Sample records for text input methods
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Smartphone Text Input Method Performance, Usability, and Preference With Younger and Older Adults.
Smith, Amanda L; Chaparro, Barbara S
2015-09-01
User performance, perceived usability, and preference for five smartphone text input methods were compared with younger and older novice adults. Smartphones are used for a variety of functions other than phone calls, including text messaging, e-mail, and web browsing. Research comparing performance with methods of text input on smartphones reveals a high degree of variability in reported measures, procedures, and results. This study reports on a direct comparison of five of the most common input methods among a population of younger and older adults, who had no experience with any of the methods. Fifty adults (25 younger, 18-35 years; 25 older, 60-84 years) completed a text entry task using five text input methods (physical Qwerty, onscreen Qwerty, tracing, handwriting, and voice). Entry and error rates, perceived usability, and preference were recorded. Both age groups input text equally fast using voice input, but older adults were slower than younger adults using all other methods. Both age groups had low error rates when using physical Qwerty and voice, but older adults committed more errors with the other three methods. Both younger and older adults preferred voice and physical Qwerty input to the remaining methods. Handwriting consistently performed the worst and was rated lowest by both groups. Voice and physical Qwerty input methods proved to be the most effective for both younger and older adults, and handwriting input was the least effective overall. These findings have implications to the design of future smartphone text input methods and devices, particularly for older adults. © 2015, Human Factors and Ergonomics Society.
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Comparison of Text-Based and Visual-Based Programming Input Methods for First-Time Learners
ERIC Educational Resources Information Center
Saito, Daisuke; Washizaki, Hironori; Fukazawa, Yoshiaki
2017-01-01
Aim/Purpose: When learning to program, both text-based and visual-based input methods are common. However, it is unclear which method is more appropriate for first-time learners (first learners). Background: The differences in the learning effect between text-based and visual-based input methods for first learners are compared the using a…
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Encryption and decryption using FPGA
NASA Astrophysics Data System (ADS)
Nayak, Nikhilesh; Chandak, Akshay; Shah, Nisarg; Karthikeyan, B.
2017-11-01
In this paper, we are performing multiple cryptography methods on a set of data and comparing their outputs. Here AES algorithm and RSA algorithm are used. Using AES Algorithm an 8 bit input (plain text) gets encrypted using a cipher key and the result is displayed on tera term (serially). For simulation a 128 bit input is used and operated with a 128 bit cipher key to generate encrypted text. The reverse operations are then performed to get decrypted text. In RSA Algorithm file handling is used to input plain text. This text is then operated on to get the encrypted and decrypted data, which are then stored in a file. Finally the results of both the algorithms are compared.
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Evaluation of user input methods for manipulating a tablet personal computer in sterile techniques.
Yamada, Akira; Komatsu, Daisuke; Suzuki, Takeshi; Kurozumi, Masahiro; Fujinaga, Yasunari; Ueda, Kazuhiko; Kadoya, Masumi
2017-02-01
To determine a quick and accurate user input method for manipulating tablet personal computers (PCs) in sterile techniques. We evaluated three different manipulation methods, (1) Computer mouse and sterile system drape, (2) Fingers and sterile system drape, and (3) Digitizer stylus and sterile ultrasound probe cover with a pinhole, in terms of the central processing unit (CPU) performance, manipulation performance, and contactlessness. A significant decrease in CPU score ([Formula: see text]) and an increase in CPU temperature ([Formula: see text]) were observed when a system drape was used. The respective mean times taken to select a target image from an image series (ST) and the mean times for measuring points on an image (MT) were [Formula: see text] and [Formula: see text] s for the computer mouse method, [Formula: see text] and [Formula: see text] s for the finger method, and [Formula: see text] and [Formula: see text] s for the digitizer stylus method, respectively. The ST for the finger method was significantly longer than for the digitizer stylus method ([Formula: see text]). The MT for the computer mouse method was significantly longer than for the digitizer stylus method ([Formula: see text]). The mean success rate for measuring points on an image was significantly lower for the finger method when the diameter of the target was equal to or smaller than 8 mm than for the other methods. No significant difference in the adenosine triphosphate amount at the surface of the tablet PC was observed before, during, or after manipulation via the digitizer stylus method while wearing starch-powdered sterile gloves ([Formula: see text]). Quick and accurate manipulation of tablet PCs in sterile techniques without CPU load is feasible using a digitizer stylus and sterile ultrasound probe cover with a pinhole.
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Children's Text Messaging: Abbreviations, Input Methods and Links with Literacy
ERIC Educational Resources Information Center
Kemp, N.; Bushnell, C.
2011-01-01
This study investigated the effects of mobile phone text-messaging method (predictive and multi-press) and experience (in texters and non-texters) on children's textism use and understanding. It also examined popular claims that the use of text-message abbreviations, or "textese" spelling, is associated with poor literacy skills. A sample of 86…
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Moradi, Milad; Ghadiri, Nasser
2018-01-01
Automatic text summarization tools help users in the biomedical domain to acquire their intended information from various textual resources more efficiently. Some of biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text. However, it seems that exploring other measures rather than the raw frequency for identifying valuable contents within an input document, or considering correlations existing between concepts, may be more useful for this type of summarization. In this paper, we describe a Bayesian summarization method for biomedical text documents. The Bayesian summarizer initially maps the input text to the Unified Medical Language System (UMLS) concepts; then it selects the important ones to be used as classification features. We introduce six different feature selection approaches to identify the most important concepts of the text and select the most informative contents according to the distribution of these concepts. We show that with the use of an appropriate feature selection approach, the Bayesian summarizer can improve the performance of biomedical summarization. Using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) toolkit, we perform extensive evaluations on a corpus of scientific papers in the biomedical domain. The results show that when the Bayesian summarizer utilizes the feature selection methods that do not use the raw frequency, it can outperform the biomedical summarizers that rely on the frequency of concepts, domain-independent and baseline methods. Copyright © 2017 Elsevier B.V. All rights reserved.
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Reconstruction of an input function from a dynamic PET water image using multiple tissue curves
NASA Astrophysics Data System (ADS)
Kudomi, Nobuyuki; Maeda, Yukito; Yamamoto, Yuka; Nishiyama, Yoshihiro
2016-08-01
Quantification of cerebral blood flow (CBF) is important for the understanding of normal and pathologic brain physiology. When CBF is assessed using PET with {{\\text{H}}2} 15O or C15O2, its calculation requires an arterial input function, which generally requires invasive arterial blood sampling. The aim of the present study was to develop a new technique to reconstruct an image derived input function (IDIF) from a dynamic {{\\text{H}}2} 15O PET image as a completely non-invasive approach. Our technique consisted of using a formula to express the input using tissue curve with rate constant parameter. For multiple tissue curves extracted from the dynamic image, the rate constants were estimated so as to minimize the sum of the differences of the reproduced inputs expressed by the extracted tissue curves. The estimated rates were used to express the inputs and the mean of the estimated inputs was used as an IDIF. The method was tested in human subjects (n = 29) and was compared to the blood sampling method. Simulation studies were performed to examine the magnitude of potential biases in CBF and to optimize the number of multiple tissue curves used for the input reconstruction. In the PET study, the estimated IDIFs were well reproduced against the measured ones. The difference between the calculated CBF values obtained using the two methods was small as around <8% and the calculated CBF values showed a tight correlation (r = 0.97). The simulation showed that errors associated with the assumed parameters were <10%, and that the optimal number of tissue curves to be used was around 500. Our results demonstrate that IDIF can be reconstructed directly from tissue curves obtained through {{\\text{H}}2} 15O PET imaging. This suggests the possibility of using a completely non-invasive technique to assess CBF in patho-physiological studies.
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Virtual Sliding QWERTY: A new text entry method for smartwatches using Tap-N-Drag.
Cha, Jae-Min; Choi, Eunjung; Lim, Jihyoun
2015-11-01
A smaller screen of smartwatches compare to conventional mobile devices such as PDAs and smartphones is one of the main factors that makes users to input texts difficult. However, several studies have only proposed a concept for entering texts for smartwatches without usability tests while other studies showed low text input performance. In this study, we proposed a new text entry method called Virtual Sliding QWERTY (VSQ) which utilizes a virtual qwerty-layout keyboard and a 'Tap-N-Drag' method to move the keyboard to the desired position. In addition, to verify VSQ we conducted a usability test with 20 participants for a combination of 5 key sizes and 4 CD-gains. As a result, VSQ achieved an average of 11.9 Words per Minute which was higher than previous studies. In particular, VSQ at 5 × 5 key size and 2×, or 3× CD-gain had the highest performance in terms of the quantitative and qualitative usability test. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
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NASA Astrophysics Data System (ADS)
Sboev, A.; Moloshnikov, I.; Gudovskikh, D.; Rybka, R.
2017-12-01
In this work we compare several data-driven approaches to the task of author’s gender identification for texts with or without gender imitation. The data corpus has been specially gathered with crowdsourcing for this task. The best models are convolutional neural network with input of morphological data (fl-measure: 88%±3) for texts without imitation, and gradient boosting model with vector of character n-grams frequencies as input data (f1-measure: 64% ± 3) for texts with gender imitation. The method to filter the crowdsourced corpus using limited reference sample of texts to increase the accuracy of result is discussed.
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Integrated editing system for Japanese text and image information "Linernote"
NASA Astrophysics Data System (ADS)
Tanaka, Kazuto
Integrated Japanese text editing system "Linernote" developed by Toyo Industries Co. is explained. The system has been developed on the concept of electronic publishing. It is composed of personal computer NEC PC-9801 VX and other peripherals. Sentence, drawing and image data is inputted and edited under the integrated operating environment in the system and final text is printed out by laser printer. Handling efficiency of time consuming work such as pattern input or page make up has been improved by draft image data indication method on CRT. It is the latest DTP system equipped with three major functions, namly, typesetting for high quality text editing, easy drawing/tracing and high speed image processing.
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Online Adaptation for Mobile Device Text Input Personalization
ERIC Educational Resources Information Center
Baldwin, Tyler
2012-01-01
As mobile devices have become more common, the need for efficient methods of mobile device text entry has grown. With this growth comes new challenges, as the constraints imposed by the size, processing power, and design of mobile devices impairs traditional text entry mechanisms in ways not seen in previous text entry tasks. To combat this,…
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XML-Based Generator of C++ Code for Integration With GUIs
NASA Technical Reports Server (NTRS)
Hua, Hook; Oyafuso, Fabiano; Klimeck, Gerhard
2003-01-01
An open source computer program has been developed to satisfy a need for simplified organization of structured input data for scientific simulation programs. Typically, such input data are parsed in from a flat American Standard Code for Information Interchange (ASCII) text file into computational data structures. Also typically, when a graphical user interface (GUI) is used, there is a need to completely duplicate the input information while providing it to a user in a more structured form. Heretofore, the duplication of the input information has entailed duplication of software efforts and increases in susceptibility to software errors because of the concomitant need to maintain two independent input-handling mechanisms. The present program implements a method in which the input data for a simulation program are completely specified in an Extensible Markup Language (XML)-based text file. The key benefit for XML is storing input data in a structured manner. More importantly, XML allows not just storing of data but also describing what each of the data items are. That XML file contains information useful for rendering the data by other applications. It also then generates data structures in the C++ language that are to be used in the simulation program. In this method, all input data are specified in one place only, and it is easy to integrate the data structures into both the simulation program and the GUI. XML-to-C is useful in two ways: 1. As an executable, it generates the corresponding C++ classes and 2. As a library, it automatically fills the objects with the input data values.
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Tippey, Kathryn G; Sivaraj, Elayaraj; Ferris, Thomas K
2017-06-01
This study evaluated the individual and combined effects of voice (vs. manual) input and head-up (vs. head-down) display in a driving and device interaction task. Advances in wearable technology offer new possibilities for in-vehicle interaction but also present new challenges for managing driver attention and regulating device usage in vehicles. This research investigated how driving performance is affected by interface characteristics of devices used for concurrent secondary tasks. A positive impact on driving performance was expected when devices included voice-to-text functionality (reducing demand for visual and manual resources) and a head-up display (HUD) (supporting greater visibility of the driving environment). Driver behavior and performance was compared in a texting-while-driving task set during a driving simulation. The texting task was completed with and without voice-to-text using a smartphone and with voice-to-text using Google Glass's HUD. Driving task performance degraded with the addition of the secondary texting task. However, voice-to-text input supported relatively better performance in both driving and texting tasks compared to using manual entry. HUD functionality further improved driving performance compared to conditions using a smartphone and often was not significantly worse than performance without the texting task. This study suggests that despite the performance costs of texting-while-driving, voice input methods improve performance over manual entry, and head-up displays may further extend those performance benefits. This study can inform designers and potential users of wearable technologies as well as policymakers tasked with regulating the use of these technologies while driving.
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Sentiment analysis of feature ranking methods for classification accuracy
NASA Astrophysics Data System (ADS)
Joseph, Shashank; Mugauri, Calvin; Sumathy, S.
2017-11-01
Text pre-processing and feature selection are important and critical steps in text mining. Text pre-processing of large volumes of datasets is a difficult task as unstructured raw data is converted into structured format. Traditional methods of processing and weighing took much time and were less accurate. To overcome this challenge, feature ranking techniques have been devised. A feature set from text preprocessing is fed as input for feature selection. Feature selection helps improve text classification accuracy. Of the three feature selection categories available, the filter category will be the focus. Five feature ranking methods namely: document frequency, standard deviation information gain, CHI-SQUARE, and weighted-log likelihood -ratio is analyzed.
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NASA Astrophysics Data System (ADS)
Krasilenko, Vladimir G.; Bardachenko, Vitaliy F.; Nikolsky, Alexander I.; Lazarev, Alexander A.; Ogorodnik, Konstantin V.
2006-04-01
We analyse the existent methods of cryptographic defence for the facsimile information transfer, consider their shortcomings and prove the necessity of better information protection degree. The method of information protection that is based on presentation of input data as images is proposed. We offer a new noise-immune algorithm for realization of this method which consists in transformation of an input frame by pixels transposition according to an entered key. At decoding mode the reverse transformation of image with the use of the same key is used. Practical realization of the given method takes into account noise in the transmission channels and information distortions by scanners, faxes and others like that. We show that the given influences are reduced to the transformation of the input image coordinates. We show the algorithm in detail and consider its basic steps. We show the possibility of the offered method by the means of the developed software. The realized algorithm corrects curvature of frames: turn, scaling, fallout of pixels and others like that. At low noise level (loss of pixel information less than 10 percents) it is possible to encode, transfer and decode any types of images and texts with 12-size font character. The software filters for information restore and noise removing allow to transfer fax data with 30 percents pixels loss at 18-size font text. This percent of data loss can be considerably increased by the use of the software character recognition block that can be realized on fuzzy-neural algorithms. Examples of encoding and decryption of images and texts are shown.
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Pouplin, Samuel; Roche, Nicolas; Antoine, Jean-Yves; Vaugier, Isabelle; Pottier, Sandra; Figere, Marjorie; Bensmail, Djamel
2017-06-01
To determine whether activation of the frequency of use and automatic learning parameters of word prediction software has an impact on text input speed. Forty-five participants with cervical spinal cord injury between C4 and C8 Asia A or B accepted to participate to this study. Participants were separated in two groups: a high lesion group for participants with lesion level is at or above C5 Asia AIS A or B and a low lesion group for participants with lesion is between C6 and C8 Asia AIS A or B. A single evaluation session was carried out for each participant. Text input speed was evaluated during three copying tasks: • without word prediction software (WITHOUT condition) • with automatic learning of words and frequency of use deactivated (NOT_ACTIV condition) • with automatic learning of words and frequency of use activated (ACTIV condition) Results: Text input speed was significantly higher in the WITHOUT than the NOT_ACTIV (p< 0.001) or ACTIV conditions (p = 0.02) for participants with low lesions. Text input speed was significantly higher in the ACTIV than in the NOT_ACTIV (p = 0.002) or WITHOUT (p < 0.001) conditions for participants with high lesions. Use of word prediction software with the activation of frequency of use and automatic learning increased text input speed in participants with high-level tetraplegia. For participants with low-level tetraplegia, the use of word prediction software with frequency of use and automatic learning activated only decreased the number of errors. Implications in rehabilitation Access to technology can be difficult for persons with disabilities such as cervical spinal cord injury (SCI). Several methods have been developed to increase text input speed such as word prediction software.This study show that parameter of word prediction software (frequency of use) affected text input speed in persons with cervical SCI and differed according to the level of the lesion. • For persons with high-level lesion, our results suggest that this parameter must be activated so that text input speed is increased. • For persons with low lesion group, this parameter must be activated so that the numbers of errors are decreased. • In all cases, the activation of the parameter of frequency of use is essential in order to improve the efficiency of the word prediction software. • Health-related professionals should use these results in their clinical practice for better results and therefore better patients 'satisfaction.
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Surface code implementation of block code state distillation.
Fowler, Austin G; Devitt, Simon J; Jones, Cody
2013-01-01
State distillation is the process of taking a number of imperfect copies of a particular quantum state and producing fewer better copies. Until recently, the lowest overhead method of distilling states produced a single improved [formula: see text] state given 15 input copies. New block code state distillation methods can produce k improved [formula: see text] states given 3k + 8 input copies, potentially significantly reducing the overhead associated with state distillation. We construct an explicit surface code implementation of block code state distillation and quantitatively compare the overhead of this approach to the old. We find that, using the best available techniques, for parameters of practical interest, block code state distillation does not always lead to lower overhead, and, when it does, the overhead reduction is typically less than a factor of three.
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A High Input Impedance Low Noise Integrated Front-End Amplifier for Neural Monitoring.
Zhou, Zhijun; Warr, Paul A
2016-12-01
Within neural monitoring systems, the front-end amplifier forms the critical element for signal detection and pre-processing, which determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a novel combined feedback loop-controlled approach is proposed to compensate for input leakage currents generated by low noise amplifiers when in integrated circuit form alongside signal leakage into the input bias network. This loop topology ensures the Front-End Amplifier (FEA) maintains a high input impedance across all manufacturing and operational variations. Measured results from a prototype manufactured on the AMS 0.35 [Formula: see text] CMOS technology is provided. This FEA consumes 3.1 [Formula: see text] in 0.042 [Formula: see text], achieves input impedance of 42 [Formula: see text], and 18.2 [Formula: see text] input-referred noise.
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Kudomi, Nobuyuki; Maeda, Yukito; Yamamoto, Hiroyuki; Yamamoto, Yuka; Hatakeyama, Tetsuhiro; Nishiyama, Yoshihiro
2018-05-01
CBF, OEF, and CMRO 2 images can be quantitatively assessed using PET. Their image calculation requires arterial input functions, which require invasive procedure. The aim of the present study was to develop a non-invasive approach with image-derived input functions (IDIFs) using an image from an ultra-rapid O 2 and C 15 O 2 protocol. Our technique consists of using a formula to express the input using tissue curve with rate constants. For multiple tissue curves, the rate constants were estimated so as to minimize the differences of the inputs using the multiple tissue curves. The estimated rates were used to express the inputs and the mean of the estimated inputs was used as an IDIF. The method was tested in human subjects ( n = 24). The estimated IDIFs were well-reproduced against the measured ones. The difference in the calculated CBF, OEF, and CMRO 2 values by the two methods was small (<10%) against the invasive method, and the values showed tight correlations ( r = 0.97). The simulation showed errors associated with the assumed parameters were less than ∼10%. Our results demonstrate that IDIFs can be reconstructed from tissue curves, suggesting the possibility of using a non-invasive technique to assess CBF, OEF, and CMRO 2 .
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Quasi-Monte Carlo Methods Applied to Tau-Leaping in Stochastic Biological Systems.
Beentjes, Casper H L; Baker, Ruth E
2018-05-25
Quasi-Monte Carlo methods have proven to be effective extensions of traditional Monte Carlo methods in, amongst others, problems of quadrature and the sample path simulation of stochastic differential equations. By replacing the random number input stream in a simulation procedure by a low-discrepancy number input stream, variance reductions of several orders have been observed in financial applications. Analysis of stochastic effects in well-mixed chemical reaction networks often relies on sample path simulation using Monte Carlo methods, even though these methods suffer from typical slow [Formula: see text] convergence rates as a function of the number of sample paths N. This paper investigates the combination of (randomised) quasi-Monte Carlo methods with an efficient sample path simulation procedure, namely [Formula: see text]-leaping. We show that this combination is often more effective than traditional Monte Carlo simulation in terms of the decay of statistical errors. The observed convergence rate behaviour is, however, non-trivial due to the discrete nature of the models of chemical reactions. We explain how this affects the performance of quasi-Monte Carlo methods by looking at a test problem in standard quadrature.
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Script-independent text line segmentation in freestyle handwritten documents.
Li, Yi; Zheng, Yefeng; Doermann, David; Jaeger, Stefan; Li, Yi
2008-08-01
Text line segmentation in freestyle handwritten documents remains an open document analysis problem. Curvilinear text lines and small gaps between neighboring text lines present a challenge to algorithms developed for machine printed or hand-printed documents. In this paper, we propose a novel approach based on density estimation and a state-of-the-art image segmentation technique, the level set method. From an input document image, we estimate a probability map, where each element represents the probability that the underlying pixel belongs to a text line. The level set method is then exploited to determine the boundary of neighboring text lines by evolving an initial estimate. Unlike connected component based methods ( [1], [2] for example), the proposed algorithm does not use any script-specific knowledge. Extensive quantitative experiments on freestyle handwritten documents with diverse scripts, such as Arabic, Chinese, Korean, and Hindi, demonstrate that our algorithm consistently outperforms previous methods [1]-[3]. Further experiments show the proposed algorithm is robust to scale change, rotation, and noise.
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Type 2 Diabetes Screening Test by Means of a Pulse Oximeter.
Moreno, Enrique Monte; Lujan, Maria Jose Anyo; Rusinol, Montse Torrres; Fernandez, Paqui Juarez; Manrique, Pilar Nunez; Trivino, Cristina Aragon; Miquel, Magda Pedrosa; Rodriguez, Marife Alvarez; Burguillos, M Jose Gonzalez
2017-02-01
In this paper, we propose a method for screening for the presence of type 2 diabetes by means of the signal obtained from a pulse oximeter. The screening system consists of two parts: the first analyzes the signal obtained from the pulse oximeter, and the second consists of a machine-learning module. The system consists of a front end that extracts a set of features form the pulse oximeter signal. These features are based on physiological considerations. The set of features were the input of a machine-learning algorithm that determined the class of the input sample, i.e., whether the subject had diabetes or not. The machine-learning algorithms were random forests, gradient boosting, and linear discriminant analysis as benchmark. The system was tested on a database of [Formula: see text] subjects (two samples per subject) collected from five community health centers. The mean receiver operating characteristic area found was [Formula: see text]% (median value [Formula: see text]% and range [Formula: see text]%), with a specificity = [Formula: see text]% for a threshold that gave a sensitivity = [Formula: see text]%. We present a screening method for detecting diabetes that has a performance comparable to the glycated haemoglobin (haemoglobin A1c HbA1c) test, does not require blood extraction, and yields results in less than 5 min.
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Global image analysis to determine suitability for text-based image personalization
NASA Astrophysics Data System (ADS)
Ding, Hengzhou; Bala, Raja; Fan, Zhigang; Bouman, Charles A.; Allebach, Jan P.
2012-03-01
Lately, image personalization is becoming an interesting topic. Images with variable elements such as text usually appear much more appealing to the recipients. In this paper, we describe a method to pre-analyze the image and automatically suggest to the user the most suitable regions within an image for text-based personalization. The method is based on input gathered from experiments conducted with professional designers. It has been observed that regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are the best candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Furthermore, based on the smooth and text regions found in the image, we derive an overall metric to rate the image in terms of its suitability for personalization (SFP).
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Aircraft signal definition for flight safety system monitoring system
NASA Technical Reports Server (NTRS)
Gibbs, Michael (Inventor); Omen, Debi Van (Inventor)
2003-01-01
A system and method compares combinations of vehicle variable values against known combinations of potentially dangerous vehicle input signal values. Alarms and error messages are selectively generated based on such comparisons. An aircraft signal definition is provided to enable definition and monitoring of sets of aircraft input signals to customize such signals for different aircraft. The input signals are compared against known combinations of potentially dangerous values by operational software and hardware of a monitoring function. The aircraft signal definition is created using a text editor or custom application. A compiler receives the aircraft signal definition to generate a binary file that comprises the definition of all the input signals used by the monitoring function. The binary file also contains logic that specifies how the inputs are to be interpreted. The file is then loaded into the monitor function, where it is validated and used to continuously monitor the condition of the aircraft.
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Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck
2015-01-01
The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.
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Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.
Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo
2017-10-01
Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.
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Momentum distributions for H 2 ( e , e ' p )
Ford, William P.; Jeschonnek, Sabine; Van Orden, J. W.
2014-12-29
[Background] A primary goal of deuteron electrodisintegration is the possibility of extracting the deuteron momentum distribution. This extraction is inherently fraught with difficulty, as the momentum distribution is not an observable and the extraction relies on theoretical models dependent on other models as input. [Purpose] We present a new method for extracting the momentum distribution which takes into account a wide variety of model inputs thus providing a theoretical uncertainty due to the various model constituents. [Method] The calculations presented here are using a Bethe-Salpeter like formalism with a wide variety of bound state wave functions, form factors, and finalmore » state interactions. We present a method to extract the momentum distributions from experimental cross sections, which takes into account the theoretical uncertainty from the various model constituents entering the calculation. [Results] In order to test the extraction pseudo-data was generated, and the extracted "experimental'' distribution, which has theoretical uncertainty from the various model inputs, was compared with the theoretical distribution used to generate the pseudo-data. [Conclusions] In the examples we compared the original distribution was typically within the error band of the extracted distribution. The input wave functions do contain some outliers which are discussed in the text, but at least this process can provide an upper bound on the deuteron momentum distribution. Due to the reliance on the theoretical calculation to obtain this quantity any extraction method should account for the theoretical error inherent in these calculations due to model inputs.« less
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Suzuki, S; Svatos, M; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Taccini, C; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tam, J Y C; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tannenwald, B B; Tannoury, N; Tapprogge, S; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, F E; Taylor, G N; Taylor, P T E; Taylor, W; Teischinger, F A; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Temple, D; Ten Kate, H; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, E N; Thompson, P D; Thompson, R J; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tibbetts, M J; Ticse Torres, R E; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tiouchichine, E; Tipton, P; Tisserant, S; Todome, K; Todorov, T; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trovatelli, M; True, P; Truong, L; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tudorache, A; Tudorache, V; Tuna, A N; Tupputi, S A; Turchikhin, S; Turecek, D; Turra, R; Turvey, A J; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Ueda, I; Ueno, R; Ughetto, M; Ugland, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usanova, A; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; Van Den Wollenberg, W; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vanguri, R; Vaniachine, A; Vannucci, F; Vardanyan, G; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vazeille, F; Vazquez Schroeder, T; Veatch, J; Veloce, L M; Veloso, F; Velz, T; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Vigne, R; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; Volpi, M; von der Schmitt, H; von Radziewski, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, T; Wang, X; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Wasicki, C; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Wessels, M; Wetter, J; Whalen, K; Wharton, A M; White, A; White, M J; White, R; White, S; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, A; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winter, B T; Wittgen, M; Wittkowski, J; Wollstadt, S J; Wolter, M W; Wolters, H; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yakabe, R; Yamada, M; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yao, W-M; Yasu, Y; Yatsenko, E; Yau Wong, K H; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yurkewicz, A; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, Q; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, H; Zhang, J; Zhang, L; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zurzolo, G; Zwalinski, L
2016-01-01
The distribution of particles inside hadronic jets produced in the decay of boosted W and Z bosons can be used to discriminate such jets from the continuum background. Given that a jet has been identified as likely resulting from the hadronic decay of a boosted W or Z boson, this paper presents a technique for further differentiating Z bosons from W bosons. The variables used are jet mass, jet charge, and a b -tagging discriminant. A likelihood tagger is constructed from these variables and tested in the simulation of [Formula: see text] for bosons in the transverse momentum range 200 GeV [Formula: see text] 400 GeV in [Formula: see text] TeV pp collisions with the ATLAS detector at the LHC. For Z -boson tagging efficiencies of [Formula: see text], 50, and [Formula: see text], one can achieve [Formula: see text]-boson tagging rejection factors ([Formula: see text]) of 1.7, 8.3 and 1000, respectively. It is not possible to measure these efficiencies in the data due to the lack of a pure sample of high [Formula: see text], hadronically decaying Z bosons. However, the modelling of the tagger inputs for boosted W bosons is studied in data using a [Formula: see text]-enriched sample of events in 20.3 fb[Formula: see text] of data at [Formula: see text] TeV. The inputs are well modelled within uncertainties, which builds confidence in the expected tagger performance.
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Relevance popularity: A term event model based feature selection scheme for text classification.
Feng, Guozhong; An, Baiguo; Yang, Fengqin; Wang, Han; Zhang, Libiao
2017-01-01
Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the number of documents that contain a particular term (i.e. the document frequency) is often used. However, the frequency of a given term appearing in each document has not been fully investigated, even though it is a promising feature to produce accurate classifications. In this paper, we propose a new feature selection scheme based on a term event Multinomial naive Bayes probabilistic model. According to the model assumptions, the matching score function, which is based on the prediction probability ratio, can be factorized. Finally, we derive a feature selection measurement for each term after replacing inner parameters by their estimators. On a benchmark English text datasets (20 Newsgroups) and a Chinese text dataset (MPH-20), our numerical experiment results obtained from using two widely used text classifiers (naive Bayes and support vector machine) demonstrate that our method outperformed the representative feature selection methods.
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Dynamic characteristics of oxygen consumption.
Ye, Lin; Argha, Ahmadreza; Yu, Hairong; Celler, Branko G; Nguyen, Hung T; Su, Steven
2018-04-23
Previous studies have indicated that oxygen uptake ([Formula: see text]) is one of the most accurate indices for assessing the cardiorespiratory response to exercise. In most existing studies, the response of [Formula: see text] is often roughly modelled as a first-order system due to the inadequate stimulation and low signal to noise ratio. To overcome this difficulty, this paper proposes a novel nonparametric kernel-based method for the dynamic modelling of [Formula: see text] response to provide a more robust estimation. Twenty healthy non-athlete participants conducted treadmill exercises with monotonous stimulation (e.g., single step function as input). During the exercise, [Formula: see text] was measured and recorded by a popular portable gas analyser ([Formula: see text], COSMED). Based on the recorded data, a kernel-based estimation method was proposed to perform the nonparametric modelling of [Formula: see text]. For the proposed method, a properly selected kernel can represent the prior modelling information to reduce the dependence of comprehensive stimulations. Furthermore, due to the special elastic net formed by [Formula: see text] norm and kernelised [Formula: see text] norm, the estimations are smooth and concise. Additionally, the finite impulse response based nonparametric model which estimated by the proposed method can optimally select the order and fit better in terms of goodness-of-fit comparing to classical methods. Several kernels were introduced for the kernel-based [Formula: see text] modelling method. The results clearly indicated that the stable spline (SS) kernel has the best performance for [Formula: see text] modelling. Particularly, based on the experimental data from 20 participants, the estimated response from the proposed method with SS kernel was significantly better than the results from the benchmark method [i.e., prediction error method (PEM)] ([Formula: see text] vs [Formula: see text]). The proposed nonparametric modelling method is an effective method for the estimation of the impulse response of VO 2 -Speed system. Furthermore, the identified average nonparametric model method can dynamically predict [Formula: see text] response with acceptable accuracy during treadmill exercise.
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Chen, S C; Shao, C L; Liang, C K; Lin, S W; Huang, T H; Hsieh, M C; Yang, C H; Luo, C H; Wuo, C M
2004-01-01
In this paper, we present a text input system for the seriously disabled by using lips image recognition based on LabVIEW. This system can be divided into the software subsystem and the hardware subsystem. In the software subsystem, we adopted the technique of image processing to recognize the status of mouth-opened or mouth-closed depending the relative distance between the upper lip and the lower lip. In the hardware subsystem, parallel port built in PC is used to transmit the recognized result of mouth status to the Morse-code text input system. Integrating the software subsystem with the hardware subsystem, we implement a text input system by using lips image recognition programmed in LabVIEW language. We hope the system can help the seriously disabled to communicate with normal people more easily.
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A new method for text detection and recognition in indoor scene for assisting blind people
NASA Astrophysics Data System (ADS)
Jabnoun, Hanen; Benzarti, Faouzi; Amiri, Hamid
2017-03-01
Developing assisting system of handicapped persons become a challenging ask in research projects. Recently, a variety of tools are designed to help visually impaired or blind people object as a visual substitution system. The majority of these tools are based on the conversion of input information into auditory or tactile sensory information. Furthermore, object recognition and text retrieval are exploited in the visual substitution systems. Text detection and recognition provides the description of the surrounding environments, so that the blind person can readily recognize the scene. In this work, we aim to introduce a method for detecting and recognizing text in indoor scene. The process consists on the detection of the regions of interest that should contain the text using the connected component. Then, the text detection is provided by employing the images correlation. This component of an assistive blind person should be simple, so that the users are able to obtain the most informative feedback within the shortest time.
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75 FR 51291 - National Science Board: Sunshine Act Meetings; Notice
Federal Register 2010, 2011, 2012, 2013, 2014
2010-08-19
...-Gathering Activities. [cir] COV Report Text-Mining. [cir] Design of Research Questions for External Input. [cir] SBE/CISE Text-Mining Projects. [cir] Using a Blog for Informal Input. Committee on Education and...
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2012-01-01
Background In countries where tracking mortality and clinical cause of death are not routinely undertaken, gathering verbal autopsies (VA) is the principal method of estimating cause of death. The most common method for determining probable cause of death from the VA interview is Physician-Certified Verbal Autopsy (PCVA). A recent alternative method to interpret Verbal Autopsy (InterVA) is a computer model using a Bayesian approach to derive posterior probabilities for causes of death, given an a priori distribution at population level and a set of interview-based indicators. The model uses the same input information as PCVA, with the exception of narrative text information, which physicians can consult but which were not inputted into the model. Comparing the results of physician coding with the model, large differences could be due to difficulties in diagnosing malaria, especially in holo-endemic regions. Thus, the aim of the study was to explore whether physicians' access to electronically unavailable narrative text helps to explain the large discrepancy in malaria cause-specific mortality fractions (CSMFs) in physician coding versus the model. Methods Free-texts of electronically available records (N = 5,649) were summarised and incorporated into the InterVA version 3 (InterVA-3) for three sub-groups: (i) a 10%-representative subsample (N = 493) (ii) records diagnosed as malaria by physicians and not by the model (N = 1035), and (iii) records diagnosed by the model as malaria, but not by physicians (N = 332). CSMF results before and after free-text incorporation were compared. Results There were changes of between 5.5-10.2% between models before and after free-text incorporation. No impact on malaria CSMFs was seen in the representative sub-sample, but the proportion of malaria as cause of death increased in the physician sub-sample (2.7%) and saw a large decrease in the InterVA subsample (9.9%). Information on 13/106 indicators appeared at least once in the free-texts that had not been matched to any item in the structured, electronically available portion of the Nouna questionnaire. Discussion Free-texts are helpful in gathering information not adequately captured in VA questionnaires, though access to free-text does not explain differences in physician and model determination of malaria as cause of death. PMID:22353802
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Text line extraction in free style document
NASA Astrophysics Data System (ADS)
Shen, Xiaolu; Liu, Changsong; Ding, Xiaoqing; Zou, Yanming
2009-01-01
This paper addresses to text line extraction in free style document, such as business card, envelope, poster, etc. In free style document, global property such as character size, line direction can hardly be concluded, which reveals a grave limitation in traditional layout analysis. 'Line' is the most prominent and the highest structure in our bottom-up method. First, we apply a novel intensity function found on gradient information to locate text areas where gradient within a window have large magnitude and various directions, and split such areas into text pieces. We build a probability model of lines consist of text pieces via statistics on training data. For an input image, we group text pieces to lines using a simulated annealing algorithm with cost function based on the probability model.
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The Effect of Input-Based Instruction Type on the Acquisition of Spanish Accusative Clitics
ERIC Educational Resources Information Center
White, Justin
2015-01-01
The purpose of this paper is to compare structured input (SI) with other input-based instructional treatments. The input-based instructional types include: input flood (IF), text enhancement (TE), SI activities, and focused input (FI; SI without implicit negative feedback). Participants included 145 adult learners enrolled in an intermediate…
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Creating speech-synchronized animation.
King, Scott A; Parent, Richard E
2005-01-01
We present a facial model designed primarily to support animated speech. Our facial model takes facial geometry as input and transforms it into a parametric deformable model. The facial model uses a muscle-based parameterization, allowing for easier integration between speech synchrony and facial expressions. Our facial model has a highly deformable lip model that is grafted onto the input facial geometry to provide the necessary geometric complexity needed for creating lip shapes and high-quality renderings. Our facial model also includes a highly deformable tongue model that can represent the shapes the tongue undergoes during speech. We add teeth, gums, and upper palate geometry to complete the inner mouth. To decrease the processing time, we hierarchically deform the facial surface. We also present a method to animate the facial model over time to create animated speech using a model of coarticulation that blends visemes together using dominance functions. We treat visemes as a dynamic shaping of the vocal tract by describing visemes as curves instead of keyframes. We show the utility of the techniques described in this paper by implementing them in a text-to-audiovisual-speech system that creates animation of speech from unrestricted text. The facial and coarticulation models must first be interactively initialized. The system then automatically creates accurate real-time animated speech from the input text. It is capable of cheaply producing tremendous amounts of animated speech with very low resource requirements.
