Kazuyoshi

2011-04-01

This article reports on the lessons learned while teaching an 8-week-long online course about the principles of clinical research design in Japan. Student activity data and how it relates to performance in the course are presented. As prolog, this article focuses on the barriers and solutions to creating and delivering a web-based course and it lists and discusses the most common concerns that educators often have about this process, namely, cost of the system and time requirement of the faculty. Options that must be considered when selecting the support software and hardware needed to conduct live streaming lecture, online video-based conference course are presented. The ancillary role of e-mail based distribution lists as an essential instruction tool within an interactive, instructor-supervised online course is discussed. This article then discusses the inclusion of active learning elements within an online course as well as the pros and cons regarding open-book versus closed book, proctored testing. Lastly, copyright issues the online instructor should know about are discussed. The student tracking data show that as the course progresses, students will reduce the number for page viewings. We speculate that this reduction is due to a combination of conflicting priorities plus increasing efficiency of the students at extracting the critical information. The article also concludes that software and hardware costs to deliver an online course are relatively minor but the faculty's time requirement is initially substantially higher than teaching in a conventional face-to-face course. Copyright © 2011 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Problem-based learning in an on-line biotechnology course

NASA Astrophysics Data System (ADS)

Cheaney, James Daniel

Problem-based learning (PBL) is a pedagogical tool that uses a "real world" problem or situation as a context for learning. PBL encourages student development of critical thinking skills, a high professional competency, problem-solving ability, knowledge acquisition, the ability to work productively as a team member and make decisions in unfamiliar situations, and the acquisition of skills that support self-directed life-long learning, metacognition, and adaptation to change. However, little research has focused on the use of PBL in on-line "virtual" classes. We conducted two studies exploring the use of PBL in an on-line biotechnology course. In the first study, ethical, legal, social, and human issues were used as a motivation for learning about DNA testing technologies, applications, and bioethical issues. In the second study, we combined PBL pedagogy with a rich multimedia environment of streaming video interviews, physical artifacts, and extensive links to articles and databases to create a multidimensional immersive PBL environment called "Robert's World". In "Robert's World", a man is determining whether to undergo a pre-symptomatic DNA test for an untreatable, incurable, fatal genetic disease for which he has a family history. In both studies, design and implementation issues of the on-line PBL environment are discussed, as are differences between on-line PBL and face-to-face PBL. Both studies provide evidence to suggest that PBL stimulates higher-order learning in students. However, in both studies, student performance on an exam testing acquisition of lower-order factual learning was lower for PBL students than for students who learned the same material through a traditional lecture-based approach. Possible reasons for this lower level of performance are explored. Student feedback expressed engagement with the issues and material covered, with reservations about some aspects of the PBL format, such as the lack of flexibility provided in cooperative learning. We conclude that on-line PBL is a powerful tool in helping to develop higher-order learning in students. The reasons for the decrease in student understanding of factual information are unclear. However, there are certain circumstances unique to on-line classes to keep in mind when implementing on-line PBL. These are summarized in concluding recommendations.

Roles of Working Memory Performance and Instructional Strategy in Complex Cognitive Task Performance

ERIC Educational Resources Information Center

Cevik, V.; Altun, A.

2016-01-01

This study aims to investigate how working memory (WM) performances and instructional strategy choices affect learners' complex cognitive task performance in online environments. Three different e-learning environments were designed based on Merrill's (2006a) model of instructional strategies. The lack of experimental research on his framework is…

New-Sum: A Novel Online ABFT Scheme For General Iterative Methods

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

Tao, Dingwen; Song, Shuaiwen; Krishnamoorthy, Sriram

Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recovermore » from errors when combined with a checkpoint/rollback scheme.« less

An Investigation into Student Perceptions towards Mathematics and Their Performance in First Year Chemistry: Introduction of Online Maths Skills Support

ERIC Educational Resources Information Center

Johnston, Peter R.; Watters, Dianne J.; Brown, Christopher L.; Loughlin, Wendy A.

2016-01-01

An online Maths Skills Site was developed as an integrated support programme for first year Chemistry students, the content of which, was based on an analysis of their high-school mathematical backgrounds. This study examined the students' perceptions of Maths, their patterns of usage of the Maths Skills Site and whether there was a relationship…

The Effects of Font Type and Spacing of Text for Online Readability and Performance

ERIC Educational Resources Information Center

Hojjati, Nafiseh; Muniandy, Balakrishnan

2014-01-01

Texts are a group of letters which are printed or displayed in a particular style and size. In the course of the fast speed of technological development everywhere and expanding use of computer based instruction such as online courses, students spend more time on a computer screen than printed media. Texts have been the main element to convey…

Asymptotic analysis of online algorithms and improved scheme for the flow shop scheduling problem with release dates

NASA Astrophysics Data System (ADS)

Bai, Danyu

2015-08-01

This paper discusses the flow shop scheduling problem to minimise the total quadratic completion time (TQCT) with release dates in offline and online environments. For this NP-hard problem, the investigation is focused on the performance of two online algorithms based on the Shortest Processing Time among Available jobs rule. Theoretical results indicate the asymptotic optimality of the algorithms as the problem scale is sufficiently large. To further enhance the quality of the original solutions, the improvement scheme is provided for these algorithms. A new lower bound with performance guarantee is provided, and computational experiments show the effectiveness of these heuristics. Moreover, several results of the single-machine TQCT problem with release dates are also obtained for the deduction of the main theorem.

The Effect over Time of a Video-Based Reflection System on Preservice Teachers' Oral Presentations

ERIC Educational Resources Information Center

Cavanagh, Michael; Bower, Matt; Moloney, Robyn; Sweller, Naomi

2014-01-01

We report the development of preservice teachers' oral presentation performance based on a technology-mediated video reflection system. Participants video-recorded oral presentations and uploaded them to an online blog to view and reflect on their performance and that of their peers. Four presentations by forty-one participants were analysed…

The Relationship between Video Game Use and a Performance-Based Measure of Persistence

ERIC Educational Resources Information Center

Ventura, Matthew; Shute, Valerie; Zhao, Weinan

2013-01-01

An online performance-based measure of persistence was developed using anagrams and riddles. Persistence was measured by recording the time spent on unsolved anagrams and riddles. Time spent on unsolved problems was correlated to a self-report measure of persistence. Additionally, frequent video game players spent longer times on unsolved problems…

Exploring JavaScript and ROOT technologies to create Web-based ATLAS analysis and monitoring tools

NASA Astrophysics Data System (ADS)

Sánchez Pineda, A.

2015-12-01

We explore the potential of current web applications to create online interfaces that allow the visualization, interaction and real cut-based physics analysis and monitoring of processes through a web browser. The project consists in the initial development of web- based and cloud computing services to allow students and researchers to perform fast and very useful cut-based analysis on a browser, reading and using real data and official Monte- Carlo simulations stored in ATLAS computing facilities. Several tools are considered: ROOT, JavaScript and HTML. Our study case is the current cut-based H → ZZ → llqq analysis of the ATLAS experiment. Preliminary but satisfactory results have been obtained online.

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

A Case Study of Online Degree Course Design and Performance of Online Learners

ERIC Educational Resources Information Center

Saul, Robert

2013-01-01

The increasing demand of learners in online higher education courses currently presents a challenge to online course designs in increasing the performance of learners. The online course design process involves many challenges, including a new delivery system, understanding online drivers for success, and an emerging profession of online…

The Impact of Adding Online Homework Assignments to an Introduction to Physical Geology Class

NASA Astrophysics Data System (ADS)

Brevik, Eric C.

2017-04-01

As instructors we are constantly looking for ways to improve student performance in the classroom. In an attempt to improve student performance in my GEOL 105 - Introduction to Physical Geology class, I added online homework assignments from the Pearson Mastering Geology program beginning in the Fall semester of 2014. There were several anticipated advantages to the online homework approach. If a student is struggling with a question they can get hints that don't tell them the answer, but are designed to stimulate their thinking and lead them towards the correct answer. The students also know immediately after submitting their answers which questions they got right and which were wrong, and they can go back to the wrong answers and try to determine the correct answer so they know what it is. This gives them much more rapid feedback than traditional paper homework, all of which makes this a more student-centered approach to learning. It is also my hope that the students find the online homework more interesting and interactive than paper-based homework, which I hope in turn will stimulate the students to be more likely to do the homework and take it seriously while also having some fun while doing it. As of the end of Fall semester 2016, I had been using the online homework assignments in my classes for three years. Therefore, I analyzed student performance in the three years prior to adopting the online homework and compared it to performance over the three years since adopting online homework. In the three years prior to adopting the online homework, the average grade in my classes was 73.8%; afterwards the average grade was 81.3%, for an improvement of 7.5% on average. Most of that improvement was in average test scores, which increased by 6.3% (67.4% prior to 73.6% after). The online homework did not improve the performance of the top students, but it did improve the performance of the other students. Prior to adopting the online homework, grade distribution in the class was 15% A (90-100% scores), 32% B (80-90%), 19% C (70-80%), 19% D (60-79%), and 15% F (<60%). After adopting the online homework, the grade distribution was 13% A, 48% B, 24% C, 13% D, and 2% F. Therefore, students who either passed the class but didn't excel or who struggled with the class prior to online homework adoption saw improvements in their performance, while students who showed truly outstanding performance remained constant. Test grades showed a similar trend. The average test scores for those who received an A in the class were 88.0% prior to and 88.6% after adopting the online homework, while test averages for students who received less than an A were 63.9% prior to and 71.4% (7.5% improvement) after adopting the online homework. I am always making small changes to my classes in an effort to improve them, but the only major change made to the class over the time period covered in this study was replacing paper homework assignments (which were not graded) with the online homework assignments. In addition, there was no statistical difference in scores in the Introduction to Physical Geology Laboratory over the same period (87.8% average before adoption, 85.7% after adoption). Students are required to take the lecture and laboratory at the same time, so the student populations were identical. The online homework applied to the lecture, where grades improved, but not to the laboratory, where grades remained consistent. Therefore, it was concluded that the addition of online homework to the Introduction to Physical Geology class had a strong positive effect on student scores. While students who would excel regardless of the format (those who received A grades) showed the same performance under both class formats, those who fell farther down the grade scale showed significant improvement with the use of the online homework assignments. Acknowledgement The integration of online homework assignments into the Introduction to Physical Geology class was funded by a Summer Faculty Fellowship from the North Dakota Space Grant Consortium.

Daily online testing in large classes: boosting college performance while reducing achievement gaps.

PubMed

Pennebaker, James W; Gosling, Samuel D; Ferrell, Jason D

2013-01-01

An in-class computer-based system, that included daily online testing, was introduced to two large university classes. We examined subsequent improvements in academic performance and reductions in the achievement gaps between lower- and upper-middle class students in academic performance. Students (N = 901) brought laptop computers to classes and took daily quizzes that provided immediate and personalized feedback. Student performance was compared with the same data for traditional classes taught previously by the same instructors (N = 935). Exam performance was approximately half a letter grade above previous semesters, based on comparisons of identical questions asked from earlier years. Students in the experimental classes performed better in other classes, both in the semester they took the course and in subsequent semester classes. The new system resulted in a 50% reduction in the achievement gap as measured by grades among students of different social classes. These findings suggest that frequent consequential quizzing should be used routinely in large lecture courses to improve performance in class and in other concurrent and subsequent courses.

77 FR 20010 - Proposed Information Collection; Comment Request; Online Customer Relationship Management (CRM...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-03

... DEPARTMENT OF COMMERCE Minority Business Development Agency Proposed Information Collection; Comment Request; Online Customer Relationship Management (CRM)/Performance Databases, the Online Phoenix... of program goals via the Online CRM/Performance Databases. The data collected through the Online CRM...

A cell-phone-based brain-computer interface for communication in daily life

NASA Astrophysics Data System (ADS)

Wang, Yu-Te; Wang, Yijun; Jung, Tzyy-Ping

2011-04-01

Moving a brain-computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.

A cell-phone-based brain-computer interface for communication in daily life.

PubMed

Wang, Yu-Te; Wang, Yijun; Jung, Tzyy-Ping

2011-04-01

Moving a brain-computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.

Exploring the relationship between online buyers and sellers of image and performance enhancing drugs (IPEDs): Quality issues, trust and self-regulation.

PubMed

van de Ven, Katinka; Koenraadt, Rosa

2017-12-01

Online drug markets are expanding the boundaries of drug supply including the sale and purchase of image and performance enhancing drugs (IPEDs). However, the role of the internet in IPED markets, and in particular the ways in which these substances are supplied via the surface web, has rarely been considered. This article examines the online IPED market in order to inform drug policy and to provide a nuanced understanding of retailers involved, particularly exploring the relationship between buyers and sellers. This paper is based on two extensive research projects conducted in the Netherlands and Belgium. The first project focuses on muscle drugs and is based on 64 IPED dealing cases, semi-structured interviews with authorities (N=32), and dealers (N=15), along with an analysis of 10 steroid-selling websites. The second research project primarily focuses on weight loss drugs and sexual enhancers in the Netherlands, and relies on interviews with authorities (N=38), suppliers (N=30), and consumers (N=10), analysis of 69 criminal case files, and an online analysis. In the literature, the illicit online sale of IPEDs is generally associated with illegal online pharmacies that try to mislead buyers. While confirmed in our research, we also illustrate that there are online suppliers who invest in customer relationships and services, and that users are aware of the illegal nature of their business. These e-vendors incorporate a 'social supply business model' by providing the best possible service to their customers and attempting to minimise risks in order to attract, satisfy and maintain customers. As it is likely that users will continue to make use of the internet to order IPEDs, regardless of closing down selling websites, it is first of all important to counteract these online sources by educating all types of consumers and providing harm reduction services. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting medical staff intention to use an online reporting system with modified unified theory of acceptance and use of technology.

PubMed

Chang, I-Chiu; Hsu, Hui-Mei

2012-01-01

Barriers to report incident events using an online information system (IS) may be different from those of a paper-based reporting system. The nationwide online Patient-Safety Reporting System (PSRS) contains a value judgment behind use of the system, similar to the Value of Perceived Consequence (VPC), which is seldom discussed in ISs applications of other disciplines. This study developed a more adequate research framework by integrating the VPC construct into the well-known Unified Theory of Acceptance and Use of Technology (UTAUT) model as a theoretical base to explore the predictors of medical staff's intention to use online PSRS. The results showed that management support was an important factor to influence medical staff's intention of using PSRS. The effects of factors such as performance expectancy, perceived positive, and perceived negative consequence on medical staff's intention of using PSRS were moderated by gender, age, experience, and occupation. The results proved that the modified UTAUT model is significant and useful in predicting medical staff's intention of using the nationwide online PSRS.

IoT Service Clustering for Dynamic Service Matchmaking.

PubMed

Zhao, Shuai; Yu, Le; Cheng, Bo; Chen, Junliang

2017-07-27

As the adoption of service-oriented paradigms in the IoT (Internet of Things) environment, real-world devices will open their capabilities through service interfaces, which enable other functional entities to interact with them. In an IoT application, it is indispensable to find suitable services for satisfying users' requirements or replacing the unavailable services. However, from the perspective of performance, it is inappropriate to find desired services from the service repository online directly. Instead, clustering services offline according to their similarity and matchmaking or discovering service online in limited clusters is necessary. This paper proposes a multidimensional model-based approach to measure the similarity between IoT services. Then, density-peaks-based clustering is employed to gather similar services together according to the result of similarity measurement. Based on the service clustering, the algorithms of dynamic service matchmaking, discovery, and replacement will be performed efficiently. Evaluating experiments are conducted to validate the performance of proposed approaches, and the results are promising.

IoT Service Clustering for Dynamic Service Matchmaking

PubMed Central

Yu, Le; Cheng, Bo; Chen, Junliang

2017-01-01

As the adoption of service-oriented paradigms in the IoT (Internet of Things) environment, real-world devices will open their capabilities through service interfaces, which enable other functional entities to interact with them. In an IoT application, it is indispensable to find suitable services for satisfying users’ requirements or replacing the unavailable services. However, from the perspective of performance, it is inappropriate to find desired services from the service repository online directly. Instead, clustering services offline according to their similarity and matchmaking or discovering service online in limited clusters is necessary. This paper proposes a multidimensional model-based approach to measure the similarity between IoT services. Then, density-peaks-based clustering is employed to gather similar services together according to the result of similarity measurement. Based on the service clustering, the algorithms of dynamic service matchmaking, discovery, and replacement will be performed efficiently. Evaluating experiments are conducted to validate the performance of proposed approaches, and the results are promising. PMID:28749431

A Novel Approach to Practice-Based Learning and Improvement Using a Web-Based Audit and Feedback Module

PubMed Central

Boggan, Joel C.; Cheely, George; Shah, Bimal R.; Heffelfinger, Randy; Springall, Deanna; Thomas, Samantha M.; Zaas, Aimee; Bae, Jonathan

2014-01-01

Background Systematically engaging residents in large programs in quality improvement (QI) is challenging. Objective To coordinate a shared QI project in a large residency program using an online tool. Methods A web-based QI tool guided residents through a 2-phase evaluation of performance of foot examinations in patients with diabetes. In phase 1, residents completed reviews of health records with online data entry. Residents were then presented with personal performance data relative to peers and were prompted to develop improvement plans. In phase 2, residents again reviewed personal performance. Rates of performance were compared at the program and clinic levels for each phase, with data presented for residents. Acceptability was measured by the number of residents completing each phase. Feasibility was measured by estimated faculty, programmer, and administrator time and costs. Results Seventy-nine of 86 eligible residents (92%) completed improvement plans and reviewed 1471 patients in phase 1, whereas 68 residents (79%) reviewed 1054 patient charts in phase 2. Rates of performance of examination increased significantly between phases (from 52% to 73% for complete examination, P < .001). Development of the tool required 130 hours of programmer time. Project analysis and management required 6 hours of administrator and faculty time monthly. Conclusions An online tool developed and implemented for program-wide QI initiatives successfully engaged residents to participate in QI activities. Residents using this tool demonstrated improvement in a selected quality target. This tool could be adapted by other graduate medical education programs or for faculty development. PMID:26279782

How Adolescents Search for and Appraise Online Health Information: A Systematic Review.

PubMed

Freeman, Jaimie L; Caldwell, Patrina H Y; Bennett, Patricia A; Scott, Karen M

2018-04-01

To conduct a systematic review of the evidence concerning whether and how adolescents search for online health information and the extent to which they appraise the credibility of information they retrieve. A systematic search of online databases (MEDLINE, EMBASE, PsycINFO, ERIC) was performed. Reference lists of included papers were searched manually for additional articles. Included were studies on whether and how adolescents searched for and appraised online health information, where adolescent participants were aged 13-18 years. Thematic analysis was used to synthesize the findings. Thirty-four studies met the inclusion criteria. In line with the research questions, 2 key concepts were identified within the papers: whether and how adolescents search for online health information, and the extent to which adolescents appraise online health information. Four themes were identified regarding whether and how adolescents search for online health information: use of search engines, difficulties in selecting appropriate search strings, barriers to searching, and absence of searching. Four themes emerged concerning the extent to which adolescents appraise the credibility of online health information: evaluation based on Web site name and reputation, evaluation based on first impression of Web site, evaluation of Web site content, and absence of a sophisticated appraisal strategy. Adolescents are aware of the varying quality of online health information. Strategies used by individuals for searching and appraising online health information differ in their sophistication. It is important to develop resources to enhance search and appraisal skills and to collaborate with adolescents to ensure that such resources are appropriate for them. Copyright © 2017 Elsevier Inc. All rights reserved.

Teaching a laboratory-intensive online introductory electronics course*

NASA Astrophysics Data System (ADS)

Markes, Mark

2008-03-01

Most current online courses provide little or no hands-on laboratory content. This talk will describe the development and initial experiences with presenting an introductory online electronics course with significant hands-on laboratory content. The course is delivered using a Linux-based Apache web server, a Darwin Streaming Server, a SMART Board interactive white board, SMART Notebook software and a video camcorder. The laboratory uses primarily the Global Specialties PB-505 trainer and a Tenma 20MHz Oscilloscope that are provided to the students for the duration of the course and then returned. Testing is performed using Course Blackboard course management software.

Comparison of Onsite Versus Online Chart Reviews as Part of the American College of Radiation Oncology Accreditation Program.

PubMed

Hepel, Jaroslaw T; Heron, Dwight E; Mundt, Arno J; Yashar, Catheryn; Feigenberg, Steven; Koltis, Gordon; Regine, William F; Prasad, Dheerendra; Patel, Shilpen; Sharma, Navesh; Hebert, Mary; Wallis, Norman; Kuettel, Michael

2017-05-01

Accreditation based on peer review of professional standards of care is essential in ensuring quality and safety in administration of radiation therapy. Traditionally, medical chart reviews have been performed by a physical onsite visit. The American College of Radiation Oncology Accreditation Program has remodeled its process whereby electronic charts are reviewed remotely. Twenty-eight radiation oncology practices undergoing accreditation had three charts per practice undergo both onsite and online review. Onsite review was performed by a single reviewer for each practice. Online review consisted of one or more disease site-specific reviewers for each practice. Onsite and online reviews were blinded and scored on a 100-point scale on the basis of 20 categories. A score of less than 75 was failing, and a score of 75 to 79 was marginal. Any failed charts underwent rereview by a disease site team leader. Eighty-four charts underwent both onsite and online review. The mean scores were 86.0 and 86.9 points for charts reviewed onsite and online, respectively. Comparison of onsite and online reviews revealed no statistical difference in chart scores ( P = .43). Of charts reviewed, 21% had a marginal (n = 8) or failing (n = 10) score. There was no difference in failing charts ( P = .48) or combined marginal and failing charts ( P = .13) comparing onsite and online reviews. The American College of Radiation Oncology accreditation process of online chart review results in comparable review scores and rate of failing scores compared with traditional on-site review. However, the modern online process holds less potential for bias by using multiple reviewers per practice and allows for greater oversight via disease site team leader rereview.

An online supervised learning method based on gradient descent for spiking neurons.

PubMed

Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enhancing dissolved oxygen control using an on-line hybrid fuzzy-neural soft-sensing model-based control system in an anaerobic/anoxic/oxic process.

PubMed

Huang, Mingzhi; Wan, Jinquan; Hu, Kang; Ma, Yongwen; Wang, Yan

2013-12-01

An on-line hybrid fuzzy-neural soft-sensing model-based control system was developed to optimize dissolved oxygen concentration in a bench-scale anaerobic/anoxic/oxic (A(2)/O) process. In order to improve the performance of the control system, a self-adapted fuzzy c-means clustering algorithm and adaptive network-based fuzzy inference system (ANFIS) models were employed. The proposed control system permits the on-line implementation of every operating strategy of the experimental system. A set of experiments involving variable hydraulic retention time (HRT), influent pH (pH), dissolved oxygen in the aerobic reactor (DO), and mixed-liquid return ratio (r) was carried out. Using the proposed system, the amount of COD in the effluent stabilized at the set-point and below. The improvement was achieved with optimum dissolved oxygen concentration because the performance of the treatment process was optimized using operating rules implemented in real time. The system allows various expert operational approaches to be deployed with the goal of minimizing organic substances in the outlet while using the minimum amount of energy.

A dual-user teleoperation system with Online Authority Adjustment for haptic training.

PubMed

Fei Liu; Leleve, Arnaud; Eberard, Damien; Redarce, Tanneguy

2015-08-01

This paper introduces a dual-user teleoperation system for hands-on medical training. A shared control based architecture is presented for authority management. In this structure, the combination of control signals is obtained using a dominance factor. Its main improvement is Online Authority Adjustment (OAA): the authority can be adjusted manually/automatically during the training progress. Experimental results are provided to validate the performances of the system.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

PubMed Central

Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.

2015-01-01

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

PubMed

Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A

2015-06-29

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Online webcam-based eye tracking in cognitive science: A first look.

PubMed

Semmelmann, Kilian; Weigelt, Sarah

2018-04-01

Online experimentation is emerging in many areas of cognitive psychology as a viable alternative or supplement to classical in-lab experimentation. While performance- and reaction-time-based paradigms are covered in recent studies, one instrument of cognitive psychology has not received much attention up to now: eye tracking. In this study, we used JavaScript-based eye tracking algorithms recently made available by Papoutsaki et al. (International Joint Conference on Artificial Intelligence, 2016) together with consumer-grade webcams to investigate the potential of online eye tracking to benefit from the common advantages of online data conduction. We compared three in-lab conducted tasks (fixation, pursuit, and free viewing) with online-acquired data to analyze the spatial precision in the first two, and replicability of well-known gazing patterns in the third task. Our results indicate that in-lab data exhibit an offset of about 172 px (15% of screen size, 3.94° visual angle) in the fixation task, while online data is slightly less accurate (18% of screen size, 207 px), and shows higher variance. The same results were found for the pursuit task with a constant offset during the stimulus movement (211 px in-lab, 216 px online). In the free-viewing task, we were able to replicate the high attention attribution to eyes (28.25%) compared to other key regions like the nose (9.71%) and mouth (4.00%). Overall, we found web technology-based eye tracking to be suitable for all three tasks and are confident that the required hard- and software will be improved continuously for even more sophisticated experimental paradigms in all of cognitive psychology.

The Relationship between Shared Mental Models and Task Performance in an Online Team- Based Learning Environment

ERIC Educational Resources Information Center

Johnson, Tristan E.; Lee, Youngmin

2008-01-01

In an effort to better understand learning teams, this study examines the effects of shared mental models on team and individual performance. The results indicate that each team's shared mental model changed significantly over the time that subjects participated in team-based learning activities. The results also showed that the shared mental…

Surface inspection of flat products by means of texture analysis: on-line implementation using neural networks

NASA Astrophysics Data System (ADS)

Fernandez, Carlos; Platero, Carlos; Campoy, Pascual; Aracil, Rafael

1994-11-01

This paper describes some texture-based techniques that can be applied to quality assessment of flat products continuously produced (metal strips, wooden surfaces, cork, textile products, ...). Since the most difficult task is that of inspecting for product appearance, human-like inspection ability is required. A common feature to all these products is the presence of non- deterministic texture on their surfaces. Two main subjects are discussed: statistical techniques for both surface finishing determination and surface defect analysis as well as real-time implementation for on-line inspection in high-speed applications. For surface finishing determination a Gray Level Difference technique is presented to perform over low resolution images, that is, no-zoomed images. Defect analysis is performed by means of statistical texture analysis over defective portions of the surface. On-line implementation is accomplished by means of neural networks. When a defect arises, textural analysis is applied which result in a data-vector, acting as input of a neural net, previously trained in a supervised way. This approach tries to reach on-line performance in automated visual inspection applications when texture is presented in flat product surfaces.

Automatic Identification of Messages Related to Adverse Drug Reactions from Online User Reviews using Feature-based Classification.

PubMed

Liu, Jingfang; Zhang, Pengzhu; Lu, Yingjie

2014-11-01

User-generated medical messages on Internet contain extensive information related to adverse drug reactions (ADRs) and are known as valuable resources for post-marketing drug surveillance. The aim of this study was to find an effective method to identify messages related to ADRs automatically from online user reviews. We conducted experiments on online user reviews using different feature set and different classification technique. Firstly, the messages from three communities, allergy community, schizophrenia community and pain management community, were collected, the 3000 messages were annotated. Secondly, the N-gram-based features set and medical domain-specific features set were generated. Thirdly, three classification techniques, SVM, C4.5 and Naïve Bayes, were used to perform classification tasks separately. Finally, we evaluated the performance of different method using different feature set and different classification technique by comparing the metrics including accuracy and F-measure. In terms of accuracy, the accuracy of SVM classifier was higher than 0.8, the accuracy of C4.5 classifier or Naïve Bayes classifier was lower than 0.8; meanwhile, the combination feature sets including n-gram-based feature set and domain-specific feature set consistently outperformed single feature set. In terms of F-measure, the highest F-measure is 0.895 which was achieved by using combination feature sets and a SVM classifier. In all, we can get the best classification performance by using combination feature sets and SVM classifier. By using combination feature sets and SVM classifier, we can get an effective method to identify messages related to ADRs automatically from online user reviews.

OCICATS (Online Community Input Classification to Advance Transportation Services) - a GIS-based decision-support tool.

DOT National Transportation Integrated Search

2016-09-02

Public transportation agencies can obtain large amounts of information regarding timeliness, efficiency, cleanliness, ridership, and other : performance measures. However, these metrics are based on the interests of these agencies and do not necessar...

Online clustering algorithms for radar emitter classification.

PubMed

Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

2005-08-01

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

Automatic topic identification of health-related messages in online health community using text classification.

PubMed

Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

Architecture for Knowledge-Based and Federated Search of Online Clinical Evidence

PubMed Central

Walther, Martin; Nguyen, Ken; Lovell, Nigel H

2005-01-01

Background It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. Objectives The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. Methods A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Results Clinicians performed 1662 searches over the trial. The average search duration was 4.9 ± 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. Conclusions The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the capabilities of each individual source (to improve the quality of search results), system maintenance requires only a small additional overhead. PMID:16403716

Combined online and offline adaptive radiation therapy: a dosimetric feasibility study.

PubMed

Yang, Chengliang; Liu, Feng; Ahunbay, Ergun; Chang, Yu-Wen; Lawton, Colleen; Schultz, Christopher; Wang, Dian; Firat, Selim; Erickson, Beth; Li, X Allen

2014-01-01

The purpose of this work is to explore a new adaptive radiation therapy (ART) strategy, combined "online and offline" ART, that can fully account for interfraction variations similar to the existing online ART but with substantially reduced online effort. The concept for the combined ART is to perform online ART only for the fractions with obvious interfraction variations and to deliver the ART plan for that online fraction as well as the subsequent fractions until the next online fraction needs to be adapted. To demonstrate the idea, the daily computed tomographic (CT) data acquired during image guided radiation therapy (IGRT) with an in-room CT (CTVision, Siemens Healthcare, Amarillo, TX) for 6 representative patients (including 2 prostate, 1 head-and-neck, and 1 pancreatic cancer, 1 adrenal carcinoma, and 1 craniopharyngioma patients) were analyzed. Three types of plans were generated based on the following selected daily CTs: (1) IGRT repositioning plan, generated by applying the repositioning shifts to the original plan (representing the current IGRT practice); (2) Re-Opt plan, generated with full-scope optimization; and (3) ART plan, either online ART plan generated with an online ART tool (RealArt, Prowess Inc, Concord, CA) or offline ART plan generated with shifts from the online ART plan. Various dose-volume parameters were compared with measure dosimetric benefits of the ART plans based on daily dose distributions and the cumulative dose maps obtained with deformable image registration. In general, for all the cases studied, the ART (with 3-5 online ART) and Re-Opt plans provide comparable plan quality and offer significantly better target coverage and normal tissue sparing when compared with the repositioning plans. This improvement is statistically significant. The combined online and offline ART is dosimetrically equivalent to the online ART but with substantially reduced online effort, and enables immediate delivery of the adaptive plan when an obvious anatomic change is observed. Copyright © 2014 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance

DTIC Science & Technology

2003-07-21

Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance Vincent A. Cicirello CMU-RI-TR-03-27 Submitted in partial fulfillment...AND SUBTITLE Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...lead to the development of a search control framework, called QD-BEACON that uses online -generated statistical models of search performance to

A dedicated on-line detecting system for auto air dryers

NASA Astrophysics Data System (ADS)

Shi, Chao-yu; Luo, Zai

2013-10-01

According to the correlative automobile industry standard and the requirements of manufacturer, this dedicated on-line detecting system is designed against the shortage of low degree automatic efficiency and detection precision of auto air dryer in the domestic. Fast automatic detection is achieved by combining the technology of computer control, mechatronics and pneumatics. This system can detect the speciality performance of pressure regulating valve and sealability of auto air dryer, in which online analytical processing of test data is available, at the same time, saving and inquiring data is achieved. Through some experimental analysis, it is indicated that efficient and accurate detection of the performance of auto air dryer is realized, and the test errors are less than 3%. Moreover, we carry out the type A evaluation of uncertainty in test data based on Bayesian theory, and the results show that the test uncertainties of all performance parameters are less than 0.5kPa, which can meet the requirements of operating industrial site absolutely.

Model-Free Adaptive Control for Unknown Nonlinear Zero-Sum Differential Game.

PubMed

Zhong, Xiangnan; He, Haibo; Wang, Ding; Ni, Zhen

2018-05-01

In this paper, we present a new model-free globalized dual heuristic dynamic programming (GDHP) approach for the discrete-time nonlinear zero-sum game problems. First, the online learning algorithm is proposed based on the GDHP method to solve the Hamilton-Jacobi-Isaacs equation associated with optimal regulation control problem. By setting backward one step of the definition of performance index, the requirement of system dynamics, or an identifier is relaxed in the proposed method. Then, three neural networks are established to approximate the optimal saddle point feedback control law, the disturbance law, and the performance index, respectively. The explicit updating rules for these three neural networks are provided based on the data generated during the online learning along the system trajectories. The stability analysis in terms of the neural network approximation errors is discussed based on the Lyapunov approach. Finally, two simulation examples are provided to show the effectiveness of the proposed method.

Glove-based approach to online signature verification.

PubMed

Kamel, Nidal S; Sayeed, Shohel; Ellis, Grant A

2008-06-01

Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.

Online Meta-data Collection and Monitoring Framework for the STAR Experiment at RHIC

NASA Astrophysics Data System (ADS)

Arkhipkin, D.; Lauret, J.; Betts, W.; Van Buren, G.

2012-12-01

The STAR Experiment further exploits scalable message-oriented model principles to achieve a high level of control over online data streams. In this paper we present an AMQP-powered Message Interface and Reliable Architecture framework (MIRA), which allows STAR to orchestrate the activities of Meta-data Collection, Monitoring, Online QA and several Run-Time and Data Acquisition system components in a very efficient manner. The very nature of the reliable message bus suggests parallel usage of multiple independent storage mechanisms for our meta-data. We describe our experience with a robust data-taking setup employing MySQL- and HyperTable-based archivers for meta-data processing. In addition, MIRA has an AJAX-enabled web GUI, which allows real-time visualisation of online process flow and detector subsystem states, and doubles as a sophisticated alarm system when combined with complex event processing engines like Esper, Borealis or Cayuga. The performance data and our planned path forward are based on our experience during the 2011-2012 running of STAR.

Improved Online Support Vector Machines Spam Filtering Using String Kernels

NASA Astrophysics Data System (ADS)

Amayri, Ola; Bouguila, Nizar

A major bottleneck in electronic communications is the enormous dissemination of spam emails. Developing of suitable filters that can adequately capture those emails and achieve high performance rate become a main concern. Support vector machines (SVMs) have made a large contribution to the development of spam email filtering. Based on SVMs, the crucial problems in email classification are feature mapping of input emails and the choice of the kernels. In this paper, we present thorough investigation of several distance-based kernels and propose the use of string kernels and prove its efficiency in blocking spam emails. We detail a feature mapping variants in text classification (TC) that yield improved performance for the standard SVMs in filtering task. Furthermore, to cope for realtime scenarios we propose an online active framework for spam filtering.

Determination of fluoroquinolones in cattle manure-based biogas residue by ultrasonic-enhanced microwave-assisted extraction followed by online solid phase extraction-ultra-high performance liquid chromatography-tandem mass spectrometry.

PubMed

Lu, Xue-Feng; Zhou, Yang; Zhang, Jian; Ren, Yu-Peng

2018-06-01

The present work describes the development and application of an ultrasonic-enhanced microwave-assisted extraction (UEMAE) followed by online solid phase extraction (SPE)-ultra-high performance liquid chromatography-tandem mass spectrometry method for the analysis of 14 fluoroquinolones in cattle manure-based biogas residue (CMBBR). The UEMAE was performed using the mixed solution of sodium dihydrogen phosphate and disodium ethylenediamine tetraacetic acid, avoiding use of any organic solvent. The online SPE system employed two solid phase extraction columns in a parallel manner, and the extraction was performed by passing 1 mL of the extract through the column. Quantification was performed using standard spiked samples and structural analogue internal standard, which were indispensable to reduce the matrix effects. Validation parameters were performed and good linearity (R 2  > 0.99 in all cases) and precision (inter- and intra-day relative standard deviations were lower than 12.8%) were obtained. Limits of detection were as low as 0.021 ng ∙ g -1 and lower limits of quantification were 0.5 ng ∙ g -1 for all fluoroquinolones. The overall extraction recovery, which was the product of the UEMAE recovery and the online SPE recovery, was assessed for three concentration levels (0.8, 40 and 400 ng ∙ g -1 ) and acceptable values (74.3-99.3%) were found. As a part of the method validation, the developed method has been used to analyze real CMBBR samples. Nine fluoroquinolones were found in the concentration range of 0.9-74.6 ng ∙ g -1 , while five were not detected in the samples. The results showed the method could be adapted for screening the presence or the final fate of fluoroquinolones during fermentation of animal waste. Copyright © 2018. Published by Elsevier B.V.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Online blind source separation using incremental nonnegative matrix factorization with volume constraint.

PubMed

Zhou, Guoxu; Yang, Zuyuan; Xie, Shengli; Yang, Jun-Mei

2011-04-01

Online blind source separation (BSS) is proposed to overcome the high computational cost problem, which limits the practical applications of traditional batch BSS algorithms. However, the existing online BSS methods are mainly used to separate independent or uncorrelated sources. Recently, nonnegative matrix factorization (NMF) shows great potential to separate the correlative sources, where some constraints are often imposed to overcome the non-uniqueness of the factorization. In this paper, an incremental NMF with volume constraint is derived and utilized for solving online BSS. The volume constraint to the mixing matrix enhances the identifiability of the sources, while the incremental learning mode reduces the computational cost. The proposed method takes advantage of the natural gradient based multiplication updating rule, and it performs especially well in the recovery of dependent sources. Simulations in BSS for dual-energy X-ray images, online encrypted speech signals, and high correlative face images show the validity of the proposed method.

Teaching mathematics online in the European Area of Higher Education: an instructor's point of view

NASA Astrophysics Data System (ADS)

Juan, Angel A.; Steegmann, Cristina; Huertas, Antonia; Martinez, M. Jesus; Simosa, J.

2011-03-01

This article first discusses how information technologies are changing the way knowledge is delivered at universities worldwide. Then, the article reviews some of the most popular learning management systems available today and some of the most useful online resources in the areas of Mathematics and Statistics. After that, some long-term experiences regarding the teaching of online courses in those areas at the Open University of Catalonia are discussed. Finally, the article presents the results of a large-scale survey performed in Spain that aims to reflect instructors' opinions and feelings about potential benefits and challenges of teaching mathematics online, as well as the role of emergent technologies in the context of the European Area of Higher Education. Therefore, this article contributes to the existing literature as an additional reference point, one based on our long-term experience in a large-scale online environment, for discussions involving mathematical e-learning.

Roles and Domains to Teach in Online Learning Environments: Educational ICT Competency Framework for University Teachers

NASA Astrophysics Data System (ADS)

Guasch, Teresa; Alvarez, Ibis; Espasa, Anna

This chapter is aimed at presenting an integrated framework of the educational information and communications technology (ICT) competencies that university teachers should have to teach in an online learning environment. Teaching through ICT in higher education involves performing three main roles - pedagogical, socialist, and design/planning - and also two cross-cutting domains that arise from the online environment: technological and managerial. This framework as well as the competencies for university teachers associated with it were validated at a European level by a dual process of net-based focus groups of teachers and teacher trainers in each of the participating countries in a European Project (Elene-TLC) and an online Delphi method involving 78 experts from 14 universities of ten European countries. The competency framework and the examples provided in the chapter are the basis for designing innovative professional development activities in online university environments.

