The efficacy of stuttering measurement training: evaluating two training programs.

PubMed

Bainbridge, Lauren A; Stavros, Candace; Ebrahimian, Mineh; Wang, Yuedong; Ingham, Roger J

2015-04-01

Two stuttering measurement training programs currently used for training clinicians were evaluated for their efficacy in improving the accuracy of total stuttering event counting. Four groups, each with 12 randomly allocated participants, completed a pretest-posttest design training study. They were evaluated by their counts of stuttering events on eight 3-min audiovisual speech samples from adults and children who stutter. Stuttering judgment training involved use of either the Stuttering Measurement System (SMS), Stuttering Measurement Assessment and Training (SMAAT) programs, or no training. To test for the reliability of any training effect, SMS training was repeated with the 4th group. Both SMS-trained groups produced approximately 34% improvement, significantly better than no training or the SMAAT program. The SMAAT program produced a mixed result. The SMS program was shown to produce a "medium" effect size improvement in the accuracy of stuttering event counts, and this improvement was almost perfectly replicated in a 2nd group. Half of the SMAAT judges produced a 36% improvement in accuracy, but the other half showed no improvement. Additional studies are needed to demonstrate the durability of the reported improvements, but these positive effects justify the importance of stuttering measurement training.

Analysis on accuracy improvement of rotor-stator rubbing localization based on acoustic emission beamforming method.

PubMed

He, Tian; Xiao, Denghong; Pan, Qiang; Liu, Xiandong; Shan, Yingchun

2014-01-01

This paper attempts to introduce an improved acoustic emission (AE) beamforming method to localize rotor-stator rubbing fault in rotating machinery. To investigate the propagation characteristics of acoustic emission signals in casing shell plate of rotating machinery, the plate wave theory is used in a thin plate. A simulation is conducted and its result shows the localization accuracy of beamforming depends on multi-mode, dispersion, velocity and array dimension. In order to reduce the effect of propagation characteristics on the source localization, an AE signal pre-process method is introduced by combining plate wave theory and wavelet packet transform. And the revised localization velocity to reduce effect of array size is presented. The accuracy of rubbing localization based on beamforming and the improved method of present paper are compared by the rubbing test carried on a test table of rotating machinery. The results indicate that the improved method can localize rub fault effectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

NASA Astrophysics Data System (ADS)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions.

PubMed

Ma, Liheng; Zhan, Dejun; Jiang, Guangwen; Fu, Sihua; Jia, Hui; Wang, Xingshu; Huang, Zongsheng; Zheng, Jiaxing; Hu, Feng; Wu, Wei; Qin, Shiqiao

2015-09-01

The attitude accuracy of a star sensor decreases rapidly when star images become motion-blurred under dynamic conditions. Existing techniques concentrate on a single frame of star images to solve this problem and improvements are obtained to a certain extent. An attitude-correlated frames (ACF) approach, which concentrates on the features of the attitude transforms of the adjacent star image frames, is proposed to improve upon the existing techniques. The attitude transforms between different star image frames are measured by the strap-down gyro unit precisely. With the ACF method, a much larger star image frame is obtained through the combination of adjacent frames. As a result, the degradation of attitude accuracy caused by motion-blurring are compensated for. The improvement of the attitude accuracy is approximately proportional to the square root of the number of correlated star image frames. Simulations and experimental results indicate that the ACF approach is effective in removing random noises and improving the attitude determination accuracy of the star sensor under highly dynamic conditions.

Quality improvement of International Classification of Diseases, 9th revision, diagnosis coding in radiation oncology: single-institution prospective study at University of California, San Francisco.

PubMed

Chen, Chien P; Braunstein, Steve; Mourad, Michelle; Hsu, I-Chow J; Haas-Kogan, Daphne; Roach, Mack; Fogh, Shannon E

2015-01-01

Accurate International Classification of Diseases (ICD) diagnosis coding is critical for patient care, billing purposes, and research endeavors. In this single-institution study, we evaluated our baseline ICD-9 (9th revision) diagnosis coding accuracy, identified the most common errors contributing to inaccurate coding, and implemented a multimodality strategy to improve radiation oncology coding. We prospectively studied ICD-9 coding accuracy in our radiation therapy--specific electronic medical record system. Baseline ICD-9 coding accuracy was obtained from chart review targeting ICD-9 coding accuracy of all patients treated at our institution between March and June of 2010. To improve performance an educational session highlighted common coding errors, and a user-friendly software tool, RadOnc ICD Search, version 1.0, for coding radiation oncology specific diagnoses was implemented. We then prospectively analyzed ICD-9 coding accuracy for all patients treated from July 2010 to June 2011, with the goal of maintaining 80% or higher coding accuracy. Data on coding accuracy were analyzed and fed back monthly to individual providers. Baseline coding accuracy for physicians was 463 of 661 (70%) cases. Only 46% of physicians had coding accuracy above 80%. The most common errors involved metastatic cases, whereby primary or secondary site ICD-9 codes were either incorrect or missing, and special procedures such as stereotactic radiosurgery cases. After implementing our project, overall coding accuracy rose to 92% (range, 86%-96%). The median accuracy for all physicians was 93% (range, 77%-100%) with only 1 attending having accuracy below 80%. Incorrect primary and secondary ICD-9 codes in metastatic cases showed the most significant improvement (10% vs 2% after intervention). Identifying common coding errors and implementing both education and systems changes led to significantly improved coding accuracy. This quality assurance project highlights the potential problem of ICD-9 coding accuracy by physicians and offers an approach to effectively address this shortcoming. Copyright © 2015. Published by Elsevier Inc.

A New Chemotherapeutic Investigation: Piracetam Effects on Dyslexia.

ERIC Educational Resources Information Center

Chase, Christopher H.; Schmitt, R. Larry

1984-01-01

Compared to placebo controls, 28 individuals treated with Piracetam (a new drug thought to enhance learning and memory consolidation) showed statistically significant improvements above baseline scores on measures of effective reading accuracy and comprehension, reading speed, and writing accuracy. The medication was well tolerated and showed no…

Internal and External Imagery Effects on Tennis Skills Among Novices.

PubMed

Dana, Amir; Gozalzadeh, Elmira

2017-10-01

The purpose of this study was to determine the effects of internal and external visual imagery perspectives on performance accuracy of open and closed tennis skills (i.e., serve, forehand, and backhand) among novices. Thirty-six young male novices, aged 15-18 years, from a summer tennis program participated. Following initial skill acquisition (12 sessions), baseline assessments of imagery ability and imagery perspective preference were used to assign participants to one of three groups: internal imagery ( n = 12), external imagery ( n = 12), or a no-imagery (mental math exercise) control group ( n = 12). The experimental interventions of 15 minutes of mental imagery (internal or external) or mental math exercises followed by 15 minutes of physical practice were held three times a week for six weeks. The performance accuracy of the groups on the serve, forehand, and backhand strokes was measured at pre- and post-test using videotaping. Results showed significant increases in the performance accuracy of all three tennis strokes in all three groups, but serve accuracy in the internal imagery group and forehand accuracy in the external imagery group showed greater improvements, while backhand accuracy was similarly improved in all three groups. These findings highlight differential efficacy of internal and external visual imagery for performance improvement on complex sport skills in early stage motor learning.

Alternative Loglinear Smoothing Models and Their Effect on Equating Function Accuracy. Research Report. ETS RR-09-48

ERIC Educational Resources Information Center

Moses, Tim; Holland, Paul

2009-01-01

This simulation study evaluated the potential of alternative loglinear smoothing strategies for improving equipercentile equating function accuracy. These alternative strategies use cues from the sample data to make automatable and efficient improvements to model fit, either through the use of indicator functions for fitting large residuals or by…

Learning Linear Spatial-Numeric Associations Improves Accuracy of Memory for Numbers

PubMed Central

Thompson, Clarissa A.; Opfer, John E.

2016-01-01

Memory for numbers improves with age and experience. One potential source of improvement is a logarithmic-to-linear shift in children’s representations of magnitude. To test this, Kindergartners and second graders estimated the location of numbers on number lines and recalled numbers presented in vignettes (Study 1). Accuracy at number-line estimation predicted memory accuracy on a numerical recall task after controlling for the effect of age and ability to approximately order magnitudes (mapper status). To test more directly whether linear numeric magnitude representations caused improvements in memory, half of children were given feedback on their number-line estimates (Study 2). As expected, learning linear representations was again linked to memory for numerical information even after controlling for age and mapper status. These results suggest that linear representations of numerical magnitude may be a causal factor in development of numeric recall accuracy. PMID:26834688

Learning Linear Spatial-Numeric Associations Improves Accuracy of Memory for Numbers.

PubMed

Thompson, Clarissa A; Opfer, John E

2016-01-01

Memory for numbers improves with age and experience. One potential source of improvement is a logarithmic-to-linear shift in children's representations of magnitude. To test this, Kindergartners and second graders estimated the location of numbers on number lines and recalled numbers presented in vignettes (Study 1). Accuracy at number-line estimation predicted memory accuracy on a numerical recall task after controlling for the effect of age and ability to approximately order magnitudes (mapper status). To test more directly whether linear numeric magnitude representations caused improvements in memory, half of children were given feedback on their number-line estimates (Study 2). As expected, learning linear representations was again linked to memory for numerical information even after controlling for age and mapper status. These results suggest that linear representations of numerical magnitude may be a causal factor in development of numeric recall accuracy.

Effect of black point on accuracy of LCD displays colorimetric characterization

NASA Astrophysics Data System (ADS)

Li, Tong; Xie, Kai; He, Nannan; Ye, Yushan

2018-03-01

Black point is the point at which RGB's single channel digital drive value is 0. Due to the problem of light leakage of liquid-crystal displays (LCDs), black point's luminance value is not 0, this phenomenon bring some errors to colorimetric characterization of LCDs, especially low luminance value driving greater sampling effect. This paper describes the characteristic accuracy of polynomial model method and the effect of black point on accuracy, the color difference accuracy is given. When considering the black point in the characteristics equation, the maximum color difference is 3.246, the maximum color difference than without considering the black points reduced by 2.36. The experimental results show that the accuracy of LCDs colorimetric characterization can be improved, if the effect of black point is eliminated properly.

Eight-Week Battle Rope Training Improves Multiple Physical Fitness Dimensions and Shooting Accuracy in Collegiate Basketball Players.

PubMed

Chen, Wei-Han; Wu, Huey-June; Lo, Shin-Liang; Chen, Hui; Yang, Wen-Wen; Huang, Chen-Fu; Liu, Chiang

2018-05-28

Chen, WH, Wu, HJ, Lo, SL, Chen, H, Yang, WW, Huang, CF, and Liu, C. Eight-week battle rope training improves multiple physical fitness dimensions and shooting accuracy in collegiate basketball players. J Strength Cond Res XX(X): 000-000, 2018-Basketball players must possess optimally developed physical fitness in multiple dimensions and shooting accuracy. This study investigated whether (battle rope [BR]) training enhances multiple physical fitness dimensions, including aerobic capacity (AC), upper-body anaerobic power (AnP), upper-body and lower-body power, agility, and core muscle endurance, and shooting accuracy in basketball players and compared its effects with those of regular training (shuttle run [SR]). Thirty male collegiate basketball players were randomly assigned to the BR or SR groups (n = 15 per group). Both groups received 8-week interval training for 3 sessions per week; the protocol consisted of the same number of sets, exercise time, and rest interval time. The BR group exhibited significant improvements in AC (Progressive Aerobic Cardiovascular Endurance Run laps: 17.6%), upper-body AnP (mean power: 7.3%), upper-body power (basketball chest pass speed: 4.8%), lower-body power (jump height: 2.6%), core muscle endurance (flexion: 37.0%, extension: 22.8%, and right side bridge: 23.0%), and shooting accuracy (free throw: 14.0% and dynamic shooting: 36.2%). However, the SR group exhibited improvements in only AC (12.0%) and upper-body power (3.8%) (p < 0.05). The BR group demonstrated larger pre-post improvements in upper-body AnP (fatigue index) and dynamic shooting accuracy than the SR group did (p < 0.05). The BR group showed higher post-training performance in upper-body AnP (mean power and fatigue index) than the SR group did (p < 0.05). Thus, BR training effectively improves multiple physical fitness dimensions and shooting accuracy in collegiate basketball players.

Theta Neurofeedback Effects on Motor Memory Consolidation and Performance Accuracy: An Apparent Paradox?

PubMed

Reiner, Miriam; Lev, Dror D; Rosen, Amit

2018-05-15

Previous studies have shown that theta neurofeedback enhances motor memory consolidation on an easy-to-learn finger-tapping task. However, the simplicity of the finger-tapping task precludes evaluating the putative effects of elevated theta on performance accuracy. Mastering a motor sequence is classically assumed to entail faster performance with fewer errors. The speed-accuracy tradeoff (SAT) principle states that as action speed increases, motor performance accuracy decreases. The current study investigated whether theta neurofeedback could improve both performance speed and performance accuracy, or would only enhance performance speed at the cost of reduced accuracy. A more complex task was used to study the effects of parietal elevated theta on 45 healthy volunteers The findings confirmed previous results on the effects of theta neurofeedback on memory consolidation. In contrast to the two control groups, in the theta-neurofeedback group the speed-accuracy tradeoff was reversed. The speed-accuracy tradeoff patterns only stabilized after a night's sleep implying enhancement in terms of both speed and accuracy. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Effect of recent popularity on heat-conduction based recommendation models

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Dong, Qiang; Shi, Yang-Bo; Fu, Yan; He, Jia-Lin

2017-05-01

Accuracy and diversity are two important measures in evaluating the performance of recommender systems. It has been demonstrated that the recommendation model inspired by the heat conduction process has high diversity yet low accuracy. Many variants have been introduced to improve the accuracy while keeping high diversity, most of which regard the current node-degree of an item as its popularity. However in this way, a few outdated items of large degree may be recommended to an enormous number of users. In this paper, we take the recent popularity (recently increased item degrees) into account in the heat-conduction based methods, and propose accordingly the improved recommendation models. Experimental results on two benchmark data sets show that the accuracy can be largely improved while keeping the high diversity compared with the original models.

Correlation of ground tests and analyses of a dynamically scaled Space Station model configuration

NASA Technical Reports Server (NTRS)

Javeed, Mehzad; Edighoffer, Harold H.; Mcgowan, Paul E.

1993-01-01

Verification of analytical models through correlation with ground test results of a complex space truss structure is demonstrated. A multi-component, dynamically scaled space station model configuration is the focus structure for this work. Previously established test/analysis correlation procedures are used to develop improved component analytical models. Integrated system analytical models, consisting of updated component analytical models, are compared with modal test results to establish the accuracy of system-level dynamic predictions. Design sensitivity model updating methods are shown to be effective for providing improved component analytical models. Also, the effects of component model accuracy and interface modeling fidelity on the accuracy of integrated model predictions is examined.

The neglected tool in the Bayesian ecologist's shed: a case study testing informative priors' effect on model accuracy

PubMed Central

Morris, William K; Vesk, Peter A; McCarthy, Michael A; Bunyavejchewin, Sarayudh; Baker, Patrick J

2015-01-01

Despite benefits for precision, ecologists rarely use informative priors. One reason that ecologists may prefer vague priors is the perception that informative priors reduce accuracy. To date, no ecological study has empirically evaluated data-derived informative priors' effects on precision and accuracy. To determine the impacts of priors, we evaluated mortality models for tree species using data from a forest dynamics plot in Thailand. Half the models used vague priors, and the remaining half had informative priors. We found precision was greater when using informative priors, but effects on accuracy were more variable. In some cases, prior information improved accuracy, while in others, it was reduced. On average, models with informative priors were no more or less accurate than models without. Our analyses provide a detailed case study on the simultaneous effect of prior information on precision and accuracy and demonstrate that when priors are specified appropriately, they lead to greater precision without systematically reducing model accuracy. PMID:25628867

The neglected tool in the Bayesian ecologist's shed: a case study testing informative priors' effect on model accuracy.

PubMed

Morris, William K; Vesk, Peter A; McCarthy, Michael A; Bunyavejchewin, Sarayudh; Baker, Patrick J

2015-01-01

Despite benefits for precision, ecologists rarely use informative priors. One reason that ecologists may prefer vague priors is the perception that informative priors reduce accuracy. To date, no ecological study has empirically evaluated data-derived informative priors' effects on precision and accuracy. To determine the impacts of priors, we evaluated mortality models for tree species using data from a forest dynamics plot in Thailand. Half the models used vague priors, and the remaining half had informative priors. We found precision was greater when using informative priors, but effects on accuracy were more variable. In some cases, prior information improved accuracy, while in others, it was reduced. On average, models with informative priors were no more or less accurate than models without. Our analyses provide a detailed case study on the simultaneous effect of prior information on precision and accuracy and demonstrate that when priors are specified appropriately, they lead to greater precision without systematically reducing model accuracy.

Training of perceptual-cognitive skills in offside decision making.

PubMed

Catteeuw, Peter; Gilis, Bart; Jaspers, Arne; Wagemans, Johan; Helsen, Werner

2010-12-01

This study investigates the effect of two off-field training formats to improve offside decision making. One group trained with video simulations and another with computer animations. Feedback after every offside situation allowed assistant referees to compensate for the consequences of the flash-lag effect and to improve their decision-making accuracy. First, response accuracy improved and flag errors decreased for both training groups implying that training interventions with feedback taught assistant referees to better deal with the flash-lag effect. Second, the results demonstrated no effect of format, although assistant referees rated video simulations higher for fidelity than computer animations. This implies that a cognitive correction to a perceptual effect can be learned also when the format does not correspond closely with the original perceptual situation. Off-field offside decision-making training should be considered as part of training because it is a considerable help to gain more experience and to improve overall decision-making performance.

Laser Spot Center Detection and Comparison Test

NASA Astrophysics Data System (ADS)

Zhu, Jun; Xu, Zhengjie; Fu, Deli; Hu, Cong

2018-04-01

High efficiency and precision of the pot center detection are the foundations of avionics instrument navigation and optics measurement basis for many applications. It has noticeable impact on overall system performance. Among them, laser spot detection is very important in the optical measurement technology. In order to improve the low accuracy of the spot center position, the algorithm is improved on the basis of the circle fitting. The pretreatment is used by circle fitting, and the improved adaptive denoising filter for TV repair technology can effectively improves the accuracy of the spot center position. At the same time, the pretreatment and de-noising can effectively reduce the influence of Gaussian white noise, which enhances the anti-jamming capability.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

PubMed

Ratcliffe, Blaise; El-Dien, Omnia Gamal; Cappa, Eduardo P; Porth, Ilga; Klápště, Jaroslav; Chen, Charles; El-Kassaby, Yousry A

2017-03-10

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce ( Picea glauca ) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm. Copyright © 2017 Ratcliffe et al.

Pediatric Disaster Triage: Multiple Simulation Curriculum Improves Prehospital Care Providers' Assessment Skills.

PubMed

Cicero, Mark Xavier; Whitfill, Travis; Overly, Frank; Baird, Janette; Walsh, Barbara; Yarzebski, Jorge; Riera, Antonio; Adelgais, Kathleen; Meckler, Garth D; Baum, Carl; Cone, David Christopher; Auerbach, Marc

2017-01-01

Paramedics and emergency medical technicians (EMTs) triage pediatric disaster victims infrequently. The objective of this study was to measure the effect of a multiple-patient, multiple-simulation curriculum on accuracy of pediatric disaster triage (PDT). Paramedics, paramedic students, and EMTs from three sites were enrolled. Triage accuracy was measured three times (Time 0, Time 1 [two weeks later], and Time 2 [6 months later]) during a disaster simulation, in which high and low fidelity manikins and actors portrayed 10 victims. Accuracy was determined by participant triage decision concordance with predetermined expected triage level (RED [Immediate], YELLOW [Delayed], GREEN [Ambulatory], BLACK [Deceased]) for each victim. Between Time 0 and Time 1, participants completed an interactive online module, and after each simulation there was an individual debriefing. Associations between participant level of training, years of experience, and enrollment site were determined, as were instances of the most dangerous mistriage, when RED and YELLOW victims were triaged BLACK. The study enrolled 331 participants, and the analysis included 261 (78.9%) participants who completed the study, 123 from the Connecticut site, 83 from Rhode Island, and 55 from Massachusetts. Triage accuracy improved significantly from Time 0 to Time 1, after the educational interventions (first simulation with debriefing, and an interactive online module), with a median 10% overall improvement (p < 0.001). Subgroup analyses showed between Time 0 and Time 1, paramedics and paramedic students improved more than EMTs (p = 0.002). Analysis of triage accuracy showed greatest improvement in overall accuracy for YELLOW triage patients (Time 0 50% accurate, Time1 100%), followed by RED patients (Time 0 80%, Time 1 100%). There was no significant difference in accuracy between Time 1 and Time 2 (p = 0.073). This study shows that the multiple-victim, multiple-simulation curriculum yields a durable 10% improvement in simulated triage accuracy. Future iterations of the curriculum can target greater improvements in EMT triage accuracy.

Utilizing a language model to improve online dynamic data collection in P300 spellers.

PubMed

Mainsah, Boyla O; Colwell, Kenneth A; Collins, Leslie M; Throckmorton, Chandra S

2014-07-01

P300 spellers provide a means of communication for individuals with severe physical limitations, especially those with locked-in syndrome, such as amyotrophic lateral sclerosis. However, P300 speller use is still limited by relatively low communication rates due to the multiple data measurements that are required to improve the signal-to-noise ratio of event-related potentials for increased accuracy. Therefore, the amount of data collection has competing effects on accuracy and spelling speed. Adaptively varying the amount of data collection prior to character selection has been shown to improve spelling accuracy and speed. The goal of this study was to optimize a previously developed dynamic stopping algorithm that uses a Bayesian approach to control data collection by incorporating a priori knowledge via a language model. Participants ( n = 17) completed online spelling tasks using the dynamic stopping algorithm, with and without a language model. The addition of the language model resulted in improved participant performance from a mean theoretical bit rate of 46.12 bits/min at 88.89% accuracy to 54.42 bits/min ( ) at 90.36% accuracy.

Effects of using the developing nurses' thinking model on nursing students' diagnostic accuracy.

PubMed

Tesoro, Mary Gay

2012-08-01

This quasi-experimental study tested the effectiveness of an educational model, Developing Nurses' Thinking (DNT), on nursing students' clinical reasoning to achieve patient safety. Teaching nursing students to develop effective thinking habits that promote positive patient outcomes and patient safety is a challenging endeavor. Positive patient outcomes and safety are achieved when nurses accurately interpret data and subsequently implement appropriate plans of care. This study's pretest-posttest design determined whether use of the DNT model during 2 weeks of clinical postconferences improved nursing students' (N = 83) diagnostic accuracy. The DNT model helps students to integrate four constructs-patient safety, domain knowledge, critical thinking processes, and repeated practice-to guide their thinking when interpreting patient data and developing effective plans of care. The posttest scores of students from the intervention group showed statistically significant improvement in accuracy. Copyright 2012, SLACK Incorporated.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Accuracy Improvement Capability of Advanced Projectile Based on Course Correction Fuze Concept

PubMed Central

Elsaadany, Ahmed; Wen-jun, Yi

2014-01-01

Improvement in terminal accuracy is an important objective for future artillery projectiles. Generally it is often associated with range extension. Various concepts and modifications are proposed to correct the range and drift of artillery projectile like course correction fuze. The course correction fuze concepts could provide an attractive and cost-effective solution for munitions accuracy improvement. In this paper, the trajectory correction has been obtained using two kinds of course correction modules, one is devoted to range correction (drag ring brake) and the second is devoted to drift correction (canard based-correction fuze). The course correction modules have been characterized by aerodynamic computations and flight dynamic investigations in order to analyze the effects on deflection of the projectile aerodynamic parameters. The simulation results show that the impact accuracy of a conventional projectile using these course correction modules can be improved. The drag ring brake is found to be highly capable for range correction. The deploying of the drag brake in early stage of trajectory results in large range correction. The correction occasion time can be predefined depending on required correction of range. On the other hand, the canard based-correction fuze is found to have a higher effect on the projectile drift by modifying its roll rate. In addition, the canard extension induces a high-frequency incidence angle as canards reciprocate at the roll motion. PMID:25097873

Accuracy improvement capability of advanced projectile based on course correction fuze concept.

PubMed

Elsaadany, Ahmed; Wen-jun, Yi

2014-01-01

Improvement in terminal accuracy is an important objective for future artillery projectiles. Generally it is often associated with range extension. Various concepts and modifications are proposed to correct the range and drift of artillery projectile like course correction fuze. The course correction fuze concepts could provide an attractive and cost-effective solution for munitions accuracy improvement. In this paper, the trajectory correction has been obtained using two kinds of course correction modules, one is devoted to range correction (drag ring brake) and the second is devoted to drift correction (canard based-correction fuze). The course correction modules have been characterized by aerodynamic computations and flight dynamic investigations in order to analyze the effects on deflection of the projectile aerodynamic parameters. The simulation results show that the impact accuracy of a conventional projectile using these course correction modules can be improved. The drag ring brake is found to be highly capable for range correction. The deploying of the drag brake in early stage of trajectory results in large range correction. The correction occasion time can be predefined depending on required correction of range. On the other hand, the canard based-correction fuze is found to have a higher effect on the projectile drift by modifying its roll rate. In addition, the canard extension induces a high-frequency incidence angle as canards reciprocate at the roll motion.

Slice profile and B1 corrections in 2D magnetic resonance fingerprinting.

PubMed

Ma, Dan; Coppo, Simone; Chen, Yong; McGivney, Debra F; Jiang, Yun; Pahwa, Shivani; Gulani, Vikas; Griswold, Mark A

2017-11-01

The goal of this study is to characterize and improve the accuracy of 2D magnetic resonance fingerprinting (MRF) scans in the presence of slice profile (SP) and B 1 imperfections, which are two main factors that affect quantitative results in MRF. The SP and B 1 imperfections are characterized and corrected separately. The SP effect is corrected by simulating the radiofrequency pulse in the dictionary, and the B 1 is corrected by acquiring a B 1 map using the Bloch-Siegert method before each scan. The accuracy, precision, and repeatability of the proposed method are evaluated in phantom studies. The effects of both SP and B 1 imperfections are also illustrated and corrected in the in vivo studies. The SP and B 1 corrections improve the accuracy of the T 1 and T 2 values, independent of the shape of the radiofrequency pulse. The T 1 and T 2 values obtained from different excitation patterns become more consistent after corrections, which leads to an improvement of the robustness of the MRF design. This study demonstrates that MRF is sensitive to both SP and B 1 effects, and that corrections can be made to improve the accuracy of MRF with only a 2-s increase in acquisition time. Magn Reson Med 78:1781-1789, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Modified compensation algorithm of lever-arm effect and flexural deformation for polar shipborne transfer alignment based on improved adaptive Kalman filter

NASA Astrophysics Data System (ADS)

Wang, Tongda; Cheng, Jianhua; Guan, Dongxue; Kang, Yingyao; Zhang, Wei

2017-09-01

Due to the lever-arm effect and flexural deformation in the practical application of transfer alignment (TA), the TA performance is decreased. The existing polar TA algorithm only compensates a fixed lever-arm without considering the dynamic lever-arm caused by flexural deformation; traditional non-polar TA algorithms also have some limitations. Thus, the performance of existing compensation algorithms is unsatisfactory. In this paper, a modified compensation algorithm of the lever-arm effect and flexural deformation is proposed to promote the accuracy and speed of the polar TA. On the basis of a dynamic lever-arm model and a noise compensation method for flexural deformation, polar TA equations are derived in grid frames. Based on the velocity-plus-attitude matching method, the filter models of polar TA are designed. An adaptive Kalman filter (AKF) is improved to promote the robustness and accuracy of the system, and then applied to the estimation of the misalignment angles. Simulation and experiment results have demonstrated that the modified compensation algorithm based on the improved AKF for polar TA can effectively compensate the lever-arm effect and flexural deformation, and then improve the accuracy and speed of TA in the polar region.

The Role of Incidental Unfocused Prompts and Recasts in Improving English as a Foreign Language Learners' Accuracy

ERIC Educational Resources Information Center

Rahimi, Muhammad; Zhang, Lawrence Jun

2016-01-01

This study was designed to investigate the effects of incidental unfocused prompts and recasts on improving English as a foreign language (EFL) learners' grammatical accuracy as measured in students' oral interviews and the Test of English as a Foreign Language (TOEFL) grammar test. The design of the study was quasi-experimental with pre-tests,…

The Effects of Direct Written Corrective Feedback on Improvement of Grammatical Accuracy of High-Proficient L2 Learners

ERIC Educational Resources Information Center

Farrokhi, Farahman; Sattarpour, Simin

2012-01-01

The present article reports the findings of a study that explored(1) whether direct written corrective feedback (CF) can help high-proficient L2 learners, who has already achieved a rather high level of accuracy in English, improve in the accurate use of two functions of English articles (the use of "a" for first mention and…

[Accuracy improvement of spectral classification of crop using microwave backscatter data].

PubMed

Jia, Kun; Li, Qiang-Zi; Tian, Yi-Chen; Wu, Bing-Fang; Zhang, Fei-Fei; Meng, Ji-Hua

2011-02-01

In the present study, VV polarization microwave backscatter data used for improving accuracies of spectral classification of crop is investigated. Classification accuracy using different classifiers based on the fusion data of HJ satellite multi-spectral and Envisat ASAR VV backscatter data are compared. The results indicate that fusion data can take full advantage of spectral information of HJ multi-spectral data and the structure sensitivity feature of ASAR VV polarization data. The fusion data enlarges the spectral difference among different classifications and improves crop classification accuracy. The classification accuracy using fusion data can be increased by 5 percent compared to the single HJ data. Furthermore, ASAR VV polarization data is sensitive to non-agrarian area of planted field, and VV polarization data joined classification can effectively distinguish the field border. VV polarization data associating with multi-spectral data used in crop classification enlarges the application of satellite data and has the potential of spread in the domain of agriculture.

Enhancing Visual Perception and Motor Accuracy among School Children through a Mindfulness and Compassion Program

PubMed Central

Tarrasch, Ricardo; Margalit-Shalom, Lilach; Berger, Rony

2017-01-01

The present study assessed the effects of the mindfulness/compassion cultivating program: “Call to Care-Israel” on the performance in visual perception (VP) and motor accuracy, as well as on anxiety levels and self-reported mindfulness among 4th and 5th grade students. One hundred and thirty-eight children participated in the program for 24 weekly sessions, while 78 children served as controls. Repeated measures ANOVA’s yielded significant interactions between time of measurement and group for VP, motor accuracy, reported mindfulness, and anxiety. Post hoc tests revealed significant improvements in the four aforementioned measures in the experimental group only. In addition, significant correlations were obtained between the improvement in motor accuracy and the reduction in anxiety and the increase in mindfulness. Since VP and motor accuracy are basic skills associated with quantifiable academic characteristics, such as reading and mathematical abilities, the results may suggest that mindfulness practice has the ability to improve academic achievements. PMID:28286492

Height Error Correction for the New SRTM Elevation Product

NASA Technical Reports Server (NTRS)

Neumann, Maxim; Simard, Marc; Buckley, Sean; Shimada, Joanne; Gurrola, Eric; Martin, Jan; Hensley, Scott; Rosen, Paul

2013-01-01

The Shuttle Radar Topography Mission (SRTM), carrying a single-pass interferometric synthetic aperture radar(SAR) instrument, collected a global elevation data set, which has been widely used in scientific, military and commercial communities. In the new proposed NASA SRTM reprocessing task, the SRTM elevation data is going to be processed at higher spatial resolution and with improved height accuracy. Upon completion, the improved SRTM product will be freely available. This paper describes the calibration approaches for reduction of elevation ripple effects and height accuracy improvements.

Effects of aniracetam on delayed matching-to-sample performance of monkeys and pigeons.

PubMed

Pontecorvo, M J; Evans, H L

1985-05-01

A 3-choice, variable-delay, matching-to-sample procedure was used to evaluate drugs in both pigeons and monkeys while tested under nearly-identical conditions. Aniracetam (Roche 13-5057) improved accuracy of matching at all retention intervals following oral administration (12.5, 25 and 50 mg/kg) to macaque monkeys, with a maximal effect at 25 mg/kg. Aniracetam also antagonized scopolamine-induced impairment of the monkey's performance. Intramuscular administration of these same doses of aniracetam produced a similar, but not significant trend toward improved matching accuracy in pigeons.

Advancing the state-of-the-art of the optical atomic clock

NASA Astrophysics Data System (ADS)

Ye, Jun

2014-05-01

The continued advance in laser phase coherence has permitted an improvement of the stability of optical lattice clocks by a factor of 10. This measurement precision has facilitated characterization of systematic effects, allowing us to improve the lattice clock accuracy by a factor of 20. The accuracy and stability of the JILA Sr clock now reach the 10-18 level. Owing to these advances, the lattice clock has also emerged as an effective laboratory to study many-body spin correlations. NIST, NSF, DARPA-QuASAR.

Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

NASA Astrophysics Data System (ADS)

Wang, Qijie

2015-08-01

The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

Region-confined restoration method for motion-blurred star image of the star sensor under dynamic conditions.

PubMed

Ma, Liheng; Bernelli-Zazzera, Franco; Jiang, Guangwen; Wang, Xingshu; Huang, Zongsheng; Qin, Shiqiao

2016-06-10

Under dynamic conditions, the centroiding accuracy of the motion-blurred star image decreases and the number of identified stars reduces, which leads to the degradation of the attitude accuracy of the star sensor. To improve the attitude accuracy, a region-confined restoration method, which concentrates on the noise removal and signal to noise ratio (SNR) improvement of the motion-blurred star images, is proposed for the star sensor under dynamic conditions. A multi-seed-region growing technique with the kinematic recursive model for star image motion is given to find the star image regions and to remove the noise. Subsequently, a restoration strategy is employed in the extracted regions, taking the time consumption and SNR improvement into consideration simultaneously. Simulation results indicate that the region-confined restoration method is effective in removing noise and improving the centroiding accuracy. The identification rate and the average number of identified stars in the experiments verify the advantages of the region-confined restoration method.

The Effect of Training on Accuracy of Angle Estimation.

ERIC Educational Resources Information Center

Waller, T. Gary; Wright, Robert H.

This report describes a study to determine the effect of training on accuracy in estimating angles. The study was part of a research program directed toward improving navigation techniques for low-level flight in Army aircraft and was made to assess the feasibility of visually estimating angles on a map in order to determine angles of drift.…

Assessing disease severity: accuracy and reliability of rater estimates in relation to number of diagrams in a standard area diagram set

USDA-ARS?s Scientific Manuscript database

Error in rater estimates of plant disease severity occur, and standard area diagrams (SADs) help improve accuracy and reliability. The effects of diagram number in a SAD set on accuracy and reliability is unknown. The objective of this study was to compare estimates of pecan scab severity made witho...

[Validation of an improved Demons deformable registration algorithm and its application in re-contouring in 4D-CT].

PubMed

Zhen, Xin; Zhou, Ling-hong; Lu, Wen-ting; Zhang, Shu-xu; Zhou, Lu

2010-12-01

To validate the efficiency and accuracy of an improved Demons deformable registration algorithm and evaluate its application in contour recontouring in 4D-CT. To increase the additional Demons force and reallocate the bilateral forces to accelerate convergent speed, we propose a novel energy function as the similarity measure, and utilize a BFGS method for optimization to avoid specifying the numbers of iteration. Mathematical transformed deformable CT images and home-made deformable phantom were used to validate the accuracy of the improved algorithm, and its effectiveness for contour recontouring was tested. The improved algorithm showed a relatively high registration accuracy and speed when compared with the classic Demons algorithm and optical flow based method. Visual inspection of the positions and shapes of the deformed contours agreed well with the physician-drawn contours. Deformable registration is a key technique in 4D-CT, and this improved Demons algorithm for contour recontouring can significantly reduce the workload of the physicians. The registration accuracy of this method proves to be sufficient for clinical needs.

Development and accuracy of a multipoint method for measuring visibility.

PubMed

Tai, Hongda; Zhuang, Zibo; Sun, Dongsong

2017-10-01

Accurate measurements of visibility are of great importance in many fields. This paper reports a multipoint visibility measurement (MVM) method to measure and calculate the atmospheric transmittance, extinction coefficient, and meteorological optical range (MOR). The relative errors of atmospheric transmittance and MOR measured by the MVM method and traditional transmissometer method are analyzed and compared. Experiments were conducted indoors, and the data were simultaneously processed. The results revealed that the MVM can effectively improve the accuracy under different visibility conditions. The greatest improvement of accuracy was 27%. The MVM can be used to calibrate and evaluate visibility meters.

Methods for recalibration of mass spectrometry data

DOEpatents

Tolmachev, Aleksey V [Richland, WA; Smith, Richard D [Richland, WA

2009-03-03

Disclosed are methods for recalibrating mass spectrometry data that provide improvement in both mass accuracy and precision by adjusting for experimental variance in parameters that have a substantial impact on mass measurement accuracy. Optimal coefficients are determined using correlated pairs of mass values compiled by matching sets of measured and putative mass values that minimize overall effective mass error and mass error spread. Coefficients are subsequently used to correct mass values for peaks detected in the measured dataset, providing recalibration thereof. Sub-ppm mass measurement accuracy has been demonstrated on a complex fungal proteome after recalibration, providing improved confidence for peptide identifications.

Central additive effect of Ginkgo biloba and Rhodiola rosea on psychomotor vigilance task and short-term working memory accuracy.

PubMed

Al-Kuraishy, Hayder M

2016-01-01

The present study investigates the effect of combined treatment with Ginkgo biloba and/or Rhodiola rosea on psychomotor vigilance task (PVT) and short-term working memory accuracy. A total number of 112 volunteers were enrolled to study the effect of G. biloba and R. rosea on PVT and short-term working memory accuracy as compared to placebo effects, the central cognitive effect was assessed by critical flicker-fusion frequency, PVT, and computerized N-back test. Placebo produced no significant effects on all neurocognitive tests measure P > 0.05 in normal healthy volunteers, G. biloba or R. rosea improve PVT and low to moderate working memory accuracy, The combined effect of R. rosea and G. biloba leading to more significant effect on PVT, all levels of short-term working memory accuracy and critical fusion versus flicker P < 0.01, more than of G. biloba or R. rosea when they used alone. The combined effect of R. rosea and G. biloba leading to a more significant effect on cognitive function than either G. biloba or R. rosea when they used alone.

Effects of a risk-based online mammography intervention on accuracy of perceived risk and mammography intentions.

PubMed

Seitz, Holli H; Gibson, Laura; Skubisz, Christine; Forquer, Heather; Mello, Susan; Schapira, Marilyn M; Armstrong, Katrina; Cappella, Joseph N

2016-10-01

This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions. 2918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (<1.5%; ≥1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) x 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk. Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk ≤1.5%. For women with a risk≤1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen. A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions. Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Effects of a Risk-based Online Mammography Intervention on Accuracy of Perceived Risk and Mammography Intentions

PubMed Central

Seitz, Holli H.; Gibson, Laura; Skubisz, Christine; Forquer, Heather; Mello, Susan; Schapira, Marilyn M.; Armstrong, Katrina; Cappella, Joseph N.

2016-01-01

Objective This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions. Methods 2,918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (< 1.5%; ≥ 1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) × 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk. Results Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk <1.5%. For women with a risk < 1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen. Conclusion A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions. Practice Implications Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions. PMID:27178707

Performance analysis of improved iterated cubature Kalman filter and its application to GNSS/INS.

PubMed

Cui, Bingbo; Chen, Xiyuan; Xu, Yuan; Huang, Haoqian; Liu, Xiao

2017-01-01

In order to improve the accuracy and robustness of GNSS/INS navigation system, an improved iterated cubature Kalman filter (IICKF) is proposed by considering the state-dependent noise and system uncertainty. First, a simplified framework of iterated Gaussian filter is derived by using damped Newton-Raphson algorithm and online noise estimator. Then the effect of state-dependent noise coming from iterated update is analyzed theoretically, and an augmented form of CKF algorithm is applied to improve the estimation accuracy. The performance of IICKF is verified by field test and numerical simulation, and results reveal that, compared with non-iterated filter, iterated filter is less sensitive to the system uncertainty, and IICKF improves the accuracy of yaw, roll and pitch by 48.9%, 73.1% and 83.3%, respectively, compared with traditional iterated KF. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fourier analysis for hydrostatic pressure sensing in a polarization-maintaining photonic crystal fiber.

PubMed

Childs, Paul; Wong, Allan C L; Fu, H Y; Liao, Yanbiao; Tam, Hwayaw; Lu, Chao; Wai, P K A

2010-12-20

We measured the hydrostatic pressure dependence of the birefringence and birefringent dispersion of a Sagnac interferometric sensor incorporating a length of highly birefringent photonic crystal fiber using Fourier analysis. Sensitivity of both the phase and chirp spectra to hydrostatic pressure is demonstrated. Using this analysis, phase-based measurements showed a good linearity with an effective sensitivity of 9.45 nm/MPa and an accuracy of ±7.8 kPa using wavelength-encoded data and an effective sensitivity of -55.7 cm(-1)/MPa and an accuracy of ±4.4 kPa using wavenumber-encoded data. Chirp-based measurements, though nonlinear in response, showed an improvement in accuracy at certain pressure ranges with an accuracy of ±5.5 kPa for the full range of measured pressures using wavelength-encoded data and dropping to within ±2.5 kPa in the range of 0.17 to 0.4 MPa using wavenumber-encoded data. Improvements of the accuracy demonstrated the usefulness of implementing chirp-based analysis for sensing purposes.

Improved atmospheric effect elimination method for the roughness estimation of painted surfaces.

PubMed

Zhang, Ying; Xuan, Jiabin; Zhao, Huijie; Song, Ping; Zhang, Yi; Xu, Wujian

2018-03-01

We propose a method for eliminating the atmospheric effect in polarimetric imaging remote sensing by using polarimetric imagers to simultaneously detect ground targets and skylight, which does not need calibrated targets. In addition, calculation efficiencies are improved by the skylight division method without losing estimation accuracy. Outdoor experiments are performed to obtain the polarimetric bidirectional reflectance distribution functions of painted surfaces and skylight under different weather conditions. Finally, the roughness of the painted surfaces is estimated. We find that the estimation accuracy with the proposed method is 6% on cloudy weather, while it is 30.72% without atmospheric effect elimination.

A Final Approach Trajectory Model for Current Operations

NASA Technical Reports Server (NTRS)

Gong, Chester; Sadovsky, Alexander

2010-01-01

Predicting accurate trajectories with limited intent information is a challenge faced by air traffic management decision support tools in operation today. One such tool is the FAA's Terminal Proximity Alert system which is intended to assist controllers in maintaining safe separation of arrival aircraft during final approach. In an effort to improve the performance of such tools, two final approach trajectory models are proposed; one based on polynomial interpolation, the other on the Fourier transform. These models were tested against actual traffic data and used to study effects of the key final approach trajectory modeling parameters of wind, aircraft type, and weight class, on trajectory prediction accuracy. Using only the limited intent data available to today's ATM system, both the polynomial interpolation and Fourier transform models showed improved trajectory prediction accuracy over a baseline dead reckoning model. Analysis of actual arrival traffic showed that this improved trajectory prediction accuracy leads to improved inter-arrival separation prediction accuracy for longer look ahead times. The difference in mean inter-arrival separation prediction error between the Fourier transform and dead reckoning models was 0.2 nmi for a look ahead time of 120 sec, a 33 percent improvement, with a corresponding 32 percent improvement in standard deviation.

The Effects of Gesture Use on Young Children's Pitch Accuracy for Singing Tonal Patterns

ERIC Educational Resources Information Center

Liao, Mei-Ying

2008-01-01

The main purpose of this study was to examine the effects of gesture use on young children's singing with regard to improving pitch accuracy. The second purpose was to examine the differences in gesture use among boys and girls and different melodic motions. Eighty Taiwanese young children, five to six years old, participated in this experiment.…

FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

PubMed

Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

2016-07-12

In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

Accuracy of active chirp linearization for broadband frequency modulated continuous wave ladar.

PubMed

Barber, Zeb W; Babbitt, Wm Randall; Kaylor, Brant; Reibel, Randy R; Roos, Peter A

2010-01-10

As the bandwidth and linearity of frequency modulated continuous wave chirp ladar increase, the resulting range resolution, precisions, and accuracy are improved correspondingly. An analysis of a very broadband (several THz) and linear (<1 ppm) chirped ladar system based on active chirp linearization is presented. Residual chirp nonlinearity and material dispersion are analyzed as to their effect on the dynamic range, precision, and accuracy of the system. Measurement precision and accuracy approaching the part per billion level is predicted.

Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter

PubMed Central

Han, Houzeng; Xu, Tianhe; Wang, Jian

2016-01-01

Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height component are improved by 30.36%, 16.95% and 24.07% for three different convergence times, i.e., 60, 50 and 30 min, respectively. It shows that the ambiguity-fixed horizontal positioning accuracy has been significantly improved. When compared with the conventional PPP solution, it can be seen that position accuracies are improved by 19.51%, 61.11% and 23.53% for the north, east and height components, respectively, after one hour convergence through the troposphere constraint fixed PPP/INS with adaptive covariance model. PMID:27399721

The effects of L-theanine, caffeine and their combination on cognition and mood.

PubMed

Haskell, Crystal F; Kennedy, David O; Milne, Anthea L; Wesnes, Keith A; Scholey, Andrew B

2008-02-01

L-Theanine is an amino acid found naturally in tea. Despite the common consumption of L-theanine, predominantly in combination with caffeine in the form of tea, only one study to date has examined the cognitive effects of this substance alone, and none have examined its effects when combined with caffeine. The present randomised, placebo-controlled, double-blind, balanced crossover study investigated the acute cognitive and mood effects of L-theanine (250 mg), and caffeine (150 mg), in isolation and in combination. Salivary caffeine levels were co-monitored. L-Theanine increased 'headache' ratings and decreased correct serial seven subtractions. Caffeine led to faster digit vigilance reaction time, improved Rapid Visual Information Processing (RVIP) accuracy and attenuated increases in self-reported 'mental fatigue'. In addition to improving RVIP accuracy and 'mental fatigue' ratings, the combination also led to faster simple reaction time, faster numeric working memory reaction time and improved sentence verification accuracy. 'Headache' and 'tired' ratings were reduced and 'alert' ratings increased. There was also a significant positive caffeine x L-theanine interaction on delayed word recognition reaction time. These results suggest that beverages containing L-theanine and caffeine may have a different pharmacological profile to those containing caffeine alone.

A stereo remote sensing feature selection method based on artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

2014-05-01

To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea

NASA Astrophysics Data System (ADS)

Kim, M. S.; Onda, Y.; Kim, J. K.

2015-01-01

SHALSTAB model applied to shallow landslides induced by rainfall to evaluate soil properties related with the effect of soil depth for a granite area in Jinbu region, Republic of Korea. Soil depth measured by a knocking pole test and two soil parameters from direct shear test (a and b) as well as one soil parameters from a triaxial compression test (c) were collected to determine the input parameters for the model. Experimental soil data were used for the first simulation (Case I) and, soil data represented the effect of measured soil depth and average soil depth from soil data of Case I were used in the second (Case II) and third simulations (Case III), respectively. All simulations were analysed using receiver operating characteristic (ROC) analysis to determine the accuracy of prediction. ROC analysis results for first simulation showed the low ROC values under 0.75 may be due to the internal friction angle and particularly the cohesion value. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. The accuracy of Case II and Case III using ROC analysis showed higher accuracy values rather than first simulation. Our results clearly demonstrate that the accuracy of shallow landslide prediction can be improved when soil parameters represented the effect of soil thickness.

Performance Evaluation and Analysis for Gravity Matching Aided Navigation.

PubMed

Wu, Lin; Wang, Hubiao; Chai, Hua; Zhang, Lu; Hsu, Houtse; Wang, Yong

2017-04-05

Simulation tests were accomplished in this paper to evaluate the performance of gravity matching aided navigation (GMAN). Four essential factors were focused in this study to quantitatively evaluate the performance: gravity database (DB) resolution, fitting degree of gravity measurements, number of samples in matching, and gravity changes in the matching area. Marine gravity anomaly DB derived from satellite altimetry was employed. Actual dynamic gravimetry accuracy and operating conditions were referenced to design the simulation parameters. The results verified that the improvement of DB resolution, gravimetry accuracy, number of measurement samples, or gravity changes in the matching area generally led to higher positioning accuracies, while the effects of them were different and interrelated. Moreover, three typical positioning accuracy targets of GMAN were proposed, and the conditions to achieve these targets were concluded based on the analysis of several different system requirements. Finally, various approaches were provided to improve the positioning accuracy of GMAN.

Performance Evaluation and Analysis for Gravity Matching Aided Navigation

PubMed Central

Wu, Lin; Wang, Hubiao; Chai, Hua; Zhang, Lu; Hsu, Houtse; Wang, Yong

2017-01-01

Simulation tests were accomplished in this paper to evaluate the performance of gravity matching aided navigation (GMAN). Four essential factors were focused in this study to quantitatively evaluate the performance: gravity database (DB) resolution, fitting degree of gravity measurements, number of samples in matching, and gravity changes in the matching area. Marine gravity anomaly DB derived from satellite altimetry was employed. Actual dynamic gravimetry accuracy and operating conditions were referenced to design the simulation parameters. The results verified that the improvement of DB resolution, gravimetry accuracy, number of measurement samples, or gravity changes in the matching area generally led to higher positioning accuracies, while the effects of them were different and interrelated. Moreover, three typical positioning accuracy targets of GMAN were proposed, and the conditions to achieve these targets were concluded based on the analysis of several different system requirements. Finally, various approaches were provided to improve the positioning accuracy of GMAN. PMID:28379178

Multispectral Image Compression for Improvement of Colorimetric and Spectral Reproducibility by Nonlinear Spectral Transform

NASA Astrophysics Data System (ADS)

Yu, Shanshan; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

2006-09-01

The article proposes a multispectral image compression scheme using nonlinear spectral transform for better colorimetric and spectral reproducibility. In the method, we show the reduction of colorimetric error under a defined viewing illuminant and also that spectral accuracy can be improved simultaneously using a nonlinear spectral transform called Labplus, which takes into account the nonlinearity of human color vision. Moreover, we show that the addition of diagonal matrices to Labplus can further preserve the spectral accuracy and has a generalized effect of improving the colorimetric accuracy under other viewing illuminants than the defined one. Finally, we discuss the usage of the first-order Markov model to form the analysis vectors for the higher order channels in Labplus to reduce the computational complexity. We implement a multispectral image compression system that integrates Labplus with JPEG2000 for high colorimetric and spectral reproducibility. Experimental results for a 16-band multispectral image show the effectiveness of the proposed scheme.

Diagnostic accuracy of routine blood examinations and CSF lactate level for post-neurosurgical bacterial meningitis.

PubMed

Zhang, Yang; Xiao, Xiong; Zhang, Junting; Gao, Zhixian; Ji, Nan; Zhang, Liwei

2017-06-01

To evaluate the diagnostic accuracy of routine blood examinations and Cerebrospinal Fluid (CSF) lactate level for Post-neurosurgical Bacterial Meningitis (PBM) at a large sample-size of post-neurosurgical patients. The diagnostic accuracies of routine blood examinations and CSF lactate level to distinguish between PAM and PBM were evaluated with the values of the Area Under the Curve of the Receiver Operating Characteristic (AUC -ROC ) by retrospectively analyzing the datasets of post-neurosurgical patients in the clinical information databases. The diagnostic accuracy of routine blood examinations was relatively low (AUC -ROC <0.7). The CSF lactate level achieved rather high diagnostic accuracy (AUC -ROC =0.891; CI 95%, 0.852-0.922). The variables of patient age, operation duration, surgical diagnosis and postoperative days (the interval days between the neurosurgery and examinations) were shown to affect the diagnostic accuracy of these examinations. The variables were integrated with routine blood examinations and CSF lactate level by Fisher discriminant analysis to improve their diagnostic accuracy. As a result, the diagnostic accuracy of blood examinations and CSF lactate level was significantly improved with an AUC -ROC value=0.760 (CI 95%, 0.737-0.782) and 0.921 (CI 95%, 0.887-0.948) respectively. The PBM diagnostic accuracy of routine blood examinations was relatively low, whereas the accuracy of CSF lactate level was high. Some variables that are involved in the incidence of PBM can also affect the diagnostic accuracy for PBM. Taking into account the effects of these variables significantly improves the diagnostic accuracies of routine blood examinations and CSF lactate level. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

Merits of using color and shape differentiation to improve the speed and accuracy of drug strength identification on over-the-counter medicines by laypeople.

PubMed

Hellier, Elizabeth; Tucker, Mike; Kenny, Natalie; Rowntree, Anna; Edworthy, Judy

2010-09-01

This study aimed to examine the utility of using color and shape to differentiate drug strength information on over-the-counter medicine packages. Medication errors are an important threat to patient safety, and confusions between drug strengths are a significant source of medication error. A visual search paradigm required laypeople to search for medicine packages of a particular strength from among distracter packages of different strengths, and measures of reaction time and error were recorded. Using color to differentiate drug strength information conferred an advantage on search times and accuracy. Shape differentiation did not improve search times and had only a weak effect on search accuracy. Using color to differentiate drug strength information improves drug strength identification performance. Color differentiation of drug strength information may be a useful way of reducing medication errors and improving patient safety.

Existing methods for improving the accuracy of digital-to-analog converters

NASA Astrophysics Data System (ADS)

Eielsen, Arnfinn A.; Fleming, Andrew J.

2017-09-01

The performance of digital-to-analog converters is principally limited by errors in the output voltage levels. Such errors are known as element mismatch and are quantified by the integral non-linearity. Element mismatch limits the achievable accuracy and resolution in high-precision applications as it causes gain and offset errors, as well as harmonic distortion. In this article, five existing methods for mitigating the effects of element mismatch are compared: physical level calibration, dynamic element matching, noise-shaping with digital calibration, large periodic high-frequency dithering, and large stochastic high-pass dithering. These methods are suitable for improving accuracy when using digital-to-analog converters that use multiple discrete output levels to reconstruct time-varying signals. The methods improve linearity and therefore reduce harmonic distortion and can be retrofitted to existing systems with minor hardware variations. The performance of each method is compared theoretically and confirmed by simulations and experiments. Experimental results demonstrate that three of the five methods provide significant improvements in the resolution and accuracy when applied to a general-purpose digital-to-analog converter. As such, these methods can directly improve performance in a wide range of applications including nanopositioning, metrology, and optics.

Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

NASA Astrophysics Data System (ADS)

Xu, Ru; Zhang, Hongsheng; Wang, Ting; Lin, Hui

2017-05-01

Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

Improvement of attention with amphetamine in low- and high-performing rats.

PubMed

Turner, Karly M; Burne, Thomas H J

2016-09-01

Attentional deficits occur in a range of neuropsychiatric disorders, such as schizophrenia and attention deficit hyperactivity disorder. Psychostimulants are one of the main treatments for attentional deficits, yet there are limited reports of procognitive effects of amphetamine in preclinical studies. Therefore, task development may be needed to improve predictive validity when measuring attention in rodents. This study aimed to use a modified signal detection task (SDT) to determine if and at what doses amphetamine could improve attention in rats. Sprague-Dawley rats were trained on the SDT prior to amphetamine challenge (0.1, 0.25, 0.75 and 1.25 mg/kg). This dose range was predicted to enhance and disrupt cognition with the effect differing between individuals depending on baseline performance. Acute low dose amphetamine (0.1 and 0.25 mg/kg) improved accuracy, while the highest dose (1.25 mg/kg) significantly disrupted performance. The effects differed for low- and high-performing groups across these doses. The effect of amphetamine on accuracy was found to significantly correlate with baseline performance in rats. This study demonstrates that improvement in attentional performance with systemic amphetamine is dependent on baseline accuracy in rats. Indicative of the inverted U-shaped relationship between dopamine and cognition, there was a baseline-dependent shift in performance with increasing doses of amphetamine. The SDT may be a useful tool for investigating individual differences in attention and response to psychostimulants in rodents.

Application of Numerical Integration and Data Fusion in Unit Vector Method

NASA Astrophysics Data System (ADS)

Zhang, J.

2012-01-01

The Unit Vector Method (UVM) is a series of orbit determination methods which are designed by Purple Mountain Observatory (PMO) and have been applied extensively. It gets the conditional equations for different kinds of data by projecting the basic equation to different unit vectors, and it suits for weighted process for different kinds of data. The high-precision data can play a major role in orbit determination, and accuracy of orbit determination is improved obviously. The improved UVM (PUVM2) promoted the UVM from initial orbit determination to orbit improvement, and unified the initial orbit determination and orbit improvement dynamically. The precision and efficiency are improved further. In this thesis, further research work has been done based on the UVM: Firstly, for the improvement of methods and techniques for observation, the types and decision of the observational data are improved substantially, it is also asked to improve the decision of orbit determination. The analytical perturbation can not meet the requirement. So, the numerical integration for calculating the perturbation has been introduced into the UVM. The accuracy of dynamical model suits for the accuracy of the real data, and the condition equations of UVM are modified accordingly. The accuracy of orbit determination is improved further. Secondly, data fusion method has been introduced into the UVM. The convergence mechanism and the defect of weighted strategy have been made clear in original UVM. The problem has been solved in this method, the calculation of approximate state transition matrix is simplified and the weighted strategy has been improved for the data with different dimension and different precision. Results of orbit determination of simulation and real data show that the work of this thesis is effective: (1) After the numerical integration has been introduced into the UVM, the accuracy of orbit determination is improved obviously, and it suits for the high-accuracy data of available observation apparatus. Compare with the classical differential improvement with the numerical integration, its calculation speed is also improved obviously. (2) After data fusion method has been introduced into the UVM, weighted distribution accords rationally with the accuracy of different kinds of data, all data are fully used and the new method is also good at numerical stability and rational weighted distribution.

Improvement of Accuracy for Background Noise Estimation Method Based on TPE-AE

NASA Astrophysics Data System (ADS)

Itai, Akitoshi; Yasukawa, Hiroshi

This paper proposes a method of a background noise estimation based on the tensor product expansion with a median and a Monte carlo simulation. We have shown that a tensor product expansion with absolute error method is effective to estimate a background noise, however, a background noise might not be estimated by using conventional method properly. In this paper, it is shown that the estimate accuracy can be improved by using proposed methods.