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Bradley, D. Nathan
2012-01-01
The slope-area method is a technique for estimating the peak discharge of a flood after the water has receded (Dalrymple and Benson, 1967). This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks (HWMs) on trees or buildings. These indicators of flood stage are combined with measurements of the cross-sectional geometry of the stream, estimates of channel roughness, and a mathematical model that balances the total energy of the flow between cross sections. This is in contrast to a “direct” measurement of discharge during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a gage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the stream gage, resulting in more accurate computation of high flows. The Slope-Area Computation program (SAC; Fulford, 1994) is an implementation of the slope-area method that computes a peak-discharge estimate from inputs of water-surface slope (from surveyed HWMs), channel geometry, and estimated channel roughness. SAC is a command line program written in Fortran that reads input data from a formatted text file and prints results to another formatted text file. Preparing the input file can be time-consuming and prone to errors. This document describes the SAC graphical user interface (GUI), a crossplatform “wrapper” application that prepares the SAC input file, executes the program, and helps the user interpret the output. The SAC GUI is an update and enhancement of the slope-area method (SAM; Hortness, 2004; Berenbrock, 1996), an earlier spreadsheet tool used to aid field personnel in the completion of a slope-area measurement. The SAC GUI reads survey data, develops a plan-view plot, water-surface profile, cross-section plots, and develops the SAC input file. The SAC GUI also develops HEC-2 files that can be imported into HEC–RAS.
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-plaintext.form-control-lg,.form-control-plaintext.form-control-sm,.input-group-lg>.form-control-plaintext.form -control,.input-group-lg>.input-group-append>.form-control-plaintext.btn,.input-group-lg>.input -group-append>.form-control-plaintext.input-group-text,.input-group-lg>.input-group-prepend>
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Semantic classification of business images
NASA Astrophysics Data System (ADS)
Erol, Berna; Hull, Jonathan J.
2006-01-01
Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.
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Applying Suffix Rules to Organization Name Recognition
NASA Astrophysics Data System (ADS)
Inui, Takashi; Murakami, Koji; Hashimoto, Taiichi; Utsumi, Kazuo; Ishikawa, Masamichi
This paper presents a method for boosting the performance of the organization name recognition, which is a part of named entity recognition (NER). Although gazetteers (lists of the NEs) have been known as one of the effective features for supervised machine learning approaches on the NER task, the previous methods which have applied the gazetteers to the NER were very simple. The gazetteers have been used just for searching the exact matches between input text and NEs included in them. The proposed method generates regular expression rules from gazetteers, and, with these rules, it can realize a high-coverage searches based on looser matches between input text and NEs. To generate these rules, we focus on the two well-known characteristics of NE expressions; 1) most of NE expressions can be divided into two parts, class-reference part and instance-reference part, 2) for most of NE expressions the class-reference parts are located at the suffix position of them. A pattern mining algorithm runs on the set of NEs in the gazetteers, and some frequent word sequences from which NEs are constructed are found. Then, we employ only word sequences which have the class-reference part at the suffix position as suffix rules. Experimental results showed that our proposed method improved the performance of the organization name recognition, and achieved the 84.58 F-value for evaluation data.
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Development of EnergyPlus Utility to Batch Simulate Building Energy Performance on a National Scale
DOE Office of Scientific and Technical Information (OSTI.GOV)
Valencia, Jayson F.; Dirks, James A.
2008-08-29
EnergyPlus is a simulation program that requires a large number of details to fully define and model a building. Hundreds or even thousands of lines in a text file are needed to run the EnergyPlus simulation depending on the size of the building. To manually create these files is a time consuming process that would not be practical when trying to create input files for thousands of buildings needed to simulate national building energy performance. To streamline the process needed to create the input files for EnergyPlus, two methods were created to work in conjunction with the National Renewable Energymore » Laboratory (NREL) Preprocessor; this reduced the hundreds of inputs needed to define a building in EnergyPlus to a small set of high-level parameters. The first method uses Java routines to perform all of the preprocessing on a Windows machine while the second method carries out all of the preprocessing on the Linux cluster by using an in-house built utility called Generalized Parametrics (GPARM). A comma delimited (CSV) input file is created to define the high-level parameters for any number of buildings. Each method then takes this CSV file and uses the data entered for each parameter to populate an extensible markup language (XML) file used by the NREL Preprocessor to automatically prepare EnergyPlus input data files (idf) using automatic building routines and macro templates. Using a Linux utility called “make”, the idf files can then be automatically run through the Linux cluster and the desired data from each building can be aggregated into one table to be analyzed. Creating a large number of EnergyPlus input files results in the ability to batch simulate building energy performance and scale the result to national energy consumption estimates.« less
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NASA Astrophysics Data System (ADS)
Fume, Kosei; Ishitani, Yasuto
2008-01-01
We propose a document categorization method based on a document model that can be defined externally for each task and that categorizes Web content or business documents into a target category in accordance with the similarity of the model. The main feature of the proposed method consists of two aspects of semantics extraction from an input document. The semantics of terms are extracted by the semantic pattern analysis and implicit meanings of document substructure are specified by a bottom-up text clustering technique focusing on the similarity of text line attributes. We have constructed a system based on the proposed method for trial purposes. The experimental results show that the system achieves more than 80% classification accuracy in categorizing Web content and business documents into 15 or 70 categories.
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An improved Four-Russians method and sparsified Four-Russians algorithm for RNA folding.
Frid, Yelena; Gusfield, Dan
2016-01-01
The basic RNA secondary structure prediction problem or single sequence folding problem (SSF) was solved 35 years ago by a now well-known [Formula: see text]-time dynamic programming method. Recently three methodologies-Valiant, Four-Russians, and Sparsification-have been applied to speedup RNA secondary structure prediction. The sparsification method exploits two properties of the input: the number of subsequence Z with the endpoints belonging to the optimal folding set and the maximum number base-pairs L. These sparsity properties satisfy [Formula: see text] and [Formula: see text], and the method reduces the algorithmic running time to O(LZ). While the Four-Russians method utilizes tabling partial results. In this paper, we explore three different algorithmic speedups. We first expand the reformulate the single sequence folding Four-Russians [Formula: see text]-time algorithm, to utilize an on-demand lookup table. Second, we create a framework that combines the fastest Sparsification and new fastest on-demand Four-Russians methods. This combined method has worst-case running time of [Formula: see text], where [Formula: see text] and [Formula: see text]. Third we update the Four-Russians formulation to achieve an on-demand [Formula: see text]-time parallel algorithm. This then leads to an asymptotic speedup of [Formula: see text] where [Formula: see text] and [Formula: see text] the number of subsequence with the endpoint j belonging to the optimal folding set. The on-demand formulation not only removes all extraneous computation and allows us to incorporate more realistic scoring schemes, but leads us to take advantage of the sparsity properties. Through asymptotic analysis and empirical testing on the base-pair maximization variant and a more biologically informative scoring scheme, we show that this Sparse Four-Russians framework is able to achieve a speedup on every problem instance, that is asymptotically never worse, and empirically better than achieved by the minimum of the two methods alone.
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Rankin, Johanna C; Lorenz, Eva; Neuhann, Florian; Yé, Maurice; Sié, Ali; Becher, Heiko; Ramroth, Heribert
2012-02-21
In countries where tracking mortality and clinical cause of death are not routinely undertaken, gathering verbal autopsies (VA) is the principal method of estimating cause of death. The most common method for determining probable cause of death from the VA interview is Physician-Certified Verbal Autopsy (PCVA). A recent alternative method to interpret Verbal Autopsy (InterVA) is a computer model using a Bayesian approach to derive posterior probabilities for causes of death, given an a priori distribution at population level and a set of interview-based indicators. The model uses the same input information as PCVA, with the exception of narrative text information, which physicians can consult but which were not inputted into the model. Comparing the results of physician coding with the model, large differences could be due to difficulties in diagnosing malaria, especially in holo-endemic regions. Thus, the aim of the study was to explore whether physicians' access to electronically unavailable narrative text helps to explain the large discrepancy in malaria cause-specific mortality fractions (CSMFs) in physician coding versus the model. Free-texts of electronically available records (N = 5,649) were summarised and incorporated into the InterVA version 3 (InterVA-3) for three sub-groups: (i) a 10%-representative subsample (N = 493) (ii) records diagnosed as malaria by physicians and not by the model (N = 1035), and (iii) records diagnosed by the model as malaria, but not by physicians (N = 332). CSMF results before and after free-text incorporation were compared. There were changes of between 5.5-10.2% between models before and after free-text incorporation. No impact on malaria CSMFs was seen in the representative sub-sample, but the proportion of malaria as cause of death increased in the physician sub-sample (2.7%) and saw a large decrease in the InterVA subsample (9.9%). Information on 13/106 indicators appeared at least once in the free-texts that had not been matched to any item in the structured, electronically available portion of the Nouna questionnaire. Free-texts are helpful in gathering information not adequately captured in VA questionnaires, though access to free-text does not explain differences in physician and model determination of malaria as cause of death.
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Code of Federal Regulations, 2014 CFR
2014-10-01
...: (1) Inputs. Decoders must have the capability to receive at least two audio inputs from EAS... externally, at least two minutes of audio or text messages. A decoder manufactured without an internal means to record and store audio or text must be equipped with a means (such as an audio or digital jack...
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Code of Federal Regulations, 2013 CFR
2013-10-01
...: (1) Inputs. Decoders must have the capability to receive at least two audio inputs from EAS... externally, at least two minutes of audio or text messages. A decoder manufactured without an internal means to record and store audio or text must be equipped with a means (such as an audio or digital jack...
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Code of Federal Regulations, 2012 CFR
2012-10-01
...: (1) Inputs. Decoders must have the capability to receive at least two audio inputs from EAS... externally, at least two minutes of audio or text messages. A decoder manufactured without an internal means to record and store audio or text must be equipped with a means (such as an audio or digital jack...
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2010-09-01
differentiated between source codes and input/output files. The text makes references to a REMChlor-GoldSim model. The text also refers to the REMChlor...To the extent possible, the instructions should be accurate and precise. The documentation should differentiate between describing what is actually...Windows XP operating system Model Input Paran1eters. · n1e input parameters were identical to those utilized and reported by CDM (See Table .I .from
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Electronic collection system for spacelab mission timeline requirements
NASA Technical Reports Server (NTRS)
Lindberg, James P.; Piner, John R.; Huang, Allen K. H.
1995-01-01
This paper describes the Functional Objective Requirements Collection System (FORCS) software tool that has been developed for use by Principal Investigators (PI's) and Payload Element Developers (PED's) on their own personal computers to develop on-orbit timelining requirements for their payloads. The FORCS tool can be used either in a totally stand-alone mode, storing the information in a local file on the user's personal computer hard disk or in a remote mode where the user's computer is linked to a host computer containing the integrated database of the timeline requirements for all of the payloads on a mission. There are a number of features incorporated in the FORCS software to assist the user. The user may move freely back and forth between the various forms for inputting the data. Several methods are used to input the information, depending on the type of the information. These methods range from filling in text boxes, using check boxes and radio buttons, to inputting information into a spreadsheet format. There are automated features provided to assist in developing the proper format for the data, ranging from limit checking on some of the parameters to automatic conversion of different formats of time data inputs to the one standard format used for the timeline scheduling software.
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An open tool for input function estimation and quantification of dynamic PET FDG brain scans.
Bertrán, Martín; Martínez, Natalia; Carbajal, Guillermo; Fernández, Alicia; Gómez, Álvaro
2016-08-01
Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study. Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation. The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with [Formula: see text] relative error in the estimated influx versus ground truth on phantoms. The main contribution of this article is the development of an open-source, free to use tool that encapsulates several well-known methods for the estimation of the input function and the quantification of dynamic PET FDG studies. Some alternative strategies are also proposed and implemented in the tool for the segmentation of blood pools and parameter estimation. The tool was tested on phantoms with encouraging results that suggest that even bloodless estimators could provide a viable alternative to blood sampling for quantification using graphical analysis. The open tool is a promising opportunity for collaboration among investigators and further validation on real studies.
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Robot Task Commander with Extensible Programming Environment
NASA Technical Reports Server (NTRS)
Hart, Stephen W (Inventor); Wightman, Brian J (Inventor); Dinh, Duy Paul (Inventor); Yamokoski, John D. (Inventor); Gooding, Dustin R (Inventor)
2014-01-01
A system for developing distributed robot application-level software includes a robot having an associated control module which controls motion of the robot in response to a commanded task, and a robot task commander (RTC) in networked communication with the control module over a network transport layer (NTL). The RTC includes a script engine(s) and a GUI, with a processor and a centralized library of library blocks constructed from an interpretive computer programming code and having input and output connections. The GUI provides access to a Visual Programming Language (VPL) environment and a text editor. In executing a method, the VPL is opened, a task for the robot is built from the code library blocks, and data is assigned to input and output connections identifying input and output data for each block. A task sequence(s) is sent to the control module(s) over the NTL to command execution of the task.
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Surface vacancies concentration of CeO2(1 1 1) using kinetic Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Mattiello, S.; Kolling, S.; Heiliger, C.
2016-01-01
Kinetic Monte Carlo simulations (kMC) are useful tools for the investigation of the dynamics of surface properties. Within this method we investigate the oxygen vacancy concentration of \\text{Ce}{{\\text{O}}2}(1 1 1) at ultra high vacuum conditions (UHV). In order to achieve first principles calculations the input for the simulations, i.e. energy barriers for the microscopic processes, we use density functional theory (DFT) results from literature. We investigate the possibility of ad- and desorption of oxygen on ceria as well as the diffusion of oxygen vacancies to and from the subsurface. In particular, we focus on the vacancy surface concentration as well as on the ratio of the number of subsurface vacancies to the number of vacancies at the surface. The comparison of our dynamically obtained results to the experimental findings leads to several issues. In conclusion, we can claim a substantial incompatibility of the experimental results and the dynamical calculation using DFT inputs.
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Contribution to Terminology Internationalization by Word Alignment in Parallel Corpora
Deléger, Louise; Merkel, Magnus; Zweigenbaum, Pierre
2006-01-01
Background and objectives Creating a complete translation of a large vocabulary is a time-consuming task, which requires skilled and knowledgeable medical translators. Our goal is to examine to which extent such a task can be alleviated by a specific natural language processing technique, word alignment in parallel corpora. We experiment with translation from English to French. Methods Build a large corpus of parallel, English-French documents, and automatically align it at the document, sentence and word levels using state-of-the-art alignment methods and tools. Then project English terms from existing controlled vocabularies to the aligned word pairs, and examine the number and quality of the putative French translations obtained thereby. We considered three American vocabularies present in the UMLS with three different translation statuses: the MeSH, SNOMED CT, and the MedlinePlus Health Topics. Results We obtained several thousand new translations of our input terms, this number being closely linked to the number of terms in the input vocabularies. Conclusion Our study shows that alignment methods can extract a number of new term translations from large bodies of text with a moderate human reviewing effort, and thus contribute to help a human translator obtain better translation coverage of an input vocabulary. Short-term perspectives include their application to a corpus 20 times larger than that used here, together with more focused methods for term extraction. PMID:17238328
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Ramanujam, Nedunchelian; Kaliappan, Manivannan
2016-01-01
Nowadays, automatic multidocument text summarization systems can successfully retrieve the summary sentences from the input documents. But, it has many limitations such as inaccurate extraction to essential sentences, low coverage, poor coherence among the sentences, and redundancy. This paper introduces a new concept of timestamp approach with Naïve Bayesian Classification approach for multidocument text summarization. The timestamp provides the summary an ordered look, which achieves the coherent looking summary. It extracts the more relevant information from the multiple documents. Here, scoring strategy is also used to calculate the score for the words to obtain the word frequency. The higher linguistic quality is estimated in terms of readability and comprehensibility. In order to show the efficiency of the proposed method, this paper presents the comparison between the proposed methods with the existing MEAD algorithm. The timestamp procedure is also applied on the MEAD algorithm and the results are examined with the proposed method. The results show that the proposed method results in lesser time than the existing MEAD algorithm to execute the summarization process. Moreover, the proposed method results in better precision, recall, and F-score than the existing clustering with lexical chaining approach. PMID:27034971
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Hancock, Matthew C; Magnan, Jerry F
2016-10-01
In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists' annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 [Formula: see text], which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 ([Formula: see text]), which increases to 0.949 ([Formula: see text]) when diameter and volume features are included and has an accuracy of 88.08 [Formula: see text]. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.
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Peeters, Geeske; Barker, Anna L; Talevski, Jason; Ackerman, Ilana; Ayton, Darshini R; Reid, Christopher; Evans, Sue M; Stoelwinder, Johannes U; McNeil, John J
2018-05-01
Patient-reported outcome measures (PROMs) capture health information from the patient's perspective that can be used when weighing up benefits, risks and costs of treatment. This is important for elective procedures such as those for coronary revascularisation. Patients should be involved in the development of PROMs to accurately capture outcomes that are important for the patient. The aims of this review are to identify if patients were involved in the development of cardiovascular-specific PROMs used for assessing outcomes from elective coronary revascularisation, and to explore what methods were used to capture patient perspectives. PROMs for evaluating outcomes from elective coronary revascularisation were identified from a previous review and an updated systematic search. The studies describing the development of the PROMs were reviewed for information on patient input in their conceptual and/or item development. 24 PROMs were identified from a previous review and three additional PROMs were identified from the updated search. Full texts were obtained for 26 of the 27 PROMs. The 26 studies (11 multidimensional, 15 unidimensional) were reviewed. Only nine studies reported developing PROMs using patient input. For eight PROMs, the inclusion of patient input could not be judged due to insufficient information in the full text. Only nine of the 26 reviewed PROMs used in elective coronary revascularisation reported involving patients in their conceptual and/or item development, while patient input was unclear for eight PROMs. These findings suggest that the patient's perspective is often overlooked or poorly described in the development of PROMs.
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Machine-aided indexing at NASA
NASA Technical Reports Server (NTRS)
Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.
1994-01-01
This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.
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Automatic detection and recognition of signs from natural scenes.
Chen, Xilin; Yang, Jie; Zhang, Jing; Waibel, Alex
2004-01-01
In this paper, we present an approach to automatic detection and recognition of signs from natural scenes, and its application to a sign translation task. The proposed approach embeds multiresolution and multiscale edge detection, adaptive searching, color analysis, and affine rectification in a hierarchical framework for sign detection, with different emphases at each phase to handle the text in different sizes, orientations, color distributions and backgrounds. We use affine rectification to recover deformation of the text regions caused by an inappropriate camera view angle. The procedure can significantly improve text detection rate and optical character recognition (OCR) accuracy. Instead of using binary information for OCR, we extract features from an intensity image directly. We propose a local intensity normalization method to effectively handle lighting variations, followed by a Gabor transform to obtain local features, and finally a linear discriminant analysis (LDA) method for feature selection. We have applied the approach in developing a Chinese sign translation system, which can automatically detect and recognize Chinese signs as input from a camera, and translate the recognized text into English.
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Pouplin, Samuel; Roche, Nicolas; Hugeron, Caroline; Vaugier, Isabelle; Bensmail, Djamel
2016-02-01
For people with cervical spinal cord injury (SCI), access to computers can be difficult, thus several devices have been developed to facilitate their use. However, text input speed remains very slow compared to users who do not have a disability, even with these devices. Several methods have been developed to increase text input speed, such as word prediction software (WPS). Health-related professionals (HRP) often recommend this type of software to people with cervical SCI. WPS can be customized using different settings. It is likely that the settings used will influence the effectiveness of the software on text input speed. However, there is currently a lack of literature regarding professional practices for the setting of WPS as well as the impact for users. To analyze word prediction software settings used by HRP for people with cervical SCI. Prospective observational study. Garches, France; health-related professionals who recommend Word Prediction Software. A questionnaire was submitted to HRP who advise tetraplegic people regarding the use of communication devices. A total of 93 professionals responded to the survey. The most frequently recommended software was Skippy, a commercially available software. HRP rated the importance of the possibility to customise the settings as high. Moreover, they rated some settings as more important than others (P<0.001). However, except for the number of words displayed, each setting was configured by less than 50% of HRP. The results showed that there was a difference between the perception of the importance of some settings and data in the literature regarding the optimization of settings. Moreover, although some parameters were considered as very important, they were rarely specifically configured. Confidence in default settings and lack of information regarding optimal settings seem to be the main reasons for this discordance. This could also explain the disparate results of studies which evaluated the impact of WPS on text input speed in people with cervical SCI. The results showed that there was a difference between the perception of the importance of some settings and data in the literature regarding the optimization of settings. Moreover, although some parameters were considered as very important, they were rarely specifically configured. Confidence in default settings and lack of information regarding optimal settings seem to be the main reasons for this discordance. This could also explain the disparate results of studies which evaluated the impact of WPS on text input speed in people with cervical SCI. Professionals tend to have confidence in default settings, despite the fact they are not always appropriate for users. It thus seems essential to develop information networks and training to disseminate the results of studies and in consequence possibly improve communication for people with cervical SCI who use such devices.
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Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.
Duarte, Francisco; Martins, Bruno; Pinto, Cátia Sousa; Silva, Mário J
2018-04-01
We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep neural network that combines word embeddings, recurrent units, and neural attention, for the generation of intermediate representations of the textual contents. The neural network also explores the hierarchical nature of the input data, by building representations from the sequences of words within individual fields, which are then combined according to the sequences of fields that compose the inputs. Moreover, we explore innovative mechanisms for initializing the weights of the final nodes of the network, leveraging co-occurrences between classes together with the hierarchical structure of ICD-10. Experimental results attest to the contribution of the different neural network components. Our best model achieves accuracy scores over 89%, 81%, and 76%, respectively for ICD-10 chapters, blocks, and full-codes. Through examples, we also show that our method can produce interpretable results, useful for public health surveillance. Copyright © 2018 Elsevier Inc. All rights reserved.
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Contribution to terminology internationalization by word alignment in parallel corpora.
Deléger, Louise; Merkel, Magnus; Zweigenbaum, Pierre
2006-01-01
Creating a complete translation of a large vocabulary is a time-consuming task, which requires skilled and knowledgeable medical translators. Our goal is to examine to which extent such a task can be alleviated by a specific natural language processing technique, word alignment in parallel corpora. We experiment with translation from English to French. Build a large corpus of parallel, English-French documents, and automatically align it at the document, sentence and word levels using state-of-the-art alignment methods and tools. Then project English terms from existing controlled vocabularies to the aligned word pairs, and examine the number and quality of the putative French translations obtained thereby. We considered three American vocabularies present in the UMLS with three different translation statuses: the MeSH, SNOMED CT, and the MedlinePlus Health Topics. We obtained several thousand new translations of our input terms, this number being closely linked to the number of terms in the input vocabularies. Our study shows that alignment methods can extract a number of new term translations from large bodies of text with a moderate human reviewing effort, and thus contribute to help a human translator obtain better translation coverage of an input vocabulary. Short-term perspectives include their application to a corpus 20 times larger than that used here, together with more focused methods for term extraction.
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Constraints on the [Formula: see text] form factor from analyticity and unitarity.
Ananthanarayan, B; Caprini, I; Kubis, B
Motivated by the discrepancies noted recently between the theoretical calculations of the electromagnetic [Formula: see text] form factor and certain experimental data, we investigate this form factor using analyticity and unitarity in a framework known as the method of unitarity bounds. We use a QCD correlator computed on the spacelike axis by operator product expansion and perturbative QCD as input, and exploit unitarity and the positivity of its spectral function, including the two-pion contribution that can be reliably calculated using high-precision data on the pion form factor. From this information, we derive upper and lower bounds on the modulus of the [Formula: see text] form factor in the elastic region. The results provide a significant check on those obtained with standard dispersion relations, confirming the existence of a disagreement with experimental data in the region around [Formula: see text].
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Pathologists dislike sound? Evaluation of a computerised training microscope.
Gray, E; Duvall, E; Sprey, J; Bird, C C
1998-01-01
AIM: To evaluate the use of multimedia enhancements, using a computerised microscope, in the training of microscope skills. METHODS: The HOME microscope provides facilities to highlight features of interest in conjunction with either text display or aural presentation. A pilot study was carried out with 10 individuals, eight of whom were at different stages of pathology training. A tutorial was implemented employing sound or text, and each individual tested each version. Both the subjective impressions of users and objective measurement of their patterns of use were recorded. RESULTS: Although both versions improved learning, users took longer to work through the aural than the text version; 90% of users preferred the text only version, including all eight individuals involved in pathology training. CONCLUSIONS: Pathologists appear to prefer visual rather than aural input when using teaching systems such as the HOME microscope and sound does not give added value to the training experience. Images PMID:9659250
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NASA's online machine aided indexing system
NASA Technical Reports Server (NTRS)
Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.
1993-01-01
This report describes the NASA Lexical Dictionary, a machine aided indexing system used online at the National Aeronautics and Space Administration's Center for Aerospace Information (CASI). This system is comprised of a text processor that is based on the computational, non-syntactic analysis of input text, and an extensive 'knowledge base' that serves to recognize and translate text-extracted concepts. The structure and function of the various NLD system components are described in detail. Methods used for the development of the knowledge base are discussed. Particular attention is given to a statistically-based text analysis program that provides the knowledge base developer with a list of concept-specific phrases extracted from large textual corpora. Production and quality benefits resulting from the integration of machine aided indexing at CASI are discussed along with a number of secondary applications of NLD-derived systems including on-line spell checking and machine aided lexicography.
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Self-aligning and compressed autosophy video databases
NASA Astrophysics Data System (ADS)
Holtz, Klaus E.
1993-04-01
Autosophy, an emerging new science, explains `self-assembling structures,' such as crystals or living trees, in mathematical terms. This research provides a new mathematical theory of `learning' and a new `information theory' which permits the growing of self-assembling data network in a computer memory similar to the growing of `data crystals' or `data trees' without data processing or programming. Autosophy databases are educated very much like a human child to organize their own internal data storage. Input patterns, such as written questions or images, are converted to points in a mathematical omni dimensional hyperspace. The input patterns are then associated with output patterns, such as written answers or images. Omni dimensional information storage will result in enormous data compression because each pattern fragment is only stored once. Pattern recognition in the text or image files is greatly simplified by the peculiar omni dimensional storage method. Video databases will absorb input images from a TV camera and associate them with textual information. The `black box' operations are totally self-aligning where the input data will determine their own hyperspace storage locations. Self-aligning autosophy databases may lead to a new generation of brain-like devices.
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A pilot study comparing mouse and mouse-emulating interface devices for graphic input.
Kanny, E M; Anson, D K
1991-01-01
Adaptive interface devices make it possible for individuals with physical disabilities to use microcomputers and thus perform many tasks that they would otherwise be unable to accomplish. Special equipment is available that purports to allow functional access to the computer for users with disabilities. As technology moves from purely keyboard applications to include graphic input, it will be necessary for assistive interface devices to support graphics as well as text entry. Headpointing systems that emulate the mouse in combination with on-screen keyboards are of particular interest to persons with severe physical impairment such as high level quadriplegia. Two such systems currently on the market are the HeadMaster and the Free Wheel. The authors have conducted a pilot study comparing graphic input speed using the mouse and two headpointing interface systems on the Macintosh computer. The study used a single subject design with six able-bodied subjects, to establish a baseline for comparison with persons with severe disabilities. Results of these preliminary data indicated that the HeadMaster was nearly as effective as the mouse and that it was superior to the Free Wheel for graphics input. This pilot study, however, demonstrated several experimental design problems that need to be addressed to make the study more robust. It also demonstrated the need to include the evaluation of text input so that the effectiveness of the interface devices with text and graphic input could be compared.
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Terminologies for text-mining; an experiment in the lipoprotein metabolism domain
Alexopoulou, Dimitra; Wächter, Thomas; Pickersgill, Laura; Eyre, Cecilia; Schroeder, Michael
2008-01-01
Background The engineering of ontologies, especially with a view to a text-mining use, is still a new research field. There does not yet exist a well-defined theory and technology for ontology construction. Many of the ontology design steps remain manual and are based on personal experience and intuition. However, there exist a few efforts on automatic construction of ontologies in the form of extracted lists of terms and relations between them. Results We share experience acquired during the manual development of a lipoprotein metabolism ontology (LMO) to be used for text-mining. We compare the manually created ontology terms with the automatically derived terminology from four different automatic term recognition (ATR) methods. The top 50 predicted terms contain up to 89% relevant terms. For the top 1000 terms the best method still generates 51% relevant terms. In a corpus of 3066 documents 53% of LMO terms are contained and 38% can be generated with one of the methods. Conclusions Given high precision, automatic methods can help decrease development time and provide significant support for the identification of domain-specific vocabulary. The coverage of the domain vocabulary depends strongly on the underlying documents. Ontology development for text mining should be performed in a semi-automatic way; taking ATR results as input and following the guidelines we described. Availability The TFIDF term recognition is available as Web Service, described at PMID:18460175
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NASA Astrophysics Data System (ADS)
Tajik, Jehangir K.; Kugelmass, Steven D.; Hoffman, Eric A.
1993-07-01
We have developed a method utilizing x-ray CT for relating pulmonary perfusion to global and regional anatomy, allowing for detailed study of structure to function relationships. A thick slice, high temporal resolution mode is used to follow a bolus contrast agent for blood flow evaluation and is fused with a high spatial resolution, thin slice mode to obtain structure- function detail. To aid analysis of blood flow, we have developed a software module, for our image analysis package (VIDA), to produce the combined structure-function image. Color coded images representing blood flow, mean transit time, regional tissue content, regional blood volume, regional air content, etc. are generated and imbedded in the high resolution volume image. A text file containing these values along with a voxel's 3-D coordinates is also generated. User input can be minimized to identifying the location of the pulmonary artery from which the input function to a blood flow model is derived. Any flow model utilizing one input and one output function can be easily added to a user selectable list. We present examples from our physiologic based research findings to demonstrate the strengths of combining dynamic CT and HRCT relative to other scanning modalities to uniquely characterize pulmonary normal and pathophysiology.
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Towards a Relation Extraction Framework for Cyber-Security Concepts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, Corinne L; Bridges, Robert A; Huffer, Kelly M
In order to assist security analysts in obtaining information pertaining to their network, such as novel vulnerabilities, exploits, or patches, information retrieval methods tailored to the security domain are needed. As labeled text data is scarce and expensive, we follow developments in semi-supervised NLP and implement a bootstrapping algorithm for extracting security entities and their relationships from text. The algorithm requires little input data, specifically, a few relations or patterns (heuristics for identifying relations), and incorporates an active learning component which queries the user on the most important decisions to prevent drifting the desired relations. Preliminary testing on a smallmore » corpus shows promising results, obtaining precision of .82.« less
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Ultrasound image-based thyroid nodule automatic segmentation using convolutional neural networks.
Ma, Jinlian; Wu, Fa; Jiang, Tian'an; Zhao, Qiyu; Kong, Dexing
2017-11-01
Delineation of thyroid nodule boundaries from ultrasound images plays an important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it is challenging for accurate and automatic segmentation of thyroid nodules because of their heterogeneous appearance and components similar to the background. In this study, we employ a deep convolutional neural network (CNN) to automatically segment thyroid nodules from ultrasound images. Our CNN-based method formulates a thyroid nodule segmentation problem as a patch classification task, where the relationship among patches is ignored. Specifically, the CNN used image patches from images of normal thyroids and thyroid nodules as inputs and then generated the segmentation probability maps as outputs. A multi-view strategy is used to improve the performance of the CNN-based model. Additionally, we compared the performance of our approach with that of the commonly used segmentation methods on the same dataset. The experimental results suggest that our proposed method outperforms prior methods on thyroid nodule segmentation. Moreover, the results show that the CNN-based model is able to delineate multiple nodules in thyroid ultrasound images accurately and effectively. In detail, our CNN-based model can achieve an average of the overlap metric, dice ratio, true positive rate, false positive rate, and modified Hausdorff distance as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] on overall folds, respectively. Our proposed method is fully automatic without any user interaction. Quantitative results also indicate that our method is so efficient and accurate that it can be good enough to replace the time-consuming and tedious manual segmentation approach, demonstrating the potential clinical applications.
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Generalized minimum dominating set and application in automatic text summarization
NASA Astrophysics Data System (ADS)
Xu, Yi-Zhi; Zhou, Hai-Jun
2016-03-01
For a graph formed by vertices and weighted edges, a generalized minimum dominating set (MDS) is a vertex set of smallest cardinality such that the summed weight of edges from each outside vertex to vertices in this set is equal to or larger than certain threshold value. This generalized MDS problem reduces to the conventional MDS problem in the limiting case of all the edge weights being equal to the threshold value. We treat the generalized MDS problem in the present paper by a replica-symmetric spin glass theory and derive a set of belief-propagation equations. As a practical application we consider the problem of extracting a set of sentences that best summarize a given input text document. We carry out a preliminary test of the statistical physics-inspired method to this automatic text summarization problem.
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Input analysis for two public consultations on the EU Clinical Trials Regulation.
Langhof, Holger; Lander, Jonas; Strech, Daniel
2016-09-17
The European Union's (EU) Clinical Trials Directive was replaced by an EU-Regulation as of 2016. The policy revision process was subject to a formal impact assessment exercised by the European Commission (EC) from 2008 to 2014. Following the EU principles of Good Governance, deliberation with stakeholders was an integral part of this impact assessment and the policy formulation process. Hence, two public consultations (PCs) were held by the EC in 2009 and 2011, respectively. Various stakeholders contributed and submitted their written input to the EC. Though often cited in the further revision process, the input gathered in the PC was not communicated with full transparency and it is unclear how and to what extent the input has been processed and used in the policy formulation. The objective of this study was an analysis of submissions to both PCs in order to systematically present what topics have been discussed and which possible policy options have been raised by the stakeholders. All written submissions publicly available were downloaded from the EC's homepage and assessed for stakeholder characteristics. Thematic text analysis was applied to assess the full text of a random sample of 33% of these submissions. A total of 198 different stakeholders from the EU and the United States of America contributed to one or both of the two PCs. In total, 44 various themes have been addressed that could be clustered under 24 main themes, including the articulation of problems as well as possible policy solutions to face these problems. The two PCs on the Clinical Trials Directive were highly appreciated by the various stakeholders and their input allowed an in-depth view on their particular interests. This input provided a rich source of information for all stakeholders in the field of clinical trials as well as to the EC's impact assessment. Although the EC obviously gathered a large quantity of expert knowledge on practical implications of trials legislation by consulting stakeholders, it remained unclear how this input was used in the development of the new regulation. For the sake of transparency, it is recommended that in future PCs the EC uses better standardized methods for a more transparent analysis and presentation of results.
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Text Simplification and Comprehensible Input: A Case for an Intuitive Approach
ERIC Educational Resources Information Center
Crossley, Scott A.; Allen, David; McNamara, Danielle S.
2012-01-01
Texts are routinely simplified to make them more comprehensible for second language learners. However, the effects of simplification upon the linguistic features of texts remain largely unexplored. Here we examine the effects of one type of text simplification: intuitive text simplification. We use the computational tool, Coh-Metrix, to examine…
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NASA Technical Reports Server (NTRS)
Kotler, R. S.
1983-01-01
File Comparator program IFCOMP, is text file comparator for IBM OS/VScompatable systems. IFCOMP accepts as input two text files and produces listing of differences in pseudo-update form. IFCOMP is very useful in monitoring changes made to software at the source code level.
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Books Online: Visions, Plans, and Perspectives for Electronic Text.
ERIC Educational Resources Information Center
Basch, Reva
1991-01-01
Discussion of current applications of and future possibilities for electronic text, or e-text, focuses on activities in the area of higher education. Topics covered are input technology, including optical scanners and keyboarding; standardization; copyright issues; access to e-text through networks; user interface; hypertext; software; shareware;…
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Information Extraction for Clinical Data Mining: A Mammography Case Study
Nassif, Houssam; Woods, Ryan; Burnside, Elizabeth; Ayvaci, Mehmet; Shavlik, Jude; Page, David
2013-01-01
Breast cancer is the leading cause of cancer mortality in women between the ages of 15 and 54. During mammography screening, radiologists use a strict lexicon (BI-RADS) to describe and report their findings. Mammography records are then stored in a well-defined database format (NMD). Lately, researchers have applied data mining and machine learning techniques to these databases. They successfully built breast cancer classifiers that can help in early detection of malignancy. However, the validity of these models depends on the quality of the underlying databases. Unfortunately, most databases suffer from inconsistencies, missing data, inter-observer variability and inappropriate term usage. In addition, many databases are not compliant with the NMD format and/or solely consist of text reports. BI-RADS feature extraction from free text and consistency checks between recorded predictive variables and text reports are crucial to addressing this problem. We describe a general scheme for concept information retrieval from free text given a lexicon, and present a BI-RADS features extraction algorithm for clinical data mining. It consists of a syntax analyzer, a concept finder and a negation detector. The syntax analyzer preprocesses the input into individual sentences. The concept finder uses a semantic grammar based on the BI-RADS lexicon and the experts’ input. It parses sentences detecting BI-RADS concepts. Once a concept is located, a lexical scanner checks for negation. Our method can handle multiple latent concepts within the text, filtering out ultrasound concepts. On our dataset, our algorithm achieves 97.7% precision, 95.5% recall and an F1-score of 0.97. It outperforms manual feature extraction at the 5% statistical significance level. PMID:23765123
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Information Extraction for Clinical Data Mining: A Mammography Case Study.