Development of online instructional resources for Earth system science education: An example of current practice from China

NASA Astrophysics Data System (ADS)

Dong, Shaochun; Xu, Shijin; Lu, Xiancai

2009-06-01

Educators around the world are striving to make science more accessible and relevant to students. Online instructional resources have become an integral component of tertiary science education and will continue to grow in influence and importance over the coming decades. A case study in the iterative improvement of the online instructional resources provided for first-year undergraduates taking " Introductory Earth System Science" at Nanjing University in China is presented in this paper. Online instructional resources are used to conduct a student-centered learning model in the domain of Earth system science, resulting in a sustainable online instructional framework for students and instructors. The purpose of our practice is to make Earth system science education more accessible and exciting to students, changing instruction from a largely textbook-based teacher-centered approach to a more interactive and student-centered approach, and promoting the integration of knowledge and development of deep understanding by students. Evaluation on learning performance and learning satisfaction is conducted to identify helpful components and perception based on students' learning activities. The feedbacks indicate that the use of online instructional resources has positive impacts on mitigating Earth system science education challenges, and has the potential to promote deep learning.

Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffing.

PubMed

Hwang, Han-Jeong; Hahne, Janne Mathias; Müller, Klaus-Robert

2017-01-01

There are some practical factors, such as arm position change and donning/doffing, which prevent robust myoelectric control. The objective of this study is to precisely characterize the impacts of the two representative factors on myoelectric controllability in practical control situations, thereby providing useful references that can be potentially used to find better solutions for clinically reliable myoelectric control. To this end, a real-time target acquisition task was performed by fourteen subjects including one individual with congenital upper-limb deficiency, where the impacts of arm position change, donning/doffing and a combination of both factors on control performance was systematically evaluated. The changes in online performance were examined with seven different performance metrics to comprehensively evaluate various aspects of myoelectric controllability. As a result, arm position change significantly affects offline prediction accuracy, but not online control performance due to real-time feedback, thereby showing no significant correlation between offline and online performance. Donning/doffing was still problematic in online control conditions. It was further observed that no benefit was attained when using a control model trained with multiple position data in terms of arm position change, and the degree of electrode shift caused by donning/doffing was not severely associated with the degree of performance loss under practical conditions (around 1 cm electrode shift). Since this study is the first to concurrently investigate the impacts of arm position change and donning/doffing in practical myoelectric control situations, all findings of this study provide new insights into robust myoelectric control with respect to arm position change and donning/doffing.

Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffing

PubMed Central

Hahne, Janne Mathias; Müller, Klaus-Robert

2017-01-01

There are some practical factors, such as arm position change and donning/doffing, which prevent robust myoelectric control. The objective of this study is to precisely characterize the impacts of the two representative factors on myoelectric controllability in practical control situations, thereby providing useful references that can be potentially used to find better solutions for clinically reliable myoelectric control. To this end, a real-time target acquisition task was performed by fourteen subjects including one individual with congenital upper-limb deficiency, where the impacts of arm position change, donning/doffing and a combination of both factors on control performance was systematically evaluated. The changes in online performance were examined with seven different performance metrics to comprehensively evaluate various aspects of myoelectric controllability. As a result, arm position change significantly affects offline prediction accuracy, but not online control performance due to real-time feedback, thereby showing no significant correlation between offline and online performance. Donning/doffing was still problematic in online control conditions. It was further observed that no benefit was attained when using a control model trained with multiple position data in terms of arm position change, and the degree of electrode shift caused by donning/doffing was not severely associated with the degree of performance loss under practical conditions (around 1 cm electrode shift). Since this study is the first to concurrently investigate the impacts of arm position change and donning/doffing in practical myoelectric control situations, all findings of this study provide new insights into robust myoelectric control with respect to arm position change and donning/doffing. PMID:29095846

On-line hemodiafiltration. Gold standard or top therapy?

PubMed

Passlick-Deetjen, Jutta; Pohlmeier, Robert

2002-01-01

In summary, on-line HDF is an extracorporeal blood purification therapy with increased convective removal of uremic toxins as compared to the most frequently used low- or high-flux HD therapy. The clinical advantages of on-line HDF have shown to be dose dependent, which makes on-line HDF superior to other therapies with less convective solute removal. Among the therapies with high convective solute removal, i.e. on-line HDF, on-line HF and double high-flux dialysis, it is difficult to finally decide on the best therapy, as direct comparisons of these therapies are not performed. Theoretical considerations like the relative to on-line HDF lower achievable Kt/Vurea with on-line HF, allow to state that on-line HDF is the top therapy now available for patients with ESRD. A gold standard may be defined as something with which everything else is compared if one tries to establish it in the respective field. In order to declare on-line HDF as the gold standard in renal replacement therapy, we need more direct comparisons of on-line HDF with other therapies, including mortality as an outcome parameter. However, based on our current knowledge, it does not seem to be too speculative that high-quality clinical studies will establish on-line HDF in the next years as the new gold standard in renal replacement therapy.

Online schools and children with special health and educational needs: comparison with performance in traditional schools.

PubMed

Thompson, Lindsay A; Ferdig, Rick; Black, Erik

2012-04-30

In the United States, primary and secondary online schools are institutions that deliver online curricula for children enrolled in kindergarten through 12th grade (K-12). These institutions commonly provide opportunities for online instruction in conjunction with local schools for students who may need remediation, have advanced needs, encounter unqualified local instructors, or experience scheduling conflicts. Internet-based online schooling may potentially help children from populations known to have educational and health disadvantages, such as those from certain racial or ethnic backgrounds, those of low socioeconomic status, and children with special health care needs (CSHCN). To describe the basic and applied demographics of US online-school users and to compare student achievement in traditional versus online schooling environments. We performed a brief parental survey in three states examining basic demographics and educational history of the child and parents, the child's health status as measured by the CSHCN Screener, and their experiences and educational achievement with online schools and class(es). Results were compared with state public-school demographics and statistical analyses controlled for state-specific independence. We analyzed responses from 1971 parents with a response rate of 14.7% (1971/13,384). Parents of online-school participants were more likely to report having a bachelor's degree or higher than were parents of students statewide in traditional schools, and more of their children were white and female. Most notably, the prevalence of CSHCN was high (476/1971, 24.6%) in online schooling. Children who were male, black, or had special health care needs reported significantly lower grades in both traditional and online schools. However, when we controlled for age, gender, race, and parental education, parents of CSHCN or black children reported significantly lower grades in online than in traditional schooling (adjusted odds ratio [aOR] 1.45, 95% confidence interval [CI] 1.29-1.62 for CSHCN, P < .001; aOR 2.73, 95% CI 2.11-3.53 for black children, P < .001.) In contrast, parents with a bachelor's degree or higher reported significantly higher online-school grades than traditional-school grades for their children (aOR 1.45, 95% CI 1.15-1.82, P < .001). The demographics of children attending online schools do not mirror those of the state-specific school populations. CSHCN seem to opt into online schools at a higher rate. While parents report equivalent educational achievement in online and traditional classrooms, controlling for known achievement risks suggests that CSHCN and black children have lower performance in online than in traditional schools. Given the millions of students now in online schools, future studies must test whether direct assistance in online schools, such as taking individualized education plans into consideration, will narrow known disparities in educational success. Only then can online schools emerge as a true educational alternative for at-risk populations.

[Indication and Evidence of Internationally Developed Online Coaches as Intervention for Mental Illness - a Meta-Review].

PubMed

Stein, Janine; Röhr, Susanne; Luck, Tobias; Löbner, Margrit; Riedel-Heller, Steffi G

2018-01-01

The aim of the study was to investigate the current state of research concerning internationally developed Online Coaches for treatment support and prevention of mental disorders. Evidence and effectiveness of the Online Coaches ought to be explored. A systematic literature search was performed in international databases in order to provide a meta-review of existing Online Coaches for mental disorders. The assessment of the methodological quality and evidence of the studies was based on the established guidelines of the Scottish Intercollegiate Guideline Network. 52 studies (24 meta-analyses, 16 systematic reviews, 2 health-technology assessment reports, and 10 RCT studies) were identified. The efficacy was demonstrated for a variety of Online Coaches for mental disorders, especially for anxiety and depressive disorders, insomnia, and post-traumatic stress disorders, with predominantly acceptable and high quality. The present work provides an overview of internationally developed Online Coaches in the field of mental health care. Online Coaches can serve as a useful supplement to the treatment and prevention of mental disorders. © Georg Thieme Verlag KG Stuttgart · New York.

The Task Is Not Enough: Processing Approaches to Task-Based Performance

ERIC Educational Resources Information Center

Skehan, Peter; Xiaoyue, Bei; Qian, Li; Wang, Zhan

2012-01-01

This article reports on three research studies, all of which concern second language task performance. The first focuses on planning, and compares on-line and strategic planning as well as task repetition. The second study examines the role of familiarity on task performance, and compares this with conventional strategic planning. The third study…

PATRON: Using a Multimedia Digital Library for Learning and Teaching in the Performing Arts.

ERIC Educational Resources Information Center

Lyon, Elizabeth

The creation and application of a multimedia digital library to support learning and teaching in the performing arts is described. PATRON (Performing Arts Teaching Resources Online) delivers audio, video, music scores, dance notation, and theater scripts to the desktop via an innovative Web-based interface. Digital objects are linked subjectively…

Assessment without Testing: Using Performance Measures Embedded in a Technology-Based Instructional Program as Indicators of Reading Ability

ERIC Educational Resources Information Center

Mitchell, Alison; Baron, Lauren; Macaruso, Paul

2018-01-01

Screening and monitoring student reading progress can be costly and time consuming. Assessment embedded within the context of online instructional programs can capture ongoing student performance data while limiting testing time outside of instruction. This paper presents two studies that examined the validity of using performance measures from a…

Gas Path On-line Fault Diagnostics Using a Nonlinear Integrated Model for Gas Turbine Engines

NASA Astrophysics Data System (ADS)

Lu, Feng; Huang, Jin-quan; Ji, Chun-sheng; Zhang, Dong-dong; Jiao, Hua-bin

2014-08-01

Gas turbine engine gas path fault diagnosis is closely related technology that assists operators in managing the engine units. However, the performance gradual degradation is inevitable due to the usage, and it result in the model mismatch and then misdiagnosis by the popular model-based approach. In this paper, an on-line integrated architecture based on nonlinear model is developed for gas turbine engine anomaly detection and fault diagnosis over the course of the engine's life. These two engine models have different performance parameter update rate. One is the nonlinear real-time adaptive performance model with the spherical square-root unscented Kalman filter (SSR-UKF) producing performance estimates, and the other is a nonlinear baseline model for the measurement estimates. The fault detection and diagnosis logic is designed to discriminate sensor fault and component fault. This integration architecture is not only aware of long-term engine health degradation but also effective to detect gas path performance anomaly shifts while the engine continues to degrade. Compared to the existing architecture, the proposed approach has its benefit investigated in the experiment and analysis.

A Comparison of Mobile and Fixed Device Access on User Engagement Associated With Women, Infants, and Children (WIC) Online Nutrition Education

PubMed Central

2016-01-01

Background Online health education has expanded its reach due to cost-effective implementation and demonstrated effectiveness. However, a limitation exists with the evaluation of online health education implementations and how the impact of the system is attenuated by the extent to which a user engages with it. Moreover, the current online health education research does not consider how this engagement has been affected by the transition from fixed to mobile user access over the last decade. Objective This paper focuses on comparing the impact mobile versus fixed devices have on user engagement key performance indicators (KPI) associated with the wichealth website (.org), an Internet-based parent-child feeding intervention offered to clients associated with the US Department of Agriculture’s Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Methods Data were collected from 612,201 nutrition education lessons completed by 305,735 unique WIC participants in 21 states over a 1-year period. Data consisted of system-collected measures, profile items, and items from an exit survey administered at the conclusion of each lesson. User engagement was defined based on 3 KPIs associated with usage of the wichealth website: number of link views, link view time, and progression in stage of readiness to change. Independent samples t tests were used to compare KPIs between fixed only and mobile only device users and paired samples t tests were used to compare KPIs within users who completed at least one lesson each on both a fixed and mobile device. A logistic regression was performed to estimate the odds of KPI performance thresholds in the independent samples study group given access device type while controlling for confounding of user characteristics associated with these KPIs. Results Analysis of 8 user characteristics (lessons completed, race, ethnicity, language, state of residence, pregnancy status, beginning stage of change, and preferred nutrition education method) were significantly (P<.001) related to various KPI differences between mobile and fixed device access. Non-mobile users were significantly (P<.001) more likely to engage based on all 3 KPIs, even after logistic regression control for the potential confounding related to the strongly associated user characteristics identified. Conclusions The findings of this study support the idea that online health education developers need to seriously consider access device when creating programs. Online health education developers need to take extra effort to truly understand access patterns of populations being served, and whether or not access device will influence user engagement performance indicators. PMID:27847351

Ability of physicians to diagnose and manage illness due to category A bioterrorism agents.

PubMed

Cosgrove, Sara E; Perl, Trish M; Song, Xiaoyan; Sisson, Stephen D

2005-09-26

Early recognition of a terrorist attack with biologic agents will rely on physician diagnosis. Physicians' ability to diagnose and care for patients presenting after a bioterror event is unknown. The role of online case-based didactics to measure and improve knowledge in the diagnosis and treatment of these patients is unknown. A multicenter online educational intervention was completed by 631 physicians at 30 internal medicine residency programs in 16 states and Washington, DC, between July 1, 2003, and June 10, 2004. Participants completed a pretest, assessing ability to diagnose and manage potential cases of smallpox, anthrax, botulism, and plague. A didactic module reviewing diagnosis and management of these diseases was then completed, followed by a posttest. Pretest performance measured baseline knowledge. Posttest performance compared with pretest performance measured effectiveness of the educational intervention. Results were compared based on year of training and geographic location of the residency program. Correct diagnoses of diseases due to bioterrorism agents were as follows: smallpox, 50.7%; anthrax, 70.5%; botulism, 49.6%; and plague, 16.3% (average, 46.8%). Correct diagnosis averaged 79.0% after completing the didactic module (P<.001). Correct management of smallpox was 14.6%; anthrax, 17.0%; botulism, 60.2%; and plague, 9.7% (average, 25.4%). Correct management averaged 79.1% after completing the didactic module (P<.001). Performance did not differ based on year of training (P = .54) or geographic location (P = .64). Attending physicians performed better than residents (P<.001). Physician diagnosis and management of diseases caused by bioterrorism agents is poor. An online didactic module may improve diagnosis and management of diseases caused by these agents.

Monitoring the CMS strip tracker readout system

NASA Astrophysics Data System (ADS)

Mersi, S.; Bainbridge, R.; Baulieu, G.; Bel, S.; Cole, J.; Cripps, N.; Delaere, C.; Drouhin, F.; Fulcher, J.; Giassi, A.; Gross, L.; Hahn, K.; Mirabito, L.; Nikolic, M.; Tkaczyk, S.; Wingham, M.

2008-07-01

The CMS Silicon Strip Tracker at the LHC comprises a sensitive area of approximately 200 m2 and 10 million readout channels. Its data acquisition system is based around a custom analogue front-end chip. Both the control and the readout of the front-end electronics are performed by off-detector VME boards in the counting room, which digitise the raw event data and perform zero-suppression and formatting. The data acquisition system uses the CMS online software framework to configure, control and monitor the hardware components and steer the data acquisition. The first data analysis is performed online within the official CMS reconstruction framework, which provides many services, such as distributed analysis, access to geometry and conditions data, and a Data Quality Monitoring tool based on the online physics reconstruction. The data acquisition monitoring of the Strip Tracker uses both the data acquisition and the reconstruction software frameworks in order to provide real-time feedback to shifters on the operational state of the detector, archiving for later analysis and possibly trigger automatic recovery actions in case of errors. Here we review the proposed architecture of the monitoring system and we describe its software components, which are already in place, the various monitoring streams available, and our experiences of operating and monitoring a large-scale system.

An Electronic Library-Based Learning Environment for Supporting Web-Based Problem-Solving Activities

ERIC Educational Resources Information Center

Tsai, Pei-Shan; Hwang, Gwo-Jen; Tsai, Chin-Chung; Hung, Chun-Ming; Huang, Iwen

2012-01-01

This study aims to develop an electronic library-based learning environment to support teachers in developing web-based problem-solving activities and analyzing the online problem-solving behaviors of students. Two experiments were performed in this study. In study 1, an experiment on 103 elementary and high school teachers (the learning activity…

Implementing the Flipped Classroom in a Veterinary Pre-clinical Science Course: Student Engagement, Performance, and Satisfaction.

PubMed

Dooley, Laura M; Frankland, Sarah; Boller, Elise; Tudor, Elizabeth

2018-01-01

There has been a recent move toward active learning pedagogies in veterinary education, with increasing use of a blended approach that incorporates both online resources and live classroom sessions. In this study, an established veterinary pre-clinical course in introductory animal health was transitioned from a traditional didactic lecture delivery mode to a flipped classroom approach with core content delivered online. This study compared the experiences of two cohorts of students who studied the same course in the different formats in consecutive years. Online learning resources included short video segments and a variety of short problems and activities. Online materials were complemented with weekly small-group case-based learning classes facilitated by academic staff. A mixed methods evaluation strategy was applied using student grades, surveys, and focus groups to compare student academic performance, satisfaction, and engagement between the two cohorts. The flipped classroom cohort achieved significantly higher grades in the written answer section of the final examination. Student satisfaction with learning resources was also higher in this cohort. However, satisfaction with other aspects of the course was largely the same for both cohorts. This study revealed some of the challenges associated with achieving adequate student preparation for class using online resources. The outcomes of this study have implications for veterinary educators considering the design and development of new online learning resources.

Do Health Care Providers Use Online Patient Ratings to Improve the Quality of Care? Results From an Online-Based Cross-Sectional Study.

PubMed

Emmert, Martin; Meszmer, Nina; Sander, Uwe

2016-09-19

Physician-rating websites have become a popular tool to create more transparency about the quality of health care providers. So far, it remains unknown whether online-based rating websites have the potential to contribute to a better standard of care. Our goal was to examine which health care providers use online rating websites and for what purposes, and whether health care providers use online patient ratings to improve patient care. We conducted an online-based cross-sectional study by surveying 2360 physicians and other health care providers (September 2015). In addition to descriptive statistics, we performed multilevel logistic regression models to ascertain the effects of providers' demographics as well as report card-related variables on the likelihood that providers implement measures to improve patient care. Overall, more than half of the responding providers surveyed (54.66%, 1290/2360) used online ratings to derive measures to improve patient care (implemented measures: mean 3.06, SD 2.29). Ophthalmologists (68%, 40/59) and gynecologists (65.4%, 123/188) were most likely to implement any measures. The most widely implemented quality measures were related to communication with patients (28.77%, 679/2360), the appointment scheduling process (23.60%, 557/2360), and office workflow (21.23%, 501/2360). Scaled-survey results had a greater impact on deriving measures than narrative comments. Multilevel logistic regression models revealed medical specialty, the frequency of report card use, and the appraisal of the trustworthiness of scaled-survey ratings to be significantly associated predictors for implementing measures to improve patient care because of online ratings. Our results suggest that online ratings displayed on physician-rating websites have an impact on patient care. Despite the limitations of our study and unintended consequences of physician-rating websites, they still may have the potential to improve patient care.

Effectiveness of Simulation in a Hybrid and Online Networking Course.

ERIC Educational Resources Information Center

Cameron, Brian H.

2003-01-01

Reports on a study that compares the performance of students enrolled in two sections of a Web-based computer networking course: one utilizing a simulation package and the second utilizing a static, graphical software package. Analysis shows statistically significant improvements in performance in the simulation group compared to the…

Pricing strategies, the strength of bidding intentions, and online auction performance: a cross-cultural study.

PubMed

Peng, Yu-Shu; Jan, Lih-Tsyr

2009-10-01

Over the past decade, electronic markets based on the Internet, particularly online auctions, have become popular venues for conducting business. Previous studies often focused on the construction of the best bidding model, while few studies have tried to integrate multiple pricing strategies to predict the probability of closing an auction and the price premium. This study constructs a mediated model to examine the relationship among pricing strategies, the strength of bidding intentions, and online auction performance. The sample consists of 1,055 auctions of iPod MP3 players from eBay Web sites in Hong Kong, Singapore, Belgium, and France. Empirical results show that the pricing strategies directly influence both the probability of closing an auction and the level of price premium. The pricing strategies also indirectly influence the price premium through the mediating effect of the strength of bidding intentions.

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

A monolithic column based on covalent cross-linked polymer gels for online extraction and analysis of trace aflatoxins in food sample.

PubMed

Wei, Tianfu; Chen, Zhengyi; Li, Gongke; Zhang, Zhuomin

2018-05-04

Aflatoxins are highly toxic mycotoxin contamination, which pose serious food safety incidents. It is very important to precisely and rapidly determine trace aflatoxins in food. In this study, we designed porous monolithic column based on covalent cross-linked polymer gels for online extraction and analysis of trace aflatoxins in food samples with complicated matrices coupled with high-performance liquid chromatography-ultraviolet detector (HPLC-UV). The prepared monolithic column showed excellent enrichment performance due to its good permeability, good reproducibility and long life span. The study of adsorption mechanism suggested that the excellent enrichment performance of this monolithic column was attributed to the multiple effect of π-π stacking interaction, hydrophobic effect and steric effect. When the online analytical method was applied for the determine of trace aflatoxins in real food samples, aflatoxins G 1 and aflatoxins B 1 could be actually found in one positive bean sauce sample and quantified to be 32.8 and 26.4 μg/kg, respectively. Aflatoxins G 1 in one bean sample could be also found and quantified to be 25.9 μg/kg. The low detection limits of the developed method were achieved in range of 0.08-0.2 μg/kg. And the recoveries for spiked samples were in range from 76.1 to 113% with RSDs of 1.1-9.6%. The developed method was proved to be a promising method for online enrichment and analysis of trace aflatoxins in complicated food samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Arduino-based noise robust online heart-rate detection.

PubMed

Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

2017-04-01

This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

Integration of the work-related online aftercare intervention 'GSA-online plus' (healthy and without stress at the workplace) into clinical practice: study protocol for an implementation study.

PubMed

Zwerenz, Rüdiger; Böhme, Katja; Wirth, Astrid; Labitzke, Nicole; Pachtchenko, Sergei; Beutel, Manfred E

2018-05-02

In a previous RCT we established the efficacy of the psychodynamic online aftercare programme 'GSA-Online' ('Health Training Stress Management at the Workplace') for rehabilitants with work-related stress facing return to work after long-term sickness absence. The purpose of this trial is to implement it into routine care. The study is performed in rehabilitation clinics with patients of different medical indications (psychosomatic, orthopedic and cardiological diseases). Rehabilitants get access to the study platform during inpatient medical rehabilitation. 'GSA-Online plus' integrates exploratory and motivational videos on the web application to familiarize potential participants and motivate them to follow through with it. In the 12-week writing intervention, patients write weekly online diary entries, answered by anonymous online therapists within 24 h. Primary outcome measures are the recommendation rate of 'GSA-Online plus' and participation rates of the rehabilitants. As secondary outcomes, psychological symptoms, overall satisfaction, helpfulness of the therapeutic feedback and utilization of 'GSA-Online plus' will be analysed exploratory along with the course of weekly ratings of well-being and work ability. Meanwhile many clinical trials and meta-analysis prove that internet-based interventions are effective. This study will add insights on the dissemination and implementation of efficacious, evidence-based online treatments into medical practice. We expect a successful implementation of 'GSA-Online plus' in the clinical routine of the rehabilitation clinics. The focus of evaluation is on acceptance of the programme, both by the physicians in charge and the patients. In the future 'GSA-Online plus' could be implemented as a routine aftercare programme for rehabilitation inpatients with occupational stress. The trial was retrospectively registered on 6th January 2017 at ClinicalTrials.gov (Trial Registration number: ClinicalTrials Gov ID NCT03019718 ).

A web-based referral system for neurosurgery--a solution to our problems?

PubMed

Choo, Melissa C; Thennakon, Shyamica; Shapey, Jonathan; Tolias, Christos M

2011-06-01

Accurate handover is very important in the running of all modern neurosurgical units. Referrals are notoriously difficult to track and review due to poor quality of written paper-based recorded information for handover (illegibility, incomplete paper trail, repetition of information and loss of patients). We have recently introduced a web-based referral system to three of our referring hospitals. To review the experience of a tertiary neurosurgical unit in using the UK's first real time online referral system and to discuss its strengths and weaknesses in comparison to the currently used written paper-based referral system. A retrospective analysis of all paper-based referrals made to our unit in March 2009, compared to 14 months' referrals through the web system. Patterns of information recorded in both systems were investigated and advantages and disadvantages of each identified. One hundred ninety-six patients were referred using the online system, 483 using the traditional method. Significant problems of illegibility and missing information were identified with the paper-based referrals. In comparison, 100% documentation was achieved with the online referral system. Only 63% penetrance in the best performing trust was found using the online system, with significant delays in responding to referrals. Traditional written paper-based referrals do not provide an acceptable level of documentation. We present our experience and difficulties implementing a web-based system to address this. Although our data are unable to show improved patient care, we believe the potential benefits of a fully integrated system may offer a solution.

Computer aided statistical process control for on-line instrumentation

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

Meils, D.E.

1995-01-01

On-line chemical process instrumentation historically has been used for trending. Recent technological advances in on-line instrumentation have improved the accuracy and reliability of on-line instrumentation. However, little attention has been given to validating and verifying on-line instrumentation. This paper presents two practical approaches for validating instrument performance by comparison of on-line instrument response to either another portable instrument or another bench instrument. Because the comparison of two instruments` performance to each other requires somewhat complex statistical calculations, a computer code (Lab Stats Pack{reg_sign}) is used to simplify the calculations. Lab Stats Pack{reg_sign} also develops control charts that may be usedmore » for continuous verification of on-line instrument performance.« less

Does self-selection affect samples' representativeness in online surveys? An investigation in online video game research.

PubMed

Khazaal, Yasser; van Singer, Mathias; Chatton, Anne; Achab, Sophia; Zullino, Daniele; Rothen, Stephane; Khan, Riaz; Billieux, Joel; Thorens, Gabriel

2014-07-07

The number of medical studies performed through online surveys has increased dramatically in recent years. Despite their numerous advantages (eg, sample size, facilitated access to individuals presenting stigmatizing issues), selection bias may exist in online surveys. However, evidence on the representativeness of self-selected samples in online studies is patchy. Our objective was to explore the representativeness of a self-selected sample of online gamers using online players' virtual characters (avatars). All avatars belonged to individuals playing World of Warcraft (WoW), currently the most widely used online game. Avatars' characteristics were defined using various games' scores, reported on the WoW's official website, and two self-selected samples from previous studies were compared with a randomly selected sample of avatars. We used scores linked to 1240 avatars (762 from the self-selected samples and 478 from the random sample). The two self-selected samples of avatars had higher scores on most of the assessed variables (except for guild membership and exploration). Furthermore, some guilds were overrepresented in the self-selected samples. Our results suggest that more proficient players or players more involved in the game may be more likely to participate in online surveys. Caution is needed in the interpretation of studies based on online surveys that used a self-selection recruitment procedure. Epidemiological evidence on the reduced representativeness of sample of online surveys is warranted.

On-line evaluation of multiloop digital controller performance

NASA Technical Reports Server (NTRS)

Wieseman, Carol D.

1993-01-01

The purpose of this presentation is to inform the Guidance and Control community of capabilities which were developed by the Aeroservoelasticity Branch to evaluate the performance of multivariable control laws, on-line, during wind-tunnel testing. The capabilities are generic enough to be useful for all kinds of on-line analyses involving multivariable control in experimental testing. Consequently, it was decided to present this material at this workshop even though it has been presented elsewhere. Topics covered include: essential on-line analysis requirements; on-line analysis capabilities; on-line analysis software; frequency domain procedures; controller performance evaluation frequency-domain flutter suppression; and plant determination.

77 FR 38581 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

...: Minority Business Development Agency. Title: Online Customer Relationship Management (CRM)/Performance... client information, service activities and progress on attainment of program goals via the Online CRM/Performance Databases. The data collected through the Online CRM/Performance Databases is used to regularly...

Exploring the relation between online case-based discussions and learning outcomes in dental education.

PubMed

Koole, Sebastiaan; Vervaeke, Stijn; Cosyn, Jan; De Bruyn, Hugo

2014-11-01

Online case-based discussions, parallel to theoretical dental education, have been highly valued by students and supervisors. This study investigated the relation between variables of online group discussions and learning outcomes. At Ghent University in Belgium, undergraduate dental students (years two and three) are required to participate in online case-based discussion groups (five students/group) in conjunction with two theoretical courses on basic periodontics and related therapy. Each week, a patient case is discussed under supervision of a periodontist, who authored the case and performed the treatment. Each case includes treatment history and demand, intra- and extraoral images, and full diagnostic information with periodontal and radiographic status. For this retrospective study, data were obtained for all 252 students in forty-three discussion groups between 2009 and 2012. Spearman's rank correlations were calculated to investigate the relation among group dynamics (number of group posts and views), individual student contributions (number of individual posts, newly introduced elements, questions, and reactions to other posts), supervisors' interventions (number of posts and posed questions), and learning outcomes (examination result). The results showed that learning outcomes were significantly related to the number of student posts (Spearman's rho (ρ)=0.19), newly introduced elements (ρ=0.21), reactions to other posts (ρ=0.14), number of supervisors' interventions (ρ=0.12), and supervisors' questions (ρ=0.20). These results suggest that individual student contributions during online case-based discussions and the provided supervision were related to learning outcomes.

Secure access control and large scale robust representation for online multimedia event detection.

PubMed

Liu, Changyu; Lu, Bin; Li, Huiling

2014-01-01

We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.

Acylhydrazone bond dynamic covalent polymer gel monolithic column online coupling to high-performance liquid chromatography for analysis of sulfonamides and fluorescent whitening agents in food.

PubMed

Zhang, Chengjiang; Luo, Xialin; Wei, Tianfu; Hu, Yufei; Li, Gongke; Zhang, Zhuomin

2017-10-13

A new dynamic covalent polymer (DCP) gel was well designed and constructed based on imine chemistry. Polycondensation of 4,4'-biphenyldicarboxaldehyde and 1,3,5-benzenetricarbohydrazide via Schiff-base reaction resulted in an acylhydrazone bond gel (AB-gel) DCP. AB-gel DCP had three-dimensional network of interconnected nanoparticles with hierarchically porous structure. AB-gel DCP was successfully fabricated as a monolithic column by an in-situ chemical bonding method for online enrichment and separation purpose with excellent permeability. AB-gel DCP based monolithic column showed remarkable adsorption affinity towards target analytes including sulfonamides (SAs) and fluorescent whitening agents (FWAs) due to its strong π-π affinity, hydrophobic effect and hydrogen bonding interaction. Then, AB-gel DCP based monolithic column was applied for online separation and analysis of trace SAs and FWAs in food samples coupled with high-performance liquid chromatography (HPLC). Sulfathiazole (ST) and sulfadimidine (SM2) in one positive weever sample were actually found and determined with concentrations of 273.8 and 286.3μg/kg, respectively. 2,5-Bis(5-tert-butyl-2-benzoxazolyl) thiophene (FWA184) was actually quantified in one tea infusion sample with the concentration of 268.5ng/L. The spiked experiments suggested the good recoveries in range of 74.5-110% for SAs in weever and shrimp samples with relative standard deviations (RSDs) less than 9.7% and in range of 74.0-113% for FWAs in milk and tea infusion samples with RSDs less than 9.0%. AB-gel DCP monolithic column was proved to be a promising sample preparation medium for online separation and analysis of trace analytes in food samples with complex matrices. Copyright © 2017 Elsevier B.V. All rights reserved.

The Web Resource Collaboration Center

ERIC Educational Resources Information Center

Dunlap, Joanna C.

2004-01-01

The Web Resource Collaboration Center (WRCC) is a web-based tool developed to help software engineers build their own web-based learning and performance support systems. Designed using various online communication and collaboration technologies, the WRCC enables people to: (1) build a learning and professional development resource that provides…

On-line implementation of nonlinear parameter estimation for the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Buckland, Julia H.; Musgrave, Jeffrey L.; Walker, Bruce K.

1992-01-01

We investigate the performance of a nonlinear estimation scheme applied to the estimation of several parameters in a performance model of the Space Shuttle Main Engine. The nonlinear estimator is based upon the extended Kalman filter which has been augmented to provide estimates of several key performance variables. The estimated parameters are directly related to the efficiency of both the low pressure and high pressure fuel turbopumps. Decreases in the parameter estimates may be interpreted as degradations in turbine and/or pump efficiencies which can be useful measures for an online health monitoring algorithm. This paper extends previous work which has focused on off-line parameter estimation by investigating the filter's on-line potential from a computational standpoint. ln addition, we examine the robustness of the algorithm to unmodeled dynamics. The filter uses a reduced-order model of the engine that includes only fuel-side dynamics. The on-line results produced during this study are comparable to off-line results generated previously. The results show that the parameter estimates are sensitive to dynamics not included in the filter model. Off-line results using an extended Kalman filter with a full order engine model to address the robustness problems of the reduced-order model are also presented.

Bio-inspired online variable recruitment control of fluidic artificial muscles

NASA Astrophysics Data System (ADS)

Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

2016-12-01

This paper details the creation of a hybrid variable recruitment control scheme for fluidic artificial muscle (FAM) actuators with an emphasis on maximizing system efficiency and switching control performance. Variable recruitment is the process of altering a system’s active number of actuators, allowing operation in distinct force regimes. Previously, FAM variable recruitment was only quantified with offline, manual valve switching; this study addresses the creation and characterization of novel, on-line FAM switching control algorithms. The bio-inspired algorithms are implemented in conjunction with a PID and model-based controller, and applied to a simulated plant model. Variable recruitment transition effects and chatter rejection are explored via a sensitivity analysis, allowing a system designer to weigh tradeoffs in actuator modeling, algorithm choice, and necessary hardware. Variable recruitment is further developed through simulation of a robotic arm tracking a variety of spline position inputs, requiring several levels of actuator recruitment. Switching controller performance is quantified and compared with baseline systems lacking variable recruitment. The work extends current variable recruitment knowledge by creating novel online variable recruitment control schemes, and exploring how online actuator recruitment affects system efficiency and control performance. Key topics associated with implementing a variable recruitment scheme, including the effects of modeling inaccuracies, hardware considerations, and switching transition concerns are also addressed.

ALICE HLT Run 2 performance overview.

NASA Astrophysics Data System (ADS)

Krzewicki, Mikolaj; Lindenstruth, Volker; ALICE Collaboration

2017-10-01

For the LHC Run 2 the ALICE HLT architecture was consolidated to comply with the upgraded ALICE detector readout technology. The software framework was optimized and extended to cope with the increased data load. Online calibration of the TPC using online tracking capabilities of the ALICE HLT was deployed. Offline calibration code was adapted to run both online and offline and the HLT framework was extended to support that. The performance of this schema is important for Run 3 related developments. An additional data transport approach was developed using the ZeroMQ library, forming at the same time a test bed for the new data flow model of the O2 system, where further development of this concept is ongoing. This messaging technology was used to implement the calibration feedback loop augmenting the existing, graph oriented HLT transport framework. Utilising the online reconstruction of many detectors, a new asynchronous monitoring scheme was developed to allow real-time monitoring of the physics performance of the ALICE detector, on top of the new messaging scheme for both internal and external communication. Spare computing resources comprising the production and development clusters are run as a tier-2 GRID site using an OpenStack-based setup. The development cluster is running continuously, the production cluster contributes resources opportunistically during periods of LHC inactivity.

Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation

NASA Astrophysics Data System (ADS)

Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada

We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

Students in Fully Online Programs Report More Positive Attitudes toward Science Than Students in Traditional, In-Person Programs

PubMed Central

Perera, Viranga; Mead, Chris; Buxner, Sanlyn; Lopatto, David; Horodyskyj, Lev; Semken, Steven; Anbar, Ariel D.

2017-01-01

Following the growth of online, higher-education courses, academic institutions are now offering fully online degree programs. Yet it is not clear how students who enroll in fully online degree programs are similar to those students who enroll in in-person (“traditional”) degree programs. Because previous work has shown students’ attitudes toward science can affect their performance in a course, it is valuable to ask how attitudes toward science differ between these two populations. We studied students who completed a fully online astrobiology course. In an analysis of 451 student responses to the Classroom Undergraduate Research Experience survey, we found online program students began the course with a higher scientific sophistication and a higher sense of personal value of science than those in traditional programs. Precourse attitudes also showed some predictive power of course grades among online students, but not for traditional students. Given established relationships between feelings of personal value, intrinsic motivation, and, in turn, traits such as persistence, our results suggest that open-ended or exploration-based learning may be more engaging to online program students due to their pre-existing attitudes. The converse may also be true, that certain pre-existing attitudes among online program students are more detrimental than they are for traditional program students. PMID:29146666

Log-polar mapping-based scale space tracking with adaptive target response

NASA Astrophysics Data System (ADS)

Li, Dongdong; Wen, Gongjian; Kuai, Yangliu; Zhang, Ximing

2017-05-01

Correlation filter-based tracking has exhibited impressive robustness and accuracy in recent years. Standard correlation filter-based trackers are restricted to translation estimation and equipped with fixed target response. These trackers produce an inferior performance when encountered with a significant scale variation or appearance change. We propose a log-polar mapping-based scale space tracker with an adaptive target response. This tracker transforms the scale variation of the target in the Cartesian space into a shift along the logarithmic axis in the log-polar space. A one-dimensional scale correlation filter is learned online to estimate the shift along the logarithmic axis. With the log-polar representation, scale estimation is achieved accurately without a multiresolution pyramid. To achieve an adaptive target response, a variance of the Gaussian function is computed from the response map and updated online with a learning rate parameter. Our log-polar mapping-based scale correlation filter and adaptive target response can be combined with any correlation filter-based trackers. In addition, the scale correlation filter can be extended to a two-dimensional correlation filter to achieve joint estimation of the scale variation and in-plane rotation. Experiments performed on an OTB50 benchmark demonstrate that our tracker achieves superior performance against state-of-the-art trackers.

Microwave-assisted extraction coupled online with derivatization, restricted access material cleanup, and high-performance liquid chromatography for determination of formaldehyde in aquatic products.

PubMed

Chen, Ligang; Jin, Haiyan; Xu, Haoyan; Sun, Lei; Yu, Aimin; Zhang, Hanqi; Ding, Lan

2009-05-27

A rapid technique based on microwave-assisted extraction (MAE) coupled online with derivatization, restricted access material cleanup, and high-performance liquid chromatography (HPLC) was developed for the determination of formaldehyde in aquatic products. Formaldehyde was first extracted with water under the action of microwaves and then directly introduced into a derivatization reservoir containing 2,4-dinitrophenylhydrazine (DNPH). The formaldehyde-DNPH derivative (100 μL) was loaded into a restricted access material (RAM) precolumn for online cleanup. Subsequently, the analyte was transferred from the precolumn to an analytical column and determined by UV absorption spectrum at 352 nm. The limit of detection (LOD) was 0.27 mg kg(-1). The intraday and interday precisions expressed as RSDs were 3.5% and 5.0%, respectively. This method was applied to determine the presence of formaldehyde in various aquatic products. The results were in agreement with those obtained by the state standard method (steam-distillation and offline HPLC analysis) used in China and higher than those obtained by the online ultrasound-assisted extraction (UAE) method. The recoveries obtained by analyzing 11 spiked aquatic products were in the range of 70.0%-105.0%. The online technique was demonstrated to be rapid with little consumption of samples and reagents.

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

Evaluation of the online-presence (homepage) of burn units/burn centers in Germany, Austria and Switzerland.

PubMed

Selig, H F; Lumenta, D B; König, C; Andel, H; Kamolz, L P

2012-05-01

A successful online presence is an important key factor in the competition among hospitals today. However, little is known about the internet presence and the quality of websites of burn units on the World Wide Web. The aim was to assess the online presence of hospitals provided by specialized burn units in German speaking countries with a focus on the rate and the performance of actively run websites. A multicenter, observational, cross-sectional study was performed over a period of 1.5 month (October-December 2010). Forty-four burn units were assessed by using a previously generated criteria list. The list included 36 criteria with following topics: "research and teaching"; "patient care"; "clinical emphases", "general information"; "information brokerage". Overall, the websites examined offered a good overview about their different online services with many multimedia-based elements included. All websites consisted of hyperlinks, general multimedia-based elements and information on means of communication with the hospital, respectively. In contrast, the quality of specific information for burn patients was relatively poor. With regard to the need of elderly people, the usability and the layout, the different websites offer a lot of options for future improvements. Burn centers in Germany, Austria and Switzerland already consider the World Wide Web as an important tool for self-promotion and communication. The potential of burn center websites to function as a knowledge base for first aid as well as preventive measurements should be considered and realized in future web site designs. Copyright © 2011 Elsevier Ltd and ISBI. All rights reserved.