Accuracy optimization with wavelength tunability in overlay imaging technology

NASA Astrophysics Data System (ADS)

Lee, Honggoo; Kang, Yoonshik; Han, Sangjoon; Shim, Kyuchan; Hong, Minhyung; Kim, Seungyoung; Lee, Jieun; Lee, Dongyoung; Oh, Eungryong; Choi, Ahlin; Kim, Youngsik; Marciano, Tal; Klein, Dana; Hajaj, Eitan M.; Aharon, Sharon; Ben-Dov, Guy; Lilach, Saltoun; Serero, Dan; Golotsvan, Anna

2018-03-01

As semiconductor manufacturing technology progresses and the dimensions of integrated circuit elements shrink, overlay budget is accordingly being reduced. Overlay budget closely approaches the scale of measurement inaccuracies due to both optical imperfections of the measurement system and the interaction of light with geometrical asymmetries of the measured targets. Measurement inaccuracies can no longer be ignored due to their significant effect on the resulting device yield. In this paper we investigate a new approach for imaging based overlay (IBO) measurements by optimizing accuracy rather than contrast precision, including its effect over the total target performance, using wavelength tunable overlay imaging metrology. We present new accuracy metrics based on theoretical development and present their quality in identifying the measurement accuracy when compared to CD-SEM overlay measurements. The paper presents the theoretical considerations and simulation work, as well as measurement data, for which tunability combined with the new accuracy metrics is shown to improve accuracy performance.

The uncertainty of crop yield projections is reduced by improved temperature response functions

USDA-ARS?s Scientific Manuscript database

Increasing the accuracy of crop productivity estimates is a key Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on cr...

The Meta-Analysis of Clinical Judgment Project: Effects of Experience on Judgment Accuracy

ERIC Educational Resources Information Center

Spengler, Paul M.; White, Michael J.; Aegisdottir, Stefania; Maugherman, Alan S.; Anderson, Linda A.; Cook, Robert S.; Nichols, Cassandra N.; Lampropoulos, Georgios K.; Walker, Blain S.; Cohen, Genna R.; Rush, Jeffrey D.

2009-01-01

Clinical and educational experience is one of the most commonly studied variables in clinical judgment research. Contrary to clinicians' perceptions, clinical judgment researchers have generally concluded that accuracy does not improve with increased education, training, or clinical experience. In this meta-analysis, the authors synthesized…

Correcting Memory Improves Accuracy of Predicted Task Duration

ERIC Educational Resources Information Center

Roy, Michael M.; Mitten, Scott T.; Christenfeld, Nicholas J. S.

2008-01-01

People are often inaccurate in predicting task duration. The memory bias explanation holds that this error is due to people having incorrect memories of how long previous tasks have taken, and these biased memories cause biased predictions. Therefore, the authors examined the effect on increasing predictive accuracy of correcting memory through…

Double-Windows-Based Motion Recognition in Multi-Floor Buildings Assisted by a Built-In Barometer.

PubMed

Liu, Maolin; Li, Huaiyu; Wang, Yuan; Li, Fei; Chen, Xiuwan

2018-04-01

Accelerometers, gyroscopes and magnetometers in smartphones are often used to recognize human motions. Since it is difficult to distinguish between vertical motions and horizontal motions in the data provided by these built-in sensors, the vertical motion recognition accuracy is relatively low. The emergence of a built-in barometer in smartphones improves the accuracy of motion recognition in the vertical direction. However, there is a lack of quantitative analysis and modelling of the barometer signals, which is the basis of barometer's application to motion recognition, and a problem of imbalanced data also exists. This work focuses on using the barometers inside smartphones for vertical motion recognition in multi-floor buildings through modelling and feature extraction of pressure signals. A novel double-windows pressure feature extraction method, which adopts two sliding time windows of different length, is proposed to balance recognition accuracy and response time. Then, a random forest classifier correlation rule is further designed to weaken the impact of imbalanced data on recognition accuracy. The results demonstrate that the recognition accuracy can reach 95.05% when pressure features and the improved random forest classifier are adopted. Specifically, the recognition accuracy of the stair and elevator motions is significantly improved with enhanced response time. The proposed approach proves effective and accurate, providing a robust strategy for increasing accuracy of vertical motions.

Improved wavelet de-noising method of rail vibration signal for wheel tread detection

NASA Astrophysics Data System (ADS)

Zhao, Quan-ke; Zhao, Quanke; Gao, Xiao-rong; Luo, Lin

2011-12-01

The irregularities of wheel tread can be detected by processing acceleration vibration signal of railway. Various kinds of noise from different sources such as wheel-rail resonance, bad weather and artificial reasons are the key factors influencing detection accuracy. A method which uses wavelet threshold de-noising is investigated to reduce noise in the detection signal, and an improved signal processing algorithm based on it has been established. The results of simulations and field experiments show that the proposed method can increase signal-to-noise ratio (SNR) of the rail vibration signal effectively, and improve the detection accuracy.

Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

PubMed

Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

2015-12-01

Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

Effect of Piracetam on Dyslexic's Reading Ability.

ERIC Educational Resources Information Center

Wilsher, C.; And Others

1985-01-01

Forty-six dyslexic boys (aged eight to 13) were administered Piracetam or placebo in a double-blind, parallel experiment. Although, overall, there were no significant group effects, the within-subject design revealed improvements in reading speed and accuracy in Piracetam Ss. Dyslexics with higher reading ages improved significantly compared to…

The effect of finite field size on classification and atmospheric correction

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Fraser, R. S.

1981-01-01

The atmospheric effect on the upward radiance of sunlight scattered from the Earth-atmosphere system is strongly influenced by the contrasts between fields and their sizes. For a given atmospheric turbidity, the atmospheric effect on classification of surface features is much stronger for nonuniform surfaces than for uniform surfaces. Therefore, the classification accuracy of agricultural fields and urban areas is dependent not only on the optical characteristics of the atmosphere, but also on the size of the surface do not account for the nonuniformity of the surface have only a slight effect on the classification accuracy; in other cases the classification accuracy descreases. The radiances above finite fields were computed to simulate radiances measured by a satellite. A simulation case including 11 agricultural fields and four natural fields (water, soil, savanah, and forest) was used to test the effect of the size of the background reflectance and the optical thickness of the atmosphere on classification accuracy. It is concluded that new atmospheric correction methods, which take into account the finite size of the fields, have to be developed to improve significantly the classification accuracy.

Improving decision speed, accuracy and group cohesion through early information gathering in house-hunting ants.

PubMed

Stroeymeyt, Nathalie; Giurfa, Martin; Franks, Nigel R

2010-09-29

Successful collective decision-making depends on groups of animals being able to make accurate choices while maintaining group cohesion. However, increasing accuracy and/or cohesion usually decreases decision speed and vice-versa. Such trade-offs are widespread in animal decision-making and result in various decision-making strategies that emphasize either speed or accuracy, depending on the context. Speed-accuracy trade-offs have been the object of many theoretical investigations, but these studies did not consider the possible effects of previous experience and/or knowledge of individuals on such trade-offs. In this study, we investigated how previous knowledge of their environment may affect emigration speed, nest choice and colony cohesion in emigrations of the house-hunting ant Temnothorax albipennis, a collective decision-making process subject to a classical speed-accuracy trade-off. Colonies allowed to explore a high quality nest site for one week before they were forced to emigrate found that nest and accepted it faster than emigrating naïve colonies. This resulted in increased speed in single choice emigrations and higher colony cohesion in binary choice emigrations. Additionally, colonies allowed to explore both high and low quality nest sites for one week prior to emigration remained more cohesive, made more accurate decisions and emigrated faster than emigrating naïve colonies. These results show that colonies gather and store information about available nest sites while their nest is still intact, and later retrieve and use this information when they need to emigrate. This improves colony performance. Early gathering of information for later use is therefore an effective strategy allowing T. albipennis colonies to improve simultaneously all aspects of the decision-making process--i.e. speed, accuracy and cohesion--and partly circumvent the speed-accuracy trade-off classically observed during emigrations. These findings should be taken into account in future studies on speed-accuracy trade-offs.

Different Orthographies Different Context Effects: The Effects of Arabic Sentence Context in Skilled and Poor Readers.

ERIC Educational Resources Information Center

Rabia, Salim Abu; Siegel, Linda S.

1995-01-01

Investigates whether Arabic orthography differs from an alphabetic orthography regarding context effects among poor and skilled readers. Finds that skilled as well as poor readers significantly improved their reading accuracy when they read voweled and unvoweled words in context and that skilled readers significantly improved their reading voweled…

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

Improved hybrid information filtering based on limited time window

NASA Astrophysics Data System (ADS)

Song, Wen-Jun; Guo, Qiang; Liu, Jian-Guo

2014-12-01

Adopting the entire collecting information of users, the hybrid information filtering of heat conduction and mass diffusion (HHM) (Zhou et al., 2010) was successfully proposed to solve the apparent diversity-accuracy dilemma. Since the recent behaviors are more effective to capture the users' potential interests, we present an improved hybrid information filtering of adopting the partial recent information. We expand the time window to generate a series of training sets, each of which is treated as known information to predict the future links proven by the testing set. The experimental results on one benchmark dataset Netflix indicate that by only using approximately 31% recent rating records, the accuracy could be improved by an average of 4.22% and the diversity could be improved by 13.74%. In addition, the performance on the dataset MovieLens could be preserved by considering approximately 60% recent records. Furthermore, we find that the improved algorithm is effective to solve the cold-start problem. This work could improve the information filtering performance and shorten the computational time.

A study on low-cost, high-accuracy, and real-time stereo vision algorithms for UAV power line inspection

NASA Astrophysics Data System (ADS)

Wang, Hongyu; Zhang, Baomin; Zhao, Xun; Li, Cong; Lu, Cunyue

2018-04-01

Conventional stereo vision algorithms suffer from high levels of hardware resource utilization due to algorithm complexity, or poor levels of accuracy caused by inadequacies in the matching algorithm. To address these issues, we have proposed a stereo range-finding technique that produces an excellent balance between cost, matching accuracy and real-time performance, for power line inspection using UAV. This was achieved through the introduction of a special image preprocessing algorithm and a weighted local stereo matching algorithm, as well as the design of a corresponding hardware architecture. Stereo vision systems based on this technique have a lower level of resource usage and also a higher level of matching accuracy following hardware acceleration. To validate the effectiveness of our technique, a stereo vision system based on our improved algorithms were implemented using the Spartan 6 FPGA. In comparative experiments, it was shown that the system using the improved algorithms outperformed the system based on the unimproved algorithms, in terms of resource utilization and matching accuracy. In particular, Block RAM usage was reduced by 19%, and the improved system was also able to output range-finding data in real time.

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Slojkowski, Steven; Lowe, Jonathan; Woodburn, James

2015-01-01

Orbit determination (OD) analysis results are presented for the Lunar Reconnaissance Orbiter (LRO) using a commercially available Extended Kalman Filter, Analytical Graphics' Orbit Determination Tool Kit (ODTK). Process noise models for lunar gravity and solar radiation pressure (SRP) are described and OD results employing the models are presented. Definitive accuracy using ODTK meets mission requirements and is better than that achieved using the operational LRO OD tool, the Goddard Trajectory Determination System (GTDS). Results demonstrate that a Vasicek stochastic model produces better estimates of the coefficient of solar radiation pressure than a Gauss-Markov model, and prediction accuracy using a Vasicek model meets mission requirements over the analysis span. Modeling the effect of antenna motion on range-rate tracking considerably improves residuals and filter-smoother consistency. Inclusion of off-axis SRP process noise and generalized process noise improves filter performance for both definitive and predicted accuracy. Definitive accuracy from the smoother is better than achieved using GTDS and is close to that achieved by precision OD methods used to generate definitive science orbits. Use of a multi-plate dynamic spacecraft area model with ODTK's force model plugin capability provides additional improvements in predicted accuracy.

Do knowledge, knowledge sources and reasoning skills affect the accuracy of nursing diagnoses? a randomised study.

PubMed

Paans, Wolter; Sermeus, Walter; Nieweg, Roos Mb; Krijnen, Wim P; van der Schans, Cees P

2012-08-01

This paper reports a study about the effect of knowledge sources, such as handbooks, an assessment format and a predefined record structure for diagnostic documentation, as well as the influence of knowledge, disposition toward critical thinking and reasoning skills, on the accuracy of nursing diagnoses.Knowledge sources can support nurses in deriving diagnoses. A nurse's disposition toward critical thinking and reasoning skills is also thought to influence the accuracy of his or her nursing diagnoses. A randomised factorial design was used in 2008-2009 to determine the effect of knowledge sources. We used the following instruments to assess the influence of ready knowledge, disposition, and reasoning skills on the accuracy of diagnoses: (1) a knowledge inventory, (2) the California Critical Thinking Disposition Inventory, and (3) the Health Science Reasoning Test. Nurses (n = 249) were randomly assigned to one of four factorial groups, and were instructed to derive diagnoses based on an assessment interview with a simulated patient/actor. The use of a predefined record structure resulted in a significantly higher accuracy of nursing diagnoses. A regression analysis reveals that almost half of the variance in the accuracy of diagnoses is explained by the use of a predefined record structure, a nurse's age and the reasoning skills of `deduction' and `analysis'. Improving nurses' dispositions toward critical thinking and reasoning skills, and the use of a predefined record structure, improves accuracy of nursing diagnoses.

Do knowledge, knowledge sources and reasoning skills affect the accuracy of nursing diagnoses? a randomised study

PubMed Central

2012-01-01

Background This paper reports a study about the effect of knowledge sources, such as handbooks, an assessment format and a predefined record structure for diagnostic documentation, as well as the influence of knowledge, disposition toward critical thinking and reasoning skills, on the accuracy of nursing diagnoses. Knowledge sources can support nurses in deriving diagnoses. A nurse’s disposition toward critical thinking and reasoning skills is also thought to influence the accuracy of his or her nursing diagnoses. Method A randomised factorial design was used in 2008–2009 to determine the effect of knowledge sources. We used the following instruments to assess the influence of ready knowledge, disposition, and reasoning skills on the accuracy of diagnoses: (1) a knowledge inventory, (2) the California Critical Thinking Disposition Inventory, and (3) the Health Science Reasoning Test. Nurses (n = 249) were randomly assigned to one of four factorial groups, and were instructed to derive diagnoses based on an assessment interview with a simulated patient/actor. Results The use of a predefined record structure resulted in a significantly higher accuracy of nursing diagnoses. A regression analysis reveals that almost half of the variance in the accuracy of diagnoses is explained by the use of a predefined record structure, a nurse’s age and the reasoning skills of `deduction’ and `analysis’. Conclusions Improving nurses’ dispositions toward critical thinking and reasoning skills, and the use of a predefined record structure, improves accuracy of nursing diagnoses. PMID:22852577

Knowing What You Know: Improving Metacomprehension and Calibration Accuracy in Digital Text

ERIC Educational Resources Information Center

Reid, Alan J.; Morrison, Gary R.; Bol, Linda

2017-01-01

This paper presents results from an experimental study that examined embedded strategy prompts in digital text and their effects on calibration and metacomprehension accuracies. A sample population of 80 college undergraduates read a digital expository text on the basics of photography. The most robust treatment (mixed) read the text, generated a…

The Effect of Flexible Pavement Mechanics on the Accuracy of Axle Load Sensors in Vehicle Weigh-in-Motion Systems

PubMed Central

Rys, Dawid

2017-01-01

Weigh-in-Motion systems are tools to prevent road pavements from the adverse phenomena of vehicle overloading. However, the effectiveness of these systems can be significantly increased by improving weighing accuracy, which is now insufficient for direct enforcement of overloaded vehicles. Field tests show that the accuracy of Weigh-in-Motion axle load sensors installed in the flexible (asphalt) pavements depends on pavement temperature and vehicle speeds. Although this is a known phenomenon, it has not been explained yet. The aim of our study is to fill this gap in the knowledge. The explanation of this phenomena which is presented in the paper is based on pavement/sensors mechanics and the application of the multilayer elastic half-space theory. We show that differences in the distribution of vertical and horizontal stresses in the pavement structure are the cause of vehicle weight measurement errors. These studies are important in terms of Weigh-in-Motion systems for direct enforcement and will help to improve the weighing results accuracy. PMID:28880215

The Effect of Flexible Pavement Mechanics on the Accuracy of Axle Load Sensors in Vehicle Weigh-in-Motion Systems.

PubMed

Burnos, Piotr; Rys, Dawid

2017-09-07

Weigh-in-Motion systems are tools to prevent road pavements from the adverse phenomena of vehicle overloading. However, the effectiveness of these systems can be significantly increased by improving weighing accuracy, which is now insufficient for direct enforcement of overloaded vehicles. Field tests show that the accuracy of Weigh-in-Motion axle load sensors installed in the flexible (asphalt) pavements depends on pavement temperature and vehicle speeds. Although this is a known phenomenon, it has not been explained yet. The aim of our study is to fill this gap in the knowledge. The explanation of this phenomena which is presented in the paper is based on pavement/sensors mechanics and the application of the multilayer elastic half-space theory. We show that differences in the distribution of vertical and horizontal stresses in the pavement structure are the cause of vehicle weight measurement errors. These studies are important in terms of Weigh-in-Motion systems for direct enforcement and will help to improve the weighing results accuracy.

A neural network approach to cloud classification

NASA Technical Reports Server (NTRS)

Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.

1990-01-01

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

A Single Bout of Moderate Aerobic Exercise Improves Motor Skill Acquisition.

PubMed

Statton, Matthew A; Encarnacion, Marysol; Celnik, Pablo; Bastian, Amy J

2015-01-01

Long-term exercise is associated with improved performance on a variety of cognitive tasks including attention, executive function, and long-term memory. Remarkably, recent studies have shown that even a single bout of aerobic exercise can lead to immediate improvements in declarative learning and memory, but less is known about the effect of exercise on motor learning. Here we sought to determine the effect of a single bout of moderate intensity aerobic exercise on motor skill learning. In experiment 1, we investigated the effect of moderate aerobic exercise on motor acquisition. 24 young, healthy adults performed a motor learning task either immediately after 30 minutes of moderate intensity running, after running followed by a long rest period, or after slow walking. Motor skill was assessed via a speed-accuracy tradeoff function to determine how exercise might differentially affect two distinct components of motor learning performance: movement speed and accuracy. In experiment 2, we investigated both acquisition and retention of motor skill across multiple days of training. 20 additional participants performed either a bout of running or slow walking immediately before motor learning on three consecutive days, and only motor learning (no exercise) on a fourth day. We found that moderate intensity running led to an immediate improvement in motor acquisition for both a single session and on multiple sessions across subsequent days, but had no effect on between-day retention. This effect was driven by improved movement accuracy, as opposed to speed. However, the benefit of exercise was dependent upon motor learning occurring immediately after exercise-resting for a period of one hour after exercise diminished the effect. These results demonstrate that moderate intensity exercise can prime the nervous system for the acquisition of new motor skills, and suggest that similar exercise protocols may be effective in improving the outcomes of movement rehabilitation programs.

A Single Bout of Moderate Aerobic Exercise Improves Motor Skill Acquisition

PubMed Central

Statton, Matthew A.; Encarnacion, Marysol; Celnik, Pablo; Bastian, Amy J.

2015-01-01

Long-term exercise is associated with improved performance on a variety of cognitive tasks including attention, executive function, and long-term memory. Remarkably, recent studies have shown that even a single bout of aerobic exercise can lead to immediate improvements in declarative learning and memory, but less is known about the effect of exercise on motor learning. Here we sought to determine the effect of a single bout of moderate intensity aerobic exercise on motor skill learning. In experiment 1, we investigated the effect of moderate aerobic exercise on motor acquisition. 24 young, healthy adults performed a motor learning task either immediately after 30 minutes of moderate intensity running, after running followed by a long rest period, or after slow walking. Motor skill was assessed via a speed-accuracy tradeoff function to determine how exercise might differentially affect two distinct components of motor learning performance: movement speed and accuracy. In experiment 2, we investigated both acquisition and retention of motor skill across multiple days of training. 20 additional participants performed either a bout of running or slow walking immediately before motor learning on three consecutive days, and only motor learning (no exercise) on a fourth day. We found that moderate intensity running led to an immediate improvement in motor acquisition for both a single session and on multiple sessions across subsequent days, but had no effect on between-day retention. This effect was driven by improved movement accuracy, as opposed to speed. However, the benefit of exercise was dependent upon motor learning occurring immediately after exercise–resting for a period of one hour after exercise diminished the effect. These results demonstrate that moderate intensity exercise can prime the nervous system for the acquisition of new motor skills, and suggest that similar exercise protocols may be effective in improving the outcomes of movement rehabilitation programs. PMID:26506413

Task-relevant cognitive and motor functions are prioritized during prolonged speed-accuracy motor task performance.

PubMed

Solianik, Rima; Satas, Andrius; Mickeviciene, Dalia; Cekanauskaite, Agne; Valanciene, Dovile; Majauskiene, Daiva; Skurvydas, Albertas

2018-06-01

This study aimed to explore the effect of prolonged speed-accuracy motor task on the indicators of psychological, cognitive, psychomotor and motor function. Ten young men aged 21.1 ± 1.0 years performed a fast- and accurate-reaching movement task and a control task. Both tasks were performed for 2 h. Despite decreased motivation, and increased perception of effort as well as subjective feeling of fatigue, speed-accuracy motor task performance improved during the whole period of task execution. After the motor task, the increased working memory function and prefrontal cortex oxygenation at rest and during conflict detection, and the decreased efficiency of incorrect response inhibition and visuomotor tracking were observed. The speed-accuracy motor task increased the amplitude of motor-evoked potentials, while grip strength was not affected. These findings demonstrate that to sustain the performance of 2-h speed-accuracy task under conditions of self-reported fatigue, task-relevant functions are maintained or even improved, whereas less critical functions are impaired.

Employment of sawtooth-shaped-function excitation signal and oversampling for improving resistance measurement accuracy

NASA Astrophysics Data System (ADS)

Lin, Ling; Li, Shujuan; Yan, Wenjuan; Li, Gang

2016-10-01

In order to achieve higher measurement accuracy of routine resistance without increasing the complexity and cost of the system circuit of existing methods, this paper presents a novel method that exploits a shaped-function excitation signal and oversampling technology. The excitation signal source for resistance measurement is modulated by the sawtooth-shaped-function signal, and oversampling technology is employed to increase the resolution and the accuracy of the measurement system. Compared with the traditional method of using constant amplitude excitation signal, this method can effectively enhance the measuring accuracy by almost one order of magnitude and reduce the root mean square error by 3.75 times under the same measurement conditions. The results of experiments show that the novel method can attain the aim of significantly improve the measurement accuracy of resistance on the premise of not increasing the system cost and complexity of the circuit, which is significantly valuable for applying in electronic instruments.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar.

PubMed

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-09-09

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar's estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method.

The systematic component of phylogenetic error as a function of taxonomic sampling under parsimony.

PubMed

Debry, Ronald W

2005-06-01

The effect of taxonomic sampling on phylogenetic accuracy under parsimony is examined by simulating nucleotide sequence evolution. Random error is minimized by using very large numbers of simulated characters. This allows estimation of the consistency behavior of parsimony, even for trees with up to 100 taxa. Data were simulated on 8 distinct 100-taxon model trees and analyzed as stratified subsets containing either 25 or 50 taxa, in addition to the full 100-taxon data set. Overall accuracy decreased in a majority of cases when taxa were added. However, the magnitude of change in the cases in which accuracy increased was larger than the magnitude of change in the cases in which accuracy decreased, so, on average, overall accuracy increased as more taxa were included. A stratified sampling scheme was used to assess accuracy for an initial subsample of 25 taxa. The 25-taxon analyses were compared to 50- and 100-taxon analyses that were pruned to include only the original 25 taxa. On average, accuracy for the 25 taxa was improved by taxon addition, but there was considerable variation in the degree of improvement among the model trees and across different rates of substitution.

Assessment of colon polyp morphology: Is education effective?

PubMed Central

Kim, Jae Hyun; Nam, Kyoung Sik; Kwon, Hye Jung; Choi, Youn Jung; Jung, Kyoungwon; Kim, Sung Eun; Moon, Won; Park, Moo In; Park, Seun Ja

2017-01-01

AIM To determine the inter-observer variability for colon polyp morphology and to identify whether education can improve agreement among observers. METHODS For purposes of the tests, we recorded colonoscopy video clips that included scenes visualizing the polyps. A total of 15 endoscopists and 15 nurses participated in the study. Participants watched 60 video clips of the polyp morphology scenes and then estimated polyp morphology (pre-test). After education for 20 min, participants performed a second test in which the order of 60 video clips was changed (post-test). To determine if the effectiveness of education was sustained, four months later, a third, follow-up test was performed with the same participants. RESULTS The overall Fleiss’ kappa value of the inter-observer agreement was 0.510 in the pre-test, 0.618 in the post-test, and 0.580 in the follow-up test. The overall diagnostic accuracy of the estimation for polyp morphology in the pre-, post-, and follow-up tests was 0.662, 0.797, and 0.761, respectively. After education, the inter-observer agreement and diagnostic accuracy of all participants improved. However, after four months, the inter-observer agreement and diagnostic accuracy of expert groups were markedly decreased, and those of beginner and nurse groups remained similar to pre-test levels. CONCLUSION The education program used in this study can improve inter-observer agreement and diagnostic accuracy in assessing the morphology of colon polyps; it is especially effective when first learning endoscopy. PMID:28974894

Assessment of colon polyp morphology: Is education effective?

PubMed

Kim, Jae Hyun; Nam, Kyoung Sik; Kwon, Hye Jung; Choi, Youn Jung; Jung, Kyoungwon; Kim, Sung Eun; Moon, Won; Park, Moo In; Park, Seun Ja

2017-09-14

To determine the inter-observer variability for colon polyp morphology and to identify whether education can improve agreement among observers. For purposes of the tests, we recorded colonoscopy video clips that included scenes visualizing the polyps. A total of 15 endoscopists and 15 nurses participated in the study. Participants watched 60 video clips of the polyp morphology scenes and then estimated polyp morphology (pre-test). After education for 20 min, participants performed a second test in which the order of 60 video clips was changed (post-test). To determine if the effectiveness of education was sustained, four months later, a third, follow-up test was performed with the same participants. The overall Fleiss' kappa value of the inter-observer agreement was 0.510 in the pre-test, 0.618 in the post-test, and 0.580 in the follow-up test. The overall diagnostic accuracy of the estimation for polyp morphology in the pre-, post-, and follow-up tests was 0.662, 0.797, and 0.761, respectively. After education, the inter-observer agreement and diagnostic accuracy of all participants improved. However, after four months, the inter-observer agreement and diagnostic accuracy of expert groups were markedly decreased, and those of beginner and nurse groups remained similar to pre-test levels. The education program used in this study can improve inter-observer agreement and diagnostic accuracy in assessing the morphology of colon polyps; it is especially effective when first learning endoscopy.

Including α s1 casein gene information in genomic evaluations of French dairy goats.

PubMed

Carillier-Jacquin, Céline; Larroque, Hélène; Robert-Granié, Christèle

2016-08-04

Genomic best linear unbiased prediction methods assume that all markers explain the same fraction of the genetic variance and do not account effectively for genes with major effects such as the α s1 casein polymorphism in dairy goats. In this study, we investigated methods to include the available α s1 casein genotype effect in genomic evaluations of French dairy goats. First, the α s1 casein genotype was included as a fixed effect in genomic evaluation models based only on bucks that were genotyped at the α s1 casein locus. Less than 1 % of the females with phenotypes were genotyped at the α s1 casein gene. Thus, to incorporate these female phenotypes in the genomic evaluation, two methods that allowed for this large number of missing α s1 casein genotypes were investigated. Probabilities for each possible α s1 casein genotype were first estimated for each female of unknown genotype based on iterative peeling equations. The second method is based on a multiallelic gene content approach. For each model tested, we used three datasets each divided into a training and a validation set: (1) two-breed population (Alpine + Saanen), (2) Alpine population, and (3) Saanen population. The α s1 casein genotype had a significant effect on milk yield, fat content and protein content. Including an α s1 casein effect in genetic and genomic evaluations based only on male known α s1 casein genotypes improved accuracies (from 6 to 27 %). In genomic evaluations based on all female phenotypes, the gene content approach performed better than the other tested methods but the improvement in accuracy was only slightly better (from 1 to 14 %) than that of a genomic model without the α s1 casein effect. Including the α s1 casein effect in a genomic evaluation model for French dairy goats is possible and useful to improve accuracy. Difficulties in predicting the genotypes for ungenotyped animals limited the improvement in accuracy of the obtained estimated breeding values.

Comparison of the Effectiveness of Interactive Didactic Lecture Versus Online Simulation-Based CME Programs Directed at Improving the Diagnostic Capabilities of Primary Care Practitioners.

PubMed

McFadden, Pam; Crim, Andrew

2016-01-01

Diagnostic errors in primary care contribute to increased morbidity and mortality, and billions in costs each year. Improvements in the way practicing physicians are taught so as to optimally perform differential diagnosis can increase patient safety and lower the costs of care. This study represents a comparison of the effectiveness of two approaches to CME training directed at improving the primary care practitioner's diagnostic capabilities against seven common and important causes of joint pain. Using a convenience sampling methodology, one group of primary care practitioners was trained by a traditional live, expert-led, multimedia-based training activity supplemented with interactive practice opportunities and feedback (control group). The second group was trained online with a multimedia-based training activity supplemented with interactive practice opportunities and feedback delivered by an artificial intelligence-driven simulation/tutor (treatment group). Before their respective instructional intervention, there were no significant differences in the diagnostic performance of the two groups against a battery of case vignettes presenting with joint pain. Using the same battery of case vignettes to assess postintervention diagnostic performance, there was a slight but not statistically significant improvement in the control group's diagnostic accuracy (P = .13). The treatment group, however, demonstrated a significant improvement in accuracy (P < .02; Cohen d, effect size = 0.79). These data indicate that within the context of a CME activity, a significant improvement in diagnostic accuracy can be achieved by the use of a web-delivered, multimedia-based instructional activity supplemented by practice opportunities and feedback delivered by an artificial intelligence-driven simulation/tutor.

Two sides of the same coin: Monetary incentives concurrently improve and bias confidence judgments.

PubMed

Lebreton, Maël; Langdon, Shari; Slieker, Matthijs J; Nooitgedacht, Jip S; Goudriaan, Anna E; Denys, Damiaan; van Holst, Ruth J; Luigjes, Judy

2018-05-01

Decisions are accompanied by a feeling of confidence, that is, a belief about the decision being correct. Confidence accuracy is critical, notably in high-stakes situations such as medical or financial decision-making. We investigated how incentive motivation influences confidence accuracy by combining a perceptual task with a confidence incentivization mechanism. By varying the magnitude and valence (gains or losses) of monetary incentives, we orthogonalized their motivational and affective components. Corroborating theories of rational decision-making and motivation, our results first reveal that the motivational value of incentives improves aspects of confidence accuracy. However, in line with a value-confidence interaction hypothesis, we further show that the affective value of incentives concurrently biases confidence reports, thus degrading confidence accuracy. Finally, we demonstrate that the motivational and affective effects of incentives differentially affect how confidence builds on perceptual evidence. Together, these findings may provide new hints about confidence miscalibration in healthy or pathological contexts.

Accuracy assessment of surgical planning and three-dimensional-printed patient-specific guides for orthopaedic osteotomies.

PubMed

Sys, Gwen; Eykens, Hannelore; Lenaerts, Gerlinde; Shumelinsky, Felix; Robbrecht, Cedric; Poffyn, Bart

2017-06-01

This study analyses the accuracy of three-dimensional pre-operative planning and patient-specific guides for orthopaedic osteotomies. To this end, patient-specific guides were compared to the classical freehand method in an experimental setup with saw bones in two phases. In the first phase, the effect of guide design and oscillating versus reciprocating saws was analysed. The difference between target and performed cuts was quantified by the average distance deviation and average angular deviations in the sagittal and coronal planes for the different osteotomies. The results indicated that for one model osteotomy, the use of guides resulted in a more accurate cut when compared to the freehand technique. Reciprocating saws and slot guides improved accuracy in all planes, while oscillating saws and open guides lead to larger deviations from the planned cut. In the second phase, the accuracy of transfer of the planning to the surgical field with slot guides and a reciprocating saw was assessed and compared to the classical planning and freehand cutting method. The pre-operative plan was transferred with high accuracy. Three-dimensional-printed patient-specific guides improve the accuracy of osteotomies and bony resections in an experimental setup compared to conventional freehand methods. The improved accuracy is related to (1) a detailed and qualitative pre-operative plan and (2) an accurate transfer of the planning to the operation room with patient-specific guides by an accurate guidance of the surgical tools to perform the desired cuts.

Overlay accuracy fundamentals

NASA Astrophysics Data System (ADS)

Kandel, Daniel; Levinski, Vladimir; Sapiens, Noam; Cohen, Guy; Amit, Eran; Klein, Dana; Vakshtein, Irina

2012-03-01

Currently, the performance of overlay metrology is evaluated mainly based on random error contributions such as precision and TIS variability. With the expected shrinkage of the overlay metrology budget to < 0.5nm, it becomes crucial to include also systematic error contributions which affect the accuracy of the metrology. Here we discuss fundamental aspects of overlay accuracy and a methodology to improve accuracy significantly. We identify overlay mark imperfections and their interaction with the metrology technology, as the main source of overlay inaccuracy. The most important type of mark imperfection is mark asymmetry. Overlay mark asymmetry leads to a geometrical ambiguity in the definition of overlay, which can be ~1nm or less. It is shown theoretically and in simulations that the metrology may enhance the effect of overlay mark asymmetry significantly and lead to metrology inaccuracy ~10nm, much larger than the geometrical ambiguity. The analysis is carried out for two different overlay metrology technologies: Imaging overlay and DBO (1st order diffraction based overlay). It is demonstrated that the sensitivity of DBO to overlay mark asymmetry is larger than the sensitivity of imaging overlay. Finally, we show that a recently developed measurement quality metric serves as a valuable tool for improving overlay metrology accuracy. Simulation results demonstrate that the accuracy of imaging overlay can be improved significantly by recipe setup optimized using the quality metric. We conclude that imaging overlay metrology, complemented by appropriate use of measurement quality metric, results in optimal overlay accuracy.

Improving the Yule-Nielsen modified Neugebauer model by dot surface coverages depending on the ink superposition conditions

NASA Astrophysics Data System (ADS)

Hersch, Roger David; Crété, Frédérique

2004-12-01

Dot gain is different when dots are printed alone, printed in superposition with one ink or printed in superposition with two inks. In addition, the dot gain may also differ depending on which solid ink the considered halftone layer is superposed. In a previous research project, we developed a model for computing the effective surface coverage of a dot according to its superposition conditions. In the present contribution, we improve the Yule-Nielsen modified Neugebauer model by integrating into it our effective dot surface coverage computation model. Calibration of the reproduction curves mapping nominal to effective surface coverages in every superposition condition is carried out by fitting effective dot surfaces which minimize the sum of square differences between the measured reflection density spectra and reflection density spectra predicted according to the Yule-Nielsen modified Neugebauer model. In order to predict the reflection spectrum of a patch, its known nominal surface coverage values are converted into effective coverage values by weighting the contributions from different reproduction curves according to the weights of the contributing superposition conditions. We analyze the colorimetric prediction improvement brought by our extended dot surface coverage model for clustered-dot offset prints, thermal transfer prints and ink-jet prints. The color differences induced by the differences between measured reflection spectra and reflection spectra predicted according to the new dot surface estimation model are quantified on 729 different cyan, magenta, yellow patches covering the full color gamut. As a reference, these differences are also computed for the classical Yule-Nielsen modified spectral Neugebauer model incorporating a single halftone reproduction curve for each ink. Taking into account dot surface coverages according to different superposition conditions considerably improves the predictions of the Yule-Nielsen modified Neugebauer model. In the case of offset prints, the mean difference between predictions and measurements expressed in CIE-LAB CIE-94 ΔE94 values is reduced at 100 lpi from 1.54 to 0.90 (accuracy improvement factor: 1.7) and at 150 lpi it is reduced from 1.87 to 1.00 (accuracy improvement factor: 1.8). Similar improvements have been observed for a thermal transfer printer at 600 dpi, at lineatures of 50 and 75 lpi. In the case of an ink-jet printer at 600 dpi, the mean ΔE94 value is reduced at 75 lpi from 3.03 to 0.90 (accuracy improvement factor: 3.4) and at 100 lpi from 3.08 to 0.91 (accuracy improvement factor: 3.4).

Improving the Yule-Nielsen modified Neugebauer model by dot surface coverages depending on the ink superposition conditions

NASA Astrophysics Data System (ADS)

Hersch, Roger David; Crete, Frederique

2005-01-01

Dot gain is different when dots are printed alone, printed in superposition with one ink or printed in superposition with two inks. In addition, the dot gain may also differ depending on which solid ink the considered halftone layer is superposed. In a previous research project, we developed a model for computing the effective surface coverage of a dot according to its superposition conditions. In the present contribution, we improve the Yule-Nielsen modified Neugebauer model by integrating into it our effective dot surface coverage computation model. Calibration of the reproduction curves mapping nominal to effective surface coverages in every superposition condition is carried out by fitting effective dot surfaces which minimize the sum of square differences between the measured reflection density spectra and reflection density spectra predicted according to the Yule-Nielsen modified Neugebauer model. In order to predict the reflection spectrum of a patch, its known nominal surface coverage values are converted into effective coverage values by weighting the contributions from different reproduction curves according to the weights of the contributing superposition conditions. We analyze the colorimetric prediction improvement brought by our extended dot surface coverage model for clustered-dot offset prints, thermal transfer prints and ink-jet prints. The color differences induced by the differences between measured reflection spectra and reflection spectra predicted according to the new dot surface estimation model are quantified on 729 different cyan, magenta, yellow patches covering the full color gamut. As a reference, these differences are also computed for the classical Yule-Nielsen modified spectral Neugebauer model incorporating a single halftone reproduction curve for each ink. Taking into account dot surface coverages according to different superposition conditions considerably improves the predictions of the Yule-Nielsen modified Neugebauer model. In the case of offset prints, the mean difference between predictions and measurements expressed in CIE-LAB CIE-94 ΔE94 values is reduced at 100 lpi from 1.54 to 0.90 (accuracy improvement factor: 1.7) and at 150 lpi it is reduced from 1.87 to 1.00 (accuracy improvement factor: 1.8). Similar improvements have been observed for a thermal transfer printer at 600 dpi, at lineatures of 50 and 75 lpi. In the case of an ink-jet printer at 600 dpi, the mean ΔE94 value is reduced at 75 lpi from 3.03 to 0.90 (accuracy improvement factor: 3.4) and at 100 lpi from 3.08 to 0.91 (accuracy improvement factor: 3.4).

Effects of Emotion on Associative Recognition: Valence and Retention Interval Matter

PubMed Central

Pierce, Benton H.; Kensinger, Elizabeth A.

2011-01-01

In two experiments, we examined the effects of emotional valence and arousal on associative binding. Participants studied negative, positive, and neutral word pairs, followed by an associative recognition test. In Experiment 1, with a short-delayed test, accuracy for intact pairs was equivalent across valences, whereas accuracy for rearranged pairs was lower for negative than for positive and neutral pairs. In Experiment 2, we tested participants after a one-week delay and found that accuracy was greater for intact negative than for intact neutral pairs, whereas rearranged pair accuracy was equivalent across valences. These results suggest that, although negative emotional valence impairs associative binding after a short delay, it may improve binding after a longer delay. The results also suggest that valence, as well as arousal, needs to be considered when examining the effects of emotion on associative memory. PMID:21401233

An Improved Method of AGM for High Precision Geolocation of SAR Images

NASA Astrophysics Data System (ADS)

Zhou, G.; He, C.; Yue, T.; Huang, W.; Huang, Y.; Li, X.; Chen, Y.

2018-05-01

In order to take full advantage of SAR images, it is necessary to obtain the high precision location of the image. During the geometric correction process of images, to ensure the accuracy of image geometric correction and extract the effective mapping information from the images, precise image geolocation is important. This paper presents an improved analytical geolocation method (IAGM) that determine the high precision geolocation of each pixel in a digital SAR image. This method is based on analytical geolocation method (AGM) proposed by X. K. Yuan aiming at realizing the solution of RD model. Tests will be conducted using RADARSAT-2 SAR image. Comparing the predicted feature geolocation with the position as determined by high precision orthophoto, results indicate an accuracy of 50m is attainable with this method. Error sources will be analyzed and some recommendations about improving image location accuracy in future spaceborne SAR's will be given.

Physician involvement enhances coding accuracy to ensure national standards: an initiative to improve awareness among new junior trainees.

PubMed

Nallasivan, S; Gillott, T; Kamath, S; Blow, L; Goddard, V

2011-06-01

Record Keeping Standards is a development led by the Royal College of Physicians of London (RCP) Health Informatics Unit and funded by the National Health Service (NHS) Connecting for Health. A supplementary report produced by the RCP makes a number of recommendations based on a study held at an acute hospital trust. We audited the medical notes and coding to assess the accuracy, documentation by the junior doctors and also to correlate our findings with the RCP audit. Northern Lincolnshire & Goole Hospitals NHS Foundation Trust has 114,000 'finished consultant episodes' per year. A total of 100 consecutive medical (50) and rheumatology (50) discharges from Diana Princess of Wales Hospital from August-October 2009 were reviewed. The results showed an improvement in coding accuracy (10% errors), comparable to the RCP audit but with 5% documentation errors. Physician involvement needs enhancing to improve the effectiveness and to ensure clinical safety.

Efficiency improvement by navigated safety inspection involving visual clutter based on the random search model.

PubMed

Sun, Xinlu; Chong, Heap-Yih; Liao, Pin-Chao

2018-06-25

Navigated inspection seeks to improve hazard identification (HI) accuracy. With tight inspection schedule, HI also requires efficiency. However, lacking quantification of HI efficiency, navigated inspection strategies cannot be comprehensively assessed. This work aims to determine inspection efficiency in navigated safety inspection, controlling for the HI accuracy. Based on a cognitive method of the random search model (RSM), an experiment was conducted to observe the HI efficiency in navigation, for a variety of visual clutter (VC) scenarios, while using eye-tracking devices to record the search process and analyze the search performance. The results show that the RSM is an appropriate instrument, and VC serves as a hazard classifier for navigation inspection in improving inspection efficiency. This suggests a new and effective solution for addressing the low accuracy and efficiency of manual inspection through navigated inspection involving VC and the RSM. It also provides insights into the inspectors' safety inspection ability.

Statewide Quality Improvement Initiative to Reduce Early Elective Deliveries and Improve Birth Registry Accuracy.

PubMed

Kaplan, Heather C; King, Eileen; White, Beth E; Ford, Susan E; Fuller, Sandra; Krew, Michael A; Marcotte, Michael P; Iams, Jay D; Bailit, Jennifer L; Bouchard, Jo M; Friar, Kelly; Lannon, Carole M

2018-04-01

To evaluate the success of a quality improvement initiative to reduce early elective deliveries at less than 39 weeks of gestation and improve birth registry data accuracy rapidly and at scale in Ohio. Between February 2013 and March 2014, participating hospitals were involved in a quality improvement initiative to reduce early elective deliveries at less than 39 weeks of gestation and improve birth registry data. This initiative was designed as a learning collaborative model (group webinars and a single face-to-face meeting) and included individual quality improvement coaching. It was implemented using a stepped wedge design with hospitals divided into three balanced groups (waves) participating in the initiative sequentially. Birth registry data were used to assess hospital rates of nonmedically indicated inductions at less than 39 weeks of gestation. Comparisons were made between groups participating and those not participating in the initiative at two time points. To measure birth registry accuracy, hospitals conducted monthly audits comparing birth registry data with the medical record. Associations were assessed using generalized linear repeated measures models accounting for time effects. Seventy of 72 (97%) eligible hospitals participated. Based on birth registry data, nonmedically indicated inductions at less than 39 weeks of gestation declined in all groups with implementation (wave 1: 6.2-3.2%, P<.001; wave 2: 4.2-2.5%, P=.04; wave 3: 6.8-3.7%, P=.002). When waves 1 and 2 were participating in the initiative, they saw significant decreases in rates of early elective deliveries as compared with wave 3 (control; P=.018). All waves had significant improvement in birth registry accuracy (wave 1: 80-90%, P=.017; wave 2: 80-100%, P=.002; wave 3: 75-100%, P<.001). A quality improvement initiative enabled statewide spread of change strategies to decrease early elective deliveries and improve birth registry accuracy over 14 months and could be used for rapid dissemination of other evidence-based obstetric care practices across states or hospital systems.

Metacognitive Scaffolds Improve Self-Judgments of Accuracy in a Medical Intelligent Tutoring System

ERIC Educational Resources Information Center

Feyzi-Behnagh, Reza; Azevedo, Roger; Legowski, Elizabeth; Reitmeyer, Kayse; Tseytlin, Eugene; Crowley, Rebecca S.

2014-01-01

In this study, we examined the effect of two metacognitive scaffolds on the accuracy of confidence judgments made while diagnosing dermatopathology slides in SlideTutor. Thirty-one (N = 31) first- to fourth-year pathology and dermatology residents were randomly assigned to one of the two scaffolding conditions. The cases used in this study were…

Judgment of Learning, Monitoring Accuracy, and Student Performance in the Classroom Context

ERIC Educational Resources Information Center

Cao, Li; Nietfeld, John L.

2005-01-01

As a key component in self-regulated learning, the ability to accurately judge the status of learning enables students to become strategic and effective in the learning process. Weekly monitoring exercises were used to improve college students' (N = 94) accuracy of judgment of learning over a 14-week educational psychology course. A time series…

Effects of the Presence of Audio and Type of Game Controller on Learning of Rhythmic Accuracy

ERIC Educational Resources Information Center

Thomas, James William

2017-01-01

"Guitar Hero III" and similar games potentially offer a vehicle for improvement of musical rhythmic accuracy with training delivered in both visual and auditory formats and by use of its novel guitar-shaped interface; however, some theories regarding multimedia learning suggest sound is a possible source of extraneous cognitive load…

The Effect of Delayed-JOLs and Sentence Generation on Children's Monitoring Accuracy and Regulation of Idiom Study

ERIC Educational Resources Information Center

van Loon, Mariëtte H.; de Bruin, Anique B. H.; van Gog, Tamara; van Merriënboer, Jeroen J. G.

2013-01-01

When studying verbal materials, both adults and children are often poor at accurately monitoring their level of learning and regulating their subsequent restudy of materials, which leads to suboptimal test performance. The present experiment investigated how monitoring accuracy and regulation of study could be improved when learning idiomatic…

He's Frequency Formulation for Nonlinear Oscillators

ERIC Educational Resources Information Center

Geng, Lei; Cai, Xu-Chu

2007-01-01

Based on an ancient Chinese algorithm, J H He suggested a simple but effective method to find the frequency of a nonlinear oscillator. In this paper, a modified version is suggested to improve the accuracy of the frequency; two examples are given, revealing that the obtained solutions are of remarkable accuracy and are valid for the whole solution…

The Effects of Corrective Feedback on Chinese Learners' Writing Accuracy: A Quantitative Analysis in an EFL Context

ERIC Educational Resources Information Center

Wang, Xin

2017-01-01

Scholars debate whether corrective feedback contributes to improving L2 learners' grammatical accuracy in writing performance. Some researchers take a stance on the ineffectiveness of corrective feedback based on the impracticality of providing detailed corrective feedback for all L2 learners and detached grammar instruction in language…

Can verbal working memory training improve reading?

PubMed

Banales, Erin; Kohnen, Saskia; McArthur, Genevieve

2015-01-01

The aim of the current study was to determine whether poor verbal working memory is associated with poor word reading accuracy because the former causes the latter, or the latter causes the former. To this end, we tested whether (a) verbal working memory training improves poor verbal working memory or poor word reading accuracy, and whether (b) reading training improves poor reading accuracy or verbal working memory in a case series of four children with poor word reading accuracy and verbal working memory. Each child completed 8 weeks of verbal working memory training and 8 weeks of reading training. Verbal working memory training improved verbal working memory in two of the four children, but did not improve their reading accuracy. Similarly, reading training improved word reading accuracy in all children, but did not improve their verbal working memory. These results suggest that the causal links between verbal working memory and reading accuracy may not be as direct as has been assumed.

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel.

PubMed

Huang, Jie; Howie, Bryan; McCarthy, Shane; Memari, Yasin; Walter, Klaudia; Min, Josine L; Danecek, Petr; Malerba, Giovanni; Trabetti, Elisabetta; Zheng, Hou-Feng; Gambaro, Giovanni; Richards, J Brent; Durbin, Richard; Timpson, Nicholas J; Marchini, Jonathan; Soranzo, Nicole

2015-09-14

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.

Cognitive benefit and cost of acute stress is differentially modulated by individual brain state

PubMed Central

Hermans, Erno J.; Fernández, Guillén

2017-01-01

Abstract Acute stress is associated with beneficial as well as detrimental effects on cognition in different individuals. However, it is not yet known how stress can have such opposing effects. Stroop-like tasks typically show this dissociation: stress diminishes speed, but improves accuracy. We investigated accuracy and speed during a stroop-like task of 120 healthy male subjects after an experimental stress induction or control condition in a randomized, counter-balanced cross-over design; we assessed brain–behavior associations and determined the influence of individual brain connectivity patterns on these associations, which may moderate the effect and help identify stress resilience factors. In the mean, stress was associated to increase in accuracy, but decrease in speed. Accuracy was associated to brain activation in a distributed set of brain regions overlapping with the executive control network (ECN) and speed to temporo-parietal activation. In line with a stress-related large-scale network reconfiguration, individuals showing an upregulation of the salience and down-regulation of the executive-control network under stress displayed increased speed, but decreased performance. In contrast, individuals who upregulate their ECN under stress show improved performance. Our results indicate that the individual large-scale brain network balance under acute stress moderates cognitive consequences of threat. PMID:28402480

Cognitive benefit and cost of acute stress is differentially modulated by individual brain state.

PubMed

Kohn, Nils; Hermans, Erno J; Fernández, Guillén

2017-07-01

Acute stress is associated with beneficial as well as detrimental effects on cognition in different individuals. However, it is not yet known how stress can have such opposing effects. Stroop-like tasks typically show this dissociation: stress diminishes speed, but improves accuracy. We investigated accuracy and speed during a stroop-like task of 120 healthy male subjects after an experimental stress induction or control condition in a randomized, counter-balanced cross-over design; we assessed brain-behavior associations and determined the influence of individual brain connectivity patterns on these associations, which may moderate the effect and help identify stress resilience factors. In the mean, stress was associated to increase in accuracy, but decrease in speed. Accuracy was associated to brain activation in a distributed set of brain regions overlapping with the executive control network (ECN) and speed to temporo-parietal activation. In line with a stress-related large-scale network reconfiguration, individuals showing an upregulation of the salience and down-regulation of the executive-control network under stress displayed increased speed, but decreased performance. In contrast, individuals who upregulate their ECN under stress show improved performance. Our results indicate that the individual large-scale brain network balance under acute stress moderates cognitive consequences of threat. © The Author (2017). Published by Oxford University Press.

Note-taking in the employment interview: effects on recall and judgments.

PubMed

Middendorf, Catherine Houdek; Macan, Therese Hoff

2002-04-01

Although note-taking in the employment interview is highly recommended, little research has examined its effects. This study investigated the effects of note-taking styles, review of the notes, and content of the notes on participants' cued recall of information and decisions made from videotaped employment interviews. Note-taking increased recall accuracy but not judgment accuracy. Being able to review notes resulted in increased judgment accuracy for those taking conventional-style notes. The content of the notes also had important implications for conventional note-takers, suggesting some benefits of recording notes using the key-points style. The findings suggest that the act of note-taking may be more important for memory and legal reasons than for improving the decisions made by interviewers.

Accuracy Improvement for Light-Emitting-Diode-Based Colorimeter by Iterative Algorithm

NASA Astrophysics Data System (ADS)

Yang, Pao-Keng

2011-09-01

We present a simple algorithm, combining an interpolating method with an iterative calculation, to enhance the resolution of spectral reflectance by removing the spectral broadening effect due to the finite bandwidth of the light-emitting diode (LED) from it. The proposed algorithm can be used to improve the accuracy of a reflective colorimeter using multicolor LEDs as probing light sources and is also applicable to the case when the probing LEDs have different bandwidths in different spectral ranges, to which the powerful deconvolution method cannot be applied.

Recent Advances in Image Assisted Neurosurgical Procedures: Improved Navigational Accuracy and Patient Safety

ScienceCinema

Olivi, Alessandro, M.D.

2017-12-09

Neurosurgical procedures require precise planning and intraoperative support. Recent advances in image guided technology have provided neurosurgeons with improved navigational support for more effective and safer procedures. A number of exemplary cases will be presented.

The Effectiveness of Vowel Production Training with Real-Time Spectrographic Displays for Children with Profound Hearing Impairment.

NASA Astrophysics Data System (ADS)

Ertmer, David Joseph

1994-01-01

The effectiveness of vowel production training which incorporated direct instruction in combination with spectrographic models and feedback was assessed for two children who exhibited profound hearing impairment. A multiple-baseline design across behaviors, with replication across subjects was implemented to determine if vowel production accuracy improved following the introduction of treatment. Listener judgments of vowel correctness were obtained during the baseline, training, and follow-up phases of the study. Data were analyzed through visual inspection of changes in levels of accuracy, changes in trends of accuracy, and changes in variability of accuracy within and across phases. One subject showed significant improvement of all three trained vowel targets; the second subject for the first trained target only (Kolmogorov-Smirnov Two Sample Test). Performance trends during training sessions suggest that continued treatment would have resulted in further improvement for both subjects. Vowel duration, fundamental frequency, and the frequency locations of the first and second formants were measured before and after training. Acoustic analysis revealed highly individualized changes in the frequency locations of F1 and F2. Vowels which received the most training were maintained at higher levels than those which were introduced later in training, Some generalization of practiced vowel targets to untrained words was observed in both subjects. A bias towards judging productions as "correct" was observed for both subjects during self-evaluation tasks using spectrographic feedback.

Single-Sided Deafness: Impact of Cochlear Implantation on Speech Perception in Complex Noise and on Auditory Localization Accuracy.

PubMed

Döge, Julia; Baumann, Uwe; Weissgerber, Tobias; Rader, Tobias

2017-12-01

To assess auditory localization accuracy and speech reception threshold (SRT) in complex noise conditions in adult patients with acquired single-sided deafness, after intervention with a cochlear implant (CI) in the deaf ear. Nonrandomized, open, prospective patient series. Tertiary referral university hospital. Eleven patients with late-onset single-sided deafness (SSD) and normal hearing in the unaffected ear, who received a CI. All patients were experienced CI users. Unilateral cochlear implantation. Speech perception was tested in a complex multitalker equivalent noise field consisting of multiple sound sources. Speech reception thresholds in noise were determined in aided (with CI) and unaided conditions. Localization accuracy was assessed in complete darkness. Acoustic stimuli were radiated by multiple loudspeakers distributed in the frontal horizontal plane between -60 and +60 degrees. In the aided condition, results show slightly improved speech reception scores compared with the unaided condition in most of the patients. For 8 of the 11 subjects, SRT was improved between 0.37 and 1.70 dB. Three of the 11 subjects showed deteriorations between 1.22 and 3.24 dB SRT. Median localization error decreased significantly by 12.9 degrees compared with the unaided condition. CI in single-sided deafness is an effective treatment to improve the auditory localization accuracy. Speech reception in complex noise conditions is improved to a lesser extent in 73% of the participating CI SSD patients. However, the absence of true binaural interaction effects (summation, squelch) impedes further improvements. The development of speech processing strategies that respect binaural interaction seems to be mandatory to advance speech perception in demanding listening situations in SSD patients.

Effects of reward on the accuracy and dynamics of smooth pursuit eye movements.

PubMed

Brielmann, Aenne A; Spering, Miriam

2015-08-01

Reward modulates behavioral choices and biases goal-oriented behavior, such as eye or hand movements, toward locations or stimuli associated with higher rewards. We investigated reward effects on the accuracy and timing of smooth pursuit eye movements in 4 experiments. Eye movements were recorded in participants tracking a moving visual target on a computer monitor. Before target motion onset, a monetary reward cue indicated whether participants could earn money by tracking accurately, or whether the trial was unrewarded (Experiments 1 and 2, n = 11 each). Reward significantly improved eye-movement accuracy across different levels of task difficulty. Improvements were seen even in the earliest phase of the eye movement, within 70 ms of tracking onset, indicating that reward impacts visual-motor processing at an early level. We obtained similar findings when reward was not precued but explicitly associated with the pursuit target (Experiment 3, n = 16); critically, these results were not driven by stimulus prevalence or other factors such as preparation or motivation. Numerical cues (Experiment 4, n = 9) were not effective. (c) 2015 APA, all rights reserved).

A temperature compensation methodology for piezoelectric based sensor devices

NASA Astrophysics Data System (ADS)

Wang, Dong F.; Lou, Xueqiao; Bao, Aijian; Yang, Xu; Zhao, Ji

2017-08-01

A temperature compensation methodology comprising a negative temperature coefficient thermistor with the temperature characteristics of a piezoelectric material is proposed to improve the measurement accuracy of piezoelectric sensing based devices. The piezoelectric disk is characterized by using a disk-shaped structure and is also used to verify the effectiveness of the proposed compensation method. The measured output voltage shows a nearly linear relationship with respect to the applied pressure by introducing the proposed temperature compensation method in a temperature range of 25-65 °C. As a result, the maximum measurement accuracy is observed to be improved by 40%, and the higher the temperature, the more effective the method. The effective temperature range of the proposed method is theoretically analyzed by introducing the constant coefficient of the thermistor (B), the resistance of initial temperature (R0), and the paralleled resistance (Rx). The proposed methodology can not only eliminate the influence of piezoelectric temperature dependent characteristics on the sensing accuracy but also decrease the power consumption of piezoelectric sensing based devices by the simplified sensing structure.

Destination memory accuracy and confidence in younger and older adults.