Nassif, Houssam; Woods, Ryan; Burnside, Elizabeth; Ayvaci, Mehmet; Shavlik, Jude; Page, David
2009-01-01
Breast cancer is the leading cause of cancer mortality in women between the ages of 15 and 54. During mammography screening, radiologists use a strict lexicon (BI-RADS) to describe and report their findings. Mammography records are then stored in a well-defined database format (NMD). Lately, researchers have applied data mining and machine learning techniques to these databases. They successfully built breast cancer classifiers that can help in early detection of malignancy. However, the validity of these models depends on the quality of the underlying databases. Unfortunately, most databases suffer from inconsistencies, missing data, inter-observer variability and inappropriate term usage. In addition, many databases are not compliant with the NMD format and/or solely consist of text reports. BI-RADS feature extraction from free text and consistency checks between recorded predictive variables and text reports are crucial to addressing this problem. We describe a general scheme for concept information retrieval from free text given a lexicon, and present a BI-RADS features extraction algorithm for clinical data mining. It consists of a syntax analyzer, a concept finder and a negation detector. The syntax analyzer preprocesses the input into individual sentences. The concept finder uses a semantic grammar based on the BI-RADS lexicon and the experts' input. It parses sentences detecting BI-RADS concepts. Once a concept is located, a lexical scanner checks for negation. Our method can handle multiple latent concepts within the text, filtering out ultrasound concepts. On our dataset, our algorithm achieves 97.7% precision, 95.5% recall and an F 1 -score of 0.97. It outperforms manual feature extraction at the 5% statistical significance level.
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"Look What I Did!": Student Conferences with Text-to-Speech Software
ERIC Educational Resources Information Center
Young, Chase; Stover, Katie
2014-01-01
The authors describe a strategy that empowers students to edit and revise their own writing. Students input their writing in to text-to-speech software that rereads the text aloud. While listening, students make necessary revisions and edits.
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Using clustering and a modified classification algorithm for automatic text summarization
NASA Astrophysics Data System (ADS)
Aries, Abdelkrime; Oufaida, Houda; Nouali, Omar
2013-01-01
In this paper we describe a modified classification method destined for extractive summarization purpose. The classification in this method doesn't need a learning corpus; it uses the input text to do that. First, we cluster the document sentences to exploit the diversity of topics, then we use a learning algorithm (here we used Naive Bayes) on each cluster considering it as a class. After obtaining the classification model, we calculate the score of a sentence in each class, using a scoring model derived from classification algorithm. These scores are used, then, to reorder the sentences and extract the first ones as the output summary. We conducted some experiments using a corpus of scientific papers, and we have compared our results to another summarization system called UNIS.1 Also, we experiment the impact of clustering threshold tuning, on the resulted summary, as well as the impact of adding more features to the classifier. We found that this method is interesting, and gives good performance, and the addition of new features (which is simple using this method) can improve summary's accuracy.
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76 FR 63575 - Transportation Conformity Rule: MOVES Regional Grace Period Extension
Federal Register 2010, 2011, 2012, 2013, 2014
2011-10-13
... written in FORTRAN and used simple text files for data input and output, MOVES2010a is written in JAVA and uses a relational database structure in MYSQL to handle input and output as data tables. These changes...
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76 FR 63554 - Transportation Conformity Rule: MOVES Regional Grace Period Extension
Federal Register 2010, 2011, 2012, 2013, 2014
2011-10-13
... written in FORTRAN and used simple text files for data input and output, MOVES2010a is written in JAVA and uses a relational database structure in MYSQL to handle input and output as data tables. These changes...
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77 FR 11394 - Transportation Conformity Rule: MOVES Regional Grace Period Extension
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-27
... written in FORTRAN and used simple text files for data input and output, MOVES is written in JAVA and uses a relational database structure in MYSQL to handle input and output as data tables.\\13\\ \\13\\ Some...
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Rectification of curved document images based on single view three-dimensional reconstruction.
Kang, Lai; Wei, Yingmei; Jiang, Jie; Bai, Liang; Lao, Songyang
2016-10-01
Since distortions in camera-captured document images significantly affect the accuracy of optical character recognition (OCR), distortion removal plays a critical role for document digitalization systems using a camera for image capturing. This paper proposes a novel framework that performs three-dimensional (3D) reconstruction and rectification of camera-captured document images. While most existing methods rely on additional calibrated hardware or multiple images to recover the 3D shape of a document page, or make a simple but not always valid assumption on the corresponding 3D shape, our framework is more flexible and practical since it only requires a single input image and is able to handle a general locally smooth document surface. The main contributions of this paper include a new iterative refinement scheme for baseline fitting from connected components of text line, an efficient discrete vertical text direction estimation algorithm based on convex hull projection profile analysis, and a 2D distortion grid construction method based on text direction function estimation using 3D regularization. In order to examine the performance of our proposed method, both qualitative and quantitative evaluation and comparison with several recent methods are conducted in our experiments. The experimental results demonstrate that the proposed method outperforms relevant approaches for camera-captured document image rectification, in terms of improvements on both visual distortion removal and OCR accuracy.
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External-Compression Supersonic Inlet Design Code
NASA Technical Reports Server (NTRS)
Slater, John W.
2011-01-01
A computer code named SUPIN has been developed to perform aerodynamic design and analysis of external-compression, supersonic inlets. The baseline set of inlets include axisymmetric pitot, two-dimensional single-duct, axisymmetric outward-turning, and two-dimensional bifurcated-duct inlets. The aerodynamic methods are based on low-fidelity analytical and numerical procedures. The geometric methods are based on planar geometry elements. SUPIN has three modes of operation: 1) generate the inlet geometry from a explicit set of geometry information, 2) size and design the inlet geometry and analyze the aerodynamic performance, and 3) compute the aerodynamic performance of a specified inlet geometry. The aerodynamic performance quantities includes inlet flow rates, total pressure recovery, and drag. The geometry output from SUPIN includes inlet dimensions, cross-sectional areas, coordinates of planar profiles, and surface grids suitable for input to grid generators for analysis by computational fluid dynamics (CFD) methods. The input data file for SUPIN and the output file from SUPIN are text (ASCII) files. The surface grid files are output as formatted Plot3D or stereolithography (STL) files. SUPIN executes in batch mode and is available as a Microsoft Windows executable and Fortran95 source code with a makefile for Linux.
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Time Series Neural Network Model for Part-of-Speech Tagging Indonesian Language
NASA Astrophysics Data System (ADS)
Tanadi, Theo
2018-03-01
Part-of-speech tagging (POS tagging) is an important part in natural language processing. Many methods have been used to do this task, including neural network. This paper models a neural network that attempts to do POS tagging. A time series neural network is modelled to solve the problems that a basic neural network faces when attempting to do POS tagging. In order to enable the neural network to have text data input, the text data will get clustered first using Brown Clustering, resulting a binary dictionary that the neural network can use. To further the accuracy of the neural network, other features such as the POS tag, suffix, and affix of previous words would also be fed to the neural network.
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A pipelined FPGA implementation of an encryption algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Thirer, Nonel
2013-05-01
With the evolution of digital data storage and exchange, it is essential to protect the confidential information from every unauthorized access. High performance encryption algorithms were developed and implemented by software and hardware. Also many methods to attack the cipher text were developed. In the last years, the genetic algorithm has gained much interest in cryptanalysis of cipher texts and also in encryption ciphers. This paper analyses the possibility to use the genetic algorithm as a multiple key sequence generator for an AES (Advanced Encryption Standard) cryptographic system, and also to use a three stages pipeline (with four main blocks: Input data, AES Core, Key generator, Output data) to provide a fast encryption and storage/transmission of a large amount of data.
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Kietrys, David M; Gerg, Michael J; Dropkin, Jonathan; Gold, Judith E
2015-09-01
This study aimed to determine the effects of input device type, texting style, and screen size on upper extremity and trapezius muscle activity and cervical posture during a short texting task in college students. Users of a physical keypad produced greater thumb, finger flexor, and wrist extensor muscle activity than when texting with a touch screen device of similar dimensions. Texting on either device produced greater wrist extensor muscle activity when texting with 1 hand/thumb compared with both hands/thumbs. As touch screen size increased, more participants held the device on their lap, and chose to use both thumbs less. There was also a trend for greater finger flexor, wrist extensor, and trapezius muscle activity as touch screen size increased, and for greater cervical flexion, although mean differences for cervical flexion were small. Future research can help inform whether the ergonomic stressors observed during texting are associated with musculoskeletal disorder risk. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
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A linear-RBF multikernel SVM to classify big text corpora.
Romero, R; Iglesias, E L; Borrajo, L
2015-01-01
Support vector machine (SVM) is a powerful technique for classification. However, SVM is not suitable for classification of large datasets or text corpora, because the training complexity of SVMs is highly dependent on the input size. Recent developments in the literature on the SVM and other kernel methods emphasize the need to consider multiple kernels or parameterizations of kernels because they provide greater flexibility. This paper shows a multikernel SVM to manage highly dimensional data, providing an automatic parameterization with low computational cost and improving results against SVMs parameterized under a brute-force search. The model consists in spreading the dataset into cohesive term slices (clusters) to construct a defined structure (multikernel). The new approach is tested on different text corpora. Experimental results show that the new classifier has good accuracy compared with the classic SVM, while the training is significantly faster than several other SVM classifiers.
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Input current shaped ac-to-dc converters
NASA Technical Reports Server (NTRS)
1985-01-01
Input current shaping techniques for ac-to-dc converters were investigated. Input frequencies much higher than normal, up to 20 kHz were emphasized. Several methods of shaping the input current waveform in ac-to-dc converters were reviewed. The simplest method is the LC filter following the rectifier. The next simplest method is the resistor emulation approach in which the inductor size is determined by the converter switching frequency and not by the line input frequency. Other methods require complicated switch drive algorithms to construct the input current waveshape. For a high-frequency line input, on the order of 20 kHz, the simple LC cannot be discarded so peremptorily, since the inductor size can be compared with that for the resistor emulation method. In fact, since a dc regulator will normally be required after the filter anyway, the total component count is almost the same as for the resistor emulation method, in which the filter is effectively incorporated into the regulator.
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Evaluation of Piloted Inputs for Onboard Frequency Response Estimation
NASA Technical Reports Server (NTRS)
Grauer, Jared A.; Martos, Borja
2013-01-01
Frequency response estimation results are presented using piloted inputs and a real-time estimation method recently developed for multisine inputs. A nonlinear simulation of the F-16 and a Piper Saratoga research aircraft were subjected to different piloted test inputs while the short period stabilator/elevator to pitch rate frequency response was estimated. Results show that the method can produce accurate results using wide-band piloted inputs instead of multisines. A new metric is introduced for evaluating which data points to include in the analysis and recommendations are provided for applying this method with piloted inputs.
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Field Research Facility Data Integration Framework Data Management Plan: Survey Lines Dataset
2016-08-01
CHL and its District partners. The beach morphology surveys on which this report focuses provide quantitative measures of the dynamic nature of...topography • volume change 1.4 Data description The morphology surveys are conducted over a series of 26 shore- perpendicular profile lines spaced 50...dataset input data and products. Table 1. FRF survey lines dataset input data and products. Input Data FDIF Product Description ASCII LARC survey text
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A computer program (MACPUMP) for interactive aquifer-test analysis
Day-Lewis, F. D.; Person, M.A.; Konikow, Leonard F.
1995-01-01
This report introduces MACPUMP (Version 1.0), an aquifer-test-analysis package for use with Macintosh4 computers. The report outlines the input- data format, describes the solutions encoded in the program, explains the menu-items, and offers a tutorial illustrating the use of the program. The package reads list-directed aquifer-test data from a file, plots the data to the screen, generates and plots type curves for several different test conditions, and allows mouse-controlled curve matching. MACPUMP features pull-down menus, a simple text viewer for displaying data-files, and optional on-line help windows. This version includes the analytical solutions for nonleaky and leaky confined aquifers, using both type curves and straight-line methods, and for the analysis of single-well slug tests using type curves. An executable version of the code and sample input data sets are included on an accompanying floppy disk.
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NASA Technical Reports Server (NTRS)
1981-01-01
The set of computer programs described allows for data definition, data input, and data transfer between the LSI-11 microcomputers and the VAX-11/780 minicomputer. Program VAXCOM allows for a simple method of textual file transfer from the LSI to the VAX. Program LSICOM allows for easy file transfer from the VAX to the LSI. Program TTY changes the LSI-11 operators console to the LSI's printing device. Program DICTIN provides a means for defining a data set for input to either computer. Program DATAIN is a simple to operate data entry program which is capable of building data files on either machine. Program LEDITV is an extremely powerful, easy to use, line oriented text editor. Program COPYSBF is designed to print out textual files on the line printer without character loss from FORTRAN carriage control or wide record transfer.
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Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Aben, R; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimoto, G; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Alimonti, G; Alio, L; Alison, J; Alkire, S P; Allbrooke, B M M; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Altheimer, A; Alvarez Gonzalez, B; Piqueras, D Álvarez; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoki, M; Aperio Bella, L; Arabidze, G; Arai, Y; Araque, J P; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Auerbach, B; Augsten, K; Aurousseau, M; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Bacci, C; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Badescu, E; Bagiacchi, P; Bagnaia, P; Bai, Y; Bain, T; Baines, J T; Baker, O K; Balek, P; Balestri, T; Balli, F; Banas, E; Banerjee, Sw; Bannoura, A A E; Bansil, H S; Barak, L; Baranov, S P; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska, Z; Baroncelli, A; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Bartoldus, R; Barton, A E; Bartos, P; Bassalat, A; Basye, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, K; Becker, M; Becker, S; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Beringer, J; Bernard, C; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertsche, C; Bertsche, D; Besana, M I; Besjes, G J; Bessidskaia Bylund, O; Bessner, M; Besson, N; Betancourt, C; Bethke, S; Bevan, A J; Bhimji, W; Bianchi, R M; Bianchini, L; Bianco, M; Biebel, O; Bieniek, S P; Biglietti, M; Bilbao De Mendizabal, J; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Black, C W; Black, J E; Black, K M; Blackburn, D; Blair, R E; Blanchard, J-B; Blanco, J E; Blazek, T; Bloch, I; Blocker, C; Blum, W; Blumenschein, U; Bobbink, G J; Bobrovnikov, V S; Bocchetta, S S; Bocci, A; Bock, C; Boehler, M; Bogaerts, J A; Bogdanchikov, A G; Bohm, C; Boisvert, V; Bold, T; Boldea, V; Boldyrev, A S; Bomben, M; Bona, M; Boonekamp, M; Borisov, A; Borissov, G; Borroni, S; Bortfeldt, J; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Boudreau, J; Bouffard, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Bousson, N; Boveia, A; Boyd, J; Boyko, I R; Bozic, I; Bracinik, J; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Brazzale, S F; Brendlinger, K; Brennan, A J; Brenner, L; Brenner, R; Bressler, S; Bristow, K; Bristow, T M; Britton, D; Britzger, D; Brochu, F M; 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A search for the Standard Model Higgs boson produced in association with a top-quark pair, [Formula: see text], is presented. The analysis uses 20.3 fb -1 of pp collision data at [Formula: see text], collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the [Formula: see text] decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b -tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominated by [Formula: see text]+jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible [Formula: see text] background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level. The ratio of the measured [Formula: see text] signal cross section to the Standard Model expectation is found to be [Formula: see text] assuming a Higgs boson mass of 125[Formula: see text].
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Chen, Zhe; Rau, Pei-Luen Patrick
2017-03-01
This study presented two experiments on Chinese handwriting performance (time, accuracy, the number of protruding strokes and number of rewritings) and subjective ratings (mental workload, satisfaction, and preference) on mobile devices. Experiment 1 evaluated the effects of size of the input box, input method and display size on Chinese handwriting performance and preference. It was indicated that the optimal input sizes were 30.8 × 30.8 mm, 46.6 × 46.6 mm, 58.9 × 58.9 mm and 84.6 × 84.6 mm for devices with 3.5-inch, 5.5-inch, 7.0-inch and 9.7-inch display sizes, respectively. Experiment 2 proved the significant effects of location of the input box, input method and display size on Chinese handwriting performance and subjective ratings. It was suggested that the optimal location was central regardless of display size and input method. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Using automatically extracted information from mammography reports for decision-support
Bozkurt, Selen; Gimenez, Francisco; Burnside, Elizabeth S.; Gulkesen, Kemal H.; Rubin, Daniel L.
2016-01-01
Objective To evaluate a system we developed that connects natural language processing (NLP) for information extraction from narrative text mammography reports with a Bayesian network for decision-support about breast cancer diagnosis. The ultimate goal of this system is to provide decision support as part of the workflow of producing the radiology report. Materials and methods We built a system that uses an NLP information extraction system (which extract BI-RADS descriptors and clinical information from mammography reports) to provide the necessary inputs to a Bayesian network (BN) decision support system (DSS) that estimates lesion malignancy from BI-RADS descriptors. We used this integrated system to predict diagnosis of breast cancer from radiology text reports and evaluated it with a reference standard of 300 mammography reports. We collected two different outputs from the DSS: (1) the probability of malignancy and (2) the BI-RADS final assessment category. Since NLP may produce imperfect inputs to the DSS, we compared the difference between using perfect (“reference standard”) structured inputs to the DSS (“RS-DSS”) vs NLP-derived inputs (“NLP-DSS”) on the output of the DSS using the concordance correlation coefficient. We measured the classification accuracy of the BI-RADS final assessment category when using NLP-DSS, compared with the ground truth category established by the radiologist. Results The NLP-DSS and RS-DSS had closely matched probabilities, with a mean paired difference of 0.004 ± 0.025. The concordance correlation of these paired measures was 0.95. The accuracy of the NLP-DSS to predict the correct BI-RADS final assessment category was 97.58%. Conclusion The accuracy of the information extracted from mammography reports using the NLP system was sufficient to provide accurate DSS results. We believe our system could ultimately reduce the variation in practice in mammography related to assessment of malignant lesions and improve management decisions. PMID:27388877
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Covey, Curt; Lucas, Donald D.; Tannahill, John; ...
2013-07-01
Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less
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Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli
Aljadeff, Johnatan; Segev, Ronen; Berry, Michael J.; Sharpee, Tatyana O.
2013-01-01
Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons. PMID:24039563
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Text Characteristics of Task Input and Difficulty in Second Language Listening Comprehension
ERIC Educational Resources Information Center
Revesz, Andrea; Brunfaut, Tineke
2013-01-01
This study investigated the effects of a group of task factors on advanced English as a second language learners' actual and perceived listening performance. We examined whether the speed, linguistic complexity, and explicitness of the listening text along with characteristics of the text necessary for task completion influenced comprehension. We…
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Literary Texts and Grammar Instruction: Revisiting the Inductive Presentation
ERIC Educational Resources Information Center
Paesani, Kate
2005-01-01
This article outlines an approach to explicit grammar instruction that uses literary texts as comprehensible, meaning-bearing input. In this approach, which employs strategies from the teaching of grammar and the teaching of reading, literary texts serve as the basis of the inductive presentation of new grammatical forms and as a springboard for…
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Application of diffusion maps to identify human factors of self-reported anomalies in aviation.
Andrzejczak, Chris; Karwowski, Waldemar; Mikusinski, Piotr
2012-01-01
A study investigating what factors are present leading to pilots submitting voluntary anomaly reports regarding their flight performance was conducted. Diffusion Maps (DM) were selected as the method of choice for performing dimensionality reduction on text records for this study. Diffusion Maps have seen successful use in other domains such as image classification and pattern recognition. High-dimensionality data in the form of narrative text reports from the NASA Aviation Safety Reporting System (ASRS) were clustered and categorized by way of dimensionality reduction. Supervised analyses were performed to create a baseline document clustering system. Dimensionality reduction techniques identified concepts or keywords within records, and allowed the creation of a framework for an unsupervised document classification system. Results from the unsupervised clustering algorithm performed similarly to the supervised methods outlined in the study. The dimensionality reduction was performed on 100 of the most commonly occurring words within 126,000 text records describing commercial aviation incidents. This study demonstrates that unsupervised machine clustering and organization of incident reports is possible based on unbiased inputs. Findings from this study reinforced traditional views on what factors contribute to civil aviation anomalies, however, new associations between previously unrelated factors and conditions were also found.
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A Path to Formative Assessment through Naturalistic Inputs
ERIC Educational Resources Information Center
Cohen, Jonathan; Leroux, Audrey
2017-01-01
This paper reports on the development of a system in which naturalistic inputs are collected by a web-based e-reader and, in combination with a measurement of readers' comprehension of that text, are analyzed by a neural network to determine the nature of the relationship between the annotations and comprehension. Results showed that neural…
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NASA Technical Reports Server (NTRS)
Jones, Denise R.
1990-01-01
A piloted simulation study was conducted comparing three different input methods for interfacing to a large-screen, multiwindow, whole-flight-deck display for management of transport aircraft systems. The thumball concept utilized a miniature trackball embedded in a conventional side-arm controller. The touch screen concept provided data entry through a capacitive touch screen. The voice concept utilized a speech recognition system with input through a head-worn microphone. No single input concept emerged as the most desirable method of interacting with the display. Subjective results, however, indicate that the voice concept was the most preferred method of data entry and had the most potential for future applications. The objective results indicate that, overall, the touch screen concept was the most effective input method. There was also significant differences between the time required to perform specific tasks and the input concept employed, with each concept providing better performance relative to a specific task. These results suggest that a system combining all three input concepts might provide the most effective method of interaction.
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Robust binarization of degraded document images using heuristics
NASA Astrophysics Data System (ADS)
Parker, Jon; Frieder, Ophir; Frieder, Gideon
2013-12-01
Historically significant documents are often discovered with defects that make them difficult to read and analyze. This fact is particularly troublesome if the defects prevent software from performing an automated analysis. Image enhancement methods are used to remove or minimize document defects, improve software performance, and generally make images more legible. We describe an automated, image enhancement method that is input page independent and requires no training data. The approach applies to color or greyscale images with hand written script, typewritten text, images, and mixtures thereof. We evaluated the image enhancement method against the test images provided by the 2011 Document Image Binarization Contest (DIBCO). Our method outperforms all 2011 DIBCO entrants in terms of average F1 measure - doing so with a significantly lower variance than top contest entrants. The capability of the proposed method is also illustrated using select images from a collection of historic documents stored at Yad Vashem Holocaust Memorial in Israel.
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ERIC Educational Resources Information Center
Van Laere, E.; Braak, J.
2017-01-01
Text-to-speech technology can act as an important support tool in computer-based learning environments (CBLEs) as it provides auditory input, next to on-screen text. Particularly for students who use a language at home other than the language of instruction (LOI) applied at school, text-to-speech can be useful. The CBLE E-Validiv offers content in…
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System and method to determine electric motor efficiency nonintrusively
Lu, Bin [Kenosha, WI; Habetler, Thomas G [Snellville, GA; Harley, Ronald G [Lawrenceville, GA
2011-08-30
A system and method for nonintrusively determining electric motor efficiency includes a processor programed to, while the motor is in operation, determine a plurality of stator input currents, electrical input data, a rotor speed, a value of stator resistance, and an efficiency of the motor based on the determined rotor speed, the value of stator resistance, the plurality of stator input currents, and the electrical input data. The determination of the rotor speed is based on one of the input power and the plurality of stator input currents. The determination of the value of the stator resistance is based on at least one of a horsepower rating and a combination of the plurality of stator input currents and the electrical input data. The electrical input data includes at least one of an input power and a plurality of stator input voltages.
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Introducing Explorer of Taxon Concepts with a case study on spider measurement matrix building.
Cui, Hong; Xu, Dongfang; Chong, Steven S; Ramirez, Martin; Rodenhausen, Thomas; Macklin, James A; Ludäscher, Bertram; Morris, Robert A; Soto, Eduardo M; Koch, Nicolás Mongiardino
2016-11-17
Taxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings. From the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix. ETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the automated reuse of the published knowledge. The tools will be updated to support new requirements revealed in this case study.
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Full-text, Downloading, & Other Issues.
ERIC Educational Resources Information Center
Tenopir, Carol
1983-01-01
Issues having a possible impact on online search services in libraries are discussed including full text databases, front-end processors which translate user's input into the command language of an appropriate system, downloading to create personal files from commercial databases, and pricing. (EJS)
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System and methods for reducing harmonic distortion in electrical converters
Kajouke, Lateef A; Perisic, Milun; Ransom, Ray M
2013-12-03
Systems and methods are provided for delivering energy using an energy conversion module. An exemplary method for delivering energy from an input interface to an output interface using an energy converison module coupled between the input interface and the output interface comprises the steps of determining an input voltage reference for the input interface based on a desired output voltage and a measured voltage and the output interface, determining a duty cycle control value based on a ratio of the input voltage reference and the measured voltage, operating one or more switching elements of the energy conversion module to deliver energy from the input interface to the output interface to the output interface with a duty cycle influenced by the dute cycle control value.
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Step-control of electromechanical systems
Lewis, Robert N.
1979-01-01
The response of an automatic control system to a general input signal is improved by applying a test input signal, observing the response to the test input signal and determining correctional constants necessary to provide a modified input signal to be added to the input to the system. A method is disclosed for determining correctional constants. The modified input signal, when applied in conjunction with an operating signal, provides a total system output exhibiting an improved response. This method is applicable to open-loop or closed-loop control systems. The method is also applicable to unstable systems, thus allowing controlled shut-down before dangerous or destructive response is achieved and to systems whose characteristics vary with time, thus resulting in improved adaptive systems.
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ERIC Educational Resources Information Center
Chiang, Min-Hsun
2016-01-01
This study investigated the effects of varying text difficulty on L2 reading attitudes and reading comprehension. To provide the optimal challenge for L2 reading, comprehensible input hypothesis postulates that choosing text slightly harder than the learner's current level will enhance reading comprehension. Fifty-four freshmen from one university…
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Analytic uncertainty and sensitivity analysis of models with input correlations
NASA Astrophysics Data System (ADS)
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
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Mokhtari, Amirhossein; Christopher Frey, H; Zheng, Junyu
2006-11-01
Sensitivity analyses of exposure or risk models can help identify the most significant factors to aid in risk management or to prioritize additional research to reduce uncertainty in the estimates. However, sensitivity analysis is challenged by non-linearity, interactions between inputs, and multiple days or time scales. Selected sensitivity analysis methods are evaluated with respect to their applicability to human exposure models with such features using a testbed. The testbed is a simplified version of a US Environmental Protection Agency's Stochastic Human Exposure and Dose Simulation (SHEDS) model. The methods evaluated include the Pearson and Spearman correlation, sample and rank regression, analysis of variance, Fourier amplitude sensitivity test (FAST), and Sobol's method. The first five methods are known as "sampling-based" techniques, wheras the latter two methods are known as "variance-based" techniques. The main objective of the test cases was to identify the main and total contributions of individual inputs to the output variance. Sobol's method and FAST directly quantified these measures of sensitivity. Results show that sensitivity of an input typically changed when evaluated under different time scales (e.g., daily versus monthly). All methods provided similar insights regarding less important inputs; however, Sobol's method and FAST provided more robust insights with respect to sensitivity of important inputs compared to the sampling-based techniques. Thus, the sampling-based methods can be used in a screening step to identify unimportant inputs, followed by application of more computationally intensive refined methods to a smaller set of inputs. The implications of time variation in sensitivity results for risk management are briefly discussed.
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Bradley, D. Nathan
2013-01-01
The peak discharge of a flood can be estimated from the elevation of high-water marks near the inlet and outlet of a culvert after the flood has occurred. This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks on trees or buildings. When combined with the cross-sectional geometry of the channel upstream from the culvert and the culvert size, shape, roughness, and orientation, the high-water marks define a water-surface profile that can be used to estimate the peak discharge by using the methods described by Bodhaine (1968). This type of measurement is in contrast to a “direct” measurement of discharge made during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a streamgage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the streamgage, resulting in more accurate computation of high flows. The Culvert Analysis Program (CAP) (Fulford, 1998) is a command-line program written in Fortran for computing peak discharges and culvert rating surfaces or curves. CAP reads input data from a formatted text file and prints results to another formatted text file. Preparing and correctly formatting the input file may be time-consuming and prone to errors. This document describes the CAP graphical user interface (GUI)—a modern, cross-platform, menu-driven application that prepares the CAP input file, executes the program, and helps the user interpret the output
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FSH: fast spaced seed hashing exploiting adjacent hashes.
Girotto, Samuele; Comin, Matteo; Pizzi, Cinzia
2018-01-01
Patterns with wildcards in specified positions, namely spaced seeds , are increasingly used instead of k -mers in many bioinformatics applications that require indexing, querying and rapid similarity search, as they can provide better sensitivity. Many of these applications require to compute the hashing of each position in the input sequences with respect to the given spaced seed, or to multiple spaced seeds. While the hashing of k -mers can be rapidly computed by exploiting the large overlap between consecutive k -mers, spaced seeds hashing is usually computed from scratch for each position in the input sequence, thus resulting in slower processing. The method proposed in this paper, fast spaced-seed hashing (FSH), exploits the similarity of the hash values of spaced seeds computed at adjacent positions in the input sequence. In our experiments we compute the hash for each positions of metagenomics reads from several datasets, with respect to different spaced seeds. We also propose a generalized version of the algorithm for the simultaneous computation of multiple spaced seeds hashing. In the experiments, our algorithm can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.6[Formula: see text] to 5.3[Formula: see text], depending on the structure of the spaced seed. Spaced seed hashing is a routine task for several bioinformatics application. FSH allows to perform this task efficiently and raise the question of whether other hashing can be exploited to further improve the speed up. This has the potential of major impact in the field, making spaced seed applications not only accurate, but also faster and more efficient. The software FSH is freely available for academic use at: https://bitbucket.org/samu661/fsh/overview.
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Vocabulary Learning through Viewing Video: The Effect of Two Enhancement Techniques
ERIC Educational Resources Information Center
Montero Perez, Maribel; Peters, Elke; Desmet, Piet
2018-01-01
While most studies on L2 vocabulary learning through input have addressed learners' vocabulary uptake from written text, this study focuses on audio-visual input. In particular, we investigate the effects of enhancing video by (1) adding different types of L2 subtitling (i.e. no captioning, full captioning, keyword captioning, and glossed keyword…
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Dynamic control modification techniques in teleoperation of a flexible manipulator. M.S. Thesis
NASA Technical Reports Server (NTRS)
Magee, David Patrick
1991-01-01
The objective of this research is to reduce the end-point vibration of a large, teleoperated manipulator while preserving the usefulness of the system motion. A master arm is designed to measure desired joint angles as the user specifies a desired tip motion. The desired joint angles from the master arm are the inputs to an adaptive PD control algorithm that positions the end-point of the manipulator. As the user moves the tip of the master, the robot will vibrate at its natural frequencies which makes it difficult to position the end-point. To eliminate the tip vibration during teleoperated motions, an input shaping method is presented. The input shaping method transforms each sample of the desired input into a new set of impulses that do not excite the system resonances. The method is explained using the equation of motion for a simple, second-order system. The impulse response of such a system is derived and the constraint equations for vibrationless motion are presented. To evaluate the robustness of the method, a different residual vibration equation from Singer's is derived that more accurately represents the input shaping technique. The input shaping method is shown to actually increase the residual vibration in certain situations when the system parameters are not accurately specified. Finally, the implementation of the input shaping method to a system with varying parameters is shown to induce a vibration into the system. To eliminate this vibration, a modified command shaping technique is developed. The ability of the modified command shaping method to reduce vibration at the system resonances is tested by varying input perturbations to trajectories in a range of possible user inputs. By comparing the frequency responses of the transverse acceleration at the end-point of the manipulator, the modified method is compared to the original PD routine. The control scheme that produces the smaller magnitude of resonant vibration at the first natural frequency is considered the more effective control method.
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Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn; Lin, Guang, E-mail: guanglin@purdue.edu
2016-07-15
In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.
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Hybrid neural network for density limit disruption prediction and avoidance on J-TEXT tokamak
NASA Astrophysics Data System (ADS)
Zheng, W.; Hu, F. R.; Zhang, M.; Chen, Z. Y.; Zhao, X. Q.; Wang, X. L.; Shi, P.; Zhang, X. L.; Zhang, X. Q.; Zhou, Y. N.; Wei, Y. N.; Pan, Y.; J-TEXT team
2018-05-01
Increasing the plasma density is one of the key methods in achieving an efficient fusion reaction. High-density operation is one of the hot topics in tokamak plasmas. Density limit disruptions remain an important issue for safe operation. An effective density limit disruption prediction and avoidance system is the key to avoid density limit disruptions for long pulse steady state operations. An artificial neural network has been developed for the prediction of density limit disruptions on the J-TEXT tokamak. The neural network has been improved from a simple multi-layer design to a hybrid two-stage structure. The first stage is a custom network which uses time series diagnostics as inputs to predict plasma density, and the second stage is a three-layer feedforward neural network to predict the probability of density limit disruptions. It is found that hybrid neural network structure, combined with radiation profile information as an input can significantly improve the prediction performance, especially the average warning time ({{T}warn} ). In particular, the {{T}warn} is eight times better than that in previous work (Wang et al 2016 Plasma Phys. Control. Fusion 58 055014) (from 5 ms to 40 ms). The success rate for density limit disruptive shots is above 90%, while, the false alarm rate for other shots is below 10%. Based on the density limit disruption prediction system and the real-time density feedback control system, the on-line density limit disruption avoidance system has been implemented on the J-TEXT tokamak.
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Applications of information theory, genetic algorithms, and neural models to predict oil flow
NASA Astrophysics Data System (ADS)
Ludwig, Oswaldo; Nunes, Urbano; Araújo, Rui; Schnitman, Leizer; Lepikson, Herman Augusto
2009-07-01
This work introduces a new information-theoretic methodology for choosing variables and their time lags in a prediction setting, particularly when neural networks are used in non-linear modeling. The first contribution of this work is the Cross Entropy Function (XEF) proposed to select input variables and their lags in order to compose the input vector of black-box prediction models. The proposed XEF method is more appropriate than the usually applied Cross Correlation Function (XCF) when the relationship among the input and output signals comes from a non-linear dynamic system. The second contribution is a method that minimizes the Joint Conditional Entropy (JCE) between the input and output variables by means of a Genetic Algorithm (GA). The aim is to take into account the dependence among the input variables when selecting the most appropriate set of inputs for a prediction problem. In short, theses methods can be used to assist the selection of input training data that have the necessary information to predict the target data. The proposed methods are applied to a petroleum engineering problem; predicting oil production. Experimental results obtained with a real-world dataset are presented demonstrating the feasibility and effectiveness of the method.
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Jung, Sung-Jin; Hong, Seong-Kwan; Kwon, Oh-Kyong
2017-02-01
This paper presents a low-noise amplifier (LNA) using attenuation-adaptive noise control (AANC) for ultrasound imaging systems. The proposed AANC reduces unnecessary power consumption of the LNA, which arises from useless noise floor, by controlling the noise floor of the LNA with respect to the attenuation of the ultrasound. In addition, a current feedback amplifier with a source-degenerated input stage reduces variations of the bandwidth and the closed loop gain, which are caused by the AANC. The proposed LNA was fabricated using a 0.18-[Formula: see text] CMOS process. The input-referred voltage noise density of the fabricated LNA is 1.01 [Formula: see text] at the frequency of 5 MHz. The second harmonic distortion is -53.5 dB when the input signal frequency is 5 MHz and the output voltage swing is 2 [Formula: see text]. The power consumption of the LNA using the AANC is 16.2 mW at the supply voltage of 1.8 V, which is reduced to 64% of that without using the AANC. The noise efficiency factor (NEF) of the proposed LNA is 3.69, to our knowledge, which is the lowest NEF compared with previous LNAs for ultrasound imaging.
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System, method and apparatus for generating phrases from a database
NASA Technical Reports Server (NTRS)
McGreevy, Michael W. (Inventor)
2004-01-01
A phrase generation is a method of generating sequences of terms, such as phrases, that may occur within a database of subsets containing sequences of terms, such as text. A database is provided and a relational model of the database is created. A query is then input. The query includes a term or a sequence of terms or multiple individual terms or multiple sequences of terms or combinations thereof. Next, several sequences of terms that are contextually related to the query are assembled from contextual relations in the model of the database. The sequences of terms are then sorted and output. Phrase generation can also be an iterative process used to produce sequences of terms from a relational model of a database.
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Chen, Jingjun; Luo, Rong; Liu, Huashan
2017-08-01
With the development of ICT, digital writing is becoming much more common in people's life. Differently from keyboarding alphabets directly to input English words, keyboarding Chinese character is always through typing phonetic alphabets and then identify the glyph provided by Pinyin input-method software while in this process which do not need users to produce orthography spelling, thus it is different from traditional written language production model based on handwriting process. Much of the research in this domain has found that using Pinyin input method is beneficial to Chinese characters recognition, but only a small part explored the effects of individual's Pinyin input experience on the Chinese characters production process. We ask whether using Pinyin input-method will strengthen the semantic-phonology linkage or semantic-orthography linkage in Chinese character mental lexicon. Through recording the RT and accuracy of participants completing semantic-syllable and semantic-glyph consistency judgments, the results found the accuracy of semantic-syllable consistency judgments in high Pinyin input experienced group was higher than that in low-experienced group, and RT was reversed. There were no significant differences on semantic-glyph consistency judgments between the two groups. We conclude that using Pinyin input method in Chinese digital writing can strengthen the semantic-phonology linkage while do not weakening the semantic-orthography linkage in mental lexicon at the same time, which means that Pinyin input method is beneficial to lexical processing involving Chinese cognition.
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A supertree pipeline for summarizing phylogenetic and taxonomic information for millions of species
Redelings, Benjamin D.