ATLAS tile calorimeter cesium calibration control and analysis software

NASA Astrophysics Data System (ADS)

Solovyanov, O.; Solodkov, A.; Starchenko, E.; Karyukhin, A.; Isaev, A.; Shalanda, N.

2008-07-01

An online control system to calibrate and monitor ATLAS Barrel hadronic calorimeter (TileCal) with a movable radioactive source, driven by liquid flow, is described. To read out and control the system an online software has been developed, using ATLAS TDAQ components like DVS (Diagnostic and Verification System) to verify the hardware before running, IS (Information Server) for data and status exchange between networked computers, and other components like DDC (DCS to DAQ Connection), to connect to PVSS-based slow control systems of Tile Calorimeter, high voltage and low voltage. A system of scripting facilities, based on Python language, is used to handle all the calibration and monitoring processes from hardware perspective to final data storage, including various abnormal situations. A QT based graphical user interface to display the status of the calibration system during the cesium source scan is described. The software for analysis of the detector response, using online data, is discussed. Performance of the system and first experience from the ATLAS pit are presented.

An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

NASA Technical Reports Server (NTRS)

imon, Donald L.; Armstrong, Jeffrey B.

2012-01-01

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

On-Line Model-Based System For Nuclear Plant Monitoring

NASA Astrophysics Data System (ADS)

Tsoukalas, Lefteri H.; Lee, G. W.; Ragheb, Magdi; McDonough, T.; Niziolek, F.; Parker, M.

1989-03-01

A prototypical on-line model-based system, LASALLE1, developed at the University of Illinois in collaboration with the Illinois Department of Nuclear Safety (IDNS) is described. Its main purpose is to interpret about 300 signals, updated every two minutes at IDNS from the LaSalle Nuclear Power Plant, and to diagnose possible abnormal conditions. It is written in VAX/VMS OPS5 and operates on both the on-line and testing modes. In its knowledge base, operator and plant actions pertaining to the Emergency Operating Procedure(EOP) A-01, are encoded. This is a procedure driven by a reactor's coolant level and pressure signals; with the purpose of shutting down the reactor, maintaining adequate core cooling and reducing the reactor pressure and temperature to cold shutdown conditions ( about 90 to 200 °F). The monitoring of the procedure is performed from the perspective of Emergency Preparedness. Two major issues are addressed in this system. First, the management of the short-term or working memory of the system. LASALLE1 must reach its inferences, display its conclusion and update a message file every two minutes before a new set of data arrives from the plant. This was achieved by superimposing additional layers of control over the inferencing strategies inherent in OPS5, and developing special rules for the management of the used or outdated information. The second issue is the representation of information and its uncertainty. The concepts of information granularity and performance-level, which are based on a coupling of Probability Theory and the theory of Fuzzy Sets, are used for this purpose. The estimation of the performance-level incorporates a mathematical methodology which accounts for two types of uncertainty encountered in monitoring physical systems: Random uncertainty, in the form of of probability density functions generated by observations, measurements and sensors data and fuzzy uncertainty represented by membership functions based on symbolic , stochastic or numerical models estimating the "plausible", "possible" or "expected" values of the system parameters. Examples from both the on-line mode and the testing mode of the system will be discussed to illustrate the present methodology.

On-line Tool Wear Detection on DCMT070204 Carbide Tool Tip Based on Noise Cutting Audio Signal using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Prasetyo, T.; Amar, S.; Arendra, A.; Zam Zami, M. K.

2018-01-01

This study develops an on-line detection system to predict the wear of DCMT070204 tool tip during the cutting process of the workpiece. The machine used in this research is CNC ProTurn 9000 to cut ST42 steel cylinder. The audio signal has been captured using the microphone placed in the tool post and recorded in Matlab. The signal is recorded at the sampling rate of 44.1 kHz, and the sampling size of 1024. The recorded signal is 110 data derived from the audio signal while cutting using a normal chisel and a worn chisel. And then perform signal feature extraction in the frequency domain using Fast Fourier Transform. Feature selection is done based on correlation analysis. And tool wear classification was performed using artificial neural networks with 33 input features selected. This artificial neural network is trained with back propagation method. Classification performance testing yields an accuracy of 74%.

A visual tracking method based on improved online multiple instance learning

NASA Astrophysics Data System (ADS)

He, Xianhui; Wei, Yuxing

2016-09-01

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

Support for Online Calibration in the ALICE HLT Framework

NASA Astrophysics Data System (ADS)

Krzewicki, Mikolaj; Rohr, David; Zampolli, Chiara; Wiechula, Jens; Gorbunov, Sergey; Chauvin, Alex; Vorobyev, Ivan; Weber, Steffen; Schweda, Kai; Shahoyan, Ruben; Lindenstruth, Volker; ALICE Collaboration

2017-10-01

The ALICE detector employs sub detectors sensitive to environmental conditions such as pressure and temperature, e.g. the time projection chamber (TPC). A precise reconstruction of particle trajectories requires precise calibration of these detectors. Performing the calibration in real time in the HLT improves the online reconstruction and potentially renders certain offline calibration steps obsolete, speeding up offline physics analysis. For LHC Run 3, starting in 2020 when data reduction will rely on reconstructed data, online calibration becomes a necessity. In order to run the calibration online, the HLT now supports the processing of tasks that typically run offline. These tasks run massively in parallel on all HLT compute nodes and their output is gathered and merged periodically. The calibration results are both stored offline for later use and fed back into the HLT chain via a feedback loop in order to apply calibration information to the online track reconstruction. Online calibration and feedback loop are subject to certain time constraints in order to provide up-to-date calibration information and they must not interfere with ALICE data taking. Our approach to run these tasks in asynchronous processes enables us to separate them from normal data taking in a way that makes it failure resilient. We performed a first test of online TPC drift time calibration under real conditions during the heavy-ion run in December 2015. We present an analysis and conclusions of this first test, new improvements and developments based on this, as well as our current scheme to commission this for production use.

Evaluating the Performance of Online K-12 Schools

ERIC Educational Resources Information Center

Carpenter, Dick; Kafer, Krista; Reeser, Kelly; Shafer, Sheryl

2015-01-01

This article examines K-12 online student and school performance across an entire state (Colorado) in the United States through two comparisons. First, state assessment scores of students in online schools are compared to those in traditional brick and mortar schools. Second, the accountability scores of online schools are compared to those of…

Digital divide among people with disabilities: Analysis of data from a nationwide study for determinants of Internet use and activities performed online.

PubMed

Duplaga, Mariusz

2017-01-01

The Internet is both an opportunity as well as a challenge for people with disabilities. However, this segment of the population is usually indicated among social groups experiencing digital divide. The study is focused on the analysis of factors determining Internet usage and undertaking specific activities online among people with disabilities based on a nationwide study performed in 2013 in Poland. Secondary analysis was performed on the data of persons who declared disability status in 2013 "Social Diagnosis" study. Multivariate logistic regression models were developed for the use of the Internet and performing three types of activities online. Among 3,556 respondents with disability 51.02% were females, 25.19% 65 years of age and over and 33.05% were Internet users. The predictors of Internet usage included the degree of disability, place of residence, level of education, marital status, occupational status, net income, use of health care service and the use of mobile phone. The odds ratio that a person with disability belonging to the oldest category will use the Internet was only 0.04 (95% CI 0.02-0.09), when compared to the youngest category. The odds that a person with disability from the highest category of education will use the Internet were 18 times higher than in the case of persons with only basic education (OR 18.17, 95% CI 11.70-28.21). Common predictors of online activities (accessing websites of public institutions, checking and sending emails, publishing own content on the Internet) included age category and net income. People with disabilities in Poland are facing a significant digital divide. The factors determining the use of the Internet in this group are similar to those of the general population. On the other hand, people with disabilities who are active online, access diversified types of services including presentation of their own content online.

Digital divide among people with disabilities: Analysis of data from a nationwide study for determinants of Internet use and activities performed online

PubMed Central

2017-01-01

Introduction The Internet is both an opportunity as well as a challenge for people with disabilities. However, this segment of the population is usually indicated among social groups experiencing digital divide. The study is focused on the analysis of factors determining Internet usage and undertaking specific activities online among people with disabilities based on a nationwide study performed in 2013 in Poland. Methods Secondary analysis was performed on the data of persons who declared disability status in 2013 “Social Diagnosis” study. Multivariate logistic regression models were developed for the use of the Internet and performing three types of activities online. Results Among 3,556 respondents with disability 51.02% were females, 25.19% 65 years of age and over and 33.05% were Internet users. The predictors of Internet usage included the degree of disability, place of residence, level of education, marital status, occupational status, net income, use of health care service and the use of mobile phone. The odds ratio that a person with disability belonging to the oldest category will use the Internet was only 0.04 (95% CI 0.02–0.09), when compared to the youngest category. The odds that a person with disability from the highest category of education will use the Internet were 18 times higher than in the case of persons with only basic education (OR 18.17, 95% CI 11.70–28.21). Common predictors of online activities (accessing websites of public institutions, checking and sending emails, publishing own content on the Internet) included age category and net income. Conclusions People with disabilities in Poland are facing a significant digital divide. The factors determining the use of the Internet in this group are similar to those of the general population. On the other hand, people with disabilities who are active online, access diversified types of services including presentation of their own content online. PMID:28662125

Which Measures of Online Control Are Least Sensitive to Offline Processes?

PubMed

de Grosbois, John; Tremblay, Luc

2018-02-28

A major challenge to the measurement of online control is the contamination by offline, planning-based processes. The current study examined the sensitivity of four measures of online control to offline changes in reaching performance induced by prism adaptation and terminal feedback. These measures included the squared Z scores (Z 2 ) of correlations of limb position at 75% movement time versus movement end, variable error, time after peak velocity, and a frequency-domain analysis (pPower). The results indicated that variable error and time after peak velocity were sensitive to the prism adaptation. Furthermore, only the Z 2 values were biased by the terminal feedback. Ultimately, the current study has demonstrated the sensitivity of limb kinematic measures to offline control processes and that pPower analyses may yield the most suitable measure of online control.

Receding horizon online optimization for torque control of gasoline engines.

PubMed

Kang, Mingxin; Shen, Tielong

2016-11-01

This paper proposes a model-based nonlinear receding horizon optimal control scheme for the engine torque tracking problem. The controller design directly employs the nonlinear model exploited based on mean-value modeling principle of engine systems without any linearizing reformation, and the online optimization is achieved by applying the Continuation/GMRES (generalized minimum residual) approach. Several receding horizon control schemes are designed to investigate the effects of the integral action and integral gain selection. Simulation analyses and experimental validations are implemented to demonstrate the real-time optimization performance and control effects of the proposed torque tracking controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The Effect of Using E-Learning Tools in Online and Campus-Based Classrooms on Student Performance

ERIC Educational Resources Information Center

Galy, Edith; Downey, Clara; Johnson, Jennie

2011-01-01

Creating an integrative research framework that extends a model frequently used in the Information Systems field, the Technology Acceptance Model, together with variables used in the Education field, this empirical study investigates the factors influencing student performance as reflected by their final course grade. The Technology Acceptance…

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Looking Similar Promotes Group Stability in a Game-Based Virtual Community.

PubMed

Lortie, Catherine L; Guitton, Matthieu J

2012-08-01

Online support groups are popular Web-based resources that provide tailored information and peer support through virtual communities and fulfill the users' needs for empowerment and belonging. However, the therapeutic potential of online support groups is at present limited by the lack of systematic research on the cognitive mechanisms underlying social group cohesion in virtual communities. We might increase the benefits of participation in online support groups if we gain more insight into the factors that promote long-term commitment to peer support. One approach to foster the therapeutic potential of online support groups could be to increase social selection based on visual similarity. We performed a case study using the popular virtual setting of "World of Warcraft" (Blizzard Entertainment, Irvine, CA). We monitored the social dynamics of a virtual community composed of avatars whose appearance was identical during a period of 3 months, biweekly, for a total of 24 measures. We observed that this homogeneous community displayed a very high level of group stability over time in terms of the total number of members, the number of members that stayed the same, and the number of arrivals and departures, despite the fact that belonging to a heterogeneous group typically favors the success of the group with respect to game progression. Our results confirm that appearance can trigger social selection in online virtual communities. Displaying a similar appearance could be one way to strengthen social bonds among peers who share various health and well-being issues. Thus, the therapeutic potential of online support groups could be promoted through visual cohesion.

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ1 Regularization

PubMed Central

Sanchez-Perez, Gabriel; Toscano-Medina, Karina; Martinez-Hernandez, Victor; Olivares-Mercado, Jesus; Sanchez, Victor

2018-01-01

In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ1 regularization. PMID:29710833

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ₁ Regularization.

PubMed

Hernandez-Suarez, Aldo; Sanchez-Perez, Gabriel; Toscano-Medina, Karina; Martinez-Hernandez, Victor; Perez-Meana, Hector; Olivares-Mercado, Jesus; Sanchez, Victor

2018-04-29

In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ 1 regularization.

Online reporting of adverse drug reactions: a study from a French regional pharmacovigilance center.

PubMed

Abadie, Delphine; Chebane, Leyla; Bert, Max; Durrieu, Geneviève; Montastruc, Jean-Louis

2014-01-01

In France, online reporting via a website is a new method for notifying adverse drug reactions (ADRs). The French Midi-Pyrénées Regional Pharmacovigilance Center (RPVC) set up in July, 2010 a Web-based ADR reporting tool in order to improve ADR reporting rate. To assess feasibility, use and performances of this new ADR reporting system. To evaluate the main characteristics of these online reports. In a retrospective study, we evaluated characteristics (numbers, ADR reporting and file processing times, type of reporters, suspected drugs, "seriousness" and nature of ADRs) of online notifications reported to the RPVC between July 7(th), 2010 (first online notification) and December 31(th), 2011. We performed comparisons to a random sample of "conventional" notifications, i.e. spontaneously reported to the RPVC via traditional tools (post, fax, e-mail or telephone) during the same period. The total number of online reports was 312 over the 18-month period. There was a 45% increase in numbers of reports from ambulatory healthcare professionals after the implementation of the new reporting tool. Online reports were transmitted to the French Medicine Agency on average almost one month (26 days) earlier than "conventional" ones. This difference was mainly due to a faster ADR notification process via the online form (on average, the reporting period was decreased by 19 days with the new tool). In comparison to "conventional" notifications, online reports came more often from ambulatory healthcare professionals, and involved more frequently neuropsychiatric drugs and neuropsychiatric ADRs. None difference was observed for "seriousness" of ADRs. It is feasible to deploy an online ADR reporting system used by health professionals in current practice. We underline the efficiency of this new online reporting tool for increasing ADRs reporting. Moreover, this is the first published study demonstrating that an online reporting tool can help to save time on the ADR reporting period and file processing, which is essential to generate early safety signals. © 2014 Société Française de Pharmacologie et de Thérapeutique.

Integrated on-line system for DNA sequencing by capillary electrophoresis: From template to called bases

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

Ton, H.; Yeung, E.S.

1997-02-15

An integrated on-line prototype for coupling a microreactor to capillary electrophoresis for DNA sequencing has been demonstrated. A dye-labeled terminator cycle-sequencing reaction is performed in a fused-silica capillary. Subsequently, the sequencing ladder is directly injected into a size-exclusion chromatographic column operated at nearly 95{degree}C for purification. On-line injection to a capillary for electrophoresis is accomplished at a junction set at nearly 70{degree}C. High temperature at the purification column and injection junction prevents the renaturation of DNA fragments during on-line transfer without affecting the separation. The high solubility of DNA in and the relatively low ionic strength of 1 x TEmore » buffer permit both effective purification and electrokinetic injection of the DNA sample. The system is compatible with highly efficient separations by a replaceable poly(ethylene oxide) polymer solution in uncoated capillary tubes. Future automation and adaptation to a multiple-capillary array system should allow high-speed, high-throughput DNA sequencing from templates to called bases in one step. 32 refs., 5 figs.« less

Online Multitasking Line-Scan Imaging Techniques for Simultaneous Safety and Quality Evaluation of Apples

NASA Astrophysics Data System (ADS)

Kim, Moon Sung; Lee, Kangjin; Chao, Kaunglin; Lefcourt, Alan; Cho, Byung-Kwan; Jun, Won

We developed a push-broom, line-scan imaging system capable of simultaneous measurements of reflectance and fluorescence. The system allows multitasking inspections for quality and safety attributes of apples due to its dynamic capabilities in simultaneously capturing fluorescence and reflectance, and selectivity in multispectral bands. A multitasking image-based inspection system for online applications has been suggested in that a single imaging device that could perform a multitude of both safety and quality inspection needs. The presented multitask inspection approach in online applications may provide an economically viable means for a number of food processing industries being able to adapt to operate and meet the dynamic and specific inspection and sorting needs.

Elective course in acute care using online learning and patient simulation.

PubMed

Seybert, Amy L; Kane-Gill, Sandra L

2011-04-11

To enhance students' knowledge of and critical-thinking skills in the management of acutely ill patients using online independent learning partnered with high-fidelity patient simulation sessions. Students enrolled in the Acute Care Simulation watched 10 weekly Web-based video presentations on various critical care and advanced cardiovascular pharmacotherapy topics. After completing each online module, all students participated in groups in patient-care simulation exercises in which they prepared a pharmacotherapeutic plan for the patient, recommended this plan to the patient's physician, and completed a debriefing session with the facilitator. Students completed a pretest and posttest before and after each simulation exercise, as well as midterm and final evaluations and a satisfaction survey. Pharmacy students significantly improved their scores on 9 of the 10 tests (p ≤ 0.05). Students' performance on the final evaluation improved compared with performance on the midterm evaluation. Overall, students were satisfied with the unique dual approach to learning and enjoyed the realistic patient-care environment that the simulation laboratory provided. Participation in an elective course that combined self-directed Web-based learning and hands-on patient simulation exercises increased pharmacy students' knowledge and critical-thinking skills in acute care.

Bioanalytical Applications of Fluorescence Line-Narrowing and Non-Line-Narrowing Spectroscopy Interfaced with Capillary Electrophoresis and High-Performance Liquid Chromatography

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

Roberts, Kenneth Paul

Capillary electrophoresis (CE) and high-performance liquid chromatography (HPLC) are widely used analytical separation techniques with many applications in chemical, biochemical, and biomedical sciences. Conventional analyte identification in these techniques is based on retention/migration times of standards; requiring a high degree of reproducibility, availability of reliable standards, and absence of coelution. From this, several new information-rich detection methods (also known as hyphenated techniques) are being explored that would be capable of providing unambiguous on-line identification of separating analytes in CE and HPLC. As further discussed, a number of such on-line detection methods have shown considerable success, including Raman, nuclear magnetic resonancemore » (NMR), mass spectrometry (MS), and fluorescence line-narrowing spectroscopy (FLNS). In this thesis, the feasibility and potential of combining the highly sensitive and selective laser-based detection method of FLNS with analytical separation techniques are discussed and presented. A summary of previously demonstrated FLNS detection interfaced with chromatography and electrophoresis is given, and recent results from on-line FLNS detection in CE (CE-FLNS), and the new combination of HPLC-FLNS, are shown.« less

Online system for knowledge assessment enhances students' results on school knowledge test.

PubMed

Kralj, Benjamin; Glazar, Sasa Aleksej

2013-01-01

Variety of online tools were built to help assessing students' performance in school. Many teachers changed their methods of assessment from paper-and-pencil (P&P) to online systems. In this study we analyse the influence that using an online system for knowledge assessment has on students' knowledge. Based on both a literature study and our own research we designed and built an online system for knowledge assessment. The system is evaluated using two groups of primary school teachers and students (N = 686) in Slovenia: an experimental and a control group. Students solved P&P exams on several occasions. The experimental group was allowed to access the system either at school or at home for a limited period during the presentation of a selected school topic. Students in the experimental group were able to solve tasks and compare their own achievements with those of their coevals. A comparison of the P&P school exams results achieved by both groups revealed a positive effect on subject topic comprehension for those with access to the online self-assessment system.

QRTEngine: An easy solution for running online reaction time experiments using Qualtrics.

PubMed

Barnhoorn, Jonathan S; Haasnoot, Erwin; Bocanegra, Bruno R; van Steenbergen, Henk

2015-12-01

Performing online behavioral research is gaining increased popularity among researchers in psychological and cognitive science. However, the currently available methods for conducting online reaction time experiments are often complicated and typically require advanced technical skills. In this article, we introduce the Qualtrics Reaction Time Engine (QRTEngine), an open-source JavaScript engine that can be embedded in the online survey development environment Qualtrics. The QRTEngine can be used to easily develop browser-based online reaction time experiments with accurate timing within current browser capabilities, and it requires only minimal programming skills. After introducing the QRTEngine, we briefly discuss how to create and distribute a Stroop task. Next, we describe a study in which we investigated the timing accuracy of the engine under different processor loads using external chronometry. Finally, we show that the QRTEngine can be used to reproduce classic behavioral effects in three reaction time paradigms: a Stroop task, an attentional blink task, and a masked-priming task. These findings demonstrate that QRTEngine can be used as a tool for conducting online behavioral research even when this requires accurate stimulus presentation times.

Online Low-Rank Representation Learning for Joint Multi-subspace Recovery and Clustering.

PubMed

Li, Bo; Liu, Risheng; Cao, Junjie; Zhang, Jie; Lai, Yu-Kun; Liua, Xiuping

2017-10-06

Benefiting from global rank constraints, the lowrank representation (LRR) method has been shown to be an effective solution to subspace learning. However, the global mechanism also means that the LRR model is not suitable for handling large-scale data or dynamic data. For large-scale data, the LRR method suffers from high time complexity, and for dynamic data, it has to recompute a complex rank minimization for the entire data set whenever new samples are dynamically added, making it prohibitively expensive. Existing attempts to online LRR either take a stochastic approach or build the representation purely based on a small sample set and treat new input as out-of-sample data. The former often requires multiple runs for good performance and thus takes longer time to run, and the latter formulates online LRR as an out-ofsample classification problem and is less robust to noise. In this paper, a novel online low-rank representation subspace learning method is proposed for both large-scale and dynamic data. The proposed algorithm is composed of two stages: static learning and dynamic updating. In the first stage, the subspace structure is learned from a small number of data samples. In the second stage, the intrinsic principal components of the entire data set are computed incrementally by utilizing the learned subspace structure, and the low-rank representation matrix can also be incrementally solved by an efficient online singular value decomposition (SVD) algorithm. The time complexity is reduced dramatically for large-scale data, and repeated computation is avoided for dynamic problems. We further perform theoretical analysis comparing the proposed online algorithm with the batch LRR method. Finally, experimental results on typical tasks of subspace recovery and subspace clustering show that the proposed algorithm performs comparably or better than batch methods including the batch LRR, and significantly outperforms state-of-the-art online methods.

Fuzzy logic based on-line fault detection and classification in transmission line.

PubMed

Adhikari, Shuma; Sinha, Nidul; Dorendrajit, Thingam

2016-01-01

This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisition of transmission line. When fault occurs in the system current waveforms are distorted due to transients and their pattern changes according to the type of fault in the system. The three phase alternating current, zero sequence and positive sequence current data generated by LabVIEW through CRIO-9067 are processed directly for relaying. The result shows that proposed technique is capable of right tripping action and classification of type of fault at high speed therefore can be employed in practical application.

Does Self-Selection Affect Samples’ Representativeness in Online Surveys? An Investigation in Online Video Game Research

PubMed Central

van Singer, Mathias; Chatton, Anne; Achab, Sophia; Zullino, Daniele; Rothen, Stephane; Khan, Riaz; Billieux, Joel; Thorens, Gabriel

2014-01-01

Background The number of medical studies performed through online surveys has increased dramatically in recent years. Despite their numerous advantages (eg, sample size, facilitated access to individuals presenting stigmatizing issues), selection bias may exist in online surveys. However, evidence on the representativeness of self-selected samples in online studies is patchy. Objective Our objective was to explore the representativeness of a self-selected sample of online gamers using online players’ virtual characters (avatars). Methods All avatars belonged to individuals playing World of Warcraft (WoW), currently the most widely used online game. Avatars’ characteristics were defined using various games’ scores, reported on the WoW’s official website, and two self-selected samples from previous studies were compared with a randomly selected sample of avatars. Results We used scores linked to 1240 avatars (762 from the self-selected samples and 478 from the random sample). The two self-selected samples of avatars had higher scores on most of the assessed variables (except for guild membership and exploration). Furthermore, some guilds were overrepresented in the self-selected samples. Conclusions Our results suggest that more proficient players or players more involved in the game may be more likely to participate in online surveys. Caution is needed in the interpretation of studies based on online surveys that used a self-selection recruitment procedure. Epidemiological evidence on the reduced representativeness of sample of online surveys is warranted. PMID:25001007

Design and evaluation of online arithmetic for signal processing applications on FPGAs

NASA Astrophysics Data System (ADS)

Galli, Reto; Tenca, Alexandre F.

2001-11-01

This paper shows the design and the evaluation of on-line arithmetic modules for the most common operators used in DSP applications, using FPGAs as the target technology. The designs are highly optimized for the target technology and the common range of precision in DSP. The results are based on experimental data collected using CAD tools. All designs are synthesized for the same type of devices (Xilinx XC4000) for comparison, avoiding rough estimates of the system performance, and generating a more reliable and detailed comparison of on-line signal processing solutions with other state of the art approaches, such as distributed arithmetic. We show that on-line designs have a hard stand for basic DSP applications that use only addition and multiplication. However, we also show that on-line designs are able to overtake other approaches as the applications become more sophisticated, e.g. when data dependencies exist, or when non constant multiplicands restrict the use of other approaches.

A standardized online clinical education and assessment tool for neurology clerkship students assigned to multiple sites.

PubMed

Holland, Neil R; Grinberg, Ilya; Tabby, David

2014-01-01

The Drexel neurology clerkship experience can vary from large groups at a university hospital inpatient unit to smaller groups at private physician offices. Evaluations are based on the site director's subjective assessment and performance on the National Board of Medical Examiners neurology shelf examination. We are developing a standardized online clinical neurology course and quiz for the whole clerkship. We piloted the course and quiz at a single site for one academic year and compared their test scores with a control group of students at other clerkship sites who took the online quiz without viewing the course. Students at the pilot site achieved higher scores both on the neurology shelf examination and the clinical quiz and also reported higher teaching satisfaction scores than students at all other sites. There was a 97 % participation rate in the online quiz from the other sites. Use of this online course and quiz provides effective standardized clinical neurology teaching and evaluation that can be applied to students across multiple sites.

Construction and evaluation of an online microbiology course for nonscience majors.

PubMed

Hughes, Lee

2008-01-01

The development of web-based technologies provides a new method for course delivery. As with any new technique, evaluation is a necessary tool to determine if the method is consistent with expectations. This study describes the conversion of a nonscience majors' microbiology lecture course to online delivery and evaluates the hypothesis that the online course can be as effective as the traditional course. Course examination scores are compared between the face-to-face and online sections over a 3-year period. On all but one of the course examinations, no significant difference is found for those students in these two distinctly different course types. The success rate, as defined by those students earning grades of C or better, is high for both course types, although the traditional course success rate is slightly higher. Student evaluations of the courses are also positive, though some differences are noted. Overall, student performance in the online course is equivalent to that in the traditional course.

Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes.

PubMed

Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

2016-02-23

Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb(2+), and connecting our platform with pipelines of tap water and wastewater for real-time online Pb(2+) detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques.

Links between real and virtual networks: a comparative study of online communities in Japan and Korea.

PubMed

Ishii, Kenichi; Ogasahara, Morihiro

2007-04-01

The present study explores how online communities affect real-world personal relations based on a cross-cultural survey conducted in Japan and Korea. Findings indicate that the gratifications of online communities moderate the effects of online communities on social participation. Online communities are categorized into a real-group-based community and a virtual-network-based community. The membership of real-group-based online community is positively correlated with social bonding gratification and negatively correlated with information- seeking gratification. Japanese users prefer more virtual-network-based online communities, while their Korean counterparts prefer real-group-based online communities. Korean users are more active in online communities and seek a higher level of socializing gratifications, such as social bonding and making new friends, when compared with their Japanese counterparts. These results indicate that in Korea, personal relations via the online community are closely associated with the real-world personal relations, but this is not the case in Japan. This study suggests that the effects of the Internet are culture-specific and that the online community can serve a different function in different cultural environments.

An Investigation into the Relationship between On-Line Formative Assessments and Performance of Students

ERIC Educational Resources Information Center

Yeo, Cheok Heng; Ke, Keneth; Chatterjee, Bikram

2014-01-01

The aim of this study is to investigate the relationship between attempting online formative assessments and performance of students. The study is motivated by the dearth in research in the area of online formative assessment. The study reports mixed result of such relationship. A relationship was reported between attempting online formative…

Creation and Evaluation of a Laboratory Administration Curriculum for Pathology Residents.

PubMed

Guarner, Jeannette; Hill, Charles E; Amukele, Timothy

2017-10-01

A clinical laboratory management (CLM) curriculum that can objectively assess the Accreditation Council for Graduate Medical Education pathology systems-based practice milestones and can provide consistent resident training across institutions is needed. Faculty at Emory University created a curriculum that consists of assay verification exercises and interactive, case-based online modules. Beta testing was done at Emory University and Johns Hopkins. Residents were required to obtain a score of more than 80% in the online modules to achieve levels 3 to 4 in the milestones. In addition, residents shadowed a laboratory director, performed an inspection of a laboratory section, and completed training in human subjects research and test utilization. Fourteen residents took and evaluated the laboratory administration curriculum. The printed certificates from the modules were used for objective faculty evaluation of mastery of concepts. Of all the activities the residents performed during the rotation, the online modules were ranked most helpful by all residents. A 25-question knowledge assessment was performed before and after the rotation and showed an average increase of 8 points (P = .0001). The multimodal CLM training described here is an easily adoptable, objective system for teaching CLM. It was well liked by residents and provided an objective measurement of mastery of concepts for faculty. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Medipix2 as a tool for proton beam characterization

NASA Astrophysics Data System (ADS)

Bisogni, M. G.; Cirrone, G. A. P.; Cuttone, G.; Del Guerra, A.; Lojacono, P.; Piliero, M. A.; Romano, F.; Rosso, V.; Sipala, V.; Stefanini, A.

2009-08-01

Proton therapy is a technique used to deliver a highly accurate and effective dose for the treatment of a variety of tumor diseases. The possibility to have an instrument able to give online information could reduce the time necessary to characterize the proton beam. To this aim we propose a detection system for online proton beam characterization based on the Medipix2 chip. Medipix2 is a detection system based on a single event counter read-out chip, bump-bonded to silicon pixel detector. The read-out chip is a matrix of 256×256 cells, 55×55 μm 2 each. To demonstrate the capabilities of Medipix2 as a proton detector, we have used a 62 MeV flux proton beam at the CATANA beam line of the LNS-INFN laboratory. The measurements performed confirmed the good imaging performances of the Medipix2 system also for the characterization of proton beams.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

Addition of visual noise boosts evoked potential-based brain-computer interface.

PubMed

Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili

2014-05-14

Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7-36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs.

A strategy for screening antioxidants in Ginkgo biloba extract by comprehensive two-dimensional ultra high performance liquid chromatography.

PubMed

Guo, Ru-Zhou; Liu, Xin-Guang; Gao, Wen; Dong, Xin; Fanali, Salvatore; Li, Ping; Yang, Hua

2015-11-27

Recently, screening of bioactive compounds by on-line ultra-high performance liquid chromatography (UHPLC) draws increasing attentions for the advantages of rapidity and intuition. Nevertheless, most on-line methods were limited to the shortcoming like low resolution and peak capacity, which could interfere the active ingredient identification. Comprehensive two-dimensional UHPLC (LC×LC) has revealed to be a powerful tool to separate complex mixtures. Herein, a strategy based on LC×LC analysis coupled with pre-column 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay was proposed to screen the antioxidants from the extract of Ginkgo biloba (EGB). A total of 61 compounds were identified in EGB, and 25 of them showed appreciable radical scavenging capacity. This work may offer pharmacodynamics base for further research about EGB, also the strategy is likelihood to be applied in screening antioxidant in other herbal medicine. Copyright © 2015 Elsevier B.V. All rights reserved.

An online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation

NASA Astrophysics Data System (ADS)

Tonin, L.; Leeb, R.; Sobolewski, A.; Millán, J. del R.

2013-10-01

Objective. In this work we present—for the first time—the online operation of an electroencephalogram (EEG) brain-computer interface (BCI) system based on covert visuospatial attention (CVSA), without relying on any evoked responses. Electrophysiological correlates of pure top-down CVSA have only recently been proposed as a control signal for BCI. Such systems are expected to share the ease of use of stimulus-driven BCIs (e.g. P300, steady state visually evoked potential) with the autonomy afforded by decoding voluntary modulations of ongoing activity (e.g. motor imagery). Approach. Eight healthy subjects participated in the study. EEG signals were acquired with an active 64-channel system. The classification method was based on a time-dependent approach tuned to capture the most discriminant spectral features of the temporal evolution of attentional processes. The system was used by all subjects over two days without retraining, to verify its robustness and reliability. Main results. We report a mean online accuracy across the group of 70.6 ± 1.5%, and 88.8 ± 5.8% for the best subject. Half of the participants produced stable features over the entire duration of the study. Additionally, we explain drops in performance in subjects showing stable features in terms of known electrophysiological correlates of fatigue, suggesting the prospect of online monitoring of mental states in BCI systems. Significance. This work represents the first demonstration of the feasibility of an online EEG BCI based on CVSA. The results achieved suggest the CVSA BCI as a promising alternative to standard BCI modalities.

Paramedic student performance: comparison of online with on-campus lecture delivery methods.

PubMed

Hubble, Michael W; Richards, Michael E

2006-01-01

Colleges and universities are experiencing increasing demand for online courses in many healthcare disciplines, including emergency medical services (EMS). Development and implementation of online paramedic courses with the quality of education experienced in the traditional classroom setting is essential in order to maintain the integrity of the educational process. Currently, there is conflicting evidence of whether a significant difference exists in student performance between online and traditional nursing and allied health courses. However, there are no published investigations of the effectiveness of online learning by paramedic students. Performance of paramedic students enrolled in an online, undergraduate, research methods course is equivalent to the performance of students enrolled in the same course provided in a traditional, classroom environment. Academic performance, learning styles, and course satisfaction surveys were compared between two groups of students. The course content was identical for both courses and taught by the same instructor during the same semester. The primary difference between the traditional course and the online course was the method of lecture delivery. Lectures for the on-campus students were provided live in a traditional classroom setting using PowerPoint slides. Lectures for the online students were provided using the same PowerPoint slides with prerecorded streaming audio and video. A convenience sample of 23 online and 10 traditional students participated in this study. With the exception of two learning domains, the two groups of students exhibited similar learning styles as assessed using the Grasha-Riechmann Student Learning Style Scales instrument. The online students scored significantly lower in the competitive and dependent dimensions than did the on-campus students. Academic performance was similar between the two groups. The online students devoted slightly more time to the course than did the campus students, although this difference did not reach statistical significance. In general, the online students believed the online audio lectures were more effective than the traditional live lectures. Distance learning technology appears to be an effective mechanism for extending didactic paramedic education off-campus, and may be beneficial particularly to areas that lack paramedic training programs or adequate numbers of qualified instructors.

Conditional Random Field (CRF)-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

PubMed Central

Yang, Ehwa; Gwak, Jeonghwan; Jeon, Moongu

2017-01-01

Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT). In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF) for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable. PMID:28304366

Performances of 27 MEDLINE systems tested by searches with clinical questions.

PubMed Central

Haynes, R B; Walker, C J; McKibbon, K A; Johnston, M E; Willan, A R

1994-01-01

OBJECTIVE: To compare the performances of online and compact-disc (CD-ROM) versions of the National Library of Medicine's (NLM) MEDLINE database. DESIGN: Analytic survey. INTERVENTION: Clinical questions were drawn from 18 searches originally conducted spontaneously by clinicians from wards and clinics who had used Grateful Med Version 4.0. Clinicians' search strategies were translated to meet the specific requirements of 13 online and 14 CD-ROM MEDLINE systems. A senior librarian and vendors' representatives constructed independent searches from the clinicians' questions. The librarian and clinician searches were run through each system, in command mode for the librarian and menu mode for clinicians, when available. Vendor searches were run through the vendors' own systems only. MAIN MEASUREMENTS: Numbers of relevant and irrelevant citations retrieved, cost (for online systems only), and time. RESULTS: Systems varied substantially for all searches, and for librarian and clinician searches separately, with respect to the numbers of relevant and irrelevant citations retrieved (p < 0.001 for both) and the cost per relevant citation (p = 0.012), but not with respect to the time per search. Based on combined rankings for the highest number of relevant and the lowest number of irrelevant citations retrieved, the SilverPlatter CD-ROM MEDLINE clinical journal subset performed best for librarian searches, while the PaperChase online system worked best for clinician searches. For cost per relevant citation retrieved, Dialog's Knowledge Index performed best for both librarian and clinician searches. CONCLUSIONS: There were substantial differences in the performances of competing MEDLINE systems, and performance was affected by search strategy, which was conceived by a librarian or by clinicians. PMID:7719810

The roles of constraint-based and dedication-based influences on user's continued online shopping behavior.

PubMed

Chang, Su-Chao; Chou, Chi-Min

2012-11-01

The objective of this study was to determine empirically the role of constraint-based and dedication-based influences as drivers of the intention to continue using online shopping websites. Constraint-based influences consist of two variables: trust and perceived switching costs. Dedication-based influences consist of three variables: satisfaction, perceived usefulness, and trust. The current results indicate that both constraint-based and dedication-based influences are important drivers of the intention to continue using online shopping websites. The data also shows that trust has the strongest total effect on online shoppers' intention to continue using online shopping websites. In addition, the results indicate that the antecedents of constraint-based influences, technical bonds (e.g., perceived operational competence and perceived website interactivity) and social bonds (e.g., perceived relationship investment, community building, and intimacy) have indirect positive effects on the intention to continue using online shopping websites. Based on these findings, this research suggests that online shopping websites should build constraint-based and dedication-based influences to enhance user's continued online shopping behaviors simultaneously.

Using Game-Based Cooperative Learning to Improve Learning Motivation: A Study of Online Game Use in an Operating Systems Course

ERIC Educational Resources Information Center

Jong, Bin-Shyan; Lai, Chien-Hung; Hsia, Yen-Teh; Lin, Tsong-Wuu; Lu, Cheng-Yu

2013-01-01

Many researchers have studied the use of game-based learning. Game-based learning takes many forms, including virtual reality, role playing, and performing tasks. For students to learn specific course content, it is important that the selected game be suited to the course. Thus far, no studies have investigated the use of game-based cooperative…

A Comparison of Mobile and Fixed Device Access on User Engagement Associated With Women, Infants, and Children (WIC) Online Nutrition Education.

PubMed

Brusk, John J; Bensley, Robert J

2016-11-15

Online health education has expanded its reach due to cost-effective implementation and demonstrated effectiveness. However, a limitation exists with the evaluation of online health education implementations and how the impact of the system is attenuated by the extent to which a user engages with it. Moreover, the current online health education research does not consider how this engagement has been affected by the transition from fixed to mobile user access over the last decade. This paper focuses on comparing the impact mobile versus fixed devices have on user engagement key performance indicators (KPI) associated with the wichealth website (.org), an Internet-based parent-child feeding intervention offered to clients associated with the US Department of Agriculture's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Data were collected from 612,201 nutrition education lessons completed by 305,735 unique WIC participants in 21 states over a 1-year period. Data consisted of system-collected measures, profile items, and items from an exit survey administered at the conclusion of each lesson. User engagement was defined based on 3 KPIs associated with usage of the wichealth website: number of link views, link view time, and progression in stage of readiness to change. Independent samples t tests were used to compare KPIs between fixed only and mobile only device users and paired samples t tests were used to compare KPIs within users who completed at least one lesson each on both a fixed and mobile device. A logistic regression was performed to estimate the odds of KPI performance thresholds in the independent samples study group given access device type while controlling for confounding of user characteristics associated with these KPIs. Analysis of 8 user characteristics (lessons completed, race, ethnicity, language, state of residence, pregnancy status, beginning stage of change, and preferred nutrition education method) were significantly (P<.001) related to various KPI differences between mobile and fixed device access. Non-mobile users were significantly (P<.001) more likely to engage based on all 3 KPIs, even after logistic regression control for the potential confounding related to the strongly associated user characteristics identified. The findings of this study support the idea that online health education developers need to seriously consider access device when creating programs. Online health education developers need to take extra effort to truly understand access patterns of populations being served, and whether or not access device will influence user engagement performance indicators. ©John J Brusk, Robert J Bensley. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 15.11.2016.