PubMed

Johnson, Tara L; Jefferson, Susan C

2018-01-01

Background/Study Context: Nascent research on destination memory-remembering to whom we tell particular information-suggested that older adults have deficits in destination memory and are more confident on inaccurate responses than younger adults. This study assessed the effects of age, attentional resources, and mental imagery on destination memory accuracy and confidence in younger and older adults. Using computer format, participants told facts to pictures of famous people in one of four conditions (control, self-focus, refocus, imagery). Older adults had lower destination memory accuracy than younger adults, driven by a higher level of false alarms. Whereas younger adults were more confident in accurate answers, older adults were more confident in inaccurate answers. Accuracy across participants was lowest when attention was directed internally but significantly improved when mental imagery was used. Importantly, the age-related differences in false alarms and high-confidence inaccurate answers disappeared when imagery was used. Older adults are more likely than younger adults to commit destination memory errors and are less accurate in related confidence judgments. Furthermore, the use of associative memory strategies may help improve destination memory across age groups, improve the accuracy of confidence judgments in older adults, and decrease age-related destination memory impairment, particularly in young-old adults.

Supporting driver headway choice: the effects of discrete headway feedback when following headway instructions.

PubMed

Risto, Malte; Martens, Marieke H

2014-07-01

With specific headway instructions drivers are not able to attain the exact headways as instructed. In this study, the effects of discrete headway feedback (and the direction of headway adjustment) on headway accuracy for drivers carrying out time headway instructions were assessed experimentally. Two groups of each 10 participants (one receiving headway feedback; one control) carried out headway instructions in a driving simulator; increasing and decreasing their headway to a target headway of 2 s at speeds of 50, 80, and 100 km/h. The difference between the instructed and chosen headway was a measure for headway accuracy. The feedback group heard a sound signal at the moment that they crossed the distance of the instructed headway. Unsupported participants showed no significant difference in headway accuracy when increasing or decreasing headways. Discrete headway feedback had varying effects on headway choice accuracy. When participants decreased their headway, feedback led to higher accuracy. When increasing their headway, feedback led to a lower accuracy, compared to no headway feedback. Support did not affect driver's performance in maintaining the chosen headway. The present results suggest that (a) in its current form discrete headway feedback is not sufficient to improve the overall accuracy of chosen headways when carrying out headway instructions; (b) the effect of discrete headway feedback depends on the direction of headway adjustment. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Investigation of the interpolation method to improve the distributed strain measurement accuracy in optical frequency domain reflectometry systems.

PubMed

Cui, Jiwen; Zhao, Shiyuan; Yang, Di; Ding, Zhenyang

2018-02-20

We use a spectrum interpolation technique to improve the distributed strain measurement accuracy in a Rayleigh-scatter-based optical frequency domain reflectometry sensing system. We demonstrate that strain accuracy is not limited by the "uncertainty principle" that exists in the time-frequency analysis. Different interpolation methods are investigated and used to improve the accuracy of peak position of the cross-correlation and, therefore, improve the accuracy of the strain. Interpolation implemented by padding zeros on one side of the windowed data in the spatial domain, before the inverse fast Fourier transform, is found to have the best accuracy. Using this method, the strain accuracy and resolution are both improved without decreasing the spatial resolution. The strain of 3 μϵ within the spatial resolution of 1 cm at the position of 21.4 m is distinguished, and the measurement uncertainty is 3.3 μϵ.

Speed and accuracy of dyslexic versus typical word recognition: an eye-movement investigation

PubMed Central

Kunert, Richard; Scheepers, Christoph

2014-01-01

Developmental dyslexia is often characterized by a dual deficit in both word recognition accuracy and general processing speed. While previous research into dyslexic word recognition may have suffered from speed-accuracy trade-off, the present study employed a novel eye-tracking task that is less prone to such confounds. Participants (10 dyslexics and 12 controls) were asked to look at real word stimuli, and to ignore simultaneously presented non-word stimuli, while their eye-movements were recorded. Improvements in word recognition accuracy over time were modeled in terms of a continuous non-linear function. The words' rhyme consistency and the non-words' lexicality (unpronounceable, pronounceable, pseudohomophone) were manipulated within-subjects. Speed-related measures derived from the model fits confirmed generally slower processing in dyslexics, and showed a rhyme consistency effect in both dyslexics and controls. In terms of overall error rate, dyslexics (but not controls) performed less accurately on rhyme-inconsistent words, suggesting a representational deficit for such words in dyslexics. Interestingly, neither group showed a pseudohomophone effect in speed or accuracy, which might call the task-independent pervasiveness of this effect into question. The present results illustrate the importance of distinguishing between speed- vs. accuracy-related effects for our understanding of dyslexic word recognition. PMID:25346708

Evaluating ASTER satellite imagery and gradient modeling for mapping and characterizing wildland fire fuels

Treesearch

Michael J. Falkowski; Paul Gessler; Penelope Morgan; Alistair M. S. Smith; Andrew T. Hudak

2004-01-01

Land managers need cost-effective methods for mapping and characterizing fire fuels quickly and accurately. The advent of sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the Advanced Spaceborne Thermal Emission and Reflection...

Evaluating the ASTER sensor for mapping and characterizing forest fire fuels in northern Idaho

Treesearch

Michael J. Falkowski; Paul Gessler; Penelope Morgan; Alistair M. S. Smith; Andrew T. Hudak

2004-01-01

Land managers need cost-effective methods for mapping and characterizing fire fuels quickly and accurately. The advent of sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the Advanced Spaceborne Thermal Emission and Reflection...

Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling

Treesearch

Michael J. Falkowski; Paul E. Gessler; Penelope Morgan; Andrew T. Hudak; Alistair M. S. Smith

2005-01-01

Land managers need cost-effective methods for mapping and characterizing forest fuels quickly and accurately. The launch of satellite sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the advanced spaceborne thermal emission and...

Empirical evaluation of data normalization methods for molecular classification.

PubMed

Huang, Huei-Chung; Qin, Li-Xuan

2018-01-01

Data artifacts due to variations in experimental handling are ubiquitous in microarray studies, and they can lead to biased and irreproducible findings. A popular approach to correct for such artifacts is through post hoc data adjustment such as data normalization. Statistical methods for data normalization have been developed and evaluated primarily for the discovery of individual molecular biomarkers. Their performance has rarely been studied for the development of multi-marker molecular classifiers-an increasingly important application of microarrays in the era of personalized medicine. In this study, we set out to evaluate the performance of three commonly used methods for data normalization in the context of molecular classification, using extensive simulations based on re-sampling from a unique pair of microRNA microarray datasets for the same set of samples. The data and code for our simulations are freely available as R packages at GitHub. In the presence of confounding handling effects, all three normalization methods tended to improve the accuracy of the classifier when evaluated in an independent test data. The level of improvement and the relative performance among the normalization methods depended on the relative level of molecular signal, the distributional pattern of handling effects (e.g., location shift vs scale change), and the statistical method used for building the classifier. In addition, cross-validation was associated with biased estimation of classification accuracy in the over-optimistic direction for all three normalization methods. Normalization may improve the accuracy of molecular classification for data with confounding handling effects; however, it cannot circumvent the over-optimistic findings associated with cross-validation for assessing classification accuracy.

Improved Statistical Sampling and Accuracy with Accelerated Molecular Dynamics on Rotatable Torsions.

PubMed

Doshi, Urmi; Hamelberg, Donald

2012-11-13

In enhanced sampling techniques, the precision of the reweighted ensemble properties is often decreased due to large variation in statistical weights and reduction in the effective sampling size. To abate this reweighting problem, here, we propose a general accelerated molecular dynamics (aMD) approach in which only the rotatable dihedrals are subjected to aMD (RaMD), unlike the typical implementation wherein all dihedrals are boosted (all-aMD). Nonrotatable and improper dihedrals are marginally important to conformational changes or the different rotameric states. Not accelerating them avoids the sharp increases in the potential energies due to small deviations from their minimum energy conformations and leads to improvement in the precision of RaMD. We present benchmark studies on two model dipeptides, Ace-Ala-Nme and Ace-Trp-Nme, simulated with normal MD, all-aMD, and RaMD. We carry out a systematic comparison between the performances of both forms of aMD using a theory that allows quantitative estimation of the effective number of sampled points and the associated uncertainty. Our results indicate that, for the same level of acceleration and simulation length, as used in all-aMD, RaMD results in significantly less loss in the effective sample size and, hence, increased accuracy in the sampling of φ-ψ space. RaMD yields an accuracy comparable to that of all-aMD, from simulation lengths 5 to 1000 times shorter, depending on the peptide and the acceleration level. Such improvement in speed and accuracy over all-aMD is highly remarkable, suggesting RaMD as a promising method for sampling larger biomolecules.

Satellite and Skin Layer Effects on the Accuracy of Sea Surface Temperature Measurements from the GOES Satellites

NASA Technical Reports Server (NTRS)

Wick, Gary A.; Bates, John J.; Scott, Donna J.

2000-01-01

The latest Geostationary Operational Environmental Satellites (GOES) have facilitated significant improvements in our ability to measure sea surface temperature (SST) from geostationary satellites. Nonetheless, difficulties associated with sensor calibration and oceanic near-surface temperature gradients affect the accuracy of the measurements and our ability to estimate and interpret the diurnal cycle of the bulk SST. Overall, measurements of SST from the GOES Imagers on the GOES 8-10 satellites are shown to have very small bias (less than 0.02 K) and rms differences of between 0.6 and 0.9 K relative to buoy observations. Separate consideration of individual measurement times, however, demonstrates systematic bias variations of over 0.6 K with measurement hour. These bias variations significantly affect both the amplitude and shape of estimates of the diurnal SST cycle. Modeled estimates of the temperature difference across the oceanic cool skin and diurnal thermocline show that bias variations up to 0.3 K can result from variability in the near-surface layer. Oceanic near-surface layer and known "satellite midnight" calibration effects, however, explain only a portion of the observed bias variations, suggesting other possible calibration concerns. Methods of explicitly incorporating skin layer and diurnal thermocline effects in satellite bulk SST measurements were explored in an effort to further improve the measurement accuracy. While the approaches contain more complete physics, they do not yet significantly improve the accuracy of bulk SST measurements due to remaining uncertainties in the temperature difference across the near-surface layer.

Based on the CSI regional segmentation indoor localization algorithm

NASA Astrophysics Data System (ADS)

Zeng, Xi; Lin, Wei; Lan, Jingwei

2017-08-01

To solve the problem of high cost and low accuracy, the method of Channel State Information (CSI) regional segmentation are proposed in the indoor positioning. Because Channel State Information (CSI) stability, and effective against multipath effect, we used the Channel State Information (CSI) to segment location area. The method Acquisition CSI the influence of different link to pinpoint the location of the area. Then the method can improve the accuracy of positioning, and reduce the cost of the fingerprint localization algorithm.

Feasibility Analysis of DEM Differential Method on Tree Height Assessment wit Terra-SAR/TanDEM-X Data

NASA Astrophysics Data System (ADS)

Zhang, Wangfei; Chen, Erxue; Li, Zengyuan; Feng, Qi; Zhao, Lei

2016-08-01

DEM Differential Method is an effective and efficient way for forest tree height assessment with Polarimetric and interferometric technology, however, the assessment accuracy of it is based on the accuracy of interferometric results and DEM. Terra-SAR/TanDEM-X, which established the first spaceborne bistatic interferometer, can provide highly accurate cross-track interferometric images in the whole global without inherent accuracy limitations like temporal decorrelation and atmospheric disturbance. These characters of Terra-SAR/TandDEM-X give great potential for global or regional tree height assessment, which have been constraint by the temporal decorrelation in traditional repeat-pass interferometry. Currently, in China, it will be costly to collect high accurate DEM with Lidar. At the same time, it is also difficult to get truly representative ground survey samples to test and verify the assessment results. In this paper, we analyzed the feasibility of using TerraSAR/TanDEM-X data to assess forest tree height with current free DEM data like ASTER-GDEM and archived ground in-suit data like forest management inventory data (FMI). At first, the accuracy and of ASTER-GDEM and forest management inventory data had been assessment according to the DEM and canopy height model (CHM) extracted from Lidar data. The results show the average elevation RMSE between ASTER-GEDM and Lidar-DEM is about 13 meters, but they have high correlation with the correlation coefficient of 0.96. With a linear regression model, we can compensate ASTER-GDEM and improve its accuracy nearly to the Lidar-DEM with same scale. The correlation coefficient between FMI and CHM is 0.40. its accuracy is able to be improved by a linear regression model withinconfidence intervals of 95%. After compensation of ASTER-GDEM and FMI, we calculated the tree height in Mengla test site with DEM Differential Method. The results showed that the corrected ASTER-GDEM can effectively improve the assessment accuracy. The average assessment accuracy before and after corrected is 0.73 and 0.76, the RMSE is 5.5 and 4.4, respectively.

An orientation measurement method based on Hall-effect sensors for permanent magnet spherical actuators with 3D magnet array.

PubMed

Yan, Liang; Zhu, Bo; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-10-24

An orientation measurement method based on Hall-effect sensors is proposed for permanent magnet (PM) spherical actuators with three-dimensional (3D) magnet array. As there is no contact between the measurement system and the rotor, this method could effectively avoid friction torque and additional inertial moment existing in conventional approaches. Curved surface fitting method based on exponential approximation is proposed to formulate the magnetic field distribution in 3D space. The comparison with conventional modeling method shows that it helps to improve the model accuracy. The Hall-effect sensors are distributed around the rotor with PM poles to detect the flux density at different points, and thus the rotor orientation can be computed from the measured results and analytical models. Experiments have been conducted on the developed research prototype of the spherical actuator to validate the accuracy of the analytical equations relating the rotor orientation and the value of magnetic flux density. The experimental results show that the proposed method can measure the rotor orientation precisely, and the measurement accuracy could be improved by the novel 3D magnet array. The study result could be used for real-time motion control of PM spherical actuators.

An Improved Strong Tracking Cubature Kalman Filter for GPS/INS Integrated Navigation Systems.

PubMed

Feng, Kaiqiang; Li, Jie; Zhang, Xi; Zhang, Xiaoming; Shen, Chong; Cao, Huiliang; Yang, Yanyu; Liu, Jun

2018-06-12

The cubature Kalman filter (CKF) is widely used in the application of GPS/INS integrated navigation systems. However, its performance may decline in accuracy and even diverge in the presence of process uncertainties. To solve the problem, a new algorithm named improved strong tracking seventh-degree spherical simplex-radial cubature Kalman filter (IST-7thSSRCKF) is proposed in this paper. In the proposed algorithm, the effect of process uncertainty is mitigated by using the improved strong tracking Kalman filter technique, in which the hypothesis testing method is adopted to identify the process uncertainty and the prior state estimate covariance in the CKF is further modified online according to the change in vehicle dynamics. In addition, a new seventh-degree spherical simplex-radial rule is employed to further improve the estimation accuracy of the strong tracking cubature Kalman filter. In this way, the proposed comprehensive algorithm integrates the advantage of 7thSSRCKF’s high accuracy and strong tracking filter’s strong robustness against process uncertainties. The GPS/INS integrated navigation problem with significant dynamic model errors is utilized to validate the performance of proposed IST-7thSSRCKF. Results demonstrate that the improved strong tracking cubature Kalman filter can achieve higher accuracy than the existing CKF and ST-CKF, and is more robust for the GPS/INS integrated navigation system.

An accuracy assessment of Magellan Very Long Baseline Interferometry (VLBI)

NASA Technical Reports Server (NTRS)

Engelhardt, D. B.; Kronschnabl, G. R.; Border, J. S.

1990-01-01

Very Long Baseline Interferometry (VLBI) measurements of the Magellan spacecraft's angular position and velocity were made during July through September, 1989, during the spacecraft's heliocentric flight to Venus. The purpose of this data acquisition and reduction was to verify this data type for operational use before Magellan is inserted into Venus orbit, in August, 1990. The accuracy of these measurements are shown to be within 20 nanoradians in angular position, and within 5 picoradians/sec in angular velocity. The media effects and their calibrations are quantified; the wet fluctuating troposphere is the dominant source of measurement error for angular velocity. The charged particle effect is completely calibrated with S- and X-Band dual-frequency calibrations. Increasing the accuracy of the Earth platform model parameters, by using VLBI-derived tracking station locations consistent with the planetary ephemeris frame, and by including high frequency Earth tidal terms in the Earth rotation model, add a few nanoradians improvement to the angular position measurements. Angular velocity measurements were insensitive to these Earth platform modelling improvements.

Synchronization Design and Error Analysis of Near-Infrared Cameras in Surgical Navigation.

PubMed

Cai, Ken; Yang, Rongqian; Chen, Huazhou; Huang, Yizhou; Wen, Xiaoyan; Huang, Wenhua; Ou, Shanxing

2016-01-01

The accuracy of optical tracking systems is important to scientists. With the improvements reported in this regard, such systems have been applied to an increasing number of operations. To enhance the accuracy of these systems further and to reduce the effect of synchronization and visual field errors, this study introduces a field-programmable gate array (FPGA)-based synchronization control method, a method for measuring synchronous errors, and an error distribution map in field of view. Synchronization control maximizes the parallel processing capability of FPGA, and synchronous error measurement can effectively detect the errors caused by synchronization in an optical tracking system. The distribution of positioning errors can be detected in field of view through the aforementioned error distribution map. Therefore, doctors can perform surgeries in areas with few positioning errors, and the accuracy of optical tracking systems is considerably improved. The system is analyzed and validated in this study through experiments that involve the proposed methods, which can eliminate positioning errors attributed to asynchronous cameras and different fields of view.

Mammographic enhancement with combining local statistical measures and sliding band filter for improved mass segmentation in mammograms

NASA Astrophysics Data System (ADS)

Kim, Dae Hoe; Choi, Jae Young; Choi, Seon Hyeong; Ro, Yong Man

2012-03-01

In this study, a novel mammogram enhancement solution is proposed, aiming to improve the quality of subsequent mass segmentation in mammograms. It has been widely accepted that characteristics of masses are usually hyper-dense or uniform density with respect to its background. Also, their core parts are likely to have high-intensity values while the values of intensity tend to be decreased as the distance to core parts increases. Based on the aforementioned observations, we develop a new and effective mammogram enhancement method by combining local statistical measurements and Sliding Band Filtering (SBF). By effectively combining local statistical measurements and SBF, we are able to improve the contrast of the bright and smooth regions (which represent potential mass regions), as well as, at the same time, the regions where their surrounding gradients are converging to the centers of regions of interest. In this study, 89 mammograms were collected from the public MAIS database (DB) to demonstrate the effectiveness of the proposed enhancement solution in terms of improving mass segmentation. As for a segmentation method, widely used contour-based segmentation approach was employed. The contour-based method in conjunction with the proposed enhancement solution achieved overall detection accuracy of 92.4% with a total of 85 correct cases. On the other hand, without using our enhancement solution, overall detection accuracy of the contour-based method was only 78.3%. In addition, experimental results demonstrated the feasibility of our enhancement solution for the purpose of improving detection accuracy on mammograms containing dense parenchymal patterns.

SoRS: Social recommendation using global rating reputation and local rating similarity

NASA Astrophysics Data System (ADS)

Qian, Fulan; Zhao, Shu; Tang, Jie; Zhang, Yanping

2016-11-01

Recommendation is an important and also challenging problem in online social networks. It needs to consider not only users' personalized interests, but also social relations between users. Indeed, in practice, users are often inclined to accept recommendations from friends or opinion leaders (users with high reputations). In this paper, we present a novel recommendation framework, social recommendation using global rating reputation and local rating similarity, which combine user reputation and social similarity based on ratings. User reputation can be obtained by iteratively calculating the correlation of historical ratings of user and intrinsic qualities of items. We view the user reputation as the user's global influence and the similarity based on rating of social relation as the user's local influence, introduce it in the basic social recommender model. Thus users with high reputation have a strong influence on the others, and on the other hand, the effect of a user with low reputation has been weakened. The recommendation accuracy of proposed framework can be improved by effectively removing nature noise because of less rigorous user ratings and strengthening the effect of user influence with high reputation. We also improve the similarity based on ratings by avoiding the high similarity with the less common ratings between friends. We evaluate our approach on three datasets including Movielens, Epinions and Douban. Empirical results demonstrate that proposed framework achieves significant improvements on recommendation accuracy. User reputation and local similarity which are both based on ratings have a lot of helpful in improvement of prediction accuracy. The reputation also can help to improve the recommendation precision with the small training sets.

The zero-multipole summation method for estimating electrostatic interactions in molecular dynamics: analysis of the accuracy and application to liquid systems.

PubMed

Fukuda, Ikuo; Kamiya, Narutoshi; Nakamura, Haruki

2014-05-21

In the preceding paper [I. Fukuda, J. Chem. Phys. 139, 174107 (2013)], the zero-multipole (ZM) summation method was proposed for efficiently evaluating the electrostatic Coulombic interactions of a classical point charge system. The summation takes a simple pairwise form, but prevents the electrically non-neutral multipole states that may artificially be generated by a simple cutoff truncation, which often causes large energetic noises and significant artifacts. The purpose of this paper is to judge the ability of the ZM method by investigating the accuracy, parameter dependencies, and stability in applications to liquid systems. To conduct this, first, the energy-functional error was divided into three terms and each term was analyzed by a theoretical error-bound estimation. This estimation gave us a clear basis of the discussions on the numerical investigations. It also gave a new viewpoint between the excess energy error and the damping effect by the damping parameter. Second, with the aid of these analyses, the ZM method was evaluated based on molecular dynamics (MD) simulations of two fundamental liquid systems, a molten sodium-chlorine ion system and a pure water molecule system. In the ion system, the energy accuracy, compared with the Ewald summation, was better for a larger value of multipole moment l currently induced until l ≲ 3 on average. This accuracy improvement with increasing l is due to the enhancement of the excess-energy accuracy. However, this improvement is wholly effective in the total accuracy if the theoretical moment l is smaller than or equal to a system intrinsic moment L. The simulation results thus indicate L ∼ 3 in this system, and we observed less accuracy in l = 4. We demonstrated the origins of parameter dependencies appearing in the crossing behavior and the oscillations of the energy error curves. With raising the moment l we observed, smaller values of the damping parameter provided more accurate results and smoother behaviors with respect to cutoff length were obtained. These features can be explained, on the basis of the theoretical error analyses, such that the excess energy accuracy is improved with increasing l and that the total accuracy improvement within l ⩽ L is facilitated by a small damping parameter. Although the accuracy was fundamentally similar to the ion system, the bulk water system exhibited distinguishable quantitative behaviors. A smaller damping parameter was effective in all the practical cutoff distance, and this fact can be interpreted by the reduction of the excess subset. A lower moment was advantageous in the energy accuracy, where l = 1 was slightly superior to l = 2 in this system. However, the method with l = 2 (viz., the zero-quadrupole sum) gave accurate results for the radial distribution function. We confirmed the stability in the numerical integration for MD simulations employing the ZM scheme. This result is supported by the sufficient smoothness of the energy function. Along with the smoothness, the pairwise feature and the allowance of the atom-based cutoff mode on the energy formula lead to the exact zero total-force, ensuring the total-momentum conservations for typical MD equations of motion.

The zero-multipole summation method for estimating electrostatic interactions in molecular dynamics: Analysis of the accuracy and application to liquid systems

NASA Astrophysics Data System (ADS)

Fukuda, Ikuo; Kamiya, Narutoshi; Nakamura, Haruki

2014-05-01

In the preceding paper [I. Fukuda, J. Chem. Phys. 139, 174107 (2013)], the zero-multipole (ZM) summation method was proposed for efficiently evaluating the electrostatic Coulombic interactions of a classical point charge system. The summation takes a simple pairwise form, but prevents the electrically non-neutral multipole states that may artificially be generated by a simple cutoff truncation, which often causes large energetic noises and significant artifacts. The purpose of this paper is to judge the ability of the ZM method by investigating the accuracy, parameter dependencies, and stability in applications to liquid systems. To conduct this, first, the energy-functional error was divided into three terms and each term was analyzed by a theoretical error-bound estimation. This estimation gave us a clear basis of the discussions on the numerical investigations. It also gave a new viewpoint between the excess energy error and the damping effect by the damping parameter. Second, with the aid of these analyses, the ZM method was evaluated based on molecular dynamics (MD) simulations of two fundamental liquid systems, a molten sodium-chlorine ion system and a pure water molecule system. In the ion system, the energy accuracy, compared with the Ewald summation, was better for a larger value of multipole moment l currently induced until l ≲ 3 on average. This accuracy improvement with increasing l is due to the enhancement of the excess-energy accuracy. However, this improvement is wholly effective in the total accuracy if the theoretical moment l is smaller than or equal to a system intrinsic moment L. The simulation results thus indicate L ˜ 3 in this system, and we observed less accuracy in l = 4. We demonstrated the origins of parameter dependencies appearing in the crossing behavior and the oscillations of the energy error curves. With raising the moment l we observed, smaller values of the damping parameter provided more accurate results and smoother behaviors with respect to cutoff length were obtained. These features can be explained, on the basis of the theoretical error analyses, such that the excess energy accuracy is improved with increasing l and that the total accuracy improvement within l ⩽ L is facilitated by a small damping parameter. Although the accuracy was fundamentally similar to the ion system, the bulk water system exhibited distinguishable quantitative behaviors. A smaller damping parameter was effective in all the practical cutoff distance, and this fact can be interpreted by the reduction of the excess subset. A lower moment was advantageous in the energy accuracy, where l = 1 was slightly superior to l = 2 in this system. However, the method with l = 2 (viz., the zero-quadrupole sum) gave accurate results for the radial distribution function. We confirmed the stability in the numerical integration for MD simulations employing the ZM scheme. This result is supported by the sufficient smoothness of the energy function. Along with the smoothness, the pairwise feature and the allowance of the atom-based cutoff mode on the energy formula lead to the exact zero total-force, ensuring the total-momentum conservations for typical MD equations of motion.

A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems.

PubMed

Lyu, Weiwei; Cheng, Xianghong

2017-11-28

Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method.

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

PubMed

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-06-07

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

Are people excessive or judicious in their egocentrism? A modeling approach to understanding bias and accuracy in people's optimism.

PubMed

Windschitl, Paul D; Rose, Jason P; Stalkfleet, Michael T; Smith, Andrew R

2008-08-01

People are often egocentric when judging their likelihood of success in competitions, leading to overoptimism about winning when circumstances are generally easy and to overpessimism when the circumstances are difficult. Yet, egocentrism might be grounded in a rational tendency to favor highly reliable information (about the self) more so than less reliable information (about others). A general theory of probability called extended support theory was used to conceptualize and assess the role of egocentrism and its consequences for the accuracy of people's optimism in 3 competitions (Studies 1-3, respectively). Also, instructions were manipulated to test whether people who were urged to avoid egocentrism would show improved or worsened accuracy in their likelihood judgments. Egocentrism was found to have a potentially helpful effect on one form of accuracy, but people generally showed too much egocentrism. Debias instructions improved one form of accuracy but had no impact on another. The advantages of using the EST framework for studying optimism and other types of judgments (e.g., comparative ability judgments) are discussed. (c) 2008 APA, all rights reserved

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

PubMed Central

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-01-01

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning

PubMed Central

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-01-01

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer. PMID:27273294

Study design requirements for RNA sequencing-based breast cancer diagnostics.

PubMed

Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

The effect of spatial, spectral and radiometric factors on classification accuracy using thematic mapper data

NASA Technical Reports Server (NTRS)

Wrigley, R. C.; Acevedo, W.; Alexander, D.; Buis, J.; Card, D.

1984-01-01

An experiment of a factorial design was conducted to test the effects on classification accuracy of land cover types due to the improved spatial, spectral and radiometric characteristics of the Thematic Mapper (TM) in comparison to the Multispectral Scanner (MSS). High altitude aircraft scanner data from the Airborne Thematic Mapper instrument was acquired over central California in August, 1983 and used to simulate Thematic Mapper data as well as all combinations of the three characteristics for eight data sets in all. Results for the training sites (field center pixels) showed better classification accuracies for MSS spatial resolution, TM spectral bands and TM radiometry in order of importance.

Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review.

PubMed

Makam, Anil N; Nguyen, Oanh K; Auerbach, Andrew D

2015-06-01

Although timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. To determine whether automated real-time electronic sepsis alerts can: (1) accurately identify sepsis and (2) improve process measures and outcomes. We systematically searched MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature from database inception through June 27, 2014. Included studies that empirically evaluated 1 or both of the prespecified objectives. Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. Of 1293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n = 35,423) and 5 for the effectiveness of sepsis alerts (n = 6894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5% to 53.8%, NPV 76.5% to 99.7%, LR+ 1.2 to 145.8, and LR- 0.06 to 0.86. There was modest evidence for improvement in process measures (ie, antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts. Automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor PPV and do not improve mortality or length of stay. © 2015 Society of Hospital Medicine.

Diagnostic Accuracy and Effectiveness of Automated Electronic Sepsis Alert Systems: A Systematic Review

PubMed Central

Makam, Anil N.; Nguyen, Oanh K.; Auerbach, Andrew D.

2015-01-01

Background Although timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. Purpose To determine whether automated real-time electronic sepsis alerts can: 1) accurately identify sepsis, and 2) improve process measures and outcomes. Data Sources We systematically searched MEDLINE, Embase, The Cochrane Library, and CINAHL from database inception through June 27, 2014. Study Selection Included studies that empirically evaluated one or both of the prespecified objectives. Data Extraction Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive (PPV) and negative predictive values (NPV) and likelihood ratios (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. Data Synthesis Of 1,293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n=35,423) and 5 for the effectiveness of sepsis alerts (n=6,894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5-53.8%, NPV 76.5-99.7%; LR+ 1.2-145.8; and LR- 0.06-0.86. There was modest evidence for improvement in process measures (i.e., antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts. Conclusions Automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor positive predictive value and do not improve mortality or length of stay. PMID:25758641

Adjusted Clinical Groups: Predictive Accuracy for Medicaid Enrollees in Three States

PubMed Central

Adams, E. Kathleen; Bronstein, Janet M.; Raskind-Hood, Cheryl

2002-01-01

Actuarial split-sample methods were used to assess predictive accuracy of adjusted clinical groups (ACGs) for Medicaid enrollees in Georgia, Mississippi (lagging in managed care penetration), and California. Accuracy for two non-random groups—high-cost and located in urban poor areas—was assessed. Measures for random groups were derived with and without short-term enrollees to assess the effect of turnover on predictive accuracy. ACGs improved predictive accuracy for high-cost conditions in all States, but did so only for those in Georgia's poorest urban areas. Higher and more unpredictable expenses of short-term enrollees moderated the predictive power of ACGs. This limitation was significant in Mississippi due in part, to that State's very high proportion of short-term enrollees. PMID:12545598

Does strategy instruction on the Rey-Osterrieth Complex Figure task lead to transferred performance improvement on the Modified Taylor Complex Figure task? A randomized controlled trial in school-aged children.

PubMed

Resch, Christine; Keulers, Esther; Martens, Rosa; van Heugten, Caroline; Hurks, Petra

2018-04-05

Providing children with organizational strategy instruction on the Rey Osterrieth Complex Figure (ROCF) has previously been found to improve organizational and accuracy performance on this task. It is unknown whether strategy instruction on the ROCF would also transfer to performance improvement on copying and the recall of another complex figure. Participants were 98 typically developing children (aged 9.5-12.6 years, M = 10.6). Children completed the ROCF (copy and recall) as a pretest. Approximately a month later, they were randomized to complete the ROCF with strategy instruction in the form of a stepwise administration of the ROCF or again in the standard format. All children then copied and recalled the Modified Taylor Complex Figure (MTCF). All productions were assessed in terms of organization, accuracy and completion time. Organization scores for the MTCF did not differ for the two groups for the copy production, but did differ for the recall production, indicating transfer. Accuracy and completion times did not differ between groups. Performance on all measures, except copy accuracy, improved between pretest ROCF and posttest MTCF production for both groups, suggesting practice effects. Findings indicate that transfer of strategy instruction from one complex figure to another is only present for organization of recalled information. The increase in RCF-OSS scores did not lead to a higher accuracy or a faster copy or recall.

Predictive accuracy of combined genetic and environmental risk scores.

PubMed

Dudbridge, Frank; Pashayan, Nora; Yang, Jian

2018-02-01

The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. © 2017 WILEY PERIODICALS, INC.

Predictive accuracy of combined genetic and environmental risk scores

PubMed Central

Pashayan, Nora; Yang, Jian

2017-01-01

ABSTRACT The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. PMID:29178508

The effect of using genealogy-based haplotypes for genomic prediction

PubMed Central

2013-01-01

Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy. PMID:23496971

The effect of using genealogy-based haplotypes for genomic prediction.

PubMed

Edriss, Vahid; Fernando, Rohan L; Su, Guosheng; Lund, Mogens S; Guldbrandtsen, Bernt

2013-03-06

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.

Strain dependency of the effects of nicotine and mecamylamine in a rat model of attention.

PubMed

Hahn, Britta; Riegger, Katelyn E; Elmer, Greg I

2016-04-01

Processes of attention have a heritable component, suggesting that genetic predispositions may predict variability in the response to attention-enhancing drugs. Among lead compounds with attention-enhancing properties are nicotinic acetylcholine receptor (nAChR) agonists. This study aims to test, by comparing three rat strains, whether genotype may influence the sensitivity to nicotine in the 5-choice serial reaction time task (5-CSRTT), a rodent model of attention. Strains tested were Long Evans (LE), Sprague Dawley (SD), and Wistar rats. The 5-CSRTT requires responses to light stimuli presented randomly in one of five locations. The effect of interest was an increased percentage of responses in the correct location (accuracy), the strongest indicator of improved attention. Nicotine (0.05-0.2 mg/kg s.c.) reduced omission errors and response latency and increased anticipatory responding in all strains. In contrast, nicotine dose-dependently increased accuracy in Wistar rats only. The nAChR antagonist mecamylamine (0.75-3 mg/kg s.c.) increased omissions, slowed responses, and reduced anticipatory responding in all strains. There were no effects on accuracy, which was surprising giving the clear improvement with nicotine in the Wistar group. The findings suggest strain differences in the attention-enhancing effects of nicotine, which would indicate that genetic predispositions predict variability in the efficacy of nAChR compounds for enhancing attention. The absence of effect of mecamylamine on response accuracy may suggest a contribution of nAChR desensitization to the attention-enhancing effects of nicotine.

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks

PubMed Central

Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-01-01

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network. PMID:29267252

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

PubMed

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

The combined effects of L-theanine and caffeine on cognitive performance and mood.

PubMed

Owen, Gail N; Parnell, Holly; De Bruin, Eveline A; Rycroft, Jane A

2008-08-01

The aim of this study was to compare 50 mg caffeine, with and without 100 mg L-theanine, on cognition and mood in healthy volunteers. The effects of these treatments on word recognition, rapid visual information processing, critical flicker fusion threshold, attention switching and mood were compared to placebo in 27 participants. Performance was measured at baseline and again 60 min and 90 min after each treatment (separated by a 7-day washout). Caffeine improved subjective alertness at 60 min and accuracy on the attention-switching task at 90 min. The L-theanine and caffeine combination improved both speed and accuracy of performance of the attention-switching task at 60 min, and reduced susceptibility to distracting information in the memory task at both 60 min and 90 min. These results replicate previous evidence which suggests that L-theanine and caffeine in combination are beneficial for improving performance on cognitively demanding tasks.

An improved recommendation algorithm via weakening indirect linkage effect

NASA Astrophysics Data System (ADS)

Chen, Guang; Qiu, Tian; Shen, Xiao-Quan

2015-07-01

We propose an indirect-link-weakened mass diffusion method (IMD), by considering the indirect linkage and the source object heterogeneity effect in the mass diffusion (MD) recommendation method. Experimental results on the MovieLens, Netflix, and RYM datasets show that, the IMD method greatly improves both the recommendation accuracy and diversity, compared with a heterogeneity-weakened MD method (HMD), which only considers the source object heterogeneity. Moreover, the recommendation accuracy of the cold objects is also better elevated in the IMD than the HMD method. It suggests that eliminating the redundancy induced by the indirect linkages could have a prominent effect on the recommendation efficiency in the MD method. Project supported by the National Natural Science Foundation of China (Grant No. 11175079) and the Young Scientist Training Project of Jiangxi Province, China (Grant No. 20133BCB23017).

Perceptual experience and posttest improvements in perceptual accuracy and consistency.

PubMed

Wagman, Jeffrey B; McBride, Dawn M; Trefzger, Amanda J

2008-08-01

Two experiments investigated the relationship between perceptual experience (during practice) and posttest improvements in perceptual accuracy and consistency. Experiment 1 investigated the potential relationship between how often knowledge of results (KR) is provided during a practice session and posttest improvements in perceptual accuracy. Experiment 2 investigated the potential relationship between how often practice (PR) is provided during a practice session and posttest improvements in perceptual consistency. The results of both experiments are consistent with previous findings that perceptual accuracy improves only when practice includes KR and that perceptual consistency improves regardless of whether practice includes KR. In addition, the results showed that although there is a relationship between how often KR is provided during a practice session and posttest improvements in perceptual accuracy, there is no relationship between how often PR is provided during a practice session and posttest improvements in consistency.

SU-E-T-13: A Feasibility Study of the Use of Hybrid Computational Phantoms for Improved Historical Dose Reconstruction in the Study of Late Radiation Effects for Hodgkin's Lymphoma

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

Petroccia, H; O'Reilly, S; Bolch, W

Purpose: Radiation-induced cancer effects are well-documented following radiotherapy. Further investigation is needed to more accurately determine a dose-response relationship for late radiation effects. Recent dosimetry studies tend to use representative patients (Taylor 2009) or anthropomorphic phantoms (Wirth 2008) for estimating organ mean doses. In this study, we compare hybrid computational phantoms to patient-specific voxel phantoms to test the accuracy of University of Florida Hybrid Phantom Library (UFHP Library) for historical dose reconstructions. Methods: A cohort of 10 patients with CT images was used to reproduce the data that was collected historically for Hodgkin's lymphoma patients (i.e. caliper measurements and photographs).more » Four types of phantoms were generated to show a range of refinement from reference hybrid-computational phantom to patient-specific phantoms. Each patient is matched to a reference phantom from the UFHP Library based on height and weight. The reference phantom is refined in the anterior/posterior direction to create a ‘caliper-scaled phantom’. A photograph is simulated using a surface rendering from segmented CT images. Further refinement in the lateral direction is performed using ratios from a simulated-photograph to create a ‘photograph and caliper-scaled phantom’; breast size and position is visually adjusted. Patient-specific hybrid phantoms, with matched organ volumes, are generated and show the capabilities of the UF Hybrid Phantom Library. Reference, caliper-scaled, photograph and caliper-scaled, and patient-specific hybrid phantoms are compared with patient-specific voxel phantoms to determine the accuracy of the study. Results: Progression from reference phantom to patient specific hybrid shows good agreement with the patient specific voxel phantoms. Each stage of refinement shows an overall trend of improvement in dose accuracy within the study, which suggests that computational phantoms can show improved accuracy in historical dose estimates. Conclusion: Computational hybrid phantoms show promise for improved accuracy within retrospective studies when CTs and other x-ray images are not available.« less

A code-aided carrier synchronization algorithm based on improved nonbinary low-density parity-check codes

NASA Astrophysics Data System (ADS)

Bai, Cheng-lin; Cheng, Zhi-hui

2016-09-01

In order to further improve the carrier synchronization estimation range and accuracy at low signal-to-noise ratio ( SNR), this paper proposes a code-aided carrier synchronization algorithm based on improved nonbinary low-density parity-check (NB-LDPC) codes to study the polarization-division-multiplexing coherent optical orthogonal frequency division multiplexing (PDM-CO-OFDM) system performance in the cases of quadrature phase shift keying (QPSK) and 16 quadrature amplitude modulation (16-QAM) modes. The simulation results indicate that this algorithm can enlarge frequency and phase offset estimation ranges and enhance accuracy of the system greatly, and the bit error rate ( BER) performance of the system is improved effectively compared with that of the system employing traditional NB-LDPC code-aided carrier synchronization algorithm.

Cognitive accuracy and intelligent executive function in the brain and in business.

PubMed

Bailey, Charles E

2007-11-01

This article reviews research on cognition, language, organizational culture, brain, behavior, and evolution to posit the value of operating with a stable reference point based on cognitive accuracy and a rational bias. Drawing on rational-emotive behavioral science, social neuroscience, and cognitive organizational science on the one hand and a general model of brain and frontal lobe executive function on the other, I suggest implications for organizational success. Cognitive thought processes depend on specific brain structures functioning as effectively as possible under conditions of cognitive accuracy. However, typical cognitive processes in hierarchical business structures promote the adoption and application of subjective organizational beliefs and, thus, cognitive inaccuracies. Applying informed frontal lobe executive functioning to cognition, emotion, and organizational behavior helps minimize the negative effects of indiscriminate application of personal and cultural belief systems to business. Doing so enhances cognitive accuracy and improves communication and cooperation. Organizations operating with cognitive accuracy will tend to respond more nimbly to market pressures and achieve an overall higher level of performance and employee satisfaction.

Improving the spectral measurement accuracy based on temperature distribution and spectra-temperature relationship

NASA Astrophysics Data System (ADS)

Li, Zhe; Feng, Jinchao; Liu, Pengyu; Sun, Zhonghua; Li, Gang; Jia, Kebin

2018-05-01

Temperature is usually considered as a fluctuation in near-infrared spectral measurement. Chemometric methods were extensively studied to correct the effect of temperature variations. However, temperature can be considered as a constructive parameter that provides detailed chemical information when systematically changed during the measurement. Our group has researched the relationship between temperature-induced spectral variation (TSVC) and normalized squared temperature. In this study, we focused on the influence of temperature distribution in calibration set. Multi-temperature calibration set selection (MTCS) method was proposed to improve the prediction accuracy by considering the temperature distribution of calibration samples. Furthermore, double-temperature calibration set selection (DTCS) method was proposed based on MTCS method and the relationship between TSVC and normalized squared temperature. We compare the prediction performance of PLS models based on random sampling method and proposed methods. The results from experimental studies showed that the prediction performance was improved by using proposed methods. Therefore, MTCS method and DTCS method will be the alternative methods to improve prediction accuracy in near-infrared spectral measurement.

Randomized nutrition education intervention to improve carbohydrate counting in adolescents with type 1 diabetes study: is more intensive education needed?

PubMed

Spiegel, Gail; Bortsov, Andrey; Bishop, Franziska K; Owen, Darcy; Klingensmith, Georgeanna J; Mayer-Davis, Elizabeth J; Maahs, David M

2012-11-01

Youth with type 1 diabetes do not count carbohydrates accurately, yet it is an important strategy in blood glucose control. The study objective was to determine whether a nutrition education intervention would improve carbohydrate counting accuracy and glycemic control. We conducted a randomized, controlled nutrition intervention trial that was recruited from February 2009 to February 2010. Youth (12 to 18 years of age, n = 101) with type 1 diabetes were screened to identify those with poor carbohydrate counting accuracy, using a previously developed carbohydrate counting accuracy test covering commonly consumed foods and beverage items presented in six mixed meals and two snacks. All participants (n = 66, age = 15 ± 3 years, 41 male, diabetes duration = 6 ± 4 years, hemoglobin A1c [HbA1c] = 8.3% ± 1.1%) were randomized to the control or intervention group at the baseline visit. The intervention group attended a 90-minute class with a registered dietitian/certified diabetes educator and twice kept 3-day food records, which were used to review carbohydrate counting progress. Carbohydrate counting accuracy (measured as described) and HbA1c were evaluated at baseline and 3 months to determine the effectiveness of the intervention. t Tests, Spearman correlations, and repeated measures models were used. At baseline, carbohydrate content was over- and underestimated in 16 and 5 of 29 food items, respectively. When foods were presented as mixed meals, participants either significantly over- or underestimated 10 of the 9 meals and 4 snacks. After 3 months of follow-up, HbA1c decreased in both the intervention and control groups by -0.19% ± 0.12% (P = 0.12) and -0.08% ± 0.11% (P = 0.51), respectively; however, the overall intervention effect was not statistically significant for change in HbA1c or carbohydrate counting accuracy. More intensive intervention might be required to improve adolescents' carbohydrate counting accuracy and nutrition management of type 1 diabetes. Additional research is needed to translate nutrition education into improved health outcomes. Copyright © 2012 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

60 seconds to survival: A pilot study of a disaster triage video game for prehospital providers.

PubMed

Cicero, Mark X; Whitfill, Travis; Munjal, Kevin; Madhok, Manu; Diaz, Maria Carmen G; Scherzer, Daniel J; Walsh, Barbara M; Bowen, Angela; Redlener, Michael; Goldberg, Scott A; Symons, Nadine; Burkett, James; Santos, Joseph C; Kessler, David; Barnicle, Ryan N; Paesano, Geno; Auerbach, Marc A

2017-01-01

Disaster triage training for emergency medical service (EMS) providers is not standardized. Simulation training is costly and time-consuming. In contrast, educational video games enable low-cost and more time-efficient standardized training. We hypothesized that players of the video game "60 Seconds to Survival" (60S) would have greater improvements in disaster triage accuracy compared to control subjects who did not play 60S. Participants recorded their demographics and highest EMS training level and were randomized to play 60S (intervention) or serve as controls. At baseline, all participants completed a live school-shooting simulation in which manikins and standardized patients depicted 10 adult and pediatric victims. The intervention group then played 60S at least three times over the course of 13 weeks (time 2). Players triaged 12 patients in three scenarios (school shooting, house fire, tornado), and received in-game performance feedback. At time 2, the same live simulation was conducted for all participants. Controls had no disaster training during the study. The main outcome was improvement in triage accuracy in live simulations from baseline to time 2. Physicians and EMS providers predetermined expected triage level (RED/YELLOW/GREEN/BLACK) via modified Delphi method. There were 26 participants in the intervention group and 21 in the control group. There was no difference in gender, level of training, or years of EMS experience (median 5.5 years intervention, 3.5 years control, p = 0.49) between the groups. At baseline, both groups demonstrated median triage accuracy of 80 percent (IQR 70-90 percent, p = 0.457). At time 2, the intervention group had a significant improvement from baseline (median accuracy = 90 percent [IQR: 80-90 percent], p = 0.005), while the control group did not (median accuracy = 80 percent [IQR:80-95], p = 0.174). However, the mean improvement from baseline was not significant between the two groups (difference = 6.5, p = 0.335). The intervention demonstrated a significant improvement in accuracy from baseline to time 2 while the control did not. However, there was no significant difference in the improvement between the intervention and control groups. These results may be due to small sample size. Future directions include assessment of the game's effect on triage accuracy with a larger, multisite site cohort and iterative development to improve 60S.

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Dissolved oxygen content prediction in crab culture using a hybrid intelligent method

PubMed Central

Yu, Huihui; Chen, Yingyi; Hassan, ShahbazGul; Li, Daoliang

2016-01-01

A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds. PMID:27270206

Dissolved oxygen content prediction in crab culture using a hybrid intelligent method.

PubMed

Yu, Huihui; Chen, Yingyi; Hassan, ShahbazGul; Li, Daoliang

2016-06-08

A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds.

Improving geolocation and spatial accuracies with the modular integrated avionics group (MIAG)

NASA Astrophysics Data System (ADS)

Johnson, Einar; Souter, Keith

1996-05-01

The modular integrated avionics group (MIAG) is a single unit approach to combining position, inertial and baro-altitude/air data sensors to provide optimized navigation, guidance and control performance. Lear Astronics Corporation is currently working within the navigation community to upgrade existing MIAG performance with precise GPS positioning mechanization tightly integrated with inertial, baro and other sensors. Among the immediate benefits are the following: (1) accurate target location in dynamic conditions; (2) autonomous launch and recovery using airborne avionics only; (3) precise flight path guidance; and (4) improved aircraft and payload stability information. This paper will focus on the impact of using the MIAG with its multimode navigation accuracies on the UAV targeting mission. Gimbaled electro-optical sensors mounted on a UAV can be used to determine ground coordinates of a target at the center of the field of view by a series of vector rotation and scaling computations. The accuracy of the computed target coordinates is dependent on knowing the UAV position and the UAV-to-target offset computation. Astronics performed a series of simulations to evaluate the effects that the improved angular and position data available from the MIAG have on target coordinate accuracy.

Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

PubMed

Trakoolwilaiwan, Thanawin; Behboodi, Bahareh; Lee, Jaeseok; Kim, Kyungsoo; Choi, Ji-Woong

2018-01-01

The aim of this work is to develop an effective brain-computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand motor execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

Improving LUC estimation accuracy with multiple classification system for studying impact of urbanization on watershed flood

NASA Astrophysics Data System (ADS)

Dou, P.

2017-12-01

Guangzhou has experienced a rapid urbanization period called "small change in three years and big change in five years" since the reform of China, resulting in significant land use/cover changes(LUC). To overcome the disadvantages of single classifier for remote sensing image classification accuracy, a multiple classifier system (MCS) is proposed to improve the quality of remote sensing image classification. The new method combines advantages of different learning algorithms, and achieves higher accuracy (88.12%) than any single classifier did. With the proposed MCS, land use/cover (LUC) on Landsat images from 1987 to 2015 was obtained, and the LUCs were used on three watersheds (Shijing river, Chebei stream, and Shahe stream) to estimate the impact of urbanization on water flood. The results show that with the high accuracy LUC, the uncertainty in flood simulations are reduced effectively (for Shijing river, Chebei stream, and Shahe stream, the uncertainty reduced 15.5%, 17.3% and 19.8% respectively).

Two sides of the same coin: Monetary incentives concurrently improve and bias confidence judgments

PubMed Central

Lebreton, Maël; Slieker, Matthijs J.; Nooitgedacht, Jip S.; van Holst, Ruth J.; Luigjes, Judy

2018-01-01

Decisions are accompanied by a feeling of confidence, that is, a belief about the decision being correct. Confidence accuracy is critical, notably in high-stakes situations such as medical or financial decision-making. We investigated how incentive motivation influences confidence accuracy by combining a perceptual task with a confidence incentivization mechanism. By varying the magnitude and valence (gains or losses) of monetary incentives, we orthogonalized their motivational and affective components. Corroborating theories of rational decision-making and motivation, our results first reveal that the motivational value of incentives improves aspects of confidence accuracy. However, in line with a value-confidence interaction hypothesis, we further show that the affective value of incentives concurrently biases confidence reports, thus degrading confidence accuracy. Finally, we demonstrate that the motivational and affective effects of incentives differentially affect how confidence builds on perceptual evidence. Together, these findings may provide new hints about confidence miscalibration in healthy or pathological contexts. PMID:29854944

Technical editing of research reports in biomedical journals.

PubMed

Wager, Elizabeth; Middleton, Philippa

2008-10-08

Most journals try to improve their articles by technical editing processes such as proof-reading, editing to conform to 'house styles', grammatical conventions and checking accuracy of cited references. Despite the considerable resources devoted to technical editing, we do not know whether it improves the accessibility of biomedical research findings or the utility of articles. This is an update of a Cochrane methodology review first published in 2003. To assess the effects of technical editing on research reports in peer-reviewed biomedical journals, and to assess the level of accuracy of references to these reports. We searched The Cochrane Library Issue 2, 2007; MEDLINE (last searched July 2006); EMBASE (last searched June 2007) and checked relevant articles for further references. We also searched the Internet and contacted researchers and experts in the field. Prospective or retrospective comparative studies of technical editing processes applied to original research articles in biomedical journals, as well as studies of reference accuracy. Two review authors independently assessed each study against the selection criteria and assessed the methodological quality of each study. One review author extracted the data, and the second review author repeated this. We located 32 studies addressing technical editing and 66 surveys of reference accuracy. Only three of the studies were randomised controlled trials. A 'package' of largely unspecified editorial processes applied between acceptance and publication was associated with improved readability in two studies and improved reporting quality in another two studies, while another study showed mixed results after stricter editorial policies were introduced. More intensive editorial processes were associated with fewer errors in abstracts and references. Providing instructions to authors was associated with improved reporting of ethics requirements in one study and fewer errors in references in two studies, but no difference was seen in the quality of abstracts in one randomised controlled trial. Structuring generally improved the quality of abstracts, but increased their length. The reference accuracy studies showed a median citation error rate of 38% and a median quotation error rate of 20%. Surprisingly few studies have evaluated the effects of technical editing rigorously. However there is some evidence that the 'package' of technical editing used by biomedical journals does improve papers. A substantial number of references in biomedical articles are cited or quoted inaccurately.

Effects of training and simulated combat stress on leg tourniquet application accuracy, time, and effectiveness.

PubMed

Schreckengaust, Richard; Littlejohn, Lanny; Zarow, Gregory J

2014-02-01

The lower extremity tourniquet failure rate remains significantly higher in combat than in preclinical testing, so we hypothesized that tourniquet placement accuracy, speed, and effectiveness would improve during training and decline during simulated combat. Navy Hospital Corpsman (N = 89), enrolled in a Tactical Combat Casualty Care training course in preparation for deployment, applied Combat Application Tourniquet (CAT) and the Special Operations Forces Tactical Tourniquet (SOFT-T) on day 1 and day 4 of classroom training, then under simulated combat, wherein participants ran an obstacle course to apply a tourniquet while wearing full body armor and avoiding simulated small arms fire (paint balls). Application time and pulse elimination effectiveness improved day 1 to day 4 (p < 0.005). Under simulated combat, application time slowed significantly (p < 0.001), whereas accuracy and effectiveness declined slightly. Pulse elimination was poor for CAT (25% failure) and SOFT-T (60% failure) even in classroom conditions following training. CAT was more quickly applied (p < 0.005) and more effective (p < 0.002) than SOFT-T. Training fostered fast and effective application of leg tourniquets while performance declined under simulated combat. The inherent efficacy of tourniquet products contributes to high failure rates under combat conditions, pointing to the need for superior tourniquets and for rigorous deployment preparation training in simulated combat scenarios. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

The Eddington Experiment during the 2017 Total Solar Eclipse Will Improve On Prior Work by Near Two Orders of Magnitude

NASA Astrophysics Data System (ADS)

Schaefer, Bradley E.

2017-06-01

The original Eddington experiment (measuring the gravitational bending of light for stars near a totally eclipsed Sun) in 1919 was one of the most famous and important experiments in all physics, becoming the iconic proof of Einstein's General Relativity (GR). The Eddington experiment has been run successfully for only 7 eclipses, last in 1973, never getting much better than ~10% measurement accuracy. Since then, precision tests of various predictions of GR have been big-time forefront physics, for example the recent discovery of gravitational waves with LIGO. The best measure of the gravitational bending of light comes from radio wavelengths with VLBI, where limits of 0.045% to 0.012% have been reported in the last decade.A modern version of the Eddington experiment can and should be run for the 21 August 2017 total solar eclipse, when we can improve on the historic results by orders of magnitude. This possibility of greatly improving the Eddington experiment has only just become feasible in the last few years, with the introduction of off-the-shelf CCD cameras with >4k pixels on a side. The near-optimal set of equipment is a 4-inch f/10 refractor with a 4096x4096 CCD all on a GOTO mount. With this, a 7-second image will record 101 unsaturated stars with angular distances from the center of the Sun from 41' to 86', each with centering accuracy of 0.06" to 0.25". A single exposure by itself will measure the gravitational bending of light to 2.3% accuracy. With Gaia positions, and many stars recorded over a large field, plus calibration images from the night sky, all known systematic errors will be much smaller than the final accuracy for any single observer. With many images during totality, one observer will measure the GR effect to an accuracy of 0.59%. With many observers, the accuracy will improve by a factor of the square root of the number of observers.On an independent track, a casual observer can now readily test Einstein's GR by better than anyone has done previously. That is, a 2k CCD with a long telephoto lens can get better than 10% accuracy. With this, laypeople can test Einstein for themselves, and they can see the effects of GR for themselves.

Effects of technical editing in biomedical journals: a systematic review.

PubMed

Wager, Elizabeth; Middleton, Philippa

2002-06-05

Technical editing supposedly improves the accuracy and clarity of journal articles. We examined evidence of its effects on research reports in biomedical journals. Subset of a systematic review using Cochrane methods, searching MEDLINE, EMBASE, and other databases from earliest entries to February 2000 by using inclusive search terms; hand searching relevant journals. We selected comparative studies of the effects of editorial processes on original research articles between acceptance and publication in biomedical journals. Two reviewers assessed each study and performed independent data extraction. The 11 studies on technical editing indicate that it improves the readability of articles slightly (as measured by Gunning Fog and Flesch reading ease scores), may improve other aspects of their quality, can increase the accuracy of references and quotations, and raises the quality of abstracts. Supplying authors with abstract preparation instructions had no discernible effect. Considering the time and resources devoted to technical editing, remarkably little is know about its effects or the effects of imposing different house styles. Studies performed at 3 journals employing relatively large numbers of professional technical editors suggest that their editorial processes are associated with increases in readability and quality of articles, but these findings may not be generalizable to other journals.

Improved assessment of accuracy and performance using a rotational paper-based device for multiplexed detection of heavy metals.

PubMed

Sun, Xiange; Li, Bowei; Qi, Anjin; Tian, Chongguo; Han, Jinglong; Shi, Yajun; Lin, Bingcheng; Chen, Lingxin

2018-02-01

In this work, a novel rotational microfluidic paper-based device was developed to improve the accuracy and performance of the multiplexed colorimetric detection by effectively avoiding the diffusion of colorimetric reagent on the detection zone. The integrated paper-based rotational valves were used to control the connection or disconnection between detection zones and fluid channels. Based on the manipulation of the rotational valves, this rotational paper-based device could prevent the random diffusion of colorimetric reagent and reduce the error of quantitative analysis considerably. The multiplexed colorimetric detection of heavy metals Ni(II), Cu(II) and Cr(VI) were implemented on the rotational device and the detection limits could be found to be 4.8, 1.6, and 0.18mg/L, respectively. The developed rotational device showed the great advantage in improving the detection accuracy and was expected to be a low-cost, portable analytical platform for the on-site detection. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in skill and physical fitness following training in talent-identified volleyball players.

PubMed

Gabbett, Tim; Georgieff, Boris; Anderson, Steve; Cotton, Brad; Savovic, Darko; Nicholson, Lee

2006-02-01

This study investigated the effect of a skill-based training program on measurements of skill and physical fitness in talent-identified volleyball players. Twenty-six talented junior volleyball players (mean +/- SE age, 15.5 +/- 0.2 years) participated in an 8-week skill-based training program that included 3 skill-based court sessions per week. Skills sessions were designed to develop passing, setting, serving, spiking, and blocking technique and accuracy as well as game tactics and positioning skills. Coaches used a combination of technical and instructional coaching, coupled with skill-based games to facilitate learning. Subjects performed measurements of skill (passing, setting, serving, and spiking technique and accuracy), standard anthropometry (height, standing-reach height, body mass, and sum of 7 skinfolds), lower-body muscular power (vertical jump, spike jump), upper-body muscular power (overhead medicine-ball throw), speed (5- and 10-m sprint), agility (T-test), and maximal aerobic power (multistage fitness test) before and after training. Training induced significant (p < 0.05) improvements in spiking, setting, and passing accuracy and spiking and passing technique. Compared with pretraining, there were significant (p < 0.05) improvements in 5- and 10-m speed and agility. There were no significant differences between pretraining and posttraining for body mass, skinfold thickness, lower-body muscular power, upper-body muscular power, and maximal aerobic power. These findings demonstrate that skill-based volleyball training improves spiking, setting, and passing accuracy and spiking and passing technique, but has little effect on the physiological and anthropometric characteristics of players.