2017-01-01
We present a new supertree method that enables rapid estimation of a summary tree on the scale of millions of leaves. This supertree method summarizes a collection of input phylogenies and an input taxonomy. We introduce formal goals and criteria for such a supertree to satisfy in order to transparently and justifiably represent the input trees. In addition to producing a supertree, our method computes annotations that describe which grouping in the input trees support and conflict with each group in the supertree. We compare our supertree construction method to a previously published supertree construction method by assessing their performance on input trees used to construct the Open Tree of Life version 4, and find that our method increases the number of displayed input splits from 35,518 to 39,639 and decreases the number of conflicting input splits from 2,760 to 1,357. The new supertree method also improves on the previous supertree construction method in that it produces no unsupported branches and avoids unnecessary polytomies. This pipeline is currently used by the Open Tree of Life project to produce all of the versions of project’s “synthetic tree” starting at version 5. This software pipeline is called “propinquity”. It relies heavily on “otcetera”—a set of C++ tools to perform most of the steps of the pipeline. All of the components are free software and are available on GitHub. PMID:28265520
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Force estimation from OCT volumes using 3D CNNs.
Gessert, Nils; Beringhoff, Jens; Otte, Christoph; Schlaefer, Alexander
2018-07-01
Estimating the interaction forces of instruments and tissue is of interest, particularly to provide haptic feedback during robot-assisted minimally invasive interventions. Different approaches based on external and integrated force sensors have been proposed. These are hampered by friction, sensor size, and sterilizability. We investigate a novel approach to estimate the force vector directly from optical coherence tomography image volumes. We introduce a novel Siamese 3D CNN architecture. The network takes an undeformed reference volume and a deformed sample volume as an input and outputs the three components of the force vector. We employ a deep residual architecture with bottlenecks for increased efficiency. We compare the Siamese approach to methods using difference volumes and two-dimensional projections. Data were generated using a robotic setup to obtain ground-truth force vectors for silicon tissue phantoms as well as porcine tissue. Our method achieves a mean average error of [Formula: see text] when estimating the force vector. Our novel Siamese 3D CNN architecture outperforms single-path methods that achieve a mean average error of [Formula: see text]. Moreover, the use of volume data leads to significantly higher performance compared to processing only surface information which achieves a mean average error of [Formula: see text]. Based on the tissue dataset, our methods shows good generalization in between different subjects. We propose a novel image-based force estimation method using optical coherence tomography. We illustrate that capturing the deformation of subsurface structures substantially improves force estimation. Our approach can provide accurate force estimates in surgical setups when using intraoperative optical coherence tomography.
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MeSH indexing based on automatically generated summaries.
Jimeno-Yepes, Antonio J; Plaza, Laura; Mork, James G; Aronson, Alan R; Díaz, Alberto
2013-06-26
MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading.
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JAva GUi for Applied Research (JAGUAR) v 3.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
JAGUAR is a Java software tool for automatically rendering a graphical user interface (GUI) from a structured input specification. It is designed as a plug-in to the Eclipse workbench to enable users to create, edit, and externally execute analysis application input decks and then view the results. JAGUAR serves as a GUI for Sandia's DAKOTA software toolkit for optimization and uncertainty quantification. It will include problem (input deck)set-up, option specification, analysis execution, and results visualization. Through the use of wizards, templates, and views, JAGUAR helps uses navigate the complexity of DAKOTA's complete input specification. JAGUAR is implemented in Java, leveragingmore » Eclipse extension points and Eclipse user interface. JAGUAR parses a DAKOTA NIDR input specification and presents the user with linked graphical and plain text representations of problem set-up and option specification for DAKOTA studies. After the data has been input by the user, JAGUAR generates one or more input files for DAKOTA, executes DAKOTA, and captures and interprets the results« less
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NIH Seeks Input on In-patient Clinical Research Areas | Division of Cancer Prevention
[[{"fid":"2476","view_mode":"default","fields":{"format":"default","field_file_image_alt_text[und][0][value]":"Aerial view of the National Institutes of Health Clinical Center (Building 10) in Bethesda, Maryland.","field_file_image_title_text[und][0][value]":false},"type":"media","field_deltas":{"1":{"format":"default","field_file_image_alt_text[und][0][value]":"Aerial view of
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Chapman, Wendy W; Christensen, Lee M; Wagner, Michael M; Haug, Peter J; Ivanov, Oleg; Dowling, John N; Olszewski, Robert T
2005-01-01
Develop and evaluate a natural language processing application for classifying chief complaints into syndromic categories for syndromic surveillance. Much of the input data for artificial intelligence applications in the medical field are free-text patient medical records, including dictated medical reports and triage chief complaints. To be useful for automated systems, the free-text must be translated into encoded form. We implemented a biosurveillance detection system from Pennsylvania to monitor the 2002 Winter Olympic Games. Because input data was in free-text format, we used a natural language processing text classifier to automatically classify free-text triage chief complaints into syndromic categories used by the biosurveillance system. The classifier was trained on 4700 chief complaints from Pennsylvania. We evaluated the ability of the classifier to classify free-text chief complaints into syndromic categories with a test set of 800 chief complaints from Utah. The classifier produced the following areas under the ROC curve: Constitutional = 0.95; Gastrointestinal = 0.97; Hemorrhagic = 0.99; Neurological = 0.96; Rash = 1.0; Respiratory = 0.99; Other = 0.96. Using information stored in the system's semantic model, we extracted from the Respiratory classifications lower respiratory complaints and lower respiratory complaints with fever with a precision of 0.97 and 0.96, respectively. Results suggest that a trainable natural language processing text classifier can accurately extract data from free-text chief complaints for biosurveillance.
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Lacerda, Thaisa Cardoso; von Wangenheim, Christiane Gresse; von Wangenheim, Aldo; Giuliano, Isabela
2014-12-01
One of the main reasons that leads to a low adoption rate of telemedicine systems is poor usability. An aspect that influences usability during the reporting of findings is the input mode, e.g., if a free-text (FT) or a structured report (SR) interface is employed. The objective of our study is to compare the usability of FT and ST telemedicine systems, specifically in terms of user satisfaction, efficiency and general usability. We comparatively evaluate the usability of these two input modes in a telecardiology system for issuing electrocardiography reports in the context of a statewide telemedicine system in Brazil with more than 350.000 performed tele-electrocardiography examinations. We adopted a multiple method research strategy, applying three different kinds of usability evaluations: user satisfaction was evaluated through interviews with seven medical professionals using the System Usability Scale (SUS) questionnaire and specific questions related to adequacy and user experience. Efficiency was evaluated by estimating execution time using the Keystroke-Level Model (KLM). General usability was assessed based on the conformity of the systems to a set of e-health specific usability heuristics. The results of this comparison provide a first indication that a structured report (SR) input mode for such a system is more satisfactory and efficient with a larger conformity to usability heuristics than free-text (FT) input. User satisfaction using the SUS questionnaire has been scored in average with 58.8 and 77.5 points for the FT and SR system, respectively, which means that the SR system was rated 18.65 points higher than the FT system. In terms of efficiency, the completion of a findings report using the SR mode is estimated to take 8.5s, 3.74 times faster than using the FT system (31.8s). The SR system also demonstrated less violations to usability heuristics (8 points) in comparison to 14 points observed in the FT system. These results provide a first indication that the usage of structured reporting as an input mode in telecardiology systems may enhance usability. This also seems to confirm the advantages of the usage of structured reporting, as already described in the literature for other areas such as teleradiology. Copyright © 2014 Elsevier Inc. All rights reserved.
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Cooper, Gregory F.; Miller, Randolph A.
1998-01-01
Abstract Objective: A primary goal of the University of Pittsburgh's 1990-94 UMLS-sponsored effort was to develop and evaluate PostDoc (a lexical indexing system) and Pindex (a statistical indexing system) comparatively, and then in combination as a hybrid system. Each system takes as input a portion of the free text from a narrative part of a patient's electronic medical record and returns a list of suggested MeSH terms to use in formulating a Medline search that includes concepts in the text. This paper describes the systems and reports an evaluation. The intent is for this evaluation to serve as a step toward the eventual realization of systems that assist healthcare personnel in using the electronic medical record to construct patient-specific searches of Medline. Design: The authors tested the performances of PostDoc, Pindex, and a hybrid system, using text taken from randomly selected clinical records, which were stratified to include six radiology reports, six pathology reports, and six discharge summaries. They identified concepts in the clinical records that might conceivably be used in performing a patient-specific Medline search. Each system was given the free text of each record as an input. The extent to which a system-derived list of MeSH terms captured the relevant concepts in these documents was determined based on blinded assessments by the authors. Results: PostDoc output a mean of approximately 19 MeSH terms per report, which included about 40% of the relevant report concepts. Pindex output a mean of approximately 57 terms per report and captured about 45% of the relevant report concepts. A hybrid system captured approximately 66% of the relevant concepts and output about 71 terms per report. Conclusion: The outputs of PostDoc and Pindex are complementary in capturing MeSH terms from clinical free text. The results suggest possible approaches to reduce the number of terms output while maintaining the percentage of terms captured, including the use of UMLS semantic types to constrain the output list to contain only clinically relevant MeSH terms. PMID:9452986
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Liu, Da; Xu, Ming; Niu, Dongxiao; Wang, Shoukai; Liang, Sai
2016-01-01
Traditional forecasting models fit a function approximation from dependent invariables to independent variables. However, they usually get into trouble when date are presented in various formats, such as text, voice and image. This study proposes a novel image-encoded forecasting method that input and output binary digital two-dimensional (2D) images are transformed from decimal data. Omitting any data analysis or cleansing steps for simplicity, all raw variables were selected and converted to binary digital images as the input of a deep learning model, convolutional neural network (CNN). Using shared weights, pooling and multiple-layer back-propagation techniques, the CNN was adopted to locate the nexus among variations in local binary digital images. Due to the computing capability that was originally developed for binary digital bitmap manipulation, this model has significant potential for forecasting with vast volume of data. The model was validated by a power loads predicting dataset from the Global Energy Forecasting Competition 2012.
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Xu, Ming; Niu, Dongxiao; Wang, Shoukai; Liang, Sai
2016-01-01
Traditional forecasting models fit a function approximation from dependent invariables to independent variables. However, they usually get into trouble when date are presented in various formats, such as text, voice and image. This study proposes a novel image-encoded forecasting method that input and output binary digital two-dimensional (2D) images are transformed from decimal data. Omitting any data analysis or cleansing steps for simplicity, all raw variables were selected and converted to binary digital images as the input of a deep learning model, convolutional neural network (CNN). Using shared weights, pooling and multiple-layer back-propagation techniques, the CNN was adopted to locate the nexus among variations in local binary digital images. Due to the computing capability that was originally developed for binary digital bitmap manipulation, this model has significant potential for forecasting with vast volume of data. The model was validated by a power loads predicting dataset from the Global Energy Forecasting Competition 2012. PMID:27281032
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Method of fuzzy inference for one class of MISO-structure systems with non-singleton inputs
NASA Astrophysics Data System (ADS)
Sinuk, V. G.; Panchenko, M. V.
2018-03-01
In fuzzy modeling, the inputs of the simulated systems can receive both crisp values and non-Singleton. Computational complexity of fuzzy inference with fuzzy non-Singleton inputs corresponds to an exponential. This paper describes a new method of inference, based on the theorem of decomposition of a multidimensional fuzzy implication and a fuzzy truth value. This method is considered for fuzzy inputs and has a polynomial complexity, which makes it possible to use it for modeling large-dimensional MISO-structure systems.
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ERIC Educational Resources Information Center
Gorsuch, Greta; Taguchi, Etsuo; Umehara, Hiroaki
2015-01-01
A perennial challenge to second language educators and learners is getting sufficient input in settings where the L2 is not widely used, in this case beginning-level American university students learning Japanese. Reading is a significant means of getting L2 input, with recent calls for attention to reading and authentic texts as curriculum…
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Text Enhancement and the Acquisition of English Verbal Inflection "-s" by L1 Haitian Creole Speakers
ERIC Educational Resources Information Center
De Santis, Paulina
2008-01-01
This article contributes to the growing body of research investigating the effects of drawing learner attention to the problematic aspects of the linguistic input in the context of meaning-focused instruction. One specific approach to concentrate learner attention on form in the written input is known as textual enhancement. The pilot study…
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tESA: a distributional measure for calculating semantic relatedness.
Rybinski, Maciej; Aldana-Montes, José Francisco
2016-12-28
Semantic relatedness is a measure that quantifies the strength of a semantic link between two concepts. Often, it can be efficiently approximated with methods that operate on words, which represent these concepts. Approximating semantic relatedness between texts and concepts represented by these texts is an important part of many text and knowledge processing tasks of crucial importance in the ever growing domain of biomedical informatics. The problem of most state-of-the-art methods for calculating semantic relatedness is their dependence on highly specialized, structured knowledge resources, which makes these methods poorly adaptable for many usage scenarios. On the other hand, the domain knowledge in the Life Sciences has become more and more accessible, but mostly in its unstructured form - as texts in large document collections, which makes its use more challenging for automated processing. In this paper we present tESA, an extension to a well known Explicit Semantic Relatedness (ESA) method. In our extension we use two separate sets of vectors, corresponding to different sections of the articles from the underlying corpus of documents, as opposed to the original method, which only uses a single vector space. We present an evaluation of Life Sciences domain-focused applicability of both tESA and domain-adapted Explicit Semantic Analysis. The methods are tested against a set of standard benchmarks established for the evaluation of biomedical semantic relatedness quality. Our experiments show that the propsed method achieves results comparable with or superior to the current state-of-the-art methods. Additionally, a comparative discussion of the results obtained with tESA and ESA is presented, together with a study of the adaptability of the methods to different corpora and their performance with different input parameters. Our findings suggest that combined use of the semantics from different sections (i.e. extending the original ESA methodology with the use of title vectors) of the documents of scientific corpora may be used to enhance the performance of a distributional semantic relatedness measures, which can be observed in the largest reference datasets. We also present the impact of the proposed extension on the size of distributional representations.
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Forecasting hotspots using predictive visual analytics approach
Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David
2014-12-30
A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.
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CARE3MENU- A CARE III USER FRIENDLY INTERFACE
NASA Technical Reports Server (NTRS)
Pierce, J. L.
1994-01-01
CARE3MENU generates an input file for the CARE III program. CARE III is used for reliability prediction of complex, redundant, fault-tolerant systems including digital computers, aircraft, nuclear and chemical control systems. The CARE III input file often becomes complicated and is not easily formatted with a text editor. CARE3MENU provides an easy, interactive method of creating an input file by automatically formatting a set of user-supplied inputs for the CARE III system. CARE3MENU provides detailed on-line help for most of its screen formats. The reliability model input process is divided into sections using menu-driven screen displays. Each stage, or set of identical modules comprising the model, must be identified and described in terms of number of modules, minimum number of modules for stage operation, and critical fault threshold. The fault handling and fault occurence models are detailed in several screens by parameters such as transition rates, propagation and detection densities, Weibull or exponential characteristics, and model accuracy. The system fault tree and critical pairs fault tree screens are used to define the governing logic and to identify modules affected by component failures. Additional CARE3MENU screens prompt the user for output options and run time control values such as mission time and truncation values. There are fourteen major screens, many with default values and HELP options. The documentation includes: 1) a users guide with several examples of CARE III models, the dialog required to input them to CARE3MENU, and the output files created; and 2) a maintenance manual for assistance in changing the HELP files and modifying any of the menu formats or contents. CARE3MENU is written in FORTRAN 77 for interactive execution and has been implemented on a DEC VAX series computer operating under VMS. This program was developed in 1985.
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Magnetic resonance imaging compatible remote catheter navigation system with 3 degrees of freedom.
Tavallaei, M A; Lavdas, M K; Gelman, D; Drangova, M
2016-08-01
To facilitate MRI-guided catheterization procedures, we present an MRI-compatible remote catheter navigation system that allows remote navigation of steerable catheters with 3 degrees of freedom. The system consists of a user interface (master), a robot (slave), and an ultrasonic motor control servomechanism. The interventionalist applies conventional motions (axial, radial and plunger manipulations) on an input catheter in the master unit; this user input is measured and used by the servomechanism to control a compact catheter manipulating robot, such that it replicates the interventionalist's input motion on the patient catheter. The performance of the system was evaluated in terms of MRI compatibility (SNR and artifact), feasibility of remote navigation under real-time MRI guidance, and motion replication accuracy. Real-time MRI experiments demonstrated that catheter was successfully navigated remotely to desired target references in all 3 degrees of freedom. The system had an absolute value error of [Formula: see text]1 mm in axial catheter motion replication over 30 mm of travel and [Formula: see text] for radial catheter motion replication over [Formula: see text]. The worst case SNR drop was observed to be [Formula: see text]3 %; the robot did not introduce any artifacts in the MR images. An MRI-compatible compact remote catheter navigation system has been developed that allows remote navigation of steerable catheters with 3 degrees of freedom. The proposed system allows for safe and accurate remote catheter navigation, within conventional closed-bore scanners, without degrading MR image quality.
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Cao, Hui; Yan, Xingyu; Li, Yaojiang; Wang, Yanxia; Zhou, Yan; Yang, Sanchun
2014-01-01
Quantitative analysis for the flue gas of natural gas-fired generator is significant for energy conservation and emission reduction. The traditional partial least squares method may not deal with the nonlinear problems effectively. In the paper, a nonlinear partial least squares method with extended input based on radial basis function neural network (RBFNN) is used for components prediction of flue gas. For the proposed method, the original independent input matrix is the input of RBFNN and the outputs of hidden layer nodes of RBFNN are the extension term of the original independent input matrix. Then, the partial least squares regression is performed on the extended input matrix and the output matrix to establish the components prediction model of flue gas. A near-infrared spectral dataset of flue gas of natural gas combustion is used for estimating the effectiveness of the proposed method compared with PLS. The experiments results show that the root-mean-square errors of prediction values of the proposed method for methane, carbon monoxide, and carbon dioxide are, respectively, reduced by 4.74%, 21.76%, and 5.32% compared to those of PLS. Hence, the proposed method has higher predictive capabilities and better robustness.
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DC/DC Converter Stability Testing Study
NASA Technical Reports Server (NTRS)
Wang, Bright L.
2008-01-01
This report presents study results on hybrid DC/DC converter stability testing methods. An input impedance measurement method and a gain/phase margin measurement method were evaluated to be effective to determine front-end oscillation and feedback loop oscillation. In particular, certain channel power levels of converter input noises have been found to have high degree correlation with the gain/phase margins. It becomes a potential new method to evaluate stability levels of all type of DC/DC converters by utilizing the spectral analysis on converter input noises.
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NASA Technical Reports Server (NTRS)
Srivastava, Ashok, N.; Akella, Ram; Diev, Vesselin; Kumaresan, Sakthi Preethi; McIntosh, Dawn M.; Pontikakis, Emmanuel D.; Xu, Zuobing; Zhang, Yi
2006-01-01
This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0-
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Lee, Yoojin; Callaghan, Martina F; Nagy, Zoltan
2017-01-01
In magnetic resonance imaging, precise measurements of longitudinal relaxation time ( T 1 ) is crucial to acquire useful information that is applicable to numerous clinical and neuroscience applications. In this work, we investigated the precision of T 1 relaxation time as measured using the variable flip angle method with emphasis on the noise propagated from radiofrequency transmit field ([Formula: see text]) measurements. The analytical solution for T 1 precision was derived by standard error propagation methods incorporating the noise from the three input sources: two spoiled gradient echo (SPGR) images and a [Formula: see text] map. Repeated in vivo experiments were performed to estimate the total variance in T 1 maps and we compared these experimentally obtained values with the theoretical predictions to validate the established theoretical framework. Both the analytical and experimental results showed that variance in the [Formula: see text] map propagated comparable noise levels into the T 1 maps as either of the two SPGR images. Improving precision of the [Formula: see text] measurements significantly reduced the variance in the estimated T 1 map. The variance estimated from the repeatedly measured in vivo T 1 maps agreed well with the theoretically-calculated variance in T 1 estimates, thus validating the analytical framework for realistic in vivo experiments. We concluded that for T 1 mapping experiments, the error propagated from the [Formula: see text] map must be considered. Optimizing the SPGR signals while neglecting to improve the precision of the [Formula: see text] map may result in grossly overestimating the precision of the estimated T 1 values.
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NASA Technical Reports Server (NTRS)
1993-01-01
Using chordic technology, a data entry operator can finger key combinations for text or graphics input. Because only one hand is needed, a disabled person may use it. Strain and fatigue are less than when using a conventional keyboard; input is faster, and the system can be learned in about an hour. Infogrip, Inc. developed chordic input technology with Stennis Space Center (SSC). (NASA is interested in potentially faster human/computer interaction on spacecraft as well as a low cost tactile/visual training system for the handicapped.) The company is now marketing the BAT as an improved system for both disabled and non-disabled computer operators.
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Akce, Abdullah; Norton, James J S; Bretl, Timothy
2015-09-01
This paper presents a brain-computer interface for text entry using steady-state visually evoked potentials (SSVEP). Like other SSVEP-based spellers, ours identifies the desired input character by posing questions (or queries) to users through a visual interface. Each query defines a mapping from possible characters to steady-state stimuli. The user responds by attending to one of these stimuli. Unlike other SSVEP-based spellers, ours chooses from a much larger pool of possible queries-on the order of ten thousand instead of ten. The larger query pool allows our speller to adapt more effectively to the inherent structure of what is being typed and to the input performance of the user, both of which make certain queries provide more information than others. In particular, our speller chooses queries from this pool that maximize the amount of information to be received per unit of time, a measure of mutual information that we call information gain rate. To validate our interface, we compared it with two other state-of-the-art SSVEP-based spellers, which were re-implemented to use the same input mechanism. Results showed that our interface, with the larger query pool, allowed users to spell multiple-word texts nearly twice as fast as they could with the compared spellers.
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Method and apparatus for loss of control inhibitor systems
NASA Technical Reports Server (NTRS)
A'Harrah, Ralph C. (Inventor)
2007-01-01
Active and adaptive systems and methods to prevent loss of control incidents by providing tactile feedback to a vehicle operator are disclosed. According to the present invention, an operator gives a control input to an inceptor. An inceptor sensor measures an inceptor input value of the control input. The inceptor input is used as an input to a Steady-State Inceptor Input/Effector Output Model that models the vehicle control system design. A desired effector output from the inceptor input is generated from the model. The desired effector output is compared to an actual effector output to get a distortion metric. A feedback force is generated as a function of the distortion metric. The feedback force is used as an input to a feedback force generator which generates a loss of control inhibitor system (LOCIS) force back to the inceptor. The LOCIS force is felt by the operator through the inceptor.
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High dynamic range charge measurements
De Geronimo, Gianluigi
2012-09-04
A charge amplifier for use in radiation sensing includes an amplifier, at least one switch, and at least one capacitor. The switch selectively couples the input of the switch to one of at least two voltages. The capacitor is electrically coupled in series between the input of the amplifier and the input of the switch. The capacitor is electrically coupled to the input of the amplifier without a switch coupled therebetween. A method of measuring charge in radiation sensing includes selectively diverting charge from an input of an amplifier to an input of at least one capacitor by selectively coupling an output of the at least one capacitor to one of at least two voltages. The input of the at least one capacitor is operatively coupled to the input of the amplifier without a switch coupled therebetween. The method also includes calculating a total charge based on a sum of the amplified charge and the diverted charge.
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Text block identification in restoration process of Javanese script damage
NASA Astrophysics Data System (ADS)
Himamunanto, A. R.; Setyowati, E.
2018-05-01
Generally, in a sheet of documents there are two objects of information, namely text and image. A text block area in the sheet of manuscript is a vital object because the restoration process would be done only in this object. Text block or text area identification becomes an important step before. This paper describes the steps leading to the restoration of Java script destruction. The process stages are: pre-processing, identification of text block, segmentation, damage identification, restoration. The test result based on the input manuscript “Hamong Tani” show that the system works with a success rate of 82.07%
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Theatre of the Mind: A Project to Animate the Language of thought and Communication
ERIC Educational Resources Information Center
Wheeler, Eric S.
2009-01-01
Human language is a rich and complex part of human behaviour that can be studied in many ways. The author and his colleagues are developing an application that accepts simple texts as input and presents an animated display of characters acting out the text. It mimics the human visualization of texts, the so-called Theatre of the Mind. In so doing,…
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Optical image encryption using QR code and multilevel fingerprints in gyrator transform domains
NASA Astrophysics Data System (ADS)
Wei, Yang; Yan, Aimin; Dong, Jiabin; Hu, Zhijuan; Zhang, Jingtao
2017-11-01
A new concept of GT encryption scheme is proposed in this paper. We present a novel optical image encryption method by using quick response (QR) code and multilevel fingerprint keys in gyrator transform (GT) domains. In this method, an original image is firstly transformed into a QR code, which is placed in the input plane of cascaded GTs. Subsequently, the QR code is encrypted into the cipher-text by using multilevel fingerprint keys. The original image can be obtained easily by reading the high-quality retrieved QR code with hand-held devices. The main parameters used as private keys are GTs' rotation angles and multilevel fingerprints. Biometrics and cryptography are integrated with each other to improve data security. Numerical simulations are performed to demonstrate the validity and feasibility of the proposed encryption scheme. In the future, the method of applying QR codes and fingerprints in GT domains possesses much potential for information security.
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Aboulbanine, Zakaria; El Khayati, Naïma
2018-04-13
The use of phase space in medical linear accelerator Monte Carlo (MC) simulations significantly improves the execution time and leads to results comparable to those obtained from full calculations. The classical representation of phase space stores directly the information of millions of particles, producing bulky files. This paper presents a virtual source model (VSM) based on a reconstruction algorithm, taking as input a compressed file of roughly 800 kb derived from phase space data freely available in the International Atomic Energy Agency (IAEA) database. This VSM includes two main components; primary and scattered particle sources, with a specific reconstruction method developed for each. Energy spectra and other relevant variables were extracted from IAEA phase space and stored in the input description data file for both sources. The VSM was validated for three photon beams: Elekta Precise 6 MV/10 MV and a Varian TrueBeam 6 MV. Extensive calculations in water and comparisons between dose distributions of the VSM and IAEA phase space were performed to estimate the VSM precision. The Geant4 MC toolkit in multi-threaded mode (Geant4-[mt]) was used for fast dose calculations and optimized memory use. Four field configurations were chosen for dose calculation validation to test field size and symmetry effects, [Formula: see text] [Formula: see text], [Formula: see text] [Formula: see text], and [Formula: see text] [Formula: see text] for squared fields, and [Formula: see text] [Formula: see text] for an asymmetric rectangular field. Good agreement in terms of [Formula: see text] formalism, for 3%/3 mm and 2%/3 mm criteria, for each evaluated radiation field and photon beam was obtained within a computation time of 60 h on a single WorkStation for a 3 mm voxel matrix. Analyzing the VSM's precision in high dose gradient regions, using the distance to agreement concept (DTA), showed also satisfactory results. In all investigated cases, the mean DTA was less than 1 mm in build-up and penumbra regions. In regards to calculation efficiency, the event processing speed is six times faster using Geant4-[mt] compared to sequential Geant4, when running the same simulation code for both. The developed VSM for 6 MV/10 MV beams widely used, is a general concept easy to adapt in order to reconstruct comparable beam qualities for various linac configurations, facilitating its integration for MC treatment planning purposes.
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An Introduction to Fortran Programming: An IPI Approach.
ERIC Educational Resources Information Center
Fisher, D. D.; And Others
This text is designed to give individually paced instruction in Fortran Programing. The text contains fifteen units. Unit titles include: Flowcharts, Input and Output, Loops, and Debugging. Also included is an extensive set of appendices. These were designed to contain a great deal of practical information necessary to the course. These appendices…
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Hybrid ontology for semantic information retrieval model using keyword matching indexing system.
Uthayan, K R; Mala, G S Anandha
2015-01-01
Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.
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Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
Uthayan, K. R.; Anandha Mala, G. S.
2015-01-01
Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851
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Homeostasis, singularities, and networks.
Golubitsky, Martin; Stewart, Ian
2017-01-01
Homeostasis occurs in a biological or chemical system when some output variable remains approximately constant as an input parameter [Formula: see text] varies over some interval. We discuss two main aspects of homeostasis, both related to the effect of coordinate changes on the input-output map. The first is a reformulation of homeostasis in the context of singularity theory, achieved by replacing 'approximately constant over an interval' by 'zero derivative of the output with respect to the input at a point'. Unfolding theory then classifies all small perturbations of the input-output function. In particular, the 'chair' singularity, which is especially important in applications, is discussed in detail. Its normal form and universal unfolding [Formula: see text] is derived and the region of approximate homeostasis is deduced. The results are motivated by data on thermoregulation in two species of opossum and the spiny rat. We give a formula for finding chair points in mathematical models by implicit differentiation and apply it to a model of lateral inhibition. The second asks when homeostasis is invariant under appropriate coordinate changes. This is false in general, but for network dynamics there is a natural class of coordinate changes: those that preserve the network structure. We characterize those nodes of a given network for which homeostasis is invariant under such changes. This characterization is determined combinatorially by the network topology.
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Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.
1998-01-01
A method for generating a validated measurement of a process parameter at a point in time by using a plurality of individual sensor inputs from a scan of said sensors at said point in time. The sensor inputs from said scan are stored and a first validation pass is initiated by computing an initial average of all stored sensor inputs. Each sensor input is deviation checked by comparing each input including a preset tolerance against the initial average input. If the first deviation check is unsatisfactory, the sensor which produced the unsatisfactory input is flagged as suspect. It is then determined whether at least two of the inputs have not been flagged as suspect and are therefore considered good inputs. If two or more inputs are good, a second validation pass is initiated by computing a second average of all the good sensor inputs, and deviation checking the good inputs by comparing each good input including a present tolerance against the second average. If the second deviation check is satisfactory, the second average is displayed as the validated measurement and the suspect sensor as flagged as bad. A validation fault occurs if at least two inputs are not considered good, or if the second deviation check is not satisfactory. In the latter situation the inputs from each of all the sensors are compared against the last validated measurement and the value from the sensor input that deviates the least from the last valid measurement is displayed.
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MeSH indexing based on automatically generated summaries
2013-01-01
Background MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. Results We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. Conclusions Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading. PMID:23802936
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Systems and methods for reconfiguring input devices
NASA Technical Reports Server (NTRS)
Lancaster, Jeff (Inventor); De Mers, Robert E. (Inventor)
2012-01-01
A system includes an input device having first and second input members configured to be activated by a user. The input device is configured to generate activation signals associated with activation of the first and second input members, and each of the first and second input members are associated with an input function. A processor is coupled to the input device and configured to receive the activation signals. A memory coupled to the processor, and includes a reconfiguration module configured to store the input functions assigned to the first and second input members and, upon execution of the processor, to reconfigure the input functions assigned to the input members when the first input member is inoperable.
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Method Accelerates Training Of Some Neural Networks
NASA Technical Reports Server (NTRS)
Shelton, Robert O.
1992-01-01
Three-layer networks trained faster provided two conditions are satisfied: numbers of neurons in layers are such that majority of work done in synaptic connections between input and hidden layers, and number of neurons in input layer at least as great as number of training pairs of input and output vectors. Based on modified version of back-propagation method.
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Optical switches and switching methods
Doty, Michael
2008-03-04
A device and method for collecting subject responses, particularly during magnetic imaging experiments and testing using a method such as functional MRI. The device comprises a non-metallic input device which is coupled via fiber optic cables to a computer or other data collection device. One or more optical switches transmit the subject's responses. The input device keeps the subject's fingers comfortably aligned with the switches by partially immobilizing the forearm, wrist, and/or hand of the subject. Also a robust nonmetallic switch, particularly for use with the input device and methods for optical switching.
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Redundancy-Aware Topic Modeling for Patient Record Notes
Cohen, Raphael; Aviram, Iddo; Elhadad, Michael; Elhadad, Noémie
2014-01-01
The clinical notes in a given patient record contain much redundancy, in large part due to clinicians’ documentation habit of copying from previous notes in the record and pasting into a new note. Previous work has shown that this redundancy has a negative impact on the quality of text mining and topic modeling in particular. In this paper we describe a novel variant of Latent Dirichlet Allocation (LDA) topic modeling, Red-LDA, which takes into account the inherent redundancy of patient records when modeling content of clinical notes. To assess the value of Red-LDA, we experiment with three baselines and our novel redundancy-aware topic modeling method: given a large collection of patient records, (i) apply vanilla LDA to all documents in all input records; (ii) identify and remove all redundancy by chosing a single representative document for each record as input to LDA; (iii) identify and remove all redundant paragraphs in each record, leaving partial, non-redundant documents as input to LDA; and (iv) apply Red-LDA to all documents in all input records. Both quantitative evaluation carried out through log-likelihood on held-out data and topic coherence of produced topics and qualitative assessement of topics carried out by physicians show that Red-LDA produces superior models to all three baseline strategies. This research contributes to the emerging field of understanding the characteristics of the electronic health record and how to account for them in the framework of data mining. The code for the two redundancy-elimination baselines and Red-LDA is made publicly available to the community. PMID:24551060
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Redundancy-aware topic modeling for patient record notes.
Cohen, Raphael; Aviram, Iddo; Elhadad, Michael; Elhadad, Noémie
2014-01-01
The clinical notes in a given patient record contain much redundancy, in large part due to clinicians' documentation habit of copying from previous notes in the record and pasting into a new note. Previous work has shown that this redundancy has a negative impact on the quality of text mining and topic modeling in particular. In this paper we describe a novel variant of Latent Dirichlet Allocation (LDA) topic modeling, Red-LDA, which takes into account the inherent redundancy of patient records when modeling content of clinical notes. To assess the value of Red-LDA, we experiment with three baselines and our novel redundancy-aware topic modeling method: given a large collection of patient records, (i) apply vanilla LDA to all documents in all input records; (ii) identify and remove all redundancy by chosing a single representative document for each record as input to LDA; (iii) identify and remove all redundant paragraphs in each record, leaving partial, non-redundant documents as input to LDA; and (iv) apply Red-LDA to all documents in all input records. Both quantitative evaluation carried out through log-likelihood on held-out data and topic coherence of produced topics and qualitative assessment of topics carried out by physicians show that Red-LDA produces superior models to all three baseline strategies. This research contributes to the emerging field of understanding the characteristics of the electronic health record and how to account for them in the framework of data mining. The code for the two redundancy-elimination baselines and Red-LDA is made publicly available to the community.
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Fuzzy Neuron: Method and Hardware Realization
NASA Technical Reports Server (NTRS)
Krasowski, Michael J.; Prokop, Norman F.
2014-01-01
This innovation represents a method by which single-to-multi-input, single-to-many-output system transfer functions can be estimated from input/output data sets. This innovation can be run in the background while a system is operating under other means (e.g., through human operator effort), or may be utilized offline using data sets created from observations of the estimated system. It utilizes a set of fuzzy membership functions spanning the input space for each input variable. Linear combiners associated with combinations of input membership functions are used to create the output(s) of the estimator. Coefficients are adjusted online through the use of learning algorithms.
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An accelerated training method for back propagation networks
NASA Technical Reports Server (NTRS)
Shelton, Robert O. (Inventor)
1993-01-01
The principal objective is to provide a training procedure for a feed forward, back propagation neural network which greatly accelerates the training process. A set of orthogonal singular vectors are determined from the input matrix such that the standard deviations of the projections of the input vectors along these singular vectors, as a set, are substantially maximized, thus providing an optimal means of presenting the input data. Novelty exists in the method of extracting from the set of input data, a set of features which can serve to represent the input data in a simplified manner, thus greatly reducing the time/expense to training the system.
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Incorporating uncertainty in RADTRAN 6.0 input files.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dennis, Matthew L.; Weiner, Ruth F.; Heames, Terence John
Uncertainty may be introduced into RADTRAN analyses by distributing input parameters. The MELCOR Uncertainty Engine (Gauntt and Erickson, 2004) has been adapted for use in RADTRAN to determine the parameter shape and minimum and maximum of the distribution, to sample on the distribution, and to create an appropriate RADTRAN batch file. Coupling input parameters is not possible in this initial application. It is recommended that the analyst be very familiar with RADTRAN and able to edit or create a RADTRAN input file using a text editor before implementing the RADTRAN Uncertainty Analysis Module. Installation of the MELCOR Uncertainty Engine ismore » required for incorporation of uncertainty into RADTRAN. Gauntt and Erickson (2004) provides installation instructions as well as a description and user guide for the uncertainty engine.« less
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NASA Technical Reports Server (NTRS)
Lucas, S. H.; Davis, R. C.
1992-01-01
A user's manual is presented for MacPASCO, which is an interactive, graphic, preprocessor for panel design. MacPASCO creates input for PASCO, an existing computer code for structural analysis and sizing of longitudinally stiffened composite panels. MacPASCO provides a graphical user interface which simplifies the specification of panel geometry and reduces user input errors. The user draws the initial structural geometry and reduces user input errors. The user draws the initial structural geometry on the computer screen, then uses a combination of graphic and text inputs to: refine the structural geometry; specify information required for analysis such as panel load and boundary conditions; and define design variables and constraints for minimum mass optimization. Only the use of MacPASCO is described, since the use of PASCO has been documented elsewhere.
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A survey on annotation tools for the biomedical literature.
Neves, Mariana; Leser, Ulf
2014-03-01
New approaches to biomedical text mining crucially depend on the existence of comprehensive annotated corpora. Such corpora, commonly called gold standards, are important for learning patterns or models during the training phase, for evaluating and comparing the performance of algorithms and also for better understanding the information sought for by means of examples. Gold standards depend on human understanding and manual annotation of natural language text. This process is very time-consuming and expensive because it requires high intellectual effort from domain experts. Accordingly, the lack of gold standards is considered as one of the main bottlenecks for developing novel text mining methods. This situation led the development of tools that support humans in annotating texts. Such tools should be intuitive to use, should support a range of different input formats, should include visualization of annotated texts and should generate an easy-to-parse output format. Today, a range of tools which implement some of these functionalities are available. In this survey, we present a comprehensive survey of tools for supporting annotation of biomedical texts. Altogether, we considered almost 30 tools, 13 of which were selected for an in-depth comparison. The comparison was performed using predefined criteria and was accompanied by hands-on experiences whenever possible. Our survey shows that current tools can support many of the tasks in biomedical text annotation in a satisfying manner, but also that no tool can be considered as a true comprehensive solution.