Reflecting on the experience of interviewing online: perspectives from the Internet and HIV study in London.

PubMed

Davis, M; Bolding, G; Hart, G; Sherr, L; Elford, J

2004-11-01

This paper considers some of the strengths and weaknesses of conducting synchronous online interviews for qualitative research. It is based on a study among gay/bisexual men that used both qualitative and quantitative methods to explore the association between seeking sex through the Internet and HIV transmission risk. Between June 2002 and January 2004, 128 gay/bisexual men living in London were interviewed one-to-one by the first author (MD) about their experience of using the Internet to find sexual partners and negotiating condom use for anal sex. Thirty-five men were interviewed online, while 93 were interviewed face-to-face (i.e. offline). This paper draws on MD's experience of conducting these interviews--both online and face-to-face. Synchronous online interviews have the advantage of being cheap, convenient and attractive to people who do not like face-to-face interviews. However, some of the social conventions and technical limitations of computer-mediated-communication can introduce ambiguity into the online dialogue. To minimize this ambiguity, both interviewer and interviewee have to edit their online interaction. One of the distinctive features of the online interview is that it emerges as a form of textual performance. This raises fundamental questions about the suitability of the synchronous online interview for exploring sensitive topics such as risky sexual behaviour.

Modeling Periodic Impulsive Effects on Online TV Series Diffusion.

PubMed

Fu, Peihua; Zhu, Anding; Fang, Qiwen; Wang, Xi

Online broadcasting substantially affects the production, distribution, and profit of TV series. In addition, online word-of-mouth significantly affects the diffusion of TV series. Because on-demand streaming rates are the most important factor that influences the earnings of online video suppliers, streaming statistics and forecasting trends are valuable. In this paper, we investigate the effects of periodic impulsive stimulation and pre-launch promotion on on-demand streaming dynamics. We consider imbalanced audience feverish distribution using an impulsive susceptible-infected-removed(SIR)-like model. In addition, we perform a correlation analysis of online buzz volume based on Baidu Index data. We propose a PI-SIR model to evolve audience dynamics and translate them into on-demand streaming fluctuations, which can be observed and comprehended by online video suppliers. Six South Korean TV series datasets are used to test the model. We develop a coarse-to-fine two-step fitting scheme to estimate the model parameters, first by fitting inter-period accumulation and then by fitting inner-period feverish distribution. We find that audience members display similar viewing habits. That is, they seek new episodes every update day but fade away. This outcome means that impulsive intensity plays a crucial role in on-demand streaming diffusion. In addition, the initial audience size and online buzz are significant factors. On-demand streaming fluctuation is highly correlated with online buzz fluctuation. To stimulate audience attention and interpersonal diffusion, it is worthwhile to invest in promotion near update days. Strong pre-launch promotion is also a good marketing tool to improve overall performance. It is not advisable for online video providers to promote several popular TV series on the same update day. Inter-period accumulation is a feasible forecasting tool to predict the future trend of the on-demand streaming amount. The buzz in public social communities also represents a highly correlated analysis tool to evaluate the advertising value of TV series.

Modeling Periodic Impulsive Effects on Online TV Series Diffusion

PubMed Central

Fang, Qiwen; Wang, Xi

2016-01-01

Background Online broadcasting substantially affects the production, distribution, and profit of TV series. In addition, online word-of-mouth significantly affects the diffusion of TV series. Because on-demand streaming rates are the most important factor that influences the earnings of online video suppliers, streaming statistics and forecasting trends are valuable. In this paper, we investigate the effects of periodic impulsive stimulation and pre-launch promotion on on-demand streaming dynamics. We consider imbalanced audience feverish distribution using an impulsive susceptible-infected-removed(SIR)-like model. In addition, we perform a correlation analysis of online buzz volume based on Baidu Index data. Methods We propose a PI-SIR model to evolve audience dynamics and translate them into on-demand streaming fluctuations, which can be observed and comprehended by online video suppliers. Six South Korean TV series datasets are used to test the model. We develop a coarse-to-fine two-step fitting scheme to estimate the model parameters, first by fitting inter-period accumulation and then by fitting inner-period feverish distribution. Results We find that audience members display similar viewing habits. That is, they seek new episodes every update day but fade away. This outcome means that impulsive intensity plays a crucial role in on-demand streaming diffusion. In addition, the initial audience size and online buzz are significant factors. On-demand streaming fluctuation is highly correlated with online buzz fluctuation. Conclusion To stimulate audience attention and interpersonal diffusion, it is worthwhile to invest in promotion near update days. Strong pre-launch promotion is also a good marketing tool to improve overall performance. It is not advisable for online video providers to promote several popular TV series on the same update day. Inter-period accumulation is a feasible forecasting tool to predict the future trend of the on-demand streaming amount. The buzz in public social communities also represents a highly correlated analysis tool to evaluate the advertising value of TV series. PMID:27669520

An Evaluation of the Impact of E-Learning Media Formats on Student Perception and Performance

NASA Astrophysics Data System (ADS)

Kurbel, Karl; Stankov, Ivo; Datsenka, Rastsislau

Factors influencing student evaluation of web-based courses are analyzed, based on student feedback from an online distance-learning graduate program. The impact of different media formats on the perception of the courses by the students as well as on their performance in these courses are examined. In particular, we studied conventional hypertext-based courses, video-based courses and audio-based courses, and tried to find out whether the media format has an effect on how students assess courses and how good or bad their grades are. Statistical analyses were performed to answer several research questions related to the topic and to properly evaluate the factors influencing student evaluation.

Interactive Graphics Simulator: Design, Development, and Effectiveness/Cost Evaluation. Final Report.

ERIC Educational Resources Information Center

Pieper, William J.; And Others

This study was initiated to design, develop, implement, and evaluate a videodisc-based simulator system, the Interactive Graphics Simulator (IGS) for 6883 Converter Flight Control Test Station training at Lowry Air Force Base, Colorado. The simulator provided a means for performing task analysis online, developing simulations from the task…

Innovative Teaching: An Empirical Study of Computer-Aided Instruction in Quantitative Business Courses

ERIC Educational Resources Information Center

Gonul, Fusun F.; Solano, Roger A.

2013-01-01

We investigate business undergraduate mathematics-based courses in a blended environment of online assignments and exams and offline lectures, and report the impact on academic performance of factors such as classroom attendance, web-based course supplements, and homework. We present results from both ordinary least squares and fixed effects,…

How good are publicly available web services that predict bioactivity profiles for drug repurposing?

PubMed

Murtazalieva, K A; Druzhilovskiy, D S; Goel, R K; Sastry, G N; Poroikov, V V

2017-10-01

Drug repurposing provides a non-laborious and less expensive way for finding new human medicines. Computational assessment of bioactivity profiles shed light on the hidden pharmacological potential of the launched drugs. Currently, several freely available computational tools are available via the Internet, which predict multitarget profiles of drug-like compounds. They are based on chemical similarity assessment (ChemProt, SuperPred, SEA, SwissTargetPrediction and TargetHunter) or machine learning methods (ChemProt and PASS). To compare their performance, this study has created two evaluation sets, consisting of (1) 50 well-known repositioned drugs and (2) 12 drugs recently patented for new indications. In the first set, sensitivity values varied from 0.64 (TarPred) to 1.00 (PASS Online) for the initial indications and from 0.64 (TarPred) to 0.98 (PASS Online) for the repurposed indications. In the second set, sensitivity values varied from 0.08 (SuperPred) to 1.00 (PASS Online) for the initial indications and from 0.00 (SuperPred) to 1.00 (PASS Online) for the repurposed indications. Thus, this analysis demonstrated that the performance of machine learning methods surpassed those of chemical similarity assessments, particularly in the case of novel repurposed indications.

On-Line Fringe Tracking and Prediction at IOTA

NASA Technical Reports Server (NTRS)

Wilson, Edward; Mah, Robert; Lau, Sonie (Technical Monitor)

1999-01-01

The Infrared/Optical Telescope Array (IOTA) is a multi-aperture Michelson interferometer located on Mt. Hopkins near Tucson, Arizona. To enable viewing of fainter targets, an on-line fringe tracking system is presently under development at NASA Ames Research Center. The system has been developed off-line using actual data from IOTA, and is presently undergoing on-line implementation at IOTA. The system has two parts: (1) a fringe tracking system that identifies the center of a fringe packet by fitting a parametric model to the data; and (2) a fringe packet motion prediction system that uses characteristics of past fringe packets to predict fringe packet motion. Combined, this information will be used to optimize on-line the scanning trajectory, resulting in improved visibility of faint targets. Fringe packet identification is highly accurate and robust (99% of the 4000 fringe packets were identified correctly, the remaining 1% were either out of the scan range or too noisy to be seen) and is performed in 30-90 milliseconds on a Pentium II-based computer. Fringe packet prediction, currently performed using an adaptive linear predictor, delivers a 10% improvement over the baseline of predicting no motion.

Discriminative object tracking via sparse representation and online dictionary learning.

PubMed

Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

2014-04-01

We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

Predicting Student Performance in Web-Based Distance Education Courses Based on Survey Instruments Measuring Personality Traits and Technical Skills

ERIC Educational Resources Information Center

Hall, Michael

2008-01-01

Two common web-based surveys, "Is Online Learning Right for Me?' and "What Technical Skills Do I Need?", were combined into a single survey instrument and given to 228 on-campus and 83 distance education students. The students were enrolled in four different classes (business, computer information services, criminal justice, and…

Transforming and Turning around Low-Performing Schools: The Role of Online Learning

ERIC Educational Resources Information Center

Corry, Michael; Carlson-Bancroft, Angela

2014-01-01

This review of the literature examines online learning as a core strategy for bold, dramatic curricular reform within transformational or turnaround models in improving low-performing K-12 schools. The analysis of the literature in this area found benefits of online learning in transforming and turning around low-performing schools to include: (a)…

76 FR 16850 - 60-Day Notice of Proposed Information Collection: Agency Form DS-4127, NEA/PI Online Performance...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-25

... Form DS- 4127, NEA/PI Online Performance Reporting System (PRS), OMB Control Number 1405-0183. ACTION... Collection: NEA/PI Online Performance Reporting System (PRS). OMB Control Number: 1405-0183. Type of Request: Renewal. Originating Office: NEA/PI. Form Number: DS-4127. Respondents: Recipients of NEA/PI grants...

Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection

PubMed Central

Liu, Changyu; Li, Huiling

2014-01-01

We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches. PMID:25147840

Hack-proof Synchronization Protocol for Multi-player Online Games

NASA Astrophysics Data System (ADS)

Fung, Yeung Siu; Lui, John C. S.

Modern multi-player online games are popular and attractive because they provide a sense of virtual world experience to users: players can interact with each other on the Internet but perceive a local area network responsiveness. To make this possible, most modern multi-player online games use similar networking architecture that aims to hide the effects of network latency, packet loss, and high variance of delay from players. Because real-time interactivity is a crucial feature from a player's point of view, any delay perceived by a player can affect his/her performance [16]. Therefore, the game client must be able to run and accept new user commands continuously regardless of the condition of the underlying communication channel, and that it will not stop responding because of waiting for update packets from other players. To make this possible, multi-player online games typically use protocols based on "dead-reckoning" [5, 6, 9] which allows loose synchronization between players.

Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features

NASA Astrophysics Data System (ADS)

Bouboulis, Pantelis; Chouvardas, Symeon; Theodoridis, Sergios

2018-04-01

We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parameters as time iterations evolve. Besides complexity, this leads to an increased need of communication resources, in a distributed setting. In contrast, the proposed method approximates the solution as a fixed-size vector (of larger dimension than the input space) using Random Fourier Features. This paves the way to use standard linear combine-then-adapt techniques. To the best of our knowledge, this is the first time that a complete protocol for distributed online learning in RKHS is presented. Conditions for asymptotic convergence and boundness of the networkwise regret are also provided. The simulated tests illustrate the performance of the proposed scheme.

A Required Online Course with a Public Health Focus for Third Professional Year Pharmacy Students.

PubMed

King, Amber E; Egras, Amy M

2015-06-25

To design, deliver, and evaluate the impact of a required course on student knowledge acquisition and ability to evaluate contemporary public health issues. A 2-credit course was implemented using asynchronous, online delivery. Learning activities included literature retrieval and assessment, analytic writing, quizzes, and creation of a group wiki evaluating a current public health issue. Course topics included health care reform, social determinants of health, health disparities, evidence-based medicine, end-of-life care, patient safety, and research ethics. Strong student performance on assessments indicated an ability to use higher-order cognitive domains. Online delivery provided students with the flexibility to complete assignments at their convenience, allowed participation by all students, and encouraged self-directed learning. Completion of a required, online, asynchronous course with a public health focus allowed pharmacy students to increase their knowledge of and ability to evaluate contemporary ethical, social, cultural, and governmental issues affecting pharmacy practice.

Analysis on trust influencing factors and trust model from multiple perspectives of online Auction

NASA Astrophysics Data System (ADS)

Yu, Wang

2017-10-01

Current reputation models lack the research on online auction trading completely so they cannot entirely reflect the reputation status of users and may cause problems on operability. To evaluate the user trust in online auction correctly, a trust computing model based on multiple influencing factors is established. It aims at overcoming the efficiency of current trust computing methods and the limitations of traditional theoretical trust models. The improved model comprehensively considers the trust degree evaluation factors of three types of participants according to different participation modes of online auctioneers, to improve the accuracy, effectiveness and robustness of the trust degree. The experiments test the efficiency and the performance of our model under different scale of malicious user, under environment like eBay and Sporas model. The experimental results analysis show the model proposed in this paper makes up the deficiency of existing model and it also has better feasibility.

An information spreading model based on online social networks

NASA Astrophysics Data System (ADS)

Wang, Tao; He, Juanjuan; Wang, Xiaoxia

2018-01-01

Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

Blended shared control utilizing online identification : Regulating grasping forces of a surrogate surgical grasper.

PubMed

Stephens, Trevor K; Kong, Nathan J; Dockter, Rodney L; O'Neill, John J; Sweet, Robert M; Kowalewski, Timothy M

2018-06-01

Surgical robots are increasingly common, yet routine tasks such as tissue grasping remain potentially harmful with high occurrences of tissue crush injury due to the lack of force feedback from the grasper. This work aims to investigate whether a blended shared control framework which utilizes real-time identification of the object being grasped as part of the feedback may help address the prevalence of tissue crush injury in robotic surgeries. This work tests the proposed shared control framework and tissue identification algorithm on a custom surrogate surgical robotic grasping setup. This scheme utilizes identification of the object being grasped as part of the feedback to regulate to a desired force. The blended shared control is arbitrated between human and an implicit force controller based on a computed confidence in the identification of the grasped object. The online identification is performed using least squares based on a nonlinear tissue model. Testing was performed on five silicone tissue surrogates. Twenty grasps were conducted, with half of the grasps performed under manual control and half of the grasps performed with the proposed blended shared control, to test the efficacy of the control scheme. The identification method resulted in an average of 95% accuracy across all time samples of all tissue grasps using a full leave-grasp-out cross-validation. There was an average convergence time of [Formula: see text] ms across all training grasps for all tissue surrogates. Additionally, there was a reduction in peak forces induced during grasping for all tissue surrogates when applying blended shared control online. The blended shared control using online identification more successfully regulated grasping forces to the desired target force when compared with manual control. The preliminary work on this surrogate setup for surgical grasping merits further investigation on real surgical tools and with real human tissues.

"I like talking to people on the computer": Outcomes of a home-based intervention to develop social media skills in youth with disabilities living in rural communities.

PubMed

Raghavendra, Parimala; Hutchinson, Claire; Grace, Emma; Wood, Denise; Newman, Lareen

2018-05-01

To investigate the effectiveness of a home-based social media use intervention to enhance the social networks of rural youth with disabilities. Participants were nine youth (mean age = 17.0 years) with disabilities from two rural Australian communities. The intervention consisted of providing appropriate assistive technology and social media training on individualised goals. Using mixed methods, quantitative (a single group pre-post) and qualitative (interviews with participants and their carers) measures were used to examine outcomes of training, individual experiences of the intervention, and changes to online social networks. Participants increased their performance and satisfaction with performance on social media problem areas post-intervention; paired t-tests showed statistical significance at p < .001. There was also a significant increase in the number of online communication partners; Wilcoxon Signed Ranks showed statistical significance at p < .05. The interviews highlighted increased social participation, independence and improvements to literacy. Ongoing parental concerns regarding cyber safety and inappropriate online content were noted. The findings suggest that social media training is a feasible method for increasing social networks among rural-based youth with disabilities. To sustain ongoing benefits, parents need knowledge and training in integrating assistive technology and social media. Copyright © 2018 Elsevier Ltd. All rights reserved.

Central online hemodiafiltration in Japan: management of water quality and practice.

PubMed

Yamashita, Akihiro C; Sato, Takashi

2009-01-01

Hemodiafiltration (HDF) includes a variety of technologies and preparation of ultrapure dialysis fluid has made it possible to perform online HDF and its extensive alternatives. According to current statistics, 5.8% of ESRD patients are treated with HDF in Japan. The majority of these HDF treatments are performed using the central dialysis fluid delivery system (CDDS), this is because most Japanese clinicians and researchers consider that with CDDS it is easier to prepare substitution fluid; moreover, CDDS has economical advantages against single-patient dialysis machine (SPDM)-based counterparts. The water quality at each patient station (dialysis console) is regularly validated by bacterial culture (colony-forming units) and by measuring endotoxin concentration (ET). Since ET measurement takes much less time than bacterial culture, ET is often used as an indicator to verify the water quality for online use. Dialysis fluid with ET below the detection level (usually <0.001 EU/ml) is used for online substitution. In CDDS online HDF, since dialysis clinics must prepare not only the dialysis fluid but also the substitution fluid, they need to satisfy almost the same requirements as pharmaceutical water treatment factories do. The Japanese Society for Dialysis Therapy (JSDT) together with the Japanese Society for Hemodiafiltration (JS-HDF) is now preparing guidelines to meet all these necessary requirements on a worldwide basis. (c) 2009 S. Karger AG, Basel.

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Online Homework Put to the Test: A Report on the Impact of Two Online Learning Systems on Student Performance in General Chemistry

ERIC Educational Resources Information Center

Eichler, Jack F.; Peeples, Junelyn

2013-01-01

Two different online homework systems were administered to students in a first-quarter general chemistry course. This study used a multiple regression model to control for the students' academic and socioeconomic background, and it was found that students who completed the online homework activities performed significantly better on a common…

Traditional Versus Online Biology Courses: Connecting Course Design and Student Learning in an Online Setting

PubMed Central

Biel, Rachel; Brame, Cynthia J.

2016-01-01

Online courses are a large and growing part of the undergraduate education landscape, but many biology instructors are skeptical about the effectiveness of online instruction. We reviewed studies comparing the effectiveness of online and face-to-face (F2F) undergraduate biology courses. Five studies compared student performance in multiple course sections at community colleges, while eight were smaller scale and compared student performance in particular biology courses at a variety of types of institutions. Of the larger-scale studies, two found that students in F2F sections outperformed students in online sections, and three found no significant difference; it should be noted, however, that these studies reported little information about course design. Of the eight smaller scale studies, six found no significant difference in student performance between the F2F and online sections, while two found that the online sections outperformed the F2F sections. In alignment with general findings about online teaching and learning, these results suggest that well-designed online biology courses can be effective at promoting student learning. Three recommendations for effective online instruction in biology are given: the inclusion of an online orientation to acclimate students to the online classroom; student-instructor and student-student interactions facilitated through synchronous and asynchronous communication; and elements that prompt student reflection and self-assessment. We conclude that well-designed online biology courses can be as effective as their traditional counterparts, but that more research is needed to elucidate specific course elements and structures that can maximize online students’ learning of key biology skills and concepts. PMID:28101268

Traditional Versus Online Biology Courses: Connecting Course Design and Student Learning in an Online Setting.

PubMed

Biel, Rachel; Brame, Cynthia J

2016-12-01

Online courses are a large and growing part of the undergraduate education landscape, but many biology instructors are skeptical about the effectiveness of online instruction. We reviewed studies comparing the effectiveness of online and face-to-face (F2F) undergraduate biology courses. Five studies compared student performance in multiple course sections at community colleges, while eight were smaller scale and compared student performance in particular biology courses at a variety of types of institutions. Of the larger-scale studies, two found that students in F2F sections outperformed students in online sections, and three found no significant difference; it should be noted, however, that these studies reported little information about course design. Of the eight smaller scale studies, six found no significant difference in student performance between the F2F and online sections, while two found that the online sections outperformed the F2F sections. In alignment with general findings about online teaching and learning, these results suggest that well-designed online biology courses can be effective at promoting student learning. Three recommendations for effective online instruction in biology are given: the inclusion of an online orientation to acclimate students to the online classroom; student-instructor and student-student interactions facilitated through synchronous and asynchronous communication; and elements that prompt student reflection and self-assessment. We conclude that well-designed online biology courses can be as effective as their traditional counterparts, but that more research is needed to elucidate specific course elements and structures that can maximize online students' learning of key biology skills and concepts.

Online particle detection with Neural Networks based on topological calorimetry information

NASA Astrophysics Data System (ADS)

Ciodaro, T.; Deva, D.; de Seixas, J. M.; Damazio, D.

2012-06-01

This paper presents the latest results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction using the ATLAS calorimetry information (energy measurements). The extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time by 59%. Also, the total memory necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount.

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

PubMed

Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

2017-03-01

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Lithographically fabricated silicon microreactor for in situ characterization of heterogeneous catalysts—Enabling correlative characterization techniques

NASA Astrophysics Data System (ADS)

Baier, S.; Rochet, A.; Hofmann, G.; Kraut, M.; Grunwaldt, J.-D.

2015-06-01

We report on a new modular setup on a silicon-based microreactor designed for correlative spectroscopic, scattering, and analytic on-line gas investigations for in situ studies of heterogeneous catalysts. The silicon microreactor allows a combination of synchrotron radiation based techniques (e.g., X-ray diffraction and X-ray absorption spectroscopy) as well as infrared thermography and Raman spectroscopy. Catalytic performance can be determined simultaneously by on-line product analysis using mass spectrometry. We present the design of the reactor, the experimental setup, and as a first example for an in situ study, the catalytic partial oxidation of methane showing the applicability of this reactor for in situ studies.

Lithographically fabricated silicon microreactor for in situ characterization of heterogeneous catalysts—Enabling correlative characterization techniques.

PubMed

Baier, S; Rochet, A; Hofmann, G; Kraut, M; Grunwaldt, J-D

2015-06-01

We report on a new modular setup on a silicon-based microreactor designed for correlative spectroscopic, scattering, and analytic on-line gas investigations for in situ studies of heterogeneous catalysts. The silicon microreactor allows a combination of synchrotron radiation based techniques (e.g., X-ray diffraction and X-ray absorption spectroscopy) as well as infrared thermography and Raman spectroscopy. Catalytic performance can be determined simultaneously by on-line product analysis using mass spectrometry. We present the design of the reactor, the experimental setup, and as a first example for an in situ study, the catalytic partial oxidation of methane showing the applicability of this reactor for in situ studies.

A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

NASA Astrophysics Data System (ADS)

Lee, Kun Chang; Park, Bong-Won

Many online game users purchase game items with which to play free-to-play games. Because of a lack of research into which there is no specified framework for categorizing the values of game items, this study proposes four types of online game item values based on an analysis of literature regarding online game characteristics. It then proposes to investigate how online game users perceive satisfaction and purchase intention from the proposed four types of online game item values. Though regression analysis has been used frequently to answer this kind of research question, we propose a new approach, a General Bayesian Network (GBN), which can be performed in an understandable way without sacrificing predictive accuracy. Conventional techniques, such as regression analysis, do not provide significant explanation for this kind of problem because they are fixed to a linear structure and are limited in explaining why customers are likely to purchase game items and if they are satisfied with their purchases. In contrast, the proposed GBN provides a flexible underlying structure based on questionnaire survey data and offers robust decision support on this kind of research question by identifying its causal relationships. To illustrate the validity of GBN in solving the research question in this study, 327 valid questionnaires were analyzed using GBN with what-if and goal-seeking approaches. The experimental results were promising and meaningful in comparison with regression analysis results.

Reduced kernel recursive least squares algorithm for aero-engine degradation prediction

NASA Astrophysics Data System (ADS)

Zhou, Haowen; Huang, Jinquan; Lu, Feng

2017-10-01

Kernel adaptive filters (KAFs) generate a linear growing radial basis function (RBF) network with the number of training samples, thereby lacking sparseness. To deal with this drawback, traditional sparsification techniques select a subset of original training data based on a certain criterion to train the network and discard the redundant data directly. Although these methods curb the growth of the network effectively, it should be noted that information conveyed by these redundant samples is omitted, which may lead to accuracy degradation. In this paper, we present a novel online sparsification method which requires much less training time without sacrificing the accuracy performance. Specifically, a reduced kernel recursive least squares (RKRLS) algorithm is developed based on the reduced technique and the linear independency. Unlike conventional methods, our novel methodology employs these redundant data to update the coefficients of the existing network. Due to the effective utilization of the redundant data, the novel algorithm achieves a better accuracy performance, although the network size is significantly reduced. Experiments on time series prediction and online regression demonstrate that RKRLS algorithm requires much less computational consumption and maintains the satisfactory accuracy performance. Finally, we propose an enhanced multi-sensor prognostic model based on RKRLS and Hidden Markov Model (HMM) for remaining useful life (RUL) estimation. A case study in a turbofan degradation dataset is performed to evaluate the performance of the novel prognostic approach.

A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.

PubMed

Wöhrle, Hendrik; Tabie, Marc; Kim, Su Kyoung; Kirchner, Frank; Kirchner, Elsa Andrea

2017-07-03

A current trend in the development of assistive devices for rehabilitation, for example exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality and usability, for example by predicting the patient's upcoming movements using electroencephalography (EEG) or electromyography (EMG). However, these modalities have different temporal properties and classification accuracies, which results in specific advantages and disadvantages. To use physiological data analysis in rehabilitation devices, the processing should be performed in real-time, guarantee close to natural movement onset support, provide high mobility, and should be performed by miniaturized systems that can be embedded into the rehabilitation device. We present a novel Field Programmable Gate Array (FPGA) -based system for real-time movement prediction using physiological data. Its parallel processing capabilities allows the combination of movement predictions based on EEG and EMG and additionally a P300 detection, which is likely evoked by instructions of the therapist. The system is evaluated in an offline and an online study with twelve healthy subjects in total. We show that it provides a high computational performance and significantly lower power consumption in comparison to a standard PC. Furthermore, despite the usage of fixed-point computations, the proposed system achieves a classification accuracy similar to systems with double precision floating-point precision.

A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction

PubMed Central

Wöhrle, Hendrik; Tabie, Marc; Kim, Su Kyoung; Kirchner, Frank; Kirchner, Elsa Andrea

2017-01-01

A current trend in the development of assistive devices for rehabilitation, for example exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality and usability, for example by predicting the patient’s upcoming movements using electroencephalography (EEG) or electromyography (EMG). However, these modalities have different temporal properties and classification accuracies, which results in specific advantages and disadvantages. To use physiological data analysis in rehabilitation devices, the processing should be performed in real-time, guarantee close to natural movement onset support, provide high mobility, and should be performed by miniaturized systems that can be embedded into the rehabilitation device. We present a novel Field Programmable Gate Array (FPGA) -based system for real-time movement prediction using physiological data. Its parallel processing capabilities allows the combination of movement predictions based on EEG and EMG and additionally a P300 detection, which is likely evoked by instructions of the therapist. The system is evaluated in an offline and an online study with twelve healthy subjects in total. We show that it provides a high computational performance and significantly lower power consumption in comparison to a standard PC. Furthermore, despite the usage of fixed-point computations, the proposed system achieves a classification accuracy similar to systems with double precision floating-point precision. PMID:28671632

Multiple comorbidities of 21 psychological disorders and relationships with psychosocial variables: a study of the online assessment and diagnostic system within a web-based population.

PubMed

Al-Asadi, Ali M; Klein, Britt; Meyer, Denny

2015-02-26

While research in the area of e-mental health has received considerable attention over the last decade, there are still many areas that have not been addressed. One such area is the comorbidity of psychological disorders in a Web-based sample using online assessment and diagnostic tools, and the relationships between comorbidities and psychosocial variables. We aimed to identify comorbidities of psychological disorders of an online sample using an online diagnostic tool. Based on diagnoses made by an automated online assessment and diagnostic system administered to a large group of online participants, multiple comorbidities (co-occurrences) of 21 psychological disorders for males and females were identified. We examined the relationships between dyadic comorbidities of anxiety and depressive disorders and the psychosocial variables sex, age, suicidal ideation, social support, and quality of life. An online complex algorithm based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision, was used to assign primary and secondary diagnoses of 21 psychological disorders to 12,665 online participants. The frequency of co-occurrences of psychological disorders for males and females were calculated for all disorders. A series of hierarchical loglinear analyses were performed to examine the relationships between the dyadic comorbidities of depression and various anxiety disorders and the variables suicidal ideation, social support, quality of life, sex, and age. A 21-by-21 frequency of co-occurrences of psychological disorders matrix revealed the presence of multiple significant dyadic comorbidities for males and females. Also, for those with some of the dyadic depression and the anxiety disorders, the odds for having suicidal ideation, reporting inadequate social support, and poorer quality of life increased for those with two-disorder comorbidity than for those with only one of the same two disorders. Comorbidities of several psychological disorders using an online assessment tool within a Web-based population were similar to those found in face-to-face clinics using traditional assessment tools. Results provided support for the transdiagnostic approaches and confirmed the positive relationship between comorbidity and suicidal ideation, the negative relationship between comorbidity and social support, and the negative relationship comorbidity and quality of life. Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG).

Multiple Comorbidities of 21 Psychological Disorders and Relationships With Psychosocial Variables: A Study of the Online Assessment and Diagnostic System Within a Web-Based Population

PubMed Central

Klein, Britt; Meyer, Denny

2015-01-01

Background While research in the area of e-mental health has received considerable attention over the last decade, there are still many areas that have not been addressed. One such area is the comorbidity of psychological disorders in a Web-based sample using online assessment and diagnostic tools, and the relationships between comorbidities and psychosocial variables. Objective We aimed to identify comorbidities of psychological disorders of an online sample using an online diagnostic tool. Based on diagnoses made by an automated online assessment and diagnostic system administered to a large group of online participants, multiple comorbidities (co-occurrences) of 21 psychological disorders for males and females were identified. We examined the relationships between dyadic comorbidities of anxiety and depressive disorders and the psychosocial variables sex, age, suicidal ideation, social support, and quality of life. Methods An online complex algorithm based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision, was used to assign primary and secondary diagnoses of 21 psychological disorders to 12,665 online participants. The frequency of co-occurrences of psychological disorders for males and females were calculated for all disorders. A series of hierarchical loglinear analyses were performed to examine the relationships between the dyadic comorbidities of depression and various anxiety disorders and the variables suicidal ideation, social support, quality of life, sex, and age. Results A 21-by-21 frequency of co-occurrences of psychological disorders matrix revealed the presence of multiple significant dyadic comorbidities for males and females. Also, for those with some of the dyadic depression and the anxiety disorders, the odds for having suicidal ideation, reporting inadequate social support, and poorer quality of life increased for those with two-disorder comorbidity than for those with only one of the same two disorders. Conclusions Comorbidities of several psychological disorders using an online assessment tool within a Web-based population were similar to those found in face-to-face clinics using traditional assessment tools. Results provided support for the transdiagnostic approaches and confirmed the positive relationship between comorbidity and suicidal ideation, the negative relationship between comorbidity and social support, and the negative relationship comorbidity and quality of life. Trial Registration Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG) PMID:25803420

Self-paced brain-computer interface control of ambulation in a virtual reality environment.

PubMed

Wang, Po T; King, Christine E; Chui, Luis A; Do, An H; Nenadic, Zoran

2012-10-01

Spinal cord injury (SCI) often leaves affected individuals unable to ambulate. Electroencephalogram (EEG) based brain-computer interface (BCI) controlled lower extremity prostheses may restore intuitive and able-body-like ambulation after SCI. To test its feasibility, the authors developed and tested a novel EEG-based, data-driven BCI system for intuitive and self-paced control of the ambulation of an avatar within a virtual reality environment (VRE). Eight able-bodied subjects and one with SCI underwent the following 10-min training session: subjects alternated between idling and walking kinaesthetic motor imageries (KMI) while their EEG were recorded and analysed to generate subject-specific decoding models. Subjects then performed a goal-oriented online task, repeated over five sessions, in which they utilized the KMI to control the linear ambulation of an avatar and make ten sequential stops at designated points within the VRE. The average offline training performance across subjects was 77.2 ± 11.0%, ranging from 64.3% (p = 0.001 76) to 94.5% (p = 6.26 × 10(-23)), with chance performance being 50%. The average online performance was 8.5 ± 1.1 (out of 10) successful stops and 303 ± 53 s completion time (perfect = 211 s). All subjects achieved performances significantly different than those of random walk (p < 0.05) in 44 of the 45 online sessions. By using a data-driven machine learning approach to decode users' KMI, this BCI-VRE system enabled intuitive and purposeful self-paced control of ambulation after only 10 minutes training. The ability to achieve such BCI control with minimal training indicates that the implementation of future BCI-lower extremity prosthesis systems may be feasible.

Online Self-Administered Cognitive Testing Using the Amsterdam Cognition Scan: Establishing Psychometric Properties and Normative Data.

PubMed

Feenstra, Heleen Em; Vermeulen, Ivar E; Murre, Jaap Mj; Schagen, Sanne B

2018-05-30

Online tests enable efficient self-administered assessments and consequently facilitate large-scale data collection for many fields of research. The Amsterdam Cognition Scan is a new online neuropsychological test battery that measures a broad variety of cognitive functions. The aims of this study were to evaluate the psychometric properties of the Amsterdam Cognition Scan and to establish regression-based normative data. The Amsterdam Cognition Scan was self-administrated twice from home-with an interval of 6 weeks-by 248 healthy Dutch-speaking adults aged 18 to 81 years. Test-retest reliability was moderate to high and comparable with that of equivalent traditional tests (intraclass correlation coefficients: .45 to .80; .83 for the Amsterdam Cognition Scan total score). Multiple regression analyses indicated that (1) participants' age negatively influenced all (12) cognitive measures, (2) gender was associated with performance on six measures, and (3) education level was positively associated with performance on four measures. In addition, we observed influences of tested computer skills and of self-reported amount of computer use on cognitive performance. Demographic characteristics that proved to influence Amsterdam Cognition Scan test performance were included in regression-based predictive formulas to establish demographically adjusted normative data. Initial results from a healthy adult sample indicate that the Amsterdam Cognition Scan has high usability and can give reliable measures of various generic cognitive ability areas. For future use, the influence of computer skills and experience should be further studied, and for repeated measurements, computer configuration should be consistent. The reported normative data allow for initial interpretation of Amsterdam Cognition Scan performances. ©Heleen EM Feenstra, Ivar E Vermeulen, Jaap MJ Murre, Sanne B Schagen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

Comparison of online and offline based merging methods for high resolution rainfall intensities

NASA Astrophysics Data System (ADS)

Shehu, Bora; Haberlandt, Uwe

2016-04-01

Accurate rainfall intensities with high spatial and temporal resolution are crucial for urban flow prediction. Commonly, raw or bias corrected radar fields are used for forecasting, while different merging products are employed for simulation. The merging products are proven to be adequate for rainfall intensities estimation, however their application in forecasting is limited as they are developed for offline mode. This study aims at adapting and refining the offline merging techniques for the online implementation, and at comparing the performance of these methods for high resolution rainfall data. Radar bias correction based on mean fields and quantile mapping are analyzed individually and also are implemented in conditional merging. Special attention is given to the impact of different spatial and temporal filters on the predictive skill of all methods. Raw radar data and kriging interpolation of station data are considered as a reference to check the benefit of the merged products. The methods are applied for several extreme events in the time period 2006-2012 caused by different meteorological conditions, and their performance is evaluated by split sampling. The study area is located within the 112 km radius of Hannover radar in Lower Saxony, Germany and the data set constitutes of 80 recording stations in 5 min time steps. The results of this study reveal how the performance of the methods is affected by the adjustment of radar data, choice of merging method and selected event. Merging techniques can be used to improve the performance of online rainfall estimation, which gives way to the application of merging products in forecasting.

Online fingerprint verification.

PubMed

Upendra, K; Singh, S; Kumar, V; Verma, H K

2007-01-01

As organizations search for more secure authentication methods for user access, e-commerce, and other security applications, biometrics is gaining increasing attention. With an increasing emphasis on the emerging automatic personal identification applications, fingerprint based identification is becoming more popular. The most widely used fingerprint representation is the minutiae based representation. The main drawback with this representation is that it does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Also, it is difficult quickly to match two fingerprint images containing different number of unregistered minutiae points. In this study filter bank based representation, which eliminates these weakness, is implemented and the overall performance of the developed system is tested. The results have shown that this system can be used effectively for secure online verification applications.

Understanding the Psychological Process of Avoidance-Based Self-Regulation on Facebook.

PubMed

Marder, Ben; Houghton, David; Joinson, Adam; Shankar, Avi; Bull, Eleanor

2016-05-01

In relation to social network sites, prior research has evidenced behaviors (e.g., censoring) enacted by individuals used to avoid projecting an undesired image to their online audiences. However, no work directly examines the psychological process underpinning such behavior. Drawing upon the theory of self-focused attention and related literature, a model is proposed to fill this research gap. Two studies examine the process whereby public self-awareness (stimulated by engaging with Facebook) leads to a self-comparison with audience expectations and, if discrepant, an increase in social anxiety, which results in the intention to perform avoidance-based self-regulation. By finding support for this process, this research contributes an extended understanding of the psychological factors leading to avoidance-based regulation when online selves are subject to surveillance.

On-line crack prognosis in attachment lug using Lamb wave-deterministic resampling particle filter-based method

NASA Astrophysics Data System (ADS)

Yuan, Shenfang; Chen, Jian; Yang, Weibo; Qiu, Lei

2017-08-01

Fatigue crack growth prognosis is important for prolonging service time, improving safety, and reducing maintenance cost in many safety-critical systems, such as in aircraft, wind turbines, bridges, and nuclear plants. Combining fatigue crack growth models with the particle filter (PF) method has proved promising to deal with the uncertainties during fatigue crack growth and reach a more accurate prognosis. However, research on prognosis methods integrating on-line crack monitoring with the PF method is still lacking, as well as experimental verifications. Besides, the PF methods adopted so far are almost all sequential importance resampling-based PFs, which usually encounter sample impoverishment problems, and hence performs poorly. To solve these problems, in this paper, the piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The deterministic resampling PF (DRPF) is proposed to be used in fatigue crack growth prognosis, which can overcome the sample impoverishment problem. The proposed method is verified through fatigue tests of attachment lugs, which are a kind of important joint component in aerospace systems.

Online EEG artifact removal for BCI applications by adaptive spatial filtering.