[Using TRM to Enhance the Accuracy of Ventilator-Associated Pneumonia Preventive Measures Implemented by Neonatal Intensive Care Unit Medical Staffs].

PubMed

Huang, Yu-Ting; Huang, Chao-Ya; Su, Hsiu-Ya; Ma, Chen-Te

2018-06-01

Ventilator-associated pneumonia (VAP) is a common healthcare-associated infection in the neonatal intensive care unit (NICU). The average VAP infection density was 4.7‰ in our unit between June and August 2015. The results of a status survey indicated that in-service education lacked specialization, leading to inadequate awareness among staffs regarding the proper care of newborns with VAP and a lack of related care guides. This, in turn, resulted in inconsistencies in care measures for newborns with VAP. To improve the accuracy of implementation of preventive measures for VAP among medical staffs and reduce the density of VAP infections in the NICU. Conduct a literature search and adopt medical team resources management methods; establish effective team communication; establish monitoring mechanisms and incentives; establish mandatory in-service specialization education contents and a VAP preventive care guide exclusively for newborns as a reference for medical staffs during care execution; install additional equipment and aids and set reminders to ensure the implementation of VAP preventive measures. The accuracy rate of preventive measure execution by medical staffs improved from 70.1% to 97.9% and the VAP infection density in the NICU decreased from 4.7‰ to 0.52‰. Team integration effectively improved the accuracy of implementation of VAP-prevention measures, reduced the density of VAP infections, enhanced quality of care, and ensured that newborns received care that was more in line with specialization needs.

Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations.

PubMed

Moghaddar, N; van der Werf, J H J

2017-12-01

The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on "average information restricted maximum likelihood" using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model. © 2017 Blackwell Verlag GmbH.

Evaluating the accuracy of SHAPE-directed RNA secondary structure predictions

PubMed Central

Sükösd, Zsuzsanna; Swenson, M. Shel; Kjems, Jørgen; Heitsch, Christine E.

2013-01-01

Recent advances in RNA structure determination include using data from high-throughput probing experiments to improve thermodynamic prediction accuracy. We evaluate the extent and nature of improvements in data-directed predictions for a diverse set of 16S/18S ribosomal sequences using a stochastic model of experimental SHAPE data. The average accuracy for 1000 data-directed predictions always improves over the original minimum free energy (MFE) structure. However, the amount of improvement varies with the sequence, exhibiting a correlation with MFE accuracy. Further analysis of this correlation shows that accurate MFE base pairs are typically preserved in a data-directed prediction, whereas inaccurate ones are not. Thus, the positive predictive value of common base pairs is consistently higher than the directed prediction accuracy. Finally, we confirm sequence dependencies in the directability of thermodynamic predictions and investigate the potential for greater accuracy improvements in the worst performing test sequence. PMID:23325843

An Improved Method of Heterogeneity Compensation for the Convolution / Superposition Algorithm

NASA Astrophysics Data System (ADS)

Jacques, Robert; McNutt, Todd

2014-03-01

Purpose: To improve the accuracy of convolution/superposition (C/S) in heterogeneous material by developing a new algorithm: heterogeneity compensated superposition (HCS). Methods: C/S has proven to be a good estimator of the dose deposited in a homogeneous volume. However, near heterogeneities electron disequilibrium occurs, leading to the faster fall-off and re-buildup of dose. We propose to filter the actual patient density in a position and direction sensitive manner, allowing the dose deposited near interfaces to be increased or decreased relative to C/S. We implemented the effective density function as a multivariate first-order recursive filter and incorporated it into GPU-accelerated, multi-energetic C/S implementation. We compared HCS against C/S using the ICCR 2000 Monte-Carlo accuracy benchmark, 23 similar accuracy benchmarks and 5 patient cases. Results: Multi-energetic HCS increased the dosimetric accuracy for the vast majority of voxels; in many cases near Monte-Carlo results were achieved. We defined the per-voxel error, %|mm, as the minimum of the distance to agreement in mm and the dosimetric percentage error relative to the maximum MC dose. HCS improved the average mean error by 0.79 %|mm for the patient volumes; reducing the average mean error from 1.93 %|mm to 1.14 %|mm. Very low densities (i.e. < 0.1 g / cm3) remained problematic, but may be solvable with a better filter function. Conclusions: HCS improved upon C/S's density scaled heterogeneity correction with a position and direction sensitive density filter. This method significantly improved the accuracy of the GPU based algorithm reaching the accuracy levels of Monte Carlo based methods with performance in a few tenths of seconds per beam. Acknowledgement: Funding for this research was provided by the NSF Cooperative Agreement EEC9731748, Elekta / IMPAC Medical Systems, Inc. and the Johns Hopkins University. James Satterthwaite provided the Monte Carlo benchmark simulations.

Effectiveness of Variable-Gain Kalman Filter Based on Angle Error Calculated from Acceleration Signals in Lower Limb Angle Measurement with Inertial Sensors

PubMed Central

Watanabe, Takashi

2013-01-01

The wearable sensor system developed by our group, which measured lower limb angles using Kalman-filtering-based method, was suggested to be useful in evaluation of gait function for rehabilitation support. However, it was expected to reduce variations of measurement errors. In this paper, a variable-Kalman-gain method based on angle error that was calculated from acceleration signals was proposed to improve measurement accuracy. The proposed method was tested comparing to fixed-gain Kalman filter and a variable-Kalman-gain method that was based on acceleration magnitude used in previous studies. First, in angle measurement in treadmill walking, the proposed method measured lower limb angles with the highest measurement accuracy and improved significantly foot inclination angle measurement, while it improved slightly shank and thigh inclination angles. The variable-gain method based on acceleration magnitude was not effective for our Kalman filter system. Then, in angle measurement of a rigid body model, it was shown that the proposed method had measurement accuracy similar to or higher than results seen in other studies that used markers of camera-based motion measurement system fixing on a rigid plate together with a sensor or on the sensor directly. The proposed method was found to be effective in angle measurement with inertial sensors. PMID:24282442

The Analysis of Burrows Recognition Accuracy in XINJIANG'S Pasture Area Based on Uav Visible Images with Different Spatial Resolution

NASA Astrophysics Data System (ADS)

Sun, D.; Zheng, J. H.; Ma, T.; Chen, J. J.; Li, X.

2018-04-01

The rodent disaster is one of the main biological disasters in grassland in northern Xinjiang. The eating and digging behaviors will cause the destruction of ground vegetation, which seriously affected the development of animal husbandry and grassland ecological security. UAV low altitude remote sensing, as an emerging technique with high spatial resolution, can effectively recognize the burrows. However, how to select the appropriate spatial resolution to monitor the calamity of the rodent disaster is the first problem we need to pay attention to. The purpose of this study is to explore the optimal spatial scale on identification of the burrows by evaluating the impact of different spatial resolution for the burrows identification accuracy. In this study, we shoot burrows from different flight heights to obtain visible images of different spatial resolution. Then an object-oriented method is used to identify the caves, and we also evaluate the accuracy of the classification. We found that the highest classification accuracy of holes, the average has reached more than 80 %. At the altitude of 24 m and the spatial resolution of 1cm, the accuracy of the classification is the highest We have created a unique and effective way to identify burrows by using UAVs visible images. We draw the following conclusion: the best spatial resolution of burrows recognition is 1 cm using DJI PHANTOM-3 UAV, and the improvement of spatial resolution does not necessarily lead to the improvement of classification accuracy. This study lays the foundation for future research and can be extended to similar studies elsewhere.

Effect of Lamina Thickness of Prepreg on the Surface Accuracy of Carbon Fiber Composite Space Mirrors

NASA Astrophysics Data System (ADS)

Yang, Zhiyong; Tang, Zhanwen; Xie, Yongjie; Shi, Hanqiao; Zhang, Boming; Guo, Hongjun

2018-02-01

Composite space mirror can completely replicate the high-precision surface of mould by replication process, but the actual surface accuracy of the replication composite mirror always decreases. Lamina thickness of prepreg affects the layers and layup sequence of composite space mirror, and which would affect surface accuracy of space mirror. In our research, two groups of contrasting cases through finite element analyses (FEA) and comparative experiments were studied; the effect of different lamina thicknesses of prepreg and corresponding lay-up sequences was focused as well. We describe a special analysis model, validated process and result analysis. The simulated and measured surface figures both get the same conclusion. Reducing lamina thickness of prepreg used in replicating composite space mirror is propitious to optimal design of layup sequence for fabricating composite mirror, and could improve its surface accuracy.

The Effects of Irlen Colored Lenses on Students' Specific Reading Skills and Their Perception of Ability: A 12-Month Validity Study.

ERIC Educational Resources Information Center

Robinson, Gregory L. W.; Conway, Robert N. F.

1990-01-01

The study examined the effectiveness of the use of nonoptical tinted (Irlen) lenses with 44 children (ages 9-16) with reading disabilities. Evaluation after 6 and 12 months indicated a significant improvement in attitude to school and to basic academic skills. Reading comprehension and accuracy, but not rate, were also significantly improved.…

Effect of conductance linearity and multi-level cell characteristics of TaOx-based synapse device on pattern recognition accuracy of neuromorphic system

NASA Astrophysics Data System (ADS)

Sung, Changhyuck; Lim, Seokjae; Kim, Hyungjun; Kim, Taesu; Moon, Kibong; Song, Jeonghwan; Kim, Jae-Joon; Hwang, Hyunsang

2018-03-01

To improve the classification accuracy of an image data set (CIFAR-10) by using analog input voltage, synapse devices with excellent conductance linearity (CL) and multi-level cell (MLC) characteristics are required. We analyze the CL and MLC characteristics of TaOx-based filamentary resistive random access memory (RRAM) to implement the synapse device in neural network hardware. Our findings show that the number of oxygen vacancies in the filament constriction region of the RRAM directly controls the CL and MLC characteristics. By adopting a Ta electrode (instead of Ti) and the hot-forming step, we could form a dense conductive filament. As a result, a wide range of conductance levels with CL is achieved and significantly improved image classification accuracy is confirmed.

Predicting Earth orientation changes from global forecasts of atmosphere-hydrosphere dynamics

NASA Astrophysics Data System (ADS)

Dobslaw, Henryk; Dill, Robert

2018-02-01

Effective Angular Momentum (EAM) functions obtained from global numerical simulations of atmosphere, ocean, and land surface dynamics are routinely processed by the Earth System Modelling group at Deutsches GeoForschungsZentrum. EAM functions are available since January 1976 with up to 3 h temporal resolution. Additionally, 6 days-long EAM forecasts are routinely published every day. Based on hindcast experiments with 305 individual predictions distributed over 15 months, we demonstrate that EAM forecasts improve the prediction accuracy of the Earth Orientation Parameters at all forecast horizons between 1 and 6 days. At day 6, prediction accuracy improves down to 1.76 mas for the terrestrial pole offset, and 2.6 mas for Δ UT1, which correspond to an accuracy increase of about 41% over predictions published in Bulletin A by the International Earth Rotation and Reference System Service.

IMEKO TC1-TC7 Symposium in London: The assurance as a result of blood chemical analysis by ISO-GUM and QE

NASA Astrophysics Data System (ADS)

Iwaki, Y.

2010-07-01

The Quality Assurance (QA) of measurand has been discussed over many years by Quality Engineering (QE). It is need to more discuss about ISO standard. It is mining to find out root fault element for improvement of measured accuracy, and it remove. The accuracy assurance needs to investigate the Reference Material (RM) for calibration and an improvement accuracy of data processing. This research follows the accuracy improvement in field of data processing by how to improve of accuracy. As for the fault element relevant to measurement accuracy, in many cases, two or more element is buried exist. The QE is to assume the generating frequency of fault state, and it is solving from higher ranks for fault factor first by "Failure Mode and Effects Analysis (FMEA)". Then QE investigate the root cause over the fault element by "Root Cause Analysis (RCA)" and "Fault Tree Analysis (FTA)" and calculate order to the generating element of assume specific fault. These days comes, the accuracy assurance of measurement result became duty in the Professional Test (PT). ISO standard was legislated by ISO-GUM (Guide of express Uncertainty in Measurement) as guidance of an accuracy assurance in 1993 [1] for QA. Analysis method of ISO-GUM is changed into Exploratory Data Analysis (EDA) from Analysis of Valiance (ANOVA). EDA calculate one by one until an assurance performance is obtained according to "Law of the propagation of uncertainty". If the truth value was unknown, ISO-GUM is changed into reference value. A reference value set up by the EDA and it does check with a Key Comparison (KC) method. KC is comparing between null hypothesis and frequency hypothesis. It performs operation of assurance by ISO-GUM in order of standard uncertainty, the combined uncertainty of many fault elements and an expansion uncertain for assurance. An assurance value is authorized by multiplying the final expansion uncertainty [2] by K of coverage factor. K-value is calculated from the Effective Free Degree (EFD) which thought the number of samples is important. Free degree is based on maximum likelihood method of an improved information criterion (AIC) for a Quality Control (QC). The assurance performance of ISO-GUM is come out by set up of the confidence interval [3] and is decided. The result of research of "Decided level/Minimum Detectable Concentration (DL/MDC)" was able to profit by the operation. QE has developed for the QC of industry. However, these have been processed by regression analysis by making frequency probability of a statistic value into normalized distribution. The occurrence probability of the statistics value of a fault element which is accompanied element by a natural phenomenon becomes an abnormal distribution in many cases. The abnormal distribution needs to obtain an assurance value by other method than statistical work of type B in ISO-GUM. It is tried fusion the improvement of worker by QE became important for reservation of the reliability of measurement accuracy and safety. This research was to make the result of Blood Chemical Analysis (BCA) in the field of clinical test.

Empirical evaluation of data normalization methods for molecular classification

PubMed Central

Huang, Huei-Chung

2018-01-01

Background Data artifacts due to variations in experimental handling are ubiquitous in microarray studies, and they can lead to biased and irreproducible findings. A popular approach to correct for such artifacts is through post hoc data adjustment such as data normalization. Statistical methods for data normalization have been developed and evaluated primarily for the discovery of individual molecular biomarkers. Their performance has rarely been studied for the development of multi-marker molecular classifiers—an increasingly important application of microarrays in the era of personalized medicine. Methods In this study, we set out to evaluate the performance of three commonly used methods for data normalization in the context of molecular classification, using extensive simulations based on re-sampling from a unique pair of microRNA microarray datasets for the same set of samples. The data and code for our simulations are freely available as R packages at GitHub. Results In the presence of confounding handling effects, all three normalization methods tended to improve the accuracy of the classifier when evaluated in an independent test data. The level of improvement and the relative performance among the normalization methods depended on the relative level of molecular signal, the distributional pattern of handling effects (e.g., location shift vs scale change), and the statistical method used for building the classifier. In addition, cross-validation was associated with biased estimation of classification accuracy in the over-optimistic direction for all three normalization methods. Conclusion Normalization may improve the accuracy of molecular classification for data with confounding handling effects; however, it cannot circumvent the over-optimistic findings associated with cross-validation for assessing classification accuracy. PMID:29666754

Experimental studies of high-accuracy RFID localization with channel impairments

NASA Astrophysics Data System (ADS)

Pauls, Eric; Zhang, Yimin D.

2015-05-01

Radio frequency identification (RFID) systems present an incredibly cost-effective and easy-to-implement solution to close-range localization. One of the important applications of a passive RFID system is to determine the reader position through multilateration based on the estimated distances between the reader and multiple distributed reference tags obtained from, e.g., the received signal strength indicator (RSSI) readings. In practice, the achievable accuracy of passive RFID reader localization suffers from many factors, such as the distorted RSSI reading due to channel impairments in terms of the susceptibility to reader antenna patterns and multipath propagation. Previous studies have shown that the accuracy of passive RFID localization can be significantly improved by properly modeling and compensating for such channel impairments. The objective of this paper is to report experimental study results that validate the effectiveness of such approaches for high-accuracy RFID localization. We also examine a number of practical issues arising in the underlying problem that limit the accuracy of reader-tag distance measurements and, therefore, the estimated reader localization. These issues include the variations in tag radiation characteristics for similar tags, effects of tag orientations, and reader RSS quantization and measurement errors. As such, this paper reveals valuable insights of the issues and solutions toward achieving high-accuracy passive RFID localization.

The Role of Standardized and Study-specific Human Brain Diffusion Tensor Templates in Inter-subject Spatial Normalization

PubMed Central

Zhang, Shengwei; Arfanakis, Konstantinos

2012-01-01

Purpose To investigate the effect of standardized and study-specific human brain diffusion tensor templates on the accuracy of spatial normalization, without ignoring the important roles of data quality and registration algorithm effectiveness. Materials and Methods Two groups of diffusion tensor imaging (DTI) datasets, with and without visible artifacts, were normalized to two standardized diffusion tensor templates (IIT2, ICBM81) as well as study-specific templates, using three registration approaches. The accuracy of inter-subject spatial normalization was compared across templates, using the most effective registration technique for each template and group of data. Results It was demonstrated that, for DTI data with visible artifacts, the study-specific template resulted in significantly higher spatial normalization accuracy than standardized templates. However, for data without visible artifacts, the study-specific template and the standardized template of higher quality (IIT2) resulted in similar normalization accuracy. Conclusion For DTI data with visible artifacts, a carefully constructed study-specific template may achieve higher normalization accuracy than that of standardized templates. However, as DTI data quality improves, a high-quality standardized template may be more advantageous than a study-specific template, since in addition to high normalization accuracy, it provides a standard reference across studies, as well as automated localization/segmentation when accompanied by anatomical labels. PMID:23034880

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Estimation of genomic breeding values for residual feed intake in a multibreed cattle population.

PubMed

Khansefid, M; Pryce, J E; Bolormaa, S; Miller, S P; Wang, Z; Li, C; Goddard, M E

2014-08-01

Residual feed intake (RFI) is a measure of the efficiency of animals in feed utilization. The accuracies of GEBV for RFI could be improved by increasing the size of the reference population. Combining RFI records of different breeds is a way to do that. The aims of this study were to 1) develop a method for calculating GEBV in a multibreed population and 2) improve the accuracies of GEBV by using SNP associated with RFI. An alternative method for calculating accuracies of GEBV using genomic BLUP (GBLUP) equations is also described and compared to cross-validation tests. The dataset included RFI records and 606,096 SNP genotypes for 5,614 Bos taurus animals including 842 Holstein heifers and 2,009 Australian and 2,763 Canadian beef cattle. A range of models were tested for combining genotype and phenotype information from different breeds and the best model included an overall effect of each SNP, an effect of each SNP specific to a breed, and a small residual polygenic effect defined by the pedigree. In this model, the Holsteins and some Angus cattle were combined into 1 "breed class" because they were the only cattle measured for RFI at an early age (6-9 mo of age) and were fed a similar diet. The average empirical accuracy (0.31), estimated by calculating the correlation between GEBV and actual phenotypes divided by the square root of estimated heritability in 5-fold cross-validation tests, was near to that expected using the GBLUP equations (0.34). The average empirical and expected accuracies were 0.30 and 0.31, respectively, when the GEBV were estimated for each breed separately. Therefore, the across-breed reference population increased the accuracy of GEBV slightly, although the gain was greater for breeds with smaller number of individuals in the reference population (0.08 in Murray Grey and 0.11 in Hereford for empirical accuracy). In a second approach, SNP that were significantly (P < 0.001) associated with RFI in the beef cattle genomewide association studies were used to create an auxiliary genomic relationship matrix for estimating GEBV in Holstein heifers. The empirical (and expected) accuracy of GEBV within Holsteins increased from 0.33 (0.35) to 0.39 (0.36) and improved even more to 0.43 (0.50) when using a multibreed reference population. Therefore, a multibreed reference population is a useful resource to find SNP with a greater than average association with RFI in 1 breed and use them to estimate GEBV in another breed.

Edge effect modeling of small tool polishing in planetary movement

NASA Astrophysics Data System (ADS)

Li, Qi-xin; Ma, Zhen; Jiang, Bo; Yao, Yong-sheng

2018-03-01

As one of the most challenging problems in Computer Controlled Optical Surfacing (CCOS), the edge effect greatly affects the polishing accuracy and efficiency. CCOS rely on stable tool influence function (TIF), however, at the edge of the mirror surface,with the grinding head out of the mirror ,the contact area and pressure distribution changes, which resulting in a non-linear change of TIF, and leads to tilting or sagging at the edge of the mirror. In order reduce the adverse effects and improve the polishing accuracy and efficiency. In this paper, we used the finite element simulation to analyze the pressure distribution at the mirror edge and combined with the improved traditional method to establish a new model. The new method fully considered the non-uniformity of pressure distribution. After modeling the TIFs in different locations, the description and prediction of the edge effects are realized, which has a positive significance on the control and suppression of edge effects

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

The Application of GIM in Precise Orbit Determination for LEO Satellites with Single-frequency GPS Measurements

NASA Astrophysics Data System (ADS)

Peng, D. J.; Wu, B.

2012-01-01

With the availability of precise GPS ephemeris and clock solution, the ionospheric range delay is left as the dominant error sources in the post-processing of space-borne GPS data from single-frequency receivers. Thus, the removal of ionospheric effects is a major prerequisite for an improved orbit reconstruction of LEO satellites equipped with low cost single-frequency GPS receivers. In this paper, the use of Global Ionospheric Maps (GIM) in kinematic and dynamic orbit determination for LEO satellites with single-frequency GPS measurements is discussed first,and then, estimating the scale factor of ionosphere to remove the ionospheric effects in C/A code pseudo-range measurements in both kinematic and adynamia orbit defemination approaches is addressed. As it is known the ionospheric path delay of space-borne GPS signals is strongly dependent on the orbit altitudes of LEO satellites, we selected real space-borne GPS data from CHAMP, GRACE, TerraSAR-X and SAC-C satellites with altitudes between 300 km and 800 km as sample data in this paper. It is demonstrated that the approach of eliminating ionospheric effects in space-borne C/A code pseudo-range by estimating the scale factor of ionosphere is highly effective. Employing this approach, the accuracy of both kinematic and dynamic orbits can be improved notably. Among those five LEO satellites, CHAMP with the lowest orbit altitude has the most remarkable orbit accuracy improvements, which are 55.6% and 47.6% for kinematic and dynamic approaches, respectively. SAC-C with the highest orbit altitude has the least orbit accuracy improvements accordingly, which are 47.8% and 38.2%, respectively.

A systematic review of the PTSD Checklist's diagnostic accuracy studies using QUADAS.

PubMed

McDonald, Scott D; Brown, Whitney L; Benesek, John P; Calhoun, Patrick S

2015-09-01

Despite the popularity of the PTSD Checklist (PCL) as a clinical screening test, there has been no comprehensive quality review of studies evaluating its diagnostic accuracy. A systematic quality assessment of 22 diagnostic accuracy studies of the English-language PCL using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) assessment tool was conducted to examine (a) the quality of diagnostic accuracy studies of the PCL, and (b) whether quality has improved since the 2003 STAndards for the Reporting of Diagnostic accuracy studies (STARD) initiative regarding reporting guidelines for diagnostic accuracy studies. Three raters independently applied the QUADAS tool to each study, and a consensus among the 4 authors is reported. Findings indicated that although studies generally met standards in several quality areas, there is still room for improvement. Areas for improvement include establishing representativeness, adequately describing clinical and demographic characteristics of the sample, and presenting better descriptions of important aspects of test and reference standard execution. Only 2 studies met each of the 14 quality criteria. In addition, study quality has not appreciably improved since the publication of the STARD Statement in 2003. Recommendations for the improvement of diagnostic accuracy studies of the PCL are discussed. (c) 2015 APA, all rights reserved).

Huperzine A: Behavioral and Pharmacological Evaluation in Rhesus Monkeys

DTIC Science & Technology

2008-06-01

challenged with 30 ug/kg scopolamine . Doses of 1 and 10 ug/kg HUP improved choice accuracy on a previously learned delayed spatial memory task in the...elderly subjects, and doses of 10 and 100 ug/kg reversed the scopolamine -induced deficits in the younger monkeys. Unfortunately, no data regarding...interval) in the spatial memory task differentially modulated the drug effects on performance. Specifically, scopolamine impaired accuracy

An improved triangulation laser rangefinder using a custom CMOS HDR linear image sensor

NASA Astrophysics Data System (ADS)

Liscombe, Michael

3-D triangulation laser rangefinders are used in many modern applications, from terrain mapping to biometric identification. Although a wide variety of designs have been proposed, laser speckle noise still provides a fundamental limitation on range accuracy. These works propose a new triangulation laser rangefinder designed specifically to mitigate the effects of laser speckle noise. The proposed rangefinder uses a precision linear translator to laterally reposition the imaging system (e.g., image sensor and imaging lens). For a given spatial location of the laser spot, capturing N spatially uncorrelated laser spot profiles is shown to improve range accuracy by a factor of N . This technique has many advantages over past speckle-reduction technologies, such as a fixed system cost and form factor, and the ability to virtually eliminate laser speckle noise. These advantages are made possible through spatial diversity and come at the cost of increased acquisition time. The rangefinder makes use of the ICFYKWG1 linear image sensor, a custom CMOS sensor developed at the Vision Sensor Laboratory (York University). Tests are performed on the image sensor's innovative high dynamic range technology to determine its effects on range accuracy. As expected, experimental results have shown that the sensor provides a trade-off between dynamic range and range accuracy.

A robot-aided visuo-motor training that improves proprioception and spatial accuracy of untrained movement.

PubMed

Elangovan, Naveen; Cappello, Leonardo; Masia, Lorenzo; Aman, Joshua; Konczak, Jürgen

2017-12-06

Proprioceptive function can become enhanced during motor learning. Yet, we have incomplete knowledge to what extent proprioceptive function is trainable and how a training that enhances proprioception may influence performance in untrained motor skills. To address this knowledge gap, healthy young adults (N = 14) trained in a visuomotor task that required learners to make increasingly accurate wrist movements. Using a robotic exoskeleton coupled with a virtual visual environment, participants tilted a virtual table through continuous wrist flexion/extension movements with the goal to position a rolling ball on table into a target. With learning progress, the level of difficulty increased by altering the virtual ball mechanics and the gain between joint movement and ball velocity. Before and after training, wrist position sense acuity and spatial movement accuracy in an untrained, discrete wrist-pointing task was assessed using the same robot. All participants showed evidence of proprioceptive-motor learning. Mean position sense discrimination threshold improved by 34%. Wrist movement accuracy in the untrained pointing task improved by 27% in 13/14 participants. This demonstrates that a short sensorimotor training challenging proprioception can a) effectively enhance proprioceptive acuity and b) improve the accuracy of untrained movement. These findings provide a scientific basis for applying such somatosensory-based motor training to clinical populations with known proprioceptive dysfunction to enhance sensorimotor performance.

An Orientation Measurement Method Based on Hall-effect Sensors for Permanent Magnet Spherical Actuators with 3D Magnet Array

PubMed Central

Yan, Liang; Zhu, Bo; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-01-01

An orientation measurement method based on Hall-effect sensors is proposed for permanent magnet (PM) spherical actuators with three-dimensional (3D) magnet array. As there is no contact between the measurement system and the rotor, this method could effectively avoid friction torque and additional inertial moment existing in conventional approaches. Curved surface fitting method based on exponential approximation is proposed to formulate the magnetic field distribution in 3D space. The comparison with conventional modeling method shows that it helps to improve the model accuracy. The Hall-effect sensors are distributed around the rotor with PM poles to detect the flux density at different points, and thus the rotor orientation can be computed from the measured results and analytical models. Experiments have been conducted on the developed research prototype of the spherical actuator to validate the accuracy of the analytical equations relating the rotor orientation and the value of magnetic flux density. The experimental results show that the proposed method can measure the rotor orientation precisely, and the measurement accuracy could be improved by the novel 3D magnet array. The study result could be used for real-time motion control of PM spherical actuators. PMID:25342000

Classifying coastal resources by integrating optical and radar imagery and color infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, Gene A.; Sapkota, Sijan

1998-01-01

A progressive classification of a marsh and forest system using Landsat Thematic Mapper (TM), color infrared (CIR) photograph, and ERS-1 synthetic aperture radar (SAR) data improved classification accuracy when compared to classification using solely TM reflective band data. The classification resulted in a detailed identification of differences within a nearly monotypic black needlerush marsh. Accuracy percentages of these classes were surprisingly high given the complexities of classification. The detailed classification resulted in a more accurate portrayal of the marsh transgressive sequence than was obtainable with TM data alone. Individual sensor contribution to the improved classification was compared to that using only the six reflective TM bands. Individually, the green reflective CIR and SAR data identified broad categories of water, marsh, and forest. In combination with TM, SAR and the green CIR band each improved overall accuracy by about 3% and 15% respectively. The SAR data improved the TM classification accuracy mostly in the marsh classes. The green CIR data also improved the marsh classification accuracy and accuracies in some water classes. The final combination of all sensor data improved almost all class accuracies from 2% to 70% with an overall improvement of about 20% over TM data alone. Not only was the identification of vegetation types improved, but the spatial detail of the classification approached 10 m in some areas.

A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems

PubMed Central

Lyu, Weiwei

2017-01-01

Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method. PMID:29182592

Real-time, resource-constrained object classification on a micro-air vehicle

NASA Astrophysics Data System (ADS)

Buck, Louis; Ray, Laura

2013-12-01

A real-time embedded object classification algorithm is developed through the novel combination of binary feature descriptors, a bag-of-visual-words object model and the cortico-striatal loop (CSL) learning algorithm. The BRIEF, ORB and FREAK binary descriptors are tested and compared to SIFT descriptors with regard to their respective classification accuracies, execution times, and memory requirements when used with CSL on a 12.6 g ARM Cortex embedded processor running at 800 MHz. Additionally, the effect of x2 feature mapping and opponent-color representations used with these descriptors is examined. These tests are performed on four data sets of varying sizes and difficulty, and the BRIEF descriptor is found to yield the best combination of speed and classification accuracy. Its use with CSL achieves accuracies between 67% and 95% of those achieved with SIFT descriptors and allows for the embedded classification of a 128x192 pixel image in 0.15 seconds, 60 times faster than classification with SIFT. X2 mapping is found to provide substantial improvements in classification accuracy for all of the descriptors at little cost, while opponent-color descriptors are offer accuracy improvements only on colorful datasets.

A Practical Torque Estimation Method for Interior Permanent Magnet Synchronous Machine in Electric Vehicles.

PubMed

Wu, Zhihong; Lu, Ke; Zhu, Yuan

2015-01-01

The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment.

Use of Fuzzycones for Sun-Only Attitude Determination: THEMIS Becomes ARTEMIS

NASA Technical Reports Server (NTRS)

Hashmall, Joseph A.; Felikson, Denis; Sedlak, Joseph E.

2009-01-01

In order for two THEMIS probes to successfully transition to ARTEMIS it will be necessary to determine attitudes with moderate accuracy using Sun sensor data only. To accomplish this requirement, an implementation of the Fuzzycones maximum likelihood algorithm was developed. The effect of different measurement uncertainty models on Fuzzycones attitude accuracy was investigated and a bin-transition technique was introduced to improve attitude accuracy using data with uniform error distributions. The algorithm was tested with THEMIS data and in simulations. The analysis results show that the attitude requirements can be met using Fuzzycones and data containing two bin-transitions.

A Practical Torque Estimation Method for Interior Permanent Magnet Synchronous Machine in Electric Vehicles

PubMed Central

Zhu, Yuan

2015-01-01

The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment. PMID:26114557

Methodological quality of diagnostic accuracy studies on non-invasive coronary CT angiography: influence of QUADAS (Quality Assessment of Diagnostic Accuracy Studies included in systematic reviews) items on sensitivity and specificity.

PubMed

Schueler, Sabine; Walther, Stefan; Schuetz, Georg M; Schlattmann, Peter; Dewey, Marc

2013-06-01

To evaluate the methodological quality of diagnostic accuracy studies on coronary computed tomography (CT) angiography using the QUADAS (Quality Assessment of Diagnostic Accuracy Studies included in systematic reviews) tool. Each QUADAS item was individually defined to adapt it to the special requirements of studies on coronary CT angiography. Two independent investigators analysed 118 studies using 12 QUADAS items. Meta-regression and pooled analyses were performed to identify possible effects of methodological quality items on estimates of diagnostic accuracy. The overall methodological quality of coronary CT studies was merely moderate. They fulfilled a median of 7.5 out of 12 items. Only 9 of the 118 studies fulfilled more than 75 % of possible QUADAS items. One QUADAS item ("Uninterpretable Results") showed a significant influence (P = 0.02) on estimates of diagnostic accuracy with "no fulfilment" increasing specificity from 86 to 90 %. Furthermore, pooled analysis revealed that each QUADAS item that is not fulfilled has the potential to change estimates of diagnostic accuracy. The methodological quality of studies investigating the diagnostic accuracy of non-invasive coronary CT is only moderate and was found to affect the sensitivity and specificity. An improvement is highly desirable because good methodology is crucial for adequately assessing imaging technologies. • Good methodological quality is a basic requirement in diagnostic accuracy studies. • Most coronary CT angiography studies have only been of moderate design quality. • Weak methodological quality will affect the sensitivity and specificity. • No improvement in methodological quality was observed over time. • Authors should consider the QUADAS checklist when undertaking accuracy studies.

Search for general relativistic effects in table-top displacement metrology

NASA Technical Reports Server (NTRS)

Halverson, Peter G.; Macdonald, Daniel R.; Diaz, Rosemary T.

2004-01-01

As displacement metrology accuracy improves, general relativistic effects will become noticeable. Metrology gauges developed for the Space Interferometry Mission were used to search for locally anisotropic space-time, with a null result at the 10 to the negative tenth power level.

The effects of instructions on mothers' ratings of child attention-deficit/hyperactivity disorder symptoms.

PubMed

Johnston, Charlotte; Weiss, Margaret; Murray, Candice; Miller, Natalie

2011-11-01

We examined whether instructional materials describing how to rate child ADHD symptoms would improve the accuracy of mothers' ratings of ADHD symptoms presented in standard child behavior stimuli, and whether instructions would be equally effective across a range of maternal depressive symptoms and family incomes. A community sample of 100 mothers with 5 to 12 year old sons were randomly assigned to either receive or not receive the instructions. All mothers watched standard video recordings of boys displaying nonproblem behavior, ADHD symptoms, ADHD plus oppositional behaviors, or ADHD plus anxious behaviors, and then rated the ADHD symptoms of the boys in the videos. These ratings were compared to ratings of the boys' ADHD symptoms made by objective coders. Results indicated an interaction such that the instructional materials improved the agreement between mothers' and coders' ratings, but only for mothers at lower family income levels. The instructional materials improved all mothers' open-ended responses regarding knowledge of ADHD. All mothers rated more ADHD symptoms in boys with comorbid oppositional or anxious behaviors, and this effect was not reduced by the instructional materials. The potential utility of these instructions to improve the accuracy of ratings of child ADHD symptoms is explored.

Optimization of hole generation in Ti/CFRP stacks

NASA Astrophysics Data System (ADS)

Ivanov, Y. N.; Pashkov, A. E.; Chashhin, N. S.

2018-03-01

The article aims to describe methods for improving the surface quality and hole accuracy in Ti/CFRP stacks by optimizing cutting methods and drill geometry. The research is based on the fundamentals of machine building, theory of probability, mathematical statistics, and experiment planning and manufacturing process optimization theories. Statistical processing of experiment data was carried out by means of Statistica 6 and Microsoft Excel 2010. Surface geometry in Ti stacks was analyzed using a Taylor Hobson Form Talysurf i200 Series Profilometer, and in CFRP stacks - using a Bruker ContourGT-Kl Optical Microscope. Hole shapes and sizes were analyzed using a Carl Zeiss CONTURA G2 Measuring machine, temperatures in cutting zones were recorded with a FLIR SC7000 Series Infrared Camera. Models of multivariate analysis of variance were developed. They show effects of drilling modes on surface quality and accuracy of holes in Ti/CFRP stacks. The task of multicriteria drilling process optimization was solved. Optimal cutting technologies which improve performance were developed. Methods for assessing thermal tool and material expansion effects on the accuracy of holes in Ti/CFRP/Ti stacks were developed.

Development of a high sensitivity pinhole type gamma camera using semiconductors for low dose rate fields

NASA Astrophysics Data System (ADS)

Ueno, Yuichiro; Takahashi, Isao; Ishitsu, Takafumi; Tadokoro, Takahiro; Okada, Koichi; Nagumo, Yasushi; Fujishima, Yasutake; Yoshida, Akira; Umegaki, Kikuo

2018-06-01

We developed a pinhole type gamma camera, using a compact detector module of a pixelated CdTe semiconductor, which has suitable sensitivity and quantitative accuracy for low dose rate fields. In order to improve the sensitivity of the pinhole type semiconductor gamma camera, we adopted three methods: a signal processing method to set the discriminating level lower, a high sensitivity pinhole collimator and a smoothing image filter that improves the efficiency of the source identification. We tested basic performances of the developed gamma camera and carefully examined effects of the three methods. From the sensitivity test, we found that the effective sensitivity was about 21 times higher than that of the gamma camera for high dose rate fields which we had previously developed. We confirmed that the gamma camera had sufficient sensitivity and high quantitative accuracy; for example, a weak hot spot (0.9 μSv/h) around a tree root could be detected within 45 min in a low dose rate field test, and errors of measured dose rates with point sources were less than 7% in a dose rate accuracy test.

Galileo: The Added Value for Integrity in Harsh Environments.

PubMed

Borio, Daniele; Gioia, Ciro

2016-01-16

A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability.

Galileo: The Added Value for Integrity in Harsh Environments

PubMed Central

Borio, Daniele; Gioia, Ciro

2016-01-01

A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability. PMID:26784205

Effect of scan quality on diagnostic accuracy of spectral-domain optical coherence tomography in glaucoma.

PubMed

Rao, Harsha L; Addepalli, Uday K; Yadav, Ravi K; Senthil, Sirisha; Choudhari, Nikhil S; Garudadri, Chandra S

2014-03-01

To evaluate the effect of scan quality on the diagnostic accuracies of optic nerve head (ONH), retinal nerve fiber layer (RNFL), and ganglion cell complex (GCC) parameters of spectral-domain optical coherence tomography (SD OCT) in glaucoma. Cross-sectional study. Two hundred fifty-two eyes of 183 control subjects (mean deviation [MD]: -1.84 dB) and 207 eyes of 159 glaucoma patients (MD: -7.31 dB) underwent ONH, RNFL, and GCC scanning with SD OCT. Scan quality of SD OCT images was based on signal strength index (SSI) values. Influence of SSI on diagnostic accuracy of SD OCT was evaluated by receiver operating characteristic (ROC) regression. Diagnostic accuracies of all SD OCT parameters were better when the SSI values were higher. This effect was statistically significant (P < .05) for ONH and RNFL but not for GCC parameters. In mild glaucoma (MD of -5 dB), area under ROC curve (AUC) for rim area, average RNFL thickness, and average GCC thickness parameters improved from 0.651, 0.678, and 0.726, respectively, at an SSI value of 30 to 0.873, 0.962, and 0.886, respectively, at an SSI of 70. AUCs of the same parameters in advanced glaucoma (MD of -15 dB) improved from 0.747, 0.890, and 0.873, respectively, at an SSI value of 30 to 0.922, 0.994, and 0.959, respectively, at an SSI of 70. Diagnostic accuracies of SD OCT parameters in glaucoma were significantly influenced by the scan quality even when the SSI values were within the manufacturer-recommended limits. These results should be considered while interpreting the SD OCT scans for glaucoma. Copyright © 2014 Elsevier Inc. All rights reserved.

Laser Trimming of CuAlMo Thin-Film Resistors: Effect of Laser Processing Parameters

NASA Astrophysics Data System (ADS)

Birkett, Martin; Penlington, Roger

2012-08-01

This paper reports the effect of varying laser trimming process parameters on the electrical performance of a novel CuAlMo thin-film resistor material. The films were prepared on Al2O3 substrates by direct-current (DC) magnetron sputtering, before being laser trimmed to target resistance value. The effect of varying key laser parameters of power, Q-rate, and bite size on the resistor stability and tolerance accuracy were systematically investigated. By reducing laser power and bite size and balancing this with Q-rate setting, significant improvements in resistor stability and resistor tolerance accuracies of less than ±0.5% were achieved.

Effect of time discretization of the imaging process on the accuracy of trajectory estimation in fluorescence microscopy

PubMed Central

Wong, Yau; Chao, Jerry; Lin, Zhiping; Ober, Raimund J.

2014-01-01

In fluorescence microscopy, high-speed imaging is often necessary for the proper visualization and analysis of fast subcellular dynamics. Here, we examine how the speed of image acquisition affects the accuracy with which parameters such as the starting position and speed of a microscopic non-stationary fluorescent object can be estimated from the resulting image sequence. Specifically, we use a Fisher information-based performance bound to investigate the detector-dependent effect of frame rate on the accuracy of parameter estimation. We demonstrate that when a charge-coupled device detector is used, the estimation accuracy deteriorates as the frame rate increases beyond a point where the detector’s readout noise begins to overwhelm the low number of photons detected in each frame. In contrast, we show that when an electron-multiplying charge-coupled device (EMCCD) detector is used, the estimation accuracy improves with increasing frame rate. In fact, at high frame rates where the low number of photons detected in each frame renders the fluorescent object difficult to detect visually, imaging with an EMCCD detector represents a natural implementation of the Ultrahigh Accuracy Imaging Modality, and enables estimation with an accuracy approaching that which is attainable only when a hypothetical noiseless detector is used. PMID:25321248

Stereo Image Dense Matching by Integrating Sift and Sgm Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Y.; Song, Y.; Lu, J.

2018-05-01

Semi-global matching(SGM) performs the dynamic programming by treating the different path directions equally. It does not consider the impact of different path directions on cost aggregation, and with the expansion of the disparity search range, the accuracy and efficiency of the algorithm drastically decrease. This paper presents a dense matching algorithm by integrating SIFT and SGM. It takes the successful matching pairs matched by SIFT as control points to direct the path in dynamic programming with truncating error propagation. Besides, matching accuracy can be improved by using the gradient direction of the detected feature points to modify the weights of the paths in different directions. The experimental results based on Middlebury stereo data sets and CE-3 lunar data sets demonstrate that the proposed algorithm can effectively cut off the error propagation, reduce disparity search range and improve matching accuracy.

The effect of a specialized dyslexia font, OpenDyslexic, on reading rate and accuracy.

PubMed

Wery, Jessica J; Diliberto, Jennifer A

2017-07-01

A single-subject alternating treatment design was used to investigate the extent to which a specialized dyslexia font, OpenDyslexic, impacted reading rate or accuracy compared to two commonly used fonts when used with elementary students identified as having dyslexia. OpenDyslexic was compared to Arial and Times New Roman in three reading tasks: (a) letter naming, (b) word reading, and (c) nonsense word reading. Data were analyzed through visual analysis and improvement rate difference, a nonparametric measure of nonoverlap for comparing treatments. Results from this alternating treatment experiment show no improvement in reading rate or accuracy for individual students with dyslexia, as well as the group as a whole. While some students commented that the font was "new" or "different", none of the participants reported preferring to read material presented in that font. These results indicate there may be no benefit for translating print materials to this font.

Research on cardiovascular disease prediction based on distance metric learning

NASA Astrophysics Data System (ADS)

Ni, Zhuang; Liu, Kui; Kang, Guixia

2018-04-01

Distance metric learning algorithm has been widely applied to medical diagnosis and exhibited its strengths in classification problems. The k-nearest neighbour (KNN) is an efficient method which treats each feature equally. The large margin nearest neighbour classification (LMNN) improves the accuracy of KNN by learning a global distance metric, which did not consider the locality of data distributions. In this paper, we propose a new distance metric algorithm adopting cosine metric and LMNN named COS-SUBLMNN which takes more care about local feature of data to overcome the shortage of LMNN and improve the classification accuracy. The proposed methodology is verified on CVDs patient vector derived from real-world medical data. The Experimental results show that our method provides higher accuracy than KNN and LMNN did, which demonstrates the effectiveness of the Risk predictive model of CVDs based on COS-SUBLMNN.

An automatic step adjustment method for average power analysis technique used in fiber amplifiers

NASA Astrophysics Data System (ADS)

Liu, Xue-Ming

2006-04-01

An automatic step adjustment (ASA) method for average power analysis (APA) technique used in fiber amplifiers is proposed in this paper for the first time. In comparison with the traditional APA technique, the proposed method has suggested two unique merits such as a higher order accuracy and an ASA mechanism, so that it can significantly shorten the computing time and improve the solution accuracy. A test example demonstrates that, by comparing to the APA technique, the proposed method increases the computing speed by more than a hundredfold under the same errors. By computing the model equations of erbium-doped fiber amplifiers, the numerical results show that our method can improve the solution accuracy by over two orders of magnitude at the same amplifying section number. The proposed method has the capacity to rapidly and effectively compute the model equations of fiber Raman amplifiers and semiconductor lasers.

A Global Optimization Methodology for Rocket Propulsion Applications

NASA Technical Reports Server (NTRS)

2001-01-01

While the response surface method is an effective method in engineering optimization, its accuracy is often affected by the use of limited amount of data points for model construction. In this chapter, the issues related to the accuracy of the RS approximations and possible ways of improving the RS model using appropriate treatments, including the iteratively re-weighted least square (IRLS) technique and the radial-basis neural networks, are investigated. A main interest is to identify ways to offer added capabilities for the RS method to be able to at least selectively improve the accuracy in regions of importance. An example is to target the high efficiency region of a fluid machinery design space so that the predictive power of the RS can be maximized when it matters most. Analytical models based on polynomials, with controlled level of noise, are used to assess the performance of these techniques.

Search for general relativistic effects in table-top displacement metrology

NASA Technical Reports Server (NTRS)

Halverson, Peter G.; Diaz, Rosemary T.; Macdonald, Daniel R.

2004-01-01

As displacement metrology accuracy improves, general relativistic effects will become noticeable. Metrology gauges developed for the Space Interferometry Mission, were used to search for locally anisotropic space-time, with a null result at the 10 to the negative 10th power level.

Singing Video Games May Help Improve Pitch-Matching Accuracy

ERIC Educational Resources Information Center

Paney, Andrew S.

2015-01-01

The purpose of this study was to investigate the effect of singing video games on the pitch-matching skills of undergraduate students. Popular games like "Rock Band" and "Karaoke Revolutions" rate players' singing based on the correctness of the frequency of their sung response. Players are motivated to improve their…

Enhancing Self-Regulatory Skills through an Intervention Embedded in a Middle School Mathematics Curriculum

ERIC Educational Resources Information Center

Digiacomo, Gregory; Chen, Peggy P.

2016-01-01

We investigated the effects of a self-regulatory intervention strategy designed to improve middle-school students' calibration accuracy, self-regulatory skills, and math achievement. Focusing on self-monitoring and self-reflection as the two key processes of this intervention in relation to improving students' math achievement and overall…

Efficient use of unlabeled data for protein sequence classification: a comparative study.

PubMed

Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

2009-04-29

Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags-the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably.

Towards 10(exp 9) GPS geodesy: Vector baselines, Earth rotation and reference frames

NASA Technical Reports Server (NTRS)

Schutz, Bob E.

1994-01-01

Effort during the period form January 1, 1993 to December 31, 1993 were in the following areas: GPS orbit accuracy assessments and efforts to improve the accuracy; analysis and effects of GPS receiver antenna phase center variation; analysis of global GPS data being collected for the IGS campaign; and analysis of regional (south west Pacific) campaign data. A brief summary of each of the above activities is presented.

The Role of Teacher's Corrective Feedback in Improving Iranian EFL Learners' Writing Accuracy over Time: Is Learner's Mother Tongue Relevant?

ERIC Educational Resources Information Center

Rahimi, Mohammad

2009-01-01

The purpose of the present study was to investigate the impact of feedback on writing accuracy over time and examine the relevance of the students' mother tongue to the feedback effect. To this end, the study compared two groups of Iranian English majors (N = 56) over a period of four months: one with indirect grammar feedback and the other with…

GPS vertical axis performance enhancement for helicopter precision landing approach

NASA Technical Reports Server (NTRS)

Denaro, Robert P.; Beser, Jacques

1986-01-01

Several areas were investigated for improving vertical accuracy for a rotorcraft using the differential Global Positioning System (GPS) during a landing approach. Continuous deltaranging was studied and the potential improvement achieved by estimating acceleration was studied by comparing the performance on a constant acceleration turn and a rough landing profile of several filters: a position-velocity (PV) filter, a position-velocity-constant acceleration (PVAC) filter, and a position-velocity-turning acceleration (PVAT) filter. In overall statistics, the PVAC filter was found to be most efficient with the more complex PVAT performing equally well. Vertical performance was not significantly different among the filters. Satellite selection algorithms based on vertical errors only (vertical dilution of precision or VDOP) and even-weighted cross-track and vertical errors (XVDOP) were tested. The inclusion of an altimeter was studied by modifying the PVAC filter to include a baro bias estimate. Improved vertical accuracy during degraded DOP conditions resulted. Flight test results for raw differential results excluding filter effects indicated that the differential performance significantly improved overall navigation accuracy. A landing glidepath steering algorithm was devised which exploits the flexibility of GPS in determining precise relative position. A method for propagating the steering command over the GPS update interval was implemented.

The effect of stochastic modeling of ionospheric effect on the various lengths of baseline determination

NASA Astrophysics Data System (ADS)

Kwon, J.; Yang, H.

2006-12-01

Although GPS provides continuous and accurate position information, there are still some rooms for improvement of its positional accuracy, especially in the medium and long range baseline determination. In general, in case of more than 50 km baseline length, the effect of ionospheric delay is the one causing the largest degradation in positional accuracy. For example, the ionospheric delay in terms of double differenced mode easily reaches 10 cm with baseline length of 101 km. Therefore, many researchers have been tried to mitigate/reduce the effect using various modeling methods. In this paper, the optimal stochastic modeling of the ionospheric delay in terms of baseline length is presented. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. Here, the ionospheric delay is stochastically modeled by well-known Gaussian, 1st and 3rd order Gauss-Markov process. The parameters required in those models such as correlation distance and time is determined by the least-square adjustment using ionosphere-only observables. Mainly the results and analysis from this study show the effect of stochastic models of the ionospheric delay in terms of the baseline length, models, and parameters used. In the above example with 101 km baseline length, it was found that the positional accuracy with appropriate ionospheric modeling (Gaussian) was about ±2 cm whereas it reaches about ±15 cm with no stochastic modeling. It is expected that the approach in this study contributes to improve positional accuracy, especially in medium and long range baseline determination.

CD-Based Indices for Link Prediction in Complex Network.

PubMed

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

Effect of Carbohydrate and Caffeine Ingestion on Badminton Performance.

PubMed

Clarke, Neil D; Duncan, Michael J

2016-01-01

To investigate the effect of ingesting carbohydrate and caffeine solutions on measures that are central to success in badminton. Twelve male badminton players performed a badminton serve-accuracy test, coincidence-anticipation timing (CAT), and a choice reaction-time sprint test 60 min before exercise. Participants then consumed 7 mL/kg body mass of either water (PLA), 6.4% carbohydrate solution (CHO), a solution containing a caffeine dose of 4 mg/kg, or 6.4% carbohydrate and 4 mg/kg caffeine (C+C). All solutions were flavored with orange-flavored concentrate. During the 33-min fatigue protocol, participants were provided with an additional 3 mL/kg body mass of solution, which was ingested before the end of the protocol. As soon as the 33-min fatigue protocol was completed, all measures were recorded again. Short-serve accuracy was improved after the ingestion of CHO and C+C compared with PLA (P = .001, η(p)(2) = .50). Long-serve accuracy was improved after the ingestion of C+C compared with PLA (P < .001, η(p)(2) = .53). Absolute error in CAT demonstrated smaller deteriorations after the ingestion of C+C compared with PLA (P < .05; slow, η(p)(2) = .41; fast, η(p)(2) = .31). Choice reaction time improved in all trials with the exception of PLA, which demonstrated a reduction (P < .001, η(p)(2) = .85), although C+C was faster than all trials (P < .001, η(p)(2) = .76). These findings suggest that the ingestion of a caffeinated carbohydrate solution before and during a badminton match can maintain serve accuracy, anticipation timing, and sprinting actions around the court.

CD-Based Indices for Link Prediction in Complex Network

PubMed Central

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

Feature instructions improve face-matching accuracy

PubMed Central

Bindemann, Markus

2018-01-01

Identity comparisons of photographs of unfamiliar faces are prone to error but important for applied settings, such as person identification at passport control. Finding techniques to improve face-matching accuracy is therefore an important contemporary research topic. This study investigated whether matching accuracy can be improved by instruction to attend to specific facial features. Experiment 1 showed that instruction to attend to the eyebrows enhanced matching accuracy for optimized same-day same-race face pairs but not for other-race faces. By contrast, accuracy was unaffected by instruction to attend to the eyes, and declined with instruction to attend to ears. Experiment 2 replicated the eyebrow-instruction improvement with a different set of same-race faces, comprising both optimized same-day and more challenging different-day face pairs. These findings suggest that instruction to attend to specific features can enhance face-matching accuracy, but feature selection is crucial and generalization across face sets may be limited. PMID:29543822

Sliding-mode control combined with improved adaptive feedforward for wafer scanner

NASA Astrophysics Data System (ADS)

Li, Xiaojie; Wang, Yiguang

2018-03-01

In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

Improved accuracy and precision of tracer kinetic parameters by joint fitting to variable flip angle and dynamic contrast enhanced MRI data.

PubMed

Dickie, Ben R; Banerji, Anita; Kershaw, Lucy E; McPartlin, Andrew; Choudhury, Ananya; West, Catharine M; Rose, Chris J

2016-10-01

To improve the accuracy and precision of tracer kinetic model parameter estimates for use in dynamic contrast enhanced (DCE) MRI studies of solid tumors. Quantitative DCE-MRI requires an estimate of precontrast T1 , which is obtained prior to fitting a tracer kinetic model. As T1 mapping and tracer kinetic signal models are both a function of precontrast T1 it was hypothesized that its joint estimation would improve the accuracy and precision of both precontrast T1 and tracer kinetic model parameters. Accuracy and/or precision of two-compartment exchange model (2CXM) parameters were evaluated for standard and joint fitting methods in well-controlled synthetic data and for 36 bladder cancer patients. Methods were compared under a number of experimental conditions. In synthetic data, joint estimation led to statistically significant improvements in the accuracy of estimated parameters in 30 of 42 conditions (improvements between 1.8% and 49%). Reduced accuracy was observed in 7 of the remaining 12 conditions. Significant improvements in precision were observed in 35 of 42 conditions (between 4.7% and 50%). In clinical data, significant improvements in precision were observed in 18 of 21 conditions (between 4.6% and 38%). Accuracy and precision of DCE-MRI parameter estimates are improved when signal models are fit jointly rather than sequentially. Magn Reson Med 76:1270-1281, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Modeling and controller design of a 6-DOF precision positioning system

NASA Astrophysics Data System (ADS)

Cai, Kunhai; Tian, Yanling; Liu, Xianping; Fatikow, Sergej; Wang, Fujun; Cui, Liangyu; Zhang, Dawei; Shirinzadeh, Bijan

2018-05-01

A key hurdle to meet the needs of micro/nano manipulation in some complex cases is the inadequate workspace and flexibility of the operation ends. This paper presents a 6-degree of freedom (DOF) serial-parallel precision positioning system, which consists of two compact type 3-DOF parallel mechanisms. Each parallel mechanism is driven by three piezoelectric actuators (PEAs), guided by three symmetric T-shape hinges and three elliptical flexible hinges, respectively. It can extend workspace and improve flexibility of the operation ends. The proposed system can be assembled easily, which will greatly reduce the assembly errors and improve the positioning accuracy. In addition, the kinematic and dynamic model of the 6-DOF system are established, respectively. Furthermore, in order to reduce the tracking error and improve the positioning accuracy, the Discrete-time Model Predictive Controller (DMPC) is applied as an effective control method. Meanwhile, the effectiveness of the DMCP control method is verified. Finally, the tracking experiment is performed to verify the tracking performances of the 6-DOF stage.

Apollo oxygen tank stratification analysis, volume 2

NASA Technical Reports Server (NTRS)

Barton, J. E.; Patterson, H. W.

1972-01-01

An analysis of flight performance of the Apollo 15 cryogenic oxygen tanks was conducted with the variable grid stratification math model developed earlier in the program. Flight conditions investigated were the CMP-EVA and one passive thermal control period which exhibited heater temperature characteristics not previously observed. Heater temperatures for these periods were simulated with the math model using flight acceleration data. Simulation results (heater temperature and tank pressure) compared favorably with the Apollo 15 flight data, and it was concluded that tank performance was nominal. Math model modifications were also made to improve the simulation accuracy. The modifications included the addition of the effects of the tank wall thermal mass and an improved system flow distribution model. The modifications improved the accuracy of simulated pressure response based on comparisons with flight data.

The precision of today's satellite laser ranging systems

NASA Astrophysics Data System (ADS)

Dunn, Peter J.; Torrence, Mark H.; Hussen, Van S.; Pearlman, Michael R.

1993-06-01

Recent improvements in the accuracy of modern satellite laser ranging (SLR) systems are strengthened by the new capability of many instruments to track an increasing number of geodetic satellite targets without significant scheduling conflict. This will allow the refinement of some geophysical parameters, such as solid Earth tidal effects and GM, and the improved temporal resolution of others, such as Earth orientation and station position. Better time resolution for the locations of fixed observatories will allow us to monitor more subtle motions at the stations, and transportable systems will be able to provide indicators of long term trends with shorter occupations. If we are to take advantage of these improvements, care must be taken to preserve the essential accuracy of an increasing volume of range observations at each stage of the data reduction process.