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Ohno, Yoshiharu; Nishio, Mizuho; Koyama, Hisanobu; Fujisawa, Yasuko; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Sugimura, Kazuro
2013-06-01
The objective of our study was to prospectively compare the capability of dynamic area-detector CT analyzed with different mathematic methods and PET/CT in the management of pulmonary nodules. Fifty-two consecutive patients with 96 pulmonary nodules underwent dynamic area-detector CT, PET/CT, and microbacterial or pathologic examinations. All nodules were classified into the following groups: malignant nodules (n = 57), benign nodules with low biologic activity (n = 15), and benign nodules with high biologic activity (n = 24). On dynamic area-detector CT, the total, pulmonary arterial, and systemic arterial perfusions were calculated using the dual-input maximum slope method; perfusion was calculated using the single-input maximum slope method; and extraction fraction and blood volume (BV) were calculated using the Patlak plot method. All indexes were statistically compared among the three nodule groups. Then, receiver operating characteristic analyses were used to compare the diagnostic capabilities of the maximum standardized uptake value (SUVmax) and each perfusion parameter having a significant difference between malignant and benign nodules. Finally, the diagnostic performances of the indexes were compared by means of the McNemar test. No adverse effects were observed in this study. All indexes except extraction fraction and BV, both of which were calculated using the Patlak plot method, showed significant differences among the three groups (p < 0.05). Areas under the curve of total perfusion calculated using the dual-input method, pulmonary arterial perfusion calculated using the dual-input method, and perfusion calculated using the single-input method were significantly larger than that of SUVmax (p < 0.05). The accuracy of total perfusion (83.3%) was significantly greater than the accuracy of the other indexes: pulmonary arterial perfusion (72.9%, p < 0.05), systemic arterial perfusion calculated using the dual-input method (69.8%, p < 0.05), perfusion (66.7%, p < 0.05), and SUVmax (60.4%, p < 0.05). Dynamic area-detector CT analyzed using the dual-input maximum slope method has better potential for the diagnosis of pulmonary nodules than dynamic area-detector CT analyzed using other methods and than PET/CT.
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NASA Astrophysics Data System (ADS)
Zhou, BeiBei; Wang, QuanJiu
2017-09-01
Studies on solute transport under different pore water velocity and solute input methods in undisturbed soil could play instructive roles for crop production. Based on the experiments in the laboratory, the effect of solute input methods with small pulse input and large pulse input, as well as four pore water velocities, on chloride transport in the undisturbed soil columns obtained from the Loess Plateau under controlled condition was studied. Chloride breakthrough curves (BTCs) were generated using the miscible displacement method under water-saturated, steady flow conditions. Using the 0.15 mol L-1 CaCl2 solution as a tracer, a small pulse (0.1 pore volumes) was first induced, and then, after all the solution was wash off, a large pulse (0.5 pore volumes) was conducted. The convection-dispersion equation (CDE) and the two-region model (T-R) were used to describe the BTCs, and their prediction accuracies and fitted parameters were compared as well. All the BTCs obtained for the different input methods and the four pore water velocities were all smooth. However, the shapes of the BTCs varied greatly; small pulse inputs resulted in more rapid attainment of peak values that appeared earlier with increases in pore water velocity, whereas large pulse inputs resulted in an opposite trend. Both models could fit the experimental data well, but the prediction accuracy of the T-R was better. The values of the dispersivity, λ, calculated from the dispersion coefficient obtained from the CDE were about one order of magnitude larger than those calculated from the dispersion coefficient given by the T-R, but the calculated Peclet number, Pe, was lower. The mobile-immobile partition coefficient, β, decreased, while the mass exchange coefficient increased with increases in pore water velocity.
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Metsalu, Tauno; Vilo, Jaak
2015-01-01
The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/. PMID:25969447
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Glazoff, Michael V.; Gering, Kevin L.; Garnier, John E.; Rashkeev, Sergey N.; Pyt'ev, Yuri Petrovich
2016-05-17
Embodiments discussed herein in the form of methods, systems, and computer-readable media deal with the application of advanced "projectional" morphological algorithms for solving a broad range of problems. In a method of performing projectional morphological analysis, an N-dimensional input signal is supplied. At least one N-dimensional form indicative of at least one feature in the N-dimensional input signal is identified. The N-dimensional input signal is filtered relative to the at least one N-dimensional form and an N-dimensional output signal is generated indicating results of the filtering at least as differences in the N-dimensional input signal relative to the at least one N-dimensional form.
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Runwien: a text-based interface for the WIEN package
NASA Astrophysics Data System (ADS)
Otero de la Roza, A.; Luaña, Víctor
2009-05-01
A new text-based interface for WIEN2k, the full-potential linearized augmented plane-waves (FPLAPW) program, is presented. This code provides an easy to use, yet powerful way of generating arbitrarily large sets of calculations. Thus, properties over a potential energy surface and WIEN2k parameter exploration can be calculated using a simple input text file. This interface also provides new capabilities to the WIEN2k package, such as the calculation of elastic constants on hexagonal systems or the automatic gathering of relevant information. Additionally, runwien is modular, flexible and intuitive. Program summaryProgram title: runwien Catalogue identifier: AECM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECM_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL version 3 No. of lines in distributed program, including test data, etc.: 62 567 No. of bytes in distributed program, including test data, etc.: 610 973 Distribution format: tar.gz Programming language: gawk (with locale POSIX or similar) Computer: All running Unix, Linux Operating system: Unix, GNU/Linux Classification: 7.3 External routines: WIEN2k ( http://www.wien2k.at/), GAWK ( http://www.gnu.org/software/gawk/), rename by L. Wall, a Perl script which renames files, modified by R. Barker to check for the existence of target files, gnuplot ( http://www.gnuplot.info/) Subprograms used:Cat Id: ADSY_v1_0/AECB_v1_0, Title: GIBBS/CRITIC, Reference: CPC 158 (2004) 57/CPC 999 (2009) 999 Nature of problem: Creation of a text-based, batch-oriented interface for the WIEN2k package. Solution method: WIEN2k solves the Kohn-Sham equations of a solid using the FPLAPW formalism. Runwien interprets an input file containing the description of the geometry and structure of the solid and drives the execution of the WIEN2k programs. The input is simplified thanks to the default values of the WIEN2k parameters known to runwien. Additional comments: Designed for WIEN2k versions 06.4, 07.2, 08.2, and 08.3. Running time: For the test case (TiC), a single geometry takes 5 to 10 minutes on a typical desktop PC (Intel Pentium 4, 3.4 GHz, 1 GB RAM). The full example including the calculation of the elastic constants and the equation of state, takes 9 hours and 32 minutes.
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ERIC Educational Resources Information Center
Silver, Steven S.
FMS/3 is a system for producing hard copy documentation at high speed from free format text and command input. The system was originally written in assembler language for a 12K IBM 360 model 20 using a high speed 1403 printer with the UCS-TN chain option (upper and lower case). Input was from an IBM 2560 Multi-function Card Machine. The model 20…
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ESL Reading Textbooks vs. University Textbooks: Are We Giving Our Students the Input They May Need?
ERIC Educational Resources Information Center
Miller, Don
2011-01-01
Developing reading skills in a second language presents learners with many challenges, including lexico-grammatical decoding. An additional challenge is posed by the different registers of written text and the associated lexico-grammatical features with which learners must contend. Questioning the efficacy of using non-academic reading texts in…
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Semi-Automated Annotation of Biobank Data Using Standard Medical Terminologies in a Graph Database.
Hofer, Philipp; Neururer, Sabrina; Goebel, Georg
2016-01-01
Data describing biobank resources frequently contains unstructured free-text information or insufficient coding standards. (Bio-) medical ontologies like Orphanet Rare Diseases Ontology (ORDO) or the Human Disease Ontology (DOID) provide a high number of concepts, synonyms and entity relationship properties. Such standard terminologies increase quality and granularity of input data by adding comprehensive semantic background knowledge from validated entity relationships. Moreover, cross-references between terminology concepts facilitate data integration across databases using different coding standards. In order to encourage the use of standard terminologies, our aim is to identify and link relevant concepts with free-text diagnosis inputs within a biobank registry. Relevant concepts are selected automatically by lexical matching and SPARQL queries against a RDF triplestore. To ensure correctness of annotations, proposed concepts have to be confirmed by medical data administration experts before they are entered into the registry database. Relevant (bio-) medical terminologies describing diseases and phenotypes were identified and stored in a graph database which was tied to a local biobank registry. Concept recommendations during data input trigger a structured description of medical data and facilitate data linkage between heterogeneous systems.
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Next generation lightweight mirror modeling software
NASA Astrophysics Data System (ADS)
Arnold, William R.; Fitzgerald, Matthew; Rosa, Rubin Jaca; Stahl, H. Philip
2013-09-01
The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 3-5 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any text editor, all the shell thickness parameters and suspension spring rates are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models easier.
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Hori, Yuki; Ihara, Naoki; Teramoto, Noboru; Kunimi, Masako; Honda, Manabu; Kato, Koichi; Hanakawa, Takashi
2015-01-01
Measurement of arterial input function (AIF) for quantitative positron emission tomography (PET) studies is technically challenging. The present study aimed to develop a method based on a standard arterial input function (SIF) to estimate input function without blood sampling. We performed 18F-fluolodeoxyglucose studies accompanied by continuous blood sampling for measurement of AIF in 11 rats. Standard arterial input function was calculated by averaging AIFs from eight anesthetized rats, after normalization with body mass (BM) and injected dose (ID). Then, the individual input function was estimated using two types of SIF: (1) SIF calibrated by the individual's BM and ID (estimated individual input function, EIFNS) and (2) SIF calibrated by a single blood sampling as proposed previously (EIF1S). No significant differences in area under the curve (AUC) or cerebral metabolic rate for glucose (CMRGlc) were found across the AIF-, EIFNS-, and EIF1S-based methods using repeated measures analysis of variance. In the correlation analysis, AUC or CMRGlc derived from EIFNS was highly correlated with those derived from AIF and EIF1S. Preliminary comparison between AIF and EIFNS in three awake rats supported an idea that the method might be applicable to behaving animals. The present study suggests that EIFNS method might serve as a noninvasive substitute for individual AIF measurement. PMID:25966947
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Hori, Yuki; Ihara, Naoki; Teramoto, Noboru; Kunimi, Masako; Honda, Manabu; Kato, Koichi; Hanakawa, Takashi
2015-10-01
Measurement of arterial input function (AIF) for quantitative positron emission tomography (PET) studies is technically challenging. The present study aimed to develop a method based on a standard arterial input function (SIF) to estimate input function without blood sampling. We performed (18)F-fluolodeoxyglucose studies accompanied by continuous blood sampling for measurement of AIF in 11 rats. Standard arterial input function was calculated by averaging AIFs from eight anesthetized rats, after normalization with body mass (BM) and injected dose (ID). Then, the individual input function was estimated using two types of SIF: (1) SIF calibrated by the individual's BM and ID (estimated individual input function, EIF(NS)) and (2) SIF calibrated by a single blood sampling as proposed previously (EIF(1S)). No significant differences in area under the curve (AUC) or cerebral metabolic rate for glucose (CMRGlc) were found across the AIF-, EIF(NS)-, and EIF(1S)-based methods using repeated measures analysis of variance. In the correlation analysis, AUC or CMRGlc derived from EIF(NS) was highly correlated with those derived from AIF and EIF(1S). Preliminary comparison between AIF and EIF(NS) in three awake rats supported an idea that the method might be applicable to behaving animals. The present study suggests that EIF(NS) method might serve as a noninvasive substitute for individual AIF measurement.
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NASA Technical Reports Server (NTRS)
Reddy, T. S. R.
1995-01-01
This guide describes the input data required for using ECAP2D (Euler Cascade Aeroelastic Program-Two Dimensional). ECAP2D can be used for steady or unsteady aerodynamic and aeroelastic analysis of two dimensional cascades. Euler equations are used to obtain aerodynamic forces. The structural dynamic equations are written for a rigid typical section undergoing pitching (torsion) and plunging (bending) motion. The solution methods include harmonic oscillation method, influence coefficient method, pulse response method, and time integration method. For harmonic oscillation method, example inputs and outputs are provided for pitching motion and plunging motion. For the rest of the methods, input and output for pitching motion only are given.
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A dimension-wise analysis method for the structural-acoustic system with interval parameters
NASA Astrophysics Data System (ADS)
Xu, Menghui; Du, Jianke; Wang, Chong; Li, Yunlong
2017-04-01
The interval structural-acoustic analysis is mainly accomplished by interval and subinterval perturbation methods. Potential limitations for these intrusive methods include overestimation or interval translation effect for the former and prohibitive computational cost for the latter. In this paper, a dimension-wise analysis method is thus proposed to overcome these potential limitations. In this method, a sectional curve of the system response surface along each input dimensionality is firstly extracted, the minimal and maximal points of which are identified based on its Legendre polynomial approximation. And two input vectors, i.e. the minimal and maximal input vectors, are dimension-wisely assembled by the minimal and maximal points of all sectional curves. Finally, the lower and upper bounds of system response are computed by deterministic finite element analysis at the two input vectors. Two numerical examples are studied to demonstrate the effectiveness of the proposed method and show that, compared to the interval and subinterval perturbation method, a better accuracy is achieved without much compromise on efficiency by the proposed method, especially for nonlinear problems with large interval parameters.
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Optimal control of LQR for discrete time-varying systems with input delays
NASA Astrophysics Data System (ADS)
Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng
2018-04-01
In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.
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NASA Technical Reports Server (NTRS)
Pope, Alan T. (Inventor); Stephens, Chad L. (Inventor); Habowski, Tyler (Inventor)
2017-01-01
Method for physiologically modulating videogames and simulations includes utilizing input from a motion-sensing video game system and input from a physiological signal acquisition device. The inputs from the physiological signal sensors are utilized to change the response of a user's avatar to inputs from the motion-sensing sensors. The motion-sensing system comprises a 3D sensor system having full-body 3D motion capture of a user's body. This arrangement encourages health-enhancing physiological self-regulation skills or therapeutic amplification of healthful physiological characteristics. The system provides increased motivation for users to utilize biofeedback as may be desired for treatment of various conditions.
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Relating interesting quantitative time series patterns with text events and text features
NASA Astrophysics Data System (ADS)
Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.
2013-12-01
In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other application domains such as data analysis of smart grids, cyber physical systems or the security of critical infrastructure, where the data consists of a combination of quantitative and textual time series data.
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Designing Input Fields for Non-Narrative Open-Ended Responses in Web Surveys
Couper, Mick P.; Kennedy, Courtney; Conrad, Frederick G.; Tourangeau, Roger
2012-01-01
Web surveys often collect information such as frequencies, currency amounts, dates, or other items requiring short structured answers in an open-ended format, typically using text boxes for input. We report on several experiments exploring design features of such input fields. We find little effect of the size of the input field on whether frequency or dollar amount answers are well-formed or not. By contrast, the use of templates to guide formatting significantly improves the well-formedness of responses to questions eliciting currency amounts. For date questions (whether month/year or month/day/year), we find that separate input fields improve the quality of responses over single input fields, while drop boxes further reduce the proportion of ill-formed answers. Drop boxes also reduce completion time when the list of responses is short (e.g., months), but marginally increases completion time when the list is long (e.g., birth dates). These results suggest that non-narrative open questions can be designed to help guide respondents to provide answers in the desired format. PMID:23411468
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Comparison of gesture and conventional interaction techniques for interventional neuroradiology.
Hettig, Julian; Saalfeld, Patrick; Luz, Maria; Becker, Mathias; Skalej, Martin; Hansen, Christian
2017-09-01
Interaction with radiological image data and volume renderings within a sterile environment is a challenging task. Clinically established methods such as joystick control and task delegation can be time-consuming and error-prone and interrupt the workflow. New touchless input modalities may have the potential to overcome these limitations, but their value compared to established methods is unclear. We present a comparative evaluation to analyze the value of two gesture input modalities (Myo Gesture Control Armband and Leap Motion Controller) versus two clinically established methods (task delegation and joystick control). A user study was conducted with ten experienced radiologists by simulating a diagnostic neuroradiological vascular treatment with two frequently used interaction tasks in an experimental operating room. The input modalities were assessed using task completion time, perceived task difficulty, and subjective workload. Overall, the clinically established method of task delegation performed best under the study conditions. In general, gesture control failed to exceed the clinical input approach. However, the Myo Gesture Control Armband showed a potential for simple image selection task. Novel input modalities have the potential to take over single tasks more efficiently than clinically established methods. The results of our user study show the relevance of task characteristics such as task complexity on performance with specific input modalities. Accordingly, future work should consider task characteristics to provide a useful gesture interface for a specific use case instead of an all-in-one solution.
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Harmonize input selection for sediment transport prediction
NASA Astrophysics Data System (ADS)
Afan, Haitham Abdulmohsin; Keshtegar, Behrooz; Mohtar, Wan Hanna Melini Wan; El-Shafie, Ahmed
2017-09-01
In this paper, three modeling approaches using a Neural Network (NN), Response Surface Method (RSM) and response surface method basis Global Harmony Search (GHS) are applied to predict the daily time series suspended sediment load. Generally, the input variables for forecasting the suspended sediment load are manually selected based on the maximum correlations of input variables in the modeling approaches based on NN and RSM. The RSM is improved to select the input variables by using the errors terms of training data based on the GHS, namely as response surface method and global harmony search (RSM-GHS) modeling method. The second-order polynomial function with cross terms is applied to calibrate the time series suspended sediment load with three, four and five input variables in the proposed RSM-GHS. The linear, square and cross corrections of twenty input variables of antecedent values of suspended sediment load and water discharge are investigated to achieve the best predictions of the RSM based on the GHS method. The performances of the NN, RSM and proposed RSM-GHS including both accuracy and simplicity are compared through several comparative predicted and error statistics. The results illustrated that the proposed RSM-GHS is as uncomplicated as the RSM but performed better, where fewer errors and better correlation was observed (R = 0.95, MAE = 18.09 (ton/day), RMSE = 25.16 (ton/day)) compared to the ANN (R = 0.91, MAE = 20.17 (ton/day), RMSE = 33.09 (ton/day)) and RSM (R = 0.91, MAE = 20.06 (ton/day), RMSE = 31.92 (ton/day)) for all types of input variables.
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NGS Pretesting and QC Using Illumina Infinium Arrays CIDR IGES Posters - 2017 A Comparison of Methods fragmentation methods for input into library construction protocol Development of a Low Input FFPE workflow for Evaluation of Copy Number Variation (CNV) detection methods in whole exome sequencing (WES) data CIDR AGBT
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Systems and methods for compensating for electrical converter nonlinearities
Perisic, Milun; Ransom, Ray M.; Kajouke, Lateef A.
2013-06-18
Systems and methods are provided for delivering energy from an input interface to an output interface. An electrical system includes an input interface, an output interface, an energy conversion module coupled between the input interface and the output interface, and a control module. The control module determines a duty cycle control value for operating the energy conversion module to produce a desired voltage at the output interface. The control module determines an input power error at the input interface and adjusts the duty cycle control value in a manner that is influenced by the input power error, resulting in a compensated duty cycle control value. The control module operates switching elements of the energy conversion module to deliver energy to the output interface with a duty cycle that is influenced by the compensated duty cycle control value.
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Continuous-Time Bilinear System Identification
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan
2003-01-01
The objective of this paper is to describe a new method for identification of a continuous-time multi-input and multi-output bilinear system. The approach is to make judicious use of the linear-model properties of the bilinear system when subjected to a constant input. Two steps are required in the identification process. The first step is to use a set of pulse responses resulting from a constant input of one sample period to identify the state matrix, the output matrix, and the direct transmission matrix. The second step is to use another set of pulse responses with the same constant input over multiple sample periods to identify the input matrix and the coefficient matrices associated with the coupling terms between the state and the inputs. Numerical examples are given to illustrate the concept and the computational algorithm for the identification method.
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Code of Federal Regulations, 2011 CFR
2011-10-01
... device used to input, write, send, receive, or read text. Emergency means any hurricane, tornado, storm... public welfare, provided such hurricane, tornado, or other event results in: (1) A declaration of an...
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Code of Federal Regulations, 2012 CFR
2012-10-01
... device used to input, write, send, receive, or read text. Emergency means any hurricane, tornado, storm... public welfare, provided such hurricane, tornado, or other event results in: (1) A declaration of an...
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Method and Apparatus for Reducing the Vulnerability of Latches to Single Event Upsets
NASA Technical Reports Server (NTRS)
Shuler, Robert L., Jr. (Inventor)
2002-01-01
A delay circuit includes a first network having an input and an output node, a second network having an input and an output, the input of the second network being coupled to the output node of the first network. The first network and the second network are configured such that: a glitch at the input to the first network having a length of approximately one-half of a standard glitch time or less does not cause the voltage at the output of the second network to cross a threshold, a glitch at the input to the first network having a length of between approximately one-half and two standard glitch times causes the voltage at the output of the second network to cross the threshold for less than the length of the glitch, and a glitch at the input to the first network having a length of greater than approximately two standard glitch times causes the voltage at the output of the second network to cross the threshold for approximately the time of the glitch. The method reduces the vulnerability of a latch to single event upsets. The latch includes a gate having an input and an output and a feedback path from the output to the input of the gate. The method includes inserting a delay into the feedback path and providing a delay in the gate.
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Method and Apparatus for Reducing the Vulnerability of Latches to Single Event Upsets
NASA Technical Reports Server (NTRS)
Shuler, Robert L., Jr. (Inventor)
2002-01-01
A delay circuit includes a first network having an input and an output node, a second network having an input and an output, the input of the second network being coupled to the output node of the first network. The first network and the second network are configured such that: a glitch at the input to the first network having a length of approximately one-half of a standard glitch time or less does not cause tile voltage at the output of the second network to cross a threshold, a glitch at the input to the first network having a length of between approximately one-half and two standard glitch times causes the voltage at the output of the second network to cross the threshold for less than the length of the glitch, and a glitch at the input to the first network having a length of greater than approximately two standard glitch times causes the voltage at the output of the second network to cross the threshold for approximately the time of the glitch. A method reduces the vulnerability of a latch to single event upsets. The latch includes a gate having an input and an output and a feedback path from the output to the input of the gate. The method includes inserting a delay into the feedback path and providing a delay in the gate.
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ERIC Educational Resources Information Center
Tobia, Valentina; Ciancaleoni, Matteo; Bonifacci, Paola
2017-01-01
In this study, two alternative theoretical models were compared, in order to analyze which of them best explains primary school children's text comprehension skills. The first one was based on the distinction between two types of answers requested by the comprehension test: local or global. The second model involved texts' input modality: written…
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Smallwood, D. O.
1996-01-01
It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple) for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD) of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.
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Moessfit. A free Mössbauer fitting program
NASA Astrophysics Data System (ADS)
Kamusella, Sirko; Klauss, Hans-Henning
2016-12-01
A free data analysis program for Mössbauer spectroscopy was developed to solve commonly faced problems such as simultaneous fitting of multiple data sets, Maximum Entropy Method and a proper error estimation. The program is written in C++ using the Qt application framework and the Gnu Scientific Library. Moessfit makes use of multithreading to reasonably apply the multi core CPU capacities of modern PC. The whole fit is specified in a text input file issued to simplify work flow for the user and provide a simple start in the Mössbauer data analysis for beginners. However, the possibility to define arbitrary parameter dependencies and distributions as well as relaxation spectra makes Moessfit interesting for advanced user as well.
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NASA Technical Reports Server (NTRS)
McGreevy, Michael W.; Connors, Mary M. (Technical Monitor)
2001-01-01
To support Search Requests and Quick Responses at the Aviation Safety Reporting System (ASRS), four new QUORUM methods have been developed: keyword search, phrase search, phrase generation, and phrase discovery. These methods build upon the core QUORUM methods of text analysis, modeling, and relevance-ranking. QUORUM keyword search retrieves ASRS incident narratives that contain one or more user-specified keywords in typical or selected contexts, and ranks the narratives on their relevance to the keywords in context. QUORUM phrase search retrieves narratives that contain one or more user-specified phrases, and ranks the narratives on their relevance to the phrases. QUORUM phrase generation produces a list of phrases from the ASRS database that contain a user-specified word or phrase. QUORUM phrase discovery finds phrases that are related to topics of interest. Phrase generation and phrase discovery are particularly useful for finding query phrases for input to QUORUM phrase search. The presentation of the new QUORUM methods includes: a brief review of the underlying core QUORUM methods; an overview of the new methods; numerous, concrete examples of ASRS database searches using the new methods; discussion of related methods; and, in the appendices, detailed descriptions of the new methods.
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NASA Astrophysics Data System (ADS)
Mita, Akifumi; Okamoto, Atsushi; Funakoshi, Hisatoshi
2004-06-01
We have proposed an all-optical authentic memory with the two-wave encryption method. In the recording process, the image data are encrypted to a white noise by the random phase masks added on the input beam with the image data and the reference beam. Only reading beam with the phase-conjugated distribution of the reference beam can decrypt the encrypted data. If the encrypted data are read out with an incorrect phase distribution, the output data are transformed into a white noise. Moreover, during read out, reconstructions of the encrypted data interfere destructively resulting in zero intensity. Therefore our memory has a merit that we can detect unlawful accesses easily by measuring the output beam intensity. In our encryption method, the random phase mask on the input plane plays important roles in transforming the input image into a white noise and prohibiting to decrypt a white noise to the input image by the blind deconvolution method. Without this mask, when unauthorized users observe the output beam by using CCD in the readout with the plane wave, the completely same intensity distribution as that of Fourier transform of the input image is obtained. Therefore the encrypted image will be decrypted easily by using the blind deconvolution method. However in using this mask, even if unauthorized users observe the output beam using the same method, the encrypted image cannot be decrypted because the observed intensity distribution is dispersed at random by this mask. Thus it can be said the robustness is increased by this mask. In this report, we compare two correlation coefficients, which represents the degree of a white noise of the output image, between the output image and the input image in using this mask or not. We show that the robustness of this encryption method is increased as the correlation coefficient is improved from 0.3 to 0.1 by using this mask.
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Automatic insulation resistance testing apparatus
Wyant, Francis J.; Nowlen, Steven P.; Luker, Spencer M.
2005-06-14
An apparatus and method for automatic measurement of insulation resistances of a multi-conductor cable. In one embodiment of the invention, the apparatus comprises a power supply source, an input measuring means, an output measuring means, a plurality of input relay controlled contacts, a plurality of output relay controlled contacts, a relay controller and a computer. In another embodiment of the invention the apparatus comprises a power supply source, an input measuring means, an output measuring means, an input switching unit, an output switching unit and a control unit/data logger. Embodiments of the apparatus of the invention may also incorporate cable fire testing means. The apparatus and methods of the present invention use either voltage or current for input and output measured variables.
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GeneTopics - interpretation of gene sets via literature-driven topic models
2013-01-01
Background Annotation of a set of genes is often accomplished through comparison to a library of labelled gene sets such as biological processes or canonical pathways. However, this approach might fail if the employed libraries are not up to date with the latest research, don't capture relevant biological themes or are curated at a different level of granularity than is required to appropriately analyze the input gene set. At the same time, the vast biomedical literature offers an unstructured repository of the latest research findings that can be tapped to provide thematic sub-groupings for any input gene set. Methods Our proposed method relies on a gene-specific text corpus and extracts commonalities between documents in an unsupervised manner using a topic model approach. We automatically determine the number of topics summarizing the corpus and calculate a gene relevancy score for each topic allowing us to eliminate non-specific topics. As a result we obtain a set of literature topics in which each topic is associated with a subset of the input genes providing directly interpretable keywords and corresponding documents for literature research. Results We validate our method based on labelled gene sets from the KEGG metabolic pathway collection and the genetic association database (GAD) and show that the approach is able to detect topics consistent with the labelled annotation. Furthermore, we discuss the results on three different types of experimentally derived gene sets, (1) differentially expressed genes from a cardiac hypertrophy experiment in mice, (2) altered transcript abundance in human pancreatic beta cells, and (3) genes implicated by GWA studies to be associated with metabolite levels in a healthy population. In all three cases, we are able to replicate findings from the original papers in a quick and semi-automated manner. Conclusions Our approach provides a novel way of automatically generating meaningful annotations for gene sets that are directly tied to relevant articles in the literature. Extending a general topic model method, the approach introduced here establishes a workflow for the interpretation of gene sets generated from diverse experimental scenarios that can complement the classical approach of comparison to reference gene sets. PMID:24564875
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Peng; Barajas-Solano, David A.; Constantinescu, Emil
Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.
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WOLF; automatic typing program
Evenden, G.I.
1982-01-01
A FORTRAN IV program for the Hewlett-Packard 1000 series computer provides for automatic typing operations and can, when employed with manufacturer's text editor, provide a system to greatly facilitate preparation of reports, letters and other text. The input text and imbedded control data can perform nearly all of the functions of a typist. A few of the features available are centering, titles, footnotes, indentation, page numbering (including Roman numerals), automatic paragraphing, and two forms of tab operations. This documentation contains both user and technical description of the program.
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Measuring efficiency of university-industry Ph.D. projects using best worst method.
Salimi, Negin; Rezaei, Jafar
A collaborative Ph.D. project, carried out by a doctoral candidate, is a type of collaboration between university and industry. Due to the importance of such projects, researchers have considered different ways to evaluate the success, with a focus on the outputs of these projects. However, what has been neglected is the other side of the coin-the inputs. The main aim of this study is to incorporate both the inputs and outputs of these projects into a more meaningful measure called efficiency. A ratio of the weighted sum of outputs over the weighted sum of inputs identifies the efficiency of a Ph.D. The weights of the inputs and outputs can be identified using a multi-criteria decision-making (MCDM) method. Data on inputs and outputs are collected from 51 Ph.D. candidates who graduated from Eindhoven University of Technology. The weights are identified using a new MCDM method called Best Worst Method (BWM). Because there may be differences in the opinion of Ph.D. candidates and supervisors on weighing the inputs and outputs, data for BWM are collected from both groups. It is interesting to see that there are differences in the level of efficiency from the two perspectives, because of the weight differences. Moreover, a comparison between the efficiency scores of these projects and their success scores reveals differences that may have significant implications. A sensitivity analysis divulges the most contributing inputs and outputs.
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Robust detection of heartbeats using association models from blood pressure and EEG signals.
Jeon, Taegyun; Yu, Jongmin; Pedrycz, Witold; Jeon, Moongu; Lee, Boreom; Lee, Byeongcheol
2016-01-15
The heartbeat is fundamental cardiac activity which is straightforwardly detected with a variety of measurement techniques for analyzing physiological signals. Unfortunately, unexpected noise or contaminated signals can distort or cut out electrocardiogram (ECG) signals in practice, misleading the heartbeat detectors to report a false heart rate or suspend itself for a considerable length of time in the worst case. To deal with the problem of unreliable heartbeat detection, PhysioNet/CinC suggests a challenge in 2014 for developing robust heart beat detectors using multimodal signals. This article proposes a multimodal data association method that supplements ECG as a primary input signal with blood pressure (BP) and electroencephalogram (EEG) as complementary input signals when input signals are unreliable. If the current signal quality index (SQI) qualifies ECG as a reliable input signal, our method applies QRS detection to ECG and reports heartbeats. Otherwise, the current SQI selects the best supplementary input signal between BP and EEG after evaluating the current SQI of BP. When BP is chosen as a supplementary input signal, our association model between ECG and BP enables us to compute their regular intervals, detect characteristics BP signals, and estimate the locations of the heartbeat. When both ECG and BP are not qualified, our fusion method resorts to the association model between ECG and EEG that allows us to apply an adaptive filter to ECG and EEG, extract the QRS candidates, and report heartbeats. The proposed method achieved an overall score of 86.26 % for the test data when the input signals are unreliable. Our method outperformed the traditional method, which achieved 79.28 % using QRS detector and BP detector from PhysioNet. Our multimodal signal processing method outperforms the conventional unimodal method of taking ECG signals alone for both training and test data sets. To detect the heartbeat robustly, we have proposed a novel multimodal data association method of supplementing ECG with a variety of physiological signals and accounting for the patient-specific lag between different pulsatile signals and ECG. Multimodal signal detectors and data-fusion approaches such as those proposed in this article can reduce false alarms and improve patient monitoring.
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NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.
Martínez-Romero, Marcos; Jonquet, Clement; O'Connor, Martin J; Graybeal, John; Pazos, Alejandro; Musen, Mark A
2017-06-07
Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios. Ontology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available (both via the user interface at http://bioportal.bioontology.org/recommender , and via a Web service API).
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Reconstruction of neuronal input through modeling single-neuron dynamics and computations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Qin, Qing; Wang, Jiang; Yu, Haitao
Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-spacemore » method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.« less
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Harvey, Catherine; Stanton, Neville A; Pickering, Carl A; McDonald, Mike; Zheng, Pengjun
2011-07-01
In-vehicle information systems (IVIS) can be controlled by the user via direct or indirect input devices. In order to develop the next generation of usable IVIS, designers need to be able to evaluate and understand the usability issues associated with these two input types. The aim of this study was to investigate the effectiveness of a set of empirical usability evaluation methods for identifying important usability issues and distinguishing between the IVIS input devices. A number of usability issues were identified and their causal factors have been explored. These were related to the input type, the structure of the menu/tasks and hardware issues. In particular, the translation between inputs and on-screen actions and a lack of visual feedback for menu navigation resulted in lower levels of usability for the indirect device. This information will be useful in informing the design of new IVIS, with improved usability. STATEMENT OF RELEVANCE: This paper examines the use of empirical methods for distinguishing between direct and indirect IVIS input devices and identifying usability issues. Results have shown that the characteristics of indirect input devices produce more serious usability issues, compared with direct devices and can have a negative effect on the driver-vehicle interaction.
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Reconstruction of neuronal input through modeling single-neuron dynamics and computations
NASA Astrophysics Data System (ADS)
Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok
2016-06-01
Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.
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Time Triggered Ethernet System Testing Means and Method
NASA Technical Reports Server (NTRS)
Smithgall, William Todd (Inventor); Hall, Brendan (Inventor); Varadarajan, Srivatsan (Inventor)
2014-01-01
Methods and apparatus are provided for evaluating the performance of a Time Triggered Ethernet (TTE) system employing Time Triggered (TT) communication. A real TTE system under test (SUT) having real input elements communicating using TT messages with output elements via one or more first TTE switches during a first time interval schedule established for the SUT. A simulation system is also provided having input simulators that communicate using TT messages via one or more second TTE switches with the same output elements during a second time interval schedule established for the simulation system. The first and second time interval schedules are off-set slightly so that messages from the input simulators, when present, arrive at the output elements prior to messages from the analogous real inputs, thereby having priority over messages from the real inputs and causing the system to operate based on the simulated inputs when present.
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Unifying cost and information in information-theoretic competitive learning.
Kamimura, Ryotaro
2005-01-01
In this paper, we introduce costs into the framework of information maximization and try to maximize the ratio of information to its associated cost. We have shown that competitive learning is realized by maximizing mutual information between input patterns and competitive units. One shortcoming of the method is that maximizing information does not necessarily produce representations faithful to input patterns. Information maximizing primarily focuses on some parts of input patterns that are used to distinguish between patterns. Therefore, we introduce the cost, which represents average distance between input patterns and connection weights. By minimizing the cost, final connection weights reflect input patterns well. We applied the method to a political data analysis, a voting attitude problem and a Wisconsin cancer problem. Experimental results confirmed that, when the cost was introduced, representations faithful to input patterns were obtained. In addition, improved generalization performance was obtained within a relatively short learning time.
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System and method for motor parameter estimation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luhrs, Bin; Yan, Ting
2014-03-18
A system and method for determining unknown values of certain motor parameters includes a motor input device connectable to an electric motor having associated therewith values for known motor parameters and an unknown value of at least one motor parameter. The motor input device includes a processing unit that receives a first input from the electric motor comprising values for the known motor parameters for the electric motor and receive a second input comprising motor data on a plurality of reference motors, including values for motor parameters corresponding to the known motor parameters of the electric motor and values formore » motor parameters corresponding to the at least one unknown motor parameter value of the electric motor. The processor determines the unknown value of the at least one motor parameter from the first input and the second input and determines a motor management strategy for the electric motor based thereon.« less
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Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions
NASA Astrophysics Data System (ADS)
Jung, J. Y.; Niemann, J. D.; Greimann, B. P.
2016-12-01
Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.
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Steady-state phase error for a phase-locked loop subjected to periodic Doppler inputs
NASA Technical Reports Server (NTRS)
Chen, C.-C.; Win, M. Z.
1991-01-01
The performance of a carrier phase locked loop (PLL) driven by a periodic Doppler input is studied. By expanding the Doppler input into a Fourier series and applying the linearized PLL approximations, it is easy to show that, for periodic frequency disturbances, the resulting steady state phase error is also periodic. Compared to the method of expanding frequency excursion into a power series, the Fourier expansion method can be used to predict the maximum phase error excursion for a periodic Doppler input. For systems with a large Doppler rate fluctuation, such as an optical transponder aboard an Earth orbiting spacecraft, the method can be applied to test whether a lower order tracking loop can provide satisfactory tracking and thereby save the effect of a higher order loop design.