PubMed

Guarnieri, Roberto; Marino, Marco; Barban, Federico; Ganzetti, Marco; Mantini, Dante

2018-06-28

The performance of brain computer interfaces (BCIs) based on electroencephalography (EEG) data strongly depends on the effective attenuation of artifacts that are mixed in the recordings. To address this problem, we have developed a novel online EEG artifact removal method for BCI applications, which combines blind source separation (BSS) and regression (REG) analysis. The BSS-REG method relies on the availability of a calibration dataset of limited duration for the initialization of a spatial filter using BSS. Online artifact removal is implemented by dynamically adjusting the spatial filter in the actual experiment, based on a linear regression technique. Our results showed that the BSS-REG method is capable of attenuating different kinds of artifacts, including ocular and muscular, while preserving true neural activity. Thanks to its low computational requirements, BSS-REG can be applied to low-density as well as high-density EEG data. We argue that BSS-REG may enable the development of novel BCI applications requiring high-density recordings, such as source-based neurofeedback and closed-loop neuromodulation. © 2018 IOP Publishing Ltd.

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Online submicron particle sizing by dynamic light scattering using autodilution

NASA Technical Reports Server (NTRS)

Nicoli, David F.; Elings, V. B.

1989-01-01

Efficient production of a wide range of commercial products based on submicron colloidal dispersions would benefit from instrumentation for online particle sizing, permitting real time monitoring and control of the particle size distribution. Recent advances in the technology of dynamic light scattering (DLS), especially improvements in algorithms for inversion of the intensity autocorrelation function, have made it ideally suited to the measurement of simple particle size distributions in the difficult submicron region. Crucial to the success of an online DSL based instrument is a simple mechanism for automatically sampling and diluting the starting concentrated sample suspension, yielding a final concentration which is optimal for the light scattering measurement. A proprietary method and apparatus was developed for performing this function, designed to be used with a DLS based particle sizing instrument. A PC/AT computer is used as a smart controller for the valves in the sampler diluter, as well as an input-output communicator, video display and data storage device. Quantitative results are presented for a latex suspension and an oil-in-water emulsion.

Overview of online two-dimensional liquid chromatography based on cell membrane chromatography for screening target components from traditional Chinese medicines.

PubMed

Muhammad, Saqib; Han, Shengli; Xie, Xiaoyu; Wang, Sicen; Aziz, Muhammad Majid

2017-01-01

Cell membrane chromatography is a simple, specific, and time-saving technique for studying drug-receptor interactions, screening of active components from complex mixtures, and quality control of traditional Chinese medicines. However, the short column life, low sensitivity, low column efficiency (so cannot resolve satisfactorily mixture of compounds), low peak capacity, and inefficient in structure identification were bottleneck in its application. Combinations of cell membrane chromatography with multidimensional chromatography such as two-dimensional liquid chromatography and high sensitivity detectors like mass have significantly reduced many of the above-mentioned shortcomings. This paper provides an overview of the current advances in online two-dimensional-based cell membrane chromatography for screening target components from traditional Chinese medicines with particular emphasis on the instrumentation, preparation of cell membrane stationary phase, advantages, and disadvantages compared to alternative approaches. The last section of the review summarizes the applications of the online two-dimensional high-performance liquid chromatography based cell membrane chromatography reported since its emergence to date (2010-June 2016). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance-scalable volumetric data classification for online industrial inspection

NASA Astrophysics Data System (ADS)

Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

2002-03-01

Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

An Internet-Based Radiology Course in Medical School: Comparison of Academic Performance of Students on Campus Versus Those With Absenteeism Due to Residency Interviews.

PubMed

Alexander, Andrew George; Deas, Deborah; Lyons, Paul Eric

2018-05-18

Imaging and its optimal use are imperative to the practice of medicine, yet many students don't receive a formal education in radiology. Concurrently, students look for ways to take time away from medical school for residency interviewing. Web-based instruction provides an opportunity to combine these imperatives using online modalities. A largely Web-based course in radiology during the 4th year of medical school was evaluated both for its acceptance to students who needed to be away from campus for interviews, and its effectiveness on a nationally administered standardized test. All students were placed into a structured program utilizing online videos, online modules, online textbook assignments, and live interactive online lectures. Over half of the course could be completed away from campus. The Alliance of Medical Student Educators in Radiology test exam bank was used as a final exam to evaluate medical knowledge. Positive student feedback included the freedom to travel for interviews, hands-on ultrasound training, interactive teaching sessions, and quality Web-based learning modules. Negative feedback included taking quizzes in-person, a perceived outdated online textbook, and physically shadowing hospital technicians. Most students elected to take the course during the interview months of October through January. The Alliance of Medical Student Educators in Radiology final exam results (70.5%) were not significantly different than the national cohort (70%) who took the course in-person. Test scores from students taking the course during interview travel months were not significantly different from students who took the course before (P=.30) or after (P=.34) the interview season. Students desire to learn radiology and often choose to do so when they need to be away from campus during the fall of their 4th year of study to accomplish their residency interviews. Web-based education in radiology allows students' interview traveling and radiology course objectives to be successfully met without adversely affecting the outcomes on a nationally normed examination in radiology. A curriculum that includes online content and live Web-based teleconference access to faculty can accomplish both imperatives. ©Andrew George Alexander, Deborah Deas, Paul Eric Lyons. Originally published in JMIR Medical Education (http://mededu.jmir.org), 18.05.2018.

An Analysis of Online Students' Behaviors on Course Sites and the Effect on Learning Performance: A Case Study of Four LIS Online Classes

ERIC Educational Resources Information Center

Zhang, Xiangmin

2016-01-01

This research investigated the relationship between online students' behaviors in a learning management system and their learning performance, as measured by their final grades. Four online information technology classes in a major U.S. library and information science program were studied. The course sites' log data, as well as the students' final…

Video Gaming in a Hyperconnected World: A Cross-sectional Study of Heavy Gaming, Problematic Gaming Symptoms, and Online Socializing in Adolescents.

PubMed

Colder Carras, Michelle; Van Rooij, Antonius J; Van de Mheen, Dike; Musci, Rashelle; Xue, Qian-Li; Mendelson, Tamar

2017-03-01

Examining online social interactions along with patterns of video gaming behaviors and game addiction symptoms has the potential to enrich our understanding of disorders related to excessive video game play. We performed latent class analysis in a sample of 9733 adolescents based on heavy use of games, social networking and instant messaging, and game addiction symptoms. We used latent class regression to determine associations between classes, psychosocial well-being and friendship quality. We identified two types of heavy gaming classes that differed in probability of online social interaction. Classes with more online social interaction reported fewer problematic gaming symptoms than those with less online social interaction. Most adolescents estimated to be in heavy gaming classes had more depressive symptoms than normative classes. Male non-social gamers had more social anxiety. Female social gamers had less social anxiety and loneliness, but lower self-esteem. Friendship quality attenuated depression in some male social gamers, but strengthened associations with loneliness in some male non-social gamers. In adolescents, symptoms of video game addiction depend not only on video game play but also on concurrent levels of online communication, and those who are very socially active online report fewer symptoms of game addiction.

Video Gaming in a Hyperconnected World: A Cross-sectional Study of Heavy Gaming, Problematic Gaming Symptoms, and Online Socializing in Adolescents

PubMed Central

Colder Carras, Michelle; Van Rooij, Antonius J.; Van de Mheen, Dike; Musci, Rashelle; Xue, Qian-Li; Mendelson, Tamar

2016-01-01

Aims Examining online social interactions along with patterns of video gaming behaviors and game addiction symptoms has the potential to enrich our understanding of disorders related to excessive video game play. Methods We performed latent class analysis in a sample of 9733 adolescents based on heavy use of games, social networking and instant messaging, and game addiction symptoms. We used latent class regression to determine associations between classes, psychosocial well-being and friendship quality. Results We identified two types of heavy gaming classes that differed in probability of online social interaction. Classes with more online social interaction reported fewer problematic gaming symptoms than those with less online social interaction. Most adolescents estimated to be in heavy gaming classes had more depressive symptoms than normative classes. Male non-social gamers had more social anxiety. Female social gamers had less social anxiety and loneliness, but lower self-esteem. Friendship quality attenuated depression in some male social gamers, but strengthened associations with loneliness in some male non-social gamers. Conclusions In adolescents, symptoms of video game addiction depend not only on video game play but also on concurrent levels of online communication, and those who are very socially active online report fewer symptoms of game addiction. PMID:28260834

Feasibility of on-line temperature-based hyperthermia treatment planning to improve tumour temperatures during locoregional hyperthermia.

PubMed

Kok, H P; Korshuize-van Straten, L; Bakker, A; de Kroon-Oldenhof, R; Westerveld, G H; Versteijne, E; Stalpers, L J A; Crezee, J

2017-11-16

The effectiveness of hyperthermia is strongly dependent on the achieved tumour temperatures. Phased-array systems allow flexible power steering to realise good tumour heating while avoiding excessive heating in normal tissue, but the limited quantitative accuracy of pre-treatment planning complicates realising optimal tumour heating. On-line hyperthermia treatment planning could help to improve the heating quality. This paper demonstrates the feasibility of using on-line temperature-based treatment planning to improve the heating quality during hyperthermia in three patients. Hyperthermia treatment planning was performed using the Plan2Heat software package combined with a dedicated graphical user interface for on-line application. Electric fields were pre-calculated to allow instant update and visualisation of the predicted temperature distribution for user-selected phase-amplitude settings during treatment. On-line treatment planning using manual variation of system settings for the AMC-8 hyperthermia system was applied in one patient with a deep-seated pelvic melanoma metastasis and two cervical cancer patients. For a clinically relevant improvement the increase in average target temperature should be at least 0.2 °C. With the assistance of on-line treatment planning a substantial improvement in tumour temperatures was realised for all three patients. In the melanoma patient, the average measured target temperature increased from 38.30 °C to 39.15 °C (i.e. +0.85 °C). In the cervical cancer patients, the average measured target temperature increased from 41.30 °C to 42.05 °C (i.e. +0.75 °C) and from 41.70 °C to 42.80 °C (i.e. +1.1 °C), respectively. On-line temperature-based treatment planning is clinically feasible to improve tumour temperatures. A next, worthwhile step is automatic optimisation for a larger number of patients.

Use of Interactive Web-Based Exercises for English as a Foreign Language Learning: Learners' Perceptions

ERIC Educational Resources Information Center

Wang, Yen-Hui

2014-01-01

The study investigated the learner perceptions of a CALL component in a blended language learning context. 52 Taiwanese college students attended instructional classroom sessions and did weekly online assignments in the form of interactive web-based exercises over one semester. Their learning performance was measured by means of two computer-based…

Teaching College Microeconomics: Online vs. Traditional Classroom Instruction

ERIC Educational Resources Information Center

McCarty, Cynthia; Bennett, Doris; Carter, Shawn

2013-01-01

The use of online course offerings in college has grown sharply in recent years. Previous research, while limited, is inconclusive in determining expected student performance in online versus a traditional lecture format. This paper focuses specifically on student performance in introductory microeconomics classes, analyzing learning differences…

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

NASA Technical Reports Server (NTRS)

Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

2003-01-01

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

Efficient and Privacy-Preserving Online Medical Prediagnosis Framework Using Nonlinear SVM.

PubMed

Zhu, Hui; Liu, Xiaoxia; Lu, Rongxing; Li, Hui

2017-05-01

With the advances of machine learning algorithms and the pervasiveness of network terminals, the online medical prediagnosis system, which can provide the diagnosis of healthcare provider anywhere anytime, has attracted considerable interest recently. However, the flourish of online medical prediagnosis system still faces many challenges including information security and privacy preservation. In this paper, we propose an e fficient and privacy-preserving online medical prediagnosis framework, called eDiag, by using nonlinear kernel support vector machine (SVM). With eDiag, the sensitive personal health information can be processed without privacy disclosure during online prediagnosis service. Specifically, based on an improved expression for the nonlinear SVM, an efficient and privacy-preserving classification scheme is introduced with lightweight multiparty random masking and polynomial aggregation techniques. The encrypted user query is directly operated at the service provider without decryption, and the diagnosis result can only be decrypted by user. Through extensive analysis, we show that eDiag can ensure that users' health information and healthcare provider's prediction model are kept confidential, and has significantly less computation and communication overhead than existing schemes. In addition, performance evaluations via implementing eDiag on smartphone and computer demonstrate eDiag's effectiveness in term of real online environment.

WWC Review of the Report "Daily Online Testing in Large Classes: Boosting College Performance While Reducing Achievement Gaps." What Works Clearinghouse Single Study Review

ERIC Educational Resources Information Center

What Works Clearinghouse, 2014

2014-01-01

The 2013 study, "Daily Online Testing in Large Classes: Boosting College Performance While Reducing Achievement Gaps," examined the impact of frequent online testing and immediate feedback on the academic performance of college students. The study was conducted at the University of Texas in the fall of 2008 and 2011. Researchers found…

An online detection system for aggregate sizes and shapes based on digital image processing

NASA Astrophysics Data System (ADS)

Yang, Jianhong; Chen, Sijia

2017-02-01

Traditional aggregate size measuring methods are time-consuming, taxing, and do not deliver online measurements. A new online detection system for determining aggregate size and shape based on a digital camera with a charge-coupled device, and subsequent digital image processing, have been developed to overcome these problems. The system captures images of aggregates while falling and flat lying. Using these data, the particle size and shape distribution can be obtained in real time. Here, we calibrate this method using standard globules. Our experiments show that the maximum particle size distribution error was only 3 wt%, while the maximum particle shape distribution error was only 2 wt% for data derived from falling aggregates, having good dispersion. In contrast, the data for flat-lying aggregates had a maximum particle size distribution error of 12 wt%, and a maximum particle shape distribution error of 10 wt%; their accuracy was clearly lower than for falling aggregates. However, they performed well for single-graded aggregates, and did not require a dispersion device. Our system is low-cost and easy to install. It can successfully achieve online detection of aggregate size and shape with good reliability, and it has great potential for aggregate quality assurance.

Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.

PubMed

Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun

2017-03-01

H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.

Context-Aware Online Commercial Intention Detection

NASA Astrophysics Data System (ADS)

Hu, Derek Hao; Shen, Dou; Sun, Jian-Tao; Yang, Qiang; Chen, Zheng

With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual transactions happen. For many Web users, their online commercial activities start from submitting a search query to search engines. Just like the common Web search queries, the queries with commercial intention are usually very short. Recognizing the queries with commercial intention against the common queries will help search engines provide proper search results and advertisements, help Web users obtain the right information they desire and help the advertisers benefit from the potential transactions. However, the intentions behind a query vary a lot for users with different background and interest. The intentions can even be different for the same user, when the query is issued in different contexts. In this paper, we present a new algorithm framework based on skip-chain conditional random field (SCCRF) for automatically classifying Web queries according to context-based online commercial intention. We analyze our algorithm performance both theoretically and empirically. Extensive experiments on several real search engine log datasets show that our algorithm can improve more than 10% on F1 score than previous algorithms on commercial intention detection.

Electron Spin Relaxation Can Enhance the Performance of a Cryptochrome-Based Magnetic Compass Sensor

DTIC Science & Technology

2016-08-19

quantumbiology,migratory birds, animal navigation, radical pairmechanism Supplementarymaterial for this article is available online Abstract The radical ...certain spin relaxationmechanisms can enhance its performance.We focus on the flavin–tryptophan radical pair in cryptochrome, currently the only...candidatemagnetoreceptor molecule. Correlation functions for fluctuations in the distance between the two radicals in Arabidopsis thaliana cryptochrome

Sequential Geoacoustic Filtering and Geoacoustic Inversion

DTIC Science & Technology

2015-09-30

and online algorithms. We show here that CS obtains higher resolution than MVDR, even in scenarios, which favor classical high-resolution methods...windows actually performs better than conventional beamforming and MVDR/ MUSIC (see Figs. 1-2). Compressive geoacoustic inversion Geoacoustic...histograms based on 100 Monte Carlo simulations, and c)(CS, exhaustive-search, CBF, MVDR, and MUSIC performance versus SNR. The true source positions

Supporting the Distant Student: The Effect of ARCS-Based Strategies on Confidence and Performance

ERIC Educational Resources Information Center

Huett, Jason Bond; Young, Jon; Huett, Kimberly Cleaves; Moller, Leslie; Bray, Marty

2008-01-01

The purpose of this research was to manipulate the component of confidence found in Keller's ARCS Model to enhance the confidence and performance of undergraduate students enrolled in an online course at a Texas University. This experiment used SAM Office 2003 and WebCT for the delivery of the tactics, strategies, confidence-enhancing e-mails…

On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

PubMed Central

Calcagno, Cristina; Coppo, Mario

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed. PMID:25050327

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

PubMed

Aldinucci, Marco; Calcagno, Cristina; Coppo, Mario; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Torquati, Massimo; Troina, Angelo

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

Comparison of Online Versus Classroom Delivery of an Immunization Elective Course

PubMed Central

Pitterle, Michael E.; Hayney, Mary S.

2014-01-01

Objective. To compare performance and preferences of students who were randomly allocated to classroom or online sections of an elective course on immunization. Methods. Students were randomly assigned to either the classroom or online section. All course activities (lectures, quizzes, case discussions, vaccine administration, and final examination) were the same for both sections, except for the delivery of lecture material. Assessment. Students were surveyed on their preferences at the beginning and end of the semester. At the end of the semester, the majority of students in the classroom group preferred classroom or blended delivery while the majority of students in the online group preferred blended or online delivery (p<0.01). Student performance was compared at the end of the semester. There was no significant difference for any of the grades in the course between the 2 sections. Conclusion. There was no difference in student performance between the classroom and online sections, suggesting that online delivery is an effective way to teach students about immunization. PMID:24954936

KMgene: a unified R package for gene-based association analysis for complex traits.

PubMed

Yan, Qi; Fang, Zhou; Chen, Wei; Stegle, Oliver

2018-02-09

In this report, we introduce an R package KMgene for performing gene-based association tests for familial, multivariate or longitudinal traits using kernel machine (KM) regression under a generalized linear mixed model (GLMM) framework. Extensive simulations were performed to evaluate the validity of the approaches implemented in KMgene. http://cran.r-project.org/web/packages/KMgene. qi.yan@chp.edu or wei.chen@chp.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

The development and implementation of an online applied biochemistry bridge course for a dental hygiene curriculum.

PubMed

Gadbury-Amyot, Cynthia C; Overman, Pamela R; Crain, Geralyn

2009-01-01

This article describes a curricular change project designed to improve instruction in biochemistry. After years of unsatisfactory outcomes from a dental hygiene biochemistry course, a decision was made to change the traditional lecture-based course to an online format. Using online technology and principles of educational pedagogy, a course was developed that fosters application of biomaterials principles to dental hygiene practice and provides a bridge between prerequisite chemistry coursework and biochemistry in a health professions program. Members of the dental hygiene graduating Classes of 2007 and 2008 participated in the revised course. The outcome measures used to assess the effectiveness of the revised course were student end-of-semester course evaluations, graduating senior survey results, student course performance, and National Board examination performance. While the results are based on only two classes, the positive outcomes suggest that the revision was a worthwhile endeavor. The use of technology in teaching holds the potential for solving many of the curriculum and instruction issues currently under discussion: overcrowding of the curriculum, lack of active learning methods, and basic sciences taught in isolation from the rest of the curriculum. It is hoped that the results of this change will be helpful to other faculty members seeking curricular change and innovation.

Online virtual isocenter based radiation field targeting for high performance small animal microirradiation

NASA Astrophysics Data System (ADS)

Stewart, James M. P.; Ansell, Steve; Lindsay, Patricia E.; Jaffray, David A.

2015-12-01

Advances in precision microirradiators for small animal radiation oncology studies have provided the framework for novel translational radiobiological studies. Such systems target radiation fields at the scale required for small animal investigations, typically through a combination of on-board computed tomography image guidance and fixed, interchangeable collimators. Robust targeting accuracy of these radiation fields remains challenging, particularly at the millimetre scale field sizes achievable by the majority of microirradiators. Consistent and reproducible targeting accuracy is further hindered as collimators are removed and inserted during a typical experimental workflow. This investigation quantified this targeting uncertainty and developed an online method based on a virtual treatment isocenter to actively ensure high performance targeting accuracy for all radiation field sizes. The results indicated that the two-dimensional field placement uncertainty was as high as 1.16 mm at isocenter, with simulations suggesting this error could be reduced to 0.20 mm using the online correction method. End-to-end targeting analysis of a ball bearing target on radiochromic film sections showed an improved targeting accuracy with the three-dimensional vector targeting error across six different collimators reduced from 0.56+/- 0.05 mm (mean  ±  SD) to 0.05+/- 0.05 mm for an isotropic imaging voxel size of 0.1 mm.

Environmental scan and evaluation of best practices for online systematic review resources.

PubMed

Parker, Robin M N; Boulos, Leah M; Visintini, Sarah; Ritchie, Krista; Hayden, Jill

2018-04-01

Online training for systematic review methodology is an attractive option due to flexibility and limited availability of in-person instruction. Librarians often direct new reviewers to these online resources, so they should be knowledgeable about the variety of available resources. The objective for this project was to conduct an environmental scan of online systematic review training resources and evaluate those identified resources. The authors systematically searched for electronic learning resources pertaining to systematic review methods. After screening for inclusion, we collected data about characteristics of training resources and assigned scores in the domains of (1) content, (2) design, (3) interactivity, and (4) usability by applying a previously published evaluation rubric for online instruction modules. We described the characteristics and scores for each training resource and compared performance across the domains. Twenty training resources were evaluated. Average overall score of online instructional resources was 61%. Online courses (n=7) averaged 73%, web modules (n=5) 64%, and videos (n=8) 48%. The top 5 highest scoring resources were in course or web module format, featured high interactivity, and required a longer (>5hrs) time commitment from users. This study revealed that resources include appropriate content but are less likely to adhere to principles of online training design and interactivity. Awareness of these resources will allow librarians to make informed recommendations for training based on patrons' needs. Future online systematic review training resources should use established best practices for e-learning to provide high-quality resources, regardless of format or user time commitment.

Self-Efficacy, Self-Regulation, and Goal Orientation: Learner Motivational Characteristics That Influence Online Student Performance

ERIC Educational Resources Information Center

Wintling, Cheral Ann

2012-01-01

Learner motivational constructs of self-efficacy, self-regulation, and goal orientation in predicting successful student performance in online courses were explored. Thirty-three undergraduate students from the online courses Introduction to Educational Technology and Introduction to Education completed sections of the Motivated Strategies for…

Performance Outcomes of an Online First Aid and CPR Course for Laypersons

ERIC Educational Resources Information Center

Cason, Carolyn L.; Stiller, Janeth

2011-01-01

Objective: The study evaluated the effectiveness of an online first aid course by comparing it with the traditional instructor-led course. An effective online course increases course accessibility and mitigates the major deterrent to widespread layperson training. Design: A comparison group design evaluated performances among 25 laypersons…

Online Recorded Data-Based Composite Neural Control of Strict-Feedback Systems With Application to Hypersonic Flight Dynamics.

PubMed

Xu, Bin; Yang, Daipeng; Shi, Zhongke; Pan, Yongping; Chen, Badong; Sun, Fuchun

2017-09-25

This paper investigates the online recorded data-based composite neural control of uncertain strict-feedback systems using the backstepping framework. In each step of the virtual control design, neural network (NN) is employed for uncertainty approximation. In previous works, most designs are directly toward system stability ignoring the fact how the NN is working as an approximator. In this paper, to enhance the learning ability, a novel prediction error signal is constructed to provide additional correction information for NN weight update using online recorded data. In this way, the neural approximation precision is highly improved, and the convergence speed can be faster. Furthermore, the sliding mode differentiator is employed to approximate the derivative of the virtual control signal, and thus, the complex analysis of the backstepping design can be avoided. The closed-loop stability is rigorously established, and the boundedness of the tracking error can be guaranteed. Through simulation of hypersonic flight dynamics, the proposed approach exhibits better tracking performance.

Experimental demonstration of the real-time online fault monitoring technique for chaos-based passive optical networks

NASA Astrophysics Data System (ADS)

Dou, Xinyu; Yin, Hongxi; Yue, Hehe; Jin, Yu; Shen, Jing; Li, Lin

2015-09-01

In this paper, a real-time online fault monitoring technique for chaos-based passive optical networks (PONs) is proposed and experimentally demonstrated. The fault monitoring is performed by the chaotic communication signal. The proof-of-concept experiments are demonstrated for two PON structures, i.e., wavelength-division-multiplexing (WDM) PON and Ethernet PON (EPON), respectively. For WDM PON, two monitoring approaches are investigated, one deploying a chaotic optical time domain reflectometry (OTDR) for each transmitter, and the other using only one tunable chaotic OTDR. The experimental results show that the faults at beyond 20 km from the OLT can be detected and located. The spatial resolution of the tunable chaotic OTDR is an order of magnitude of centimeter. Meanwhile, the monitoring process can operate in parallel with the chaotic optical secure communications. The proposed technique has benefits of real-time, online, precise fault location, and simple realization, which will significantly reduce the cost of operation, administration and maintenance (OAM) of PON.

Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

PubMed

Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

2006-04-01

This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control system. Performance of the control system is successfully tested by performing several six-degrees-of-freedom nonlinear simulations.

Partially supervised P300 speller adaptation for eventual stimulus timing optimization: target confidence is superior to error-related potential score as an uncertain label

NASA Astrophysics Data System (ADS)

Zeyl, Timothy; Yin, Erwei; Keightley, Michelle; Chau, Tom

2016-04-01

Objective. Error-related potentials (ErrPs) have the potential to guide classifier adaptation in BCI spellers, for addressing non-stationary performance as well as for online optimization of system parameters, by providing imperfect or partial labels. However, the usefulness of ErrP-based labels for BCI adaptation has not been established in comparison to other partially supervised methods. Our objective is to make this comparison by retraining a two-step P300 speller on a subset of confident online trials using naïve labels taken from speller output, where confidence is determined either by (i) ErrP scores, (ii) posterior target scores derived from the P300 potential, or (iii) a hybrid of these scores. We further wish to evaluate the ability of partially supervised adaptation and retraining methods to adjust to a new stimulus-onset asynchrony (SOA), a necessary step towards online SOA optimization. Approach. Eleven consenting able-bodied adults attended three online spelling sessions on separate days with feedback in which SOAs were set at 160 ms (sessions 1 and 2) and 80 ms (session 3). A post hoc offline analysis and a simulated online analysis were performed on sessions two and three to compare multiple adaptation methods. Area under the curve (AUC) and symbols spelled per minute (SPM) were the primary outcome measures. Main results. Retraining using supervised labels confirmed improvements of 0.9 percentage points (session 2, p < 0.01) and 1.9 percentage points (session 3, p < 0.05) in AUC using same-day training data over using data from a previous day, which supports classifier adaptation in general. Significance. Using posterior target score alone as a confidence measure resulted in the highest SPM of the partially supervised methods, indicating that ErrPs are not necessary to boost the performance of partially supervised adaptive classification. Partial supervision significantly improved SPM at a novel SOA, showing promise for eventual online SOA optimization.

Face-to-face or face-to-screen? Undergraduates' opinions and test performance in classroom vs. online learning

PubMed Central

Kemp, Nenagh; Grieve, Rachel

2014-01-01

As electronic communication becomes increasingly common, and as students juggle study, work, and family life, many universities are offering their students more flexible learning opportunities. Classes once delivered face-to-face are often replaced by online activities and discussions. However, there is little research comparing students' experience and learning in these two modalities. The aim of this study was to compare undergraduates' preference for, and academic performance on, class material and assessment presented online vs. in traditional classrooms. Psychology students (N = 67) at an Australian university completed written exercises, a class discussion, and a written test on two academic topics. The activities for one topic were conducted face-to-face, and the other online, with topics counterbalanced across two groups. The results showed that students preferred to complete activities face-to-face rather than online, but there was no significant difference in their test performance in the two modalities. In their written responses, students expressed a strong preference for class discussions to be conducted face-to-face, reporting that they felt more engaged, and received more immediate feedback, than in online discussion. A follow-up study with a separate group (N = 37) confirmed that although students appreciated the convenience of completing written activities online in their own time, they also strongly preferred to discuss course content with peers in the classroom rather than online. It is concluded that online and face-to-face activities can lead to similar levels of academic performance, but that students would rather do written activities online but engage in discussion in person. Course developers could aim to structure classes so that students can benefit from both the flexibility of online learning, and the greater engagement experienced in face-to-face discussion. PMID:25429276

Face-to-face or face-to-screen? Undergraduates' opinions and test performance in classroom vs. online learning.

PubMed

Kemp, Nenagh; Grieve, Rachel

2014-01-01

As electronic communication becomes increasingly common, and as students juggle study, work, and family life, many universities are offering their students more flexible learning opportunities. Classes once delivered face-to-face are often replaced by online activities and discussions. However, there is little research comparing students' experience and learning in these two modalities. The aim of this study was to compare undergraduates' preference for, and academic performance on, class material and assessment presented online vs. in traditional classrooms. Psychology students (N = 67) at an Australian university completed written exercises, a class discussion, and a written test on two academic topics. The activities for one topic were conducted face-to-face, and the other online, with topics counterbalanced across two groups. The results showed that students preferred to complete activities face-to-face rather than online, but there was no significant difference in their test performance in the two modalities. In their written responses, students expressed a strong preference for class discussions to be conducted face-to-face, reporting that they felt more engaged, and received more immediate feedback, than in online discussion. A follow-up study with a separate group (N = 37) confirmed that although students appreciated the convenience of completing written activities online in their own time, they also strongly preferred to discuss course content with peers in the classroom rather than online. It is concluded that online and face-to-face activities can lead to similar levels of academic performance, but that students would rather do written activities online but engage in discussion in person. Course developers could aim to structure classes so that students can benefit from both the flexibility of online learning, and the greater engagement experienced in face-to-face discussion.

Analysis on online word-of-mouth of customer satisfaction in cultural and creative industries of Taiwan: using cultural heritage application and performance facilities as examples

NASA Astrophysics Data System (ADS)

Tsai, Li-Fen; Shaw, Jing-Chi; Wang, Pei-Wen; Shih, Meng-Long; Su, Yi-Jing

2011-10-01

This study aims to probe into customers' online word-of-mouth regarding cultural heritage applications and performance facilities in Cultural and Creative Industries. Findings demonstrate that, regarding online word-of-mouth for art museums, museums, and art villages, items valued by customers are design aesthetics of displays and collections, educational functions, and environments and landscapes. The percentages are 10.102%, 11.208% and 11.44%, respectively. In addition, cultural heritage applications and performance facility industries in Taiwan are highly valued in online word-of-mouth.

A continually online-trained neural network controller for brushless DC motor drives

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

Rubaai, A.; Kotaru, R.; Kankam, M.D.

2000-04-01

In this paper, a high-performance controller with simultaneous online identification and control is designed for brushless dc motor drives. The dynamics of the motor/load are modeled online, and controlled using two different neural network based identification and control schemes, as the system is in operation. In the first scheme, an attempt is made to control the rotor angular speed, utilizing a single three-hidden-layer network. The second scheme attempts to control the stator currents, using a predetermined control law as a function of the estimated states. This schemes incorporates three multilayered feedforward neural networks that are online trained, using the Levenburg-Marquadtmore » training algorithm. The control of the direct and quadrature components of the stator current successfully tracked a wide variety of trajectories after relatively short online training periods. The control strategy adapts to the uncertainties of the motor/load dynamics and, in addition, learns their inherent nonlinearities. Simulation results illustrated that a neurocontroller used in conjunction with adaptive control schemes can result in a flexible control device which may be utilized in a wide range of environments.« less

Usability evaluation of cloud-based mapping tools for the display of very large datasets

NASA Astrophysics Data System (ADS)

Stotz, Nicole Marie

The elasticity and on-demand nature of cloud services have made it easier to create web maps. Users only need access to a web browser and the Internet to utilize cloud based web maps, eliminating the need for specialized software. To encourage a wide variety of users, a map must be well designed; usability is a very important concept in designing a web map. Fusion Tables, a new product from Google, is one example of newer cloud-based distributed GIS services. It allows for easy spatial data manipulation and visualization, within the Google Maps framework. ESRI has also introduced a cloud based version of their software, called ArcGIS Online, built on Amazon's EC2 cloud. Utilizing a user-centered design framework, two prototype maps were created with data from the San Diego East County Economic Development Council. One map was built on Fusion Tables, and another on ESRI's ArcGIS Online. A usability analysis was conducted and used to compare both map prototypes in term so of design and functionality. Load tests were also ran, and performance metrics gathered on both map prototypes. The usability analysis was taken by 25 geography students, and consisted of time based tasks and questions on map design and functionality. Survey participants completed the time based tasks for the Fusion Tables map prototype quicker than those of the ArcGIS Online map prototype. While response was generally positive towards the design and functionality of both prototypes, overall the Fusion Tables map prototype was preferred. For the load tests, the data set was broken into 22 groups for a total of 44 tests. While the Fusion Tables map prototype performed more efficiently than the ArcGIS Online prototype, differences are almost unnoticeable. A SWOT analysis was conducted for each prototype. The results from this research point to the Fusion Tables map prototype. A redesign of this prototype would incorporate design suggestions from the usability survey, while some functionality would need to be dropped. This is a free product and would therefore be the best option if cost is an issue, but this map may not be supported in the future.

Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis.

PubMed

Ortiz-Ruiz, Alejandra; Postigo, María; Gil-Casanova, Sara; Cuadrado, Daniel; Bautista, José M; Rubio, José Miguel; Luengo-Oroz, Miguel; Linares, María

2018-01-30

Routine field diagnosis of malaria is a considerable challenge in rural and low resources endemic areas mainly due to lack of personnel, training and sample processing capacity. In addition, differential diagnosis of Plasmodium species has a high level of misdiagnosis. Real time remote microscopical diagnosis through on-line crowdsourcing platforms could be converted into an agile network to support diagnosis-based treatment and malaria control in low resources areas. This study explores whether accurate Plasmodium species identification-a critical step during the diagnosis protocol in order to choose the appropriate medication-is possible through the information provided by non-trained on-line volunteers. 88 volunteers have performed a series of questionnaires over 110 images to differentiate species (Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, Plasmodium malariae, Plasmodium knowlesi) and parasite staging from thin blood smear images digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Visual cues evaluated in the surveys include texture and colour, parasite shape and red blood size. On-line volunteers are able to discriminate Plasmodium species (P. falciparum, P. malariae, P. vivax, P. ovale, P. knowlesi) and stages in thin-blood smears according to visual cues observed on digitalized images of parasitized red blood cells. Friendly textual descriptions of the visual cues and specialized malaria terminology is key for volunteers learning and efficiency. On-line volunteers with short-training are able to differentiate malaria parasite species and parasite stages from digitalized thin smears based on simple visual cues (shape, size, texture and colour). While the accuracy of a single on-line expert is far from perfect, a single parasite classification obtained by combining the opinions of multiple on-line volunteers over the same smear, could improve accuracy and reliability of Plasmodium species identification in remote malaria diagnosis.

A novel onset detection technique for brain-computer interfaces using sound-production related cognitive tasks in simulated-online system

NASA Astrophysics Data System (ADS)

Song, YoungJae; Sepulveda, Francisco

2017-02-01

Objective. Self-paced EEG-based BCIs (SP-BCIs) have traditionally been avoided due to two sources of uncertainty: (1) precisely when an intentional command is sent by the brain, i.e., the command onset detection problem, and (2) how different the intentional command is when compared to non-specific (or idle) states. Performance evaluation is also a problem and there are no suitable standard metrics available. In this paper we attempted to tackle these issues. Approach. Self-paced covert sound-production cognitive tasks (i.e., high pitch and siren-like sounds) were used to distinguish between intentional commands (IC) and idle states. The IC states were chosen for their ease of execution and negligible overlap with common cognitive states. Band power and a digital wavelet transform were used for feature extraction, and the Davies-Bouldin index was used for feature selection. Classification was performed using linear discriminant analysis. Main results. Performance was evaluated under offline and simulated-online conditions. For the latter, a performance score called true-false-positive (TFP) rate, ranging from 0 (poor) to 100 (perfect), was created to take into account both classification performance and onset timing errors. Averaging the results from the best performing IC task for all seven participants, an 77.7% true-positive (TP) rate was achieved in offline testing. For simulated-online analysis the best IC average TFP score was 76.67% (87.61% TP rate, 4.05% false-positive rate). Significance. Results were promising when compared to previous IC onset detection studies using motor imagery, in which best TP rates were reported as 72.0% and 79.7%, and which, crucially, did not take timing errors into account. Moreover, based on our literature review, there is no previous covert sound-production onset detection system for spBCIs. Results showed that the proposed onset detection technique and TFP performance metric have good potential for use in SP-BCIs.

Team Trust in Online Education: Assessing and Comparing Team-Member Trust in Online Teams versus Face-to-Face Teams

ERIC Educational Resources Information Center

Beranek, Peggy M.; French, Monique L.

2011-01-01

Trust is a key factor in enabling effective team performance and, in online teams, needs to be built quickly and early. As universities expand their online offerings students are increasingly working in online teams. Understanding how trust development may differ in online teams versus face-to-face can have implications for online education…

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran.

PubMed

Ghaemi, Z; Alimohammadi, A; Farnaghi, M

2018-04-20

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.

Online Magnetic Resonance Image Guided Adaptive Radiation Therapy: First Clinical Applications

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

Acharya, Sahaja; Fischer-Valuck, Benjamin W.; Kashani, Rojano

Purpose: To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiation therapy (MR-IGRT) through reporting of our initial clinical experience and workflow considerations. Methods and Materials: The first clinically deployed online adaptive MR-IGRT system consisted of a split 0.35T MR scanner straddling a ring gantry with 3 multileaf collimator-equipped {sup 60}Co heads. The unit is supported by a Monte Carlo–based treatment planning system that allows real-time adaptive planning with the patient on the table. All patients undergo computed tomography and MR imaging (MRI) simulation for initial treatment planning. A volumetric MRI scan is acquired for each patient atmore » the daily treatment setup. Deformable registration is performed using the planning computed tomography data set, which allows for the transfer of the initial contours and the electron density map to the daily MRI scan. The deformed electron density map is then used to recalculate the original plan on the daily MRI scan for physician evaluation. Recontouring and plan reoptimization are performed when required, and patient-specific quality assurance (QA) is performed using an independent in-house software system. Results: The first online adaptive MR-IGRT treatments consisted of 5 patients with abdominopelvic malignancies. The clinical setting included neoadjuvant colorectal (n=3), unresectable gastric (n=1), and unresectable pheochromocytoma (n=1). Recontouring and reoptimization were deemed necessary for 3 of 5 patients, and the initial plan was deemed sufficient for 2 of the 5 patients. The reasons for plan adaptation included tumor progression or regression and a change in small bowel anatomy. In a subsequently expanded cohort of 170 fractions (20 patients), 52 fractions (30.6%) were reoptimized online, and 92 fractions (54.1%) were treated with an online-adapted or previously adapted plan. The median time for recontouring, reoptimization, and QA was 26 minutes. Conclusion: Online adaptive MR-IGRT has been successfully implemented with planning and QA workflow suitable for routine clinical application. Clinical trials are in development to formally evaluate adaptive treatments for a variety of disease sites.« less

A web-based micro-simulation program for self-learning BLS skills and the use of an AED. Can laypeople train themselves without a manikin?

PubMed

de Vries, Wiebe; Handley, Anthony J

2007-12-01

Various methods, including self-instruction, have been used to try to improve the acquisition of basic life support skills. This is a preliminary report of the effectiveness of a web-based self-training program for BLS and the use of an AED. Sixteen volunteers completed on-line training in their own time over a period of 8 weeks. The program included theory, scenario training and self-testing, but without practice on a manikin, or any instructor input. The volunteers were assessed, without prior warning, in a scenario setting. A recording manikin, expert assessors and video recording were used with a modified version of the Cardiff Test. All 16 volunteers performed the assessed skills in the use of an AED correctly. Most of the skills of BLS assessed were performed well. Chest compression depth and rate were performed less well (59% and 67% of participants, respectively, performed correctly). Opening the airway and lung inflation were performed poorly (38% and 13% of participants performed correctly), as was checking for safety (19% participants performed correctly). There was no significant correlation between the time a participant spent on-line and the quality of performance. Only 5 of the volunteers had ever attended a BLS course or used a resuscitation manikin before the assessment; their performance scores were not significantly better than those of the other 11 volunteers. These results suggest that it may be possible to train people in BLS and AED skills using a micro-simulation web-based interactive program but without any practice on a manikin. This seems to be particularly the case for the use of an AED, where performance achieved a uniformly high standard.