The precision of today's satellite laser ranging systems

NASA Technical Reports Server (NTRS)

Dunn, Peter J.; Torrence, Mark H.; Hussen, Van S.; Pearlman, Michael R.

1993-01-01

Recent improvements in the accuracy of modern satellite laser ranging (SLR) systems are strengthened by the new capability of many instruments to track an increasing number of geodetic satellite targets without significant scheduling conflict. This will allow the refinement of some geophysical parameters, such as solid Earth tidal effects and GM, and the improved temporal resolution of others, such as Earth orientation and station position. Better time resolution for the locations of fixed observatories will allow us to monitor more subtle motions at the stations, and transportable systems will be able to provide indicators of long term trends with shorter occupations. If we are to take advantage of these improvements, care must be taken to preserve the essential accuracy of an increasing volume of range observations at each stage of the data reduction process.

Improving substructure identification accuracy of shear structures using virtual control system

NASA Astrophysics Data System (ADS)

Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

2018-02-01

Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

Vision-based real-time position control of a semi-automated system for robot-assisted joint fracture surgery.

PubMed

Dagnino, Giulio; Georgilas, Ioannis; Tarassoli, Payam; Atkins, Roger; Dogramadzi, Sanja

2016-03-01

Joint fracture surgery quality can be improved by robotic system with high-accuracy and high-repeatability fracture fragment manipulation. A new real-time vision-based system for fragment manipulation during robot-assisted fracture surgery was developed and tested. The control strategy was accomplished by merging fast open-loop control with vision-based control. This two-phase process is designed to eliminate the open-loop positioning errors by closing the control loop using visual feedback provided by an optical tracking system. Evaluation of the control system accuracy was performed using robot positioning trials, and fracture reduction accuracy was tested in trials on ex vivo porcine model. The system resulted in high fracture reduction reliability with a reduction accuracy of 0.09 mm (translations) and of [Formula: see text] (rotations), maximum observed errors in the order of 0.12 mm (translations) and of [Formula: see text] (rotations), and a reduction repeatability of 0.02 mm and [Formula: see text]. The proposed vision-based system was shown to be effective and suitable for real joint fracture surgical procedures, contributing a potential improvement of their quality.

Accuracy improvement of the H-drive air-levitating wafer inspection stage based on error analysis and compensation

NASA Astrophysics Data System (ADS)

Zhang, Fan; Liu, Pinkuan

2018-04-01

In order to improve the inspection precision of the H-drive air-bearing stage for wafer inspection, in this paper the geometric error of the stage is analyzed and compensated. The relationship between the positioning errors and error sources are initially modeled, and seven error components are identified that are closely related to the inspection accuracy. The most effective factor that affects the geometric error is identified by error sensitivity analysis. Then, the Spearman rank correlation method is applied to find the correlation between different error components, aiming at guiding the accuracy design and error compensation of the stage. Finally, different compensation methods, including the three-error curve interpolation method, the polynomial interpolation method, the Chebyshev polynomial interpolation method, and the B-spline interpolation method, are employed within the full range of the stage, and their results are compared. Simulation and experiment show that the B-spline interpolation method based on the error model has better compensation results. In addition, the research result is valuable for promoting wafer inspection accuracy and will greatly benefit the semiconductor industry.

Effects of peer tutoring and consequences on the math performance of elementary classroom students1

PubMed Central

Harris, V. William; Sherman, James A.

1973-01-01

The effects of unstructured peer-tutoring procedures on the math performance of fourth- and fifth-grade students were investigated. Students' performances in two daily math sessions, during which they worked problems of the same type and difficulty, were compared. When students tutored each other over the same math problems as they subsequently worked, higher accuracies and rates of performance were associated with the tutored math sessions. The use of consequences for accurate performance seemed to enhance the effects of tutoring on accuracy. The results from an independent-study control condition, which was the same peer-tutoring except that students did not interact with each other, suggested that interactions between students during the tutoring procedure were, in part, responsible for improved accuracy and rate of performance. When students tutored each other over different but related problems to those that they were subsequently asked to solve, accuracies and rates during tutored math sessions were also higher, suggesting the development of generalized skills in solving particular types of math problems. PMID:16795443

Application of preconditioned alternating direction method of multipliers in depth from focal stack

NASA Astrophysics Data System (ADS)

Javidnia, Hossein; Corcoran, Peter

2018-03-01

Postcapture refocusing effect in smartphone cameras is achievable using focal stacks. However, the accuracy of this effect is totally dependent on the combination of the depth layers in the stack. The accuracy of the extended depth of field effect in this application can be improved significantly by computing an accurate depth map, which has been an open issue for decades. To tackle this issue, a framework is proposed based on a preconditioned alternating direction method of multipliers for depth from the focal stack and synthetic defocus application. In addition to its ability to provide high structural accuracy, the optimization function of the proposed framework can, in fact, converge faster and better than state-of-the-art methods. The qualitative evaluation has been done on 21 sets of focal stacks and the optimization function has been compared against five other methods. Later, 10 light field image sets have been transformed into focal stacks for quantitative evaluation purposes. Preliminary results indicate that the proposed framework has a better performance in terms of structural accuracy and optimization in comparison to the current state-of-the-art methods.

Near-Infrared Spectrum Detection of Wheat Gluten Protein Content Based on a Combined Filtering Method.

PubMed

Cai, Jian-Hua

2017-09-01

To eliminate the random error of the derivative near-IR (NIR) spectrum and to improve model stability and the prediction accuracy of the gluten protein content, a combined method is proposed for pretreatment of the NIR spectrum based on both empirical mode decomposition and the wavelet soft-threshold method. The principle and the steps of the method are introduced and the denoising effect is evaluated. The wheat gluten protein content is calculated based on the denoised spectrum, and the results are compared with those of the nine-point smoothing method and the wavelet soft-threshold method. Experimental results show that the proposed combined method is effective in completing pretreatment of the NIR spectrum, and the proposed method improves the accuracy of detection of wheat gluten protein content from the NIR spectrum.

Remote kinematic training for patients with chronic neck pain: a randomised controlled trial.

PubMed

Sarig Bahat, Hilla; Croft, Kate; Carter, Courtney; Hoddinott, Anna; Sprecher, Elliot; Treleaven, Julia

2018-06-01

To evaluate short- and intermediate-term effects of kinematic training (KT) using virtual reality (VR) or laser in patients with chronic neck pain. A randomised controlled trial with three arms (laser, VR, control) to post-intervention (N = 90), and two arms (laser or VR) continuing to 3 months follow-up. Home training intervention was provided during 4 weeks to VR and laser groups while control group waited. Primary outcome measures included neck disability index (NDI), global perceived effect (GPE), and cervical motion velocity (mean and peak). Secondary outcome measures included pain intensity (VAS), health status (EQ5D), kinesiophobia (TSK), range, smoothness, and accuracy of neck motion as measured by the neck VR system. Measures were taken at baseline, immediately post-training, and 3 months later. Ninety patients with neck pain were randomised to the trial, of which 76 completed 1 month follow-up, and 56 the 3 months follow-up. Significant improvements were demonstrated in NDI and velocity with good effect sizes in intervention groups compared to control. No within-group changes were presented in the control group, compared to global improvements in intervention groups. Velocity significantly improved at both time points in both groups. NDI, VAS, EQ5D, TSK and accuracy significantly improved at both time points in VR and in laser at 3 months evaluation in all but TSK. GPE scores showed 74-84% of participants perceived improvement and/or were satisfied. Significant advantages to the VR group compared to laser were found in velocity, pain intensity, health status and accuracy at both time points. The results support home kinematic training using VR or laser for improving disability, neck pain and kinematics in the short and intermediate term with an advantage to the VR group. The results provide directions for future research, use and development. ACTRN12615000231549.

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

Accurate ECG diagnosis of atrial tachyarrhythmias using quantitative analysis: a prospective diagnostic and cost-effectiveness study.

PubMed

Krummen, David E; Patel, Mitul; Nguyen, Hong; Ho, Gordon; Kazi, Dhruv S; Clopton, Paul; Holland, Marian C; Greenberg, Scott L; Feld, Gregory K; Faddis, Mitchell N; Narayan, Sanjiv M

2010-11-01

Quantitative ECG Analysis. Optimal atrial tachyarrhythmia management is facilitated by accurate electrocardiogram interpretation, yet typical atrial flutter (AFl) may present without sawtooth F-waves or RR regularity, and atrial fibrillation (AF) may be difficult to separate from atypical AFl or rapid focal atrial tachycardia (AT). We analyzed whether improved diagnostic accuracy using a validated analysis tool significantly impacts costs and patient care. We performed a prospective, blinded, multicenter study using a novel quantitative computerized algorithm to identify atrial tachyarrhythmia mechanism from the surface ECG in patients referred for electrophysiology study (EPS). In 122 consecutive patients (age 60 ± 12 years) referred for EPS, 91 sustained atrial tachyarrhythmias were studied. ECGs were also interpreted by 9 physicians from 3 specialties for comparison and to allow healthcare system modeling. Diagnostic accuracy was compared to the diagnosis at EPS. A Markov model was used to estimate the impact of improved arrhythmia diagnosis. We found 13% of typical AFl ECGs had neither sawtooth flutter waves nor RR regularity, and were misdiagnosed by the majority of clinicians (0/6 correctly diagnosed by consensus visual interpretation) but correctly by quantitative analysis in 83% (5/6, P = 0.03). AF diagnosis was also improved through use of the algorithm (92%) versus visual interpretation (primary care: 76%, P < 0.01). Economically, we found that these improvements in diagnostic accuracy resulted in an average cost-savings of $1,303 and 0.007 quality-adjusted-life-years per patient. Typical AFl and AF are frequently misdiagnosed using visual criteria. Quantitative analysis improves diagnostic accuracy and results in improved healthcare costs and patient outcomes. © 2010 Wiley Periodicals, Inc.

Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

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

Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar

With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual modelmore » has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.« less

An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks.

PubMed

Yan, Jun; Yu, Kegen; Chen, Ruizhi; Chen, Liang

2017-05-30

In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position error. In the coarse localization phase, by formulating target localization as a sparse signal recovery problem, grids with recovery vector components greater than a threshold are chosen as the candidate target grids. In the fine localization phase, by partitioning each candidate grid, the target position in a grid is iteratively refined by using the minimum residual error rule and the least-squares technique. When all the candidate target grids are iteratively partitioned and the measurement matrix is updated, the recovery vector is re-estimated. Threshold-based detection is employed again to determine the target grids and hence the target population. As a consequence, both the target population and the position estimation accuracy can be significantly improved. Simulation results demonstrate that the proposed approach achieves the best accuracy among all the algorithms compared.

Vascular input function correction of inflow enhancement for improved pharmacokinetic modeling of liver DCE-MRI.

PubMed

Ning, Jia; Schubert, Tilman; Johnson, Kevin M; Roldán-Alzate, Alejandro; Chen, Huijun; Yuan, Chun; Reeder, Scott B

2018-06-01

To propose a simple method to correct vascular input function (VIF) due to inflow effects and to test whether the proposed method can provide more accurate VIFs for improved pharmacokinetic modeling. A spoiled gradient echo sequence-based inflow quantification and contrast agent concentration correction method was proposed. Simulations were conducted to illustrate improvement in the accuracy of VIF estimation and pharmacokinetic fitting. Animal studies with dynamic contrast-enhanced MR scans were conducted before, 1 week after, and 2 weeks after portal vein embolization (PVE) was performed in the left portal circulation of pigs. The proposed method was applied to correct the VIFs for model fitting. Pharmacokinetic parameters fitted using corrected and uncorrected VIFs were compared between different lobes and visits. Simulation results demonstrated that the proposed method can improve accuracy of VIF estimation and pharmacokinetic fitting. In animal study results, pharmacokinetic fitting using corrected VIFs demonstrated changes in perfusion consistent with changes expected after PVE, whereas the perfusion estimates derived by uncorrected VIFs showed no significant changes. The proposed correction method improves accuracy of VIFs and therefore provides more precise pharmacokinetic fitting. This method may be promising in improving the reliability of perfusion quantification. Magn Reson Med 79:3093-3102, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Influence of different topographic correction strategies on mountain vegetation classification accuracy in the Lancang Watershed, China

NASA Astrophysics Data System (ADS)

Zhang, Zhiming; de Wulf, Robert R.; van Coillie, Frieke M. B.; Verbeke, Lieven P. C.; de Clercq, Eva M.; Ou, Xiaokun

2011-01-01

Mapping of vegetation using remote sensing in mountainous areas is considerably hampered by topographic effects on the spectral response pattern. A variety of topographic normalization techniques have been proposed to correct these illumination effects due to topography. The purpose of this study was to compare six different topographic normalization methods (Cosine correction, Minnaert correction, C-correction, Sun-canopy-sensor correction, two-stage topographic normalization, and slope matching technique) for their effectiveness in enhancing vegetation classification in mountainous environments. Since most of the vegetation classes in the rugged terrain of the Lancang Watershed (China) did not feature a normal distribution, artificial neural networks (ANNs) were employed as a classifier. Comparing the ANN classifications, none of the topographic correction methods could significantly improve ETM+ image classification overall accuracy. Nevertheless, at the class level, the accuracy of pine forest could be increased by using topographically corrected images. On the contrary, oak forest and mixed forest accuracies were significantly decreased by using corrected images. The results also showed that none of the topographic normalization strategies was satisfactorily able to correct for the topographic effects in severely shadowed areas.

Oxytocin Reduces Face Processing Time but Leaves Recognition Accuracy and Eye-Gaze Unaffected.

PubMed

Hubble, Kelly; Daughters, Katie; Manstead, Antony S R; Rees, Aled; Thapar, Anita; van Goozen, Stephanie H M

2017-01-01

Previous studies have found that oxytocin (OXT) can improve the recognition of emotional facial expressions; it has been proposed that this effect is mediated by an increase in attention to the eye-region of faces. Nevertheless, evidence in support of this claim is inconsistent, and few studies have directly tested the effect of oxytocin on emotion recognition via altered eye-gaze Methods: In a double-blind, within-subjects, randomized control experiment, 40 healthy male participants received 24 IU intranasal OXT and placebo in two identical experimental sessions separated by a 2-week interval. Visual attention to the eye-region was assessed on both occasions while participants completed a static facial emotion recognition task using medium intensity facial expressions. Although OXT had no effect on emotion recognition accuracy, recognition performance was improved because face processing was faster across emotions under the influence of OXT. This effect was marginally significant (p<.06). Consistent with a previous study using dynamic stimuli, OXT had no effect on eye-gaze patterns when viewing static emotional faces and this was not related to recognition accuracy or face processing time. These findings suggest that OXT-induced enhanced facial emotion recognition is not necessarily mediated by an increase in attention to the eye-region of faces, as previously assumed. We discuss several methodological issues which may explain discrepant findings and suggest the effect of OXT on visual attention may differ depending on task requirements. (JINS, 2017, 23, 23-33).

Accuracy of the unified approach in maternally influenced traits - illustrated by a simulation study in the honey bee (Apis mellifera)

PubMed Central

2013-01-01

Background The honey bee is an economically important species. With a rapid decline of the honey bee population, it is necessary to implement an improved genetic evaluation methodology. In this study, we investigated the applicability of the unified approach and its impact on the accuracy of estimation of breeding values for maternally influenced traits on a simulated dataset for the honey bee. Due to the limitation to the number of individuals that can be genotyped in a honey bee population, the unified approach can be an efficient strategy to increase the genetic gain and to provide a more accurate estimation of breeding values. We calculated the accuracy of estimated breeding values for two evaluation approaches, the unified approach and the traditional pedigree based approach. We analyzed the effects of different heritabilities as well as genetic correlation between direct and maternal effects on the accuracy of estimation of direct, maternal and overall breeding values (sum of maternal and direct breeding values). The genetic and reproductive biology of the honey bee was accounted for by taking into consideration characteristics such as colony structure, uncertain paternity, overlapping generations and polyandry. In addition, we used a modified numerator relationship matrix and a realistic genome for the honey bee. Results For all values of heritability and correlation, the accuracy of overall estimated breeding values increased significantly with the unified approach. The increase in accuracy was always higher for the case when there was no correlation as compared to the case where a negative correlation existed between maternal and direct effects. Conclusions Our study shows that the unified approach is a useful methodology for genetic evaluation in honey bees, and can contribute immensely to the improvement of traits of apicultural interest such as resistance to Varroa or production and behavioural traits. In particular, the study is of great interest for cases where negative correlation between maternal and direct effects and uncertain paternity exist, thus, is of relevance for other species as well. The study also provides an important framework for simulating genomic and pedigree datasets that will prove to be helpful for future studies. PMID:23647776

Accuracy of the unified approach in maternally influenced traits--illustrated by a simulation study in the honey bee (Apis mellifera).

PubMed

Gupta, Pooja; Reinsch, Norbert; Spötter, Andreas; Conrad, Tim; Bienefeld, Kaspar

2013-05-06

The honey bee is an economically important species. With a rapid decline of the honey bee population, it is necessary to implement an improved genetic evaluation methodology. In this study, we investigated the applicability of the unified approach and its impact on the accuracy of estimation of breeding values for maternally influenced traits on a simulated dataset for the honey bee. Due to the limitation to the number of individuals that can be genotyped in a honey bee population, the unified approach can be an efficient strategy to increase the genetic gain and to provide a more accurate estimation of breeding values. We calculated the accuracy of estimated breeding values for two evaluation approaches, the unified approach and the traditional pedigree based approach. We analyzed the effects of different heritabilities as well as genetic correlation between direct and maternal effects on the accuracy of estimation of direct, maternal and overall breeding values (sum of maternal and direct breeding values). The genetic and reproductive biology of the honey bee was accounted for by taking into consideration characteristics such as colony structure, uncertain paternity, overlapping generations and polyandry. In addition, we used a modified numerator relationship matrix and a realistic genome for the honey bee. For all values of heritability and correlation, the accuracy of overall estimated breeding values increased significantly with the unified approach. The increase in accuracy was always higher for the case when there was no correlation as compared to the case where a negative correlation existed between maternal and direct effects. Our study shows that the unified approach is a useful methodology for genetic evaluation in honey bees, and can contribute immensely to the improvement of traits of apicultural interest such as resistance to Varroa or production and behavioural traits. In particular, the study is of great interest for cases where negative correlation between maternal and direct effects and uncertain paternity exist, thus, is of relevance for other species as well. The study also provides an important framework for simulating genomic and pedigree datasets that will prove to be helpful for future studies.

Diagnostic Accuracy of the Slump Test for Identifying Neuropathic Pain in the Lower Limb.

PubMed

Urban, Lawrence M; MacNeil, Brian J

2015-08-01

Diagnostic accuracy study with nonconsecutive enrollment. To assess the diagnostic accuracy of the slump test for neuropathic pain (NeP) in those with low to moderate levels of chronic low back pain (LBP), and to determine whether accuracy of the slump test improves by adding anatomical or qualitative pain descriptors. Neuropathic pain has been linked with poor outcomes, likely due to inadequate diagnosis, which precludes treatment specific for NeP. Current diagnostic approaches are time consuming or lack accuracy. A convenience sample of 21 individuals with LBP, with or without radiating leg pain, was recruited. A standardized neurosensory examination was used to determine the reference diagnosis for NeP. Afterward, the slump test was administered to all participants. Reports of pain location and quality produced during the slump test were recorded. The neurosensory examination designated 11 of the 21 participants with LBP/sciatica as having NeP. The slump test displayed high sensitivity (0.91), moderate specificity (0.70), a positive likelihood ratio of 3.03, and a negative likelihood ratio of 0.13. Adding the criterion of pain below the knee significantly increased specificity to 1.00 (positive likelihood ratio = 11.9). Pain-quality descriptors did not improve diagnostic accuracy. The slump test was highly sensitive in identifying NeP within the study sample. Adding a pain-location criterion improved specificity. Combining the diagnostic outcomes was very effective in identifying all those without NeP and half of those with NeP. Limitations arising from the small and narrow spectrum of participants with LBP/sciatica sampled within the study prevent application of the findings to a wider population. Diagnosis, level 4-.

Team training in obstetrics: A multi-level evaluation.

PubMed

Sonesh, Shirley C; Gregory, Megan E; Hughes, Ashley M; Feitosa, Jennifer; Benishek, Lauren E; Verhoeven, Dana; Patzer, Brady; Salazar, Maritza; Gonzalez, Laura; Salas, Eduardo

2015-09-01

Obstetric complications and adverse patient events are often preventable. Teamwork and situational awareness (SA) can improve detection and coordination of critical obstetric (OB) emergencies, subsequently improving decision making and patient outcomes. The purpose of this study was to assess the effectiveness of a team training intervention in improving learning and transfer of teamwork, SA, decision making, and cognitive bias as well as patient outcomes in OB. An adapted TeamSTEPPS training program was delivered to OB clinicians. Training targeted communication, mutual support, situation monitoring, leadership, SA, and cognitive bias. We conducted a repeated measures multilevel evaluation of the training using Kirkpatrick's (1994) framework of training evaluation to determine impact on trainee reactions, learning, transfer, and results. Data were collected using surveys, situational judgment tests (SJTs), observations, and patient chart reviews. Participants perceived the training as useful. Additionally, participants acquired knowledge of communication strategies, though knowledge of other team competencies did not significantly improve nor did self-reported teamwork on the unit. Although SJT decision accuracy did not significantly improve for all scenarios, results of behavioral observation suggest that decision accuracy significantly improved on the job, and there was a marginally significant reduction in babies' hospital length of stay. These findings indicate that the training intervention was partially effective, but more work needs to be done to determine the conditions under which training is most effective, and the ways in which to sustain improvements. Future research is needed to confirm its generalizability to additional OB units and departments. (c) 2015 APA, all rights reserved).

EEG source localization: Sensor density and head surface coverage.

PubMed

Song, Jasmine; Davey, Colin; Poulsen, Catherine; Luu, Phan; Turovets, Sergei; Anderson, Erik; Li, Kai; Tucker, Don

2015-12-30

The accuracy of EEG source localization depends on a sufficient sampling of the surface potential field, an accurate conducting volume estimation (head model), and a suitable and well-understood inverse technique. The goal of the present study is to examine the effect of sampling density and coverage on the ability to accurately localize sources, using common linear inverse weight techniques, at different depths. Several inverse methods are examined, using the popular head conductivity. Simulation studies were employed to examine the effect of spatial sampling of the potential field at the head surface, in terms of sensor density and coverage of the inferior and superior head regions. In addition, the effects of sensor density and coverage are investigated in the source localization of epileptiform EEG. Greater sensor density improves source localization accuracy. Moreover, across all sampling density and inverse methods, adding samples on the inferior surface improves the accuracy of source estimates at all depths. More accurate source localization of EEG data can be achieved with high spatial sampling of the head surface electrodes. The most accurate source localization is obtained when the voltage surface is densely sampled over both the superior and inferior surfaces. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Improving the accuracy of CT dimensional metrology by a novel beam hardening correction method

NASA Astrophysics Data System (ADS)

Zhang, Xiang; Li, Lei; Zhang, Feng; Xi, Xiaoqi; Deng, Lin; Yan, Bin

2015-01-01

Its powerful nondestructive characteristics are attracting more and more research into the study of computed tomography (CT) for dimensional metrology, which offers a practical alternative to the common measurement methods. However, the inaccuracy and uncertainty severely limit the further utilization of CT for dimensional metrology due to many factors, among which the beam hardening (BH) effect plays a vital role. This paper mainly focuses on eliminating the influence of the BH effect in the accuracy of CT dimensional metrology. To correct the BH effect, a novel exponential correction model is proposed. The parameters of the model are determined by minimizing the gray entropy of the reconstructed volume. In order to maintain the consistency and contrast of the corrected volume, a punishment term is added to the cost function, enabling more accurate measurement results to be obtained by the simple global threshold method. The proposed method is efficient, and especially suited to the case where there is a large difference in gray value between material and background. Different spheres with known diameters are used to verify the accuracy of dimensional measurement. Both simulation and real experimental results demonstrate the improvement in measurement precision. Moreover, a more complex workpiece is also tested to show that the proposed method is of general feasibility.

A low-cost GPS/INS integrated vehicle heading angle measurement system

NASA Astrophysics Data System (ADS)

Wu, Ye; Gao, Tongyue; Ding, Yi

2018-04-01

GPS can provide continuous heading information, but the accuracy is easily affected by the velocity and shelter from buildings or trees. For vehicle systems, we propose a low-cost heading angle update algorithm. Based on the GPS/INS integrated navigation kalman filter, we add the GPS heading angle to the measurement vector, and establish its error model. The experiment results show that this algorithm can effectively improve the accuracy of GPS heading angle.

Effect of cleaning status on accuracy and precision of oxygen flowmeters of various ages.

PubMed

Fissekis, Stephanie; Hodgson, David S; Bello, Nora M

2017-07-01

To evaluate oxygen flowmeters for accuracy and precision, assess the effects of cleaning and assess conformity to the American Society for Testing Materials (ASTM) standards. Experimental study. The flow of oxygen flowmeters from 31 anesthesia machines aged 1-45 years was measured before and after cleaning using a volumetric flow analyzer set at 0.5, 1.0, 2.0, 3.0, and 4.0 L minute -1 . A general linear mixed models approach was used to assess flow accuracy and precision. Flowmeters 1 year of age delivered accurate mean oxygen flows at all settings regardless of cleaning status. Flowmeters ≥5 years of age underdelivered at flows of 3.0 and 4.0 L minute -1 . Flowmeters ≥12 years underdelivered at flows of 2.0, 3.0 and 4.0 L minute -1 prior to cleaning. There was no evidence of any beneficial effect of cleaning on accuracy of flowmeters 5-12 years of age (p > 0.22), but the accuracy of flowmeters ≥15 years of age was improved by cleaning (p < 0.05). Regardless of age, cleaning increased precision, decreasing flow variability by approximately 17%. Nine of 31 uncleaned flowmeters did not meet ASTM standards. After cleaning, a different set of nine flowmeters did not meet standards, including three that had met standards prior to cleaning. Older flowmeters were more likely to underdeliver oxygen, especially at higher flows. Regardless of age, cleaning decreased flow variability, improving precision. However, flowmeters still may fail to meet ASTM standards, regardless of cleaning status. Cleaning anesthesia machine oxygen flowmeters improved precision for all tested machines and partially corrected inaccuracies in flowmeters ≥15 years old. A notable proportion of flowmeters did not meet ASTM standards. Cleaning did not ensure that they subsequently conformed to ASTM standards. We recommend annual flow output validation to identify whether flowmeters are acceptable for continued clinical use. Copyright © 2017 Association of Veterinary Anaesthetists and American College of Veterinary Anesthesia and Analgesia. Published by Elsevier Ltd. All rights reserved.

Effects of Recovery Behavior and Strain-Rate Dependence of Stress-Strain Curve on Prediction Accuracy of Thermal Stress Analysis During Casting

NASA Astrophysics Data System (ADS)

Motoyama, Yuichi; Shiga, Hidetoshi; Sato, Takeshi; Kambe, Hiroshi; Yoshida, Makoto

2017-06-01

Recovery behavior (recovery) and strain-rate dependence of the stress-strain curve (strain-rate dependence) are incorporated into constitutive equations of alloys to predict residual stress and thermal stress during casting. Nevertheless, few studies have systematically investigated the effects of these metallurgical phenomena on the prediction accuracy of thermal stress in a casting. This study compares the thermal stress analysis results with in situ thermal stress measurement results of an Al-Si-Cu specimen during casting. The results underscore the importance for the alloy constitutive equation of incorporating strain-rate dependence to predict thermal stress that develops at high temperatures where the alloy shows strong strain-rate dependence of the stress-strain curve. However, the prediction accuracy of the thermal stress developed at low temperatures did not improve by considering the strain-rate dependence. Incorporating recovery into the constitutive equation improved the accuracy of the simulated thermal stress at low temperatures. Results of comparison implied that the constitutive equation should include strain-rate dependence to simulate defects that develop from thermal stress at high temperatures, such as hot tearing and hot cracking. Recovery should be incorporated into the alloy constitutive equation to predict the casting residual stress and deformation caused by the thermal stress developed mainly in the low temperature range.

Automatically identifying health outcome information in MEDLINE records.

PubMed

Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George

2006-01-01

Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.

Reducing errors benefits the field-based learning of a fundamental movement skill in children.

PubMed

Capio, C M; Poolton, J M; Sit, C H P; Holmstrom, M; Masters, R S W

2013-03-01

Proficient fundamental movement skills (FMS) are believed to form the basis of more complex movement patterns in sports. This study examined the development of the FMS of overhand throwing in children through either an error-reduced (ER) or error-strewn (ES) training program. Students (n = 216), aged 8-12 years (M = 9.16, SD = 0.96), practiced overhand throwing in either a program that reduced errors during practice (ER) or one that was ES. ER program reduced errors by incrementally raising the task difficulty, while the ES program had an incremental lowering of task difficulty. Process-oriented assessment of throwing movement form (Test of Gross Motor Development-2) and product-oriented assessment of throwing accuracy (absolute error) were performed. Changes in performance were examined among children in the upper and lower quartiles of the pretest throwing accuracy scores. ER training participants showed greater gains in movement form and accuracy, and performed throwing more effectively with a concurrent secondary cognitive task. Movement form improved among girls, while throwing accuracy improved among children with low ability. Reduced performance errors in FMS training resulted in greater learning than a program that did not restrict errors. Reduced cognitive processing costs (effective dual-task performance) associated with such approach suggest its potential benefits for children with developmental conditions. © 2011 John Wiley & Sons A/S.

Alcohol-related hot-spot analysis and prediction : final report.

DOT National Transportation Integrated Search

2017-05-01

This project developed methods to more accurately identify alcohol-related crash hot spots, ultimately allowing for more effective and efficient enforcement and safety campaigns. Advancements in accuracy came from improving the calculation of spatial...

One improved LSB steganography algorithm

NASA Astrophysics Data System (ADS)

Song, Bing; Zhang, Zhi-hong

2013-03-01

It is easy to be detected by X2 and RS steganalysis with high accuracy that using LSB algorithm to hide information in digital image. We started by selecting information embedded location and modifying the information embedded method, combined with sub-affine transformation and matrix coding method, improved the LSB algorithm and a new LSB algorithm was proposed. Experimental results show that the improved one can resist the X2 and RS steganalysis effectively.

Continuous Glucose Monitoring in Subjects with Type 1 Diabetes: Improvement in Accuracy by Correcting for Background Current

PubMed Central

Youssef, Joseph El; Engle, Julia M.; Massoud, Ryan G.; Ward, W. Kenneth

2010-01-01

Abstract Background A cause of suboptimal accuracy in amperometric glucose sensors is the presence of a background current (current produced in the absence of glucose) that is not accounted for. We hypothesized that a mathematical correction for the estimated background current of a commercially available sensor would lead to greater accuracy compared to a situation in which we assumed the background current to be zero. We also tested whether increasing the frequency of sensor calibration would improve sensor accuracy. Methods This report includes analysis of 20 sensor datasets from seven human subjects with type 1 diabetes. Data were divided into a training set for algorithm development and a validation set on which the algorithm was tested. A range of potential background currents was tested. Results Use of the background current correction of 4 nA led to a substantial improvement in accuracy (improvement of absolute relative difference or absolute difference of 3.5–5.5 units). An increase in calibration frequency led to a modest accuracy improvement, with an optimum at every 4 h. Conclusions Compared to no correction, a correction for the estimated background current of a commercially available glucose sensor led to greater accuracy and better detection of hypoglycemia and hyperglycemia. The accuracy-optimizing scheme presented here can be implemented in real time. PMID:20879968

Effects of grammar instruction and fluency training on the learning of the and a by native speakers of japanese

PubMed Central

Shimamune, Satoru; Jitsumori, Masako

1999-01-01

In a computer-assisted sentence completion task, the effects of grammar instruction and fluency training on learning the use of the definite and indefinite articles of English were examined. Forty-eight native Japanese-speaking students were assigned to four groups: with grammar/accuracy (G/A), without grammar/accuracy (N/A), with grammar/fluency (G/F), and without grammar/fluency (N/F). In the G/A and N/A groups, training continued until performance reached 100% accuracy (accuracy criterion). In the G/F and N/F groups, training continued until 100% accuracy was reached and the correct responses were made at a high speed (fluency criterion). Grammar instruction was given to participants in the G/A and G/F groups but not to those in the N/A and N/F groups. Generalization to new sentences was tested immediately after reaching the required criterion. High levels of generalization occurred, regardless of the type of mastery criterion and whether the grammar instruction was given. Retention tests were conducted 4, 6, and 8 weeks after training. Fluency training effectively improved retention of the performance attained without the grammar instruction. This effect was diminished when grammar instruction was given during training. Learning grammatical rules was not necessary for the generalized use of appropriate definite and indefinite articles or for the maintenance of the performance attained through fluency training. PMID:22477154

Accuracy assessment of Precise Point Positioning with multi-constellation GNSS data under ionospheric scintillation effects

NASA Astrophysics Data System (ADS)

Marques, Haroldo Antonio; Marques, Heloísa Alves Silva; Aquino, Marcio; Veettil, Sreeja Vadakke; Monico, João Francisco Galera

2018-02-01

GPS and GLONASS are currently the Global Navigation Satellite Systems (GNSS) with full operational capacity. The integration of GPS, GLONASS and future GNSS constellations can provide better accuracy and more reliability in geodetic positioning, in particular for kinematic Precise Point Positioning (PPP), where the satellite geometry is considered a limiting factor to achieve centimeter accuracy. The satellite geometry can change suddenly in kinematic positioning in urban areas or under conditions of strong atmospheric effects such as for instance ionospheric scintillation that may degrade satellite signal quality, causing cycle slips and even loss of lock. Scintillation is caused by small scale irregularities in the ionosphere and is characterized by rapid changes in amplitude and phase of the signal, which are more severe in equatorial and high latitudes geomagnetic regions. In this work, geodetic positioning through the PPP method was evaluated with integrated GPS and GLONASS data collected in the equatorial region under varied scintillation conditions. The GNSS data were processed in kinematic PPP mode and the analyses show accuracy improvements of up to 60% under conditions of strong scintillation when using multi-constellation data instead of GPS data alone. The concepts and analyses related to the ionospheric scintillation effects, the mathematical model involved in PPP with GPS and GLONASS data integration as well as accuracy assessment with data collected under ionospheric scintillation effects are presented.

Improving critical thinking and clinical reasoning with a continuing education course.

PubMed

Cruz, Dina Monteiro; Pimenta, Cibele Mattos; Lunney, Margaret

2009-03-01

Continuing education courses related to critical thinking and clinical reasoning are needed to improve the accuracy of diagnosis. This study evaluated a 4-day, 16-hour continuing education course conducted in Brazil.Thirty-nine nurses completed a pretest and a posttest consisting of two written case studies designed to measure the accuracy of nurses' diagnoses. There were significant differences in accuracy from pretest to posttest for case 1 (p = .008) and case 2 (p = .042) and overall (p = .001). Continuing education courses should be implemented to improve the accuracy of nurses' diagnoses.

An Examination of Treatment Effects of a First Grade Literacy Intervention Using a Regression Discontinuity Design

ERIC Educational Resources Information Center

Chaparro, Erin A.; Smolkowski, Keith; Baker, Scott K.; Fien, Hank; Smith, Jean Louise M.

2012-01-01

Response to Intervention (RTI) is a tiered instructional delivery framework developed to meet the needs of all students and has the potential to improve reading achievement, prevent reading problems, and improve identification accuracy for learning disabilities. Tier 1 typically occurs in the context of the general education classroom and is…

Artificial dissipation and central difference schemes for the Euler and Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Swanson, R. C.; Turkel, Eli

1987-01-01

An artificial dissipation model, including boundary treatment, that is employed in many central difference schemes for solving the Euler and Navier-Stokes equations is discussed. Modifications of this model such as the eigenvalue scaling suggested by upwind differencing are examined. Multistage time stepping schemes with and without a multigrid method are used to investigate the effects of changes in the dissipation model on accuracy and convergence. Improved accuracy for inviscid and viscous airfoil flow is obtained with the modified eigenvalue scaling. Slower convergence rates are experienced with the multigrid method using such scaling. The rate of convergence is improved by applying a dissipation scaling function that depends on mesh cell aspect ratio.

Spelling on the fly: investigating a pentop computer to improve the spelling skills of three elementary students with disabilities.

PubMed

Doughty, Teresa Taber; Bouck, Emily C; Bassette, Laura; Szwed, Kathryn; Flanagan, Sara

2013-01-01

The purpose of this study was to examine the effects of a pentop computer and accompanying spelling software on the spelling accuracy and academic engagement behavior in three elementary students with disabilities who were served in a resource room setting. Using a multiple baseline across students single subject research design, researchers determined student use of the pentop computer--the FLYPen--and its spelling software may serve as an equivalent intervention to traditional spelling instruction. While academic engagement performance increased considerably for students when using the FLYPen, results indicated little to no improvement over traditional instruction in spelling accuracy. Implications and suggestions for future research are presented.

Improving reading skills in students with dyslexia: the efficacy of a sublexical training with rhythmic background

PubMed Central

Bonacina, Silvia; Cancer, Alice; Lanzi, Pier Luca; Lorusso, Maria Luisa; Antonietti, Alessandro

2015-01-01

The core deficit underlying developmental dyslexia (DD) has been identified in difficulties in dynamic and rapidly changing auditory information processing, which contribute to the development of impaired phonological representations for words. It has been argued that enhancing basic musical rhythm perception skills in children with DD may have a positive effect on reading abilities because music and language share common mechanisms and thus transfer effects from the former to the latter are expected to occur. A computer-assisted training, called Rhythmic Reading Training (RRT), was designed in which reading exercises are combined with rhythm background. Fourteen junior high school students with DD took part to 9 biweekly individual sessions of 30 min in which RRT was implemented. Reading improvements after the intervention period were compared with ones of a matched control group of 14 students with DD who received no intervention. Results indicated that RRT had a positive effect on both reading speed and accuracy and significant effects were found on short pseudo-words reading speed, long pseudo-words reading speed, high frequency long words reading accuracy, and text reading accuracy. No difference in rhythm perception between the intervention and control group were found. Findings suggest that rhythm facilitates the development of reading skill because of the temporal structure it imposes to word decoding. PMID:26500581

A Comparison between the Effect of Free Time and Daily Report Cards on the Academic Behavior of Junior High School Students.

ERIC Educational Resources Information Center

Martin, R. C.; McLaughlin, T. F.

1981-01-01

When the effectiveness of free time and daily report card systems on assignment completion and accuracy of four junior high school special education students were compared, results indicated that both procedures improved students' performance. (Author)

Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin's frog.

PubMed

Uribe-Rivera, David E; Soto-Azat, Claudio; Valenzuela-Sánchez, Andrés; Bizama, Gustavo; Simonetti, Javier A; Pliscoff, Patricio

2017-07-01

Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios. © 2017 by the Ecological Society of America.

The effects of aging on ERP correlates of source memory retrieval for self-referential information.

PubMed

Dulas, Michael R; Newsome, Rachel N; Duarte, Audrey

2011-03-04

Numerous behavioral studies have suggested that normal aging negatively affects source memory accuracy for various kinds of associations. Neuroimaging evidence suggests that less efficient retrieval processing (temporally delayed and attenuated) may contribute to these impairments. Previous aging studies have not compared source memory accuracy and corresponding neural activity for different kinds of source details; namely, those that have been encoded via a more or less effective strategy. Thus, it is not yet known whether encoding source details in a self-referential manner, a strategy suggested to promote successful memory in the young and old, may enhance source memory accuracy and reduce the commonly observed age-related changes in neural activity associated with source memory retrieval. Here, we investigated these issues by using event-related potentials (ERPs) to measure the effects of aging on the neural correlates of successful source memory retrieval ("old-new effects") for objects encoded either self-referentially or self-externally. Behavioral results showed that both young and older adults demonstrated better source memory accuracy for objects encoded self-referentially. ERP results showed that old-new effects onsetted earlier for self-referentially encoded items in both groups and that age-related differences in the onset latency of these effects were reduced for self-referentially, compared to self-externally, encoded items. These results suggest that the implementation of an effective encoding strategy, like self-referential processing, may lead to more efficient retrieval, which in turn may improve source memory accuracy in both young and older adults. Published by Elsevier B.V.

Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm.

PubMed

Zhang, Tao; Zhu, Yongyun; Zhou, Feng; Yan, Yaxiong; Tong, Jinwu

2017-06-17

Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability.

Predictive accuracy of particle filtering in dynamic models supporting outbreak projections.

PubMed

Safarishahrbijari, Anahita; Teyhouee, Aydin; Waldner, Cheryl; Liu, Juxin; Osgood, Nathaniel D

2017-09-26

While a new generation of computational statistics algorithms and availability of data streams raises the potential for recurrently regrounding dynamic models with incoming observations, the effectiveness of such arrangements can be highly subject to specifics of the configuration (e.g., frequency of sampling and representation of behaviour change), and there has been little attempt to identify effective configurations. Combining dynamic models with particle filtering, we explored a solution focusing on creating quickly formulated models regrounded automatically and recurrently as new data becomes available. Given a latent underlying case count, we assumed that observed incident case counts followed a negative binomial distribution. In accordance with the condensation algorithm, each such observation led to updating of particle weights. We evaluated the effectiveness of various particle filtering configurations against each other and against an approach without particle filtering according to the accuracy of the model in predicting future prevalence, given data to a certain point and a norm-based discrepancy metric. We examined the effectiveness of particle filtering under varying times between observations, negative binomial dispersion parameters, and rates with which the contact rate could evolve. We observed that more frequent observations of empirical data yielded super-linearly improved accuracy in model predictions. We further found that for the data studied here, the most favourable assumptions to make regarding the parameters associated with the negative binomial distribution and changes in contact rate were robust across observation frequency and the observation point in the outbreak. Combining dynamic models with particle filtering can perform well in projecting future evolution of an outbreak. Most importantly, the remarkable improvements in predictive accuracy resulting from more frequent sampling suggest that investments to achieve efficient reporting mechanisms may be more than paid back by improved planning capacity. The robustness of the results on particle filter configuration in this case study suggests that it may be possible to formulate effective standard guidelines and regularized approaches for such techniques in particular epidemiological contexts. Most importantly, the work tentatively suggests potential for health decision makers to secure strong guidance when anticipating outbreak evolution for emerging infectious diseases by combining even very rough models with particle filtering method.

Software reliability studies

NASA Technical Reports Server (NTRS)

Hoppa, Mary Ann; Wilson, Larry W.

1994-01-01

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Our research has shown that by improving the quality of the data one can greatly improve the predictions. We are working on methodologies which control some of the randomness inherent in the standard data generation processes in order to improve the accuracy of predictions. Our contribution is twofold in that we describe an experimental methodology using a data structure called the debugging graph and apply this methodology to assess the robustness of existing models. The debugging graph is used to analyze the effects of various fault recovery orders on the predictive accuracy of several well-known software reliability algorithms. We found that, along a particular debugging path in the graph, the predictive performance of different models can vary greatly. Similarly, just because a model 'fits' a given path's data well does not guarantee that the model would perform well on a different path. Further we observed bug interactions and noted their potential effects on the predictive process. We saw that not only do different faults fail at different rates, but that those rates can be affected by the particular debugging stage at which the rates are evaluated. Based on our experiment, we conjecture that the accuracy of a reliability prediction is affected by the fault recovery order as well as by fault interaction.

A Study on Micropipetting Detection Technology of Automatic Enzyme Immunoassay Analyzer.

PubMed

Shang, Zhiwu; Zhou, Xiangping; Li, Cheng; Tsai, Sang-Bing

2018-04-10

In order to improve the accuracy and reliability of micropipetting, a method of micro-pipette detection and calibration combining the dynamic pressure monitoring in pipetting process and quantitative identification of pipette volume in image processing was proposed. Firstly, the normalized pressure model for the pipetting process was established with the kinematic model of the pipetting operation, and the pressure model is corrected by the experimental method. Through the pipetting process pressure and pressure of the first derivative of real-time monitoring, the use of segmentation of the double threshold method as pipetting fault evaluation criteria, and the pressure sensor data are processed by Kalman filtering, the accuracy of fault diagnosis is improved. When there is a fault, the pipette tip image is collected through the camera, extract the boundary of the liquid region by the background contrast method, and obtain the liquid volume in the tip according to the geometric characteristics of the pipette tip. The pipette deviation feedback to the automatic pipetting module and deviation correction is carried out. The titration test results show that the combination of the segmented pipetting kinematic model of the double threshold method of pressure monitoring, can effectively real-time judgment and classification of the pipette fault. The method of closed-loop adjustment of pipetting volume can effectively improve the accuracy and reliability of the pipetting system.

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Effects of Q-Matrix Design on Classification Accuracy in the Log-Linear Cognitive Diagnosis Model.

PubMed

Madison, Matthew J; Bradshaw, Laine P

2015-06-01

Diagnostic classification models are psychometric models that aim to classify examinees according to their mastery or non-mastery of specified latent characteristics. These models are well-suited for providing diagnostic feedback on educational assessments because of their practical efficiency and increased reliability when compared with other multidimensional measurement models. A priori specifications of which latent characteristics or attributes are measured by each item are a core element of the diagnostic assessment design. This item-attribute alignment, expressed in a Q-matrix, precedes and supports any inference resulting from the application of the diagnostic classification model. This study investigates the effects of Q-matrix design on classification accuracy for the log-linear cognitive diagnosis model. Results indicate that classification accuracy, reliability, and convergence rates improve when the Q-matrix contains isolated information from each measured attribute.

Information Filtering via Clustering Coefficients of User-Object Bipartite Networks

NASA Astrophysics Data System (ADS)

Guo, Qiang; Leng, Rui; Shi, Kerui; Liu, Jian-Guo

The clustering coefficient of user-object bipartite networks is presented to evaluate the overlap percentage of neighbors rating lists, which could be used to measure interest correlations among neighbor sets. The collaborative filtering (CF) information filtering algorithm evaluates a given user's interests in terms of his/her friends' opinions, which has become one of the most successful technologies for recommender systems. In this paper, different from the object clustering coefficient, users' clustering coefficients of user-object bipartite networks are introduced to improve the user similarity measurement. Numerical results for MovieLens and Netflix data sets show that users' clustering effects could enhance the algorithm performance. For MovieLens data set, the algorithmic accuracy, measured by the average ranking score, can be improved by 12.0% and the diversity could be improved by 18.2% and reach 0.649 when the recommendation list equals to 50. For Netflix data set, the accuracy could be improved by 14.5% at the optimal case and the popularity could be reduced by 13.4% comparing with the standard CF algorithm. Finally, we investigate the sparsity effect on the performance. This work indicates the user clustering coefficients is an effective factor to measure the user similarity, meanwhile statistical properties of user-object bipartite networks should be investigated to estimate users' tastes.

Long-term effects of user preference-oriented recommendation method on the evolution of online system

NASA Astrophysics Data System (ADS)

Shi, Xiaoyu; Shang, Ming-Sheng; Luo, Xin; Khushnood, Abbas; Li, Jian

2017-02-01

As the explosion growth of Internet economy, recommender system has become an important technology to solve the problem of information overload. However, recommenders are not one-size-fits-all, different recommenders have different virtues, making them be suitable for different users. In this paper, we propose a novel personalized recommender based on user preferences, which allows multiple recommenders to exist in E-commerce system simultaneously. We find that output of a recommender to each user is quite different when using different recommenders, the recommendation accuracy can be significantly improved if each user is assigned with his/her optimal personalized recommender. Furthermore, different from previous works focusing on short-term effects on recommender, we also evaluate the long-term effect of the proposed method by modeling the evolution of mutual feedback between user and online system. Finally, compared with single recommender running on the online system, the proposed method can improve the accuracy of recommendation significantly and get better trade-offs between short- and long-term performances of recommendation.

Reward Pays the Cost of Noise Reduction in Motor and Cognitive Control.

PubMed

Manohar, Sanjay G; Chong, Trevor T-J; Apps, Matthew A J; Batla, Amit; Stamelou, Maria; Jarman, Paul R; Bhatia, Kailash P; Husain, Masud

2015-06-29

Speed-accuracy trade-off is an intensively studied law governing almost all behavioral tasks across species. Here we show that motivation by reward breaks this law, by simultaneously invigorating movement and improving response precision. We devised a model to explain this paradoxical effect of reward by considering a new factor: the cost of control. Exerting control to improve response precision might itself come at a cost--a cost to attenuate a proportion of intrinsic neural noise. Applying a noise-reduction cost to optimal motor control predicted that reward can increase both velocity and accuracy. Similarly, application to decision-making predicted that reward reduces reaction times and errors in cognitive control. We used a novel saccadic distraction task to quantify the speed and accuracy of both movements and decisions under varying reward. Both faster speeds and smaller errors were observed with higher incentives, with the results best fitted by a model including a precision cost. Recent theories consider dopamine to be a key neuromodulator in mediating motivational effects of reward. We therefore examined how Parkinson's disease (PD), a condition associated with dopamine depletion, alters the effects of reward. Individuals with PD showed reduced reward sensitivity in their speed and accuracy, consistent in our model with higher noise-control costs. Including a cost of control over noise explains how reward may allow apparent performance limits to be surpassed. On this view, the pattern of reduced reward sensitivity in PD patients can specifically be accounted for by a higher cost for controlling noise. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

PPP Sliding Window Algorithm and Its Application in Deformation Monitoring.

PubMed

Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming

2016-05-31

Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts.

Re-examination of "release-from-PI" phenomena: recall accuracy does not recover after a semantic switch.

PubMed

Hubbard, Nicholas A; Weaver, Travis P; Turner, Monroe P; Rypma, Bart

2018-01-29

Recall accuracy decreases over successive memory trials using similar memoranda. This effect reflects proactive interference (PI) - the tendency for previously studied information to reduce recall of new information. However, recall improves if memoranda for a subsequent trial are semantically dissimilar from the previous trials. This improvement is thought to reflect a release from PI. We tested whether PI is reduced or released from the semantic category for which it had been induced by employing paradigms which featured inducement, semantic switch, and then return-to-original category epochs. Two experiments confirmed that PI was not released after various semantic switch trials (effects from d = -0.93 to -1.6). Combined analyses from both studies demonstrated that the number of intervening new category trials did not reduce or release PI. In fact, in all conditions recall accuracy decreased, demonstrating that PI is maintained and can increase after the new category trials. The release-from-PI account cannot accommodate these broader dynamics of PI. This account is also incongruent with evidence and theory from cognitive psychology, linguistics, and neuroscience. We propose a reintroduction-of-PI account which explains these broader PI dynamics and is consistent with the wider psychological and neurosciences.

[Study on physical deviation factors on laser induced breakdown spectroscopy measurement].

PubMed

Wan, Xiong; Wang, Peng; Wang, Qi; Zhang, Qing; Zhang, Zhi-Min; Zhang, Hua-Ming

2013-10-01

In order to eliminate the deviation between the measured LIBS spectral line and the standard LIBS spectral line, and improve the accuracy of elements measurement, a research of physical deviation factors in laser induced breakdown spectroscopy technology was proposed. Under the same experimental conditions, the relationship of ablated hole effect and spectral wavelength was tested, the Stark broadening data of Mg plasma laser induced breakdown spectroscopy with sampling time-delay from 1.00 to 3.00 micros was also studied, thus the physical deviation influences such as ablated hole effect and Stark broadening could be obtained while collecting the spectrum. The results and the method of the research and analysis can also be applied to other laser induced breakdown spectroscopy experiment system, which is of great significance to improve the accuracy of LIBS elements measuring and is also important to the research on the optimum sampling time-delay of LIBS.

Tomography for two-dimensional gas temperature distribution based on TDLAS

NASA Astrophysics Data System (ADS)

Luo, Can; Wang, Yunchu; Xing, Fei

2018-03-01

Based on tunable diode laser absorption spectroscopy (TDLAS), the tomography is used to reconstruct the combustion gas temperature distribution. The effects of number of rays, number of grids, and spacing of rays on the temperature reconstruction results for parallel ray are researched. The reconstruction quality is proportional to the ray number. The quality tends to be smoother when the ray number exceeds a certain value. The best quality is achieved when η is between 0.5 and 1. A virtual ray method combined with the reconstruction algorithms is tested. It is found that virtual ray method is effective to improve the accuracy of reconstruction results, compared with the original method. The linear interpolation method and cubic spline interpolation method, are used to improve the calculation accuracy of virtual ray absorption value. According to the calculation results, cubic spline interpolation is better. Moreover, the temperature distribution of a TBCC combustion chamber is used to validate those conclusions.

Analysis of spatial distribution of land cover maps accuracy

NASA Astrophysics Data System (ADS)

Khatami, R.; Mountrakis, G.; Stehman, S. V.

2017-12-01

Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain yielded similar AUC; iv) for the larger sample size (i.e., very dense spatial sample) and per-class predictions, the spatial domain yielded larger AUC; v) increasing the sample size improved accuracy predictions with a greater benefit accruing to the spatial domain; and vi) the function used for interpolation had the smallest effect on AUC.

Edge detection and localization with edge pattern analysis and inflection characterization

NASA Astrophysics Data System (ADS)

Jiang, Bo

2012-05-01

In general edges are considered to be abrupt changes or discontinuities in two dimensional image signal intensity distributions. The accuracy of front-end edge detection methods in image processing impacts the eventual success of higher level pattern analysis downstream. To generalize edge detectors designed from a simple ideal step function model to real distortions in natural images, research on one dimensional edge pattern analysis to improve the accuracy of edge detection and localization proposes an edge detection algorithm, which is composed by three basic edge patterns, such as ramp, impulse, and step. After mathematical analysis, general rules for edge representation based upon the classification of edge types into three categories-ramp, impulse, and step (RIS) are developed to reduce detection and localization errors, especially reducing "double edge" effect that is one important drawback to the derivative method. But, when applying one dimensional edge pattern in two dimensional image processing, a new issue is naturally raised that the edge detector should correct marking inflections or junctions of edges. Research on human visual perception of objects and information theory pointed out that a pattern lexicon of "inflection micro-patterns" has larger information than a straight line. Also, research on scene perception gave an idea that contours have larger information are more important factor to determine the success of scene categorization. Therefore, inflections or junctions are extremely useful features, whose accurate description and reconstruction are significant in solving correspondence problems in computer vision. Therefore, aside from adoption of edge pattern analysis, inflection or junction characterization is also utilized to extend traditional derivative edge detection algorithm. Experiments were conducted to test my propositions about edge detection and localization accuracy improvements. The results support the idea that these edge detection method improvements are effective in enhancing the accuracy of edge detection and localization.

Spectral-element Method for 3D Marine Controlled-source EM Modeling

NASA Astrophysics Data System (ADS)

Liu, L.; Yin, C.; Zhang, B., Sr.; Liu, Y.; Qiu, C.; Huang, X.; Zhu, J.

2017-12-01

As one of the predrill reservoir appraisal methods, marine controlled-source EM (MCSEM) has been widely used in mapping oil reservoirs to reduce risk of deep water exploration. With the technical development of MCSEM, the need for improved forward modeling tools has become evident. We introduce in this paper spectral element method (SEM) for 3D MCSEM modeling. It combines the flexibility of finite-element and high accuracy of spectral method. We use Galerkin weighted residual method to discretize the vector Helmholtz equation, where the curl-conforming Gauss-Lobatto-Chebyshev (GLC) polynomials are chosen as vector basis functions. As a kind of high-order complete orthogonal polynomials, the GLC have the characteristic of exponential convergence. This helps derive the matrix elements analytically and improves the modeling accuracy. Numerical 1D models using SEM with different orders show that SEM method delivers accurate results. With increasing SEM orders, the modeling accuracy improves largely. Further we compare our SEM with finite-difference (FD) method for a 3D reservoir model (Figure 1). The results show that SEM method is more effective than FD method. Only when the mesh is fine enough, can FD achieve the same accuracy of SEM. Therefore, to obtain the same precision, SEM greatly reduces the degrees of freedom and cost. Numerical experiments with different models (not shown here) demonstrate that SEM is an efficient and effective tool for MSCEM modeling that has significant advantages over traditional numerical methods.This research is supported by Key Program of National Natural Science Foundation of China (41530320), China Natural Science Foundation for Young Scientists (41404093), and Key National Research Project of China (2016YFC0303100, 2017YFC0601900).

Positional and Dimensional Accuracy Assessment of Drone Images Geo-referenced with Three Different GPSs

NASA Astrophysics Data System (ADS)

Cao, C.; Lee, X.; Xu, J.

2017-12-01

Unmanned Aerial Vehicles (UAVs) or drones have been widely used in environmental, ecological and engineering applications in recent years. These applications require assessment of positional and dimensional accuracy. In this study, positional accuracy refers to the accuracy of the latitudinal and longitudinal coordinates of locations on the mosaicked image in reference to the coordinates of the same locations measured by a Global Positioning System (GPS) in a ground survey, and dimensional accuracy refers to length and height of a ground target. Here, we investigate the effects of the number of Ground Control Points (GCPs) and the accuracy of the GPS used to measure the GCPs on positional and dimensional accuracy of a drone 3D model. Results show that using on-board GPS and a hand-held GPS produce a positional accuracy on the order of 2-9 meters. In comparison, using a differential GPS with high accuracy (30 cm) improves the positional accuracy of the drone model by about 40 %. Increasing the number of GCPs can compensate for the uncertainty brought by the GPS equipment with low accuracy. In terms of the dimensional accuracy of the drone model, even with the use of a low resolution GPS onboard the vehicle, the mean absolute errors are only 0.04 m for height and 0.10 m for length, which are well suited for some applications in precision agriculture and in land survey studies.

Reliability, Validity, and Classification Accuracy of the DSM-5 Diagnostic Criteria for Gambling Disorder and Comparison to DSM-IV.

PubMed

Stinchfield, Randy; McCready, John; Turner, Nigel E; Jimenez-Murcia, Susana; Petry, Nancy M; Grant, Jon; Welte, John; Chapman, Heather; Winters, Ken C

2016-09-01

The DSM-5 was published in 2013 and it included two substantive revisions for gambling disorder (GD). These changes are the reduction in the threshold from five to four criteria and elimination of the illegal activities criterion. The purpose of this study was to twofold. First, to assess the reliability, validity and classification accuracy of the DSM-5 diagnostic criteria for GD. Second, to compare the DSM-5-DSM-IV on reliability, validity, and classification accuracy, including an examination of the effect of the elimination of the illegal acts criterion on diagnostic accuracy. To compare DSM-5 and DSM-IV, eight datasets from three different countries (Canada, USA, and Spain; total N = 3247) were used. All datasets were based on similar research methods. Participants were recruited from outpatient gambling treatment services to represent the group with a GD and from the community to represent the group without a GD. All participants were administered a standardized measure of diagnostic criteria. The DSM-5 yielded satisfactory reliability, validity and classification accuracy. In comparing the DSM-5 to the DSM-IV, most comparisons of reliability, validity and classification accuracy showed more similarities than differences. There was evidence of modest improvements in classification accuracy for DSM-5 over DSM-IV, particularly in reduction of false negative errors. This reduction in false negative errors was largely a function of lowering the cut score from five to four and this revision is an improvement over DSM-IV. From a statistical standpoint, eliminating the illegal acts criterion did not make a significant impact on diagnostic accuracy. From a clinical standpoint, illegal acts can still be addressed in the context of the DSM-5 criterion of lying to others.