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Passively damped vibration welding system and method
Tan, Chin-An; Kang, Bongsu; Cai, Wayne W.; Wu, Tao
2013-04-02
A vibration welding system includes a controller, welding horn, an anvil, and a passive damping mechanism (PDM). The controller generates an input signal having a calibrated frequency. The horn vibrates in a desirable first direction at the calibrated frequency in response to the input signal to form a weld in a work piece. The PDM is positioned with respect to the system, and substantially damps or attenuates vibration in an undesirable second direction. A method includes connecting the PDM having calibrated properties and a natural frequency to an anvil of an ultrasonic welding system. Then, an input signal is generated using a weld controller. The method includes vibrating a welding horn in a desirable direction in response to the input signal, and passively damping vibration in an undesirable direction using the PDM.
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Overview of multi-input frequency domain modal testing methods with an emphasis on sine testing
NASA Technical Reports Server (NTRS)
Rost, Robert W.; Brown, David L.
1988-01-01
An overview of the current state of the art multiple-input, multiple-output modal testing technology is discussed. A very brief review of the current time domain methods is given. A detailed review of frequency and spatial domain methods is presented with an emphasis on sine testing.
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Approaches for Evaluating the Usability of Assistive Technology Product Prototypes
ERIC Educational Resources Information Center
Choi, Young Mi; Sprigle, Stephen H.
2011-01-01
User input is an important component to help guide designers in producing a more usable product. Evaluation of prototypes is one method of obtaining this input, but methods for evaluating assistive technology prototypes during design have not been adequately described or evaluated. This project aimed to compare different methods of evaluating…
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Quark flavour observables in the Littlest Higgs model with T-parity after LHC Run 1.
Blanke, Monika; Buras, Andrzej J; Recksiegel, Stefan
2016-01-01
The Littlest Higgs model with T-parity (LHT) belongs to the simplest new physics scenarios with new sources of flavour and CP violation. The latter originate in the interactions of ordinary quarks and leptons with heavy mirror quarks and leptons that are mediated by new heavy gauge bosons. Also a heavy fermionic top partner is present in this model which communicates with the SM fermions by means of standard [Formula: see text] and [Formula: see text] gauge bosons. We present a new analysis of quark flavour observables in the LHT model in view of the oncoming flavour precision era. We use all available information on the CKM parameters, lattice QCD input and experimental data on quark flavour observables and corresponding theoretical calculations, taking into account new lower bounds on the symmetry breaking scale and the mirror quark masses from the LHC. We investigate by how much the branching ratios for a number of rare K and B decays are still allowed to depart from their SM values. This includes [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]. Taking into account the constraints from [Formula: see text] processes, significant departures from the SM predictions for [Formula: see text] and [Formula: see text] are possible, while the effects in B decays are much smaller. In particular, the LHT model favours [Formula: see text], which is not supported by the data, and the present anomalies in [Formula: see text] decays cannot be explained in this model. With the recent lattice and large N input the imposition of the [Formula: see text] constraint implies a significant suppression of the branching ratio for [Formula: see text] with respect to its SM value while allowing only for small modifications of [Formula: see text]. Finally, we investigate how the LHT physics could be distinguished from other models by means of indirect measurements and discuss the consequences for quark flavour observables of not finding any LHT state in the coming years.
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Long-term performance of minimum-input oak restoration plantings
Elizabeth Bernhardt; Tedmund J. Swiecki
2015-01-01
Starting in 1989, we used minimum-input methods to restore native oaks to parts of their former ranges in Vacaville, California. Each restoration site was analyzed, and only those inputs deemed necessary to overcome expected limiting factors for oak establishment were used. We avoided unnecessary inputs that added to cost and could have unintended negative consequences...
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Input-current shaped ac to dc converters
NASA Technical Reports Server (NTRS)
1986-01-01
The problem of achieving near unity power factor while supplying power to a dc load from a single phase ac source of power is examined. Power processors for this application must perform three functions: input current shaping, energy storage, and output voltage regulation. The methods available for performing each of these three functions are reviewed. Input current shaping methods are either active or passive, with the active methods divided into buck-like and boost-like techniques. In addition to large reactances, energy storage methods include resonant filters, active filters, and active storage schemes. Fast voltage regulation can be achieved by post regulation or by supplementing the current shaping topology with an extra switch. Some indications of which methods are best suited for particular applications concludes the discussion.
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Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network
NASA Astrophysics Data System (ADS)
Jiang, Hongkai; Li, Xingqiu; Shao, Haidong; Zhao, Ke
2018-06-01
Traditional intelligent fault diagnosis methods for rolling bearings heavily depend on manual feature extraction and feature selection. For this purpose, an intelligent deep learning method, named the improved deep recurrent neural network (DRNN), is proposed in this paper. Firstly, frequency spectrum sequences are used as inputs to reduce the input size and ensure good robustness. Secondly, DRNN is constructed by the stacks of the recurrent hidden layer to automatically extract the features from the input spectrum sequences. Thirdly, an adaptive learning rate is adopted to improve the training performance of the constructed DRNN. The proposed method is verified with experimental rolling bearing data, and the results confirm that the proposed method is more effective than traditional intelligent fault diagnosis methods.
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Image scale measurement with correlation filters in a volume holographic optical correlator
NASA Astrophysics Data System (ADS)
Zheng, Tianxiang; Cao, Liangcai; He, Qingsheng; Jin, Guofan
2013-08-01
A search engine containing various target images or different part of a large scene area is of great use for many applications, including object detection, biometric recognition, and image registration. The input image captured in realtime is compared with all the template images in the search engine. A volume holographic correlator is one type of these search engines. It performs thousands of comparisons among the images at a super high speed, with the correlation task accomplishing mainly in optics. However, the inputted target image always contains scale variation to the filtering template images. At the time, the correlation values cannot properly reflect the similarity of the images. It is essential to estimate and eliminate the scale variation of the inputted target image. There are three domains for performing the scale measurement, as spatial, spectral and time domains. Most methods dealing with the scale factor are based on the spatial or the spectral domains. In this paper, a method with the time domain is proposed to measure the scale factor of the input image. It is called a time-sequential scaled method. The method utilizes the relationship between the scale variation and the correlation value of two images. It sends a few artificially scaled input images to compare with the template images. The correlation value increases and decreases with the increasing of the scale factor at the intervals of 0.8~1 and 1~1.2, respectively. The original scale of the input image can be measured by estimating the largest correlation value through correlating the artificially scaled input image with the template images. The measurement range for the scale can be 0.8~4.8. Scale factor beyond 1.2 is measured by scaling the input image at the factor of 1/2, 1/3 and 1/4, correlating the artificially scaled input image with the template images, and estimating the new corresponding scale factor inside 0.8~1.2.
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Room-temperature quantum noise limited spectrometry and methods of the same
Stevens, Charles G.; Tringe, Joseph W.; Cunningham, Christopher Thomas
2014-08-26
In one embodiment, a heterodyne detection system for detecting light includes a first input aperture adapted for receiving first light from a scene input, a second input aperture adapted for receiving second light from a local oscillator input, a broadband local oscillator adapted for providing the second light to the second input aperture, a dispersive element adapted for dispersing the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is adapted for concentrating incident light from a primary condensing lens onto the infrared detector, and the infrared detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are described according to other embodiments.
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Room-temperature quantum noise limited spectrometry and methods of the same
Stevens, Charles G; Tringe, Joseph W
2014-12-02
In one embodiment, a heterodyne detection system for detecting light includes a first input aperture adapted for receiving a first light from a scene input, a second input aperture adapted for receiving a second light from a local oscillator input, a broadband local oscillator adapted for providing the second light to the second input aperture, a dispersive element adapted for dispersing the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is adapted for concentrating incident light from a primary condensing lens onto the detector, and the detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are disclosed according to more embodiments.
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Room-temperature quantum noise limited spectrometry and methods of the same
Stevens, Charles G.; Tringe, Joseph W.; Cunningham, Christopher T.
2016-08-02
In one embodiment, a heterodyne detection system for detecting light includes a first input aperture configured to receive first light from a scene input, a second input aperture configured to receive second light from a local oscillator input, a broadband local oscillator configured to provide the second light to the second input aperture, a dispersive element configured to disperse the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is configured to concentrate incident light from a primary condensing lens onto the infrared detector, and the infrared detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are described according to other embodiments.
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Arterial input function derived from pairwise correlations between PET-image voxels.
Schain, Martin; Benjaminsson, Simon; Varnäs, Katarina; Forsberg, Anton; Halldin, Christer; Lansner, Anders; Farde, Lars; Varrone, Andrea
2013-07-01
A metabolite corrected arterial input function is a prerequisite for quantification of positron emission tomography (PET) data by compartmental analysis. This quantitative approach is also necessary for radioligands without suitable reference regions in brain. The measurement is laborious and requires cannulation of a peripheral artery, a procedure that can be associated with patient discomfort and potential adverse events. A non invasive procedure for obtaining the arterial input function is thus preferable. In this study, we present a novel method to obtain image-derived input functions (IDIFs). The method is based on calculation of the Pearson correlation coefficient between the time-activity curves of voxel pairs in the PET image to localize voxels displaying blood-like behavior. The method was evaluated using data obtained in human studies with the radioligands [(11)C]flumazenil and [(11)C]AZ10419369, and its performance was compared with three previously published methods. The distribution volumes (VT) obtained using IDIFs were compared with those obtained using traditional arterial measurements. Overall, the agreement in VT was good (∼3% difference) for input functions obtained using the pairwise correlation approach. This approach performed similarly or even better than the other methods, and could be considered in applied clinical studies. Applications to other radioligands are needed for further verification.
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Enriching Students' Linguistic Repertoires through Text-Based Guided Output Tasks
ERIC Educational Resources Information Center
Koval, Natalie G.
2014-01-01
L2 input, such as a reading text, constitutes a rich source of information on how meanings are expressed in the L2. Helping learners to use this information effectively should be one of the main goals of L2 teaching. In this article, I propose textbased guided output (TBGO) as a technique for "pushing" learners to make better use of the…
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Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.
Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun
2017-10-03
This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.
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Chaos based video encryption using maps and Ikeda time delay system
NASA Astrophysics Data System (ADS)
Valli, D.; Ganesan, K.
2017-12-01
Chaos based cryptosystems are an efficient method to deal with improved speed and highly secured multimedia encryption because of its elegant features, such as randomness, mixing, ergodicity, sensitivity to initial conditions and control parameters. In this paper, two chaos based cryptosystems are proposed: one is the higher-dimensional 12D chaotic map and the other is based on the Ikeda delay differential equation (DDE) suitable for designing a real-time secure symmetric video encryption scheme. These encryption schemes employ a substitution box (S-box) to diffuse the relationship between pixels of plain video and cipher video along with the diffusion of current input pixel with the previous cipher pixel, called cipher block chaining (CBC). The proposed method enhances the robustness against statistical, differential and chosen/known plain text attacks. Detailed analysis is carried out in this paper to demonstrate the security and uniqueness of the proposed scheme.
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Approximation methods for control of structural acoustics models with piezoceramic actuators
NASA Astrophysics Data System (ADS)
Banks, H. T.; Fang, W.; Silcox, R. J.; Smith, R. C.
1993-01-01
The active control of acoustic pressure in a 2-D cavity with a flexible boundary (a beam) is considered. Specifically, this control is implemented via piezoceramic patches on the beam which produces pure bending moments. The incorporation of the feedback control in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input team. Approximation methods in the context of linear quadratic regulator (LQR) state space control formulation are discussed and numerical results demonstrating the effectiveness of this approach in computing feedback controls for noise reduction are presented.
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Comparison of estimates of snow input to a small alpine watershed
R. A. Sommerfeld; R. C. Musselman; G. L. Wooldridge
1990-01-01
We have used five methods to estimate the snow water equivalent input to the Glacier Lakes Ecosystem Experiments Site (GLEES) in south-central Wyoming during the winter 1987-1988 and to obtain an estimate of the errors. The methods are: (1) the Martinec and Rango degree-day method; (2) Wooldridge et al. method of determining the average yearly snowfall from tree...
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Input variable selection and calibration data selection for storm water quality regression models.
Sun, Siao; Bertrand-Krajewski, Jean-Luc
2013-01-01
Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.
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Input-variable sensitivity assessment for sediment transport relations
NASA Astrophysics Data System (ADS)
Fernández, Roberto; Garcia, Marcelo H.
2017-09-01
A methodology to assess input-variable sensitivity for sediment transport relations is presented. The Mean Value First Order Second Moment Method (MVFOSM) is applied to two bed load transport equations showing that it may be used to rank all input variables in terms of how their specific variance affects the overall variance of the sediment transport estimation. In sites where data are scarce or nonexistent, the results obtained may be used to (i) determine what variables would have the largest impact when estimating sediment loads in the absence of field observations and (ii) design field campaigns to specifically measure those variables for which a given transport equation is most sensitive; in sites where data are readily available, the results would allow quantifying the effect that the variance associated with each input variable has on the variance of the sediment transport estimates. An application of the method to two transport relations using data from a tropical mountain river in Costa Rica is implemented to exemplify the potential of the method in places where input data are limited. Results are compared against Monte Carlo simulations to assess the reliability of the method and validate its results. For both of the sediment transport relations used in the sensitivity analysis, accurate knowledge of sediment size was found to have more impact on sediment transport predictions than precise knowledge of other input variables such as channel slope and flow discharge.
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Banta, Edward R.; Provost, Alden M.
2008-01-01
This report documents HUFPrint, a computer program that extracts and displays information about model structure and hydraulic properties from the input data for a model built using the Hydrogeologic-Unit Flow (HUF) Package of the U.S. Geological Survey's MODFLOW program for modeling ground-water flow. HUFPrint reads the HUF Package and other MODFLOW input files, processes the data by hydrogeologic unit and by model layer, and generates text and graphics files useful for visualizing the data or for further processing. For hydrogeologic units, HUFPrint outputs such hydraulic properties as horizontal hydraulic conductivity along rows, horizontal hydraulic conductivity along columns, horizontal anisotropy, vertical hydraulic conductivity or anisotropy, specific storage, specific yield, and hydraulic-conductivity depth-dependence coefficient. For model layers, HUFPrint outputs such effective hydraulic properties as horizontal hydraulic conductivity along rows, horizontal hydraulic conductivity along columns, horizontal anisotropy, specific storage, primary direction of anisotropy, and vertical conductance. Text files tabulating hydraulic properties by hydrogeologic unit, by model layer, or in a specified vertical section may be generated. Graphics showing two-dimensional cross sections and one-dimensional vertical sections at specified locations also may be generated. HUFPrint reads input files designed for MODFLOW-2000 or MODFLOW-2005.
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NASA Astrophysics Data System (ADS)
Farsadnia, Farhad; Ghahreman, Bijan
2016-04-01
Hydrologic homogeneous group identification is considered both fundamental and applied research in hydrology. Clustering methods are among conventional methods to assess the hydrological homogeneous regions. Recently, Self-Organizing feature Map (SOM) method has been applied in some studies. However, the main problem of this method is the interpretation on the output map of this approach. Therefore, SOM is used as input to other clustering algorithms. The aim of this study is to apply a two-level Self-Organizing feature map and Ward hierarchical clustering method to determine the hydrologic homogenous regions in North and Razavi Khorasan provinces. At first by principal component analysis, we reduced SOM input matrix dimension, then the SOM was used to form a two-dimensional features map. To determine homogeneous regions for flood frequency analysis, SOM output nodes were used as input into the Ward method. Generally, the regions identified by the clustering algorithms are not statistically homogeneous. Consequently, they have to be adjusted to improve their homogeneity. After adjustment of the homogeneity regions by L-moment tests, five hydrologic homogeneous regions were identified. Finally, adjusted regions were created by a two-level SOM and then the best regional distribution function and associated parameters were selected by the L-moment approach. The results showed that the combination of self-organizing maps and Ward hierarchical clustering by principal components as input is more effective than the hierarchical method, by principal components or standardized inputs to achieve hydrologic homogeneous regions.
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van der Ham, Alida J; van Erp, Nicole; Broerse, Jacqueline E W
2016-04-01
The aim of this study was to gain better insight into the quality of patient participation in the development of clinical practice guidelines and to contribute to approaches for the monitoring and evaluation of such initiatives. In addition, we explore the potential of a dialogue-based approach for reconciliation of preferences of patients and professionals in the guideline development processes. The development of the Multidisciplinary Guideline for Employment and Severe Mental Illness in the Netherlands served as a case study. Methods for patient involvement in guideline development included the following: four patient representatives in the development group and advisory committee, two focus group discussions with patients, a dialogue session and eight case studies. To evaluate the quality of patient involvement, we developed a monitoring and evaluation framework including both process and outcome criteria. Data collection included observations, document analysis and semi-structured interviews (n = 26). The quality of patient involvement was enhanced using different methods, reflection of patient input in the guideline text, a supportive attitude among professionals and attention to patient involvement throughout the process. The quality was lower with respect to representing the diversity of the target group, articulation of the patient perspective in the GDG, and clarity and transparency concerning methods of involvement. The monitoring and evaluation framework was useful in providing detailed insights into patient involvement in guideline development. Patient involvement was evaluated as being of good quality. The dialogue-based approach appears to be a promising method for obtaining integrated stakeholder input in a multidisciplinary setting. © 2015 John Wiley & Sons Ltd.
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2013-01-01
Background Practitioners who come into contact with the intoxicated, such as those in unscheduled care, often have limited resources to provide structured interventions. There is therefore a need for cost-effective alcohol interventions requiring minimal input. This study assesses the barriers, acceptability and validity of text messaging to collect daily alcohol consumption data and explores the feasibility of a text-delivered intervention in an exploratory randomised controlled trial. Methods Study I. Participants (n = 82) completed the initial online screening survey and those eligible were asked each day, for 157 days via text message, to reply with the number of alcohol units consumed the previous day. Analyses compared standard measures of hazardous consumption with self-report alcohol use. Attrition and sampling biases were examined. Study I included secondary exploratory analyses using data from 70 participants to determine associations between events (including Christmas and other celebratory occasions) and consumption. Study I further included the thematic analysis of semi-structured interview data and assessed the feasibility of and barriers to surveillance and interventions delivered through text messaging. Developing findings from Study I, Study II developed an exploratory randomised control trial that delivered a single message on monthly alcohol expenditure in order to assess effect size and test generalisability. Results Self-report alcohol consumption data was significantly associated with FAST and AUDIT scores. Attrition from the study was not associated with greater alcohol use. Greater alcohol use was observed on Fridays, Saturdays and Wednesdays as were notable celebratory events. Interview data indicated that text messaging was acceptable to participants and preferred over email and web-based methods. The exploratory randomised controlled trial suggested that a simple text delivered intervention might be effective in eliciting a reduction in alcohol consumption in a future trial. Conclusions The ubiquity of mobile telephones and the acceptability of text messaging suggests that this approach can be developed as a surveillance tool to collect high frequency consumption data to identify periods of vulnerability and that it can offer a platform through which targeted interventions can be delivered. PMID:24160674
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NASA Astrophysics Data System (ADS)
Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao
2017-03-01
Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction.
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System and method for improved rotor tip performance
NASA Technical Reports Server (NTRS)
Bussom, Richard (Inventor); McVeigh, Michael A. (Inventor); Narducci, Robert P. (Inventor); Zientek, Thomas A. (Inventor)
2010-01-01
Embodiments of systems and methods for enhancing the performance of rotary wing aircraft through reduced torque, noise and vibration are disclosed. In one embodiment, a method includes configuring the rotorcraft in a selected flight condition, communicating input signals to a control system operable to position sails coupled to tips of blades of a rotor assembly, processing the input signals according to a constraint condition to generate sail positional information, and transferring the sail positional information to the sail. Alternately, input signals may be communicated to a control system operable to position a plurality of sails, each sail having an aerodynamic shape and positioned proximate to a tip portion of the rotor blade. The input signals may be configured to rotate each sail about a longitudinal axis into a corresponding pitch angle independently of the other sails.
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The design of an intelligent human-computer interface for the test, control and monitor system
NASA Technical Reports Server (NTRS)
Shoaff, William D.
1988-01-01
The graphical intelligence and assistance capabilities of a human-computer interface for the Test, Control, and Monitor System at Kennedy Space Center are explored. The report focuses on how a particular commercial off-the-shelf graphical software package, Data Views, can be used to produce tools that build widgets such as menus, text panels, graphs, icons, windows, and ultimately complete interfaces for monitoring data from an application; controlling an application by providing input data to it; and testing an application by both monitoring and controlling it. A complete set of tools for building interfaces is described in a manual for the TCMS toolkit. Simple tools create primitive widgets such as lines, rectangles and text strings. Intermediate level tools create pictographs from primitive widgets, and connect processes to either text strings or pictographs. Other tools create input objects; Data Views supports output objects directly, thus output objects are not considered. Finally, a set of utilities for executing, monitoring use, editing, and displaying the content of interfaces is included in the toolkit.
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User's Guide for RESRAD-OFFSITE
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gnanapragasam, E.; Yu, C.
2015-04-01
The RESRAD-OFFSITE code can be used to model the radiological dose or risk to an offsite receptor. This User’s Guide for RESRAD-OFFSITE Version 3.1 is an update of the User’s Guide for RESRAD-OFFSITE Version 2 contained in the Appendix A of the User’s Manual for RESRAD-OFFSITE Version 2 (ANL/EVS/TM/07-1, DOE/HS-0005, NUREG/CR-6937). This user’s guide presents the basic information necessary to use Version 3.1 of the code. It also points to the help file and other documents that provide more detailed information about the inputs, the input forms and features/tools in the code; two of the features (overriding the source termmore » and computing area factors) are discussed in the appendices to this guide. Section 2 describes how to download and install the code and then verify the installation of the code. Section 3 shows ways to navigate through the input screens to simulate various exposure scenarios and to view the results in graphics and text reports. Section 4 has screen shots of each input form in the code and provides basic information about each parameter to increase the user’s understanding of the code. Section 5 outlines the contents of all the text reports and the graphical output. It also describes the commands in the two output viewers. Section 6 deals with the probabilistic and sensitivity analysis tools available in the code. Section 7 details the various ways of obtaining help in the code.« less
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Improved automatic adjustment of density and contrast in FCR system using neural network
NASA Astrophysics Data System (ADS)
Takeo, Hideya; Nakajima, Nobuyoshi; Ishida, Masamitsu; Kato, Hisatoyo
1994-05-01
FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.
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A Support System for Mouse Operations Using Eye-Gaze Input
NASA Astrophysics Data System (ADS)
Abe, Kiyohiko; Nakayama, Yasuhiro; Ohi, Shoichi; Ohyama, Minoru
We have developed an eye-gaze input system for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS) patients. This system utilizes a personal computer and a home video camera to detect eye-gaze under natural light. The system detects both vertical and horizontal eye-gaze by simple image analysis, and does not require special image processing units or sensors. Our conventional eye-gaze input system can detect horizontal eye-gaze with a high degree of accuracy. However, it can only classify vertical eye-gaze into 3 directions (up, middle and down). In this paper, we propose a new method for vertical eye-gaze detection. This method utilizes the limbus tracking method for vertical eye-gaze detection. Therefore our new eye-gaze input system can detect the two-dimension coordinates of user's gazing point. By using this method, we develop a new support system for mouse operation. This system can move the mouse cursor to user's gazing point.
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Chen, Dong; Coteus, Paul W; Eisley, Noel A; Gara, Alan; Heidelberger, Philip; Senger, Robert M; Salapura, Valentina; Steinmacher-Burow, Burkhard; Sugawara, Yutaka; Takken, Todd E
2013-08-27
Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.
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Peak-Seeking Control Using Gradient and Hessian Estimates
NASA Technical Reports Server (NTRS)
Ryan, John J.; Speyer, Jason L.
2010-01-01
A peak-seeking control method is presented which utilizes a linear time-varying Kalman filter. Performance function coordinate and magnitude measurements are used by the Kalman filter to estimate the gradient and Hessian of the performance function. The gradient and Hessian are used to command the system toward a local extremum. The method is naturally applied to multiple-input multiple-output systems. Applications of this technique to a single-input single-output example and a two-input one-output example are presented.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Yi; Jakeman, John; Gittelson, Claude
2015-01-08
In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained frommore » the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.« less
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Integration of Artificial Market Simulation and Text Mining for Market Analysis
NASA Astrophysics Data System (ADS)
Izumi, Kiyoshi; Matsui, Hiroki; Matsuo, Yutaka
We constructed an evaluation system of the self-impact in a financial market using an artificial market and text-mining technology. Economic trends were first extracted from text data circulating in the real world. Then, the trends were inputted into the market simulation. Our simulation revealed that an operation by intervention could reduce over 70% of rate fluctuation in 1995. By the simulation results, the system was able to help for its user to find the exchange policy which can stabilize the yen-dollar rate.
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NASA Technical Reports Server (NTRS)
Briggs, Maxwell; Schifer, Nicholas
2011-01-01
Test hardware used to validate net heat prediction models. Problem: Net Heat Input cannot be measured directly during operation. Net heat input is a key parameter needed in prediction of efficiency for convertor performance. Efficiency = Electrical Power Output (Measured) divided by Net Heat Input (Calculated). Efficiency is used to compare convertor designs and trade technology advantages for mission planning.
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NECAP 4.1: NASA's Energy-Cost Analysis Program fast input manual and example
NASA Technical Reports Server (NTRS)
Jensen, R. N.; Miner, D. L.
1982-01-01
NASA's Energy-Cost Analysis Program (NECAP) is a powerful computerized method to determine and to minimize building energy consumption. The program calculates hourly heat gain or losses taking into account the building thermal resistance and mass, using hourly weather and a response factor method. Internal temperatures are allowed to vary in accordance with thermostat settings and equipment capacity. NECAP 4.1 has a simplified input procedure and numerous other technical improvements. A very short input method is provided. It is limited to a single zone building. The user must still describe the building's outside geometry and select the type of system to be used.
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NASA Technical Reports Server (NTRS)
Silva, Walter A.; Vartio, Eric; Shimko, Anthony; Kvaternik, Raymond G.; Eure, Kenneth W.; Scott,Robert C.
2007-01-01
Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.
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NASA Technical Reports Server (NTRS)
Silva, Walter A.; Shimko, Anthony; Kvaternik, Raymond G.; Eure, Kenneth W.; Scott, Robert C.
2006-01-01
Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.
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Monitoring water quality in Northwest Atlantic coastal waters using dinoflagellate cysts
Nutrient pollution is a major environmental problem in many coastal waters around the US. Determining the total input of nutrients to estuaries is a challenge. One method to evaluate nutrient input is through nutrient loading models. Another method relies upon using indicators as...
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Simulated lumped-parameter system reduced-order adaptive control studies
NASA Technical Reports Server (NTRS)
Johnson, C. R., Jr.; Lawrence, D. A.; Taylor, T.; Malakooti, M. V.
1981-01-01
Two methods of interpreting the misbehavior of reduced order adaptive controllers are discussed. The first method is based on system input-output description and the second is based on state variable description. The implementation of the single input, single output, autoregressive, moving average system is considered.
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Signal Prediction With Input Identification
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Chen, Ya-Chin
1999-01-01
A novel coding technique is presented for signal prediction with applications including speech coding, system identification, and estimation of input excitation. The approach is based on the blind equalization method for speech signal processing in conjunction with the geometric subspace projection theory to formulate the basic prediction equation. The speech-coding problem is often divided into two parts, a linear prediction model and excitation input. The parameter coefficients of the linear predictor and the input excitation are solved simultaneously and recursively by a conventional recursive least-squares algorithm. The excitation input is computed by coding all possible outcomes into a binary codebook. The coefficients of the linear predictor and excitation, and the index of the codebook can then be used to represent the signal. In addition, a variable-frame concept is proposed to block the same excitation signal in sequence in order to reduce the storage size and increase the transmission rate. The results of this work can be easily extended to the problem of disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. Simulations are included to demonstrate the proposed method.
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Frømyr, Tomas-Roll; Bourgeaux-Goget, Marie; Hansen, Finn Knut
2015-05-01
A method has been developed to characterize the dispersion of multi-wall carbon nanotubes in water using a disc centrifuge for the detection of individual carbon nanotubes, residual aggregates, and contaminants. Carbon nanotubes produced by arc-discharge have been measured and compared with carbon nanotubes produced by chemical vapour deposition. Studies performed on both pristine (see text) arc-discharge nanotubes is rather strong and that high ultra-sound intensity is required to achieve complete dispersion of carbon nanotube bundles. The logarithm of the mode of the particle size distribution of the arc-discharge carbon nanotubes was found to be a linear function of the logarithm of the total ultrasonic energy input in the dispersion process.
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Text-to-audiovisual speech synthesizer for children with learning disabilities.
Mendi, Engin; Bayrak, Coskun
2013-01-01
Learning disabilities affect the ability of children to learn, despite their having normal intelligence. Assistive tools can highly increase functional capabilities of children with learning disorders such as writing, reading, or listening. In this article, we describe a text-to-audiovisual synthesizer that can serve as an assistive tool for such children. The system automatically converts an input text to audiovisual speech, providing synchronization of the head, eye, and lip movements of the three-dimensional face model with appropriate facial expressions and word flow of the text. The proposed system can enhance speech perception and help children having learning deficits to improve their chances of success.
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The Lexicocalorimeter: Gauging public health through caloric input and output on social media.
Alajajian, Sharon E; Williams, Jake Ryland; Reagan, Andrew J; Alajajian, Stephen C; Frank, Morgan R; Mitchell, Lewis; Lahne, Jacob; Danforth, Christopher M; Dodds, Peter Sheridan
2017-01-01
We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the "caloric content" of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity related phrases, and respectively assigning them with sourced estimates of caloric intake and expenditure. We show that for Twitter, our naive measures of "caloric input", "caloric output", and the ratio of these measures are all strong correlates with health and well-being measures for the contiguous United States. Our caloric balance measure in many cases outperforms both its constituent quantities; is tunable to specific health and well-being measures such as diabetes rates; has the capability of providing a real-time signal reflecting a population's health; and has the potential to be used alongside traditional survey data in the development of public policy and collective self-awareness. Because our Lexicocalorimeter is a linear superposition of principled phrase scores, we also show we can move beyond correlations to explore what people talk about in collective detail, and assist in the understanding and explanation of how population-scale conditions vary, a capacity unavailable to black-box type methods.
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Begum, S; Achary, P Ganga Raju
2015-01-01
Quantitative structure-activity relationship (QSAR) models were built for the prediction of inhibition (pIC50, i.e. negative logarithm of the 50% effective concentration) of MAP kinase-interacting protein kinase (MNK1) by 43 potent inhibitors. The pIC50 values were modelled with five random splits, with the representations of the molecular structures by simplified molecular input line entry system (SMILES). QSAR model building was performed by the Monte Carlo optimisation using three methods: classic scheme; balance of correlations; and balance correlation with ideal slopes. The robustness of these models were checked by parameters as rm(2), r(*)m(2), [Formula: see text] and randomisation technique. The best QSAR model based on single optimal descriptors was applied to study in vitro structure-activity relationships of 6-(4-(2-(piperidin-1-yl) ethoxy) phenyl)-3-(pyridin-4-yl) pyrazolo [1,5-a] pyrimidine derivatives as a screening tool for the development of novel potent MNK1 inhibitors. The effects of alkyl group, -OH, -NO2, F, Cl, Br, I, etc. on the IC50 values towards the inhibition of MNK1 were also reported.
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Prediction of Critical Power and W' in Hypoxia: Application to Work-Balance Modelling.
Townsend, Nathan E; Nichols, David S; Skiba, Philip F; Racinais, Sebastien; Périard, Julien D
2017-01-01
Purpose: Develop a prediction equation for critical power (CP) and work above CP (W') in hypoxia for use in the work-balance ([Formula: see text]) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W' at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W' at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W' were used to compute W' during HIIT using differential ([Formula: see text]) and integral ([Formula: see text]) forms of the [Formula: see text] model. Results: CP decreased at altitude ( P < 0.001) as described by 3rd order polynomial function ( R 2 = 0.99). W' decreased at 4,250 m only ( P < 0.001). A double-linear function characterized the effect of altitude on W' ( R 2 = 0.99). There was no significant effect of parameter input (actual vs. predicted CP and W') on modelled [Formula: see text] at 2,250 m ( P = 0.24). [Formula: see text] returned higher values than [Formula: see text] throughout HIIT ( P < 0.001). During HIIT, [Formula: see text] was not different to 0 kJ at completion, at 250 m (0.7 ± 2.0 kJ; P = 0.33) and 2,250 m (-1.3 ± 3.5 kJ; P = 0.30). However, [Formula: see text] was lower than 0 kJ at 250 m (-0.9 ± 1.3 kJ; P = 0.058) and 2,250 m (-2.8 ± 2.8 kJ; P = 0.02). Conclusion: The altitude prediction equations for CP and W' developed in this study are suitable for use with the [Formula: see text] model in acute hypoxia. This enables the application of [Formula: see text] modelling to training prescription and competition analysis at altitude.
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NASA Astrophysics Data System (ADS)
Nakano, Takuma; Yazawa, Shota; Araki, Shota; Kogoshi, Sumio; Katayama, Noboru; Kudo, Yusuke; Nakanishi, Tetsuya
2015-01-01
Oxygen-deficient TiO2 (TiO2-x) has been proposed as a visible-light-responsive photocatalyst. TiO2-x thin films were prepared by Ar/H2 plasma surface treatment, applying varying levels of microwave input power and processing times. The highest visible light photocatalytic activity was observed when using an input power of 200 W, a plasma processing time of 10 min, and a 1:1 \\text{Ar}:\\text{H}2 ratio, conditions that generate an electron temperature of 5.7(±1.0) eV and an electron density of 8.5 × 1010 cm-3. The maximum formaldehyde (HCHO) removal rate of the TiO2-x film was 2.6 times higher than that obtained from a TiO2-xNx film under the same test conditions.
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Joint statistics of strongly correlated neurons via dimensionality reduction
NASA Astrophysics Data System (ADS)
Deniz, Taşkın; Rotter, Stefan
2017-06-01
The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input.
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Probabilistic Methods for Uncertainty Propagation Applied to Aircraft Design
NASA Technical Reports Server (NTRS)
Green, Lawrence L.; Lin, Hong-Zong; Khalessi, Mohammad R.
2002-01-01
Three methods of probabilistic uncertainty propagation and quantification (the method of moments, Monte Carlo simulation, and a nongradient simulation search method) are applied to an aircraft analysis and conceptual design program to demonstrate design under uncertainty. The chosen example problems appear to have discontinuous design spaces and thus these examples pose difficulties for many popular methods of uncertainty propagation and quantification. However, specific implementation features of the first and third methods chosen for use in this study enable successful propagation of small uncertainties through the program. Input uncertainties in two configuration design variables are considered. Uncertainties in aircraft weight are computed. The effects of specifying required levels of constraint satisfaction with specified levels of input uncertainty are also demonstrated. The results show, as expected, that the designs under uncertainty are typically heavier and more conservative than those in which no input uncertainties exist.
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NASA Astrophysics Data System (ADS)
Hameed, M.; Demirel, M. C.; Moradkhani, H.
2015-12-01
Global Sensitivity Analysis (GSA) approach helps identify the effectiveness of model parameters or inputs and thus provides essential information about the model performance. In this study, the effects of the Sacramento Soil Moisture Accounting (SAC-SMA) model parameters, forcing data, and initial conditions are analysed by using two GSA methods: Sobol' and Fourier Amplitude Sensitivity Test (FAST). The simulations are carried out over five sub-basins within the Columbia River Basin (CRB) for three different periods: one-year, four-year, and seven-year. Four factors are considered and evaluated by using the two sensitivity analysis methods: the simulation length, parameter range, model initial conditions, and the reliability of the global sensitivity analysis methods. The reliability of the sensitivity analysis results is compared based on 1) the agreement between the two sensitivity analysis methods (Sobol' and FAST) in terms of highlighting the same parameters or input as the most influential parameters or input and 2) how the methods are cohered in ranking these sensitive parameters under the same conditions (sub-basins and simulation length). The results show the coherence between the Sobol' and FAST sensitivity analysis methods. Additionally, it is found that FAST method is sufficient to evaluate the main effects of the model parameters and inputs. Another conclusion of this study is that the smaller parameter or initial condition ranges, the more consistency and coherence between the sensitivity analysis methods results.
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Synthesis of image sequences for Korean sign language using 3D shape model
NASA Astrophysics Data System (ADS)
Hong, Mun-Ho; Choi, Chang-Seok; Kim, Chang-Seok; Jeon, Joon-Hyeon
1995-05-01
This paper proposes a method for offering information and realizing communication to the deaf-mute. The deaf-mute communicates with another person by means of sign language, but most people are unfamiliar with it. This method enables to convert text data into the corresponding image sequences for Korean sign language (KSL). Using a general 3D shape model of the upper body leads to generating the 3D motions of KSL. It is necessary to construct the general 3D shape model considering the anatomical structure of the human body. To obtain a personal 3D shape model, this general model is to adjust to the personal base images. Image synthesis for KSL consists of deforming a personal 3D shape model and texture-mapping the personal images onto the deformed model. The 3D motions for KSL have the facial expressions and the 3D movements of the head, trunk, arms and hands and are parameterized for easily deforming the model. These motion parameters of the upper body are extracted from a skilled signer's motion for each KSL and are stored to the database. Editing the parameters according to the inputs of text data yields to generate the image sequences of 3D motions.