Online solid-phase extraction with high-performance liquid chromatography and mass spectrometry for the determination of five tannins in traditional Chinese medicine injections.

PubMed

Sun, Meng; Lin, Yuanyuan; Zhang, Jie; Zheng, Shaohua; Wang, Sicen

2016-03-01

A rapid analytical method based on online solid-phase extraction with high-performance liquid chromatography and mass spectrometry has been established and applied to the determination of tannin compounds that may cause adverse effects in traditional Chinese medicine injections. Different solid-phase extraction sorbents have been compared and the elution buffer was optimized. The performance of the method was verified by evaluation of recovery (≥40%), repeatability (RSD ≤ 6%), linearity (r(2) ≥ 0.993), and limit of quantification (≤0.35 μg/mL). Five tannin compounds, gallic acid, cianidanol, gallocatechin gallate, ellagic acid, and penta-O-galloylglucose, were identified with concentrations ranging from 3.1-37.4 μg/mL in the analyzed traditional Chinese medicine injections. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Online 3D EPID-based dose verification: Proof of concept.

PubMed

Spreeuw, Hanno; Rozendaal, Roel; Olaciregui-Ruiz, Igor; González, Patrick; Mans, Anton; Mijnheer, Ben; van Herk, Marcel

2016-07-01

Delivery errors during radiotherapy may lead to medical harm and reduced life expectancy for patients. Such serious incidents can be avoided by performing dose verification online, i.e., while the patient is being irradiated, creating the possibility of halting the linac in case of a large overdosage or underdosage. The offline EPID-based 3D in vivo dosimetry system clinically employed at our institute is in principle suited for online treatment verification, provided the system is able to complete 3D dose reconstruction and verification within 420 ms, the present acquisition time of a single EPID frame. It is the aim of this study to show that our EPID-based dosimetry system can be made fast enough to achieve online 3D in vivo dose verification. The current dose verification system was sped up in two ways. First, a new software package was developed to perform all computations that are not dependent on portal image acquisition separately, thus removing the need for doing these calculations in real time. Second, the 3D dose reconstruction algorithm was sped up via a new, multithreaded implementation. Dose verification was implemented by comparing planned with reconstructed 3D dose distributions delivered to two regions in a patient: the target volume and the nontarget volume receiving at least 10 cGy. In both volumes, the mean dose is compared, while in the nontarget volume, the near-maximum dose (D2) is compared as well. The real-time dosimetry system was tested by irradiating an anthropomorphic phantom with three VMAT plans: a 6 MV head-and-neck treatment plan, a 10 MV rectum treatment plan, and a 10 MV prostate treatment plan. In all plans, two types of serious delivery errors were introduced. The functionality of automatically halting the linac was also implemented and tested. The precomputation time per treatment was ∼180 s/treatment arc, depending on gantry angle resolution. The complete processing of a single portal frame, including dose verification, took 266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5-10 s irradiation time. A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

P2P-Based Data System for the EAST Experiment

NASA Astrophysics Data System (ADS)

Shu, Yantai; Zhang, Liang; Zhao, Weifeng; Chen, Haiming; Luo, Jiarong

2006-06-01

A peer-to-peer (P2P)-based EAST Data System is being designed to provide data acquisition and analysis support for the EAST superconducting tokamak. Instead of transferring data to the servers, all collected data are stored in the data acquisition subsystems locally and the PC clients can access the raw data directly using the P2P architecture. Both online and offline systems are based on Napster-like P2P architecture. This allows the peer (PC) to act both as a client and as a server. A simulation-based method and a steady-state operational analysis technique are used for performance evaluation. These analyses show that the P2P technique can significantly reduce the completion time of raw data display and real-time processing on the online system, and raise the workload capacity and reduce the delay on the offline system.

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

PubMed Central

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks. PMID:28932180

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

PubMed

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

Social and place-focused communities in location-based online social networks

NASA Astrophysics Data System (ADS)

Brown, Chloë; Nicosia, Vincenzo; Scellato, Salvatore; Noulas, Anastasios; Mascolo, Cecilia

2013-06-01

Thanks to widely available, cheap Internet access and the ubiquity of smartphones, millions of people around the world now use online location-based social networking services. Understanding the structural properties of these systems and their dependence upon users' habits and mobility has many potential applications, including resource recommendation and link prediction. Here, we construct and characterise social and place-focused graphs by using longitudinal information about declared social relationships and about users' visits to physical places collected from a popular online location-based social service. We show that although the social and place-focused graphs are constructed from the same data set, they have quite different structural properties. We find that the social and location-focused graphs have different global and meso-scale structure, and in particular that social and place-focused communities have negligible overlap. Consequently, group inference based on community detection performed on the social graph alone fails to isolate place-focused groups, even though these do exist in the network. By studying the evolution of tie structure within communities, we show that the time period over which location data are aggregated has a substantial impact on the stability of place-focused communities, and that information about place-based groups may be more useful for user-centric applications than that obtained from the analysis of social communities alone.

Examining pediatric emergency home ventilation practices in home health nurses: Opportunities for improved care.

PubMed

Kun, Sheila S; Beas, Virginia N; Keens, Thomas G; Ward, Sally S L; Gold, Jeffrey I

2015-07-01

To assess the pediatric home health nurses' knowledge in tracheostomy and ventilator emergency care on home mechanical ventilation (HMV). Emergencies are frightening experiences for solo home health nurses and require advanced skills in emergency response and care, especially in pediatric patients who pose unique challenges. Nurses with greater years of nursing experience would perform better on emergency HMV case-based scenarios than nurses with less years of experience. An exploratory online survey was used to evaluate emergency case-based pediatric scenarios. Demographic and professional experiences were profiled. Seventy-nine nurses had an average of 6.73 (SD = 1.41) years in pediatric nursing. Over 70% received their HMV training in their agency, 41% had less than 4 years of experience, and 30.4% had encountered at least one emergency situation at home. The online survey was distributed by managers of 22 home health agencies to nurses providing pediatric HMV care. Nurses scored an average of 4.87 out of 10 possible points. There were no significant differences between nurses with <4 years of experience versus those with more experience on ventilator alarms knowledge or total knowledge. Ninety-seven percent of the nurses favored more training in HMV from a variety of settings (e.g., agency, on-line training). Nurses did not perform well in case-based ventilator alarm scenarios. Length of nursing experience did not differentiate greater knowledge. It is clear that nurses require and want more training in emergency-based HMV. Recommendations for an enhanced curriculum are suggested. © 2014 Wiley Periodicals, Inc.

On-Line Use of Three-Dimensional Marker Trajectory Estimation From Cone-Beam Computed Tomography Projections for Precise Setup in Radiotherapy for Targets With Respiratory Motion

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

Worm, Esben S., E-mail: esbeworm@rm.dk; Department of Medical Physics, Aarhus University Hospital, Aarhus; Hoyer, Morten

2012-05-01

Purpose: To develop and evaluate accurate and objective on-line patient setup based on a novel semiautomatic technique in which three-dimensional marker trajectories were estimated from two-dimensional cone-beam computed tomography (CBCT) projections. Methods and Materials: Seven treatment courses of stereotactic body radiotherapy for liver tumors were delivered in 21 fractions in total to 6 patients by a linear accelerator. Each patient had two to three gold markers implanted close to the tumors. Before treatment, a CBCT scan with approximately 675 two-dimensional projections was acquired during a full gantry rotation. The marker positions were segmented in each projection. From this, the three-dimensionalmore » marker trajectories were estimated using a probability based method. The required couch shifts for patient setup were calculated from the mean marker positions along the trajectories. A motion phantom moving with known tumor trajectories was used to examine the accuracy of the method. Trajectory-based setup was retrospectively used off-line for the first five treatment courses (15 fractions) and on-line for the last two treatment courses (6 fractions). Automatic marker segmentation was compared with manual segmentation. The trajectory-based setup was compared with setup based on conventional CBCT guidance on the markers (first 15 fractions). Results: Phantom measurements showed that trajectory-based estimation of the mean marker position was accurate within 0.3 mm. The on-line trajectory-based patient setup was performed within approximately 5 minutes. The automatic marker segmentation agreed with manual segmentation within 0.36 {+-} 0.50 pixels (mean {+-} SD; pixel size, 0.26 mm in isocenter). The accuracy of conventional volumetric CBCT guidance was compromised by motion smearing ({<=}21 mm) that induced an absolute three-dimensional setup error of 1.6 {+-} 0.9 mm (maximum, 3.2) relative to trajectory-based setup. Conclusions: The first on-line clinical use of trajectory estimation from CBCT projections for precise setup in stereotactic body radiotherapy was demonstrated. Uncertainty in the conventional CBCT-based setup procedure was eliminated with the new method.« less

Attitudes of Middle School Students: Learning Online Compared to Face to Face

ERIC Educational Resources Information Center

Edwards, Clayton; Rule, Audrey

2013-01-01

Education in an online setting is an increasingly popular method of instruction. Previous studies comparing college or high school student performance in online and face-to-face courses found, in most cases, similar achievement between conditions. However, research is lacking regarding middle school students' academic performance and attitudes…

Students Reflecting on Test Performance and Feedback: An On-Line Approach

ERIC Educational Resources Information Center

Fyfe, Georgina; Fyfe, Sue; Meyer, Jan; Ziman, Mel; Sanders, Kathy; Hill, Julie

2014-01-01

Undergraduate students accessing on-line tests in Human Biology in three Western Australian universities were asked to complete an on-line post-test reflective survey about their perceptions of their test performance in light of automated feedback. The survey allowed pre-determined choices and comment text boxes relating to students' perceptions…

High Performance Work Systems for Online Education

ERIC Educational Resources Information Center

Contacos-Sawyer, Jonna; Revels, Mark; Ciampa, Mark

2010-01-01

The purpose of this paper is to identify the key elements of a High Performance Work System (HPWS) and explore the possibility of implementation in an online institution of higher learning. With the projected rapid growth of the demand for online education and its importance in post-secondary education, providing high quality curriculum, excellent…

Learning Styles, Online Content Usage and Exam Performance in a Mixed-Format Introductory Computer Information Systems Course

ERIC Educational Resources Information Center

Lang, Guido; O'Connell, Stephen D.

2015-01-01

We investigate the relationship between learning styles, online content usage and exam performance in an undergraduate introductory Computer Information Systems class comprised of both online video tutorials and in-person classes. Our findings suggest that, across students, (1) traditional learning style classification methodologies do not predict…

A Comparison of Student Academic Performance with Traditional, Online, and Flipped Instructional Approaches in a C# Programming Course

ERIC Educational Resources Information Center

Sharp, Jason H.; Sharp, Laurie A.

2017-01-01

Aim/Purpose: Compared student academic performance on specific course requirements in a C# programming course across three instructional approaches: traditional, online, and flipped. Background: Addressed the following research question--When compared to the online and traditional instructional approaches, does the flipped instructional approach…

Lithographically fabricated silicon microreactor for in situ characterization of heterogeneous catalysts—Enabling correlative characterization techniques

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

Baier, S.; Rochet, A.; Hofmann, G.

2015-06-15

We report on a new modular setup on a silicon-based microreactor designed for correlative spectroscopic, scattering, and analytic on-line gas investigations for in situ studies of heterogeneous catalysts. The silicon microreactor allows a combination of synchrotron radiation based techniques (e.g., X-ray diffraction and X-ray absorption spectroscopy) as well as infrared thermography and Raman spectroscopy. Catalytic performance can be determined simultaneously by on-line product analysis using mass spectrometry. We present the design of the reactor, the experimental setup, and as a first example for an in situ study, the catalytic partial oxidation of methane showing the applicability of this reactor formore » in situ studies.« less

Reactome diagram viewer: data structures and strategies to boost performance.

PubMed

Fabregat, Antonio; Sidiropoulos, Konstantinos; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-04-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community. The pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partitioning data structure minimizes CPU workload, enabling the introduction of new features that further enhance user experience. Through the use of highly optimized data structures and algorithms, Reactome has boosted the performance and usability of the new pathway diagram viewer, providing a robust, scalable and easy-to-integrate solution to pathway visualization. As graph-based visualization of complex data is a frequent challenge in bioinformatics, many of the individual strategies presented here are applicable to a wide range of web-based bioinformatics resources. Reactome is available online at: https://reactome.org. The diagram viewer is part of the Reactome pathway browser (https://reactome.org/PathwayBrowser/) and also available as a stand-alone widget at: https://reactome.org/dev/diagram/. The source code is freely available at: https://github.com/reactome-pwp/diagram. fabregat@ebi.ac.uk or hhe@ebi.ac.uk. Supplementary data are available at Bioinformatics online.

A massive open online course for teaching physiotherapy students and physiotherapists about spinal cord injuries.

PubMed

Harvey, L A; Glinsky, J V; Lowe, R; Lowe, T

2014-12-01

A descriptive audit. To audit the participation and satisfaction in a Massive Open Online Course (MOOC) for teaching physiotherapy students and physiotherapists about spinal cord injuries. Global and online. A 5-week MOOC about the physiotherapy management of spinal cord injuries was hosted by Physiopedia and run in partnership with the International Spinal Cord Society. The MOOC was based on the physiotherapy-specific module of www.elearnSCI.org, and also involved extra readings, activities and online discussion through a closed Facebook group. Participation and satisfaction was quantified through a pre- and post-MOOC knowledge assessment and an online course evaluation. Participation was also gauged through Facebook activity and internet-based usage statistics. Three thousand five hundred and twenty-three people from 108 countries registered for the MOOC and 2527 joined the Facebook group. One thousand one hundred and twenty-one completed the pre- and post-MOOC knowledge assessments, with more completing one or the other. The median (interquartile range) results for those who completed the pre and post-MOOC knowledge assessments were 70% (60-80%) and 90% (80-95%), respectively. One thousand and twenty-nine completed the online course evaluation, with more than 80% agreeing or strongly agreeing with 12 of the 13 positive statements posed to them about the course. Most participants who completed the MOOC performed well on the post-MOOC knowledge assessment and enjoyed the learning experience. However, these results may be biased if those who did not complete the MOOC were dissatisfied and/or did not sit the post-MOOC knowledge assessment.

Investigating the Use of Mastery-Style Online Homework Exercises in Introductory Algebra-Based Mechanics in a Controlled Clinical Study

ERIC Educational Resources Information Center

Evans, William R.; Selen, Mats A.

2017-01-01

Homework in introductory physics represents an important part of a student's learning experience; therefore, choosing the manner in which homework is presented merits investigation. We performed three rounds of clinical trials comparing the effects of mastery-style homework vs. traditional-style homework with students in both algebra-based and…

Research Findings on a Virtual Training Center--Measuring Web Based Training as an Effective Project Management Facilitation Intervention.

ERIC Educational Resources Information Center

Hoyt, Brian; Stockman, Mark

This paper focuses on the design of an assessment plan that can accurately measure the impact of using World Wide Web-based deliveries to increase performance. Key trends in technology and training are reviewed, and effective assessment of online training deliveries is examined. The Virtual Business Training Center (VBTC) is an integrated business…

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…

An online sleep apnea detection method based on recurrence quantification analysis.

PubMed

Nguyen, Hoa Dinh; Wilkins, Brek A; Cheng, Qi; Benjamin, Bruce Allen

2014-07-01

This paper introduces an online sleep apnea detection method based on heart rate complexity as measured by recurrence quantification analysis (RQA) statistics of heart rate variability (HRV) data. RQA statistics can capture nonlinear dynamics of a complex cardiorespiratory system during obstructive sleep apnea. In order to obtain a more robust measurement of the nonstationarity of the cardiorespiratory system, we use different fixed amount of neighbor thresholdings for recurrence plot calculation. We integrate a feature selection algorithm based on conditional mutual information to select the most informative RQA features for classification, and hence, to speed up the real-time classification process without degrading the performance of the system. Two types of binary classifiers, i.e., support vector machine and neural network, are used to differentiate apnea from normal sleep. A soft decision fusion rule is developed to combine the results of these classifiers in order to improve the classification performance of the whole system. Experimental results show that our proposed method achieves better classification results compared with the previous recurrence analysis-based approach. We also show that our method is flexible and a strong candidate for a real efficient sleep apnea detection system.

Copyright Resources for School Librarians

ERIC Educational Resources Information Center

Johnson, Yvonne M.; Johnson, Nicole M.

2016-01-01

This article provides a collection of annotated citations for online resources of interest to school librarians; the focus is on copyright law, related information, and guidelines. The citations are organized by themes based on common issues. Copyright protects originally created works, including movies, recorded music performances, novels,…

Structured Reflection Breaks Embedded in an Online Course--Effects on Learning Experience, Time on Task and Performance

ERIC Educational Resources Information Center

Verpoorten, Dominique; Westera, Wim

2016-01-01

The purpose of this article is to gain an insight into the effects of practicing short, frequent, and structured reflection breaks interspersed with the learning material in a computer-based course. To that end, the study sets up a standardized control trial with two groups of secondary school pupils. The study shows that while performance is not…

User recommendation in healthcare social media by assessing user similarity in heterogeneous network.

PubMed

Jiang, Ling; Yang, Christopher C

2017-09-01

The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way. We propose to represent the healthcare social media data as a heterogeneous healthcare information network and introduce the local and global structural approaches for measuring user similarity in a heterogeneous network. We compare the proposed structural approaches with the content-based approach. Experiments were conducted on a dataset collected from a popular online health social website, and the results showed that content-based approach performed better for inactive users, while structural approaches performed better for active users. Moreover, global structural approach outperformed local structural approach for all user groups. In addition, we conducted experiments on local and global structural approaches using different weight schemas for the edges in the network. Leverage performed the best for both local and global approaches. Finally, we integrated different approaches and demonstrated that hybrid method yielded better performance than the individual approach. The results indicate that content-based methods can effectively capture the similarity of inactive users who usually have focused interests, while structural methods can achieve better performance when rich structural information is available. Local structural approach only considers direct connections between nodes in the network, while global structural approach takes the indirect connections into account. Therefore, the global similarity approach can deal with sparse networks and capture the implicit similarity between two users. Different approaches may capture different aspects of the similarity relationship between two users. When we combine different methods together, we could achieve a better performance than using each individual method. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of response patterns in different survey designs: a longitudinal panel with mixed-mode and online-only design.

PubMed

Rübsamen, Nicole; Akmatov, Manas K; Castell, Stefanie; Karch, André; Mikolajczyk, Rafael T

2017-01-01

Increasing availability of the Internet allows using only online data collection for more epidemiological studies. We compare response patterns in a population-based health survey using two survey designs: mixed-mode (choice between paper-and-pencil and online questionnaires) and online-only design (without choice). We used data from a longitudinal panel, the Hygiene and Behaviour Infectious Diseases Study (HaBIDS), conducted in 2014/2015 in four regions in Lower Saxony, Germany. Individuals were recruited using address-based probability sampling. In two regions, individuals could choose between paper-and-pencil and online questionnaires. In the other two regions, individuals were offered online-only participation. We compared sociodemographic characteristics of respondents who filled in all panel questionnaires between the mixed-mode group (n = 1110) and the online-only group (n = 482). Using 134 items, we performed multinomial logistic regression to compare responses between survey designs in terms of type (missing, "do not know" or valid response) and ordinal regression to compare responses in terms of content. We applied the false discovery rates (FDR) to control for multiple testing and investigated effects of adjusting for sociodemographic characteristic. For validation of the differential response patterns between mixed-mode and online-only, we compared the response patterns between paper and online mode among the respondents in the mixed-mode group in one region (n = 786). Respondents in the online-only group were older than those in the mixed-mode group, but both groups did not differ regarding sex or education. Type of response did not differ between the online-only and the mixed-mode group. Survey design was associated with different content of response in 18 of the 134 investigated items; which decreased to 11 after adjusting for sociodemographic variables. In the validation within the mixed-mode, only two of those were among the 11 significantly different items. The probability of observing by chance the same two or more significant differences in this setting was 22%. We found similar response patterns in both survey designs with only few items being answered differently, likely attributable to chance. Our study supports the equivalence of the compared survey designs and suggests that, in the studied setting, using online-only design does not cause strong distortion of the results.

Clinical decision support tools: performance of personal digital assistant versus online drug information databases.

PubMed

Clauson, Kevin A; Polen, Hyla H; Marsh, Wallace A

2007-12-01

To evaluate personal digital assistant (PDA) drug information databases used to support clinical decision-making, and to compare the performance of PDA databases with their online versions. Prospective evaluation with descriptive analysis. Five drug information databases available for PDAs and online were evaluated according to their scope (inclusion of correct answers), completeness (on a 3-point scale), and ease of use; 158 question-answer pairs across 15 weighted categories of drug information essential to health care professionals were used to evaluate these databases. An overall composite score integrating these three measures was then calculated. Scores for the PDA databases and for each PDA-online pair were compared. Among the PDA databases, composite rankings, from highest to lowest, were as follows: Lexi-Drugs, Clinical Pharmacology OnHand, Epocrates Rx Pro, mobileMicromedex (now called Thomson Clinical Xpert), and Epocrates Rx free version. When we compared database pairs, online databases that had greater scope than their PDA counterparts were Clinical Pharmacology (137 vs 100 answers, p<0.001), Micromedex (132 vs 96 answers, p<0.001), Lexi-Comp Online (131 vs 119 answers, p<0.001), and Epocrates Online Premium (103 vs 98 answers, p=0.001). Only Micromedex online was more complete than its PDA version (p=0.008). Regarding ease of use, the Lexi-Drugs PDA database was superior to Lexi-Comp Online (p<0.001); however, Epocrates Online Premium, Epocrates Online Free, and Micromedex online were easier to use than their PDA counterparts (p<0.001). In terms of composite scores, only the online versions of Clinical Pharmacology and Micromedex demonstrated superiority over their PDA versions (p>0.01). Online and PDA drug information databases assist practitioners in improving their clinical decision-making. Lexi-Drugs performed significantly better than all of the other PDA databases evaluated. No PDA database demonstrated superiority to its online counterpart; however, the online versions of Clinical Pharmacology and Micromedex were superior to their PDA versions in answering questions.

The Effects of Clickers and Online Homework on Students' Achievement in General Chemistry

NASA Astrophysics Data System (ADS)

Gebru, Misganaw T.

Retention of an introductory general chemistry course material is vital for student success in future chemistry and chemistry-related courses. This study investigated the effects of clickers versus online homework on students' long-term content retention, examined the effectiveness of online homework versus no graded homework on students' achievement in a first-semester general chemistry course, and assessed students' attitudes toward the use of online homework. Students' data from the yearlong American Chemical Society General Chemistry (ACS GC97) exam, teacher-prepared final exams, and online surveys were analyzed to measure the effects of clickers and online homework on students' long-term content retention and performance, and to capture students' attitudes. A variety of methods including Welch ANOVA, independent samples t -test (Welch), Pearson's correlation, test of proportions, and Pearson's Chi-square test were used to analyze the data. The analyses indicated that the use of clickers or online homework did not significantly improve students' long-term content retention of general chemistry course material, that the use of online homework was more beneficial than, or at least as effective as no graded homework in improving students' performance, and students valued the fact that online homework provided immediate feedback. Additionally, results of this study revealed that greater numbers of students were retained in clicker and online homework classes than non-clicker, non-online homework classes and that various types of online homework systems used in general chemistry could impact student performance differently. Implications of the findings and future research directions were presented.

Development of on-line monitoring system for Nuclear Power Plant (NPP) using neuro-expert, noise analysis, and modified neural networks

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

Subekti, M.; Center for Development of Reactor Safety Technology, National Nuclear Energy Agency of Indonesia, Puspiptek Complex BO.80, Serpong-Tangerang, 15340; Ohno, T.

2006-07-01

The neuro-expert has been utilized in previous monitoring-system research of Pressure Water Reactor (PWR). The research improved the monitoring system by utilizing neuro-expert, conventional noise analysis and modified neural networks for capability extension. The parallel method applications required distributed architecture of computer-network for performing real-time tasks. The research aimed to improve the previous monitoring system, which could detect sensor degradation, and to perform the monitoring demonstration in High Temperature Engineering Tested Reactor (HTTR). The developing monitoring system based on some methods that have been tested using the data from online PWR simulator, as well as RSG-GAS (30 MW research reactormore » in Indonesia), will be applied in HTTR for more complex monitoring. (authors)« less

Applicability of Online Education to Large Undergraduate Engineering Courses

NASA Astrophysics Data System (ADS)

Bir, Devayan Debashis

With the increase in undergraduate engineering enrollment, many universities have chosen to teach introductory engineering courses such as Statics of Engineering and Mechanics of Materials in large classes due to budget limitations. With the overwhelming literature against traditionally taught large classes, this study aims to see the effects of the trending online pedagogy. Online courses are the latest trend in education due to the flexibility they provide to students in terms of schedule and pace of learning with the added advantage of being less expensive for the university over a period. In this research, the effects of online lectures on engineering students' course performances and students' attitudes towards online learning were examined. Specifically, the academic performances of students enrolled in a traditionally taught, lecture format Mechanics of Materials course with the performance of students in an online Mechanics of Materials course in summer 2016 were compared. To see the effect of the two different teaching approaches across student types, students were categorized by gender, enrollment status, nationality, and by the grades students obtained for Statics, one of the prerequisite courses for Mechanics of Materials. Student attitudes towards the online course will help to keep the process of continuously improving the online course, specifically, to provide quality education through the online medium in terms of course content and delivery. The findings of the study show that the online pedagogy negatively affects student academic performance when compared to the traditional face-to-face pedagogy across all categories, except for the high scoring students. Student attitudes reveal that while they enjoyed the flexibility schedule and control over their pace of studying, they faced issues with self-regulation and face-to-face interaction.

The new on-line Czech Food Composition Database.

PubMed

Machackova, Marie; Holasova, Marie; Maskova, Eva

2013-10-01

The new on-line Czech Food Composition Database (FCDB) was launched on http://www.czfcdb.cz in December 2010 as a main freely available channel for dissemination of Czech food composition data. The application is based on a complied FCDB documented according to the EuroFIR standardised procedure for full value documentation and indexing of foods by the LanguaL™ Thesaurus. A content management system was implemented for administration of the website and performing data export (comma-separated values or EuroFIR XML transport package formats) by a compiler. Reference/s are provided for each published value with linking to available freely accessible on-line sources of data (e.g. full texts, EuroFIR Document Repository, on-line national FCDBs). LanguaL™ codes are displayed within each food record as searchable keywords of the database. A photo (or a photo gallery) is used as a visual descriptor of a food item. The application is searchable on foods, components, food groups, alphabet and a multi-field advanced search. Copyright © 2013 Elsevier Ltd. All rights reserved.

Brain-actuated gait trainer with visual and proprioceptive feedback

NASA Astrophysics Data System (ADS)

Liu, Dong; Chen, Weihai; Lee, Kyuhwa; Chavarriaga, Ricardo; Bouri, Mohamed; Pei, Zhongcai; Millán, José del R.

2017-10-01

Objective. Brain-machine interfaces (BMIs) have been proposed in closed-loop applications for neuromodulation and neurorehabilitation. This study describes the impact of different feedback modalities on the performance of an EEG-based BMI that decodes motor imagery (MI) of leg flexion and extension. Approach. We executed experiments in a lower-limb gait trainer (the legoPress) where nine able-bodied subjects participated in three consecutive sessions based on a crossover design. A random forest classifier was trained from the offline session and tested online with visual and proprioceptive feedback, respectively. Post-hoc classification was conducted to assess the impact of feedback modalities and learning effect (an improvement over time) on the simulated trial-based performance. Finally, we performed feature analysis to investigate the discriminant power and brain pattern modulations across the subjects. Main results. (i) For real-time classification, the average accuracy was 62.33 +/- 4.95 % and 63.89 +/- 6.41 % for the two online sessions. The results were significantly higher than chance level, demonstrating the feasibility to distinguish between MI of leg extension and flexion. (ii) For post-hoc classification, the performance with proprioceptive feedback (69.45 +/- 9.95 %) was significantly better than with visual feedback (62.89 +/- 9.20 %), while there was no significant learning effect. (iii) We reported individual discriminate features and brain patterns associated to each feedback modality, which exhibited differences between the two modalities although no general conclusion can be drawn. Significance. The study reported a closed-loop brain-controlled gait trainer, as a proof of concept for neurorehabilitation devices. We reported the feasibility of decoding lower-limb movement in an intuitive and natural way. As far as we know, this is the first online study discussing the role of feedback modalities in lower-limb MI decoding. Our results suggest that proprioceptive feedback has an advantage over visual feedback, which could be used to improve robot-assisted strategies for motor training and functional recovery.

Brain-actuated gait trainer with visual and proprioceptive feedback.

PubMed

Liu, Dong; Chen, Weihai; Lee, Kyuhwa; Chavarriaga, Ricardo; Bouri, Mohamed; Pei, Zhongcai; Del R Millán, José

2017-10-01

Brain-machine interfaces (BMIs) have been proposed in closed-loop applications for neuromodulation and neurorehabilitation. This study describes the impact of different feedback modalities on the performance of an EEG-based BMI that decodes motor imagery (MI) of leg flexion and extension. We executed experiments in a lower-limb gait trainer (the legoPress) where nine able-bodied subjects participated in three consecutive sessions based on a crossover design. A random forest classifier was trained from the offline session and tested online with visual and proprioceptive feedback, respectively. Post-hoc classification was conducted to assess the impact of feedback modalities and learning effect (an improvement over time) on the simulated trial-based performance. Finally, we performed feature analysis to investigate the discriminant power and brain pattern modulations across the subjects. (i) For real-time classification, the average accuracy was [Formula: see text]% and [Formula: see text]% for the two online sessions. The results were significantly higher than chance level, demonstrating the feasibility to distinguish between MI of leg extension and flexion. (ii) For post-hoc classification, the performance with proprioceptive feedback ([Formula: see text]%) was significantly better than with visual feedback ([Formula: see text]%), while there was no significant learning effect. (iii) We reported individual discriminate features and brain patterns associated to each feedback modality, which exhibited differences between the two modalities although no general conclusion can be drawn. The study reported a closed-loop brain-controlled gait trainer, as a proof of concept for neurorehabilitation devices. We reported the feasibility of decoding lower-limb movement in an intuitive and natural way. As far as we know, this is the first online study discussing the role of feedback modalities in lower-limb MI decoding. Our results suggest that proprioceptive feedback has an advantage over visual feedback, which could be used to improve robot-assisted strategies for motor training and functional recovery.

Online damage detection using recursive principal component analysis and recursive condition indicators

NASA Astrophysics Data System (ADS)

Krishnan, M.; Bhowmik, B.; Tiwari, A. K.; Hazra, B.

2017-08-01

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using recursive principal component analysis (RPCA) in conjunction with online damage indicators is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal modes in online using the rank-one perturbation method, and subsequently utilized to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/nonlinear-states that indicate damage. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. An online condition indicator (CI) based on the L2 norm of the error between actual response and the response projected using recursive eigenvector matrix updates over successive iterations is proposed. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data. The proposed CI, named recursive residual error, is also adopted for simultaneous spatio-temporal damage detection. Numerical simulations performed on five-degree of freedom nonlinear system under white noise and El Centro excitations, with different levels of nonlinearity simulating the damage scenarios, demonstrate the robustness of the proposed algorithm. Successful results obtained from practical case studies involving experiments performed on a cantilever beam subjected to earthquake excitation, for full sensors and underdetermined cases; and data from recorded responses of the UCLA Factor building (full data and its subset) demonstrate the efficacy of the proposed methodology as an ideal candidate for real-time, reference free structural health monitoring.

Text Classification for Assisting Moderators in Online Health Communities

PubMed Central

Huh, Jina; Yetisgen-Yildiz, Meliha; Pratt, Wanda

2013-01-01

Objectives Patients increasingly visit online health communities to get help on managing health. The large scale of these online communities makes it impossible for the moderators to engage in all conversations; yet, some conversations need their expertise. Our work explores low-cost text classification methods to this new domain of determining whether a thread in an online health forum needs moderators’ help. Methods We employed a binary classifier on WebMD’s online diabetes community data. To train the classifier, we considered three feature types: (1) word unigram, (2) sentiment analysis features, and (3) thread length. We applied feature selection methods based on χ2 statistics and under sampling to account for unbalanced data. We then performed a qualitative error analysis to investigate the appropriateness of the gold standard. Results Using sentiment analysis features, feature selection methods, and balanced training data increased the AUC value up to 0.75 and the F1-score up to 0.54 compared to the baseline of using word unigrams with no feature selection methods on unbalanced data (0.65 AUC and 0.40 F1-score). The error analysis uncovered additional reasons for why moderators respond to patients’ posts. Discussion We showed how feature selection methods and balanced training data can improve the overall classification performance. We present implications of weighing precision versus recall for assisting moderators of online health communities. Our error analysis uncovered social, legal, and ethical issues around addressing community members’ needs. We also note challenges in producing a gold standard, and discuss potential solutions for addressing these challenges. Conclusion Social media environments provide popular venues in which patients gain health-related information. Our work contributes to understanding scalable solutions for providing moderators’ expertise in these large-scale, social media environments. PMID:24025513

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

NASA Technical Reports Server (NTRS)

Thompson, David R.; Majid, Walid A.; Reed, Colorado J.; Wagstaff, Kiri L.

2011-01-01

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

Enhanced online convolutional neural networks for object tracking

NASA Astrophysics Data System (ADS)

Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

2018-04-01

In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

Student Outcomes in Economics Principles: Online vs. Face-to-Face Delivery

ERIC Educational Resources Information Center

Birkeland, Kathryn; Weinandt, Mandie; Carr, David L.

2015-01-01

This study looks at the performance of students in an online and face-to-face section of economic principles with the same instructor. After controlling for the bias of students selecting the online section and observable characteristics, we did not find any statistical difference in the exam performance of students across delivery modes of the…

Regulating Interest when Learning Online: Potential Motivation and Performance Trade-Offs

ERIC Educational Resources Information Center

Sansone, Carol; Smith, Jessi L.; Thoman, Dustin B.; MacNamara, Atara

2012-01-01

Online learning may be particularly sensitive to self-regulatory trade-offs between maintaining interest and performance. Undergraduates in online or on-campus sections of the same course rated strategies used to motivate studying for the first exam, and interest after the first exam and at semester's end. First exam and final class grades were…

An Online Premium? Characteristics and Performance of Online versus Face-to-Face Students in Principles of Microeconomics

ERIC Educational Resources Information Center

Dendir, Seife

2016-01-01

The author uses data from two Principles of Microeconomics courses to examine differences in characteristics and performance of online versus face-to-face students. The analysis indicates that even in a traditional institution, the two delivery modes may be serving students with distinctly different backgrounds and characteristics. In terms of…

Analyzing the Social Networks of High- and Low-Performing Students in Online Discussion Forums

ERIC Educational Resources Information Center

Ghadirian, Hajar; Salehi, Keyvan; Ayub, Ahmad Fauzi Mohd

2018-01-01

An ego network is an individual's social network relationships with core members. In this study, the ego network parameters in online discussion spaces of high- and low-performing students were compared. The extent to which students' ego networks changed over the course were also analyzed. Participation in 7 weeks of online discussions were…

Student Perceptions and Performance in Online and Offline Collaboration in an Interior Design Studio

ERIC Educational Resources Information Center

Cho, Ji Young; Cho, Moon-Heum

2014-01-01

Competence in collaboration is one of the critical abilities that interior design majors are expected to develop during the course of their education; however, few students are competent to collaborate with others online. The purposes of this study were to identify student perceptions and performance in online collaboration compared to those of…

To See or Not to See: Effects of Online Access to Peer-Generated Questions on Performance

ERIC Educational Resources Information Center

Yu, Fu-Yun; Yang, Yen-Ting

2014-01-01

This study examined the effects on performance of online access to peer-generated questions during question-generation activities. Two eighth grade classes (N = 63) participated in six weekly question-generation sessions to support English learning. An online student question-generation learning system was adopted. In contrast to expectations…

An Analysis of Online Course Sizes as It Relates to Student Success and Faculty Performance through Hierarchical Regression

ERIC Educational Resources Information Center

Aylward, Bryan T.

2018-01-01

Online distance education program has continued to change the educational landscape in higher education. There has been extensive research on the relationship between course size, faculty performance, and student success within traditional on-ground colleges and universities, but limited research as it related to online educational modalities. The…

An online handwriting recognition system for Turkish

NASA Astrophysics Data System (ADS)

Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

2004-12-01

Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

An online handwriting recognition system for Turkish

NASA Astrophysics Data System (ADS)

Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

2005-01-01

Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

An Examination of Online Instructional Practices Based on the Learning Styles of Graduate Education Students

ERIC Educational Resources Information Center

Tonsing-Meyer, Julie

2013-01-01

The purpose of this qualitative case study was to understand the perceptions of online learning based on the learning styles of currently enrolled online graduate education students. Designing courses to provide meaningful experiences based on the learning styles of students, as well as the unique approaches to teaching online is a contemporary…

Recruiting and retaining youth and young adults: challenges and opportunities in survey research for tobacco control.

PubMed

Cantrell, Jennifer; Hair, Elizabeth C; Smith, Alexandria; Bennett, Morgane; Rath, Jessica Miller; Thomas, Randall K; Fahimi, Mansour; Dennis, J Michael; Vallone, Donna

2018-03-01

Evaluation studies of population-based tobacco control interventions often rely on large-scale survey data from numerous respondents across many geographic areas to provide evidence of their effectiveness. Significant challenges for survey research have emerged with the evolving communications landscape, particularly for surveying hard-to-reach populations such as youth and young adults. This study combines the comprehensive coverage of an address-based sampling (ABS) frame with the timeliness of online data collection to develop a nationally representative longitudinal cohort of young people aged 15-21. We constructed an ABS frame, partially supplemented with auxiliary data, to recruit this hard-to-reach sample. Branded and tested mail-based recruitment materials were designed to bring respondents online for screening, consent and surveying. Once enrolled, respondents completed online surveys every 6 months via computer, tablet or smartphone. Numerous strategies were utilized to enhance retention and representativeness RESULTS: Results detail sample performance, representativeness and retention rates as well as device utilization trends for survey completion among youth and young adult respondents. Panel development efforts resulted in a large, nationally representative sample with high retention rates. This study is among the first to employ this hybrid ABS-to-online methodology to recruit and retain youth and young adults in a probability-based online cohort panel. The approach is particularly valuable for conducting research among younger populations as it capitalizes on their increasing access to and comfort with digital communication. We discuss challenges and opportunities of panel recruitment and retention methods in an effort to provide valuable information for tobacco control researchers seeking to obtain representative, population-based samples of youth and young adults in the U.S. as well as across the globe. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Effects of online games on student performance in undergraduate physics

NASA Astrophysics Data System (ADS)

Sadiq, Irfan

The present state of physics teaching and learning is a reflection of the difficulty of the subject matter which has resulted in students' low motivation toward physics as well as lack of meaningful and deeper learning experiences. In light of an overall decline in interest in physics, an investigation of alternate teaching and learning methods and tools was appropriate. The research posed the following question: To what extent do online games about kinematics and two-dimensional motion impact student performance in undergraduate general physics as measured by a unit posttest? Two intact classes of 20 students each were randomly assigned to either the experimental group or the control group. Only the experimental group received the treatment of using online games. The duration of topics covered in the game content was identical to the lecture on kinematics and two-dimensional motion. Instructors for the experimental group incorporated online games in their regular classroom teaching, whereas those in the control group continued with their previously used curriculum without games. This study was conducted in three weekly sessions. Although students were not selected using random sampling, existing classes were randomly assigned to either the experimental group or the control group. There were 20 students in the experimental group and 20 students in the control group. The independent samples t test was conducted to compare the means of two independently sampled experimental and control groups. Analysis of covariance (ANCOVA) was used to determine if the two groups were significantly different with regard to their general physics performance on the posttest while controlling for the pretest scores. Analysis of posttest and pretest scores revealed that game-based learning did not significantly impact student performance.