Real-time positioning in logging: Effects of forest stand characteristics, topography, and line-of-sight obstructions on GNSS-RF transponder accuracy and radio signal propagation.

PubMed

Zimbelman, Eloise G; Keefe, Robert F

2018-01-01

Real-time positioning on mobile devices using global navigation satellite system (GNSS) technology paired with radio frequency (RF) transmission (GNSS-RF) may help to improve safety on logging operations by increasing situational awareness. However, GNSS positional accuracy for ground workers in motion may be reduced by multipath error, satellite signal obstruction, or other factors. Radio propagation of GNSS locations may also be impacted due to line-of-sight (LOS) obstruction in remote, forested areas. The objective of this study was to characterize the effects of forest stand characteristics, topography, and other LOS obstructions on the GNSS accuracy and radio signal propagation quality of multiple Raveon Atlas PT GNSS-RF transponders functioning as a network in a range of forest conditions. Because most previous research with GNSS in forestry has focused on stationary units, we chose to analyze units in motion by evaluating the time-to-signal accuracy of geofence crossings in 21 randomly-selected stands on the University of Idaho Experimental Forest. Specifically, we studied the effects of forest stand characteristics, topography, and LOS obstructions on (1) the odds of missed GNSS-RF signals, (2) the root mean squared error (RMSE) of Atlas PTs, and (3) the time-to-signal accuracy of safety geofence crossings in forested environments. Mixed-effects models used to analyze the data showed that stand characteristics, topography, and obstructions in the LOS affected the odds of missed radio signals while stand variables alone affected RMSE. Both stand characteristics and topography affected the accuracy of geofence alerts.

Real-time positioning in logging: Effects of forest stand characteristics, topography, and line-of-sight obstructions on GNSS-RF transponder accuracy and radio signal propagation

PubMed Central

2018-01-01

Real-time positioning on mobile devices using global navigation satellite system (GNSS) technology paired with radio frequency (RF) transmission (GNSS-RF) may help to improve safety on logging operations by increasing situational awareness. However, GNSS positional accuracy for ground workers in motion may be reduced by multipath error, satellite signal obstruction, or other factors. Radio propagation of GNSS locations may also be impacted due to line-of-sight (LOS) obstruction in remote, forested areas. The objective of this study was to characterize the effects of forest stand characteristics, topography, and other LOS obstructions on the GNSS accuracy and radio signal propagation quality of multiple Raveon Atlas PT GNSS-RF transponders functioning as a network in a range of forest conditions. Because most previous research with GNSS in forestry has focused on stationary units, we chose to analyze units in motion by evaluating the time-to-signal accuracy of geofence crossings in 21 randomly-selected stands on the University of Idaho Experimental Forest. Specifically, we studied the effects of forest stand characteristics, topography, and LOS obstructions on (1) the odds of missed GNSS-RF signals, (2) the root mean squared error (RMSE) of Atlas PTs, and (3) the time-to-signal accuracy of safety geofence crossings in forested environments. Mixed-effects models used to analyze the data showed that stand characteristics, topography, and obstructions in the LOS affected the odds of missed radio signals while stand variables alone affected RMSE. Both stand characteristics and topography affected the accuracy of geofence alerts. PMID:29324794

Cadastral Database Positional Accuracy Improvement

NASA Astrophysics Data System (ADS)

Hashim, N. M.; Omar, A. H.; Ramli, S. N. M.; Omar, K. M.; Din, N.

2017-10-01

Positional Accuracy Improvement (PAI) is the refining process of the geometry feature in a geospatial dataset to improve its actual position. This actual position relates to the absolute position in specific coordinate system and the relation to the neighborhood features. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS), the PAI campaign is inevitable especially to the legacy cadastral database. Integration of legacy dataset and higher accuracy dataset like GNSS observation is a potential solution for improving the legacy dataset. However, by merely integrating both datasets will lead to a distortion of the relative geometry. The improved dataset should be further treated to minimize inherent errors and fitting to the new accurate dataset. The main focus of this study is to describe a method of angular based Least Square Adjustment (LSA) for PAI process of legacy dataset. The existing high accuracy dataset known as National Digital Cadastral Database (NDCDB) is then used as bench mark to validate the results. It was found that the propose technique is highly possible for positional accuracy improvement of legacy spatial datasets.

A Fast Robot Identification and Mapping Algorithm Based on Kinect Sensor.

PubMed

Zhang, Liang; Shen, Peiyi; Zhu, Guangming; Wei, Wei; Song, Houbing

2015-08-14

Internet of Things (IoT) is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB) method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN) k-Nearest Neighbor (KNN) algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC) estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP) is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS) algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University's datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy.

Broadband EIT borehole measurements with high phase accuracy using numerical corrections of electromagnetic coupling effects

NASA Astrophysics Data System (ADS)

Zhao, Y.; Zimmermann, E.; Huisman, J. A.; Treichel, A.; Wolters, B.; van Waasen, S.; Kemna, A.

2013-08-01

Electrical impedance tomography (EIT) is gaining importance in the field of geophysics and there is increasing interest for accurate borehole EIT measurements in a broad frequency range (mHz to kHz) in order to study subsurface properties. To characterize weakly polarizable soils and sediments with EIT, high phase accuracy is required. Typically, long electrode cables are used for borehole measurements. However, this may lead to undesired electromagnetic coupling effects associated with the inductive coupling between the double wire pairs for current injection and potential measurement and the capacitive coupling between the electrically conductive shield of the cable and the electrically conductive environment surrounding the electrode cables. Depending on the electrical properties of the subsurface and the measured transfer impedances, both coupling effects can cause large phase errors that have typically limited the frequency bandwidth of field EIT measurements to the mHz to Hz range. The aim of this paper is to develop numerical corrections for these phase errors. To this end, the inductive coupling effect was modeled using electronic circuit models, and the capacitive coupling effect was modeled by integrating discrete capacitances in the electrical forward model describing the EIT measurement process. The correction methods were successfully verified with measurements under controlled conditions in a water-filled rain barrel, where a high phase accuracy of 0.8 mrad in the frequency range up to 10 kHz was achieved. The corrections were also applied to field EIT measurements made using a 25 m long EIT borehole chain with eight electrodes and an electrode separation of 1 m. The results of a 1D inversion of these measurements showed that the correction methods increased the measurement accuracy considerably. It was concluded that the proposed correction methods enlarge the bandwidth of the field EIT measurement system, and that accurate EIT measurements can now be made in the mHz to kHz frequency range. This increased accuracy in the kHz range will allow a more accurate field characterization of the complex electrical conductivity of soils and sediments, which may lead to the improved estimation of saturated hydraulic conductivity from electrical properties. Although the correction methods have been developed for a custom-made EIT system, they also have potential to improve the phase accuracy of EIT measurements made with commercial systems relying on multicore cables.

Electronic discharge summary and prescription: improving communication between hospital and primary care.

PubMed

Murphy, S F; Lenihan, L; Orefuwa, F; Colohan, G; Hynes, I; Collins, C G

2017-05-01

The discharge letter is a key component of the communication pathway between the hospital and primary care. Accuracy and timeliness of delivery are crucial to ensure continuity of patient care. Electronic discharge summaries (EDS) and prescriptions have been shown to improve quality of discharge information for general practitioners (GPs). The aim of this study was to evaluate the effect of a new EDS on GP satisfaction levels and accuracy of discharge diagnosis. A GP survey was carried out whereby semi-structured interviews were conducted with 13 GPs from three primary care centres who receive a high volume of discharge letters from the hospital. A chart review was carried out on 90 charts to compare accuracy of ICD-10 coding of Non-Consultant Hospital Doctors (NCHDs) with that of trained Hopital In-Patient Enquiry (HIPE) coders. GP satisfaction levels were over 90 % with most aspects of the EDS, including amount of information (97 %), accuracy (95 %), GP information and follow-up (97 %) and medications (91 %). 70 % of GPs received the EDS within 2 weeks. ICD-10 coding of discharge diagnosis by NCHDs had an accuracy of 33 %, compared with 95.6 % when done by trained coders (p < 0.00001). The introduction of the EDS and prescription has led to improved quality of timeliness of communication with primary care. It has led to a very high satisfaction rating with GPs. ICD-10 coding was found to be grossly inaccurate when carried out by NCHDs and it is more appropriate for this task to be carried out by trained coders.

Improved technical success and radiation safety of adrenal vein sampling using rapid, semi-quantitative point-of-care cortisol measurement.

PubMed

Page, Michael M; Taranto, Mario; Ramsay, Duncan; van Schie, Greg; Glendenning, Paul; Gillett, Melissa J; Vasikaran, Samuel D

2018-01-01

Objective Primary aldosteronism is a curable cause of hypertension which can be treated surgically or medically depending on the findings of adrenal vein sampling studies. Adrenal vein sampling studies are technically demanding with a high failure rate in many centres. The use of intraprocedural cortisol measurement could improve the success rates of adrenal vein sampling but may be impracticable due to cost and effects on procedural duration. Design Retrospective review of the results of adrenal vein sampling procedures since commencement of point-of-care cortisol measurement using a novel single-use semi-quantitative measuring device for cortisol, the adrenal vein sampling Accuracy Kit. Success rate and complications of adrenal vein sampling procedures before and after use of the adrenal vein sampling Accuracy Kit. Routine use of the adrenal vein sampling Accuracy Kit device for intraprocedural measurement of cortisol commenced in 2016. Results Technical success rate of adrenal vein sampling increased from 63% of 99 procedures to 90% of 48 procedures ( P = 0.0007) after implementation of the adrenal vein sampling Accuracy Kit. Failure of right adrenal vein cannulation was the main reason for an unsuccessful study. Radiation dose decreased from 34.2 Gy.cm 2 (interquartile range, 15.8-85.9) to 15.7 Gy.cm 2 (6.9-47.3) ( P = 0.009). No complications were noted, and implementation costs were minimal. Conclusions Point-of-care cortisol measurement during adrenal vein sampling improved cannulation success rates and reduced radiation exposure. The use of the adrenal vein sampling Accuracy Kit is now standard practice at our centre.

Efficient use of unlabeled data for protein sequence classification: a comparative study

PubMed Central

Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

2009-01-01

Background Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags–the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Results Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. Conclusion The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably. PMID:19426450

On the Impact of Multi-GNSS Observations on Real-Time Precise Point Positioning Zenith Total Delay Estimates

NASA Astrophysics Data System (ADS)

Ding, Wenwu; Teferle, Norman; Kaźmierski, Kamil; Laurichesse, Denis; Yuan, Yunbin

2017-04-01

Observations from multiple Global Navigation Satellite System (GNSS) can improve the performance of real-time (RT) GNSS meteorology, in particular of the Zenith Total Delay (ZTD) estimates. RT ZTD estimates in combination with derived precipitable water vapour estimates can be used for weather now-casting and the tracking of severe weather events. While a number of published literature has already highlighted this positive development, in this study we describe an operational RT system for extracting ZTD using a modified version of the PPP-wizard (with PPP denoting Precise Point Positioning). Multi-GNSS, including GPS, GLONASS and Galileo, observation streams are processed using a RT PPP strategy based on RT satellite orbit and clock products from the Centre National d'Etudes Spatiales (CNES). A continuous experiment for 30 days was conducted, in which the RT observation streams of 20 globally distributed stations were processed. The initialization time and accuracy of the RT troposphere products using single and/or multi-system observations were evaluated. The effect of RT PPP ambiguity resolution was also evaluated. The results revealed that the RT troposphere products based on single system observations can fulfill the requirements of the meteorological application in now-casting systems. We noted that the GPS-only solution is better than the GLONASS-only solution in both initialization and accuracy. While the ZTD performance can be improved by applying RT PPP ambiguity resolution, the inclusion of observations from multiple GNSS has a more profound effect. Specifically, we saw that the ambiguity resolution is more effective in improving the accuracy, whereas the initialization process can be better accelerated by multi-GNSS observations. Combining all systems, RT troposphere products with an average accuracy of about 8 mm in ZTD were achieved after an initialization process of approximately 9 minutes, which supports the application of multi-GNSS observations and ambiguity resolution for RT meteorological applications.

Voxel-Wise Time-Series Analysis of Quantitative MRI in Relapsing-Remitting MS: Dynamic Imaging Metrics of Disease Activity Including Pre-Lesional Changes

DTIC Science & Technology

2015-12-01

other parameters match the previous simulation. A third simulation was performed to evaluate the effect of gradient and RF spoiling on the accuracy of...this increase also offers an opportunity to increase the length of the spoiler gradient and improve the accuracy of FA quanti - fication (27). To...Relaxation Pouria Mossahebi,1 Vasily L. Yarnykh,2 and Alexey Samsonov3* Purpose: Cross-relaxation imaging (CRI) is a family of quanti - tative

Frequency of Loaded Road March Training and Performance on a Loaded Road March

DTIC Science & Technology

1990-04-01

heart rate through the use of beta - blockers can substantially improve shooting accuracy (29, 44). Post road march decrements in the grenade throw may...the road march. An Increase in body tremors due to fatigue or an elevated post exercise heart rate may account for this. Whole body sway while aiming...a rifle is substantially increased even after a short period of exercise (39) and this may effect accuracy. Muscle tremors increase after brief or

Pricing and simulation for real estate index options: Radial basis point interpolation

NASA Astrophysics Data System (ADS)

Gong, Pu; Zou, Dong; Wang, Jiayue

2018-06-01

This study employs the meshfree radial basis point interpolation (RBPI) for pricing real estate derivatives contingent on real estate index. This method combines radial and polynomial basis functions, which can guarantee the interpolation scheme with Kronecker property and effectively improve accuracy. An exponential change of variables, a mesh refinement algorithm and the Richardson extrapolation are employed in this study to implement the RBPI. Numerical results are presented to examine the computational efficiency and accuracy of our method.

Improving photometric redshift estimation using GPZ: size information, post processing, and improved photometry

NASA Astrophysics Data System (ADS)

Gomes, Zahra; Jarvis, Matt J.; Almosallam, Ibrahim A.; Roberts, Stephen J.

2018-03-01

The next generation of large-scale imaging surveys (such as those conducted with the Large Synoptic Survey Telescope and Euclid) will require accurate photometric redshifts in order to optimally extract cosmological information. Gaussian Process for photometric redshift estimation (GPZ) is a promising new method that has been proven to provide efficient, accurate photometric redshift estimations with reliable variance predictions. In this paper, we investigate a number of methods for improving the photometric redshift estimations obtained using GPZ (but which are also applicable to others). We use spectroscopy from the Galaxy and Mass Assembly Data Release 2 with a limiting magnitude of r < 19.4 along with corresponding Sloan Digital Sky Survey visible (ugriz) photometry and the UKIRT Infrared Deep Sky Survey Large Area Survey near-IR (YJHK) photometry. We evaluate the effects of adding near-IR magnitudes and angular size as features for the training, validation, and testing of GPZ and find that these improve the accuracy of the results by ˜15-20 per cent. In addition, we explore a post-processing method of shifting the probability distributions of the estimated redshifts based on their Quantile-Quantile plots and find that it improves the bias by ˜40 per cent. Finally, we investigate the effects of using more precise photometry obtained from the Hyper Suprime-Cam Subaru Strategic Program Data Release 1 and find that it produces significant improvements in accuracy, similar to the effect of including additional features.

Concept Mapping Improves Metacomprehension Accuracy among 7th Graders

ERIC Educational Resources Information Center

Redford, Joshua S.; Thiede, Keith W.; Wiley, Jennifer; Griffin, Thomas D.

2012-01-01

Two experiments explored concept map construction as a useful intervention to improve metacomprehension accuracy among 7th grade students. In the first experiment, metacomprehension was marginally better for a concept mapping group than for a rereading group. In the second experiment, metacomprehension accuracy was significantly greater for a…

Improving the Accuracy of Software-Based Energy Analysis for Residential Buildings (Presentation)

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

Polly, B.

2011-09-01

This presentation describes the basic components of software-based energy analysis for residential buildings, explores the concepts of 'error' and 'accuracy' when analysis predictions are compared to measured data, and explains how NREL is working to continuously improve the accuracy of energy analysis methods.

Scientific analysis of satellite ranging data

NASA Technical Reports Server (NTRS)

Smith, David E.

1994-01-01

A network of satellite laser ranging (SLR) tracking systems with continuously improving accuracies is challenging the modelling capabilities of analysts worldwide. Various data analysis techniques have yielded many advances in the development of orbit, instrument and Earth models. The direct measurement of the distance to the satellite provided by the laser ranges has given us a simple metric which links the results obtained by diverse approaches. Different groups have used SLR data, often in combination with observations from other space geodetic techniques, to improve models of the static geopotential, the solid Earth, ocean tides, and atmospheric drag models for low Earth satellites. Radiation pressure models and other non-conservative forces for satellite orbits above the atmosphere have been developed to exploit the full accuracy of the latest SLR instruments. SLR is the baseline tracking system for the altimeter missions TOPEX/Poseidon, and ERS-1 and will play an important role in providing the reference frame for locating the geocentric position of the ocean surface, in providing an unchanging range standard for altimeter calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. However, even with the many improvements in the models used to support the orbital analysis of laser observations, there remain systematic effects which limit the full exploitation of SLR accuracy today.

Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins

PubMed Central

Yang, Jing; He, Bao-Ji; Jang, Richard; Zhang, Yang; Shen, Hong-Bin

2015-01-01

Abstract Motivation: Cysteine-rich proteins cover many important families in nature but there are currently no methods specifically designed for modeling the structure of these proteins. The accuracy of disulfide connectivity pattern prediction, particularly for the proteins of higher-order connections, e.g. >3 bonds, is too low to effectively assist structure assembly simulations. Results: We propose a new hierarchical order reduction protocol called Cyscon for disulfide-bonding prediction. The most confident disulfide bonds are first identified and bonding prediction is then focused on the remaining cysteine residues based on SVR training. Compared with purely machine learning-based approaches, Cyscon improved the average accuracy of connectivity pattern prediction by 21.9%. For proteins with more than 5 disulfide bonds, Cyscon improved the accuracy by 585% on the benchmark set of PDBCYS. When applied to 158 non-redundant cysteine-rich proteins, Cyscon predictions helped increase (or decrease) the TM-score (or RMSD) of the ab initio QUARK modeling by 12.1% (or 14.4%). This result demonstrates a new avenue to improve the ab initio structure modeling for cysteine-rich proteins. Availability and implementation: http://www.csbio.sjtu.edu.cn/bioinf/Cyscon/ Contact: zhng@umich.edu or hbshen@sjtu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26254435

Note: An improved calibration system with phase correction for electronic transformers with digital output.

PubMed

Cheng, Han-miao; Li, Hong-bin

2015-08-01

The existing electronic transformer calibration systems employing data acquisition cards cannot satisfy some practical applications, because the calibration systems have phase measurement errors when they work in the mode of receiving external synchronization signals. This paper proposes an improved calibration system scheme with phase correction to improve the phase measurement accuracy. We employ NI PCI-4474 to design a calibration system, and the system has the potential to receive external synchronization signals and reach extremely high accuracy classes. Accuracy verification has been carried out in the China Electric Power Research Institute, and results demonstrate that the system surpasses the accuracy class 0.05. Furthermore, this system has been used to test the harmonics measurement accuracy of all-fiber optical current transformers. In the same process, we have used an existing calibration system, and a comparison of the test results is presented. The system after improvement is suitable for the intended applications.

Techniques for improving the accuracy of cyrogenic temperature measurement in ground test programs

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Fabik, Richard H.

1993-01-01

The performance of a sensor is often evaluated by determining to what degree of accuracy a measurement can be made using this sensor. The absolute accuracy of a sensor is an important parameter considered when choosing the type of sensor to use in research experiments. Tests were performed to improve the accuracy of cryogenic temperature measurements by calibration of the temperature sensors when installed in their experimental operating environment. The calibration information was then used to correct for temperature sensor measurement errors by adjusting the data acquisition system software. This paper describes a method to improve the accuracy of cryogenic temperature measurements using corrections in the data acquisition system software such that the uncertainty of an individual temperature sensor is improved from plus or minus 0.90 deg R to plus or minus 0.20 deg R over a specified range.

Humans Optimize Decision-Making by Delaying Decision Onset

PubMed Central

Teichert, Tobias; Ferrera, Vincent P.; Grinband, Jack

2014-01-01

Why do humans make errors on seemingly trivial perceptual decisions? It has been shown that such errors occur in part because the decision process (evidence accumulation) is initiated before selective attention has isolated the relevant sensory information from salient distractors. Nevertheless, it is typically assumed that subjects increase accuracy by prolonging the decision process rather than delaying decision onset. To date it has not been tested whether humans can strategically delay decision onset to increase response accuracy. To address this question we measured the time course of selective attention in a motion interference task using a novel variant of the response signal paradigm. Based on these measurements we estimated time-dependent drift rate and showed that subjects should in principle be able trade speed for accuracy very effectively by delaying decision onset. Using the time-dependent estimate of drift rate we show that subjects indeed delay decision onset in addition to raising response threshold when asked to stress accuracy over speed in a free reaction version of the same motion-interference task. These findings show that decision onset is a critical aspect of the decision process that can be adjusted to effectively improve decision accuracy. PMID:24599295

Improving the accuracy of camber predictions for precast pretensioned concrete beams : [tech transfer summary].

DOT National Transportation Integrated Search

2015-07-01

Implementing the recommendations of this study is expected to significantly : improve the accuracy of camber measurements and predictions and to : ultimately help reduce construction delays, improve bridge serviceability, : and decrease costs.

Effect of citizen engagement levels in flood forecasting by assimilating crowdsourced observations in hydrological models

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Cortes Arevalo, Juliette; Alfonso, Leonardo; Wehn, Uta; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri

2017-04-01

In the past years, a number of methods have been proposed to reduce uncertainty in flood prediction by means of model updating techniques. Traditional physical observations are usually integrated into hydrological and hydraulic models to improve model performances and consequent flood predictions. Nowadays, low-cost sensors can be used for crowdsourced observations. Different type of social sensors can measure, in a more distributed way, physical variables such as precipitation and water level. However, these crowdsourced observations are not integrated into a real-time fashion into water-system models due to their varying accuracy and random spatial-temporal coverage. We assess the effect in model performance due to the assimilation of crowdsourced observations of water level. Our method consists in (1) implementing a Kalman filter into a cascade of hydrological and hydraulic models. (2) defining observation errors depending on the type of sensor either physical or social. Randomly distributed errors are based on accuracy ranges that slightly improve according to the citizens' expertise level. (3) Using a simplified social model to realistically represent citizen engagement levels based on population density and citizens' motivation scenarios. To test our method, we synthetically derive crowdsourced observations for different citizen engagement levels from a distributed network of physical and social sensors. The observations are assimilated during a particular flood event occurred in the Bacchiglione catchment, Italy. The results of this study demonstrate that sharing crowdsourced water level observations (often motivated by a feeling of belonging to a community of friends) can help in improving flood prediction. On the other hand, a growing participation of individual citizens or weather enthusiasts sharing hydrological observations in cities can help to improve model performance. This study is a first step to assess the effects of crowdsourced observations in flood model predictions. Effective communication and feedback about the quality of observations from water authorities to engaged citizens are further required to minimize their intrinsic low-variable accuracy.

Impact of Scribes on Physician Satisfaction, Patient Satisfaction, and Charting Efficiency: A Randomized Controlled Trial

PubMed Central

Gidwani, Risha; Nguyen, Cathina; Kofoed, Alexis; Carragee, Catherine; Rydel, Tracy; Nelligan, Ian; Sattler, Amelia; Mahoney, Megan; Lin, Steven

2017-01-01

PURPOSE Scribes are increasingly being used in clinical practice despite a lack of high-quality evidence regarding their effects. Our objective was to evaluate the effect of medical scribes on physician satisfaction, patient satisfaction, and charting efficiency. METHODS We conducted a randomized controlled trial in which physicians in an academic family medicine clinic were randomized to 1 week with a scribe then 1 week without a scribe for the course of 1 year. Scribes drafted all relevant documentation, which was reviewed by the physician before attestation and signing. In encounters without a scribe, the physician performed all charting duties. Our outcomes were physician satisfaction, measured by a 5-item instrument that included physicians’ perceptions of chart quality and chart accuracy; patient satisfaction, measured by a 6-item instrument; and charting efficiency, measured by time to chart close. RESULTS Scribes improved all aspects of physician satisfaction, including overall satisfaction with clinic (OR = 10.75), having enough face time with patients (OR = 3.71), time spent charting (OR = 86.09), chart quality (OR = 7.25), and chart accuracy (OR = 4.61) (all P values <.001). Scribes had no effect on patient satisfaction. Scribes increased the proportion of charts that were closed within 48 hours (OR =1.18, P =.028). CONCLUSIONS To our knowledge, we have conducted the first randomized controlled trial of scribes. We found that scribes produced significant improvements in overall physician satisfaction, satisfaction with chart quality and accuracy, and charting efficiency without detracting from patient satisfaction. Scribes appear to be a promising strategy to improve health care efficiency and reduce physician burnout. PMID:28893812

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological review of health technology assessments.

PubMed

Shinkins, Bethany; Yang, Yaling; Abel, Lucy; Fanshawe, Thomas R

2017-04-14

Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests.

An Investigation of Working Memory Effects on Oral Grammatical Accuracy and Fluency in Producing Questions in English

ERIC Educational Resources Information Center

Wright, Clare

2013-01-01

This article addresses the question of how far working memory may affect second language (L2) learners' improvement in spoken language during a period of immersion. Research is presented testing the hypothesis that individual differences in working memory (WM) capacity are associated with individual variation in improvements in oral production of…

An Evaluation of the Conservative Dual-Criterion Method for Teaching University Students to Visually Inspect AB-Design Graphs

ERIC Educational Resources Information Center

Stewart, Kelise K.; Carr, James E.; Brandt, Charles W.; McHenry, Meade M.

2007-01-01

The present study evaluated the effects of both a traditional lecture and the conservative dual-criterion (CDC) judgment aid on the ability of 6 university students to visually inspect AB-design line graphs. The traditional lecture reliably failed to improve visual inspection accuracy, whereas the CDC method substantially improved the performance…

Image enhancement and advanced information extraction techniques for ERTS-1 data

NASA Technical Reports Server (NTRS)

Malila, W. A. (Principal Investigator); Nalepka, R. F.; Sarno, J. E.

1975-01-01

The author has identified the following significant results. It was demonstrated and concluded that: (1) the atmosphere has significant effects on ERTS MSS data which can seriously degrade recognition performance; (2) the application of selected signature extension techniques serve to reduce the deleterious effects of both the atmosphere and changing ground conditions on recognition performance; and (3) a proportion estimation algorithm for overcoming problems in acreage estimation accuracy resulting from the coarse spatial resolution of the ERTS MSS, was able to significantly improve acreage estimation accuracy over that achievable by conventional techniques, especially for high contrast targets such as lakes and ponds.

Vital sign sensing method based on EMD in terahertz band

NASA Astrophysics Data System (ADS)

Xu, Zhengwu; Liu, Tong

2014-12-01

Non-contact respiration and heartbeat rates detection could be applied to find survivors trapped in the disaster or the remote monitoring of the respiration and heartbeat of a patient. This study presents an improved algorithm that extracts the respiration and heartbeat rates of humans by utilizing the terahertz radar, which further lessens the effects of noise, suppresses the cross-term, and enhances the detection accuracy. A human target echo model for the terahertz radar is first presented. Combining the over-sampling method, low-pass filter, and Empirical Mode Decomposition improves the signal-to-noise ratio. The smoothed pseudo Wigner-Ville distribution time-frequency technique and the centroid of the spectrogram are used to estimate the instantaneous velocity of the target's cardiopulmonary motion. The down-sampling method is adopted to prevent serious distortion. Finally, a second time-frequency analysis is applied to the centroid curve to extract the respiration and heartbeat rates of the individual. Simulation results show that compared with the previously presented vital sign sensing method, the improved algorithm enhances the signal-to-noise ratio to 1 dB with a detection accuracy of 80%. The improved algorithm is an effective approach for the detection of respiration and heartbeat signal in a complicated environment.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to that of the complex model including epistatic effects. Conclusions This simulation study showed that the fBayesB approach is convenient for genetic value prediction. Jointly estimating additive and non-additive effects (especially dominance) has reasonable impact on the accuracy of prediction and the proportion of genetic variation assigned to the additive genetic source. PMID:21867519

Effects of a Training Package to Improve the Accuracy of Descriptive Analysis Data Recording

ERIC Educational Resources Information Center

Mayer, Kimberly L.; DiGennaro Reed, Florence D.

2013-01-01

Functional behavior assessment is an important precursor to developing interventions to address a problem behavior. Descriptive analysis, a type of functional behavior assessment, is effective in informing intervention design only if the gathered data accurately capture relevant events and behaviors. We investigated a training procedure to improve…

The Effectiveness of the "Golfer's Groove" in Improving Golfers' Scores

ERIC Educational Resources Information Center

Yost, Michael; And Others

1976-01-01

Use of the "golfer's groove," a device for controlling the angle and plane of a practicing golfer's swing, significantly influences the accuracy with which male and female college students can be taught to drive golfballs. (MB)

Vibration modes interference in the MEMS resonant pressure sensor

NASA Astrophysics Data System (ADS)

Zhang, Fangfang; Li, Anlin; Bu, Zhenxiang; Wang, Lingyun; Sun, Daoheng; Du, Xiaohui; Gu, Dandan

2017-11-01

A new type of coupled balanced-mass double-ended tuning fork resonator (CBDETF) pressure sensor is fabricated and tested. However, the low accuracy of the CBDETF pressure sensor is not satisfied to us. Based on systematic analysis and tests, the coupling effect between the operational mode and interference mode is considered to be the main cause for the sensor in accuracy. To solve this problem, the stiffness of the serpentine beams is increased to pull up the resonant frequency of the interfering mode and make it separate far from the operational mode. Finally, the accuracy of the CBDETF pressure sensor is improved from + /-0.5% to less than + /-0.03% of the Full Scale (F.S.).

Pseudorange Measurement Method Based on AIS Signals.

PubMed

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-05-22

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system.

Pseudorange Measurement Method Based on AIS Signals

PubMed Central

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-01-01

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system. PMID:28531153

Reputation-Based Secure Sensor Localization in Wireless Sensor Networks

PubMed Central

He, Jingsha; Xu, Jing; Zhu, Xingye; Zhang, Yuqiang; Zhang, Ting; Fu, Wanqing

2014-01-01

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments. PMID:24982940

A calibration procedure for load cells to improve accuracy of mini-lysimeters in monitoring evapotranspiration

NASA Astrophysics Data System (ADS)

Misra, R. K.; Padhi, J.; Payero, J. O.

2011-08-01

SummaryWe used twelve load cells (20 kg capacity) in a mini-lysimeter system to measure evapotranspiration simultaneously from twelve plants growing in separate pots in a glasshouse. A data logger combined with a multiplexer was used to connect all load cells with the full-bridge excitation mode to acquire load-cell signal. Each load cell was calibrated using fixed load within the range of 0-0.8 times the full load capacity of load cells. Performance of all load cells was assessed on the basis of signal settling time, excitation compensation, hysteresis and temperature. Final calibration of load cells included statistical consideration of these effects to allow prediction of lysimeter weights and evapotranspiration over short-time intervals for improved accuracy and sustained performance. Analysis of the costs for the mini-lysimeter system indicates that evapotranspiration can be measured economically at a reasonable accuracy and sufficient resolution with robust method of load-cell calibration.

Investigating Atmospheric Rivers using GPS TPW during CalWater 2015

NASA Astrophysics Data System (ADS)

Almanza, V.; Foster, J. H.; Businger, S.

2015-12-01

Ship-based Global Positioning System (GPS) receivers have been successful in obtaining millimeter accuracy total precipitable water (TPW). We apply this technique with a field experiment using a GPS meteorology system installed on board the R/V Ronald Brown during the CalWater 2015 project. The goal of CalWater is to monitor atmospheric river (AR) events over the Eastern Pacific Ocean and improve forecasting of the extreme precipitation events they can produce. During the 30-day cruise, TPW derived from radiosonde balloons released from the Ron Brown are used to verify the accuracy of shipboard GPS TPW. The results suggest that ship-based GPS TPW offers a cost-effective approach for acquiring accurate real-time meteorological observations of TPW in AR's over remote oceans, as well as near the coastlines where satellites algorithms have limited accuracy. The results have implications for augmenting operational observing networks to improve weather prediction and nowcasting of ARs, thereby supporting hazard response and mitigation efforts associated with coastal flooding events.

Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.

PubMed

Lee, Jack; Zee, Benny Chung Ying; Li, Qing

2013-01-01

Diabetic retinopathy is a major cause of blindness. Proliferative diabetic retinopathy is a result of severe vascular complication and is visible as neovascularization of the retina. Automatic detection of such new vessels would be useful for the severity grading of diabetic retinopathy, and it is an important part of screening process to identify those who may require immediate treatment for their diabetic retinopathy. We proposed a novel new vessels detection method including statistical texture analysis (STA), high order spectrum analysis (HOS), fractal analysis (FA), and most importantly we have shown that by incorporating their associated interactions the accuracy of new vessels detection can be greatly improved. To assess its performance, the sensitivity, specificity and accuracy (AUC) are obtained. They are 96.3%, 99.1% and 98.5% (99.3%), respectively. It is found that the proposed method can improve the accuracy of new vessels detection significantly over previous methods. The algorithm can be automated and is valuable to detect relatively severe cases of diabetic retinopathy among diabetes patients.

Mining HIV protease cleavage data using genetic programming with a sum-product function.

PubMed

Yang, Zheng Rong; Dalby, Andrew R; Qiu, Jing

2004-12-12

In order to design effective HIV inhibitors, studying and understanding the mechanism of HIV protease cleavage specification is critical. Various methods have been developed to explore the specificity of HIV protease cleavage activity. However, success in both extracting discriminant rules and maintaining high prediction accuracy is still challenging. The earlier study had employed genetic programming with a min-max scoring function to extract discriminant rules with success. However, the decision will finally be degenerated to one residue making further improvement of the prediction accuracy difficult. The challenge of revising the min-max scoring function so as to improve the prediction accuracy motivated this study. This paper has designed a new scoring function called a sum-product function for extracting HIV protease cleavage discriminant rules using genetic programming methods. The experiments show that the new scoring function is superior to the min-max scoring function. The software package can be obtained by request to Dr Zheng Rong Yang.

The effects of 6-week training programs on throwing accuracy, proprioception, and core endurance in baseball.

PubMed

Lust, Kathleen R; Sandrey, Michelle A; Bulger, Sean M; Wilder, Nathan

2009-08-01

With a limited number of outcomes-based studies, only recommendations for strength-training and rehabilitation programs can be made. To determine the extent to which throwing accuracy, core stability, and proprioception improved after completion of a 6-week training program that included open kinetic chain (OKC), closed kinetic chain (CKC), and/or core-stability exercises. A 2 x 3 factorial design. Division III college. 19 healthy baseball athletes with a control group of 15. Two 6-week programs including OKC, CKC, and core-stabilization exercises that were progressed each week. Functional throwing-performance index, closed kinetic chain upper extremity stability test, back-extensor test, 45 degrees abdominal-fatigue test, and right- and left-side bridging test. There was no significant difference between groups. An increase was evident in all pretest-to-posttest results, with improvement ranging from 1.36% to 140%. Both of the 6-week training programs could be used to increase throwing accuracy, core stability, and proprioception in baseball.

Evaluation of spatial filtering on the accuracy of wheat area estimate

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Delima, A. M.

1982-01-01

A 3 x 3 pixel spatial filter for postclassification was used for wheat classification to evaluate the effects of this procedure on the accuracy of area estimation using LANDSAT digital data obtained from a single pass. Quantitative analyses were carried out in five test sites (approx 40 sq km each) and t tests showed that filtering with threshold values significantly decreased errors of commission and omission. In area estimation filtering improved the overestimate of 4.5% to 2.7% and the root-mean-square error decreased from 126.18 ha to 107.02 ha. Extrapolating the same procedure of automatic classification using spatial filtering for postclassification to the whole study area, the accuracy in area estimate was improved from the overestimate of 10.9% to 9.7%. It is concluded that when single pass LANDSAT data is used for crop identification and area estimation the postclassification procedure using a spatial filter provides a more accurate area estimate by reducing classification errors.

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach

PubMed Central

Tan, Robin; Perkowski, Marek

2017-01-01

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems. PMID:28230745

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach.

PubMed

Tan, Robin; Perkowski, Marek

2017-02-20

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems.

Improved motor sequence retention by motionless listening.

PubMed

Lahav, Amir; Katz, Tal; Chess, Roxanne; Saltzman, Elliot

2013-05-01

This study examined the effect of listening to a newly learned musical piece on subsequent motor retention of the piece. Thirty-six non-musicians were trained to play an unfamiliar melody on a piano keyboard. Next, they were randomly assigned to participate in three follow-up listening sessions over 1 week. Subjects who, during their listening sessions, listened to the same initial piece showed significant improvements in motor memory and retention of the piece despite the absence of physical practice. These improvements included increased pitch accuracy, time accuracy, and dynamic intensity of key pressing. Similar improvements, though to a lesser degree, were observed in subjects who, during their listening sessions, were distracted by another task. Control subjects, who after learning the piece had listened to nonmusical sounds, showed impaired motoric retention of the piece at 1 week from the initial acquisition day. These results imply that motor sequences can be established in motor memory without direct access to motor-related information. In addition, the study revealed that the listening-induced improvements did not generalize to the learning of a new musical piece composed of the same notes as the initial piece learned, limiting the effects to musical motor sequences that are already part of the individual's motor repertoire.

Infrared Imagery of Shuttle (IRIS). Task 2, summary report

NASA Technical Reports Server (NTRS)

Chocol, C. J.

1978-01-01

End-to-end tests of a 16 element indium antimonide sensor array and 10 channels of associated electronic signal processing were completed. Quantitative data were gathered on system responsivity, frequency response, noise, stray capacitance effects, and sensor paralleling. These tests verify that the temperature accuracies, predicted in the Task 1 study, can be obtained with a very carefully designed electro-optical flight system. Pre-flight and inflight calibration of a high quality are mandatory to obtain these accuracies. Also, optical crosstalk in the array-dewar assembly must be carefully eliminated by its design. Tests of the scaled up tracking system reticle also demonstrate that the predicted tracking system accuracies can be met in the flight system. In addition, improvements in the reticle pattern and electronics are possible, which will reduce the complexity of the flight system and increase tracking accuracy.

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

Shi, Xin, E-mail: xinshih86029@gmail.com; Zhao, Xiangmo, E-mail: xinshih86029@gmail.com; Hui, Fei, E-mail: xinshih86029@gmail.com

Clock synchronization in wireless sensor networks (WSNs) has been studied extensively in recent years and many protocols are put forward based on the point of statistical signal processing, which is an effective way to optimize accuracy. However, the accuracy derived from the statistical data can be improved mainly by sufficient packets exchange, which will consume the limited power resources greatly. In this paper, a reliable clock estimation using linear weighted fusion based on pairwise broadcast synchronization is proposed to optimize sync accuracy without expending additional sync packets. As a contribution, a linear weighted fusion scheme for multiple clock deviations ismore » constructed with the collaborative sensing of clock timestamp. And the fusion weight is defined by the covariance of sync errors for different clock deviations. Extensive simulation results show that the proposed approach can achieve better performance in terms of sync overhead and sync accuracy.« less

Description of Panel Method Code ANTARES

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert; George, Mike (Technical Monitor)

2000-01-01

Panel method code ANTARES was developed to compute wall interference corrections in a rectangular wind tunnel. The code uses point doublets to represent blockage effects and line doublets to represent lifting effects of a wind tunnel model. Subsonic compressibility effects are modeled by applying the Prandtl-Glauert transformation. The closed wall, open jet, or perforated wall boundary condition may be assigned to a wall panel centroid. The tunnel walls can be represented by using up to 8000 panels. The accuracy of panel method code ANTARES was successfully investigated by comparing solutions for the closed wall and open jet boundary condition with corresponding Method of Images solutions. Fourier transform solutions of a two-dimensional wind tunnel flow field were used to check the application of the perforated wall boundary condition. Studies showed that the accuracy of panel method code ANTARES can be improved by increasing the total number of wall panels in the circumferential direction. It was also shown that the accuracy decreases with increasing free-stream Mach number of the wind tunnel flow field.

Effect Coding as a Mechanism for Improving the Accuracy of Measuring Students Who Self-Identify with More than One Race

ERIC Educational Resources Information Center

Mayhew, Matthew J.; Simonoff, Jeffrey S.

2015-01-01

The purpose of this paper is to describe effect coding as an alternative quantitative practice for analyzing and interpreting categorical, multi-raced independent variables in higher education research. Not only may effect coding enable researchers to get closer to respondents' original intentions, it allows for more accurate analyses of all race…

Eye movement training is most effective when it involves a task-relevant sensorimotor decision.

PubMed

Fooken, Jolande; Lalonde, Kathryn M; Mann, Gurkiran K; Spering, Miriam

2018-04-01

Eye and hand movements are closely linked when performing everyday actions. We conducted a perceptual-motor training study to investigate mutually beneficial effects of eye and hand movements, asking whether training in one modality benefits performance in the other. Observers had to predict the future trajectory of a briefly presented moving object, and intercept it at its assumed location as accurately as possible with their finger. Eye and hand movements were recorded simultaneously. Different training protocols either included eye movements or a combination of eye and hand movements with or without external performance feedback. Eye movement training did not transfer across modalities: Irrespective of feedback, finger interception accuracy and precision improved after training that involved the hand, but not after isolated eye movement training. Conversely, eye movements benefited from hand movement training or when external performance feedback was given, thus improving only when an active interceptive task component was involved. These findings indicate only limited transfer across modalities. However, they reveal the importance of creating a training task with an active sensorimotor decision to improve the accuracy and precision of eye and hand movements.

Information filtering via weighted heat conduction algorithm

NASA Astrophysics Data System (ADS)

Liu, Jian-Guo; Guo, Qiang; Zhang, Yi-Cheng

2011-06-01

In this paper, by taking into account effects of the user and object correlations on a heat conduction (HC) algorithm, a weighted heat conduction (WHC) algorithm is presented. We argue that the edge weight of the user-object bipartite network should be embedded into the HC algorithm to measure the object similarity. The numerical results indicate that both the accuracy and diversity could be improved greatly compared with the standard HC algorithm and the optimal values reached simultaneously. On the Movielens and Netflix datasets, the algorithmic accuracy, measured by the average ranking score, can be improved by 39.7% and 56.1% in the optimal case, respectively, and the diversity could reach 0.9587 and 0.9317 when the recommendation list equals to 5. Further statistical analysis indicates that, in the optimal case, the distributions of the edge weight are changed to the Poisson form, which may be the reason why HC algorithm performance could be improved. This work highlights the effect of edge weight on a personalized recommendation study, which maybe an important factor affecting personalized recommendation performance.

A new generation of effective core potentials for correlated calculations

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

Bennett, Michael Chandler; Melton, Cody A.; Annaberdiyev, Abdulgani

Here, we outline ideas on desired properties for a new generation of effective core potentials (ECPs) that will allow valence-only calculations to reach the full potential offered by recent advances in many-body wave function methods. The key improvements include consistent use of correlated methods throughout ECP constructions and improved transferability as required for an accurate description of molecular systems over a range of geometries. The guiding principle is the isospectrality of all-electron and ECP Hamiltonians for a subset of valence states. We illustrate these concepts on a few first- and second-row atoms (B, C, N, O, S), and we obtainmore » higher accuracy in transferability than previous constructions while using semi-local ECPs with a small number of parameters. In addition, the constructed ECPs enable many-body calculations of valence properties with higher (or same) accuracy than their all-electron counterparts with uncorrelated cores. This implies that the ECPs include also some of the impacts of core-core and core-valence correlations on valence properties. The results open further prospects for ECP improvements and refinements.« less

A new generation of effective core potentials for correlated calculations

DOE PAGES

Bennett, Michael Chandler; Melton, Cody A.; Annaberdiyev, Abdulgani; ...

2017-12-12

Here, we outline ideas on desired properties for a new generation of effective core potentials (ECPs) that will allow valence-only calculations to reach the full potential offered by recent advances in many-body wave function methods. The key improvements include consistent use of correlated methods throughout ECP constructions and improved transferability as required for an accurate description of molecular systems over a range of geometries. The guiding principle is the isospectrality of all-electron and ECP Hamiltonians for a subset of valence states. We illustrate these concepts on a few first- and second-row atoms (B, C, N, O, S), and we obtainmore » higher accuracy in transferability than previous constructions while using semi-local ECPs with a small number of parameters. In addition, the constructed ECPs enable many-body calculations of valence properties with higher (or same) accuracy than their all-electron counterparts with uncorrelated cores. This implies that the ECPs include also some of the impacts of core-core and core-valence correlations on valence properties. The results open further prospects for ECP improvements and refinements.« less

A new fault diagnosis algorithm for AUV cooperative localization system

NASA Astrophysics Data System (ADS)

Shi, Hongyang; Miao, Zhiyong; Zhang, Yi

2017-10-01

Multiple AUVs cooperative localization as a new kind of underwater positioning technology, not only can improve the positioning accuracy, but also has many advantages the single AUV does not have. It is necessary to detect and isolate the fault to increase the reliability and availability of the AUVs cooperative localization system. In this paper, the Extended Multiple Model Adaptive Cubature Kalmam Filter (EMMACKF) method is presented to detect the fault. The sensor failures are simulated based on the off-line experimental data. Experimental results have shown that the faulty apparatus can be diagnosed effectively using the proposed method. Compared with Multiple Model Adaptive Extended Kalman Filter and Multi-Model Adaptive Unscented Kalman Filter, both accuracy and timelines have been improved to some extent.

Design and Hardware Implementation of a New Chaotic Secure Communication Technique

PubMed Central

Xiong, Li; Lu, Yan-Jun; Zhang, Yong-Fang; Zhang, Xin-Guo; Gupta, Parag

2016-01-01

In this paper, a scheme for chaotic modulation secure communication is proposed based on chaotic synchronization of an improved Lorenz system. For the first time, the intensity limit and stability of the transmitted signal, the characteristics of broadband and the requirements for accuracy of electronic components are presented by Multisim simulation. In addition, some improvements are made on the measurement method and the proposed experimental circuit in order to facilitate the experiments of chaotic synchronization, chaotic non-synchronization, experiment without signal and experiment with signal. To illustrate the effectiveness of the proposed scheme, some numerical simulations are presented. Then, the proposed chaotic secure communication circuit is implemented through analog electronic circuit, which is characterized by its high accuracy and good robustness. PMID:27548385

An improved graph cut segmentation method for cervical lymph nodes on sonograms and its relationship with node's shape assessment.

PubMed

Zhang, Junhua; Wang, Yuanyuan; Shi, Xinling

2009-12-01

A modified graph cut was proposed under the elliptical shape constraint to segment cervical lymph nodes on sonograms, and its effect on the measurement of short axis to long axis ratio (S/L) was investigated by using the relative ultimate measurement accuracy (RUMA). Under the same user inputs, the proposed algorithm successfully segmented all 60 sonograms tested, while the traditional graph cut failed. The mean RUMA resulted from the developed method was comparable to that resulted from the manual segmentation. Results indicated that utilizing the elliptical shape prior could appreciably improve the graph cut for nodes segmentation, and the proposed method satisfied the accuracy requirement of S/L measurement.

Design and Hardware Implementation of a New Chaotic Secure Communication Technique.

PubMed

Xiong, Li; Lu, Yan-Jun; Zhang, Yong-Fang; Zhang, Xin-Guo; Gupta, Parag

2016-01-01

In this paper, a scheme for chaotic modulation secure communication is proposed based on chaotic synchronization of an improved Lorenz system. For the first time, the intensity limit and stability of the transmitted signal, the characteristics of broadband and the requirements for accuracy of electronic components are presented by Multisim simulation. In addition, some improvements are made on the measurement method and the proposed experimental circuit in order to facilitate the experiments of chaotic synchronization, chaotic non-synchronization, experiment without signal and experiment with signal. To illustrate the effectiveness of the proposed scheme, some numerical simulations are presented. Then, the proposed chaotic secure communication circuit is implemented through analog electronic circuit, which is characterized by its high accuracy and good robustness.

Link prediction boosted psychiatry disorder classification for functional connectivity network

NASA Astrophysics Data System (ADS)

Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

2017-02-01

Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

Using known map category marginal frequencies to improve estimates of thematic map accuracy

NASA Technical Reports Server (NTRS)

Card, D. H.

1982-01-01

By means of two simple sampling plans suggested in the accuracy-assessment literature, it is shown how one can use knowledge of map-category relative sizes to improve estimates of various probabilities. The fact that maximum likelihood estimates of cell probabilities for the simple random sampling and map category-stratified sampling were identical has permitted a unified treatment of the contingency-table analysis. A rigorous analysis of the effect of sampling independently within map categories is made possible by results for the stratified case. It is noted that such matters as optimal sample size selection for the achievement of a desired level of precision in various estimators are irrelevant, since the estimators derived are valid irrespective of how sample sizes are chosen.

Divergence-free smoothing for MRV data on stenosed carotid artery phantom flows

NASA Astrophysics Data System (ADS)

Im, Chaehyuk; Ko, Seungbin; Song, Simon

2017-11-01

Magnetic Resonance Velocimetry (MRV) is a versatile technique for measuring flow velocity using an MRI machine. It is frequently used for visualization and analysis of blood flows. However, it is difficult to accurately estimate hemodynamics parameters like wall shear stress (WSS) and oscillatory shear index (OSI) due to its low spatial resolution and low signal-to-noise ratio. We suggest a divergence-free smoothing (DFS) method to correct the erroneous velocity vectors obtained with MRV and improve the estimation accuracy of those parameters. Unlike previous studies on DFS for a wall-free flow, we developed a house code to apply a DFS method to a wall-bounded flow. A Hagen-Poiseuille flow and stenosed carotid artery phantom flows were measured with MRV. Each of them was analyzed for validation of the DFS code and confirmation on the accuracy improvement of hemodynamic parameters. We will discuss the effects of DFS on the improvement of the estimation accuracy of velocity vectors, WSS, OSI and etc in detail This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(MSIP) (No. 2016R1A2B3009541).

Physics and biophysics experiments needed for improved risk assessment in space

NASA Astrophysics Data System (ADS)

Sihver, L.

To improve the risk assessment of radiation carcinogenesis, late degenerative tissue effects, acute syndromes, synergistic effects of radiation and microgravity or other spacecraft factors, and hereditary effects, on future LEO and interplanetary space missions, the radiobiological effects of cosmic radiation before and after shielding must be well understood. However, cosmic radiation is very complex and includes low and high LET components of many different neutral and charged particles. The understanding of the radiobiology of the heavy ions, from GCRs and SPEs, is still a subject of great concern due to the complicated dependence of their biological effects on the type of ion and energy, and its interaction with various targets both outside and within the spacecraft and the human body. In order to estimate the biological effects of cosmic radiation, accurate knowledge of the physics of the interactions of both charged and non-charged high-LET particles is necessary. Since it is practically impossible to measure all primary and secondary particles from all projectile-target-energy combinations needed for a correct risk assessment in space, accurate particle and heavy ion transport codes might be a helpful instrument to overcome those difficulties. These codes have to be carefully validated to make sure they fulfill preset accuracy criteria, e.g. to be able to predict particle fluence and energy distributions within a certain accuracy. When validating the accuracy of the transport codes, both space and ground-based accelerator experiments are needed. In this paper current and future physics and biophysics experiments needed for improved risk assessment in space will be discussed. The cyclotron HIRFL (heavy ion research facility in Lanzhou) and the new synchrotron CSR (cooling storage ring), which can be used to provide ion beams for space related experiments at the Institute of Modern Physics, Chinese Academy of Sciences (IMP-CAS), will be presented together with the physical and biomedical research performed at IMP-CAS.

Economic Value of Improved Accuracy for Self-Monitoring of Blood Glucose Devices for Type 1 and Type 2 Diabetes in England.

PubMed

McQueen, Robert Brett; Breton, Marc D; Craig, Joyce; Holmes, Hayden; Whittington, Melanie D; Ott, Markus A; Campbell, Jonathan D

2018-04-01

The objective was to model clinical and economic outcomes of self-monitoring blood glucose (SMBG) devices with varying error ranges and strip prices for type 1 and insulin-treated type 2 diabetes patients in England. We programmed a simulation model that included separate risk and complication estimates by type of diabetes and evidence from in silico modeling validated by the Food and Drug Administration. Changes in SMBG error were associated with changes in hemoglobin A1c (HbA1c) and separately, changes in hypoglycemia. Markov cohort simulation estimated clinical and economic outcomes. A SMBG device with 8.4% error and strip price of £0.30 (exceeding accuracy requirements by International Organization for Standardization [ISO] 15197:2013/EN ISO 15197:2015) was compared to a device with 15% error (accuracy meeting ISO 15197:2013/EN ISO 15197:2015) and price of £0.20. Outcomes were lifetime costs, quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). With SMBG errors associated with changes in HbA1c only, the ICER was £3064 per QALY in type 1 diabetes and £264 668 per QALY in insulin-treated type 2 diabetes for an SMBG device with 8.4% versus 15% error. With SMBG errors associated with hypoglycemic events only, the device exceeding accuracy requirements was cost-saving and more effective in insulin-treated type 1 and type 2 diabetes. Investment in devices with higher strip prices but improved accuracy (less error) appears to be an efficient strategy for insulin-treated diabetes patients at high risk of severe hypoglycemia.

Earth Orientation Effects on Mobile VLBI Baselines

NASA Technical Reports Server (NTRS)

Allen, S. L.

1984-01-01

Improvements in data quality for the mobile VLBI systems have placed higher accuracy requirements on Earth orientation calibrations. Errors in these calibrations may give rise to systematic effects in the nonlength components of the baselines. Various sources of Earth orientation data were investigated for calibration of Mobile VLBI baselines. Significant differences in quality between the several available sources of UT1-UTC were found. It was shown that the JPL Kalman filtered space technology data were at least as good as any other and adequate to the needs of current Mobile VLBI systems and observing plans. For polar motion, the values from all service suffice. The effect of Earth orientation errors on the accuracy of differenced baselines was also investigated. It is shown that the effect is negligible for the current mobile systems and observing plan.

Inversion technique for IR heterodyne sounding of stratospheric constituents from space platforms

NASA Technical Reports Server (NTRS)

Abbas, M. M.; Shapiro, G. L.; Alvarez, J. M.

1981-01-01

The techniques which have been employed for inversion of IR heterodyne measurements for remote sounding of stratospheric trace constituents usually rely on either geometric effects based on limb-scan observations (i.e., onion peel techniques) or spectral effects by using weighting functions corresponding to different frequencies of an IR spectral line. An experimental approach and inversion technique are discussed which optimize the retrieval of concentration profiles by combining the geometric and the spectral effects in an IR heterodyne receiver. The results of inversions of some synthetic CIO spectral lines corresponding to solar occultation limb scans of the stratosphere are presented, indicating considerable improvement in the accuracy of the retrieved profiles. The effects of noise on the accuracy of retrievals are discussed for realistic situations.

Inversion technique for IR heterodyne sounding of stratospheric constituents from space platforms.

PubMed

Abbas, M M; Shapiro, G L; Alvarez, J M

1981-11-01

The techniques which have been employed for inversion of IR heterodyne measurements for remote sounding of stratospheric trace constituents usually rely on either geometric effects based on limb-scan observations (i.e., onion peel techniques) or spectral effects by using weighting functions corresponding to different frequencies of an IR spectral line. An experimental approach and inversion technique are discussed which optimize the retrieval of concentration profiles by combining the geometric and the spectral effects in an IR heterodyne receiver. The results of inversions of some synthetic ClO spectral lines corresponding to solar occultation limb scans of the stratosphere are presented, indicating considerable improvement in the accuracy of the retrieved profiles. The effects of noise on the accuracy of retrievals are discussed for realistic situations.

23 CFR 1200.22 - State traffic safety information system improvements grants.

Code of Federal Regulations, 2013 CFR

2013-04-01

... measures to be used to demonstrate quantitative progress in the accuracy, completeness, timeliness... to implement, provides an explanation. (d) Requirement for quantitative improvement. A State shall demonstrate quantitative improvement in the data attributes of accuracy, completeness, timeliness, uniformity...

23 CFR 1200.22 - State traffic safety information system improvements grants.

Code of Federal Regulations, 2014 CFR

2014-04-01

... measures to be used to demonstrate quantitative progress in the accuracy, completeness, timeliness... to implement, provides an explanation. (d) Requirement for quantitative improvement. A State shall demonstrate quantitative improvement in the data attributes of accuracy, completeness, timeliness, uniformity...

A Systematic Review and Meta-Analysis of the Effects of Transcranial Direct Current Stimulation (tDCS) Over the Dorsolateral Prefrontal Cortex in Healthy and Neuropsychiatric Samples: Influence of Stimulation Parameters.