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Oscar, Nels; Fox, Pamela A; Croucher, Racheal; Wernick, Riana; Keune, Jessica; Hooker, Karen
2017-09-01
Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer's disease (AD) and dementia portrayal on Twitter to demonstrate its use. The approach improves feasibility of examining large publicly available datasets. Machine learning techniques modeled stigmatization expressed in 31,150 AD-related tweets collected via Twitter's search API based on 9 AD-related keywords. Two researchers manually coded 311 random tweets on 6 dimensions. This input from 1% of the dataset was used to train a classifier against the tweet text and code the remaining 99% of the dataset. Our automated process identified that 21.13% of the AD-related tweets used AD-related keywords to perpetuate public stigma, which could impact stereotypes and negative expectations for individuals with the disease and increase "excess disability". This technique could be applied to questions in social gerontology related to how social media outlets reflect and shape attitudes bearing on other developmental outcomes. Recommendations for the collection and analysis of large Twitter datasets are discussed. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Affine Projection Algorithm with Improved Data-Selective Method Using the Condition Number
NASA Astrophysics Data System (ADS)
Ban, Sung Jun; Lee, Chang Woo; Kim, Sang Woo
Recently, a data-selective method has been proposed to achieve low misalignment in affine projection algorithm (APA) by keeping the condition number of an input data matrix small. We present an improved method, and a complexity reduction algorithm for the APA with the data-selective method. Experimental results show that the proposed algorithm has lower misalignment and a lower condition number for an input data matrix than both the conventional APA and the APA with the previous data-selective method.
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Zeng, Xiaozheng; McGough, Robert J.
2009-01-01
The angular spectrum approach is evaluated for the simulation of focused ultrasound fields produced by large thermal therapy arrays. For an input pressure or normal particle velocity distribution in a plane, the angular spectrum approach rapidly computes the output pressure field in a three dimensional volume. To determine the optimal combination of simulation parameters for angular spectrum calculations, the effect of the size, location, and the numerical accuracy of the input plane on the computed output pressure is evaluated. Simulation results demonstrate that angular spectrum calculations performed with an input pressure plane are more accurate than calculations with an input velocity plane. Results also indicate that when the input pressure plane is slightly larger than the array aperture and is located approximately one wavelength from the array, angular spectrum simulations have very small numerical errors for two dimensional planar arrays. Furthermore, the root mean squared error from angular spectrum simulations asymptotically approaches a nonzero lower limit as the error in the input plane decreases. Overall, the angular spectrum approach is an accurate and robust method for thermal therapy simulations of large ultrasound phased arrays when the input pressure plane is computed with the fast nearfield method and an optimal combination of input parameters. PMID:19425640
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The human motor neuron pools receive a dominant slow‐varying common synaptic input
Negro, Francesco; Yavuz, Utku Şükrü
2016-01-01
Key points Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated.Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non‐linearity of motor neurons.We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (<5 Hz) to motor neurons in humans.We applied the proposed method to three human muscles and determined experimentally that they receive a similar large amount (>60%) of common input, irrespective of their different functional and control properties.These results increase our knowledge about the role of common and independent input to motor neurons in force control. Abstract Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (<5 Hz) to a motor neuron pool in humans. This estimate is based on a phenomenological model and the theoretical fitting of the experimental values of coherence between the permutations of groups of motor unit spike trains. We demonstrate the validity of this theoretical estimate with several simulations. Moreover, we applied this method to three human muscles: the abductor digiti minimi, tibialis anterior and vastus medialis. Despite these muscles having different functional roles and control properties, as confirmed by the results of the present study, we estimate that their motor pools receive a similar and large (>60%) proportion of common low frequency oscillations with respect to their total synaptic input. These results suggest that the central nervous system provides a large amount of common input to motor neuron pools, in a similar way to that for muscles with different functional and control properties. PMID:27151459
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Room-temperature quantum noise limited spectrometry and methods of the same
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stevens, Charles G.; Tringe, Joseph W.; Cunningham, Christopher T.
According to one embodiment, a heterodyne detection system for detecting light, includes: a first input aperture configured to receive first light from a scene input; a second input aperture configured to receive second light from a local oscillator input; a broadband local oscillator configured to provide the second light to the second input aperture; a dispersive element configured to disperse the first light and the second light; and a final condensing lens coupled to a detector. The final condensing lens is configured to concentrate incident light from a primary condensing lens onto the detector. The detector is configured to sensemore » a frequency difference between the first light and the second light; and the final condensing lens comprises a plasmonic condensing lens. Methods for forming a plasmonic condensing lens to enable room temperature quantum noise limited spectrometry are also disclosed.« less
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Apparatus and method for combining light from two or more fibers into a single fiber
Klingsporn, Paul Edward
2007-02-20
An apparatus and method for combining light signals carried on a plurality of input fibers onto a single receiving fiber with a high degree of efficiency. The apparatus broadly comprises the receiving fiber and a plurality of input fiber-lens assemblies, with each fiber lens assembly including an input fiber; a collimating lens interposed between the input fiber and the receiving fiber and adapted to collimate the light signal; and a focusing lens interposed between the collimating lens and the receiving fiber and adapted to focus the collimated light signal onto the face of the receiving fiber. The components of each fiber-lens assembly are oriented along an optic axis that is inclined relative to the receiving fiber, with the inclination angle depending at least in part on the input fiber's numerical aperture and the focal lengths and diameters of the collimating and focusing lenses.
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Apparatus and method for combining light from two or more fibers into a single fiber
Klingsporn, Paul Edward
2006-03-14
An apparatus and method for combining light signals carried on a plurality of input fibers onto a single receiving fiber with a high degree of efficiency. The apparatus broadly comprises the receiving fiber and a plurality of input fiber-lens assemblies, with each fiber lens assembly including an input fiber; a collimating lens interposed between the input fiber and the receiving fiber and adapted to collimate the light signal; and a focusing lens interposed between the collimating lens and the receiving fiber and adapted to focus the collimated light signal onto the face of the receiving fiber. The components of each fiber-lens assembly are oriented along an optic axis that is inclined relative to the receiving fiber, with the inclination angle depending at least in part on the input fiber's numerical aperture and the focal lengths and diameters of the collimating and focusing lenses.
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Systems and methods for predicting materials properties
Ceder, Gerbrand; Fischer, Chris; Tibbetts, Kevin; Morgan, Dane; Curtarolo, Stefano
2007-11-06
Systems and methods for predicting features of materials of interest. Reference data are analyzed to deduce relationships between the input data sets and output data sets. Reference data includes measured values and/or computed values. The deduced relationships can be specified as equations, correspondences, and/or algorithmic processes that produce appropriate output data when suitable input data is used. In some instances, the output data set is a subset of the input data set, and computational results may be refined by optionally iterating the computational procedure. To deduce features of a new material of interest, a computed or measured input property of the material is provided to an equation, correspondence, or algorithmic procedure previously deduced, and an output is obtained. In some instances, the output is iteratively refined. In some instances, new features deduced for the material of interest are added to a database of input and output data for known materials.
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Reservoir property grids improve with geostatistics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vogt, J.
1993-09-01
Visualization software, reservoir simulators and many other E and P software applications need reservoir property grids as input. Using geostatistics, as compared to other gridding methods, to produce these grids leads to the best output from the software programs. For the purpose stated herein, geostatistics is simply two types of gridding methods. Mathematically, these methods are based on minimizing or duplicating certain statistical properties of the input data. One geostatical method, called kriging, is used when the highest possible point-by-point accuracy is desired. The other method, called conditional simulation, is used when one wants statistics and texture of the resultingmore » grid to be the same as for the input data. In the following discussion, each method is explained, compared to other gridding methods, and illustrated through example applications. Proper use of geostatistical data in flow simulations, use of geostatistical data for history matching, and situations where geostatistics has no significant advantage over other methods, also will be covered.« less
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Influential input classification in probabilistic multimedia models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.
1999-05-01
Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions onemore » should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.« less
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Method and system for continuous atomic layer deposition
Elam, Jeffrey W.; Yanguas-Gil, Angel; Libera, Joseph A.
2017-03-21
A system and method for continuous atomic layer deposition. The system and method includes a housing, a moving bed which passes through the housing, a plurality of precursor gases and associated input ports and the amount of precursor gases, position of the input ports, and relative velocity of the moving bed and carrier gases enabling exhaustion of the precursor gases at available reaction sites.
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Konstantinidis, Spyridon; Titchener-Hooker, Nigel; Velayudhan, Ajoy
2017-08-01
Bioprocess development studies often involve the investigation of numerical and categorical inputs via the adoption of Design of Experiments (DoE) techniques. An attractive alternative is the deployment of a grid compatible Simplex variant which has been shown to yield optima rapidly and consistently. In this work, the method is combined with dummy variables and it is deployed in three case studies wherein spaces are comprised of both categorical and numerical inputs, a situation intractable by traditional Simplex methods. The first study employs in silico data and lays out the dummy variable methodology. The latter two employ experimental data from chromatography based studies performed with the filter-plate and miniature column High Throughput (HT) techniques. The solute of interest in the former case study was a monoclonal antibody whereas the latter dealt with the separation of a binary system of model proteins. The implemented approach prevented the stranding of the Simplex method at local optima, due to the arbitrary handling of the categorical inputs, and allowed for the concurrent optimization of numerical and categorical, multilevel and/or dichotomous, inputs. The deployment of the Simplex method, combined with dummy variables, was therefore entirely successful in identifying and characterizing global optima in all three case studies. The Simplex-based method was further shown to be of equivalent efficiency to a DoE-based approach, represented here by D-Optimal designs. Such an approach failed, however, to both capture trends and identify optima, and led to poor operating conditions. It is suggested that the Simplex-variant is suited to development activities involving numerical and categorical inputs in early bioprocess development. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Gold, Judith E; Rauscher, Kimberly J; Zhu, Motao
2015-04-02
Texting is associated with adverse health effects including musculoskeletal disorders, sleep disturbances, and traffic crashes. Many studies have relied on self-reported texting frequency, yet the validity of self-reports is unknown. Our objective was to provide some of the first data on the validity of self-reported texting frequency, cell phone characteristics including input device (e.g. touchscreen), key configuration (e.g., QWERTY), and texting styles including phone orientation (e.g., horizontal) and hands holding the phone while texting. Data were collected using a self-administered questionnaire and observation of a texting task among college students ages 18 to 24. To gauge agreement between self-reported and phone bill-derived categorical number of daily text messages sent, we calculated percent of agreement, Spearman correlation coefficient, and a linear weighted kappa statistic. For agreement between self-reported and observed cell phone characteristics and texting styles we calculated percentages of agreement. We used chi-square tests to detect significant differences (α = 0.05) by gender and study protocol. There were 106 participants; 87 of which had complete data for texting frequency analyses. Among these 87, there was 26% (95% CI: 21-31) agreement between self-reported and phone bill-derived number of daily text messages sent with a Spearman's rho of 0.48 and a weighted kappa of 0.17 (95% CI: 0.06-0.27). Among those who did not accurately report the number of daily texts sent, 81% overestimated this number. Among the full sample (n = 106), there was high agreement between self-reported and observed texting input device (96%, 95% CI: 91-99), key configuration (89%, 95% CI: 81-94), and phone orientation while texting (93%, 95% CI: 86-97). No differences were found by gender or study protocol among any items. While young adults correctly reported their cell phone's characteristics and phone orientation while texting, most incorrectly estimated the number of daily text messages they sent. This suggests that while self-reported texting frequency may be useful for studies where relative ordering is adequate, it should not be used in epidemiologic studies to identify a risk threshold. For these studies, it is recommended that a less biased measure, such as a cell phone bill, be utilized.
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SutraPrep, a pre-processor for SUTRA, a model for ground-water flow with solute or energy transport
Provost, Alden M.
2002-01-01
SutraPrep facilitates the creation of three-dimensional (3D) input datasets for the USGS ground-water flow and transport model SUTRA Version 2D3D.1. It is most useful for applications in which the geometry of the 3D model domain and the spatial distribution of physical properties and boundary conditions is relatively simple. SutraPrep can be used to create a SUTRA main input (?.inp?) file, an initial conditions (?.ics?) file, and a 3D plot of the finite-element mesh in Virtual Reality Modeling Language (VRML) format. Input and output are text-based. The code can be run on any platform that has a standard FORTRAN-90 compiler. Executable code is available for Microsoft Windows.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Tauke-Pedretti, Anna; Skogen, Erik J; Vawter, Gregory A
An optical sampler includes a first and second 1.times.n optical beam splitters splitting an input optical sampling signal and an optical analog input signal into n parallel channels, respectively, a plurality of optical delay elements providing n parallel delayed input optical sampling signals, n photodiodes converting the n parallel optical analog input signals into n respective electrical output signals, and n optical modulators modulating the input optical sampling signal or the optical analog input signal by the respective electrical output signals, and providing n successive optical samples of the optical analog input signal. A plurality of output photodiodes and eADCsmore » convert the n successive optical samples to n successive digital samples. The optical modulator may be a photodiode interconnected Mach-Zehnder Modulator. A method of sampling the optical analog input signal is disclosed.« less
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Computer retrieval of bibliographies using an editing program
Brethauer, G.E.; Brokaw, V.L.
1979-01-01
A simple program permits use of the text .editor 'qedx,' part of many computer systems, to input bibliographic entries and to retrieve specific entries which contain keywords of interest. Multiple keywords may be used sequentially to find specific entries.
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NASA Astrophysics Data System (ADS)
Cai, Xiushan; Meng, Lingxin; Zhang, Wei; Liu, Leipo
2018-03-01
We establish robustness of the predictor feedback control law to perturbations appearing at the system input for affine nonlinear systems with time-varying input delay and additive disturbances. Furthermore, it is shown that it is inverse optimal with respect to a differential game problem. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation and an appropriate Lyapunov functional. A single-link manipulator subject to input delays and disturbances is given to illustrate the validity of the proposed method.
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Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M
2017-10-01
Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal transmission. This is the first application of a deterministic state-space model to represent the discharge characteristics of motor units during voluntary contractions. Copyright © 2017 the American Physiological Society.
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Method and apparatus for wavefront sensing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bahk, Seung-Whan
A method for performing optical wavefront sensing includes providing an amplitude transmission mask having a light input side, a light output side, and an optical transmission axis passing from the light input side to the light output side. The amplitude transmission mask is characterized by a checkerboard pattern having a square unit cell of size .LAMBDA.. The method also includes directing an incident light field having a wavelengthmore » $$ \\lamda $$ to be incident on the light input side and propagating the incident light field through the amplitude transmission mask. The method further includes producing a plurality of diffracted light fields on the light output side and detecting, at a detector disposed a distance L from the amplitude transmission mask, an interferogram associated with the plurality of diffracted light fields.« less
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Preshaping command inputs to reduce telerobotic system oscillations
NASA Technical Reports Server (NTRS)
Singer, Neil C.; Seering, Warren P.
1989-01-01
The results of using a new technique for shaping inputs to a model of the space shuttle Remote Manipulator System (RMS) are presented. The shapes inputs move the system to the same location that was originally commanded, however, the oscillations of the machine are considerably reduced. An overview of the new shaping method is presented. A description of RMS model is provided. The problem of slow joint servo rates on the RMS is accommodated with an extension of the shaping method. The results and sample data are also presented for both joint and three-dimensional cartesian motions. The results demonstrate that the new shaping method performs well on large, telerobotic systems which exhibit significant structural vibration. The new method is shown to also result in considerable energy savings during operations of the RMS manipulator.
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Molecular structure input on the web.
Ertl, Peter
2010-02-02
A molecule editor, that is program for input and editing of molecules, is an indispensable part of every cheminformatics or molecular processing system. This review focuses on a special type of molecule editors, namely those that are used for molecule structure input on the web. Scientific computing is now moving more and more in the direction of web services and cloud computing, with servers scattered all around the Internet. Thus a web browser has become the universal scientific user interface, and a tool to edit molecules directly within the web browser is essential.The review covers a history of web-based structure input, starting with simple text entry boxes and early molecule editors based on clickable maps, before moving to the current situation dominated by Java applets. One typical example - the popular JME Molecule Editor - will be described in more detail. Modern Ajax server-side molecule editors are also presented. And finally, the possible future direction of web-based molecule editing, based on technologies like JavaScript and Flash, is discussed.
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Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions.
Chandrakar, Kamal Kant; Cantrell, Will; Chang, Kelken; Ciochetto, David; Niedermeier, Dennis; Ovchinnikov, Mikhail; Shaw, Raymond A; Yang, Fan
2016-12-13
The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics ([Formula: see text]) for high aerosol concentration, and slow microphysics ([Formula: see text]) for low aerosol concentration; here, [Formula: see text] is the phase-relaxation time and [Formula: see text] is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as [Formula: see text], and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.
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An attention-based effective neural model for drug-drug interactions extraction.
Zheng, Wei; Lin, Hongfei; Luo, Ling; Zhao, Zhehuan; Li, Zhengguang; Zhang, Yijia; Yang, Zhihao; Wang, Jian
2017-10-10
Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory. In this study, we propose an effective model that classifies DDIs from the literature by combining an attention mechanism and a recurrent neural network with long short-term memory (LSTM) units. In our approach, first, a candidate-drug-oriented input attention acting on word-embedding vectors automatically learns which words are more influential for a given drug pair. Next, the inputs merging the position- and POS-embedding vectors are passed to a bidirectional LSTM layer whose outputs at the last time step represent the high-level semantic information of the whole sentence. Finally, a softmax layer performs DDI classification. Experimental results from the DDIExtraction 2013 corpus show that our system performs the best with respect to detection and classification (84.0% and 77.3%, respectively) compared with other state-of-the-art methods. In particular, for the Medline-2013 dataset with long and complex sentences, our F-score far exceeds those of top-ranking systems by 12.6%. Our approach effectively improves the performance of DDI classification tasks. Experimental analysis demonstrates that our model performs better with respect to recognizing not only close-range but also long-range patterns among words, especially for long, complex and compound sentences.
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Inverse methods for estimating primary input signals from time-averaged isotope profiles
NASA Astrophysics Data System (ADS)
Passey, Benjamin H.; Cerling, Thure E.; Schuster, Gerard T.; Robinson, Todd F.; Roeder, Beverly L.; Krueger, Stephen K.
2005-08-01
Mammalian teeth are invaluable archives of ancient seasonality because they record along their growth axes an isotopic record of temporal change in environment, plant diet, and animal behavior. A major problem with the intra-tooth method is that intra-tooth isotope profiles can be extremely time-averaged compared to the actual pattern of isotopic variation experienced by the animal during tooth formation. This time-averaging is a result of the temporal and spatial characteristics of amelogenesis (tooth enamel formation), and also results from laboratory sampling. This paper develops and evaluates an inverse method for reconstructing original input signals from time-averaged intra-tooth isotope profiles. The method requires that the temporal and spatial patterns of amelogenesis are known for the specific tooth and uses a minimum length solution of the linear system Am = d, where d is the measured isotopic profile, A is a matrix describing temporal and spatial averaging during amelogenesis and sampling, and m is the input vector that is sought. Accuracy is dependent on several factors, including the total measurement error and the isotopic structure of the measured profile. The method is shown to accurately reconstruct known input signals for synthetic tooth enamel profiles and the known input signal for a rabbit that underwent controlled dietary changes. Application to carbon isotope profiles of modern hippopotamus canines reveals detailed dietary histories that are not apparent from the measured data alone. Inverse methods show promise as an effective means of dealing with the time-averaging problem in studies of intra-tooth isotopic variation.
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Optimal input sizes for neural network de-interlacing
NASA Astrophysics Data System (ADS)
Choi, Hyunsoo; Seo, Guiwon; Lee, Chulhee
2009-02-01
Neural network de-interlacing has shown promising results among various de-interlacing methods. In this paper, we investigate the effects of input size for neural networks for various video formats when the neural networks are used for de-interlacing. In particular, we investigate optimal input sizes for CIF, VGA and HD video formats.
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Field measurement of moisture-buffering model inputs for residential buildings
Woods, Jason; Winkler, Jon
2016-02-05
Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less
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Assessing the skeletal age from a hand radiograph: automating the Tanner-Whitehouse method
NASA Astrophysics Data System (ADS)
Niemeijer, Meindert; van Ginneken, Bram; Maas, Casper A.; Beek, Frederik J. A.; Viergever, Max A.
2003-05-01
The skeletal maturity of children is usually assessed from a standard radiograph of the left hand and wrist. An established clinical method to determine the skeletal maturity is the Tanner-Whitehouse (TW2) method. This method divides the skeletal development into several stages (labelled A, B, ...,I). We are developing an automated system based on this method. In this work we focus on assigning a stage to one region of interest (ROI), the middle phalanx of the third finger. We classify each ROI as follows. A number of ROIs which have been assigned a certain stage by a radiologist are used to construct a mean image for that stage. For a new input ROI, landmarks are detected by using an Active Shape Model. These are used to align the mean images with the input image. Subsequently the correlation between each transformed mean stage image and the input is calculated. The input ROI can be assigned to the stage with the highest correlation directly, or the values can be used as features in a classifier. The method was tested on 71 cases ranging from stage E to I. The ROI was staged correctly in 73.2% of all cases and in 97.2% of all incorrectly staged cases the error was not more than one stage.
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Kaltsa, O; Michon, C; Yanniotis, S; Mandala, I
2013-05-01
Ultrasonication may be a cost-effective emulsion formation technique, but its impact on emulsion final structure and droplet size needs to be further investigated. Olive oil emulsions (20wt%) were formulated (pH∼7) using whey protein (3wt%), three kinds of hydrocolloids (0.1-0.5wt%) and two different emulsification energy inputs (single- and two-stage, methods A and B, respectively). Formula and energy input effects on emulsion performance are discussed. Emulsions stability was evaluated over a 10-day storage period at 5°C recording the turbidity profiles of the emulsions. Optical micrographs, droplet size and viscosity values were also obtained. A differential scanning calorimetric (DSC) multiple cool-heat cyclic method (40 to -40°C) was performed to examine stability via crystallization phenomena of the dispersed phase. Ultrasonication energy input duplication from 11kJ to 25kJ (method B) resulted in stable emulsions production (reduction of back scattering values, dBS∼1% after 10days of storage) at 0.5wt% concentration of any of the stabilizers used. At lower gum amount samples became unstable due to depletion flocculation phenomena, regardless of emulsification energy input used. High energy input during ultrasonic emulsification also resulted in sub-micron oil-droplets emulsions (D(50)=0.615μm compared to D(50)=1.3μm using method A) with narrower particle size distribution and in viscosity reduction. DSC experiments revealed no presence of bulk oil formation, suggesting stability for XG 0.5wt% emulsions prepared by both methods. Reduced enthalpy values found when method B was applied suggesting structural modifications produced by extensive ultrasonication. Change of ultrasonication conditions results in significant changes of oil droplet size and stability of the produced emulsions. Copyright © 2012 Elsevier B.V. All rights reserved.
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Reservoir water level forecasting using group method of data handling
NASA Astrophysics Data System (ADS)
Zaji, Amir Hossein; Bonakdari, Hossein; Gharabaghi, Bahram
2018-06-01
Accurately forecasted reservoir water level is among the most vital data for efficient reservoir structure design and management. In this study, the group method of data handling is combined with the minimum description length method to develop a very practical and functional model for predicting reservoir water levels. The models' performance is evaluated using two groups of input combinations based on recent days and recent weeks. Four different input combinations are considered in total. The data collected from Chahnimeh#1 Reservoir in eastern Iran are used for model training and validation. To assess the models' applicability in practical situations, the models are made to predict a non-observed dataset for the nearby Chahnimeh#4 Reservoir. According to the results, input combinations (L, L -1) and (L, L -1, L -12) for recent days with root-mean-squared error (RMSE) of 0.3478 and 0.3767, respectively, outperform input combinations (L, L -7) and (L, L -7, L -14) for recent weeks with RMSE of 0.3866 and 0.4378, respectively, with the dataset from https://www.typingclub.com/st. Accordingly, (L, L -1) is selected as the best input combination for making 7-day ahead predictions of reservoir water levels.
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NASA Astrophysics Data System (ADS)
Muinul Islam, Muhammad; Tsujikawa, Tetsuya; Mori, Tetsuya; Kiyono, Yasushi; Okazawa, Hidehiko
2017-06-01
A noninvasive method to estimate input function directly from H2 15O brain PET data for measurement of cerebral blood flow (CBF) was proposed in this study. The image derived input function (IDIF) method extracted the time-activity curves (TAC) of the major cerebral arteries at the skull base from the dynamic PET data. The extracted primordial IDIF showed almost the same radioactivity as the arterial input function (AIF) from sampled blood at the plateau part in the later phase, but significantly lower radioactivity in the initial arterial phase compared with that of AIF-TAC. To correct the initial part of the IDIF, a dispersion function was applied and two constants for the correction were determined by fitting with the individual AIF in 15 patients with unilateral arterial stenoocclusive lesions. The area under the curves (AUC) from the two input functions showed good agreement with the mean AUCIDIF/AUCAIF ratio of 0.92 ± 0.09. The final products of CBF and arterial-to-capillary vascular volume (V 0) obtained from the IDIF and AIF showed no difference, and had with high correlation coefficients.
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Sensitivity Analysis of the Integrated Medical Model for ISS Programs
NASA Technical Reports Server (NTRS)
Goodenow, D. A.; Myers, J. G.; Arellano, J.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Young, M.
2016-01-01
Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.
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NASA Technical Reports Server (NTRS)
Wang, Ray (Inventor)
2009-01-01
A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.
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NASA Astrophysics Data System (ADS)
Zheng, Guangdi; Pan, Mingbo; Liu, Wei; Wu, Xuetong
2018-03-01
The target identification of the sea battlefield is the prerequisite for the judgment of the enemy in the modern naval battle. In this paper, a collaborative identification method based on convolution neural network is proposed to identify the typical targets of sea battlefields. Different from the traditional single-input/single-output identification method, the proposed method constructs a multi-input/single-output co-identification architecture based on optimized convolution neural network and weighted D-S evidence theory. The simulation results show that
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An Application of Cartesian-Grid and Volume-of-Fluid Methods to Numerical Ship Hydrodynamics
2007-10-01
water-particle ve- locity is discontinuous across the air-water interface, and where CiEA is the Levi - Civita function. rj is the moment the vertical...methods and volume-of- immersed- body and volume-of-fluid (VOF) methods. fluid methods is used to simulate breaking waves around The governing equations are...of a ship hull is used as input to automat- body -fitted grids. The sole geometric input into NFA ically generate an immersed-boundary representation of
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Majima, Yutaka; Hackenberger, Guillaume; Azuma, Yasuo; Kano, Shinya; Matsuzaki, Kosuke; Susaki, Tomofumi; Sakamoto, Masanori; Teranishi, Toshiharu
2017-01-01
Single-electron transistors (SETs) are sub-10-nm scale electronic devices based on conductive Coulomb islands sandwiched between double-barrier tunneling barriers. Chemically assembled SETs with alkanethiol-protected Au nanoparticles show highly stable Coulomb diamonds and two-input logic operations. The combination of bottom-up and top-down processes used to form the passivation layer is vital for realizing multi-gate chemically assembled SET circuits, as this combination enables us to connect conventional complementary metal oxide semiconductor (CMOS) technologies via planar processes. Here, three-input gate exclusive-OR (XOR) logic operations are demonstrated in passivated chemically assembled SETs. The passivation layer is a hybrid bilayer of self-assembled monolayers (SAMs) and pulsed laser deposited (PLD) aluminum oxide (AlO[Formula: see text]), and top-gate electrodes were prepared on the hybrid passivation layers. Top and two-side-gated SETs showed clear Coulomb oscillation and diamonds for each of the three available gates, and three-input gate XOR logic operation was clearly demonstrated. These results show the potential of chemically assembled SETs to work as logic devices with multi-gate inputs using organic and inorganic hybrid passivation layers.
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Farmer, Shu; Mindry, Deborah; Comulada, W Scott; Swendeman, Dallas
Stressful life events and daily hassles affect people living with HIV (PLWH). However, capturing stress-related events and cognitive impairment is often plagued with recall biases. Incorporating reliable information technology, such as mobile phones, can be a resourceful method for measuring health behaviors (MHB). We report findings from an MHB pilot study with 32 African American, Latino/Hispanic, and White PLWH from Los Angeles. Participants reported perceived stressors in their daily routines using a smartphone Ecological Momentary Assessment (EMA) application. Participants self-initiated in-the-moment stressful events reports for up to 6 weeks. Stressful event EMAs queried perceived stress levels (1-10 scale) and open-ended text descriptions. Qualitative analysis of participant text responses was completed using grounded thematic coding. Participants reported multiple stressors in their daily routines, impacting activities of daily living or daily functioning. Eliciting input from PLWH via EMA in real time is a novel approach for assessing and identifying sources of stress. Copyright © 2017 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.
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Method and apparatus for measuring response time
Johanson, Edward W.; August, Charles
1985-01-01
A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.
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Method and apparatus for measuring response time
Johanson, E.W.; August, C.
1983-08-11
A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.
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Method and apparatus for clockless analog-to-digital conversion and peak detection
DeGeronimo, Gianluigi
2007-03-06
An apparatus and method for analog-to-digital conversion and peak detection includes at least one stage, which includes a first switch, second switch, current source or capacitor, and discriminator. The discriminator changes state in response to a current or charge associated with the input signal exceeding a threshold, thereby indicating whether the current or charge associated with the input signal is greater than the threshold. The input signal includes a peak or a charge, and the converter includes a peak or charge detect mode in which a state of the switch is retained in response to a decrease in the current or charge associated with the input signal. The state of the switch represents at least a portion of a value of the peak or of the charge.
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NASA Technical Reports Server (NTRS)
On, F. J.
1975-01-01
Test methods were evaluated to ascertain whether a spacecraft, properly tested within its shroud, could be vibroacoustic tested without the shroud, with adjustments made in the acoustic input spectra to simulate the acoustic response of the missing shroud. The evaluation was based on vibroacoustic test results obtained from a baseline model composed (1) of a spacecraft with adapter, lower support structure, and shroud; (2) of the spacecraft, adapter, and lower structure, but without the shroud; and (3) of the spacecraft and adapter only. Emphasis was placed on the magnitude of the acoustic input changes required to substitute for the shroud and the difficulty of making such input changes, and the degree of missimulation which can result from the performance of a particular, less-than optimum test. Conclusions are drawn on the advantages and disadvantages derived from the use of input spectra adjustment methods and lower support structure simulations. Test guidelines were also developed for planning and performing a launch acoustic-environmental test.
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Abel, Francois [Rueschlikon, CH; Iliadis, Ilias [Rueschlikon, CH; Minkenberg, Cyriel J. A. [Adliswil, CH
2009-02-03
A method for allocating pending requests for data packet transmission at a number of inputs to a number of outputs of a switching system in successive time slots, including a matching method including the steps of providing a first request information in a first time slot indicating data packets at the inputs requesting transmission to the outputs of the switching system, performing a first step in the first time slot depending on the first request information to obtain a first matching information, providing a last request information in a last time slot successive to the first time slot, performing a last step in the last time slot depending on the last request information and depending on the first matching information to obtain a final matching information, and assigning the pending data packets at the number of inputs to the number of outputs based on the final matching information.
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Inference of segmented color and texture description by tensor voting.
Jia, Jiaya; Tang, Chi-Keung
2004-06-01
A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach.
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NASA Astrophysics Data System (ADS)
Yang, Jia Sheng
2018-06-01
In this paper, we investigate a H∞ memory controller with input limitation minimization (HMCIM) for offshore jacket platforms stabilization. The main objective of this study is to reduce the control consumption as well as protect the actuator when satisfying the requirement of the system performance. First, we introduce a dynamic model of offshore platform with low order main modes based on mode reduction method in numerical analysis. Then, based on H∞ control theory and matrix inequality techniques, we develop a novel H∞ memory controller with input limitation. Furthermore, a non-convex optimization model to minimize input energy consumption is proposed. Since it is difficult to solve this non-convex optimization model by optimization algorithm, we use a relaxation method with matrix operations to transform this non-convex optimization model to be a convex optimization model. Thus, it could be solved by a standard convex optimization solver in MATLAB or CPLEX. Finally, several numerical examples are given to validate the proposed models and methods.
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Real Time Calibration Method for Signal Conditioning Amplifiers
NASA Technical Reports Server (NTRS)
Medelius, Pedro J. (Inventor); Mata, Carlos T. (Inventor); Eckhoff, Anthony (Inventor); Perotti, Jose (Inventor); Lucena, Angel (Inventor)
2004-01-01
A signal conditioning amplifier receives an input signal from an input such as a transducer. The signal is amplified and processed through an analog to digital converter and sent to a processor. The processor estimates the input signal provided by the transducer to the amplifier via a multiplexer. The estimated input signal is provided as a calibration voltage to the amplifier immediately following the receipt of the amplified input signal. The calibration voltage is amplified by the amplifier and provided to the processor as an amplified calibration voltage. The amplified calibration voltage is compared to the amplified input signal, and if a significant error exists, the gain and/or offset of the amplifier may be adjusted as necessary.
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Dynamic modal estimation using instrumental variables
NASA Technical Reports Server (NTRS)
Salzwedel, H.
1980-01-01
A method to determine the modes of dynamical systems is described. The inputs and outputs of a system are Fourier transformed and averaged to reduce the error level. An instrumental variable method that estimates modal parameters from multiple correlations between responses of single input, multiple output systems is applied to estimate aircraft, spacecraft, and off-shore platform modal parameters.
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A throughfall collection method using mixed bed ion exchange resin columns
Mark E. Fenn; Mark A. Poth; Michael J. Arbaugh
2002-01-01
Measurement of ionic deposition in throughfall is a widely used method for measuring deposition inputs to the forest floor. Many studies have been published, providing a large database of throughfall deposition inputs to forests. However, throughfall collection and analysis is labor intensive and expensive because of the large number of replicate collectors needed and...
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Tuning fuzzy PD and PI controllers using reinforcement learning.
Boubertakh, Hamid; Tadjine, Mohamed; Glorennec, Pierre-Yves; Labiod, Salim
2010-10-01
In this paper, we propose a new auto-tuning fuzzy PD and PI controllers using reinforcement Q-learning (QL) algorithm for SISO (single-input single-output) and TITO (two-input two-output) systems. We first, investigate the design parameters and settings of a typical class of Fuzzy PD (FPD) and Fuzzy PI (FPI) controllers: zero-order Takagi-Sugeno controllers with equidistant triangular membership functions for inputs, equidistant singleton membership functions for output, Larsen's implication method, and average sum defuzzification method. Secondly, the analytical structures of these typical fuzzy PD and PI controllers are compared to their classical counterpart PD and PI controllers. Finally, the effectiveness of the proposed method is proven through simulation examples. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
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Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input.
Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Lin, Chong
2017-09-01
In this paper, command filtering-based fuzzy control is designed for uncertain multi-input multioutput (MIMO) nonlinear systems with saturation nonlinearity input. First, the command filtering method is employed to deal with the explosion of complexity caused by the derivative of virtual controllers. Then, fuzzy logic systems are utilized to approximate the nonlinear functions of MIMO systems. Furthermore, error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. The developed method will guarantee all signals of the systems are bounded. The effectiveness and advantages of the theoretic result are obtained by a simulation example.
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Design of vaccination and fumigation on Host-Vector Model by input-output linearization method
NASA Astrophysics Data System (ADS)
Nugraha, Edwin Setiawan; Naiborhu, Janson; Nuraini, Nuning
2017-03-01
Here, we analyze the Host-Vector Model and proposed design of vaccination and fumigation to control infectious population by using feedback control especially input-output liniearization method. Host population is divided into three compartments: susceptible, infectious and recovery. Whereas the vector population is divided into two compartment such as susceptible and infectious. In this system, vaccination and fumigation treat as input factors and infectious population as output result. The objective of design is to stabilize of the output asymptotically tend to zero. We also present the examples to illustrate the design model.
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Method of Characteristic (MOC) Nozzle Flowfield Solver - User’s Guide and Input Manual Version 2.0
2018-01-01
TECHNICAL REPORT RDMR-SS-17-13 METHOD OF CHARACTERISTIC (MOC) NOZZLE FLOWFIELD SOLVER—USER’S GUIDE AND INPUT MANUAL VERSION 2.0 Kevin D. Kennedy...System Simulation and Development Directorate Aviation and Missile Research , Development, and Engineering Center January 2018 Distribution Statement...DOCUMENTS, DESTROY BY ANY METHOD THAT WILL PREVENT DISCLOSURE OF CONTENTS OR RECONSTRUCTION OF THE DOCUMENT. DISCLAIMER THE FINDINGS IN THIS REPORT
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ERIC Educational Resources Information Center
Hadley, Pamela A.; Rispoli, Matthew; Holt, Janet K.
2017-01-01
Purpose: This follow-up study examined whether a parent intervention that increased the diversity of lexical noun phrase subjects in parent input and accelerated children's sentence diversity (Hadley et al., 2017) had indirect benefits on tense/agreement (T/A) morphemes in parent input and children's spontaneous speech. Method: Differences in…
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Scientific and technical advisory committee review of the nutrient inputs to the watershed model
USDA-ARS?s Scientific Manuscript database
The following is a report by a STAC Review Team concerning the methods and documentation used by the Chesapeake Bay Partnership for evaluation of nutrient inputs to Phase 6 of the Chesapeake Bay Watershed Model. The “STAC Review of the Nutrient Inputs to the Watershed Model” (previously referred to...
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[Application of numerical convolution in in vivo/in vitro correlation research].
Yue, Peng
2009-01-01
This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.