A New Statistics-Based Online Baseline Restorer for a High Count-Rate Fully Digital System.

PubMed

Li, Hongdi; Wang, Chao; Baghaei, Hossain; Zhang, Yuxuan; Ramirez, Rocio; Liu, Shitao; An, Shaohui; Wong, Wai-Hoi

2010-04-01

The goal of this work is to develop a novel, accurate, real-time digital baseline restorer using online statistical processing for a high count-rate digital system such as positron emission tomography (PET). In high count-rate nuclear instrumentation applications, analog signals are DC-coupled for better performance. However, the detectors, pre-amplifiers and other front-end electronics would cause a signal baseline drift in a DC-coupling system, which will degrade the performance of energy resolution and positioning accuracy. Event pileups normally exist in a high-count rate system and the baseline drift will create errors in the event pileup-correction. Hence, a baseline restorer (BLR) is required in a high count-rate system to remove the DC drift ahead of the pileup correction. Many methods have been reported for BLR from classic analog methods to digital filter solutions. However a single channel BLR with analog method can only work under 500 kcps count-rate, and normally an analog front-end application-specific integrated circuits (ASIC) is required for the application involved hundreds BLR such as a PET camera. We have developed a simple statistics-based online baseline restorer (SOBLR) for a high count-rate fully digital system. In this method, we acquire additional samples, excluding the real gamma pulses, from the existing free-running ADC in the digital system, and perform online statistical processing to generate a baseline value. This baseline value will be subtracted from the digitized waveform to retrieve its original pulse with zero-baseline drift. This method can self-track the baseline without a micro-controller involved. The circuit consists of two digital counter/timers, one comparator, one register and one subtraction unit. Simulation shows a single channel works at 30 Mcps count-rate with pileup condition. 336 baseline restorer circuits have been implemented into 12 field-programmable-gate-arrays (FPGA) for our new fully digital PET system.

Telegenetics use in presymptomatic genetic counselling: patient evaluations on satisfaction and quality of care

PubMed Central

Otten, Ellen; Birnie, Erwin; Ranchor, Adelita V; van Langen, Irene M

2016-01-01

In recent years, online counselling has been introduced in clinical genetics to increase patients' access to care and to reduce time and cost for both patients and professionals. Most telegenetics reports so far evaluated online oncogenetic counselling at remote health centres in regions with large travelling distances, generally showing positive patient outcomes. We think online counselling – including the use of supportive tools that are also available during in-person counselling – of presymptomatic patients in their homes can also be feasible and valuable for patients in relatively small regions. We performed a single-centre pilot study of online genetic counselling for 57 patients who were presymptomatic cardiogenetic (n=17), presymptomatic oncogenetic (n=34) and prenatal (3 couples). One-third of presymptomatic patients we approached consented to online counselling. Patient evaluations of practical aspects, satisfaction and psychological outcomes were assessed and compared with a matched control group. Patients managed to fulfil the preparations, were significantly more satisfied with their counsellor and counselling session than controls and were satisfied with the online counselling more than they expected to be beforehand. Psychological outcomes (decreased anxiety and increased control) did not differ with control patients. Technical problems occurred in almost half of online sessions. Nonetheless, online counselling in patients' homes proved to be feasible and was appreciated by a substantial part of presymptomatic patients at our genetics centre in the Netherlands. Based on these outcomes, we conclude online counselling can be a valuable addition to existing counselling options in regular patient care. PMID:26173963

Environmental scan and evaluation of best practices for online systematic review resources

PubMed Central

Parker, Robin M. N.; Boulos, Leah M.; Visintini, Sarah; Ritchie, Krista; Hayden, Jill

2018-01-01

Objective Online training for systematic review methodology is an attractive option due to flexibility and limited availability of in-person instruction. Librarians often direct new reviewers to these online resources, so they should be knowledgeable about the variety of available resources. The objective for this project was to conduct an environmental scan of online systematic review training resources and evaluate those identified resources. Methods The authors systematically searched for electronic learning resources pertaining to systematic review methods. After screening for inclusion, we collected data about characteristics of training resources and assigned scores in the domains of (1) content, (2) design, (3) interactivity, and (4) usability by applying a previously published evaluation rubric for online instruction modules. We described the characteristics and scores for each training resource and compared performance across the domains. Results Twenty training resources were evaluated. Average overall score of online instructional resources was 61%. Online courses (n=7) averaged 73%, web modules (n=5) 64%, and videos (n=8) 48%. The top 5 highest scoring resources were in course or web module format, featured high interactivity, and required a longer (>5hrs) time commitment from users. Conclusion This study revealed that resources include appropriate content but are less likely to adhere to principles of online training design and interactivity. Awareness of these resources will allow librarians to make informed recommendations for training based on patrons’ needs. Future online systematic review training resources should use established best practices for e-learning to provide high-quality resources, regardless of format or user time commitment. PMID:29632443

Development and pilot testing of an online case-based approach to shared decision making skills training for clinicians.

PubMed

Volk, Robert J; Shokar, Navkiran K; Leal, Viola B; Bulik, Robert J; Linder, Suzanne K; Mullen, Patricia Dolan; Wexler, Richard M; Shokar, Gurjeet S

2014-11-01

Although research suggests that patients prefer a shared decision making (SDM) experience when making healthcare decisions, clinicians do not routinely implement SDM into their practice and training programs are needed. Using a novel case-based strategy, we developed and pilot tested an online educational program to promote shared decision making (SDM) by primary care clinicians. A three-phased approach was used: 1) development of a conceptual model of the SDM process; 2) development of an online teaching case utilizing the Design A Case (DAC) authoring template, a well-tested process used to create peer-reviewed web-based clinical cases across all levels of healthcare training; and 3) pilot testing of the case. Participants were clinician members affiliated with several primary care research networks across the United States who answered an invitation email. The case used prostate cancer screening as the clinical context and was delivered online. Post-intervention ratings of clinicians' general knowledge of SDM, knowledge of specific SDM steps, confidence in and intention to perform SDM steps were also collected online. Seventy-nine clinicians initially volunteered to participate in the study, of which 49 completed the case and provided evaluations. Forty-three clinicians (87.8%) reported the case met all the learning objectives, and 47 (95.9%) indicated the case was relevant for other equipoise decisions. Thirty-one clinicians (63.3%) accessed supplementary information via links provided in the case. After viewing the case, knowledge of SDM was high (over 90% correctly identified the steps in a SDM process). Determining a patient's preferred role in making the decision (62.5% very confident) and exploring a patient's values (65.3% very confident) about the decisions were areas where clinician confidence was lowest. More than 70% of the clinicians intended to perform SDM in the future. A comprehensive model of the SDM process was used to design a case-based approach to teaching SDM skills to primary care clinicians. The case was favorably rated in this pilot study. Clinician skills training for helping patients clarify their values and for assessing patients' desire for involvement in decision making remain significant challenges and should be a focus of future comparative studies.

VizieR Online Data Catalog: MV Lyr - bursts and periods (Pavlenko, 1998)

NASA Astrophysics Data System (ADS)

Pavlenko, E. P.

2001-01-01

The analysis of photometric behavior of the nova-like star MV Lyr in B in the low brightness state in 1995-1996 based on the observations performed at the Crimean Astrophysical Observatory with the MTM-500 television system was presented. (1 data file).

Embodiment and Performance

ERIC Educational Resources Information Center

Bessell, Jacquelyn; Riddell, Patricia

2016-01-01

Evidence suggests that some cognitive processes are based on sensorimotor systems in the brain (embodied cognition). The premise of this is that "Biological brains are first and foremost the control systems for biological bodies". It has therefore been suggested that both online cognition (processing as we move through the world) and…

Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Jozmaleki, Mehrdad; Valipour, Mahsa

2018-01-01

One of the main features to invest in stock exchange companies is their financial performance. On the other hand, conventional evaluation methods such as data envelopment analysis are not only a retrospective process, but are also a process, which are incomplete and ineffective approaches to evaluate the companies in the future. To remove this problem, it is required to plan an expert system for evaluating organizations when the online data are received from stock exchange market. This paper deals with an approach for predicting the online financial performance of companies when data are received in different time's intervals. The proposed approach is based on integrating fuzzy C-means (FCM), data envelopment analysis (DEA) and artificial neural network (ANN). The classical FCM method is unable to update the number of clusters and their members when the data are changed or the new data are received. Hence, this method is developed in order to make dynamic features for the number of clusters and clusters members in classical FCM. Then, DEA is used to evaluate DMUs by using financial ratios to provide targets in neural network. Finally, the designed network is trained and prepared for predicting companies' future performance. The data on Tehran Stock Market companies for six consecutive years (2007-2012) are used to show the abilities of the proposed approach.

Identifying online user reputation in terms of user preference

NASA Astrophysics Data System (ADS)

Dai, Lu; Guo, Qiang; Liu, Xiao-Lu; Liu, Jian-Guo; Zhang, Yi-Cheng

2018-03-01

Identifying online user reputation is significant for online social systems. In this paper, taking into account the preference physics of online user collective behaviors, we present an improved group-based rating method for ranking online user reputation based on the user preference (PGR). All the ratings given by each specific user are mapped to the same rating criteria. By grouping users according to their mapped ratings, the online user reputation is calculated based on the corresponding group sizes. Results for MovieLens and Netflix data sets show that the AUC values of the PGR method can reach 0.9842 (0.9493) and 0.9995 (0.9987) for malicious (random) spammers, respectively, outperforming the results generated by the traditional group-based method, which indicates that the online preference plays an important role for measuring user reputation.

Consumer Preference and Attitude Regarding Online Food Products in Hanoi, Vietnam

PubMed Central

Kim Dang, Anh; Xuan Tran, Bach; Tat Nguyen, Cuong; Thi Le, Huong; Thi Do, Hoa; Duc Nguyen, Hinh; Hoang Nguyen, Long; Huu Nguyen, Tu; Thi Mai, Hue; Dinh Tran, Tho; Ngo, Chau; Thi Minh Vu, Thuc; Latkin, Carl A.; Zhang, Melvyn W.B.

2018-01-01

This study aimed to examine: (1) how the Internet has changed consumers food-buying behavior and identify its associated factors; (2) consumers’ concern about food safety information of online food products. A cross-sectional study was performed from October to December 2015 in Hanoi—a Vietnamese epicenter of food service. One thousand seven hundred and thirty six (1736) customers were randomly chosen from food establishments of 176 communes. Data were collected through face-to-face interviews using structured questionnaires. The majority of participants reported using the Internet to search for food products (81.3%). The most crucial factors influencing food purchases through the Internet were convenience (69.1%) and price (59.3%). Only one-third of participants selected products based on accurate evidence about food safety certification or food origin. The majority of participants were concerned about the expiration date (51.6%), while brand (9.8%) and food licensing information (11.3%) were often neglected. People who were:(1) female, (2) highly influenced by online relationships, and (3) having difficulty in doing usual activities were more likely to look for online food products. These findings produce practical advice to consumers when purchasing their desired food products on the Internet, to online food retailers and to the Government of Vietnam to implement appropriate legislation regarding trading online food products. PMID:29757954

Consumer Preference and Attitude Regarding Online Food Products in Hanoi, Vietnam.

PubMed

Kim Dang, Anh; Xuan Tran, Bach; Tat Nguyen, Cuong; Thi Le, Huong; Thi Do, Hoa; Duc Nguyen, Hinh; Hoang Nguyen, Long; Huu Nguyen, Tu; Thi Mai, Hue; Dinh Tran, Tho; Ngo, Chau; Thi Minh Vu, Thuc; Latkin, Carl A; Zhang, Melvyn W B; Ho, Roger C M

2018-05-14

This study aimed to examine: (1) how the Internet has changed consumers food-buying behavior and identify its associated factors; (2) consumers' concern about food safety information of online food products. A cross-sectional study was performed from October to December 2015 in Hanoi-a Vietnamese epicenter of food service. One thousand seven hundred and thirty six (1736) customers were randomly chosen from food establishments of 176 communes. Data were collected through face-to-face interviews using structured questionnaires. The majority of participants reported using the Internet to search for food products (81.3%). The most crucial factors influencing food purchases through the Internet were convenience (69.1%) and price (59.3%). Only one-third of participants selected products based on accurate evidence about food safety certification or food origin. The majority of participants were concerned about the expiration date (51.6%), while brand (9.8%) and food licensing information (11.3%) were often neglected. People who were:(1) female, (2) highly influenced by online relationships, and (3) having difficulty in doing usual activities were more likely to look for online food products. These findings produce practical advice to consumers when purchasing their desired food products on the Internet, to online food retailers and to the Government of Vietnam to implement appropriate legislation regarding trading online food products.

An online outlier identification and removal scheme for improving fault detection performance.

PubMed

Ferdowsi, Hasan; Jagannathan, Sarangapani; Zawodniok, Maciej

2014-05-01

Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be used to remove the outliers. The OIR scheme uses a neural network (NN) to estimate the actual system states from measured system states involving outliers. With this method, the outlier detection is performed online at each time instant by finding the difference between the estimated and the measured states and comparing its median with its standard deviation over a moving time window. The NN weight update law in OIR is designed such that the detected outliers will have no effect on the state estimation, which is subsequently used for model-based fault diagnosis. In addition, since the OIR estimator cannot distinguish between the faulty or healthy operating conditions, a separate model-based observer is designed for fault diagnosis, which uses the OIR scheme as a preprocessing unit to improve the FD performance. The stability analysis of both OIR and fault diagnosis schemes are introduced. Finally, a three-tank benchmarking system and a simple linear system are used to verify the proposed scheme in simulations, and then the scheme is applied on an axial piston pump testbed. The scheme can be applied to nonlinear systems whose dynamics and underlying distribution of states are subjected to change due to both unknown faults and operating conditions.

Sol-gel niobia sorbent with a positively charged octadecyl ligand providing enhanced enrichment of nucleotides and organophosphorus pesticides in capillary microextraction for online HPLC analysis.

PubMed

Kesani, Sheshanka; Malik, Abdul

2018-04-01

A niobia-based sol-gel organic-inorganic hybrid sorbent carrying a positively charged C 18 ligand (Nb 2 O 5 -C 18 (+ve)) was synthesized to achieve enhanced enrichment capability in capillary microextraction of organophosphorus compounds (which include organophosphorus pesticides and nucleotides) before their online analysis by high-performance liquid chromatography. The sorbent was designed to simultaneously provide three different types of molecular level interactions: electrostatic, Lewis acid-base, and van der Waals interactions. To understand relative contributions of various molecular level analyte-sorbent interactions in the extraction process, two other sol-gel niobia sorbents were also created: (a) a purely inorganic sol-gel niobia sorbent (Nb 2 O 5 ) and (b) an organic-inorganic hybrid sol-gel niobia sorbent carrying an electrically neutral-bonded octadecyl ligand (Nb 2 O 5 -C 18 ). The extraction efficiency of the created sol-gel niobia sorbent (Nb 2 O 5 -C 18 (+ve)) was compared with that of analogously designed and synthesized titania-based sol-gel sorbent (TiO 2 -C 18 (+ve)), taking into consideration that titania-based sorbents present state-of-the-art extraction media for organophosphorus compounds. In capillary microextraction with high-performance liquid chromatography analysis, Nb 2 O 5 -C 18 (+ve) had shown 40-50% higher specific extraction values (a measure of extraction efficiency) over that of TiO 2 -C 18 (+ve). Compared to TiO 2 -C 18 (+ve), Nb 2 O 5 -C 18 (+ve) also provided superior analyte desorption efficiency (96 vs. 90%) during the online release of the extracted organophosphorus pesticides from the sorbent coating in the capillary microextraction capillary to the chromatographic column using reversed-phase high-performance liquid chromatography mobile phase. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Guided and unguided internet-based vestibular rehabilitation versus usual care for dizzy adults of 50 years and older: a protocol for a three-armed randomised trial

PubMed Central

van der Wouden, Johannes C; Bosmans, Judith E; Smalbrugge, Martin; van Diest, Willianne; Essery, Rosie; Yardley, Lucy; van der Horst, Henriëtte E; Maarsingh, Otto R

2017-01-01

Introduction Dizziness is a common symptom in general practice with a high prevalence among older adults. The most common cause of dizziness in general practice is peripheral vestibular disease. Vestibular rehabilitation (VR) is a safe and effective treatment for peripheral vestibular disease that entails specific exercises to maximise the central nervous system compensation for the effects of vestibular pathology. An internet-based VR intervention has recently been shown to be safe and effective. Online interventions are low cost and easily accessible, but prone to attrition and non-adherence. A combination of online and face-to-face therapy, known as blended care, may balance these advantages and disadvantages. Methods and analysis A single-blind, three-arm, randomised controlled trial among patients aged 50 years and over presenting with dizziness of vestibular origin in general practice will be performed. In this study, we will compare the clinical and cost-effectiveness of stand-alone internet-based VR and internet-based VR with physiotherapeutic support (‘blended care’) with usual care during 6 months of follow-up. We will use a translated Dutch version of a British online VR intervention. Randomisation will be stratified by dizziness severity. The primary outcome measure is the Vertigo Symptoms Scale—Short Form. Intention-to-treat analysis will be performed, adjusting for confounders. The economic evaluation will be conducted from a societal perspective. We will perform an additional analysis on the data to identify predictors of successful treatment in the same population to develop a clinical decision rule for general practitioners. Ethics and dissemination The ethical committee of the VU University Medical Center approved ethics and dissemination of the study protocol. The insights and results of this study will be widely disseminated through international peer-reviewed journals and conference presentations. Trial registration number Pre-results, NTR5712. PMID:28110290

A comparative analysis of traditional and online lab science transfer courses in the rural community college

NASA Astrophysics Data System (ADS)

Scott, Andrea

Through distance learning, the community college system has moved beyond geographical boundaries to serve all students and provide educational opportunities at a distance to individuals previously out of reach of the college community. With the inception of the Mississippi Virtual Community College (MSVCC) in January 2000, Mississippi's public community colleges have experienced unprecedented growth in online enrollments and online course offerings to include the laboratory sciences; however, transfer of online lab science courses are problematic for individuals who wish to gain admittance to Medical, Dental, and Pharmacy schools in Mississippi. Currently online lab science courses are not accepted for transfer for students seeking admission to Mississippi Medical, Dental, or Pharmacy schools. The need for this study, the statement of the problem, and the purpose of the study address transfer issues related to the transfer of online lab science courses in Mississippi and the impact of such on the student and community college. The study also addresses existing doubts regarding online course delivery as a viable method of lab science delivery. The purpose of the study was to investigate differences between online instructional delivery as compared to traditional face-to-face delivery with the following research questions to: (1) Investigate the perception of quality of online courses as compared to traditional face-to-face courses. (2) Investigate the difference in student performance in online transfer lab science courses as compared to student performance in traditional face-to-face lab science courses. The results of this 13 semester study show significant differences in both perception of quality and student performance between online instructional delivery as compared to traditional face-to-face delivery. The findings demonstrate a need for Mississippi Dental, Medical, and Pharmacy schools to reexamine the articulation agreement between IHL and Community and Junior Colleges and consider accepting online lab sciences courses taken at the community college as transfer for admission to Medical, Dental, and Pharmacy schools. Conclusions are included in the study; however, additional studies are needed to address the issue of student performance in the online lab science classroom.

Online access to journal abstracts and articles.

PubMed

Giedd, J N; Smith, K G

1997-01-01

Advances in information technology now offer several options for child and adolescent psychopharmacologists to navigate the increasingly complex terrain of scientific literature and keep abreast of the rapidly changing advances in our field. MEDLINE, the world's largest database of medical literature, can be accessed and searched by a variety of free or fee-based services. In addition to efficient retrieval of citations and abstracts based on subject, author, or title, many of these services now provide, for a fee, the entire text and graphics of articles (displayed on computer screen, faxed, or mailed). There are also current awareness services to alert the user when new requested literature become available as well as services to send via e-mail the tables of contents of requested journals (sometimes prior to paper publication). For online citation and abstract retrieval, we found that free services, such as PubMed, performed as good or better than fee-based services. Physicians' Online, sponsored by the pharmaceutical industry, offered the lowest price for full-text manuscript delivery. In this article, we review literature search, delivery, and update services and offer some tips on how to most effectively use these resources.

Incorporating a collaborative web-based virtual laboratory in an undergraduate bioinformatics course.

PubMed

Weisman, David

2010-01-01

Face-to-face bioinformatics courses commonly include a weekly, in-person computer lab to facilitate active learning, reinforce conceptual material, and teach practical skills. Similarly, fully-online bioinformatics courses employ hands-on exercises to achieve these outcomes, although students typically perform this work offsite. Combining a face-to-face lecture course with a web-based virtual laboratory presents new opportunities for collaborative learning of the conceptual material, and for fostering peer support of technical bioinformatics questions. To explore this combination, an in-person lecture-only undergraduate bioinformatics course was augmented with a remote web-based laboratory, and tested with a large class. This study hypothesized that the collaborative virtual lab would foster active learning and peer support, and tested this hypothesis by conducting a student survey near the end of the semester. Respondents broadly reported strong benefits from the online laboratory, and strong benefits from peer-provided technical support. In comparison with traditional in-person teaching labs, students preferred the virtual lab by a factor of two. Key aspects of the course architecture and design are described to encourage further experimentation in teaching collaborative online bioinformatics laboratories. Copyright © 2010 International Union of Biochemistry and Molecular Biology, Inc.

PEEK tube-based online solid-phase microextraction-high-performance liquid chromatography for the determination of yohimbine in rat plasma and its application in pharmacokinetics study.

PubMed

Xiang, Xiaowei; Shang, Bing; Wang, Xiaozheng; Chen, Qinhua

2017-04-01

Yohimbine is a novel compound for the treatment of erectile dysfunction derived from natural products, and pharmacokinetic study is important for its further development as a new medicine. In this work, we developed a novel PEEK tube-based solid-phase microextraction (SPME)-HPLC method for analysis of yohimbine in plasma and further for pharmacokinetic study. Poly (AA-EGDMA) was synthesized inside a PEEK tube as the sorbent for microextraction of yohimbine, and parameters that could influence extraction efficiency were systematically investigated. Under optimum conditions, the PEEK tube-based SPME method exhibits excellent enrichment efficiency towards yohimbine. By using berberine as internal standard, an online SPME-HPLC method was developed for analysis of yohimbine in human plasma sample. The method has wide linear range (2-1000 ng/mL) with an R 2 of 0.9962; the limit of detection was determined and was as low as 0.1 ng/mL using UV detection. Finally, a pharmacokinetic study of yohimbine was carried out by the online SPME-HPLC method and the results have been compared with those of reported methods. Copyright © 2016 John Wiley & Sons, Ltd.

Understanding user intents in online health forums.

PubMed

Zhang, Thomas; Cho, Jason H D; Zhai, Chengxiang

2015-07-01

Online health forums provide a convenient way for patients to obtain medical information and connect with physicians and peers outside of clinical settings. However, large quantities of unstructured and diversified content generated on these forums make it difficult for users to digest and extract useful information. Understanding user intents would enable forums to find and recommend relevant information to users by filtering out threads that do not match particular intents. In this paper, we derive a taxonomy of intents to capture user information needs in online health forums and propose novel pattern-based features for use with a multiclass support vector machine (SVM) classifier to classify original thread posts according to their underlying intents. Since no dataset existed for this task, we employ three annotators to manually label a dataset of 1192 HealthBoards posts spanning four forum topics. Experimental results show that a SVM using pattern-based features is highly capable of identifying user intents in forum posts, reaching a maximum precision of 75%, and that a SVM-based hierarchical classifier using both pattern and word features outperforms its SVM counterpart that uses only word features. Furthermore, comparable classification performance can be achieved by training and testing on posts from different forum topics.

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

PubMed

Zwartjes, Ardjan; Havinga, Paul J M; Smit, Gerard J M; Hurink, Johann L

2016-10-01

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

Teaching Renewable Energy Using Online PBL in Investigating Its Effect on Behaviour towards Energy Conservation among Malaysian Students: ANOVA Repeated Measures Approach

ERIC Educational Resources Information Center

Nordin, Norfarah; Samsudin, Mohd Ali; Harun, Abdul Hadi

2017-01-01

This research aimed to investigate whether online problem based learning (PBL) approach to teach renewable energy topic improves students' behaviour towards energy conservation. A renewable energy online problem based learning (REePBaL) instruction package was developed based on the theory of constructivism and adaptation of the online learning…

A scintillator-based online detector for the angularly resolved measurement of laser-accelerated proton spectra.

PubMed

Metzkes, J; Karsch, L; Kraft, S D; Pawelke, J; Richter, C; Schürer, M; Sobiella, M; Stiller, N; Zeil, K; Schramm, U

2012-12-01

In recent years, a new generation of high repetition rate (~10 Hz), high power (~100 TW) laser systems has stimulated intense research on laser-driven sources for fast protons. Considering experimental instrumentation, this development requires online diagnostics for protons to be added to the established offline detection tools such as solid state track detectors or radiochromic films. In this article, we present the design and characterization of a scintillator-based online detector that gives access to the angularly resolved proton distribution along one spatial dimension and resolves 10 different proton energy ranges. Conceived as an online detector for key parameters in laser-proton acceleration, such as the maximum proton energy and the angular distribution, the detector features a spatial resolution of ~1.3 mm and a spectral resolution better than 1.5 MeV for a maximum proton energy above 12 MeV in the current design. Regarding its areas of application, we consider the detector a useful complement to radiochromic films and Thomson parabola spectrometers, capable to give immediate feedback on the experimental performance. The detector was characterized at an electrostatic Van de Graaff tandetron accelerator and tested in a laser-proton acceleration experiment, proving its suitability as a diagnostic device for laser-accelerated protons.

An accurate online calibration system based on combined clamp-shape coil for high voltage electronic current transformers.

PubMed

Li, Zhen-hua; Li, Hong-bin; Zhang, Zhi

2013-07-01

Electronic transformers are widely used in power systems because of their wide bandwidth and good transient performance. However, as an emerging technology, the failure rate of electronic transformers is higher than that of traditional transformers. As a result, the calibration period needs to be shortened. Traditional calibration methods require the power of transmission line be cut off, which results in complicated operation and power off loss. This paper proposes an online calibration system which can calibrate electronic current transformers without power off. In this work, the high accuracy standard current transformer and online operation method are the key techniques. Based on the clamp-shape iron-core coil and clamp-shape air-core coil, a combined clamp-shape coil is designed as the standard current transformer. By analyzing the output characteristics of the two coils, the combined clamp-shape coil can achieve verification of the accuracy. So the accuracy of the online calibration system can be guaranteed. Moreover, by employing the earth potential working method and using two insulating rods to connect the combined clamp-shape coil to the high voltage bus, the operation becomes simple and safe. Tests in China National Center for High Voltage Measurement and field experiments show that the proposed system has a high accuracy of up to 0.05 class.

Benchmarking the ATLAS software through the Kit Validation engine

NASA Astrophysics Data System (ADS)

De Salvo, Alessandro; Brasolin, Franco

2010-04-01

The measurement of the experiment software performance is a very important metric in order to choose the most effective resources to be used and to discover the bottlenecks of the code implementation. In this work we present the benchmark techniques used to measure the ATLAS software performance through the ATLAS offline testing engine Kit Validation and the online portal Global Kit Validation. The performance measurements, the data collection, the online analysis and display of the results will be presented. The results of the measurement on different platforms and architectures will be shown, giving a full report on the CPU power and memory consumption of the Monte Carlo generation, simulation, digitization and reconstruction of the most CPU-intensive channels. The impact of the multi-core computing on the ATLAS software performance will also be presented, comparing the behavior of different architectures when increasing the number of concurrent processes. The benchmark techniques described in this paper have been used in the HEPiX group since the beginning of 2008 to help defining the performance metrics for the High Energy Physics applications, based on the real experiment software.

A fast and precise indoor localization algorithm based on an online sequential extreme learning machine.

PubMed

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-15

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.

Impact of Online Orientation for First-Time Online Students on Retention, Academic Success, and Persistence

ERIC Educational Resources Information Center

Marshall, Lynda

2017-01-01

A challenge faced by higher education is whether online orientation that is offered before the start of class can impact academic performance for online students. The purpose of this quantitative research study was to determine if there are significant differences in retention, academic success, and persistence between first time online students…

A Comparison of the Performance of Online versus Traditional On-Campus Earth Science Students on Identical Exams

ERIC Educational Resources Information Center

Werhner, Matthew J.

2010-01-01

In this paper I compare the performance of online versus traditional on-campus students on identical exams in an earth science class. The number of college level distance learning classes offered online continues to increase as they offer greater scheduling flexibility to students, they appeal to students who like to work independently, and allow…

Student Performance in Computing Education: An Empirical Analysis of Online Learning in Programming Education Environments

ERIC Educational Resources Information Center

Xia, Belle Selene; Liitiäinen, Elia

2017-01-01

The benefits of using online exercises have been analysed in terms of distance learning, automatic assessment and self-regulated learning. In this study, we have not found a direct proportional relationship between student performance in the course exercises that use online technologies and the exam grades. We see that the average submission rate…

Do the Timeliness, Regularity, and Intensity of Online Work Habits Predict Academic Performance?

ERIC Educational Resources Information Center

Dvorak, Tomas; Jia, Miaoqing

2016-01-01

This study analyzes the relationship between students' online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students'…

Evaluating the Advantages and Disadvantages of Providing Lecture Notes: The Role of Internet Technology as a Delivery System and Research Tool

ERIC Educational Resources Information Center

Grabe, Mark; Christopherson, Kimberly

2005-01-01

Relationships among patterns of access to online notes, examination performance, and student absenteeism were examined. Students who made more frequent use of online notes performed at a higher level on course examinations. Students most frequently accessed online notes while corresponding lecture content was being presented in class, but this…

A Thermal Expert System (TEXSYS) development overview - AI-based control of a Space Station prototype thermal bus

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hack, E. C.

1990-01-01

A knowledge-based control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external thermal control system (TCS) is discussed in this paper. The Thermal Expert System (TEXSYS) has been demonstrated in recent tests to be capable of both fault anticipation and detection and real-time control of the thermal bus. Performance requirements were achieved by using a symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous during software development and testing. One representative example is given from on-line TCS tests of TEXSYS. The integration and testing of TEXSYS with a live TCS testbed provides some insight on the use of formal software design, development and documentation methodologies to qualify knowledge-based systems for on-line or flight applications.

A trap for the unwary: jury decision making in cases involving the entrapment defense.

PubMed

Peters, Christopher S; Lampinen, James Michael; Malesky, L Alvin

2013-02-01

This article examines the opinions of jury-eligible participants regarding entrapment-related issues in online sex offender sting operations. Participants provided lower guilt ratings when the undercover officer initiated the online sexual solicitation than when the defendant initiated the online sexual solicitation. This effect was mediated by the causal attributions (situational vs. dispositional) made by mock jurors for the defendant's actions. The results also suggested that the entrapment defense was less successful for participants with a crime control orientation than for participants with a due process orientation. Based on the results, it is implied that law enforcement should exercise caution when performing these types of sting operations. Furthermore, defense and prosecuting attorneys should take into account the originators of the sexual solicitation when deciding whether to plea bargain or take a case to trial.

Visual object tracking by correlation filters and online learning

NASA Astrophysics Data System (ADS)

Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

2018-06-01

Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

A pulse shape discriminator and an online system for the balloon-borne hard X-ray/gamma-ray detector

NASA Astrophysics Data System (ADS)

Takahashi, T.; Kamae, T.; Tanaka, M.; Gunji, S.; Miyazuki, S.; Tamura, T.; Sekimoto, Y.; Yamaoka, N.; Nishimura, J.; Yajima, N.

Attention is given to a new kind of phoswich counters (the well-type phoswich counter) that will be capable of detecting very low flux hard X-rays/gamma-rays (40-1000 keV) from astronomical objects. A specially designed pulse-shape discriminator (PSD) selects hard X-rays/gamma-rays that has deposited energy only in the detection part. Sixty-four such counters are assembled into an array where each phoswich element acts as an active shield to the neighboring elements too. The ADCs, the TDCs, the hit-pattern latches, and the precision clock are read out by a VME-based online system, stored on an 8-mm video tape, and transmitted to the ground station. The design and performance of the pulse shape discriminator and the online system are described.

Automated solid-phase extraction coupled online with HPLC-FLD for the quantification of zearalenone in edible oil.

PubMed

Drzymala, Sarah S; Weiz, Stefan; Heinze, Julia; Marten, Silvia; Prinz, Carsten; Zimathies, Annett; Garbe, Leif-Alexander; Koch, Matthias

2015-05-01

Established maximum levels for the mycotoxin zearalenone (ZEN) in edible oil require monitoring by reliable analytical methods. Therefore, an automated SPE-HPLC online system based on dynamic covalent hydrazine chemistry has been developed. The SPE step comprises a reversible hydrazone formation by ZEN and a hydrazine moiety covalently attached to a solid phase. Seven hydrazine materials with different properties regarding the resin backbone, pore size, particle size, specific surface area, and loading have been evaluated. As a result, a hydrazine-functionalized silica gel was chosen. The final automated online method was validated and applied to the analysis of three maize germ oil samples including a provisionally certified reference material. Important performance criteria for the recovery (70-120 %) and precision (RSDr <25 %) as set by the Commission Regulation EC 401/2006 were fulfilled: The mean recovery was 78 % and RSDr did not exceed 8 %. The results of the SPE-HPLC online method were further compared to results obtained by liquid-liquid extraction with stable isotope dilution analysis LC-MS/MS and found to be in good agreement. The developed SPE-HPLC online system with fluorescence detection allows a reliable, accurate, and sensitive quantification (limit of quantification, 30 μg/kg) of ZEN in edible oils while significantly reducing the workload. To our knowledge, this is the first report on an automated SPE-HPLC method based on a covalent SPE approach.

Early Identification of Student Performance and Effort Using an Online Homework System: A Pilot Study

ERIC Educational Resources Information Center

Perdian, David C.

2013-01-01

Two distinct student groups, in terms of academic performance, were identified early in the semester as either being under-performing students or over-performing students using an online homework system. The students who are identified as under-performing received, on average, lower grades than their fellow students but spent more time completing…

Quality assurance for kilo- and megavoltage in-room imaging and localization for off- and online setup error correction.

PubMed

Balter, James M; Antonuk, Larry E

2008-01-01

In-room radiography is not a new concept for image-guided radiation therapy. Rapid advances in technology, however, have made this positioning method convenient, and thus radiograph-based positioning has propagated widely. The paradigms for quality assurance of radiograph-based positioning include imager performance, systems integration, infrastructure, procedure documentation and testing, and support for positioning strategy implementation.

Interactional leader–follower sensorimotor communication strategies during repetitive joint actions

PubMed Central

Candidi, Matteo; Curioni, Arianna; Donnarumma, Francesco; Sacheli, Lucia Maria; Pezzulo, Giovanni

2015-01-01

Non-verbal communication is the basis of animal interactions. In dyadic leader–follower interactions, leaders master the ability to carve their motor behaviour in order to ‘signal’ their future actions and internal plans while these signals influence the behaviour of follower partners, who automatically tend to imitate the leader even in complementary interactions. Despite their usefulness, signalling and imitation have a biomechanical cost, and it is unclear how this cost–benefits trade-off is managed during repetitive dyadic interactions that present learnable regularities. We studied signalling and imitation dynamics (indexed by movement kinematics) in pairs of leaders and followers during a repetitive, rule-based, joint action. Trial-by-trial Bayesian model comparison was used to evaluate the relation between signalling, imitation and pair performance. The different models incorporate different hypotheses concerning the factors (past interactions versus online movements) influencing the leader's signalling (or follower's imitation) kinematics. This approach showed that (i) leaders' signalling strategy improves future couple performance, (ii) leaders used the history of past interactions to shape their signalling, (iii) followers' imitative behaviour is more strongly affected by the online movement of the leader. This study elucidates the ways online sensorimotor communication help individuals align their task representations and ultimately improves joint action performance. PMID:26333815

Interactional leader-follower sensorimotor communication strategies during repetitive joint actions.

PubMed

Candidi, Matteo; Curioni, Arianna; Donnarumma, Francesco; Sacheli, Lucia Maria; Pezzulo, Giovanni

2015-09-06

Non-verbal communication is the basis of animal interactions. In dyadic leader-follower interactions, leaders master the ability to carve their motor behaviour in order to 'signal' their future actions and internal plans while these signals influence the behaviour of follower partners, who automatically tend to imitate the leader even in complementary interactions. Despite their usefulness, signalling and imitation have a biomechanical cost, and it is unclear how this cost-benefits trade-off is managed during repetitive dyadic interactions that present learnable regularities. We studied signalling and imitation dynamics (indexed by movement kinematics) in pairs of leaders and followers during a repetitive, rule-based, joint action. Trial-by-trial Bayesian model comparison was used to evaluate the relation between signalling, imitation and pair performance. The different models incorporate different hypotheses concerning the factors (past interactions versus online movements) influencing the leader's signalling (or follower's imitation) kinematics. This approach showed that (i) leaders' signalling strategy improves future couple performance, (ii) leaders used the history of past interactions to shape their signalling, (iii) followers' imitative behaviour is more strongly affected by the online movement of the leader. This study elucidates the ways online sensorimotor communication help individuals align their task representations and ultimately improves joint action performance. © 2015 The Author(s).

A Team-Based Online Game Improves Blood Glucose Control in Veterans With Type 2 Diabetes: A Randomized Controlled Trial.

PubMed

Kerfoot, B Price; Gagnon, David R; McMahon, Graham T; Orlander, Jay D; Kurgansky, Katherine E; Conlin, Paul R

2017-09-01

Rigorous evidence is lacking whether online games can improve patients' longer-term health outcomes. We investigated whether an online team-based game delivering diabetes self-management education (DSME) to patients via e-mail or mobile application (app) can generate longer-term improvements in hemoglobin A 1c (HbA 1c ). Patients ( n = 456) on oral diabetes medications with HbA 1c ≥58 mmol/mol were randomly assigned between a DSME game (with a civics booklet) and a civics game (with a DSME booklet). The 6-month games sent two questions twice weekly via e-mail or mobile app. Participants accrued points based on performance, with scores posted on leaderboards. Winning teams and individuals received modest financial rewards. Our primary outcome measure was HbA 1c change over 12 months. DSME game patients had significantly greater HbA 1c reductions over 12 months than civics game patients (-8 mmol/mol [95% CI -10 to -7] and -5 mmol/mol [95% CI -7 to -3], respectively; P = 0.048). HbA 1c reductions were greater among patients with baseline HbA 1c >75 mmol/mol: -16 mmol/mol [95% CI -21 to -12] and -9 mmol/mol [95% CI -14 to -5] for DSME and civics game patients, respectively; P = 0.031. Patients with diabetes who were randomized to an online game delivering DSME demonstrated sustained and meaningful HbA 1c improvements. Among patients with poorly controlled diabetes, the DSME game reduced HbA 1c by a magnitude comparable to starting a new diabetes medication. Online games may be a scalable approach to improve outcomes among geographically dispersed patients with diabetes and other chronic diseases. © 2017 by the American Diabetes Association.

Lexicon-enhanced sentiment analysis framework using rule-based classification scheme.

PubMed

Asghar, Muhammad Zubair; Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

2017-01-01

With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public's feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users' reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users' reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods.

A self-paced brain-computer interface for controlling a robot simulator: an online event labelling paradigm and an extended Kalman filter based algorithm for online training.

PubMed

Tsui, Chun Sing Louis; Gan, John Q; Roberts, Stephen J

2009-03-01

Due to the non-stationarity of EEG signals, online training and adaptation are essential to EEG based brain-computer interface (BCI) systems. Self-paced BCIs offer more natural human-machine interaction than synchronous BCIs, but it is a great challenge to train and adapt a self-paced BCI online because the user's control intention and timing are usually unknown. This paper proposes a novel motor imagery based self-paced BCI paradigm for controlling a simulated robot in a specifically designed environment which is able to provide user's control intention and timing during online experiments, so that online training and adaptation of the motor imagery based self-paced BCI can be effectively investigated. We demonstrate the usefulness of the proposed paradigm with an extended Kalman filter based method to adapt the BCI classifier parameters, with experimental results of online self-paced BCI training with four subjects.