PubMed

Dedoncker, Josefien; Brunoni, Andre R; Baeken, Chris; Vanderhasselt, Marie-Anne

2016-01-01

Research into the effects of transcranial direct current stimulation of the dorsolateral prefrontal cortex on cognitive functioning is increasing rapidly. However, methodological heterogeneity in prefrontal tDCS research is also increasing, particularly in technical stimulation parameters that might influence tDCS effects. To systematically examine the influence of technical stimulation parameters on DLPFC-tDCS effects. We performed a systematic review and meta-analysis of tDCS studies targeting the DLPFC published from the first data available to February 2016. Only single-session, sham-controlled, within-subject studies reporting the effects of tDCS on cognition in healthy controls and neuropsychiatric patients were included. Evaluation of 61 studies showed that after single-session a-tDCS, but not c-tDCS, participants responded faster and more accurately on cognitive tasks. Sub-analyses specified that following a-tDCS, healthy subjects responded faster, while neuropsychiatric patients responded more accurately. Importantly, different stimulation parameters affected a-tDCS effects, but not c-tDCS effects, on accuracy in healthy samples vs. increased current density and density charge resulted in improved accuracy in healthy samples, most prominently in females; for neuropsychiatric patients, task performance during a-tDCS resulted in stronger increases in accuracy rates compared to task performance following a-tDCS. Healthy participants respond faster, but not more accurate on cognitive tasks after a-tDCS. However, increasing the current density and/or charge might be able to enhance response accuracy, particularly in females. In contrast, online task performance leads to greater increases in response accuracy than offline task performance in neuropsychiatric patients. Possible implications and practical recommendations are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Direct Detection Doppler Lidar for Spaceborne Wind Measurement

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Flesia, Cristina

1999-01-01

The theory of double edge lidar techniques for measuring the atmospheric wind using aerosol and molecular backscatter is described. Two high spectral resolution filters with opposite slopes are located about the laser frequency for the aerosol based measurement or in the wings of the Rayleigh - Brillouin profile for the molecular measurement. This doubles the signal change per unit Doppler shift and improves the measurement accuracy by nearly a factor of 2 relative to the single edge technique. For the aerosol based measurement, the use of two high resolution edge filters reduces the effects of background, Rayleigh scattering, by as much as an order of magnitude and substantially improves the measurement accuracy. Also, we describe a method that allows the Rayleigh and aerosol components of the signal to be independently determined. A measurement accuracy of 1.2 m/s can be obtained for a signal level of 1000 detected photons which corresponds to signal levels in the boundary layer. For the molecular based measurement, we describe the use of a crossover region where the sensitivity of a molecular and aerosol-based measurement are equal. This desensitizes the molecular measurement to the effects of aerosol scattering and greatly simplifies the measurement. Simulations using a conical scanning spaceborne lidar at 355 nm give an accuracy of 2-3 m/s for altitudes of 2-15 km for a 1 km vertical resolution, a satellite altitude of 400 km, and a 200 km x 200 km spatial.

Genotyping by sequencing for genomic prediction in a soybean breeding population.

PubMed

Jarquín, Diego; Kocak, Kyle; Posadas, Luis; Hyma, Katie; Jedlicka, Joseph; Graef, George; Lorenz, Aaron

2014-08-29

Advances in genotyping technology, such as genotyping by sequencing (GBS), are making genomic prediction more attractive to reduce breeding cycle times and costs associated with phenotyping. Genomic prediction and selection has been studied in several crop species, but no reports exist in soybean. The objectives of this study were (i) evaluate prospects for genomic selection using GBS in a typical soybean breeding program and (ii) evaluate the effect of GBS marker selection and imputation on genomic prediction accuracy. To achieve these objectives, a set of soybean lines sampled from the University of Nebraska Soybean Breeding Program were genotyped using GBS and evaluated for yield and other agronomic traits at multiple Nebraska locations. Genotyping by sequencing scored 16,502 single nucleotide polymorphisms (SNPs) with minor-allele frequency (MAF) > 0.05 and percentage of missing values ≤ 5% on 301 elite soybean breeding lines. When SNPs with up to 80% missing values were included, 52,349 SNPs were scored. Prediction accuracy for grain yield, assessed using cross validation, was estimated to be 0.64, indicating good potential for using genomic selection for grain yield in soybean. Filtering SNPs based on missing data percentage had little to no effect on prediction accuracy, especially when random forest imputation was used to impute missing values. The highest accuracies were observed when random forest imputation was used on all SNPs, but differences were not significant. A standard additive G-BLUP model was robust; modeling additive-by-additive epistasis did not provide any improvement in prediction accuracy. The effect of training population size on accuracy began to plateau around 100, but accuracy steadily climbed until the largest possible size was used in this analysis. Including only SNPs with MAF > 0.30 provided higher accuracies when training populations were smaller. Using GBS for genomic prediction in soybean holds good potential to expedite genetic gain. Our results suggest that standard additive G-BLUP models can be used on unfiltered, imputed GBS data without loss in accuracy.

Wire-positioning algorithm for coreless Hall array sensors in current measurement

NASA Astrophysics Data System (ADS)

Chen, Wenli; Zhang, Huaiqing; Chen, Lin; Gu, Shanyun

2018-05-01

This paper presents a scheme of circular-arrayed, coreless Hall-effect current transformers. It can satisfy the demands of wide dynamic range and bandwidth current in the distribution system, as well as the demand of AC and DC simultaneous measurements. In order to improve the signal to noise ratio (SNR) of the sensor, a wire-positioning algorithm is proposed, which can improve the measurement accuracy based on the post-processing of measurement data. The simulation results demonstrate that the maximum errors are 70%, 6.1% and 0.95% corresponding to Ampère’s circuital method, approximate positioning algorithm and precise positioning algorithm, respectively. It is obvious that the accuracy of the positioning algorithm is significantly improved when compared with that of the Ampère’s circuital method. The maximum error of the positioning algorithm is smaller in the experiment.

Magnetic resonance imaging of the preterm infant brain.

PubMed

Doria, Valentina; Arichi, Tomoki; Edwards, David A

2014-01-01

Despite improvements in neonatal care, survivors of preterm birth are still at a significantly increased risk of developing life-long neurological difficulties including cerebral palsy and cognitive difficulties. Cranial ultrasound is routinely used in neonatal practice, but has a low sensitivity for identifying later neurodevelopmental difficulties. Magnetic Resonance Imaging (MRI) can be used to identify intracranial abnormalities with greater diagnostic accuracy in preterm infants, and theoretically might improve the planning and targeting of long-term neurodevelopmental care; reducing parental stress and unplanned healthcare utilisation; and ultimately may improve healthcare cost effectiveness. Furthermore, MR imaging offers the advantage of allowing the quantitative assessment of the integrity, growth and function of intracranial structures, thereby providing the means to develop sensitive biomarkers which may be predictive of later neurological impairment. However further work is needed to define the accuracy and value of diagnosis by MR and the techniques's precise role in care pathways for preterm infants.

Characterisation of residual ionospheric errors in bending angles using GNSS RO end-to-end simulations

NASA Astrophysics Data System (ADS)

Liu, C. L.; Kirchengast, G.; Zhang, K. F.; Norman, R.; Li, Y.; Zhang, S. C.; Carter, B.; Fritzer, J.; Schwaerz, M.; Choy, S. L.; Wu, S. Q.; Tan, Z. X.

2013-09-01

Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique.

Acoustic⁻Seismic Mixed Feature Extraction Based on Wavelet Transform for Vehicle Classification in Wireless Sensor Networks.

PubMed

Zhang, Heng; Pan, Zhongming; Zhang, Wenna

2018-06-07

An acoustic⁻seismic mixed feature extraction method based on the wavelet coefficient energy ratio (WCER) of the target signal is proposed in this study for classifying vehicle targets in wireless sensor networks. The signal was decomposed into a set of wavelet coefficients using the à trous algorithm, which is a concise method used to implement the wavelet transform of a discrete signal sequence. After the wavelet coefficients of the target acoustic and seismic signals were obtained, the energy ratio of each layer coefficient was calculated as the feature vector of the target signals. Subsequently, the acoustic and seismic features were merged into an acoustic⁻seismic mixed feature to improve the target classification accuracy after the acoustic and seismic WCER features of the target signal were simplified using the hierarchical clustering method. We selected the support vector machine method for classification and utilized the data acquired from a real-world experiment to validate the proposed method. The calculated results show that the WCER feature extraction method can effectively extract the target features from target signals. Feature simplification can reduce the time consumption of feature extraction and classification, with no effect on the target classification accuracy. The use of acoustic⁻seismic mixed features effectively improved target classification accuracy by approximately 12% compared with either acoustic signal or seismic signal alone.

Improving Children’s Knowledge of Fraction Magnitudes

PubMed Central

Fazio, Lisa K.; Kennedy, Casey A.; Siegler, Robert S.

2016-01-01

We examined whether playing a computerized fraction game, based on the integrated theory of numerical development and on the Common Core State Standards’ suggestions for teaching fractions, would improve children’s fraction magnitude understanding. Fourth and fifth-graders were given brief instruction about unit fractions and played Catch the Monster with Fractions, a game in which they estimated fraction locations on a number line and received feedback on the accuracy of their estimates. The intervention lasted less than 15 minutes. In our initial study, children showed large gains from pretest to posttest in their fraction number line estimates, magnitude comparisons, and recall accuracy. In a more rigorous second study, the experimental group showed similarly large improvements, whereas a control group showed no improvement from practicing fraction number line estimates without feedback. The results provide evidence for the effectiveness of interventions emphasizing fraction magnitudes and indicate how psychological theories and research can be used to evaluate specific recommendations of the Common Core State Standards. PMID:27768756

Comparative Approach of MRI-Based Brain Tumor Segmentation and Classification Using Genetic Algorithm.

PubMed

Bahadure, Nilesh Bhaskarrao; Ray, Arun Kumar; Thethi, Har Pal

2018-01-17

The detection of a brain tumor and its classification from modern imaging modalities is a primary concern, but a time-consuming and tedious work was performed by radiologists or clinical supervisors. The accuracy of detection and classification of tumor stages performed by radiologists is depended on their experience only, so the computer-aided technology is very important to aid with the diagnosis accuracy. In this study, to improve the performance of tumor detection, we investigated comparative approach of different segmentation techniques and selected the best one by comparing their segmentation score. Further, to improve the classification accuracy, the genetic algorithm is employed for the automatic classification of tumor stage. The decision of classification stage is supported by extracting relevant features and area calculation. The experimental results of proposed technique are evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on segmentation score, accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 92.03% accuracy, 91.42% specificity, 92.36% sensitivity, and an average segmentation score between 0.82 and 0.93 demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 93.79% dice similarity index coefficient, which indicates better overlap between the automated extracted tumor regions with manually extracted tumor region by radiologists.

Fusion with Language Models Improves Spelling Accuracy for ERP-based Brain Computer Interface Spellers

PubMed Central

Orhan, Umut; Erdogmus, Deniz; Roark, Brian; Purwar, Shalini; Hild, Kenneth E.; Oken, Barry; Nezamfar, Hooman; Fried-Oken, Melanie

2013-01-01

Event related potentials (ERP) corresponding to a stimulus in electroencephalography (EEG) can be used to detect the intent of a person for brain computer interfaces (BCI). This paradigm is widely utilized to build letter-by-letter text input systems using BCI. Nevertheless using a BCI-typewriter depending only on EEG responses will not be sufficiently accurate for single-trial operation in general, and existing systems utilize many-trial schemes to achieve accuracy at the cost of speed. Hence incorporation of a language model based prior or additional evidence is vital to improve accuracy and speed. In this paper, we study the effects of Bayesian fusion of an n-gram language model with a regularized discriminant analysis ERP detector for EEG-based BCIs. The letter classification accuracies are rigorously evaluated for varying language model orders as well as number of ERP-inducing trials. The results demonstrate that the language models contribute significantly to letter classification accuracy. Specifically, we find that a BCI-speller supported by a 4-gram language model may achieve the same performance using 3-trial ERP classification for the initial letters of the words and using single trial ERP classification for the subsequent ones. Overall, fusion of evidence from EEG and language models yields a significant opportunity to increase the word rate of a BCI based typing system. PMID:22255652

Robotic Assistance Enables Inexperienced Surgeons to Perform Unicompartmental Knee Arthroplasties on Dry Bone Models with Accuracy Superior to Conventional Methods

PubMed Central

Masjedi, Milad; Andrews, Barry; Cobb, Justin

2013-01-01

Robotic systems have been shown to improve unicompartmental knee arthroplasty (UKA) component placement accuracy compared to conventional methods when used by experienced surgeons. We aimed to determine whether inexperienced UKA surgeons can position components accurately using robotic assistance when compared to conventional methods and to demonstrate the effect repetition has on accuracy. Sixteen surgeons were randomised to an active constraint robot or conventional group performing three UKAs over three weeks. Implanted component positions and orientations were compared to planned component positions in six degrees of freedom for both femoral and tibial components. Mean procedure time decreased for both robot (37.5 mins to 25.7 mins) (P = 0.002) and conventional (33.8 mins to 21.0 mins) (P = 0.002) groups by attempt three indicating the presence of a learning curve; however, neither group demonstrated changes in accuracy. Mean compound rotational and translational errors were lower in the robot group compared to the conventional group for both components at all attempts for which rotational error differences were significant at every attempt. The conventional group's positioning remained inaccurate even with repeated attempts although procedure time improved. In comparison, by limiting inaccuracies inherent in conventional equipment, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their experience. PMID:23862069

ISEA (International geodetic project in SouthEastern Alaska) for rapid uplifting caused by glacial retreat: (4) Gravity tide observation

NASA Astrophysics Data System (ADS)

Sato, T.; Miura, S.; Sun, W.; Kaufman, A. M.; Cross, R.; Freymueller, J. T.; Heavner, M.

2006-12-01

The southeastern Alaska shows a large uplift rate as 30 mm/yr at most, which is considered to be closely related to the glacial isostatic adjustment (GIA) including two effects of the past and present-day ice melting (Larsen et al., 2004). So, this area is important to improve our knowledge of the viscoelastic property of the earth and to consider the global changes. Combing the displacement and gravity observations is useful to constrain the model computation results for GIA (Sato et al., 2006). In order to progress the previous work by the group of Univ. Alaska, Fairbanks (UAF), an observation project by Japan and USA groups was started in 2005 (Miura et al., this meeting). Under this project, June 2006, the continuous GPS measurements started (M. Kufman et al., this meeting) and the absolute gravity (AG) measurements were conducted (W. Sun et al., this meeting). Precise correction for the effect of ocean tide loading is one of the key to increase the observation accuracy of the GPS and gravity observations, especially for the AG measurement. Thanks for the satellite sea surface altimeters such as TOPEX/Poseidon and Jason-1, the accuracy of global ocean tide models based on these data has been much improved, and its accuracy is estimated at a level better than 1.3 cm as a RMS error of the vector differences of the 8 main tidal waves (Matsumoto et al., 2006). However, on the other hand, it is known that the southeastern Alaska is a place that shows a large discrepancy among the proposed global ocean tide models mainly due to a complex topography and bathymetry of the fjord area. In order to improve the accuracy of the ocean tide correction, we started the gravity tide observation at Juneau from June 2006. Two kinds of gravimeters are used for the observation. Sampling interval of the data is at every 1 min. We analyzed the 1 month data from the beginning of the observation and compared the tidal analysis results with the model tide including both effects of the solid and ocean tides. For this computation, we used the Love numbers and the loading Green function for the PREM earth model (Dziewonski & Anderson, 1981) and a global ocean tide model by Schwiderski (1980). Our comparison clearly indicates that a possibility to improve the accuracy of the model prediction by taking into account the actual tidal harmonics observed in the southeastern Alaska.

Knowing where is different from knowing what: Distinct response time profiles and accuracy effects for target location, orientation, and color probability.

PubMed

Jabar, Syaheed B; Filipowicz, Alex; Anderson, Britt

2017-11-01

When a location is cued, targets appearing at that location are detected more quickly. When a target feature is cued, targets bearing that feature are detected more quickly. These attentional cueing effects are only superficially similar. More detailed analyses find distinct temporal and accuracy profiles for the two different types of cues. This pattern parallels work with probability manipulations, where both feature and spatial probability are known to affect detection accuracy and reaction times. However, little has been done by way of comparing these effects. Are probability manipulations on space and features distinct? In a series of five experiments, we systematically varied spatial probability and feature probability along two dimensions (orientation or color). In addition, we decomposed response times into initiation and movement components. Targets appearing at the probable location were reported more quickly and more accurately regardless of whether the report was based on orientation or color. On the other hand, when either color probability or orientation probability was manipulated, response time and accuracy improvements were specific for that probable feature dimension. Decomposition of the response time benefits demonstrated that spatial probability only affected initiation times, whereas manipulations of feature probability affected both initiation and movement times. As detection was made more difficult, the two effects further diverged, with spatial probability disproportionally affecting initiation times and feature probability disproportionately affecting accuracy. In conclusion, all manipulations of probability, whether spatial or featural, affect detection. However, only feature probability affects perceptual precision, and precision effects are specific to the probable attribute.

The effect of clock, media, and station location errors on Doppler measurement accuracy

NASA Technical Reports Server (NTRS)

Miller, J. K.

1993-01-01

Doppler tracking by the Deep Space Network (DSN) is the primary radio metric data type used by navigation to determine the orbit of a spacecraft. The accuracy normally attributed to orbits determined exclusively with Doppler data is about 0.5 microradians in geocentric angle. Recently, the Doppler measurement system has evolved to a high degree of precision primarily because of tracking at X-band frequencies (7.2 to 8.5 GHz). However, the orbit determination system has not been able to fully utilize this improved measurement accuracy because of calibration errors associated with transmission media, the location of tracking stations on the Earth's surface, the orientation of the Earth as an observing platform, and timekeeping. With the introduction of Global Positioning System (GPS) data, it may be possible to remove a significant error associated with the troposphere. In this article, the effect of various calibration errors associated with transmission media, Earth platform parameters, and clocks are examined. With the introduction of GPS calibrations, it is predicted that a Doppler tracking accuracy of 0.05 microradians is achievable.

Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation

PubMed Central

Parsons, Helen M; Ludwig, Christian; Günther, Ulrich L; Viant, Mark R

2007-01-01

Background Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend upon the variance of the data, it is important to first minimise any contribution from unwanted technical variance arising from sample preparation and analytical measurements, and thereby maximise any contribution from wanted biological variance between different classes. The generalised logarithm (glog) transform was developed to stabilise the variance in DNA microarray datasets, but has rarely been applied to metabolomics data. In particular, it has not been rigorously evaluated against other scaling techniques used in metabolomics, nor tested on all forms of NMR spectra including 1-dimensional (1D) 1H, projections of 2D 1H, 1H J-resolved (pJRES), and intact 2D J-resolved (JRES). Results Here, the effects of the glog transform are compared against two commonly used variance stabilising techniques, autoscaling and Pareto scaling, as well as unscaled data. The four methods are evaluated in terms of the effects on the variance of NMR metabolomics data and on the classification accuracy following multivariate analysis, the latter achieved using principal component analysis followed by linear discriminant analysis. For two of three datasets analysed, classification accuracies were highest following glog transformation: 100% accuracy for discriminating 1D NMR spectra of hypoxic and normoxic invertebrate muscle, and 100% accuracy for discriminating 2D JRES spectra of fish livers sampled from two rivers. For the third dataset, pJRES spectra of urine from two breeds of dog, the glog transform and autoscaling achieved equal highest accuracies. Additionally we extended the glog algorithm to effectively suppress noise, which proved critical for the analysis of 2D JRES spectra. Conclusion We have demonstrated that the glog and extended glog transforms stabilise the technical variance in NMR metabolomics datasets. This significantly improves the discrimination between sample classes and has resulted in higher classification accuracies compared to unscaled, autoscaled or Pareto scaled data. Additionally we have confirmed the broad applicability of the glog approach using three disparate datasets from different biological samples using 1D NMR spectra, 1D projections of 2D JRES spectra, and intact 2D JRES spectra. PMID:17605789

Confidence and Information Access in Clinical Decision-Making: An Examination of the Cognitive Processes that affect the Information-seeking Behavior of Physicians.

PubMed

Uy, Raymonde Charles; Sarmiento, Raymond Francis; Gavino, Alex; Fontelo, Paul

2014-01-01

Clinical decision-making involves the interplay between cognitive processes and physicians' perceptions of confidence in the context of their information-seeking behavior. The objectives of the study are: to examine how these concepts interact, to determine whether physician confidence, defined in relation to information need, affects clinical decision-making, and if information access improves decision accuracy. We analyzed previously collected data about resident physicians' perceptions of information need from a study comparing abstracts and full-text articles in clinical decision accuracy. We found that there is a significant relation between confidence and accuracy (φ=0.164, p<0.01). We also found various differences in the alignment of confidence and accuracy, demonstrating the concepts of underconfidence and overconfidence across years of clinical experience. Access to online literature also has a significant effect on accuracy (p<0.001). These results highlight possible CDSS strategies to reduce medical errors.

Improving the Reading of Bisyllabic Words That Involve Context-Sensitive Spelling Rules: Focus on Successes or on Failures?

ERIC Educational Resources Information Center

Steenbeek-Planting, Esther G.; van Bon, Wim H. J.; Schreuder, Robert

2013-01-01

The effect of two training procedures on the improvement of reading accuracy in poor readers was examined in relation to their initial reading level. A randomized controlled trial was conducted with 60 poor readers. Poor readers were assigned to a control group that received no training, or one of two training conditions. One training concentrated…

Accuracy Improvement of Neutron Nuclear Data on Minor Actinides

NASA Astrophysics Data System (ADS)

Harada, Hideo; Iwamoto, Osamu; Iwamoto, Nobuyuki; Kimura, Atsushi; Terada, Kazushi; Nakao, Taro; Nakamura, Shoji; Mizuyama, Kazuhito; Igashira, Masayuki; Katabuchi, Tatsuya; Sano, Tadafumi; Takahashi, Yoshiyuki; Takamiya, Koichi; Pyeon, Cheol Ho; Fukutani, Satoshi; Fujii, Toshiyuki; Hori, Jun-ichi; Yagi, Takahiro; Yashima, Hiroshi

2015-05-01

Improvement of accuracy of neutron nuclear data for minor actinides (MAs) and long-lived fission products (LLFPs) is required for developing innovative nuclear system transmuting these nuclei. In order to meet the requirement, the project entitled as "Research and development for Accuracy Improvement of neutron nuclear data on Minor ACtinides (AIMAC)" has been started as one of the "Innovative Nuclear Research and Development Program" in Japan at October 2013. The AIMAC project team is composed of researchers in four different fields: differential nuclear data measurement, integral nuclear data measurement, nuclear chemistry, and nuclear data evaluation. By integrating all of the forefront knowledge and techniques in these fields, the team aims at improving the accuracy of the data. The background and research plan of the AIMAC project are presented.

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

PubMed

Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

2016-05-30

Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R² = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m²), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

The effect of balance training on cervical sensorimotor function and neck pain.

PubMed

Beinert, Konstantin; Taube, Wolfgang

2013-01-01

The authors' aim was to evaluate the effect of balance training on cervical joint position sense in people with subclinical neck pain. Thirty-four participants were randomly assigned to balance training or to stay active. Sensorimotor function was determined before and after 5 weeks of training by assessing the ability to reproduce the neutral head position and a predefined rotated head position. After balance training, the intervention group showed improved joint repositioning accuracy and decreased pain whereas no effects were observed in the control group. A weak correlation was identified between reduced neck pain intensity and improved joint repositioning. The present data demonstrate that balance training can effectively improve cervical sensorimotor function and decrease neck pain intensity.

Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.

PubMed

Maldonado, G; Greenland, S

1998-07-01

A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.

Bayesian Network Structure Learning for Urban Land Use Classification from Landsat ETM+ and Ancillary Data

NASA Astrophysics Data System (ADS)

Park, M.; Stenstrom, M. K.

2004-12-01

Recognizing urban information from the satellite imagery is problematic due to the diverse features and dynamic changes of urban landuse. The use of Landsat imagery for urban land use classification involves inherent uncertainty due to its spatial resolution and the low separability among land uses. To resolve the uncertainty problem, we investigated the performance of Bayesian networks to classify urban land use since Bayesian networks provide a quantitative way of handling uncertainty and have been successfully used in many areas. In this study, we developed the optimized networks for urban land use classification from Landsat ETM+ images of Marina del Rey area based on USGS land cover/use classification level III. The networks started from a tree structure based on mutual information between variables and added the links to improve accuracy. This methodology offers several advantages: (1) The network structure shows the dependency relationships between variables. The class node value can be predicted even with particular band information missing due to sensor system error. The missing information can be inferred from other dependent bands. (2) The network structure provides information of variables that are important for the classification, which is not available from conventional classification methods such as neural networks and maximum likelihood classification. In our case, for example, bands 1, 5 and 6 are the most important inputs in determining the land use of each pixel. (3) The networks can be reduced with those input variables important for classification. This minimizes the problem without considering all possible variables. We also examined the effect of incorporating ancillary data: geospatial information such as X and Y coordinate values of each pixel and DEM data, and vegetation indices such as NDVI and Tasseled Cap transformation. The results showed that the locational information improved overall accuracy (81%) and kappa coefficient (76%), and lowered the omission and commission errors compared with using only spectral data (accuracy 71%, kappa coefficient 62%). Incorporating DEM data did not significantly improve overall accuracy (74%) and kappa coefficient (66%) but lowered the omission and commission errors. Incorporating NDVI did not much improve the overall accuracy (72%) and k coefficient (65%). Including Tasseled Cap transformation reduced the accuracy (accuracy 70%, kappa 61%). Therefore, additional information from the DEM and vegetation indices was not useful as locational ancillary data.

[A practical procedure to improve the accuracy of radiochromic film dosimetry: a integration with a correction method of uniformity correction and a red/blue correction method].

PubMed

Uehara, Ryuzo; Tachibana, Hidenobu; Ito, Yasushi; Yoshino, Shinichi; Matsubayashi, Fumiyasu; Sato, Tomoharu

2013-06-01

It has been reported that the light scattering could worsen the accuracy of dose distribution measurement using a radiochromic film. The purpose of this study was to investigate the accuracy of two different films, EDR2 and EBT2, as film dosimetry tools. The effectiveness of a correction method for the non-uniformity caused from EBT2 film and the light scattering was also evaluated. In addition the efficacy of this correction method integrated with the red/blue correction method was assessed. EDR2 and EBT2 films were read using a flatbed charge-coupled device scanner (EPSON 10000G). Dose differences on the axis perpendicular to the scanner lamp movement axis were within 1% with EDR2, but exceeded 3% (Maximum: +8%) with EBT2. The non-uniformity correction method, after a single film exposure, was applied to the readout of the films. A corrected dose distribution data was subsequently created. The correction method showed more than 10%-better pass ratios in dose difference evaluation than when the correction method was not applied. The red/blue correction method resulted in 5%-improvement compared with the standard procedure that employed red color only. The correction method with EBT2 proved to be able to rapidly correct non-uniformity, and has potential for routine clinical IMRT dose verification if the accuracy of EBT2 is required to be similar to that of EDR2. The use of red/blue correction method may improve the accuracy, but we recommend we should use the red/blue correction method carefully and understand the characteristics of EBT2 for red color only and the red/blue correction method.

Back to Anatomy: Improving Landmarking Accuracy of Clinical Procedures Using a Novel Approach to Procedural Teaching.

PubMed

Zeller, Michelle; Cristancho, Sayra; Mangel, Joy; Goldszmidt, Mark

2015-06-01

Many believe that knowledge of anatomy is essential for performing clinical procedures; however, unlike their surgical counterparts, internal medicine (IM) programs rarely incorporate anatomy review into procedural teaching. This study tested the hypothesis that an educational intervention focused on teaching relevant surface and underlying anatomy would result in improved bone marrow procedure landmarking accuracy. This was a preintervention-postintervention prospective study on landmarking accuracy of consenting IM residents attending their mandatory academic half-day. The intervention included an interactive video and visualization exercise; the video was developed specifically to teach the relevant underlying anatomy and includes views of live volunteers, cadavers, and skeletons. Thirty-one IM residents participated. At pretest, 48% (15/31) of residents landmarked accurately. Inaccuracy of pretest landmarking varied widely (n = 16, mean 20.06 mm; standard deviation 30.03 mm). At posttest, 74% (23/31) of residents accurately performed the procedure. McNemar test revealed a nonsignificant trend toward increased performance at posttest (P = 0.076; unadjusted odds for discordant pairs 3; 95% confidence interval 0.97-9.3). The Wilcoxon signed rank test demonstrated a significant difference between pre- and posttest accuracy in the 16 residents who were inaccurate at pretest (P = 0.004). No association was detected between participant baseline characteristics and pretest accuracy. This study demonstrates that residents who were initially inaccurate were able to significantly improve their landmarking skills by interacting with an educational tool emphasizing the relation between the surface and underlying anatomy. Our results support the use of basic anatomy in teaching bone marrow procedures. Results also support the proper use of video as an effective means for incorporating anatomy teaching around procedural skills.

Note: An improved calibration system with phase correction for electronic transformers with digital output

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

Cheng, Han-miao, E-mail: chenghanmiao@hust.edu.cn; Li, Hong-bin, E-mail: lihongbin@hust.edu.cn; State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan 430074

The existing electronic transformer calibration systems employing data acquisition cards cannot satisfy some practical applications, because the calibration systems have phase measurement errors when they work in the mode of receiving external synchronization signals. This paper proposes an improved calibration system scheme with phase correction to improve the phase measurement accuracy. We employ NI PCI-4474 to design a calibration system, and the system has the potential to receive external synchronization signals and reach extremely high accuracy classes. Accuracy verification has been carried out in the China Electric Power Research Institute, and results demonstrate that the system surpasses the accuracy classmore » 0.05. Furthermore, this system has been used to test the harmonics measurement accuracy of all-fiber optical current transformers. In the same process, we have used an existing calibration system, and a comparison of the test results is presented. The system after improvement is suitable for the intended applications.« less

The Effects of Instructions on Mothers' Ratings of Child Attention-Deficit/Hyperactivity Disorder Symptoms

ERIC Educational Resources Information Center

Johnston, Charlotte; Weiss, Margaret; Murray, Candice; Miller, Natalie

2011-01-01

We examined whether instructional materials describing how to rate child ADHD symptoms would improve the accuracy of mothers' ratings of ADHD symptoms presented in standard child behavior stimuli, and whether instructions would be equally effective across a range of maternal depressive symptoms and family incomes. A community sample of 100 mothers…

Percutaneous spinal fixation simulation with virtual reality and haptics.

PubMed

Luciano, Cristian J; Banerjee, P Pat; Sorenson, Jeffery M; Foley, Kevin T; Ansari, Sameer A; Rizzi, Silvio; Germanwala, Anand V; Kranzler, Leonard; Chittiboina, Prashant; Roitberg, Ben Z

2013-01-01

In this study, we evaluated the use of a part-task simulator with 3-dimensional and haptic feedback as a training tool for percutaneous spinal needle placement. To evaluate the learning effectiveness in terms of entry point/target point accuracy of percutaneous spinal needle placement on a high-performance augmented-reality and haptic technology workstation with the ability to control the duration of computer-simulated fluoroscopic exposure, thereby simulating an actual situation. Sixty-three fellows and residents performed needle placement on the simulator. A virtual needle was percutaneously inserted into a virtual patient's thoracic spine derived from an actual patient computed tomography data set. Ten of 126 needle placement attempts by 63 participants ended in failure for a failure rate of 7.93%. From all 126 needle insertions, the average error (15.69 vs 13.91), average fluoroscopy exposure (4.6 vs 3.92), and average individual performance score (32.39 vs 30.71) improved from the first to the second attempt. Performance accuracy yielded P = .04 from a 2-sample t test in which the rejected null hypothesis assumes no improvement in performance accuracy from the first to second attempt in the test session. The experiments showed evidence (P = .04) of performance accuracy improvement from the first to the second percutaneous needle placement attempt. This result, combined with previous learning retention and/or face validity results of using the simulator for open thoracic pedicle screw placement and ventriculostomy catheter placement, supports the efficacy of augmented reality and haptics simulation as a learning tool.

Post processing for offline Chinese handwritten character string recognition

NASA Astrophysics Data System (ADS)

Wang, YanWei; Ding, XiaoQing; Liu, ChangSong

2012-01-01

Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition. Due to the free writing style, large variability in character shapes and different geometric characteristics, Chinese handwritten character string recognition is a challenging problem to deal with. However, among the current methods over-segmentation and merging method which integrates geometric information, character recognition information and contextual information, shows a promising result. It is found experimentally that a large part of errors are segmentation error and mainly occur around non-Chinese characters. In a Chinese character string, there are not only wide characters namely Chinese characters, but also narrow characters like digits and letters of the alphabet. The segmentation error is mainly caused by uniform geometric model imposed on all segmented candidate characters. To solve this problem, post processing is employed to improve recognition accuracy of narrow characters. On one hand, multi-geometric models are established for wide characters and narrow characters respectively. Under multi-geometric models narrow characters are not prone to be merged. On the other hand, top rank recognition results of candidate paths are integrated to boost final recognition of narrow characters. The post processing method is investigated on two datasets, in total 1405 handwritten address strings. The wide character recognition accuracy has been improved lightly and narrow character recognition accuracy has been increased up by 10.41% and 10.03% respectively. It indicates that the post processing method is effective to improve recognition accuracy of narrow characters.

Facilitating text reading in posterior cortical atrophy.

PubMed

Yong, Keir X X; Rajdev, Kishan; Shakespeare, Timothy J; Leff, Alexander P; Crutch, Sebastian J

2015-07-28

We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%-270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. © 2015 American Academy of Neurology.

Facilitating text reading in posterior cortical atrophy

PubMed Central

Rajdev, Kishan; Shakespeare, Timothy J.; Leff, Alexander P.; Crutch, Sebastian J.

2015-01-01

Objective: We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Methods: Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Results: Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%–270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. Conclusions: These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. Classification of evidence: This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. PMID:26138948

Conclusions about children's reporting accuracy for energy and macronutrients over multiple interviews depend on the analytic approach for comparing reported information to reference information.

PubMed

Baxter, Suzanne Domel; Smith, Albert F; Hardin, James W; Nichols, Michele D

2007-04-01

Validation study data are used to illustrate that conclusions about children's reporting accuracy for energy and macronutrients over multiple interviews (ie, time) depend on the analytic approach for comparing reported and reference information-conventional, which disregards accuracy of reported items and amounts, or reporting-error-sensitive, which classifies reported items as matches (eaten) or intrusions (not eaten), and amounts as corresponding or overreported. Children were observed eating school meals on 1 day (n=12), or 2 (n=13) or 3 (n=79) nonconsecutive days separated by >or=25 days, and interviewed in the morning after each observation day about intake the previous day. Reference (observed) and reported information were transformed to energy and macronutrients (ie, protein, carbohydrate, and fat), and compared. For energy and each macronutrient: report rates (reported/reference), correspondence rates (genuine accuracy measures), and inflation ratios (error measures). Mixed-model analyses. Using the conventional approach for analyzing energy and macronutrients, report rates did not vary systematically over interviews (all four P values >0.61). Using the reporting-error-sensitive approach for analyzing energy and macronutrients, correspondence rates increased over interviews (all four P values <0.04), indicating that reporting accuracy improved over time; inflation ratios decreased, although not significantly, over interviews, also suggesting that reporting accuracy improved over time. Correspondence rates were lower than report rates, indicating that reporting accuracy was worse than implied by conventional measures. When analyzed using the reporting-error-sensitive approach, children's dietary reporting accuracy for energy and macronutrients improved over time, but the conventional approach masked improvements and overestimated accuracy. The reporting-error-sensitive approach is recommended when analyzing data from validation studies of dietary reporting accuracy for energy and macronutrients.

Conclusions about children’s reporting accuracy for energy and macronutrients over multiple interviews depend on the analytic approach for comparing reported information to reference information

PubMed Central

Baxter, Suzanne Domel; Smith, Albert F.; Hardin, James W.; Nichols, Michele D.

2008-01-01

Objective Validation-study data are used to illustrate that conclusions about children’s reporting accuracy for energy and macronutrients over multiple interviews (ie, time) depend on the analytic approach for comparing reported and reference information—conventional, which disregards accuracy of reported items and amounts, or reporting-error-sensitive, which classifies reported items as matches (eaten) or intrusions (not eaten), and amounts as corresponding or overreported. Subjects and design Children were observed eating school meals on one day (n = 12), or two (n = 13) or three (n = 79) nonconsecutive days separated by ≥25 days, and interviewed in the morning after each observation day about intake the previous day. Reference (observed) and reported information were transformed to energy and macronutrients (protein, carbohydrate, fat), and compared. Main outcome measures For energy and each macronutrient: report rates (reported/reference), correspondence rates (genuine accuracy measures), inflation ratios (error measures). Statistical analyses Mixed-model analyses. Results Using the conventional approach for analyzing energy and macronutrients, report rates did not vary systematically over interviews (Ps > .61). Using the reporting-error-sensitive approach for analyzing energy and macronutrients, correspondence rates increased over interviews (Ps < .04), indicating that reporting accuracy improved over time; inflation ratios decreased, although not significantly, over interviews, also suggesting that reporting accuracy improved over time. Correspondence rates were lower than report rates, indicating that reporting accuracy was worse than implied by conventional measures. Conclusions When analyzed using the reporting-error-sensitive approach, children’s dietary reporting accuracy for energy and macronutrients improved over time, but the conventional approach masked improvements and overestimated accuracy. Applications The reporting-error-sensitive approach is recommended when analyzing data from validation studies of dietary reporting accuracy for energy and macronutrients. PMID:17383265

PCVs Estimation and their Impacts on Precise Orbit Determination of LEOs

NASA Astrophysics Data System (ADS)

Chunmei, Z.; WANG, X.

2017-12-01

In the last decade the precise orbit determination (POD) based on GNSS, such as GPS, has been considered as one of the efficient methods to derive orbits of Low Earth Orbiters (LEOs) that demand accuracy requirements. The Earth gravity field recovery and its related researches require precise dynamic orbits of LEOs. With the improvements of GNSS satellites' orbit and clock accuracy, the algorithm optimization and the refinement of perturbation force models, the antenna phase-center variations (PCVs) of space-borne GNSS receiver have become an increasingly important factor that affects POD accuracy. A series of LEOs such as HY-2, ZY-3 and FY-3 with homebred space-borne GNSS receivers have been launched in the past several years in China. Some of these LEOs load dual-mode GNSS receivers of GPS and BDS signals. The reliable performance of these space-borne receivers has been establishing an important foundation for the future launches of China gravity satellites. Therefore, we first evaluate the data quality of on-board GNSS measurement by examining integrity, multipath error, cycle slip ratio and other quality indices. Then we determine the orbits of several LEOs at different altitudes by the reduced dynamic orbit determination method. The corresponding ionosphere-free carrier phase post-fit residual time series are obtained. And then we establish the PCVs model by the ionosphere-free residual approach and analyze the effects of antenna phase-center variation on orbits. It is shown that orbit accuracy of LEO satellites is greatly improved after in-flight PCV calibration. Finally, focus on the dual-mode receiver of FY-3 satellite we analyze the quality of onboard BDS data and then evaluate the accuracy of the FY-3 orbit determined using only BDS measurement onboard. The accuracy of LEO satellites orbit based on BDS would be well improved with the global completion of BDS by 2020.

Practice increases procedural errors after task interruption.

PubMed

Altmann, Erik M; Hambrick, David Z

2017-05-01

Positive effects of practice are ubiquitous in human performance, but a finding from memory research suggests that negative effects are possible also. The finding is that memory for items on a list depends on the time interval between item presentations. This finding predicts a negative effect of practice on procedural performance under conditions of task interruption. As steps of a procedure are performed more quickly, memory for past performance should become less accurate, increasing the rate of skipped or repeated steps after an interruption. We found this effect, with practice generally improving speed and accuracy, but impairing accuracy after interruptions. The results show that positive effects of practice can interact with architectural constraints on episodic memory to have negative effects on performance. In practical terms, the results suggest that practice can be a risk factor for procedural errors in task environments with a high incidence of task interruption. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Numerical orbit generators of artificial earth satellites

NASA Astrophysics Data System (ADS)

Kugar, H. K.; Dasilva, W. C. C.

1984-04-01

A numerical orbit integrator containing updatings and improvements relative to the previous ones that are being utilized by the Departmento de Mecanica Espacial e Controle (DMC), of INPE, besides incorporating newer modellings resulting from the skill acquired along the time is presented. Flexibility and modularity were taken into account in order to allow future extensions and modifications. Characteristics of numerical accuracy, processing quickness, memory saving as well as utilization aspects were also considered. User's handbook, whole program listing and qualitative analysis of accuracy, processing time and orbit perturbation effects were included as well.

Analysis of polonium-210 in food products and bioassay samples by isotope-dilution alpha spectrometry.

PubMed

Lin, Zhichao; Wu, Zhongyu

2009-05-01

A rapid and reliable radiochemical method coupled with a simple and compact plating apparatus was developed, validated, and applied for the analysis of (210)Po in variety of food products and bioassay samples. The method performance characteristics, including accuracy, precision, robustness, and specificity, were evaluated along with a detailed measurement uncertainty analysis. With high Po recovery, improved energy resolution, and effective removal of interfering elements by chromatographic extraction, the overall method accuracy was determined to be better than 5% with measurement precision of 10%, at 95% confidence level.

Assessing effects of the e-Chasqui laboratory information system on accuracy and timeliness of bacteriology results in the Peruvian tuberculosis program.

PubMed

Blaya, Joaquin A; Shin, Sonya S; Yagui, Martin J A; Yale, Gloria; Suarez, Carmen; Asencios, Luis; Fraser, Hamish

2007-10-11

We created a web-based laboratory information system, e-Chasqui to connect public laboratories to health centers to improve communication and analysis. After one year, we performed a pre and post assessment of communication delays and found that e-Chasqui maintained the average delay but eliminated delays of over 60 days. Adding digital verification maintained the average delay, but should increase accuracy. We are currently performing a randomized evaluation of the impacts of e-Chasqui.

Improvement of Head-Up Display Standards. Volume 5. Head Up Display ILS (Instrument Landing System) Accuracy Flight Tests.

DTIC Science & Technology

1987-09-01

amber system. The front canopy of the NT-33A is cov- ered with an amber plastic sheet; when the front seat pilot low- ers his blue visor, the...tigation of the effect of head-up display symbol dynamic response caracteristics on flying qualities; Task B was an investigation of symbol accuracy...An amber vinyl plastic sheet covered the in- side front half of the NT-33 canopy. Blue snap-on visors were pi ovided to the evaluation pilots. The

Navigating highly elliptical earth orbiters with simultaneous VLBI from orthogonal baseline pairs

NASA Technical Reports Server (NTRS)

Frauenholz, Raymond B.

1986-01-01

Navigation strategies for determining highly elliptical orbits with VLBI are described. The predicted performance of wideband VLBI and Delta VLBI measurements obtained by orthogonal baseline pairs are compared for a 16-hr equatorial orbit. It is observed that the one-sigma apogee position accuracy improves two orders of magnitude to the meter level when Delta VLBI measurements are added to coherent Doppler and range, and the simpler VLBI strategy provides nearly the same orbit accuracy. The effects of differential measurement noise and acquisition geometry on orbit accuracy are investigated. The data reveal that quasar position uncertainty limits the accuracy of wideband Delta VLBI measurements, and that polar motion and baseline uncertainties and offsets between station clocks affect the wideband VLBI data. It is noted that differential one-way range (DOR) has performance nearly equal to that of the more complex Delta DOR and is recommended for use on spacecraft in high elliptical orbits.

Homo Heuristicus: Less-is-More Effects in Adaptive Cognition

PubMed Central

Brighton, Henry; Gigerenzer, Gerd

2012-01-01

Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We discuss some of the major progress made so far, focusing on the discovery of less-is-more effects and the study of the ecological rationality of heuristics which examines in which environments a given strategy succeeds or fails, and why. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies. PMID:23613644

A humming retrieval system based on music fingerprint

NASA Astrophysics Data System (ADS)

Han, Xingkai; Cao, Baiyu

2011-10-01

In this paper, we proposed an improved music information retrieval method utilizing the music fingerprint. The goal of this method is to represent the music with compressed musical information. Based on the selected MIDI files, which are generated automatically as our music target database, we evaluate the accuracy, effectiveness, and efficiency of this method. In this research we not only extract the feature sequence, which can represent the file effectively, from the query and melody database, but also make it possible for retrieving the results in an innovative way. We investigate on the influence of noise to the performance of our system. As experimental result shows, the retrieval accuracy arriving at up to91% without noise is pretty well

On aerodynamic wake analysis and its relation to total aerodynamic drag in a wind tunnel environment

NASA Astrophysics Data System (ADS)

Guterres, Rui M.

The present work was developed with the goal of advancing the state of the art in the application of three-dimensional wake data analysis to the quantification of aerodynamic drag on a body in a low speed wind tunnel environment. Analysis of the existing tools, their strengths and limitations is presented. Improvements to the existing analysis approaches were made. Software tools were developed to integrate the analysis into a practical tool. A comprehensive derivation of the equations needed for drag computations based on three dimensional separated wake data is developed. A set of complete steps ranging from the basic mathematical concept to the applicable engineering equations is presented. An extensive experimental study was conducted. Three representative body types were studied in varying ground effect conditions. A detailed qualitative wake analysis using wake imaging and two and three dimensional flow visualization was performed. Several significant features of the flow were identified and their relation to the total aerodynamic drag established. A comprehensive wake study of this type is shown to be in itself a powerful tool for the analysis of the wake aerodynamics and its relation to body drag. Quantitative wake analysis techniques were developed. Significant post processing and data conditioning tools and precision analysis were developed. The quality of the data is shown to be in direct correlation with the accuracy of the computed aerodynamic drag. Steps are taken to identify the sources of uncertainty. These are quantified when possible and the accuracy of the computed results is seen to significantly improve. When post processing alone does not resolve issues related to precision and accuracy, solutions are proposed. The improved quantitative wake analysis is applied to the wake data obtained. Guidelines are established that will lead to more successful implementation of these tools in future research programs. Close attention is paid to implementation of issues that are of crucial importance for the accuracy of the results and that are not detailed in the literature. The impact of ground effect on the flows in hand is qualitatively and quantitatively studied. Its impact on the accuracy of the computations as well as the wall drag incompatibility with the theoretical model followed are discussed. The newly developed quantitative analysis provides significantly increased accuracy. The aerodynamic drag coefficient is computed within one percent of balance measured value for the best cases.

Using Functional Electrical Stimulation Mediated by Iterative Learning Control and Robotics to Improve Arm Movement for People With Multiple Sclerosis.

PubMed

Sampson, Patrica; Freeman, Chris; Coote, Susan; Demain, Sara; Feys, Peter; Meadmore, Katie; Hughes, Ann-Marie

2016-02-01

Few interventions address multiple sclerosis (MS) arm dysfunction but robotics and functional electrical stimulation (FES) appear promising. This paper investigates the feasibility of combining FES with passive robotic support during virtual reality (VR) training tasks to improve upper limb function in people with multiple sclerosis (pwMS). The system assists patients in following a specified trajectory path, employing an advanced model-based paradigm termed iterative learning control (ILC) to adjust the FES to improve accuracy and maximise voluntary effort. Reaching tasks were repeated six times with ILC learning the optimum control action from previous attempts. A convenience sample of five pwMS was recruited from local MS societies, and the intervention comprised 18 one-hour training sessions over 10 weeks. The accuracy of tracking performance without FES and the amount of FES delivered during training were analyzed using regression analysis. Clinical functioning of the arm was documented before and after treatment with standard tests. Statistically significant results following training included: improved accuracy of tracking performance both when assisted and unassisted by FES; reduction in maximum amount of FES needed to assist tracking; and less impairment in the proximal arm that was trained. The system was well tolerated by all participants with no increase in muscle fatigue reported. This study confirms the feasibility of FES combined with passive robot assistance as a potentially effective intervention to improve arm movement and control in pwMS and provides the basis for a follow-up study.

Implementation of a hospital-based quality assessment program for rectal cancer.

PubMed

Hendren, Samantha; McKeown, Ellen; Morris, Arden M; Wong, Sandra L; Oerline, Mary; Poe, Lyndia; Campbell, Darrell A; Birkmeyer, Nancy J

2014-05-01

Quality improvement programs in Europe have had a markedly beneficial effect on the processes and outcomes of rectal cancer care. The quality of rectal cancer care in the United States is not as well understood, and scalable quality improvement programs have not been developed. The purpose of this article is to describe the implementation of a hospital-based quality assessment program for rectal cancer, targeting both community and academic hospitals. We recruited 10 hospitals from a surgical quality improvement organization. Nurse reviewers were trained to abstract rectal cancer data from hospital medical records, and abstracts were assessed for accuracy. We conducted two surveys to assess the training program and limitations of the data abstraction. We validated data completeness and accuracy by comparing hospital medical record and tumor registry data. Nine of 10 hospitals successfully performed abstractions with ≥ 90% accuracy. Experienced nurse reviewers were challenged by the technical details in operative and pathology reports. Although most variables had less than 10% missing data, outpatient testing information was lacking from some hospitals' inpatient records. This implementation project yielded a final quality assessment program consisting of 20 medical records variables and 11 tumor registry variables. An innovative program linking tumor registry data to quality-improvement data for rectal cancer quality assessment was successfully implemented in 10 hospitals. This data platform and training program can serve as a template for other organizations that are interested in assessing and improving the quality of rectal cancer care. Copyright © 2014 by American Society of Clinical Oncology.

Improving coding accuracy in an academic practice.

PubMed

Nguyen, Dana; O'Mara, Heather; Powell, Robert

2017-01-01

Practice management has become an increasingly important component of graduate medical education. This applies to every practice environment; private, academic, and military. One of the most critical aspects of practice management is documentation and coding for physician services, as they directly affect the financial success of any practice. Our quality improvement project aimed to implement a new and innovative method for teaching billing and coding in a longitudinal fashion in a family medicine residency. We hypothesized that implementation of a new teaching strategy would increase coding accuracy rates among residents and faculty. Design: single group, pretest-posttest. military family medicine residency clinic. Study populations: 7 faculty physicians and 18 resident physicians participated as learners in the project. Educational intervention: monthly structured coding learning sessions in the academic curriculum that involved learner-presented cases, small group case review, and large group discussion. overall coding accuracy (compliance) percentage and coding accuracy per year group for the subjects that were able to participate longitudinally. Statistical tests used: average coding accuracy for population; paired t test to assess improvement between 2 intervention periods, both aggregate and by year group. Overall coding accuracy rates remained stable over the course of time regardless of the modality of the educational intervention. A paired t test was conducted to compare coding accuracy rates at baseline (mean (M)=26.4%, SD=10%) to accuracy rates after all educational interventions were complete (M=26.8%, SD=12%); t24=-0.127, P=.90. Didactic teaching and small group discussion sessions did not improve overall coding accuracy in a residency practice. Future interventions could focus on educating providers at the individual level.

[A plane-based hand-eye calibration method for surgical robots].

PubMed

Zeng, Bowei; Meng, Fanle; Ding, Hui; Liu, Wenbo; Wu, Di; Wang, Guangzhi

2017-04-01

In order to calibrate the hand-eye transformation of the surgical robot and laser range finder (LRF), a calibration algorithm based on a planar template was designed. A mathematical model of the planar template had been given and the approach to address the equations had been derived. Aiming at the problems of the measurement error in a practical system, we proposed a new algorithm for selecting coplanar data. This algorithm can effectively eliminate considerable measurement error data to improve the calibration accuracy. Furthermore, three orthogonal planes were used to improve the calibration accuracy, in which a nonlinear optimization for hand-eye calibration was used. With the purpose of verifying the calibration precision, we used the LRF to measure some fixed points in different directions and a cuboid's surfaces. Experimental results indicated that the precision of a single planar template method was (1.37±0.24) mm, and that of the three orthogonal planes method was (0.37±0.05) mm. Moreover, the mean FRE of three-dimensional (3D) points was 0.24 mm and mean TRE was 0.26 mm. The maximum angle measurement error was 0.4 degree. Experimental results show that the method presented in this paper is effective with high accuracy and can meet the requirements of surgical robot precise location.

The short-term effects of trigger point therapy, stretching and medicine ball exercises on accuracy and back swing hip turn in elite, male golfers - A randomised controlled trial.

PubMed

Quinn, Samantha-Lynn; Olivier, Benita; Wood, Wendy-Ann

2016-11-01

This study aimed to compare the effect of myofascial trigger point therapy (MTPT) and stretching, MTPT and medicine ball exercises, and no intervention, on hip flexor length (HFL), golf swing biomechanics and performance in elite, male golfers. Single blind, randomised controlled trial with two experimental groups (stretch group: MTPT and stretching; and the ball group: MTPT, a single stretch and medicine ball exercises) and one control group (no intervention). Professional golf academy. One hundred, elite, male golfers aged 16-25 years. HFL, 3D biomechanical analysis of the golf swing, club head speed (CHS), smash ratio, accuracy and distance at baseline and after the interventions. Backswing hip turn (BSHT) improved in the ball group relative to the control group (p = 0.0248). Accuracy in the ball group and the stretch group improved relative to the control group (Fisher's exact = 0.016). Other performance parameters such as: smash ratio, distance and CHS were not compromised by either intervention. This study advocates the use of MTPT combined with medicine ball exercises over MTPT combined with stretching in the treatment of golfers with shortened hip flexors - even immediately preceding a tournament. Copyright © 2016 Elsevier Ltd. All rights reserved.

Can plantar soft tissue mechanics enhance prognosis of diabetic foot ulcer?

PubMed

Naemi, R; Chatzistergos, P; Suresh, S; Sundar, L; Chockalingam, N; Ramachandran, A

2017-04-01

To investigate if the assessment of the mechanical properties of plantar soft tissue can increase the accuracy of predicting Diabetic Foot Ulceration (DFU). 40 patients with diabetic neuropathy and no DFU were recruited. Commonly assessed clinical parameters along with plantar soft tissue stiffness and thickness were measured at baseline using ultrasound elastography technique. 7 patients developed foot ulceration during a 12months follow-up. Logistic regression was used to identify parameters that contribute to predicting the DFU incidence. The effect of using parameters related to the mechanical behaviour of plantar soft tissue on the specificity, sensitivity, prediction strength and accuracy of the predicting models for DFU was assessed. Patients with higher plantar soft tissue thickness and lower stiffness at the 1st Metatarsal head area showed an increased risk of DFU. Adding plantar soft tissue stiffness and thickness to the model improved its specificity (by 3%), sensitivity (by 14%), prediction accuracy (by 5%) and prognosis strength (by 1%). The model containing all predictors was able to effectively (χ 2 (8, N=40)=17.55, P<0.05) distinguish between the patients with and without DFU incidence. The mechanical properties of plantar soft tissue can be used to improve the predictability of DFU in moderate/high risk patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Accuracy improvement of multimodal measurement of speed of sound based on image processing

NASA Astrophysics Data System (ADS)

Nitta, Naotaka; Kaya, Akio; Misawa, Masaki; Hyodo, Koji; Numano, Tomokazu

2017-07-01

Since the speed of sound (SOS) reflects tissue characteristics and is expected as an evaluation index of elasticity and water content, the noninvasive measurement of SOS is eagerly anticipated. However, it is difficult to measure the SOS by using an ultrasound device alone. Therefore, we have presented a noninvasive measurement method of SOS using ultrasound (US) and magnetic resonance (MR) images. By this method, we determine the longitudinal SOS based on the thickness measurement using the MR image and the time of flight (TOF) measurement using the US image. The accuracy of SOS measurement is affected by the accuracy of image registration and the accuracy of thickness measurements in the MR and US images. In this study, we address the accuracy improvement in the latter thickness measurement, and present an image-processing-based method for improving the accuracy of thickness measurement. The method was investigated by using in vivo data obtained from a tissue-engineered cartilage implanted in the back of a rat, with an unclear boundary.

Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Mi; Xu, Wen; Li, Deren; Gong, Jianya; Pi, Yingdong

2017-12-01

The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs.

Lunar Reconnaissance Orbiter Orbit Determination Accuracy Analysis

NASA Technical Reports Server (NTRS)

Slojkowski, Steven E.

2014-01-01

Results from operational OD produced by the NASA Goddard Flight Dynamics Facility for the LRO nominal and extended mission are presented. During the LRO nominal mission, when LRO flew in a low circular orbit, orbit determination requirements were met nearly 100% of the time. When the extended mission began, LRO returned to a more elliptical frozen orbit where gravity and other modeling errors caused numerous violations of mission accuracy requirements. Prediction accuracy is particularly challenged during periods when LRO is in full-Sun. A series of improvements to LRO orbit determination are presented, including implementation of new lunar gravity models, improved spacecraft solar radiation pressure modeling using a dynamic multi-plate area model, a shorter orbit determination arc length, and a constrained plane method for estimation. The analysis presented in this paper shows that updated lunar gravity models improved accuracy in the frozen orbit, and a multiplate dynamic area model improves prediction accuracy during full-Sun orbit periods. Implementation of a 36-hour tracking data arc and plane constraints during edge-on orbit geometry also provide benefits. A comparison of the operational solutions to precision orbit determination solutions shows agreement on a 100- to 250-meter level in definitive accuracy.

Multiple-modality exercise and mind-motor training to improve mobility in older adults: A randomized controlled trial.

PubMed

Boa Sorte Silva, Narlon C; Gill, Dawn P; Gregory, Michael A; Bocti, John; Petrella, Robert J

2018-03-01

To investigate the effects of multiple-modality exercise with or without additional mind-motor training on mobility outcomes in older adults with subjective cognitive complaints. This was a 24-week randomized controlled trial with a 28-week no-contact follow-up. Community-dwelling older adults underwent a thrice -weekly, Multiple-Modality exercise and Mind-Motor (M4) training or Multiple-Modality (M2) exercise with an active control intervention (balance, range of motion and breathing exercises). Study outcomes included differences between groups at 24weeks and after the no-contact follow-up (i.e., 52weeks) in usual and dual-task (DT, i.e., serial sevens [S7] and phonemic verbal fluency [VF] tasks) gait velocity, step length and cycle time variability, as well as DT cognitive accuracy. 127 participants (mean age 67.5 [7.3] years, 71% women) were randomized to either M2 (n=64) or M4 (n=63) groups. Participants were assessed at baseline, intervention endpoint (24weeks), and study endpoint (52weeks). At 24weeks, the M2 group demonstrated greater improvements in usual gait velocity, usual step length, and DT gait velocity (VF) compared to the M4 group, and no between- or within-group changes in DT accuracy were observed. At 52weeks, the M2 group retained the gains in gait velocity and step length, whereas the M4 group demonstrated trends for improvement (p=0.052) in DT cognitive accuracy (VF). Our results suggest that additional mind-motor training was not effective to improve mobility outcomes. In fact, participants in the active control group experienced greater benefits as a result of the intervention. Copyright © 2017 Elsevier Inc. All rights reserved.

Classification of Parkinson's disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples.

PubMed

Zhang, He-Hua; Yang, Liuyang; Liu, Yuchuan; Wang, Pin; Yin, Jun; Li, Yongming; Qiu, Mingguo; Zhu, Xueru; Yan, Fang

2016-11-16

The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis methods applicable to Parkinsonism for building predictive tele-diagnosis and tele-monitoring models. One of the obstacles in optimizing classifications is to reduce noise within the collected speech samples, thus ensuring better classification accuracy and stability. While the currently used methods are effect, the ability to invoke instance selection has been seldomly examined. In this study, a PD classification algorithm was proposed and examined that combines a multi-edit-nearest-neighbor (MENN) algorithm and an ensemble learning algorithm. First, the MENN algorithm is applied for selecting optimal training speech samples iteratively, thereby obtaining samples with high separability. Next, an ensemble learning algorithm, random forest (RF) or decorrelated neural network ensembles (DNNE), is used to generate trained samples from the collected training samples. Lastly, the trained ensemble learning algorithms are applied to the test samples for PD classification. This proposed method was examined using a more recently deposited public datasets and compared against other currently used algorithms for validation. Experimental results showed that the proposed algorithm obtained the highest degree of improved classification accuracy (29.44%) compared with the other algorithm that was examined. Furthermore, the MENN algorithm alone was found to improve classification accuracy by as much as 45.72%. Moreover, the proposed algorithm was found to exhibit a higher stability, particularly when combining the MENN and RF algorithms. This study showed that the proposed method could improve PD classification when using speech data and can be applied to future studies seeking to improve PD classification methods.

Memory color of natural familiar objects: effects of surface texture and 3-D shape.

PubMed

Vurro, Milena; Ling, Yazhu; Hurlbert, Anya C

2013-06-28

Natural objects typically possess characteristic contours, chromatic surface textures, and three-dimensional shapes. These diagnostic features aid object recognition, as does memory color, the color most associated in memory with a particular object. Here we aim to determine whether polychromatic surface texture, 3-D shape, and contour diagnosticity improve memory color for familiar objects, separately and in combination. We use solid three-dimensional familiar objects rendered with their natural texture, which participants adjust in real time to match their memory color for the object. We analyze mean, accuracy, and precision of the memory color settings relative to the natural color of the objects under the same conditions. We find that in all conditions, memory colors deviate slightly but significantly in the same direction from the natural color. Surface polychromaticity, shape diagnosticity, and three dimensionality each improve memory color accuracy, relative to uniformly colored, generic, or two-dimensional shapes, respectively. Shape diagnosticity improves the precision of memory color also, and there is a trend for polychromaticity to do so as well. Differently from other studies, we find that the object contour alone also improves memory color. Thus, enhancing the naturalness of the stimulus, in terms of either surface or shape properties, enhances the accuracy and precision of memory color. The results support the hypothesis that memory color representations are polychromatic and are synergistically linked with diagnostic shape representations.

A GIS Tool for evaluating and improving NEXRAD and its application in distributed hydrologic modeling

NASA Astrophysics Data System (ADS)

Zhang, X.; Srinivasan, R.

2008-12-01

In this study, a user friendly GIS tool was developed for evaluating and improving NEXRAD using raingauge data. This GIS tool can automatically read in raingauge and NEXRAD data, evaluate the accuracy of NEXRAD for each time unit, implement several geostatistical methods to improve the accuracy of NEXRAD through raingauge data, and output spatial precipitation map for distributed hydrologic model. The geostatistical methods incorporated in this tool include Simple Kriging with varying local means, Kriging with External Drift, Regression Kriging, Co-Kriging, and a new geostatistical method that was newly developed by Li et al. (2008). This tool was applied in two test watersheds at hourly and daily temporal scale. The preliminary cross-validation results show that incorporating raingauge data to calibrate NEXRAD can pronouncedly change the spatial pattern of NEXRAD and improve its accuracy. Using different geostatistical methods, the GIS tool was applied to produce long term precipitation input for a distributed hydrologic model - Soil and Water Assessment Tool (SWAT). Animated video was generated to vividly illustrate the effect of using different precipitation input data on distributed hydrologic modeling. Currently, this GIS tool is developed as an extension of SWAT, which is used as water quantity and quality modeling tool by USDA and EPA. The flexible module based design of this tool also makes it easy to be adapted for other hydrologic models for hydrological modeling and water resources management.

Forest tree species discrimination in western Himalaya using EO-1 Hyperion

NASA Astrophysics Data System (ADS)

George, Rajee; Padalia, Hitendra; Kushwaha, S. P. S.

2014-05-01

The information acquired in the narrow bands of hyperspectral remote sensing data has potential to capture plant species spectral variability, thereby improving forest tree species mapping. This study assessed the utility of spaceborne EO-1 Hyperion data in discrimination and classification of broadleaved evergreen and conifer forest tree species in western Himalaya. The pre-processing of 242 bands of Hyperion data resulted into 160 noise-free and vertical stripe corrected reflectance bands. Of these, 29 bands were selected through step-wise exclusion of bands (Wilk's Lambda). Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) algorithms were applied to the selected bands to assess their effectiveness in classification. SVM was also applied to broadband data (Landsat TM) to compare the variation in classification accuracy. All commonly occurring six gregarious tree species, viz., white oak, brown oak, chir pine, blue pine, cedar and fir in western Himalaya could be effectively discriminated. SVM produced a better species classification (overall accuracy 82.27%, kappa statistic 0.79) than SAM (overall accuracy 74.68%, kappa statistic 0.70). It was noticed that classification accuracy achieved with Hyperion bands was significantly higher than Landsat TM bands (overall accuracy 69.62%, kappa statistic 0.65). Study demonstrated the potential utility of narrow spectral bands of Hyperion data in discriminating tree species in a hilly terrain.

High-precision radiometric tracking for planetary approach and encounter in the inner solar system

NASA Technical Reports Server (NTRS)

Christensen, C. S.; Thurman, S. W.; Davidson, J. M.; Finger, M. H.; Folkner, W. M.

1989-01-01

The benefits of improved radiometric tracking data have been studied for planetary approach within the inner Solar System using the Mars Rover Sample Return trajectory as a model. It was found that the benefit of improved data to approach and encounter navigation was highly dependent on the a priori uncertainties assumed for several non-estimated parameters, including those for frame-tie, Earth orientation, troposphere delay, and station locations. With these errors at their current levels, navigational performance was found to be insensitive to enhancements in data accuracy. However, when expected improvements in these errors are modeled, performance with current-accuracy data significantly improves, with substantial further improvements possible with enhancements in data accuracy.

Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

PubMed Central

Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

2017-01-01

Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

IMPROVING THE ACCURACY OF HISTORIC SATELLITE IMAGE CLASSIFICATION BY COMBINING LOW-RESOLUTION MULTISPECTRAL DATA WITH HIGH-RESOLUTION PANCHROMATIC DATA

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

Getman, Daniel J

2008-01-01

Many attempts to observe changes in terrestrial systems over time would be significantly enhanced if it were possible to improve the accuracy of classifications of low-resolution historic satellite data. In an effort to examine improving the accuracy of historic satellite image classification by combining satellite and air photo data, two experiments were undertaken in which low-resolution multispectral data and high-resolution panchromatic data were combined and then classified using the ECHO spectral-spatial image classification algorithm and the Maximum Likelihood technique. The multispectral data consisted of 6 multispectral channels (30-meter pixel resolution) from Landsat 7. These data were augmented with panchromatic datamore » (15m pixel resolution) from Landsat 7 in the first experiment, and with a mosaic of digital aerial photography (1m pixel resolution) in the second. The addition of the Landsat 7 panchromatic data provided a significant improvement in the accuracy of classifications made using the ECHO algorithm. Although the inclusion of aerial photography provided an improvement in accuracy, this improvement was only statistically significant at a 40-60% level. These results suggest that once error levels associated with combining aerial photography and multispectral satellite data are reduced, this approach has the potential to significantly enhance the precision and accuracy of classifications made using historic remotely sensed data, as a way to extend the time range of efforts to track temporal changes in terrestrial systems.« less

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

USGS Publications Warehouse

Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.

2007-01-01

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

PubMed Central

ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. PMID:18642470

Effect of tropospheric models on derived precipitable water vapor over Southeast Asia

NASA Astrophysics Data System (ADS)

Rahimi, Zhoobin; Mohd Shafri, Helmi Zulhaidi; Othman, Faridah; Norman, Masayu

2017-05-01

An interesting subject in the field of GPS technology is estimating variation of precipitable water vapor (PWV). This estimation can be used as a data source to assess and monitor rapid changes in meteorological conditions. So far, numerous GPS stations are distributed across the world and the number of GPS networks is increasing. Despite these developments, a challenging aspect of estimating PWV through GPS networks is the need of tropospheric parameters such as temperature, pressure, and relative humidity (Liu et al., 2015). To estimate the tropospheric parameters, global pressure temperature (GPT) model developed by Boehm et al. (2007) is widely used in geodetic analysis for GPS observations. To improve the accuracy, Lagler et al. (2013) introduced GPT2 model by adding annual and semi-annual variation effects to GPT model. Furthermore, Boehm et al. (2015) proposed the GPT2 wet (GPT2w) model which uses water vapor pressure to improve the calculations. The global accuracy of GPT2 and GPT2w models has been evaluated by previous researches (Fund et al., 2011; Munekane and Boehm, 2010); however, investigations to assess the accuracy of global tropospheric models in tropical regions such as Southeast Asia is not sufficient. This study tests and examines the accuracy of GPT2w as one of the most recent versions of tropospheric models (Boehm et al., 2015). We developed a new regional model called Malaysian Pressure Temperature (MPT) model, and compared this model with GPT2w model. The compared results at one international GNSS service (IGS) station located in the south of Peninsula Malaysia shows that MPT model has a better performance than GPT2w model to produce PWV during monsoon season. According to the results, MPT has improved the accuracy of estimated pressure and temperature by 30% and 10%, respectively, in comparison with GPT2w model. These results indicate that MPT model can be a good alternative tool in the absence of meteorological sensors at GPS stations in Peninsula Malaysia. Therefore, for GPS-based studies, we recommend MPT model to be used as a complementary tool for the Malaysia Real-Time Kinematic Network to develop a real-time PWV monitoring system.

Swing arm profilometer: high accuracy testing for large reaction-bonded silicon carbide optics with a capacitive probe

NASA Astrophysics Data System (ADS)

Xiong, Ling; Luo, Xiao; Hu, Hai-xiang; Zhang, Zhi-yu; Zhang, Feng; Zheng, Li-gong; Zhang, Xue-jun

2017-08-01

A feasible way to improve the manufacturing efficiency of large reaction-bonded silicon carbide optics is to increase the processing accuracy in the ground stage before polishing, which requires high accuracy metrology. A swing arm profilometer (SAP) has been used to measure large optics during the ground stage. A method has been developed for improving the measurement accuracy of SAP using a capacitive probe and implementing calibrations. The experimental result compared with the interferometer test shows the accuracy of 0.068 μm in root-mean-square (RMS) and maps in 37 low-order Zernike terms show accuracy of 0.048 μm RMS, which shows a powerful capability to provide a major input in high-precision grinding.

STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies.

PubMed

Bossuyt, Patrick M; Reitsma, Johannes B; Bruns, David E; Gatsonis, Constantine A; Glasziou, Paul P; Irwig, Les; Lijmer, Jeroen G; Moher, David; Rennie, Drummond; de Vet, Henrica C W; Kressel, Herbert Y; Rifai, Nader; Golub, Robert M; Altman, Douglas G; Hooft, Lotty; Korevaar, Daniël A; Cohen, Jérémie F

2015-12-01

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

The space station: Human factors and productivity

NASA Technical Reports Server (NTRS)

Gillan, D. J.; Burns, M. J.; Nicodemus, C. L.; Smith, R. L.

1986-01-01

Human factor researchers and engineers are making inputs into the early stages of the design of the Space Station to improve both the quality of life and work on-orbit. Effective integration of the human factors information related to various Intravehicular Activity (IVA), Extravehicular Activity (EVA), and teletobotics systems during the Space Station design will result in increased productivity, increased flexibility of the Space Stations systems, lower cost of operations, improved reliability, and increased safety for the crew onboard the Space Station. The major features of productivity examined include the cognitive and physical effort involved in work, the accuracy of worker output and ability to maintain performance at a high level of accuracy, the speed and temporal efficiency with which a worker performs, crewmember satisfaction with their work environment, and the relation between performance and cost.

FMRI Is a Valid Noninvasive Alternative to Wada Testing

PubMed Central

Binder, Jeffrey R.

2010-01-01

Partial removal of the anterior temporal lobe (ATL) is a highly effective surgical treatment for intractable temporal lobe epilepsy, yet roughly half of patients who undergo left ATL resection show decline in language or verbal memory function postoperatively. Two recent studies demonstrate that preoperative fMRI can predict postoperative naming and verbal memory changes in such patients. Most importantly, fMRI significantly improves the accuracy of prediction relative to other noninvasive measures used alone. Addition of language and memory lateralization data from the intracarotid amobarbital (Wada) test did not improve prediction accuracy in these studies. Thus, fMRI provides patients and practitioners with a safe, non-invasive, and well-validated tool for making better-informed decisions regarding elective surgery based on a quantitative assessment of cognitive risk. PMID:20850386

Intraoperative perception and estimates on extent of resection during awake glioma surgery: overcoming the learning curve.

PubMed

Lau, Darryl; Hervey-Jumper, Shawn L; Han, Seunggu J; Berger, Mitchel S

2018-05-01

OBJECTIVE There is ample evidence that extent of resection (EOR) is associated with improved outcomes for glioma surgery. However, it is often difficult to accurately estimate EOR intraoperatively, and surgeon accuracy has yet to be reviewed. In this study, the authors quantitatively assessed the accuracy of intraoperative perception of EOR during awake craniotomy for tumor resection. METHODS A single-surgeon experience of performing awake craniotomies for tumor resection over a 17-year period was examined. Retrospective review of operative reports for quantitative estimation of EOR was recorded. Definitive EOR was based on postoperative MRI. Analysis of accuracy of EOR estimation was examined both as a general outcome (gross-total resection [GTR] or subtotal resection [STR]), and quantitatively (5% within EOR on postoperative MRI). Patient demographics, tumor characteristics, and surgeon experience were examined. The effects of accuracy on motor and language outcomes were assessed. RESULTS A total of 451 patients were included in the study. Overall accuracy of intraoperative perception of whether GTR or STR was achieved was 79.6%, and overall accuracy of quantitative perception of resection (within 5% of postoperative MRI) was 81.4%. There was a significant difference (p = 0.049) in accuracy for gross perception over the 17-year period, with improvement over the later years: 1997-2000 (72.6%), 2001-2004 (78.5%), 2005-2008 (80.7%), and 2009-2013 (84.4%). Similarly, there was a significant improvement (p = 0.015) in accuracy of quantitative perception of EOR over the 17-year period: 1997-2000 (72.2%), 2001-2004 (69.8%), 2005-2008 (84.8%), and 2009-2013 (93.4%). This improvement in accuracy is demonstrated by the significantly higher odds of correctly estimating quantitative EOR in the later years of the series on multivariate logistic regression. Insular tumors were associated with the highest accuracy of gross perception (89.3%; p = 0.034), but lowest accuracy of quantitative perception (61.1% correct; p < 0.001) compared with tumors in other locations. Even after adjusting for surgeon experience, this particular trend for insular tumors remained true. The absence of 1p19q co-deletion was associated with higher quantitative perception accuracy (96.9% vs 81.5%; p = 0.051). Tumor grade, recurrence, diagnosis, and isocitrate dehydrogenase-1 (IDH-1) status were not associated with accurate perception of EOR. Overall, new neurological deficits occurred in 8.4% of cases, and 42.1% of those new neurological deficits persisted after the 3-month follow-up. Correct quantitative perception was associated with lower postoperative motor deficits (2.4%) compared with incorrect perceptions (8.0%; p = 0.029). There were no detectable differences in language outcomes based on perception of EOR. CONCLUSIONS The findings from this study suggest that there is a learning curve associated with the ability to accurately assess intraoperative EOR during glioma surgery, and it may take more than a decade to be truly proficient. Understanding the factors associated with this ability to accurately assess EOR will provide safer surgeries while maximizing tumor resection.

Generating Keywords Improves Metacomprehension and Self-Regulation in Elementary and Middle School Children

ERIC Educational Resources Information Center

de Bruin, Anique B. H.; Thiede, Keith W.; Camp, Gino; Redford, Joshua

2011-01-01

The ability to monitor understanding of texts, usually referred to as metacomprehension accuracy, is typically quite poor in adult learners; however, recently interventions have been developed to improve accuracy. In two experiments, we evaluated whether generating delayed keywords prior to judging comprehension improved metacomprehension accuracy…

Electro-encephalogram based brain-computer interface: improved performance by mental practice and concentration skills.

PubMed

Mahmoudi, Babak; Erfanian, Abbas

2006-11-01

Mental imagination is the essential part of the most EEG-based communication systems. Thus, the quality of mental rehearsal, the degree of imagined effort, and mind controllability should have a major effect on the performance of electro-encephalogram (EEG) based brain-computer interface (BCI). It is now well established that mental practice using motor imagery improves motor skills. The effects of mental practice on motor skill learning are the result of practice on central motor programming. According to this view, it seems logical that mental practice should modify the neuronal activity in the primary sensorimotor areas and consequently change the performance of EEG-based BCI. For developing a practical BCI system, recognizing the resting state with eyes opened and the imagined voluntary movement is important. For this purpose, the mind should be able to focus on a single goal for a period of time, without deviation to another context. In this work, we are going to examine the role of mental practice and concentration skills on the EEG control during imaginative hand movements. The results show that the mental practice and concentration can generally improve the classification accuracy of the EEG patterns. It is found that mental training has a significant effect on the classification accuracy over the primary motor cortex and frontal area.

Simple and Effective Algorithms: Computer-Adaptive Testing.

ERIC Educational Resources Information Center

Linacre, John Michael

Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…

Understanding key tradeoffs for cost-effective deployment of surveillance to support advanced traveler information systems (ATIS)

DOT National Transportation Integrated Search

2004-04-01

This paper presents the authors' understanding of a key tradeoff in ATIS investment planning: investment in expanding surveillance coverage to additional miles of roadway vs. improving the accuracy of the information provided on roadways already cove...

Improved Forecasting Methods for Naval Manpower Studies

DTIC Science & Technology

2015-03-25

Using monthly data is likely to improve the overall fit of the models and the accuracy of the BP test . A measure of unemployment to control for...measure of the relative goodness of fit of a statistical model. It is grounded in the concept of information entropy, in effect, offering a relative...the Kullback – Leibler divergence, DKL(f,g1); similarly, the information lost from using g2 to

[Study on Differential Optical Absorption Spectroscopy Data Processing Based on Chirp-Z Transformation].

PubMed

Zheng, Hai-ming; Li, Guang-jie; Wu, Hao

2015-06-01

Differential optical absorption spectroscopy (DOAS) is a commonly used atmospheric pollution monitoring method. Denoising of monitoring spectral data will improve the inversion accuracy. Fourier transform filtering method is effectively capable of filtering out the noise in the spectral data. But the algorithm itself can introduce errors. In this paper, a chirp-z transform method is put forward. By means of the local thinning of Fourier transform spectrum, it can retain the denoising effect of Fourier transform and compensate the error of the algorithm, which will further improve the inversion accuracy. The paper study on the concentration retrieving of SO2 and NO2. The results show that simple division causes bigger error and is not very stable. Chirp-z transform is proved to be more accurate than Fourier transform. Results of the frequency spectrum analysis show that Fourier transform cannot solve the distortion and weakening problems of characteristic absorption spectrum. Chirp-z transform shows ability in fine refactoring of specific frequency spectrum.

Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data.

PubMed

Won, Sungho; Choi, Hosik; Park, Suyeon; Lee, Juyoung; Park, Changyi; Kwon, Sunghoon

2015-01-01

Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called "large P and small N" problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO) and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.

Towards online iris and periocular recognition under relaxed imaging constraints.

PubMed

Tan, Chun-Wei; Kumar, Ajay

2013-10-01

Online iris recognition using distantly acquired images in a less imaging constrained environment requires the development of a efficient iris segmentation approach and recognition strategy that can exploit multiple features available for the potential identification. This paper presents an effective solution toward addressing such a problem. The developed iris segmentation approach exploits a random walker algorithm to efficiently estimate coarsely segmented iris images. These coarsely segmented iris images are postprocessed using a sequence of operations that can effectively improve the segmentation accuracy. The robustness of the proposed iris segmentation approach is ascertained by providing comparison with other state-of-the-art algorithms using publicly available UBIRIS.v2, FRGC, and CASIA.v4-distance databases. Our experimental results achieve improvement of 9.5%, 4.3%, and 25.7% in the average segmentation accuracy, respectively, for the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with most competing approaches. We also exploit the simultaneously extracted periocular features to achieve significant performance improvement. The joint segmentation and combination strategy suggest promising results and achieve average improvement of 132.3%, 7.45%, and 17.5% in the recognition performance, respectively, from the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with the related competing approaches.

Identification of facilitators and barriers to residents' use of a clinical reasoning tool.

PubMed

DiNardo, Deborah; Tilstra, Sarah; McNeil, Melissa; Follansbee, William; Zimmer, Shanta; Farris, Coreen; Barnato, Amber E

2018-03-28

While there is some experimental evidence to support the use of cognitive forcing strategies to reduce diagnostic error in residents, the potential usability of such strategies in the clinical setting has not been explored. We sought to test the effect of a clinical reasoning tool on diagnostic accuracy and to obtain feedback on its usability and acceptability. We conducted a randomized behavioral experiment testing the effect of this tool on diagnostic accuracy on written cases among post-graduate 3 (PGY-3) residents at a single internal medical residency program in 2014. Residents completed written clinical cases in a proctored setting with and without prompts to use the tool. The tool encouraged reflection on concordant and discordant aspects of each case. We used random effects regression to assess the effect of the tool on diagnostic accuracy of the independent case sets, controlling for case complexity. We then conducted audiotaped structured focus group debriefing sessions and reviewed the tapes for facilitators and barriers to use of the tool. Of 51 eligible PGY-3 residents, 34 (67%) participated in the study. The average diagnostic accuracy increased from 52% to 60% with the tool, a difference that just met the test for statistical significance in adjusted analyses (p=0.05). Residents reported that the tool was generally acceptable and understandable but did not recognize its utility for use with simple cases, suggesting the presence of overconfidence bias. A clinical reasoning tool improved residents' diagnostic accuracy on written cases. Overconfidence bias is a potential barrier to its use in the clinical setting.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Fourier transform profilometry (FTP) using an innovative band-pass filter for accurate 3-D surface reconstruction

NASA Astrophysics Data System (ADS)

Chen, Liang-Chia; Ho, Hsuan-Wei; Nguyen, Xuan-Loc

2010-02-01

This article presents a novel band-pass filter for Fourier transform profilometry (FTP) for accurate 3-D surface reconstruction. FTP can be employed to obtain 3-D surface profiles by one-shot images to achieve high-speed measurement. However, its measurement accuracy has been significantly influenced by the spectrum filtering process required to extract the phase information representing various surface heights. Using the commonly applied 2-D Hanning filter, the measurement errors could be up to 5-10% of the overall measuring height and it is unacceptable to various industrial application. To resolve this issue, the article proposes an elliptical band-pass filter for extracting the spectral region possessing essential phase information for reconstructing accurate 3-D surface profiles. The elliptical band-pass filter was developed and optimized to reconstruct 3-D surface models with improved measurement accuracy. Some experimental results verify that the accuracy can be effectively enhanced by using the elliptical filter. The accuracy improvement of 44.1% and 30.4% can be achieved in 3-D and sphericity measurement, respectively, when the elliptical filter replaces the traditional filter as the band-pass filtering method. Employing the developed method, the maximum measured error can be kept within 3.3% of the overall measuring range.

Accuracy and time requirements of a bar-code inventory system for medical supplies.

PubMed

Hanson, L B; Weinswig, M H; De Muth, J E

1988-02-01

The effects of implementing a bar-code system for issuing medical supplies to nursing units at a university teaching hospital were evaluated. Data on the time required to issue medical supplies to three nursing units at a 480-bed, tertiary-care teaching hospital were collected (1) before the bar-code system was implemented (i.e., when the manual system was in use), (2) one month after implementation, and (3) four months after implementation. At the same times, the accuracy of the central supply perpetual inventory was monitored using 15 selected items. One-way analysis of variance tests were done to determine any significant differences between the bar-code and manual systems. Using the bar-code system took longer than using the manual system because of a significant difference in the time required for order entry into the computer. Multiple-use requirements of the central supply computer system made entering bar-code data a much slower process. There was, however, a significant improvement in the accuracy of the perpetual inventory. Using the bar-code system for issuing medical supplies to the nursing units takes longer than using the manual system. However, the accuracy of the perpetual inventory was significantly improved with the implementation of the bar-code system.

Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks.

PubMed

Bergamini, Elena; Ligorio, Gabriele; Summa, Aurora; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2014-10-09

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

Improved computer-aided detection of small polyps in CT colonography using interpolation for curvature estimationa

PubMed Central

Liu, Jiamin; Kabadi, Suraj; Van Uitert, Robert; Petrick, Nicholas; Deriche, Rachid; Summers, Ronald M.

2011-01-01

Purpose: Surface curvatures are important geometric features for the computer-aided analysis and detection of polyps in CT colonography (CTC). However, the general kernel approach for curvature computation can yield erroneous results for small polyps and for polyps that lie on haustral folds. Those erroneous curvatures will reduce the performance of polyp detection. This paper presents an analysis of interpolation’s effect on curvature estimation for thin structures and its application on computer-aided detection of small polyps in CTC. Methods: The authors demonstrated that a simple technique, image interpolation, can improve the accuracy of curvature estimation for thin structures and thus significantly improve the sensitivity of small polyp detection in CTC. Results: Our experiments showed that the merits of interpolating included more accurate curvature values for simulated data, and isolation of polyps near folds for clinical data. After testing on a large clinical data set, it was observed that sensitivities with linear, quadratic B-spline and cubic B-spline interpolations significantly improved the sensitivity for small polyp detection. Conclusions: The image interpolation can improve the accuracy of curvature estimation for thin structures and thus improve the computer-aided detection of small polyps in CTC. PMID:21859029

Age-related differences in strategy knowledge updating: blocked testing produces greater improvements in metacognitive accuracy for younger than older adults.

PubMed

Price, Jodi; Hertzog, Christopher; Dunlosky, John

2008-09-01

Age-related differences in updating knowledge about strategy effectiveness after task experience have not been consistently found, perhaps because the magnitude of observed knowledge updating has been rather meager for both age groups. We examined whether creating homogeneous blocks of recall tests based on two strategies used at encoding (imagery and repetition) would enhance people's learning about strategy effects on recall. Younger and older adults demonstrated greater knowledge updating (as measured by questionnaire ratings of strategy effectiveness and by global judgments of performance) with blocked (versus random) testing. The benefit of blocked testing for absolute accuracy of global predictions was smaller for older than younger adults. However, individual differences in correlations of strategy effectiveness ratings and postdictions showed similar upgrades for both age groups. Older adults learn about imagery's superior effectiveness but do not accurately estimate the magnitude of its benefit, even after blocked testing.

Global Optimization Ensemble Model for Classification Methods

PubMed Central

Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

2014-01-01

Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

Limited-angle effect compensation for respiratory binned cardiac SPECT

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

Qi, Wenyuan; Yang, Yongyi, E-mail: yy@ece.iit.edu; Wernick, Miles N.

Purpose: In cardiac single photon emission computed tomography (SPECT), respiratory-binned study is used to combat the motion blur associated with respiratory motion. However, owing to the variability in respiratory patterns during data acquisition, the acquired data counts can vary significantly both among respiratory bins and among projection angles within individual bins. If not properly accounted for, such variation could lead to artifacts similar to limited-angle effect in image reconstruction. In this work, the authors aim to investigate several reconstruction strategies for compensating the limited-angle effect in respiratory binned data for the purpose of reducing the image artifacts. Methods: The authorsmore » first consider a model based correction approach, in which the variation in acquisition time is directly incorporated into the imaging model, such that the data statistics are accurately described among both the projection angles and respiratory bins. Afterward, the authors consider an approximation approach, in which the acquired data are rescaled to accommodate the variation in acquisition time among different projection angles while the imaging model is kept unchanged. In addition, the authors also consider the use of a smoothing prior in reconstruction for suppressing the artifacts associated with limited-angle effect. In our evaluation study, the authors first used Monte Carlo simulated imaging with 4D NCAT phantom wherein the ground truth is known for quantitative comparison. The authors evaluated the accuracy of the reconstructed myocardium using a number of metrics, including regional and overall accuracy of the myocardium, uniformity and spatial resolution of the left ventricle (LV) wall, and detectability of perfusion defect using a channelized Hotelling observer. As a preliminary demonstration, the authors also tested the different approaches on five sets of clinical acquisitions. Results: The quantitative evaluation results show that the three compensation methods could all, but to different extents, reduce the reconstruction artifacts over no compensation. In particular, the model based approach reduced the mean-squared-error of the reconstructed myocardium by as much as 40%. Compared to the approach of data rescaling, the model based approach further improved both the overall and regional accuracy of the myocardium; it also further improved the lesion detectability and the uniformity of the LV wall. When ML reconstruction was used, the model based approach was notably more effective for improving the LV wall; when MAP reconstruction was used, the smoothing prior could reduce the noise level and artifacts with little or no increase in bias, but at the cost of a slight resolution loss of the LV wall. The improvements in image quality by the different compensation methods were also observed in the clinical acquisitions. Conclusions: Compensating for the uneven distribution of acquisition time among both projection angles and respiratory bins can effectively reduce the limited-angle artifacts in respiratory-binned cardiac SPECT reconstruction. Direct incorporation of the time variation into the imaging model together with a smoothing prior in reconstruction can lead to the most improvement in the accuracy of the reconstructed myocardium.« less

Finite element analysis of transonic flows in cascades: Importance of computational grids in improving accuracy and convergence

NASA Technical Reports Server (NTRS)

Ecer, A.; Akay, H. U.

1981-01-01

The finite element method is applied for the solution of transonic potential flows through a cascade of airfoils. Convergence characteristics of the solution scheme are discussed. Accuracy of the numerical solutions is investigated for various flow regions in the transonic flow configuration. The design of an efficient finite element computational grid is discussed for improving accuracy and convergence.

Accuracy requirements and uncertainties in radiotherapy: a report of the International Atomic Energy Agency.

PubMed

van der Merwe, Debbie; Van Dyk, Jacob; Healy, Brendan; Zubizarreta, Eduardo; Izewska, Joanna; Mijnheer, Ben; Meghzifene, Ahmed

2017-01-01

Radiotherapy technology continues to advance and the expectation of improved outcomes requires greater accuracy in various radiotherapy steps. Different factors affect the overall accuracy of dose delivery. Institutional comprehensive quality assurance (QA) programs should ensure that uncertainties are maintained at acceptable levels. The International Atomic Energy Agency has recently developed a report summarizing the accuracy achievable and the suggested action levels, for each step in the radiotherapy process. Overview of the report: The report seeks to promote awareness and encourage quantification of uncertainties in order to promote safer and more effective patient treatments. The radiotherapy process and the radiobiological and clinical frameworks that define the need for accuracy are depicted. Factors that influence uncertainty are described for a range of techniques, technologies and systems. Methodologies for determining and combining uncertainties are presented, and strategies for reducing uncertainties through QA programs are suggested. The role of quality audits in providing international benchmarking of achievable accuracy and realistic action levels is also discussed. The report concludes with nine general recommendations: (1) Radiotherapy should be applied as accurately as reasonably achievable, technical and biological factors being taken into account. (2) For consistency in prescribing, reporting and recording, recommendations of the International Commission on Radiation Units and Measurements should be implemented. (3) Each institution should determine uncertainties for their treatment procedures. Sample data are tabulated for typical clinical scenarios with estimates of the levels of accuracy that are practically achievable and suggested action levels. (4) Independent dosimetry audits should be performed regularly. (5) Comprehensive quality assurance programs should be in place. (6) Professional staff should be appropriately educated and adequate staffing levels should be maintained. (7) For reporting purposes, uncertainties should be presented. (8) Manufacturers should provide training on all equipment. (9) Research should aid in improving the accuracy of radiotherapy. Some example research projects are suggested.

Improved fibrosis staging by elastometry and blood test in chronic hepatitis C.

PubMed

Calès, Paul; Boursier, Jérôme; Ducancelle, Alexandra; Oberti, Frédéric; Hubert, Isabelle; Hunault, Gilles; de Lédinghen, Victor; Zarski, Jean-Pierre; Salmon, Dominique; Lunel, Françoise

2014-07-01

Our main objective was to improve non-invasive fibrosis staging accuracy by resolving the limits of previous methods via new test combinations. Our secondary objectives were to improve staging precision, by developing a detailed fibrosis classification, and reliability (personalized accuracy) determination. All patients (729) included in the derivation population had chronic hepatitis C, liver biopsy, 6 blood tests and Fibroscan. Validation populations included 1584 patients. The most accurate combination was provided by using most markers of FibroMeter and Fibroscan results targeted for significant fibrosis, i.e. 'E-FibroMeter'. Its classification accuracy (91.7%) and precision (assessed by F difference with Metavir: 0.62 ± 0.57) were better than those of FibroMeter (84.1%, P < 0.001; 0.72 ± 0.57, P < 0.001), Fibroscan (88.2%, P = 0.011; 0.68 ± 0.57, P = 0.020), and a previous CSF-SF classification of FibroMeter + Fibroscan (86.7%, P < 0.001; 0.65 ± 0.57, P = 0.044). The accuracy for fibrosis absence (F0) was increased, e.g. from 16.0% with Fibroscan to 75.0% with E-FibroMeter (P < 0.001). Cirrhosis sensitivity was improved, e.g. E-FibroMeter: 92.7% vs. Fibroscan: 83.3%, P = 0.004. The combination improved reliability by deleting unreliable results (accuracy <50%) observed with a single test (1.2% of patients) and increasing optimal reliability (accuracy ≥85%) from 80.4% of patients with Fibroscan (accuracy: 90.9%) to 94.2% of patients with E-FibroMeter (accuracy: 92.9%), P < 0.001. The patient rate with 100% predictive values for cirrhosis by the best combination was twice (36.2%) that of the best single test (FibroMeter: 16.2%, P < 0.001). The new test combination increased: accuracy, globally and especially in patients without fibrosis, staging precision, cirrhosis prediction, and even reliability, thus offering improved fibrosis staging. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

[Design and accuracy analysis of upper slicing system of MSCT].

PubMed

Jiang, Rongjian

2013-05-01

The upper slicing system is the main components of the optical system in MSCT. This paper focuses on the design of upper slicing system and its accuracy analysis to improve the accuracy of imaging. The error of slice thickness and ray center by bearings, screw and control system were analyzed and tested. In fact, the accumulated error measured is less than 1 microm, absolute error measured is less than 10 microm. Improving the accuracy of the upper slicing system contributes to the appropriate treatment methods and success rate of treatment.

Method to improve accuracy of positioning object by eLoran system with applying standard Kalman filter

NASA Astrophysics Data System (ADS)

Grunin, A. P.; Kalinov, G. A.; Bolokhovtsev, A. V.; Sai, S. V.

2018-05-01

This article reports on a novel method to improve the accuracy of positioning an object by a low frequency hyperbolic radio navigation system like an eLoran. This method is based on the application of the standard Kalman filter. Investigations of an affection of the filter parameters and the type of the movement on accuracy of the vehicle position estimation are carried out. Evaluation of the method accuracy was investigated by separating data from the semi-empirical movement model to different types of movements.

Toward a hybrid brain-computer interface based on imagined movement and visual attention

NASA Astrophysics Data System (ADS)

Allison, B. Z.; Brunner, C.; Kaiser, V.; Müller-Putz, G. R.; Neuper, C.; Pfurtscheller, G.

2010-04-01

Brain-computer interface (BCI) systems do not work for all users. This article introduces a novel combination of tasks that could inspire BCI systems that are more accurate than conventional BCIs, especially for users who cannot attain accuracy adequate for effective communication. Subjects performed tasks typically used in two BCI approaches, namely event-related desynchronization (ERD) and steady state visual evoked potential (SSVEP), both individually and in a 'hybrid' condition that combines both tasks. Electroencephalographic (EEG) data were recorded across three conditions. Subjects imagined moving the left or right hand (ERD), focused on one of the two oscillating visual stimuli (SSVEP), and then simultaneously performed both tasks. Accuracy and subjective measures were assessed. Offline analyses suggested that half of the subjects did not produce brain patterns that could be accurately discriminated in response to at least one of the two tasks. If these subjects produced comparable EEG patterns when trying to use a BCI, these subjects would not be able to communicate effectively because the BCI would make too many errors. Results also showed that switching to a different task used in BCIs could improve accuracy in some of these users. Switching to a hybrid approach eliminated this problem completely, and subjects generally did not consider the hybrid condition more difficult. Results validate this hybrid approach and suggest that subjects who cannot use a BCI should consider switching to a different BCI approach, especially a hybrid BCI. Subjects proficient with both approaches might combine them to increase information throughput by improving accuracy, reducing selection time, and/or increasing the number of possible commands.

Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region

PubMed Central

Zhou, Tao; Pan, Jianjun; Zhang, Peiyu; Wei, Shanbao; Han, Tao

2017-01-01

Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure–up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data. PMID:28587066

Improved shallow trench isolation and gate process control using scatterometry based metrology

NASA Astrophysics Data System (ADS)

Rudolph, P.; Bradford, S. M.

2005-05-01

The ability to control critical dimensions of structures on semiconductor devices is essential to improving die yield and device performance. As geometries shrink, accuracy of the metrology equipment has increasingly become a contributing factor to the inability to detect shifts which result in yield loss. Scatterometry provides optical measurement that better enables process control of critical dimensions. Superior precision, accuracy, and higher throughput can be achieved more cost effectively through the use of this technology in production facilities. This paper outlines the implementation of Scatterometry based metrology in a production facility. The accuracy advantage it has over conventional Scanning Electron Microscope (SEM) measurement is presented. The Scatterometry tool used has demonstrated repeatability on the order of 3σ < 1 nm at STI-Etch-FICD for CD and Trench Depth (TD), and Side Wall Angle (SWA) measurements to within 0.1 degrees. Poly CD also shows 3σ < 1 nm, and poly thickness measurement 3σ < 2.5 Å. Scatterometry has capabilities which include measurement of CD, structure height and trench depth, Sidewall angle (SWA), and film thickness. The greater accuracy and the addition of in-situ Trench depth and sidewall angle have provided new measurement capabilities. There are inherent difficulties in implementing scatterometry in production wafer fabs. Difficulties with photo resist measurements, film characterization and stack set-up will be discussed. In addition, there are challenges due to the quantity data generated, in how to organize and store this data effectively. A comparison of the advantages and shortcomings of the method are presented.

Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship.

PubMed

Lee, S Hong; Clark, Sam; van der Werf, Julius H J

2017-01-01

Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne). Both the effective number of chromosome segments (Me) and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulated as well as real data, and illustrate that the variation in genomic relationships with the target is a predictor of the information content of the reference set. With a similar amount of data available for each source, we show that close relatives can have a substantially larger effect on genomic prediction accuracy than lesser related individuals. We also illustrate that when prediction relies on closer relatives, there is less improvement in prediction accuracy with an increase in training data or marker panel density. We release software that can estimate the expected prediction accuracy and power when combining different reference sources with various degrees of relationship to the target, which is useful when planning genomic prediction (before or after collecting data) in animal, plant and human genetics.

Effects of treadmill exercise intensity on spatial working memory and long-term memory in rats.

PubMed

Wang, Xiao-Qin; Wang, Gong-Wu

2016-03-15

Moderate exercise promotes learning and memory. Most studies mainly focused on memory exercise effects of in the ageing and patients. There is lack of quantitative research about effect of regular exercise intensity on different memory types in normal subjects. Present study investigated the effects of different intensities of treadmill exercise on working memory and long-term memory. Fifty female Wistar rats were trained by T-maze delayed spatial alternation (DSA) task with 3 delays (10s, 60s and 300s). Then they got a 30min treadmill exercise for 30days in 4 intensities (control, 0m/min; lower, 15m/min; middle, 20m/min, and higher, 30m/min). Then animals were tested in DSA, passive avoidance and Morris water maze tasks. 1. Exercise increased the neuronal density of hippocampal subregions (CA1, CA3 and dentate gyrus) vs. naïve/control. 2. In DSA task, all groups have similar baseline, lower intensity improved 10s delay accuracy vs. baseline/control; middle and higher intensities improved 300s delay accuracy vs. baseline/control. 3. In water maze learning, all groups successfully found the platform, but middle intensity improved platform field crossing times vs. control in test phase. Present results suggested that treadmill exercise can improve long-term spatial memory and working memory; lower intensity benefits to short-term delayed working memory, and middle or higher intensity benefits to long-term delayed working memory. There was an inverted U dose-effect relationship between exercise intensity and memory performance, but exercise -working memory effect was impacted by delay duration. Copyright © 2016 Elsevier Inc. All rights reserved.

Civil & Military Operations: Evolutionary Prep Steps to Pass Smart Power Current Limitations

DTIC Science & Technology

2011-06-01

and outcomes – Identifying the best time, place, and method for action – Reduced ambiguity for action application, reduced side effects – Find the...improvements to arrive at increased accuracy, precision, and reduction of un-intended effects . The examples of these streams will demonstrate the...DIME – Diplomatic, Intelligence, Military, and Economic; EBO – Effects Based Operations. 16th International Command and Control Research and

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units.

PubMed

Cai, Qingzhong; Yang, Gongliu; Song, Ningfang; Liu, Yiliang

2016-06-22

An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10(-6)°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs.

Systematic review of discharge coding accuracy

PubMed Central

Burns, E.M.; Rigby, E.; Mamidanna, R.; Bottle, A.; Aylin, P.; Ziprin, P.; Faiz, O.D.

2012-01-01

Introduction Routinely collected data sets are increasingly used for research, financial reimbursement and health service planning. High quality data are necessary for reliable analysis. This study aims to assess the published accuracy of routinely collected data sets in Great Britain. Methods Systematic searches of the EMBASE, PUBMED, OVID and Cochrane databases were performed from 1989 to present using defined search terms. Included studies were those that compared routinely collected data sets with case or operative note review and those that compared routinely collected data with clinical registries. Results Thirty-two studies were included. Twenty-five studies compared routinely collected data with case or operation notes. Seven studies compared routinely collected data with clinical registries. The overall median accuracy (routinely collected data sets versus case notes) was 83.2% (IQR: 67.3–92.1%). The median diagnostic accuracy was 80.3% (IQR: 63.3–94.1%) with a median procedure accuracy of 84.2% (IQR: 68.7–88.7%). There was considerable variation in accuracy rates between studies (50.5–97.8%). Since the 2002 introduction of Payment by Results, accuracy has improved in some respects, for example primary diagnoses accuracy has improved from 73.8% (IQR: 59.3–92.1%) to 96.0% (IQR: 89.3–96.3), P= 0.020. Conclusion Accuracy rates are improving. Current levels of reported accuracy suggest that routinely collected data are sufficiently robust to support their use for research and managerial decision-making. PMID:21795302

Effects of a rater training on rating accuracy in a physical examination skills assessment

PubMed Central

Weitz, Gunther; Vinzentius, Christian; Twesten, Christoph; Lehnert, Hendrik; Bonnemeier, Hendrik; König, Inke R.

2014-01-01

Background: The accuracy and reproducibility of medical skills assessment is generally low. Rater training has little or no effect. Our knowledge in this field, however, relies on studies involving video ratings of overall clinical performances. We hypothesised that a rater training focussing on the frame of reference could improve accuracy in grading the curricular assessment of a highly standardised physical head-to-toe examination. Methods: Twenty-one raters assessed the performance of 242 third-year medical students. Eleven raters had been randomly assigned to undergo a brief frame-of-reference training a few days before the assessment. 218 encounters were successfully recorded on video and re-assessed independently by three additional observers. Accuracy was defined as the concordance between the raters' grade and the median of the observers' grade. After the assessment, both students and raters filled in a questionnaire about their views on the assessment. Results: Rater training did not have a measurable influence on accuracy. However, trained raters rated significantly more stringently than untrained raters, and their overall stringency was closer to the stringency of the observers. The questionnaire indicated a higher awareness of the halo effect in the trained raters group. Although the self-assessment of the students mirrored the assessment of the raters in both groups, the students assessed by trained raters felt more discontent with their grade. Conclusions: While training had some marginal effects, it failed to have an impact on the individual accuracy. These results in real-life encounters are consistent with previous studies on rater training using video assessments of clinical performances. The high degree of standardisation in this study was not suitable to harmonize the trained raters’ grading. The data support the notion that the process of appraising medical performance is highly individual. A frame-of-reference training as applied does not effectively adjust the physicians' judgement on medical students in real-live assessments. PMID:25489341

Effects of a rater training on rating accuracy in a physical examination skills assessment.

PubMed

Weitz, Gunther; Vinzentius, Christian; Twesten, Christoph; Lehnert, Hendrik; Bonnemeier, Hendrik; König, Inke R

2014-01-01

The accuracy and reproducibility of medical skills assessment is generally low. Rater training has little or no effect. Our knowledge in this field, however, relies on studies involving video ratings of overall clinical performances. We hypothesised that a rater training focussing on the frame of reference could improve accuracy in grading the curricular assessment of a highly standardised physical head-to-toe examination. Twenty-one raters assessed the performance of 242 third-year medical students. Eleven raters had been randomly assigned to undergo a brief frame-of-reference training a few days before the assessment. 218 encounters were successfully recorded on video and re-assessed independently by three additional observers. Accuracy was defined as the concordance between the raters' grade and the median of the observers' grade. After the assessment, both students and raters filled in a questionnaire about their views on the assessment. Rater training did not have a measurable influence on accuracy. However, trained raters rated significantly more stringently than untrained raters, and their overall stringency was closer to the stringency of the observers. The questionnaire indicated a higher awareness of the halo effect in the trained raters group. Although the self-assessment of the students mirrored the assessment of the raters in both groups, the students assessed by trained raters felt more discontent with their grade. While training had some marginal effects, it failed to have an impact on the individual accuracy. These results in real-life encounters are consistent with previous studies on rater training using video assessments of clinical performances. The high degree of standardisation in this study was not suitable to harmonize the trained raters' grading. The data support the notion that the process of appraising medical performance is highly individual. A frame-of-reference training as applied does not effectively adjust the physicians' judgement on medical students in real-live assessments.

Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-05-12

A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features. GFBLUP, an extension of GBLUP, includes a separate genomic effect of SNPs within a genomic feature, and allows differential weighting of the individual marker relationships in the prediction equation. Since GFBLUP is computationally intensive, we investigated whether a SNP set test could be a computationally fast way to preselect predictive genomic features. The SNP set test assesses the association between a genomic feature and a trait based on single-SNP genome-wide association studies. We applied these two approaches to mastitis and milk production traits (milk, fat and protein yield) in Holstein (HOL, n = 5056) and Jersey (JER, n = 1231) cattle. We observed that a majority of genomic features were enriched in genomic variants that were associated with mastitis and milk production traits. Compared to GBLUP, the accuracy of genomic prediction with GFBLUP was marginally improved (3.2 to 3.9%) in within-breed prediction. The highest increase (164.4%) in prediction accuracy was observed in across-breed prediction. The significance of genomic features based on the SNP set test were correlated with changes in prediction accuracy of GFBLUP (P < 0.05). GFBLUP provides a framework for integrating multiple layers of biological knowledge to provide novel insights into the biological basis of complex traits, and to improve the accuracy of genomic prediction. The SNP set test might be used as a first-step to improve GFBLUP models. Approaches like GFBLUP and SNP set test will become increasingly useful, as the functional annotations of genomes keep accumulating for a range of species and traits.

Phase accuracy evaluation for phase-shifting fringe projection profilometry based on uniform-phase coded image

NASA Astrophysics Data System (ADS)

Zhang, Chunwei; Zhao, Hong; Zhu, Qian; Zhou, Changquan; Qiao, Jiacheng; Zhang, Lu

2018-06-01

Phase-shifting fringe projection profilometry (PSFPP) is a three-dimensional (3D) measurement technique widely adopted in industry measurement. It recovers the 3D profile of measured objects with the aid of the fringe phase. The phase accuracy is among the dominant factors that determine the 3D measurement accuracy. Evaluation of the phase accuracy helps refine adjustable measurement parameters, contributes to evaluating the 3D measurement accuracy, and facilitates improvement of the measurement accuracy. Although PSFPP has been deeply researched, an effective, easy-to-use phase accuracy evaluation method remains to be explored. In this paper, methods based on the uniform-phase coded image (UCI) are presented to accomplish phase accuracy evaluation for PSFPP. These methods work on the principle that the phase value of a UCI can be manually set to be any value, and once the phase value of a UCI pixel is the same as that of a pixel of a corresponding sinusoidal fringe pattern, their phase accuracy values are approximate. The proposed methods provide feasible approaches to evaluating the phase accuracy for PSFPP. Furthermore, they can be used to experimentally research the property of the random and gamma phase errors in PSFPP without the aid of a mathematical model to express random phase error or a large-step phase-shifting algorithm. In this paper, some novel and interesting phenomena are experimentally uncovered with the aid of the proposed methods.

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

NASA Astrophysics Data System (ADS)

Conen, N.; Hastedt, H.; Kahmen, O.; Luhmann, T.

2018-05-01

In dense stereo matching applications surface reflections may lead to incorrect measurements and blunders in the resulting point cloud. To overcome the problem of disturbing reflexions polarising filters can be mounted on the camera lens and light source. Reflections in the images can be suppressed by crossing the polarising direction of the filters leading to homogeneous illuminated images and better matching results. However, the filter may influence the camera's orientation parameters as well as the measuring accuracy. To quantify these effects, a calibration and an accuracy analysis is conducted within a spatial test arrangement according to the German guideline VDI/VDE 2634.1 (2002) using a DSLR with and without polarising filter. In a second test, the interior orientation is analysed in more detail. The results do not show significant changes of the measuring accuracy in object space and only very small changes of the interior orientation (Δc ≤ 4 μm) with the polarising filter in use. Since in medical applications many tiny reflections are present and impede robust surface measurements, a prototypic trinocular endoscope is equipped with polarising technique. The interior and relative orientation is determined and analysed. The advantage of the polarising technique for medical image matching is shown in an experiment with a moistened pig kidney. The accuracy and completeness of the resulting point cloud can be improved clearly when using polarising filters. Furthermore, an accuracy analysis using a laser triangulation system is performed and the special reflection properties of metallic surfaces are presented.

Comparison Between One-Point Calibration and Two-Point Calibration Approaches in a Continuous Glucose Monitoring Algorithm

PubMed Central

Mahmoudi, Zeinab; Johansen, Mette Dencker; Christiansen, Jens Sandahl

2014-01-01

Background: The purpose of this study was to investigate the effect of using a 1-point calibration approach instead of a 2-point calibration approach on the accuracy of a continuous glucose monitoring (CGM) algorithm. Method: A previously published real-time CGM algorithm was compared with its updated version, which used a 1-point calibration instead of a 2-point calibration. In addition, the contribution of the corrective intercept (CI) to the calibration performance was assessed. Finally, the sensor background current was estimated real-time and retrospectively. The study was performed on 132 type 1 diabetes patients. Results: Replacing the 2-point calibration with the 1-point calibration improved the CGM accuracy, with the greatest improvement achieved in hypoglycemia (18.4% median absolute relative differences [MARD] in hypoglycemia for the 2-point calibration, and 12.1% MARD in hypoglycemia for the 1-point calibration). Using 1-point calibration increased the percentage of sensor readings in zone A+B of the Clarke error grid analysis (EGA) in the full glycemic range, and also enhanced hypoglycemia sensitivity. Exclusion of CI from calibration reduced hypoglycemia accuracy, while slightly increased euglycemia accuracy. Both real-time and retrospective estimation of the sensor background current suggest that the background current can be considered zero in the calibration of the SCGM1 sensor. Conclusions: The sensor readings calibrated with the 1-point calibration approach indicated to have higher accuracy than those calibrated with the 2-point calibration approach. PMID:24876420

Position Accuracy Improvement by Implementing the DGNSS-CP Algorithm in Smartphones

PubMed Central

Yoon, Donghwan; Kee, Changdon; Seo, Jiwon; Park, Byungwoon

2016-01-01

The position accuracy of Global Navigation Satellite System (GNSS) modules is one of the most significant factors in determining the feasibility of new location-based services for smartphones. Considering the structure of current smartphones, it is impossible to apply the ordinary range-domain Differential GNSS (DGNSS) method. Therefore, this paper describes and applies a DGNSS-correction projection method to a commercial smartphone. First, the local line-of-sight unit vector is calculated using the elevation and azimuth angle provided in the position-related output of Android’s LocationManager, and this is transformed to Earth-centered, Earth-fixed coordinates for use. To achieve position-domain correction for satellite systems other than GPS, such as GLONASS and BeiDou, the relevant line-of-sight unit vectors are used to construct an observation matrix suitable for multiple constellations. The results of static and dynamic tests show that the standalone GNSS accuracy is improved by about 30%–60%, thereby reducing the existing error of 3–4 m to just 1 m. The proposed algorithm enables the position error to be directly corrected via software, without the need to alter the hardware and infrastructure of the smartphone. This method of implementation and the subsequent improvement in performance are expected to be highly effective to portability and cost saving. PMID:27322284

A Strapdown Interial Navigation System/Beidou/Doppler Velocity Log Integrated Navigation Algorithm Based on a Cubature Kalman Filter

PubMed Central

Gao, Wei; Zhang, Ya; Wang, Jianguo

2014-01-01

The integrated navigation system with strapdown inertial navigation system (SINS), Beidou (BD) receiver and Doppler velocity log (DVL) can be used in marine applications owing to the fact that the redundant and complementary information from different sensors can markedly improve the system accuracy. However, the existence of multisensor asynchrony will introduce errors into the system. In order to deal with the problem, conventionally the sampling interval is subdivided, which increases the computational complexity. In this paper, an innovative integrated navigation algorithm based on a Cubature Kalman filter (CKF) is proposed correspondingly. A nonlinear system model and observation model for the SINS/BD/DVL integrated system are established to more accurately describe the system. By taking multi-sensor asynchronization into account, a new sampling principle is proposed to make the best use of each sensor's information. Further, CKF is introduced in this new algorithm to enable the improvement of the filtering accuracy. The performance of this new algorithm has been examined through numerical simulations. The results have shown that the positional error can be effectively reduced with the new integrated navigation algorithm. Compared with the traditional algorithm based on EKF, the accuracy of the SINS/BD/DVL integrated navigation system is improved, making the proposed nonlinear integrated navigation algorithm feasible and efficient. PMID:24434842

Case studies on forecasting for innovative technologies: frequent revisions improve accuracy.

PubMed

Lerner, Jeffrey C; Robertson, Diane C; Goldstein, Sara M

2015-02-01

Health technology forecasting is designed to provide reliable predictions about costs, utilization, diffusion, and other market realities before the technologies enter routine clinical use. In this article we address three questions central to forecasting's usefulness: Are early forecasts sufficiently accurate to help providers acquire the most promising technology and payers to set effective coverage policies? What variables contribute to inaccurate forecasts? How can forecasters manage the variables to improve accuracy? We analyzed forecasts published between 2007 and 2010 by the ECRI Institute on four technologies: single-room proton beam radiation therapy for various cancers; digital breast tomosynthesis imaging technology for breast cancer screening; transcatheter aortic valve replacement for serious heart valve disease; and minimally invasive robot-assisted surgery for various cancers. We then examined revised ECRI forecasts published in 2013 (digital breast tomosynthesis) and 2014 (the other three topics) to identify inaccuracies in the earlier forecasts and explore why they occurred. We found that five of twenty early predictions were inaccurate when compared with the updated forecasts. The inaccuracies pertained to two technologies that had more time-sensitive variables to consider. The case studies suggest that frequent revision of forecasts could improve accuracy, especially for complex technologies whose eventual use is governed by multiple interactive factors. Project HOPE—The People-to-People Health Foundation, Inc.

Smiles in face matching: Idiosyncratic information revealed through a smile improves unfamiliar face matching performance.

PubMed

Mileva, Mila; Burton, A Mike

2018-06-19

Unfamiliar face matching is a surprisingly difficult task, yet we often rely on people's matching decisions in applied settings (e.g., border control). Most attempts to improve accuracy (including training and image manipulation) have had very limited success. In a series of studies, we demonstrate that using smiling rather than neutral pairs of images brings about significant improvements in face matching accuracy. This is true for both match and mismatch trials, implying that the information provided through a smile helps us detect images of the same identity as well as distinguishing between images of different identities. Study 1 compares matching performance when images in the face pair display either an open-mouth smile or a neutral expression. In Study 2, we add an intermediate level, closed-mouth smile, to identify the effect of teeth being exposed, and Study 3 explores face matching accuracy when only information about the lower part of the face is available. Results demonstrate that an open-mouth smile changes the face in an idiosyncratic way which aids face matching decisions. Such findings have practical implications for matching in the applied context where we typically use neutral images to represent ourselves in official documents. © 2018 The British Psychological Society.

IMU-based online kinematic calibration of robot manipulator.

PubMed

Du, Guanglong; Zhang, Ping

2013-01-01

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

A study of ionospheric grid modification technique for BDS/GPS receiver

NASA Astrophysics Data System (ADS)

Liu, Xuelin; Li, Meina; Zhang, Lei

2017-07-01

For the single-frequency GPS receiver, ionospheric delay is an important factor affecting the positioning performance. There are many kinds of ionospheric correction methods, common models are Bent model, IRI model, Klobuchar model, Ne Quick model and so on. The US Global Positioning System (GPS) uses the Klobuchar coefficients transmitted in the satellite signal to correct the ionospheric delay error for a single frequency GPS receiver, but this model can only reduce the ionospheric error of about 50% in the mid-latitudes. In the Beidou system, the accuracy of the correction delay is higher. Therefore, this paper proposes a method that using BD grid information to correct GPS ionospheric delay to improve the ionospheric delay for the BDS/GPS compatible positioning receiver. In this paper, the principle of ionospheric grid algorithm is introduced in detail, and the positioning accuracy of GPS system and BDS/GPS compatible positioning system is compared and analyzed by the real measured data. The results show that the method can effectively improve the positioning accuracy of the receiver in a more concise way.