Multilabel user classification using the community structure of online networks

PubMed Central

Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user’s graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score. PMID:28278242

Multilabel user classification using the community structure of online networks.

PubMed

Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

Monitoring gradient profile on-line in micro- and nano-high performance liquid chromatography using conductivity detection.

PubMed

Zhang, Min; Chen, Apeng; Lu, Joann J; Cao, Chengxi; Liu, Shaorong

2016-08-19

In micro- or nano-flow high performance liquid chromatography (HPLC), flow-splitters and gradient elutions are commonly used for reverse phase HPLC separations. When a flow splitter was used at a high split-ratio (e.g., 1000:1 or higher), the actual gradient may deviate away from the programmed gradient. Sometimes, mobile phase concentrations can deviate by as much as 5%. In this work, we noticed that the conductivity (σ) of a gradient decreased with the increasing organic-solvent fraction (φ). Based on the relationship between σ and φ, a method was developed for monitoring gradient profile on-line to record any deviations in these HPLC systems. The conductivity could be measured by a traditional conductivity detector or a capacitively coupled contactless conductivity detector (C(4)D). The method was applied for assessing the performance of an electroosmotic pump (EOP) based nano-HPLC. We also observed that σ value of the gradient changed with system pressure; a=0.0175ΔP (R(2)=0.964), where a is the percentage of the conductivity increase and ΔP is the system pressure in bar. This effect was also investigated. Copyright © 2016. Published by Elsevier B.V.

Study protocol for a transversal study to develop a screening model for excessive gambling behaviours on a representative sample of users of French authorised gambling websites

PubMed Central

Hardouin, Jean-Benoit; Grall-Bronnec, Marie; Challet-Bouju, Gaëlle

2017-01-01

Introduction Since the legalisation of online gambling in France in 2010, gambling operators must implement responsible gambling measures to prevent excessive gambling practices. However, actually there is no screening procedure for identifying problematic gamblers. Although several studies have already been performed using several data sets from online gambling operators, the authors deplored several methodological and clinical limits that prevent scientifically validating the existence of problematic gambling behaviour. The aim of this study is to develop a model for screening excessive gambling practices based on the gambling behaviours observed on French gambling websites, coupled with a clinical validation. Methods and analysis The research is divided into three successive stages. All analyses will be performed for each major type of authorised online gambling in France. The first stage aims at defining a typology of users of French authorised gambling websites based on their gambling behaviour. This analysis will be based on data from the Authority for Regulating Online Gambling (ARJEL) and the Française Des Jeux (FDJ). For the second stage aiming at determining a score to predict whether a gambler is problematic or not, we will cross answers from the Canadian Problem Gambling Index with real gambling data. The objective of the third stage is to clinically validate the score previously developed. Results from the screening model will be compared (using sensitivity, specificity, area under the curve, and positive and negative predictive values) with the diagnosis obtained with a telephone clinical interview, including diagnostic criteria for gambling addiction. Ethics and dissemination This study was approved by the local Research Ethics Committee (GNEDS) on 25 March 2015. Results will be presented in national and international conferences, submitted to peer-reviewed journals and will be part of a PhD thesis. A final report with the study results will be presented to the ARJEL, especially the final screening model. Trial registration number NCT02415296. PMID:28515192

Performance Evaluation of an Online Argumentation Learning Assistance Agent

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Wang, Yu-Wu; Huang, Tz-Hau; Chen, Ying-Chen; Chen, Heng-Ming; Chang, Shun-Chih

2011-01-01

Recent research indicated that students' ability to construct evidence-based explanations in classrooms through scientific inquiry is critical to successful science education. Structured argumentation support environments have been built and used in scientific discourse in the literature. To the best of our knowledge, no research work in the…

Incorporating a Collaborative Web-Based Virtual Laboratory in an Undergraduate Bioinformatics Course

ERIC Educational Resources Information Center

Weisman, David

2010-01-01

Face-to-face bioinformatics courses commonly include a weekly, in-person computer lab to facilitate active learning, reinforce conceptual material, and teach practical skills. Similarly, fully-online bioinformatics courses employ hands-on exercises to achieve these outcomes, although students typically perform this work offsite. Combining a…

Decision Making in Online Fantasy Sports Communities

ERIC Educational Resources Information Center

Smith, Brian; Sharma, Priya; Hooper, Paula

2006-01-01

This paper describes the forms of knowledge used by players of fantasy sports, games where players create ideal sports teams and compete to accumulate points based on professional athletes' statistical performances. Messages from a discussion forum associated with a popular fantasy basketball game were analyzed to understand how players described…

A Final Report for the Evaluation of the Achieve3000 Programs

ERIC Educational Resources Information Center

Shannon, Lisa; Grant, Billie-Jo

2015-01-01

Achieve3000 publishes a number of online literacy programs that differentiate lessons and activities based on student performance. Magnolia Consulting--an independent, third party evaluation firm--assessed Achieve3000 Solutions' impact on student learning during the 2014-15 school year. The researchers used a randomized control trial, where…

The BIOSIS data base: Evaluation of its indexes and the STRATBLDR, CHEMFILE, STAIRS and DIALOG systems for on-line searching

NASA Technical Reports Server (NTRS)

Nees, M.; Green, H. O.

1977-01-01

An IBM-developed program, STAIRS, was selected for performing a search on the BIOSIS file. The evaluation of the hardware and search systems and the strategies used are discussed. The searches are analyzed by type of end user.

Case Study: eCoaching in a Corporate Environment

ERIC Educational Resources Information Center

Warner, Teri L. C.

2012-01-01

This qualitative particularistic case study was an exploration and evaluation of an online, asynchronous, non-human coaching system called an "eCoaching system." Developed by the researcher, the eCoaching system combined performance coaching with the latest technologies in eLearning. The coaching was based on the appreciative inquiry approach, and…

How Virtual Team Leaders Cope with Creativity Challenges

ERIC Educational Resources Information Center

Han, Soo Jeoung; Chae, Chungil; Macko, Patricia; Park, Woongbae; Beyerlein, Michael

2017-01-01

Purpose: As technology-mediated communication improves, many organizations increasingly use new types of collaborative online tools to promote team-based learning and performance. The purpose of this study is to explore how virtual team leaders cope with process challenges in developing a context for team creativity. Design/methodology/approach:…

A Proposed Performance-Based System for Teacher Interactive Electronic Continuous Professional Development (TIE-CPD)

ERIC Educational Resources Information Center

Razak, Rafiza Abdul; Yusop, Farrah Dina; Idris, Aizal Yusrina; Al-Sinaiyah, Yanbu; Halili, Siti Hajar

2016-01-01

The paper introduces Teacher Interactive Electronic Continuous Professional Development (TIE-CPD), an online interactive training system. The framework and methodology of TIE-CPD are designed with functionalities comparable with existing e-training systems. The system design and development literature offers several methodology and framework…

Using E-Learning to Improve Prescribing Practice in Emerging Prescribers

ERIC Educational Resources Information Center

Baskett, Karen

2011-01-01

This paper reports on "The National Prescribing Curriculum" (NPC), a series of online, case-based modules designed to improve prescribing performance and confidence in emerging Australian prescribers. The modules mirror the decision-making process outlined in the "WHO Guide to Good Prescribing" (de Vries "et al.",…

Responding to an RFP: A Vendor's Viewpoint.

ERIC Educational Resources Information Center

Kington, Robert A.

1987-01-01

Outlines factors used by online vendors to decide whether to bid on RFPs (requests for proposals) for library automation systems, including specifications for software, hardware or performance requirements not met by the vendor; specifications based on competitors' systems; the size and complexity of the request itself; and vendors' time…

Learning from label proportions in brain-computer interfaces: Online unsupervised learning with guarantees.

PubMed

Hübner, David; Verhoeven, Thibault; Schmid, Konstantin; Müller, Klaus-Robert; Tangermann, Michael; Kindermans, Pieter-Jan

2017-01-01

Using traditional approaches, a brain-computer interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g., by subject-to-subject transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratch and adapt over time. While such heuristics work well in practice, none of them can provide theoretical guarantees. Our objective is to modify an event-related potential (ERP) paradigm to work in unison with the machine learning decoder, and thus to achieve a reliable unsupervised calibrationless decoding with a guarantee to recover the true class means. We introduce learning from label proportions (LLP) to the BCI community as a new unsupervised, and easy-to-implement classification approach for ERP-based BCIs. The LLP estimates the mean target and non-target responses based on known proportions of these two classes in different groups of the data. We present a visual ERP speller to meet the requirements of LLP. For evaluation, we ran simulations on artificially created data sets and conducted an online BCI study with 13 subjects performing a copy-spelling task. Theoretical considerations show that LLP is guaranteed to minimize the loss function similar to a corresponding supervised classifier. LLP performed well in simulations and in the online application, where 84.5% of characters were spelled correctly on average without prior calibration. The continuously adapting LLP classifier is the first unsupervised decoder for ERP BCIs guaranteed to find the optimal decoder. This makes it an ideal solution to avoid tedious calibration sessions. Additionally, LLP works on complementary principles compared to existing unsupervised methods, opening the door for their further enhancement when combined with LLP.

Learning from label proportions in brain-computer interfaces: Online unsupervised learning with guarantees

PubMed Central

Verhoeven, Thibault; Schmid, Konstantin; Müller, Klaus-Robert; Tangermann, Michael; Kindermans, Pieter-Jan

2017-01-01

Objective Using traditional approaches, a brain-computer interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g., by subject-to-subject transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratch and adapt over time. While such heuristics work well in practice, none of them can provide theoretical guarantees. Our objective is to modify an event-related potential (ERP) paradigm to work in unison with the machine learning decoder, and thus to achieve a reliable unsupervised calibrationless decoding with a guarantee to recover the true class means. Method We introduce learning from label proportions (LLP) to the BCI community as a new unsupervised, and easy-to-implement classification approach for ERP-based BCIs. The LLP estimates the mean target and non-target responses based on known proportions of these two classes in different groups of the data. We present a visual ERP speller to meet the requirements of LLP. For evaluation, we ran simulations on artificially created data sets and conducted an online BCI study with 13 subjects performing a copy-spelling task. Results Theoretical considerations show that LLP is guaranteed to minimize the loss function similar to a corresponding supervised classifier. LLP performed well in simulations and in the online application, where 84.5% of characters were spelled correctly on average without prior calibration. Significance The continuously adapting LLP classifier is the first unsupervised decoder for ERP BCIs guaranteed to find the optimal decoder. This makes it an ideal solution to avoid tedious calibration sessions. Additionally, LLP works on complementary principles compared to existing unsupervised methods, opening the door for their further enhancement when combined with LLP. PMID:28407016

Hollow porous ionic liquids composite polymers based solid phase extraction coupled online with high performance liquid chromatography for selective analysis of hydrophilic hydroxybenzoic acids from complex samples.

PubMed

Dai, Xingping; Wang, Dongsheng; Li, Hui; Chen, Yanyi; Gong, Zhicheng; Xiang, Haiyan; Shi, Shuyun; Chen, Xiaoqing

2017-02-10

Polar and hydrophilic properties of hydroxybenzoic acids usually made them coelute with interferences in high performance liquid chromatography (HPLC) analysis. Then selective analysis of them was necessary. Herein, hollow porous ionic liquids composite polymers (PILs) based solid phase extraction (SPE) was firstly fabricated and coupled online with HPLC for selective analysis of hydroxybenzoic acids from complex matrices. Hollow porous PILs were firstly synthesized using Mobil Composition of Matter No. 48 (MCM-48) spheres as sacrificial support, 1-vinyl-3-methylimidazolium chloride (VMIM + Cl - ) as monomer, and ethylene glycol dimethacrylate (EGDMA) as cross-linker. Various parameters affecting synthesis, adsorption and desorption behaviors were investigated and optimized. Steady-state adsorption studies showed the resulting hollow porous PILs exhibited high adsorption capacity, fast adsorption kinetics, and excellent specific adsorption. Subsequently, the application of online SPE system was studied by selective analysis of protocatechuic acid (PCA), 4-hydroxybenzoic acid (4-HBA), and vanillic acid (VA) from Pollen Typha angustifolia. The obtained limit of detection (LOD) varied from 0.002 to 0.01μg/mL, the linear range (0.05-5.0μg/mL) was wide with correlation coefficient (R) from 0.9982 to 0.9994, and the average recoveries at three spiking levels ranged from 82.7 to 102.4%, with column-to-column relative standard deviation (RSD) below 8.1%. The proposed online method showed good accuracy, precision, specificity and convenience, which opened up a universal and efficient route for selective analysis of hydroxybenzoic acids from complex samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Breastfeeding Infants with Ankyloglossia: Insight into Mothers' Experiences.

PubMed

Wong, Kevin; Patel, Punam; Cohen, Michael B; Levi, Jessica R

2017-03-01

Breastfeeding difficulty from ankyloglossia can affect both the mother and baby in a breastfeeding dyad. With renewed emphasis in today's culture on breast milk, mothers may feel increasing pressure to breastfeed, and the inability for some to do so may cause significant distress. Recently, online parenting forums have seen exponential growth; these forums allow mothers to connect with peers undergoing similar life transitions. The purpose of this study was to review online discussions regarding ankyloglossia to understand mothers' experiences with breastfeeding. We performed an ethnographic content analysis of 76 online threads and 501 posts regarding ankyloglossia based on six domains: (1) initial expectations, (2) breastfeeding complications, (3) questions, (4) diagnosis, (5) treatment, and (6) outcomes. About one-fourth of women who participated in online forum discussions had initial expectations to breastfeed, however, many found it impossible due to poor latch or pain. Concerns were frequently exacerbated by healthcare providers who reportedly missed or overlooked ankyloglossia. Although these complications made breastfeeding a challenging experience, mothers often described both subjective and physical improvements after frenotomy. Breastfeeding difficulty was a commonly voiced concern in online ankyloglossia forums. Forum analysis is an effective way to gain insight into patients' experiences, which allows providers to anticipate concerns and provides more effective counseling.

On-line bolt-loosening detection method of key components of running trains using binocular vision

NASA Astrophysics Data System (ADS)

Xie, Yanxia; Sun, Junhua

2017-11-01

Bolt loosening, as one of hidden faults, affects the running quality of trains and even causes serious safety accidents. However, the developed fault detection approaches based on two-dimensional images cannot detect bolt-loosening due to lack of depth information. Therefore, we propose a novel online bolt-loosening detection method using binocular vision. Firstly, the target detection model based on convolutional neural network (CNN) is used to locate the target regions. And then, stereo matching and three-dimensional reconstruction are performed to detect bolt-loosening faults. The experimental results show that the looseness of multiple bolts can be characterized by the method simultaneously. The measurement repeatability and precision are less than 0.03mm, 0.09mm respectively, and its relative error is controlled within 1.09%.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

PubMed

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

PubMed Central

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294

Design of on-line system for measuring and tracking time of assembly

NASA Astrophysics Data System (ADS)

Senderská, Katarína; Mareš, Albert; Evin, Emil

2016-04-01

Manual assembly performed at assembly workstations nowadays still has a unique place in different kinds of production. To increase the productivity and quality of manual assembly it is necessary to analyse the existing workplaces and find ways to improve and streamline work done at these workplaces. The article deals with the design of a model for on-line analysis of a manual assembly process. The proposed model is based on the use of sensors or the so-called button-box and the use of software for recording and evaluating data. Based on the obtained data it is then possible to evaluate the time characteristics of the assembly process, aswell as to find sources of delays and mistakes and then take appropriate action to correct them.

Relationship Among Dental Students' Class Lecture Attendance, Use of Online Resources, and Performance.

PubMed

Azab, Ehab; Saksena, Yun; Alghanem, Tofool; Midle, Jennifer Bassett; Molgaard, Kathleen; Albright, Susan; Karimbux, Nadeem

2016-04-01

This study aimed to evaluate the relationship among dental students' attendance at class lectures, use of online lecture materials, and performance in didactic courses. The study was conducted with second-year predoctoral students at Tufts University School of Dental Medicine during the fall semester of 2014. Three basic science and three preclinical dental courses were selected for evaluation. Online usage for each participant was collected, and a survey with questions about attendance and online behavior was conducted. The final grade for each participant in each selected course was obtained and matched with his or her online usage and attendance. Out of a total 190 students, 146 (77%) participated. The results showed no significant relationship between students' grades and their class attendance or online usage except for a weak negative relationship between class attendance and online usage for the Epidemiology course (p<0.001) and the overall preclinical dental courses (p=0.03). Although the results did not show strong relationships among class attendance, online usage, and course grades, most of the students reported that having the online resources in addition to the lectures was helpful.

Localization of Mobile Robots Using Odometry and an External Vision Sensor

PubMed Central

Pizarro, Daniel; Mazo, Manuel; Santiso, Enrique; Marron, Marta; Jimenez, David; Cobreces, Santiago; Losada, Cristina

2010-01-01

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields. PMID:22319318

Localization of mobile robots using odometry and an external vision sensor.

PubMed

Pizarro, Daniel; Mazo, Manuel; Santiso, Enrique; Marron, Marta; Jimenez, David; Cobreces, Santiago; Losada, Cristina

2010-01-01

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.

Using the Cognitive Apprenticeship Web-based Argumentation System to Improve Argumentation Instruction

NASA Astrophysics Data System (ADS)

Tsai, Chun-Yen; Jack, Brady Michael; Huang, Tai-Chu; Yang, Jin-Tan

2012-08-01

This study investigated how the instruction of argumentation skills could be promoted by using an online argumentation system. This system entitled `Cognitive Apprenticeship Web-based Argumentation' (CAWA) system was based on cognitive apprenticeship model. One hundred eighty-nine fifth grade students took part in this study. A quasi-experimental design was adopted and qualitative and quantitative analyses were used to evaluate the effectiveness of this online system in measuring students' progress in learning argumentation. The results of this study showed that different teaching strategies had effects on students' use of argumentation in the topics of daily life and the concept of `vision.' When the CAWA system was employed during the instruction and practice of argumentation on these two topics, the students' argumentation performance improved. Suggestions on how the CAWA system could be used to enhance the instruction of argumentation skills in science education were also discussed.

Online quizzes promote inconsistent improvements on in-class test performance in introductory anatomy and physiology.

PubMed

Brown, Gregory A; Bice, Matthew R; Shaw, Brandon S; Shaw, Ina

2015-06-01

Review quizzes can provide students with feedback and assist in the preparation for in-class tests, but students often do not voluntarily use self-testing resources. The purpose of the present study was to evaluate if taking a mandatory online review quiz alters performance on subsequent in-class tests. During two semesters of a single-semester introductory anatomy and physiology course, students were required to complete brief online quizzes after each textbook chapter had been covered during lecture as well as the day before an in-class test. During the next two semesters, students were not required to take the online review quizzes. Overall scores on chapter specific in-class tests were higher (P < 0.05) during the semesters in which students took online review quizzes (82.9 ± 14.3%) compared with when they did not (78.7 ± 15.5%), but all in-class tests were not improved. Scores on comprehensive midterm examinations were higher (83.0 ± 12.9% vs. 78.9 ± 13.7%, P < 0.05) but not on final examinations (72.4 ± 13.8% vs. 71.8 ± 14.0%) between those with online review quizzes and those without, respectively. Overall scores on in-class tests and comprehensive examinations were higher (P < 0.05) during the semesters in which students took online review quizzes (83.4 ± 16.8%) compared with when they did not (80.3 ± 17.6%). These data suggest that an online review quiz taken the day before an in-class test increases performance on some in-class tests. However, online review quizzes taken after completion of each chapter do not consistently enhance performance on comprehensive examinations. Copyright © 2015 The American Physiological Society.

PSO-SVM-Based Online Locomotion Mode Identification for Rehabilitation Robotic Exoskeletons.

PubMed

Long, Yi; Du, Zhi-Jiang; Wang, Wei-Dong; Zhao, Guang-Yu; Xu, Guo-Qiang; He, Long; Mao, Xi-Wang; Dong, Wei

2016-09-02

Locomotion mode identification is essential for the control of a robotic rehabilitation exoskeletons. This paper proposes an online support vector machine (SVM) optimized by particle swarm optimization (PSO) to identify different locomotion modes to realize a smooth and automatic locomotion transition. A PSO algorithm is used to obtain the optimal parameters of SVM for a better overall performance. Signals measured by the foot pressure sensors integrated in the insoles of wearable shoes and the MEMS-based attitude and heading reference systems (AHRS) attached on the shoes and shanks of leg segments are fused together as the input information of SVM. Based on the chosen window whose size is 200 ms (with sampling frequency of 40 Hz), a three-layer wavelet packet analysis (WPA) is used for feature extraction, after which, the kernel principal component analysis (kPCA) is utilized to reduce the dimension of the feature set to reduce computation cost of the SVM. Since the signals are from two types of different sensors, the normalization is conducted to scale the input into the interval of [0, 1]. Five-fold cross validation is adapted to train the classifier, which prevents the classifier over-fitting. Based on the SVM model obtained offline in MATLAB, an online SVM algorithm is constructed for locomotion mode identification. Experiments are performed for different locomotion modes and experimental results show the effectiveness of the proposed algorithm with an accuracy of 96.00% ± 2.45%. To improve its accuracy, majority vote algorithm (MVA) is used for post-processing, with which the identification accuracy is better than 98.35% ± 1.65%. The proposed algorithm can be extended and employed in the field of robotic rehabilitation and assistance.

PSO-SVM-Based Online Locomotion Mode Identification for Rehabilitation Robotic Exoskeletons

PubMed Central

Long, Yi; Du, Zhi-Jiang; Wang, Wei-Dong; Zhao, Guang-Yu; Xu, Guo-Qiang; He, Long; Mao, Xi-Wang; Dong, Wei

2016-01-01

Locomotion mode identification is essential for the control of a robotic rehabilitation exoskeletons. This paper proposes an online support vector machine (SVM) optimized by particle swarm optimization (PSO) to identify different locomotion modes to realize a smooth and automatic locomotion transition. A PSO algorithm is used to obtain the optimal parameters of SVM for a better overall performance. Signals measured by the foot pressure sensors integrated in the insoles of wearable shoes and the MEMS-based attitude and heading reference systems (AHRS) attached on the shoes and shanks of leg segments are fused together as the input information of SVM. Based on the chosen window whose size is 200 ms (with sampling frequency of 40 Hz), a three-layer wavelet packet analysis (WPA) is used for feature extraction, after which, the kernel principal component analysis (kPCA) is utilized to reduce the dimension of the feature set to reduce computation cost of the SVM. Since the signals are from two types of different sensors, the normalization is conducted to scale the input into the interval of [0, 1]. Five-fold cross validation is adapted to train the classifier, which prevents the classifier over-fitting. Based on the SVM model obtained offline in MATLAB, an online SVM algorithm is constructed for locomotion mode identification. Experiments are performed for different locomotion modes and experimental results show the effectiveness of the proposed algorithm with an accuracy of 96.00% ± 2.45%. To improve its accuracy, majority vote algorithm (MVA) is used for post-processing, with which the identification accuracy is better than 98.35% ± 1.65%. The proposed algorithm can be extended and employed in the field of robotic rehabilitation and assistance. PMID:27598160

Managing Trust in Online Social Networks

NASA Astrophysics Data System (ADS)

Bhuiyan, Touhid; Josang, Audun; Xu, Yue

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

Robust high-performance control for robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1991-01-01

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies have been merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal component that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and a feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nominal feedforward signal.

Robust high-performance control for robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies were merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal componet that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nomical feedforward signal.

Wlan-Based Indoor Localization Using Neural Networks

NASA Astrophysics Data System (ADS)

Saleem, Fasiha; Wyne, Shurjeel

2016-07-01

Wireless indoor localization has generated recent research interest due to its numerous applications. This work investigates Wi-Fi based indoor localization using two variants of the fingerprinting approach. Specifically, we study the application of an artificial neural network (ANN) for implementing the fingerprinting approach and compare its localization performance with a probabilistic fingerprinting method that is based on maximum likelihood estimation (MLE) of the user location. We incorporate spatial correlation of fading into our investigations, which is often neglected in simulation studies and leads to erroneous location estimates. The localization performance is quantified in terms of accuracy, precision, robustness, and complexity. Multiple methods for handling the case of missing APs in online stage are investigated. Our results indicate that ANN-based fingerprinting outperforms the probabilistic approach for all performance metrics considered in this work.

Impact of Online Discussions on Web Based Assessments

ERIC Educational Resources Information Center

Powell, Loreen M.; Wimmer, Hayden; Kilgus, Lawrence; Force, Christina

2017-01-01

The practice of including online discussion posts to traditional courses is increasing. Online discussions allow for active learning to occur as students express their ideas and respond to others. The time and thought provided by online discussion posts allows students to utilize higher level cognitive skills. Web-based assessments are another…

Design Considerations for Today's Online Learners: A Study of Personalized, Relationship-Based Social Awareness Information

ERIC Educational Resources Information Center

Heo, Misook

2009-01-01

This article examined online learners' preferences in personalized, relationship-based social awareness information sharing in course management systems. Three hundred seventy-seven online learners' willingness to share social awareness information was measured through a national survey. Results indicated that today's online learners are open…

Multiple UAV Cooperation for Wildfire Monitoring

NASA Astrophysics Data System (ADS)

Lin, Zhongjie

Wildfires have been a major factor in the development and management of the world's forest. An accurate assessment of wildfire status is imperative for fire management. This thesis is dedicated to the topic of utilizing multiple unmanned aerial vehicles (UAVs) to cooperatively monitor a large-scale wildfire. This is achieved through wildfire spreading situation estimation based on on-line measurements and wise cooperation strategy to ensure efficiency. First, based on the understanding of the physical characteristics of the wildfire propagation behavior, a wildfire model and a Kalman filter-based method are proposed to estimate the wildfire rate of spread and the fire front contour profile. With the enormous on-line measurements from on-board sensors of UAVs, the proposed method allows a wildfire monitoring mission to benefit from on-line information updating, increased flexibility, and accurate estimation. An independent wildfire simulator is utilized to verify the effectiveness of the proposed method. Second, based on the filter analysis, wildfire spreading situation and vehicle dynamics, the influence of different cooperation strategies of UAVs to the overall mission performance is studied. The multi-UAV cooperation problem is formulated in a distributed network. A consensus-based method is proposed to help address the problem. The optimal cooperation strategy of UAVs is obtained through mathematical analysis. The derived optimal cooperation strategy is then verified in an independent fire simulation environment to verify its effectiveness.

Towards the development of a hybrid-integrated chip interferometer for online surface profile measurements

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

Kumar, P.; Martin, H.; Jiang, X.

Non-destructive testing and online measurement of surface features are pressing demands in manufacturing. Thus optical techniques are gaining importance for characterization of complex engineering surfaces. Harnessing integrated optics for miniaturization of interferometry systems onto a silicon wafer and incorporating a compact optical probe would enable the development of a handheld sensor for embedded metrology applications. In this work, we present the progress in the development of a hybrid photonics based metrology sensor device for online surface profile measurements. The measurement principle along with test and measurement results of individual components has been presented. For non-contact measurement, a spectrally encoded lateralmore » scanning probe based on the laser scanning microscopy has been developed to provide fast measurement with lateral resolution limited to the diffraction limit. The probe demonstrates a lateral resolution of ∼3.6 μm while high axial resolution (sub-nanometre) is inherently achieved by interferometry. Further the performance of the hybrid tuneable laser and the scanning probe was evaluated by measuring a standard step height sample of 100 nm.« less

A hand and a field effect in on-line motor control in unilateral optic ataxia.

PubMed

Blangero, Annabelle; Gaveau, Valérie; Luauté, Jacques; Rode, Gilles; Salemme, Romeo; Guinard, Marine; Boisson, Dominique; Rossetti, Yves; Pisella, Laure

2008-05-01

Patients with bilateral optic ataxia fail to show rapid perturbation-induced corrections during manual aiming movements. Based on this, it has been proposed that this pathology results from a disruption of processes of on-line motor control in the posterior parietal cortex (PPC). Here, we show that on-line motor control performance in a patient with unilateral optic ataxia is similar to that of pointing towards stationary targets in peripheral vision, showing the same combination of hand and field effects. We also show that in the patient, manual correction towards his ataxic field was possible only when a preceding saccade (100msec earlier) rapidly provides foveal information about the new target location. In control subjects, manual correction was often, but not necessarily preceded by a saccade. These results allow us to put forward a model of visuo-manual transformation, which involves updating of the reach plan based on the target-eye error, and rely upon two dissociated spatial representations (of the hand and of the target, respectively) within the PPC.

Automated one-step DNA sequencing based on nanoliter reaction volumes and capillary electrophoresis.

PubMed

Pang, H M; Yeung, E S

2000-08-01

An integrated system with a nano-reactor for cycle-sequencing reaction coupled to on-line purification and capillary gel electrophoresis has been demonstrated. Fifty nanoliters of reagent solution, which includes dye-labeled terminators, polymerase, BSA and template, was aspirated and mixed with the template inside the nano-reactor followed by cycle-sequencing reaction. The reaction products were then purified by a size-exclusion chromatographic column operated at 50 degrees C followed by room temperature on-line injection of the DNA fragments into a capillary for gel electrophoresis. Over 450 bases of DNA can be separated and identified. As little as 25 nl reagent solution can be used for the cycle-sequencing reaction with a slightly shorter read length. Significant savings on reagent cost is achieved because the remaining stock solution can be reused without contamination. The steps of cycle sequencing, on-line purification, injection, DNA separation, capillary regeneration, gel-filling and fluidic manipulation were performed with complete automation. This system can be readily multiplexed for high-throughput DNA sequencing or PCR analysis directly from templates or even biological materials.

SOCR: Statistics Online Computational Resource

PubMed Central

Dinov, Ivo D.

2011-01-01

The need for hands-on computer laboratory experience in undergraduate and graduate statistics education has been firmly established in the past decade. As a result a number of attempts have been undertaken to develop novel approaches for problem-driven statistical thinking, data analysis and result interpretation. In this paper we describe an integrated educational web-based framework for: interactive distribution modeling, virtual online probability experimentation, statistical data analysis, visualization and integration. Following years of experience in statistical teaching at all college levels using established licensed statistical software packages, like STATA, S-PLUS, R, SPSS, SAS, Systat, etc., we have attempted to engineer a new statistics education environment, the Statistics Online Computational Resource (SOCR). This resource performs many of the standard types of statistical analysis, much like other classical tools. In addition, it is designed in a plug-in object-oriented architecture and is completely platform independent, web-based, interactive, extensible and secure. Over the past 4 years we have tested, fine-tuned and reanalyzed the SOCR framework in many of our undergraduate and graduate probability and statistics courses and have evidence that SOCR resources build student’s intuition and enhance their learning. PMID:21451741

How to improve essential skills in introductory physics through brief, spaced, online practice.

NASA Astrophysics Data System (ADS)

Heckler, Andrew; Mikula, Brendon

2017-01-01

We developed and implemented a set of online ``essential skills'' tasks to help students achieve and retain a core level of mastery and fluency in basic skills necessary for their coursework. The task design is based on our research on student understanding and difficulties as well as three well-established cognitive principles: 1) spaced practice, to promote retention, 2) interleaved practice, to promote the ability to recognize when the learned skill is needed, and 3) mastery practice mastery practice, to promote a base level of performance. We report on training on a variety of skills with vector math. Students spent a relatively small amount of time, 10-20 minutes in practice each week, answering relevant questions online until a mastery level was achieved. Results indicate significant and often dramatic gains, often with average gains of over one standard deviation. Notably, these large gains are retained at least several months after the final practice session, including for less-prepared students. Funding for this research was provided by the Center for Emergent Materials: an NSF MRSEC under Award Number DMR-1420451.

Online automatic tuning and control for fed-batch cultivation

PubMed Central

van Straten, Gerrit; van der Pol, Leo A.; van Boxtel, Anton J. B.

2007-01-01

Performance of controllers applied in biotechnological production is often below expectation. Online automatic tuning has the capability to improve control performance by adjusting control parameters. This work presents automatic tuning approaches for model reference specific growth rate control during fed-batch cultivation. The approaches are direct methods that use the error between observed specific growth rate and its set point; systematic perturbations of the cultivation are not necessary. Two automatic tuning methods proved to be efficient, in which the adaptation rate is based on a combination of the error, squared error and integral error. These methods are relatively simple and robust against disturbances, parameter uncertainties, and initialization errors. Application of the specific growth rate controller yields a stable system. The controller and automatic tuning methods are qualified by simulations and laboratory experiments with Bordetella pertussis. PMID:18157554

Phototoxicity testing by online irradiation and HPLC.

PubMed

Schröder, Sven; Surmann, J P

2006-11-01

A high-performance liquid chromatography (HPLC) system was developed for the determination of drug photostability and phototoxicity based on an automated column-switching system with aqueous online UV-A irradiation and hyphenated organic separation of the drug and its photoproducts. The photoreactor is built with an poly(ethylene-co-tetrafluoroethylene) (ETFE) reaction coil knitted around a UV-A light source. The chromatographic separation was performed with two special C18 columns, which are also suitable for using with pure water as eluent. Degradation of chlorpromazine (CPZ) by ultraviolet light was investigated at pH 7 and pH 3. Furthermore chlorpromazine was irradiated in the presence of guanosine-5-monophosphate (GMP) in pH 7 buffered solution, leading to a new photoproduct. In the pH 3 irradiation studies of CPZ and GMP, no reaction was detected between the molecules.

Electrochemical Impedance Sensors for Monitoring Trace Amounts of NO3 in Selected Growing Media.

PubMed

Ghaffari, Seyed Alireza; Caron, William-O; Loubier, Mathilde; Normandeau, Charles-O; Viens, Jeff; Lamhamedi, Mohammed S; Gosselin, Benoit; Messaddeq, Younes

2015-07-21

With the advent of smart cities and big data, precision agriculture allows the feeding of sensor data into online databases for continuous crop monitoring, production optimization, and data storage. This paper describes a low-cost, compact, and scalable nitrate sensor based on electrochemical impedance spectroscopy for monitoring trace amounts of NO3- in selected growing media. The nitrate sensor can be integrated to conventional microelectronics to perform online nitrate sensing continuously over a wide concentration range from 0.1 ppm to 100 ppm, with a response time of about 1 min, and feed data into a database for storage and analysis. The paper describes the structural design, the Nyquist impedance response, the measurement sensitivity and accuracy, and the field testing of the nitrate sensor performed within tree nursery settings under ISO/IEC 17025 certifications.

Electrochemical Impedance Sensors for Monitoring Trace Amounts of NO3 in Selected Growing Media

PubMed Central

Ghaffari, Seyed Alireza; Caron, William-O.; Loubier, Mathilde; Normandeau, Charles-O.; Viens, Jeff; Lamhamedi, Mohammed S.; Gosselin, Benoit; Messaddeq, Younes

2015-01-01

With the advent of smart cities and big data, precision agriculture allows the feeding of sensor data into online databases for continuous crop monitoring, production optimization, and data storage. This paper describes a low-cost, compact, and scalable nitrate sensor based on electrochemical impedance spectroscopy for monitoring trace amounts of NO3− in selected growing media. The nitrate sensor can be integrated to conventional microelectronics to perform online nitrate sensing continuously over a wide concentration range from 0.1 ppm to 100 ppm, with a response time of about 1 min, and feed data into a database for storage and analysis. The paper describes the structural design, the Nyquist impedance response, the measurement sensitivity and accuracy, and the field testing of the nitrate sensor performed within tree nursery settings under ISO/IEC 17025 certifications. PMID:26197322

A Comparative Study of Socioeconomically Disadvantaged and Non-Socioeconomically Disadvantaged Fourth-Grade Students in Reading and Math in an Online Charter School and a Traditional School

ERIC Educational Resources Information Center

Mansheim, Richard Lynn

2017-01-01

Few empirical studies explore how socioeconomic status (SES) disadvantaged students perform academically in a 100% online school. This causal-comparative ex post facto quantitative study examined how SES-disadvantaged students at an online charter school performed academically when compared with both SES-disadvantaged and non-SES-disadvantaged…

Dynamic online peer evaluations to improve group assignments in nursing e-learning environment.

PubMed

Adwan, Jehad

2016-06-01

The purpose of this research was to evaluate the use of online peer evaluation forms for online group activities in improving group project outcomes. The investigator developed and used a web-based Google Forms® self and peer evaluation form of 2 group assignments' rubric for junior and senior nursing students. The form covered elements of the assignments including: research activity, analysis of the literature, writing of report, participation in making of presentation, overall contribution to the project, and participation in the weekly group discussions. Items were rated from 1 (did not contribute) to 5 (outstanding contribution) in addition to NA when one activity did not apply. The self and peer evaluation process was conducted twice: once after group assignment 1 and once after group assignment 2. The group assignments final products were done in the form of VoiceThread online presentations that were shared with the rest of the class reflecting the groups' work on a health informatics topic of interest. Data collected as the students completed self and peer evaluations for group assignments 1 and 2. Also, optional comments regarding member performance were collected to add contextual information in addition to ratings. Students received credit for completing the peer evaluations and the grade for the particular assignment was affected by their performance based on peer evaluations of their contributions. Students' peer evaluations showed in a color-coded spreadsheet which enabled the course faculty to view real time results of students' ratings after each assignment. The faculty provided timely and tailored feedback to groups or individuals as needed, using positive feedback and commending high performance while urging struggling individual students and groups to improve lower ratings in specific areas. Comparing evaluations of both assignments, there were statistically significant improvements among all students. The mean scores of the entire sample were skewed toward the higher end of the scale, suggesting an overall high performance group. However, analysis of the lower performing individuals showed consistent and statistically significant improvements in all areas of the evaluation criteria. Anonymous peer evaluation activities and timely faculty feedback in e-Learning environment can be a useful tool to faculty to improve group performance over time by engaging the learners within their groups. Peer evaluations provided real time view of group mid-semester formative evaluations that allowed the faculty to provide timely and tailored feedback on student performance which allowed for better outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficacy of a hybrid online training for panic symptoms and agoraphobia: study protocol for a randomized controlled trial.

PubMed

Ebenfeld, Lara; Kleine Stegemann, Stefan; Lehr, Dirk; Ebert, David Daniel; Jazaieri, Hooria; van Ballegooijen, Wouter; Funk, Burkhardt; Riper, Heleen; Berking, Matthias

2014-11-04

Recently, internet-based interventions have been proposed as effective treatments for people with panic disorder (PD). However, little is known about the clinical effects of integrating mobile technology into these interventions. Because users carry their smartphones with them throughout the day, we hypothesize that this technology can be used to significantly support individuals with monitoring and overcoming their PD symptoms. The aim of the present study is to evaluate the efficacy and cost-effectiveness of a newly developed hybrid intervention that combines internet/PC with smartphone delivery to treat the symptoms of PD. The intervention is based on cognitive behavioral therapy and consists of six modules over a total of six weeks. A two-arm randomized controlled trial (RCT) will be conducted to evaluate the effects of a hybrid online training module for PD. Based on a power calculation (d =0.60; 1-β of 80%; α =0.05), 90 participants with mild to moderate panic symptoms with or without agoraphobia (as assessed by the Panic and Agoraphobia Scale) will be recruited from the general population and randomly assigned to either the intervention group or a six-month waitlist control group. The primary outcome measure will be the severity of panic symptoms. Secondary outcomes will include depression, quality of life, and an observer-based rating of panic severity. Furthermore, data regarding acceptance and the usability of the smartphone app will be assessed. Assessments will take place at baseline as well as eight weeks, three months, and six months after randomization. Moreover, a cost-effectiveness analysis will be performed from a societal perspective. Data will be analyzed on an intention-to-treat basis and per protocol. To our knowledge, this RCT is one of the first to examine the efficacy of a hybrid online training for adult PD. This study seeks to contribute to the emerging field of hybrid online training. If the intervention is efficacious, then research on this hybrid online training should be extended. The cost-effectiveness analysis will also indicate whether online training is an economical tool for treating PD among adults. German Clinical Trial Register: DRKS00005223 (registered on 15 August 2013).