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Hess, J A; Mootz, R D
1999-06-01
Resource-based relative value scales (RBRVS) have become a standard method for identifying costs and determining reimbursement for physician services. Development of RBRVS systems and methods are reviewed, and the RBRVS concept of physician "work" is defined. Results of work and time inputs from chiropractic physicians are compared with those reported by osteopathic and medical specialties. Last, implications for reimbursement of chiropractic fee services are discussed. Total work, intraservice work, and time inputs for clinical vignettes reported by chiropractic, osteopathic, and medical physicians are compared. Data for chiropractic work and time reports were drawn from a national random sample of chiropractors conducted as part of a 1997 workers' compensation chiropractic fee schedule development project. Medical and osteopathic inputs were drawn from RBRVS research conducted at Harvard University under a federal contract reported in 1990. Both data sets used the same or similar clinical vignettes and similar methods. Comparisons of work and time inputs are made for clinical vignettes to assess whether work reported by chiropractors is of similar magnitude and variability as work reported by other specialties. Chiropractic inputs for vignettes related to evaluation and management services are similar to those reported by medical specialists and osteopathic physicians. The range of variation between chiropractic work input and other specialties is of similar magnitude to that within other specialties. Chiropractors report greater work input for radiologic interpretation and lower work input for manipulation services. Chiropractors seem to perform similar total "work" for evaluation and management services as other specialties. No basis exists for excluding chiropractors from using evaluation and management codes for reimbursement purposes on grounds of dissimilar physician time or work estimates. Greater work input by chiropractors in radiology interpretation may be related to a greater importance placed on findings in care planning. Consistently higher reports for osteopathic work input on manipulation are likely attributable to differences in reference vignettes used in the respective populations. Research with a common reference vignette used for manipulation providers is recommended, as is development of a single generic approach to coding for manipulation services.
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DAKOTA JAGUAR 3.0 user's manual.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Adams, Brian M.; Bauman, Lara E; Chan, Ethan
2013-05-01
JAGUAR (JAva GUi for Applied Research) is a Java software tool providing an advanced text editor and graphical user interface (GUI) to manipulate DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) input specifications. This document focuses on the features necessary to use JAGUAR.
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Reading Machines for Blind People.
ERIC Educational Resources Information Center
Fender, Derek H.
1983-01-01
Ten stages of developing reading machines for blind people are analyzed: handling of text material; optics; electro-optics; pattern recognition; character recognition; storage; speech synthesizers; browsing and place finding; computer indexing; and other sources of input. Cost considerations of the final product are emphasized. (CL)
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Automatic NEPHIS Coding of Descriptive Titles for Permuted Index Generation.
ERIC Educational Resources Information Center
Craven, Timothy C.
1982-01-01
Describes a system for the automatic coding of most descriptive titles which generates Nested Phrase Indexing System (NEPHIS) input strings of sufficient quality for permuted index production. A series of examples and an 11-item reference list accompany the text. (JL)
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chan, Ethan
2011-06-01
JAGUAR (JAva GUi for Applied Research) is a Java software tool providing an advanced text editor and graphical user interface (GUI) to manipulate DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) input specifications. This document focuses on the technical background necessary for a developer to understand JAGUAR.
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The dairy_wa.zip file is a zip file containing an Arc/Info export file and a text document. Note the DISCLAIM.TXT file as these data are not verified. Map extent: statewide. Input Source: Address database obtained from Wa Dept of Agriculture. Data was originally developed und...
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Cascaded Segmentation-Detection Networks for Word-Level Text Spotting.
Qin, Siyang; Manduchi, Roberto
2017-11-01
We introduce an algorithm for word-level text spotting that is able to accurately and reliably determine the bounding regions of individual words of text "in the wild". Our system is formed by the cascade of two convolutional neural networks. The first network is fully convolutional and is in charge of detecting areas containing text. This results in a very reliable but possibly inaccurate segmentation of the input image. The second network (inspired by the popular YOLO architecture) analyzes each segment produced in the first stage, and predicts oriented rectangular regions containing individual words. No post-processing (e.g. text line grouping) is necessary. With execution time of 450 ms for a 1000 × 560 image on a Titan X GPU, our system achieves good performance on the ICDAR 2013, 2015 benchmarks [2], [1].
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Lim, Jun-Seok; Pang, Hee-Suk
2016-01-01
In this paper an [Formula: see text]-regularized recursive total least squares (RTLS) algorithm is considered for the sparse system identification. Although recursive least squares (RLS) has been successfully applied in sparse system identification, the estimation performance in RLS based algorithms becomes worse, when both input and output are contaminated by noise (the error-in-variables problem). We proposed an algorithm to handle the error-in-variables problem. The proposed [Formula: see text]-RTLS algorithm is an RLS like iteration using the [Formula: see text] regularization. The proposed algorithm not only gives excellent performance but also reduces the required complexity through the effective inversion matrix handling. Simulations demonstrate the superiority of the proposed [Formula: see text]-regularized RTLS for the sparse system identification setting.
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A Comprehensive Study of Gridding Methods for GPS Horizontal Velocity Fields
NASA Astrophysics Data System (ADS)
Wu, Yanqiang; Jiang, Zaisen; Liu, Xiaoxia; Wei, Wenxin; Zhu, Shuang; Zhang, Long; Zou, Zhenyu; Xiong, Xiaohui; Wang, Qixin; Du, Jiliang
2017-03-01
Four gridding methods for GPS velocities are compared in terms of their precision, applicability and robustness by analyzing simulated data with uncertainties from 0.0 to ±3.0 mm/a. When the input data are 1° × 1° grid sampled and the uncertainty of the additional error is greater than ±1.0 mm/a, the gridding results show that the least-squares collocation method is highly robust while the robustness of the Kriging method is low. In contrast, the spherical harmonics and the multi-surface function are moderately robust, and the regional singular values for the multi-surface function method and the edge effects for the spherical harmonics method become more significant with increasing uncertainty of the input data. When the input data (with additional errors of ±2.0 mm/a) are decimated by 50% from the 1° × 1° grid data and then erased in three 6° × 12° regions, the gridding results in these three regions indicate that the least-squares collocation and the spherical harmonics methods have good performances, while the multi-surface function and the Kriging methods may lead to singular values. The gridding techniques are also applied to GPS horizontal velocities with an average error of ±0.8 mm/a over the Chinese mainland and the surrounding areas, and the results show that the least-squares collocation method has the best performance, followed by the Kriging and multi-surface function methods. Furthermore, the edge effects of the spherical harmonics method are significantly affected by the sparseness and geometric distribution of the input data. In general, the least-squares collocation method is superior in terms of its robustness, edge effect, error distribution and stability, while the other methods have several positive features.
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The uncertainty of nitrous oxide emissions from grazed grasslands: A New Zealand case study
NASA Astrophysics Data System (ADS)
Kelliher, Francis M.; Henderson, Harold V.; Cox, Neil R.
2017-01-01
Agricultural soils emit nitrous oxide (N2O), a greenhouse gas and the primary source of nitrogen oxides which deplete stratospheric ozone. Agriculture has been estimated to be the largest anthropogenic N2O source. In New Zealand (NZ), pastoral agriculture uses half the land area. To estimate the annual N2O emissions from NZ's agricultural soils, the nitrogen (N) inputs have been determined and multiplied by an emission factor (EF), the mass fraction of N inputs emitted as N2Osbnd N. To estimate the associated uncertainty, we developed an analytical method. For comparison, another estimate was determined by Monte Carlo numerical simulation. For both methods, expert judgement was used to estimate the N input uncertainty. The EF uncertainty was estimated by meta-analysis of the results from 185 NZ field trials. For the analytical method, assuming a normal distribution and independence of the terms used to calculate the emissions (correlation = 0), the estimated 95% confidence limit was ±57%. When there was a normal distribution and an estimated correlation of 0.4 between N input and EF, the latter inferred from experimental data involving six NZ soils, the analytical method estimated a 95% confidence limit of ±61%. The EF data from 185 NZ field trials had a logarithmic normal distribution. For the Monte Carlo method, assuming a logarithmic normal distribution for EF, a normal distribution for the other terms and independence of all terms, the estimated 95% confidence limits were -32% and +88% or ±60% on average. When there were the same distribution assumptions and a correlation of 0.4 between N input and EF, the Monte Carlo method estimated 95% confidence limits were -34% and +94% or ±64% on average. For the analytical and Monte Carlo methods, EF uncertainty accounted for 95% and 83% of the emissions uncertainty when the correlation between N input and EF was 0 and 0.4, respectively. As the first uncertainty analysis of an agricultural soils N2O emissions inventory using "country-specific" field trials to estimate EF uncertainty, this can be a potentially informative case study for the international scientific community.
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Fertilizer usage and cadmium in soils, crops and food.
Dharma-Wardana, M W C
2018-06-23
Phosphate fertilizers were first implicated by Schroeder and Balassa (Science 140(3568):819-820, 1963) for increasing the Cd concentration in cultivated soils and crops. This suggestion has become a part of the accepted paradigm on soil toxicity. Consequently, stringent fertilizer control programs to monitor Cd have been launched. Attempts to link Cd toxicity and fertilizers to chronic diseases, sometimes with good evidence, but mostly on less certain data are frequent. A re-assessment of this "accepted" paradigm is timely, given the larger body of data available today. The data show that both the input and output of Cd per hectare from fertilizers are negligibly small compared to the total amount of Cd/hectare usually present in the soil itself. Calculations based on current agricultural practices are used to show that it will take centuries to double the ambient soil Cd level, even after neglecting leaching and other removal effects. The concern of long-term agriculture should be the depletion of available phosphate fertilizers, rather than the negligible contamination of the soil by trace metals from fertilizer inputs. This conclusion is confirmed by showing that the claimed correlations between fertilizer input and Cd accumulation in crops are not robust. Alternative scenarios that explain the data are presented. Thus, soil acidulation on fertilizer loading and the effect of Mg, Zn and F ions contained in fertilizers are considered using recent [Formula: see text], [Formula: see text] and [Formula: see text] ion-association theories. The protective role of ions like Zn, Se, Fe is emphasized, and the question of Cd toxicity in the presence of other ions is considered. These help to clarify difficulties in the standard point of view. This analysis does not modify the accepted views on Cd contamination by airborne delivery, smoking, and industrial activity, or algal blooms caused by phosphates.
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Developing and Pretesting a Text Messaging Program for Health Behavior Change: Recommended Steps.
Abroms, Lorien C; Whittaker, Robyn; Free, Caroline; Mendel Van Alstyne, Judith; Schindler-Ruwisch, Jennifer M
2015-12-21
A growing body of evidence demonstrates that text messaging-based programs (short message service [SMS]) on mobile phones can help people modify health behaviors. Most of these programs have consisted of automated and sometimes interactive text messages that guide a person through the process of behavior change. This paper provides guidance on how to develop text messaging programs aimed at changing health behaviors. Based on their collective experience in designing, developing, and evaluating text messaging programs and a review of the literature, the authors drafted the guide. One author initially drafted the guide and the others provided input and review. Steps for developing a text messaging program include conducting formative research for insights into the target audience and health behavior, designing the text messaging program, pretesting the text messaging program concept and messages, and revising the text messaging program. The steps outlined in this guide may help in the development of SMS-based behavior change programs.
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Residents' numeric inputting error in computerized physician order entry prescription.
Wu, Xue; Wu, Changxu; Zhang, Kan; Wei, Dong
2016-04-01
Computerized physician order entry (CPOE) system with embedded clinical decision support (CDS) can significantly reduce certain types of prescription error. However, prescription errors still occur. Various factors such as the numeric inputting methods in human computer interaction (HCI) produce different error rates and types, but has received relatively little attention. This study aimed to examine the effects of numeric inputting methods and urgency levels on numeric inputting errors of prescription, as well as categorize the types of errors. Thirty residents participated in four prescribing tasks in which two factors were manipulated: numeric inputting methods (numeric row in the main keyboard vs. numeric keypad) and urgency levels (urgent situation vs. non-urgent situation). Multiple aspects of participants' prescribing behavior were measured in sober prescribing situations. The results revealed that in urgent situations, participants were prone to make mistakes when using the numeric row in the main keyboard. With control of performance in the sober prescribing situation, the effects of the input methods disappeared, and urgency was found to play a significant role in the generalized linear model. Most errors were either omission or substitution types, but the proportion of transposition and intrusion error types were significantly higher than that of the previous research. Among numbers 3, 8, and 9, which were the less common digits used in prescription, the error rate was higher, which was a great risk to patient safety. Urgency played a more important role in CPOE numeric typing error-making than typing skills and typing habits. It was recommended that inputting with the numeric keypad had lower error rates in urgent situation. An alternative design could consider increasing the sensitivity of the keys with lower frequency of occurrence and decimals. To improve the usability of CPOE, numeric keyboard design and error detection could benefit from spatial incidence of errors found in this study. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Heebner, John E [Livermore, CA
2010-08-03
In one general embodiment, a method for ultrafast optical signal detecting is provided. In operation, a first optical input signal is propagated through a first wave guiding layer of a waveguide. Additionally, a second optical input signal is propagated through a second wave guiding layer of the waveguide. Furthermore, an optical control signal is applied to a top of the waveguide, the optical control signal being oriented diagonally relative to the top of the waveguide such that the application is used to influence at least a portion of the first optical input signal propagating through the first wave guiding layer of the waveguide. In addition, the first and the second optical input signals output from the waveguide are combined. Further, the combined optical signals output from the waveguide are detected. In another general embodiment, a system for ultrafast optical signal recording is provided comprising a waveguide including a plurality of wave guiding layers, an optical control source positioned to propagate an optical control signal towards the waveguide in a diagonal orientation relative to a top of the waveguide, at least one optical input source positioned to input an optical input signal into at least a first and a second wave guiding layer of the waveguide, and a detector for detecting at least one interference pattern output from the waveguide, where at least one of the interference patterns results from a combination of the optical input signals input into the first and the second wave guiding layer. Furthermore, propagation of the optical control signal is used to influence at least a portion of the optical input signal propagating through the first wave guiding layer of the waveguide.
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Kennedy, T.A.; Ralston, B.E.
2012-01-01
Dams and associated river regulation have led to the expansion of riparian vegetation, especially nonnative species, along downstream ecosystems. Nonnative saltcedar is one of the dominant riparian plants along virtually every major river system in the arid western United States, but allochthonous inputs have never been quantified along a segment of a large river that is dominated by saltcedar. We developed a novel method for estimating direct allochthonous inputs along the 387km-long reach of the Colorado River downstream of Glen Canyon Dam that utilized a GIS vegetation map developed from aerial photographs, empirical and literature-derived litter production data for the dominant vegetation types, and virtual shorelines of annual peak discharge (566m 3s -1 stage elevation). Using this method, we estimate that direct allochthonous inputs from riparian vegetation for the entire reach studied total 186metric tonsyear -1, which represents mean inputs of 470gAFDMm -1year -1 of shoreline or 5.17gAFDMm -2year -1 of river surface. These values are comparable to allochthonous inputs for other large rivers and systems that also have sparse riparian vegetation. Nonnative saltcedar represents a significant component of annual allochthonous inputs (36% of total direct inputs) in the Colorado River. We also estimated direct allochthonous inputs for 46.8km of the Colorado River prior to closure of Glen Canyon Dam using a vegetation map that was developed from historical photographs. Regulation has led to significant increases in riparian vegetation (270-319% increase in cover, depending on stage elevation), but annual allochthonous inputs appear unaffected by regulation because of the lower flood peaks on the post-dam river. Published in 2010 by John Wiley & Sons, Ltd.
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Löpprich, Martin; Krauss, Felix; Ganzinger, Matthias; Senghas, Karsten; Riezler, Stefan; Knaup, Petra
2016-08-05
In the Multiple Myeloma clinical registry at Heidelberg University Hospital, most data are extracted from discharge letters. Our aim was to analyze if it is possible to make the manual documentation process more efficient by using methods of natural language processing for multiclass classification of free-text diagnostic reports to automatically document the diagnosis and state of disease of myeloma patients. The first objective was to create a corpus consisting of free-text diagnosis paragraphs of patients with multiple myeloma from German diagnostic reports, and its manual annotation of relevant data elements by documentation specialists. The second objective was to construct and evaluate a framework using different NLP methods to enable automatic multiclass classification of relevant data elements from free-text diagnostic reports. The main diagnoses paragraph was extracted from the clinical report of one third randomly selected patients of the multiple myeloma research database from Heidelberg University Hospital (in total 737 selected patients). An EDC system was setup and two data entry specialists performed independently a manual documentation of at least nine specific data elements for multiple myeloma characterization. Both data entries were compared and assessed by a third specialist and an annotated text corpus was created. A framework was constructed, consisting of a self-developed package to split multiple diagnosis sequences into several subsequences, four different preprocessing steps to normalize the input data and two classifiers: a maximum entropy classifier (MEC) and a support vector machine (SVM). In total 15 different pipelines were examined and assessed by a ten-fold cross-validation, reiterated 100 times. For quality indication the average error rate and the average F1-score were conducted. For significance testing the approximate randomization test was used. The created annotated corpus consists of 737 different diagnoses paragraphs with a total number of 865 coded diagnosis. The dataset is publicly available in the supplementary online files for training and testing of further NLP methods. Both classifiers showed low average error rates (MEC: 1.05; SVM: 0.84) and high F1-scores (MEC: 0.89; SVM: 0.92). However the results varied widely depending on the classified data element. Preprocessing methods increased this effect and had significant impact on the classification, both positive and negative. The automatic diagnosis splitter increased the average error rate significantly, even if the F1-score decreased only slightly. The low average error rates and high average F1-scores of each pipeline demonstrate the suitability of the investigated NPL methods. However, it was also shown that there is no best practice for an automatic classification of data elements from free-text diagnostic reports.
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Method for Atypical Opinion Extraction from Ungrammatical Answers in Open-ended Questions
NASA Astrophysics Data System (ADS)
Hiramatsu, Ayako; Tamura, Shingo; Oiso, Hiroaki; Komoda, Norihisa
This paper presents a method for atypical opinion extraction from ungrammatical answers to open-ended questions supplied through cellular phones. The proposed system excludes typical opinions and extracts only atypical opinions. To cope with incomplete syntax of texts due to the input by cellular phones, the system treats the opinions as the sets of keywords. The combinations of words are established beforehand in a typical word database. Based on the ratio of typical word combinations in sentences of an opinion, the system classifies the opinion typical or atypical. When typical word combinations are sought in an opinion, the system considers the word order and the distance of difference between the positions of words to exclude unnecessary combinations. Furthermore, when an opinion includes meanings the system divides the opinion into phrases at each typical word combination. By applying questionnaire data supplied by users of a mobile game content when they cancel their account, the extraction accuracy of the proposed system was confirmed.
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Adamski, Mateusz G; Gumann, Patryk; Baird, Alison E
2014-01-01
Over the past decade rapid advances have occurred in the understanding of RNA expression and its regulation. Quantitative polymerase chain reactions (qPCR) have become the gold standard for quantifying gene expression. Microfluidic next generation, high throughput qPCR now permits the detection of transcript copy number in thousands of reactions simultaneously, dramatically increasing the sensitivity over standard qPCR. Here we present a gene expression analysis method applicable to both standard polymerase chain reactions (qPCR) and high throughput qPCR. This technique is adjusted to the input sample quantity (e.g., the number of cells) and is independent of control gene expression. It is efficiency-corrected and with the use of a universal reference sample (commercial complementary DNA (cDNA)) permits the normalization of results between different batches and between different instruments--regardless of potential differences in transcript amplification efficiency. Modifications of the input quantity method include (1) the achievement of absolute quantification and (2) a non-efficiency corrected analysis. When compared to other commonly used algorithms the input quantity method proved to be valid. This method is of particular value for clinical studies of whole blood and circulating leukocytes where cell counts are readily available.
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Sample selection via angular distance in the space of the arguments of an artificial neural network
NASA Astrophysics Data System (ADS)
Fernández Jaramillo, J. M.; Mayerle, R.
2018-05-01
In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.
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Acoustic Signature from Flames as a Combustion Diagnostic Tool
1983-11-01
empirical visual flame length had to be input to the computer for the inversion method to give good results. That is, if the experiment cnd inversion...method were asked to yield the flame length , poor results were obtained. Since this wa3 part of the information sought for practical application of the...to small experimental uncertainty. The method gave reasonably good results for the open flame but substantial input (the flame length ) had to be
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SimBA: simulation algorithm to fit extant-population distributions.
Parida, Laxmi; Haiminen, Niina
2015-03-14
Simulation of populations with specified characteristics such as allele frequencies, linkage disequilibrium etc., is an integral component of many studies, including in-silico breeding optimization. Since the accuracy and sensitivity of population simulation is critical to the quality of the output of the applications that use them, accurate algorithms are required to provide a strong foundation to the methods in these studies. In this paper we present SimBA (Simulation using Best-fit Algorithm) a non-generative approach, based on a combination of stochastic techniques and discrete methods. We optimize a hill climbing algorithm and extend the framework to include multiple subpopulation structures. Additionally, we show that SimBA is very sensitive to the input specifications, i.e., very similar but distinct input characteristics result in distinct outputs with high fidelity to the specified distributions. This property of the simulation is not explicitly modeled or studied by previous methods. We show that SimBA outperforms the existing population simulation methods, both in terms of accuracy as well as time-efficiency. Not only does it construct populations that meet the input specifications more stringently than other published methods, SimBA is also easy to use. It does not require explicit parameter adaptations or calibrations. Also, it can work with input specified as distributions, without an exemplar matrix or population as required by some methods. SimBA is available at http://researcher.ibm.com/project/5669 .
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Fast metabolite identification with Input Output Kernel Regression.
Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho
2016-06-15
An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. celine.brouard@aalto.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
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Fast metabolite identification with Input Output Kernel Regression
Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho
2016-01-01
Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628
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A Method for Calculating Crossflow Separation Patterns on Submarine Hull/Sail Configurations
1991-03-01
according to the order of input points used in the three-dimensional panel method. Card 07 (15) NCAP Number of points of sail cap along the X direction...input points begin at the leading edge NCAP and end at the trailing edge. Card 09 (215) NXT Number of points along the x-direction for boundary-layer
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Scalable microreactors and methods for using same
Lawal, Adeniyi; Qian, Dongying
2010-03-02
The present invention provides a scalable microreactor comprising a multilayered reaction block having alternating reaction plates and heat exchanger plates that have a plurality of microchannels; a multilaminated reactor input manifold, a collecting reactor output manifold, a heat exchange input manifold and a heat exchange output manifold. The present invention also provides methods of using the microreactor for multiphase chemical reactions.
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Zhang, Meng; Liu, Zhigang; Zhu, Yu; Bu, Mingfan; Hong, Jun
2017-07-01
In this paper, a hybrid control system is developed by integrating the closed-loop force feedback and input shaping method to overcome the problem of the hysteresis and dynamic behavior in piezo-based scanning systems and increase the scanning speed of tunable external cavity diode lasers. The flexible hinge and piezoelectric actuators are analyzed, and a dynamic model of the scanning systems is established. A force sensor and an integral controller are utilized in integral force feedback (IFF) to directly augment the damping of the piezoelectric scanning systems. Hysteresis has been effectively eliminated, but the mechanical resonance is still evident. Noticeable residual vibration occurred after the inflection points and then gradually disappeared. For the further control of mechanical resonance, based on the theory of minimum-acceleration trajectory planning, the time-domain input shaping method was developed. The turning sections of a scanning trajectory are replaced by smooth curves, while the linear sections are retained. The IFF method is combined with the input shaping method to control the non-linearity and mechanical resonance in high-speed piezo-based scanning systems. Experiments are conducted, and the results demonstrate the effectiveness of the proposed control approach.
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NASA Astrophysics Data System (ADS)
Zhang, Meng; Liu, Zhigang; Zhu, Yu; Bu, Mingfan; Hong, Jun
2017-07-01
In this paper, a hybrid control system is developed by integrating the closed-loop force feedback and input shaping method to overcome the problem of the hysteresis and dynamic behavior in piezo-based scanning systems and increase the scanning speed of tunable external cavity diode lasers. The flexible hinge and piezoelectric actuators are analyzed, and a dynamic model of the scanning systems is established. A force sensor and an integral controller are utilized in integral force feedback (IFF) to directly augment the damping of the piezoelectric scanning systems. Hysteresis has been effectively eliminated, but the mechanical resonance is still evident. Noticeable residual vibration occurred after the inflection points and then gradually disappeared. For the further control of mechanical resonance, based on the theory of minimum-acceleration trajectory planning, the time-domain input shaping method was developed. The turning sections of a scanning trajectory are replaced by smooth curves, while the linear sections are retained. The IFF method is combined with the input shaping method to control the non-linearity and mechanical resonance in high-speed piezo-based scanning systems. Experiments are conducted, and the results demonstrate the effectiveness of the proposed control approach.
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ERIC Educational Resources Information Center
Chen, Jingjun; Luo, Rong; Liu, Huashan
2017-01-01
With the development of ICT, digital writing is becoming much more common in people's life. Differently from keyboarding alphabets directly to input English words, keyboarding Chinese character is always through typing phonetic alphabets and then identify the glyph provided by Pinyin input-method software while in this process which do not need…
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40 CFR 60.44c - Compliance and performance test methods and procedures for sulfur dioxide.
Code of Federal Regulations, 2010 CFR
2010-07-01
... = Fraction of the total heat input from fuel combustion derived from coal and oil, as determined by... total heat input from fuel combustion derived from coal and oil, as determined by applicable procedures... generating unit load during the 30-day period does not have to be the maximum design heat input capacity, but...
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Generating Concise Natural Language Summaries.
ERIC Educational Resources Information Center
McKeown, Kathleen; And Others
1995-01-01
Presents an approach to summarization that combines information from multiple facts into a single sentence using linguistic constructions. Describes two applications: one produces summaries of basketball games, and the other contains summaries of telephone network planning activity. Both summarize input data as opposed to full text. Discusses…
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OCR Scanners Facilitate WP Training in Business Schools and Colleges.
ERIC Educational Resources Information Center
School Business Affairs, 1983
1983-01-01
Optical Character Recognition Scanners (OCR) scan typed text and feed it directly into word processing systems, saving input time. OCRs are valuable in word processing training programs because they allow more students access to classes and more time for skill training. (MD)
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A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.
Yu, Jun; Wang, Zeng-Fu
2015-05-01
A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.
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How Much Comprehensible Input Did Heinrich Schliemann Get?
ERIC Educational Resources Information Center
Krashen, Stephen D.
1991-01-01
Examines Heinrich Schliemann's method of acquiring a second language primarily by means of conscious learning. It is revealed that Schliemann probably obtained a great deal of comprehensible input in English. (nine references) (GLR)
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Embedding global and collective in a torus network with message class map based tree path selection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Dong; Coteus, Paul W.; Eisley, Noel A.
Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computermore » program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.« less
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Sensitivity analysis and nonlinearity assessment of steam cracking furnace process
NASA Astrophysics Data System (ADS)
Rosli, M. N.; Sudibyo, Aziz, N.
2017-11-01
In this paper, sensitivity analysis and nonlinearity assessment of cracking furnace process are presented. For the sensitivity analysis, the fractional factorial design method is employed as a method to analyze the effect of input parameters, which consist of four manipulated variables and two disturbance variables, to the output variables and to identify the interaction between each parameter. The result of the factorial design method is used as a screening method to reduce the number of parameters, and subsequently, reducing the complexity of the model. It shows that out of six input parameters, four parameters are significant. After the screening is completed, step test is performed on the significant input parameters to assess the degree of nonlinearity of the system. The result shows that the system is highly nonlinear with respect to changes in an air-to-fuel ratio (AFR) and feed composition.
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Stewart, Tanya Charyk; Harrington, Jane; Batey, Brandon; Merritt, Neil H; Parry, Neil G
2015-09-01
The Impact program is an adolescent, injury prevention program with both school- and hospital-based components aimed at decreasing high-risk behaviors and preventing injury. The objective of this study was to obtain student input on the school-based component of Impact, as part of the program evaluation and redesign process, to ensure that the program content and format were optimal and relevant, addressing injury-related issues important for youth in our region. Secondary schools were selected in various geographic regions with students varying in language, religion, and socioeconomic status. A mixed-methods questionnaire was developed and pretested on program content, format, relevance, quality, and effectiveness. Attitude and opinion questions on issues facing teens today were ranked on a 7-point Likert scale. Open-ended, qualitative questions were included in the focus groups, with responses themed. There were 167 respondents in the nine geographically, socioeconomically, and culturally diverse focus groups with a mean age of 16 years, 52% were male, and 69% were in Grade 11. Ninety-three percent of respondents rated the content of Impact as comprehensive (median, 6 of 7, with 7 being very comprehensive), and 29% rated the format a 5 of 7. Impact was rated relevant (89%), addressing issues for teens (median, 6 of 7). Issues suggested to highlight included texting and driving, drugs, partying, self-harm, and abusive relationships. Texting while driving was perceived as a significantly more common (81%) injury issue for adolescents compared with other driving risk factors (p < 0.001), with one student commenting, "If you don't (text and drive), you either don't have a phone or don't have a driver's license." Injury prevention programs must be continually evaluated to ensure they are relevant, addressing issues important for youth, and presented in a format that resonates with the audience. Student focus groups identified motor vehicle collisions and texting as important issues as well as a desire for teens to hear personal stories with a visual element. This provided the information needed to develop the next logical direction for our program, the production of a distracted driving video ("Distracted Driving: Josh's Story," http://youtu.be/BFPke9gBybc) to be incorporated into school presentations. Epidemiologic/prognostic study, level III.
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NASA Astrophysics Data System (ADS)
Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo
2017-03-01
The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.
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Deep Recurrent Neural Networks for Human Activity Recognition
Murad, Abdulmajid
2017-01-01
Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103
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Deep Recurrent Neural Networks for Human Activity Recognition.
Murad, Abdulmajid; Pyun, Jae-Young
2017-11-06
Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.
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Thakkar, Jay; Barry, Tony; Thiagalingam, Aravinda; Redfern, Julie; McEwan, Alistair L; Rodgers, Anthony
2016-01-01
Background Mobile health (mHealth) has huge potential to deliver preventative health services. However, there is paucity of literature on theoretical constructs, technical, practical, and regulatory considerations that enable delivery of such services. Objectives The objective of this study was to outline the key considerations in the development of a text message-based mHealth program; thus providing broad recommendations and guidance to future researchers designing similar programs. Methods We describe the key considerations in designing the intervention with respect to functionality, technical infrastructure, data management, software components, regulatory requirements, and operationalization. We also illustrate some of the potential issues and decision points utilizing our experience of developing text message (short message service, SMS) management systems to support 2 large randomized controlled trials: TEXT messages to improve MEDication adherence & Secondary prevention (TEXTMEDS) and Tobacco, EXercise and dieT MEssages (TEXT ME). Results The steps identified in the development process were: (1) background research and development of the text message bank based on scientific evidence and disease-specific guidelines, (2) pilot testing with target audience and incorporating feedback, (3) software-hardware customization to enable delivery of complex personalized programs using prespecified algorithms, and (4) legal and regulatory considerations. Additional considerations in developing text message management systems include: balancing the use of customized versus preexisting software systems, the level of automation versus need for human inputs, monitoring, ensuring data security, interface flexibility, and the ability for upscaling. Conclusions A merging of expertise in clinical and behavioral sciences, health and research data management systems, software engineering, and mobile phone regulatory requirements is essential to develop a platform to deliver and manage support programs to hundreds of participants simultaneously as in TEXT ME and TEXTMEDS trials. This research provides broad principles that may assist other researchers in developing mHealth programs. PMID:27847350
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Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis
2017-03-01
A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.
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Exploratory analysis regarding the domain definitions for computer based analytical models
NASA Astrophysics Data System (ADS)
Raicu, A.; Oanta, E.; Barhalescu, M.
2017-08-01
Our previous computer based studies dedicated to structural problems using analytical methods defined the composite cross section of a beam as a result of Boolean operations with so-called ‘simple’ shapes. Using generalisations, in the class of the ‘simple’ shapes were included areas bounded by curves approximated using spline functions and areas approximated as polygons. However, particular definitions lead to particular solutions. In order to ascend above the actual limitations, we conceived a general definition of the cross sections that are considered now calculus domains consisting of several subdomains. The according set of input data use complex parameterizations. This new vision allows us to naturally assign a general number of attributes to the subdomains. In this way there may be modelled new phenomena that use map-wise information, such as the metal alloys equilibrium diagrams. The hierarchy of the input data text files that use the comma-separated-value format and their structure are also presented and discussed in the paper. This new approach allows us to reuse the concepts and part of the data processing software instruments already developed. The according software to be subsequently developed will be modularised and generalised in order to be used in the upcoming projects that require rapid development of computer based models.
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Improving ECG Classification Accuracy Using an Ensemble of Neural Network Modules
Javadi, Mehrdad; Ebrahimpour, Reza; Sajedin, Atena; Faridi, Soheil; Zakernejad, Shokoufeh
2011-01-01
This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization. PMID:22046232
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NASA Astrophysics Data System (ADS)
Pioldi, Fabio; Rizzi, Egidio
2016-08-01
This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.
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NASA Astrophysics Data System (ADS)
Kudomi, Nobuyuki; Watabe, Hiroshi; Hayashi, Takuya; Iida, Hidehiro
2007-04-01
Cerebral metabolic rate of oxygen (CMRO2), oxygen extraction fraction (OEF) and cerebral blood flow (CBF) images can be quantified using positron emission tomography (PET) by administrating 15O-labelled water (H152O) and oxygen (15O2). Conventionally, those images are measured with separate scans for three tracers C15O for CBV, H152O for CBF and 15O2 for CMRO2, and there are additional waiting times between the scans in order to minimize the influence of the radioactivity from the previous tracers, which results in a relatively long study period. We have proposed a dual tracer autoradiographic (DARG) approach (Kudomi et al 2005), which enabled us to measure CBF, OEF and CMRO2 rapidly by sequentially administrating H152O and 15O2 within a short time. Because quantitative CBF and CMRO2 values are sensitive to arterial input function, it is necessary to obtain accurate input function and a drawback of this approach is to require separation of the measured arterial blood time-activity curve (TAC) into pure water and oxygen input functions under the existence of residual radioactivity from the first injected tracer. For this separation, frequent manual sampling was required. The present paper describes two calculation methods: namely a linear and a model-based method, to separate the measured arterial TAC into its water and oxygen components. In order to validate these methods, we first generated a blood TAC for the DARG approach by combining the water and oxygen input functions obtained in a series of PET studies on normal human subjects. The combined data were then separated into water and oxygen components by the present methods. CBF and CMRO2 were calculated using those separated input functions and tissue TAC. The quantitative accuracy in the CBF and CMRO2 values by the DARG approach did not exceed the acceptable range, i.e., errors in those values were within 5%, when the area under the curve in the input function of the second tracer was larger than half of the first one. Bias and deviation in those values were also compatible to that of the conventional method, when noise was imposed on the arterial TAC. We concluded that the present calculation based methods could be of use for quantitatively calculating CBF and CMRO2 with the DARG approach.
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Viral-genetic tracing of the input-output organization of a central noradrenaline circuit.
Schwarz, Lindsay A; Miyamichi, Kazunari; Gao, Xiaojing J; Beier, Kevin T; Weissbourd, Brandon; DeLoach, Katherine E; Ren, Jing; Ibanes, Sandy; Malenka, Robert C; Kremer, Eric J; Luo, Liqun
2015-08-06
Deciphering how neural circuits are anatomically organized with regard to input and output is instrumental in understanding how the brain processes information. For example, locus coeruleus noradrenaline (also known as norepinephrine) (LC-NE) neurons receive input from and send output to broad regions of the brain and spinal cord, and regulate diverse functions including arousal, attention, mood and sensory gating. However, it is unclear how LC-NE neurons divide up their brain-wide projection patterns and whether different LC-NE neurons receive differential input. Here we developed a set of viral-genetic tools to quantitatively analyse the input-output relationship of neural circuits, and applied these tools to dissect the LC-NE circuit in mice. Rabies-virus-based input mapping indicated that LC-NE neurons receive convergent synaptic input from many regions previously identified as sending axons to the locus coeruleus, as well as from newly identified presynaptic partners, including cerebellar Purkinje cells. The 'tracing the relationship between input and output' method (or TRIO method) enables trans-synaptic input tracing from specific subsets of neurons based on their projection and cell type. We found that LC-NE neurons projecting to diverse output regions receive mostly similar input. Projection-based viral labelling revealed that LC-NE neurons projecting to one output region also project to all brain regions we examined. Thus, the LC-NE circuit overall integrates information from, and broadcasts to, many brain regions, consistent with its primary role in regulating brain states. At the same time, we uncovered several levels of specificity in certain LC-NE sub-circuits. These tools for mapping output architecture and input-output relationship are applicable to other neuronal circuits and organisms. More broadly, our viral-genetic approaches provide an efficient intersectional means to target neuronal populations based on cell type and projection pattern.
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Community Coauthoring: Whose Voice Remains?
ERIC Educational Resources Information Center
Larson, Joanne; Webster, Stephanie; Hopper, Mindy
2011-01-01
This article examines how texts are collaboratively produced in community development work when coauthors come from multiple racial, ethnic, and class backgrounds as well as business and other work experiences. We found that the term "wordsmithing" became a discursive tool that limited resident input and shaped the Plan toward an…
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The Case for Open Source Software: The Interactional Discourse Lab
ERIC Educational Resources Information Center
Choi, Seongsook
2016-01-01
Computational techniques and software applications for the quantitative content analysis of texts are now well established, and many qualitative data software applications enable the manipulation of input variables and the visualization of complex relations between them via interactive and informative graphical interfaces. Although advances in…
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Description of the IV + V System Software Package.
ERIC Educational Resources Information Center
Microcomputers for Information Management: An International Journal for Library and Information Services, 1984
1984-01-01
Describes the IV + V System, a software package designed by the Institut fur Maschinelle Dokumentation for the United Nations General Information Programme and UNISIST to support automation of local information and documentation services. Principle program features and functions outlined include input/output, databank, text image, output, and…
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Bastian, Nathaniel D; Ekin, Tahir; Kang, Hyojung; Griffin, Paul M; Fulton, Lawrence V; Grannan, Benjamin C
2017-06-01
The management of hospitals within fixed-input health systems such as the U.S. Military Health System (MHS) can be challenging due to the large number of hospitals, as well as the uncertainty in input resources and achievable outputs. This paper introduces a stochastic multi-objective auto-optimization model (SMAOM) for resource allocation decision-making in fixed-input health systems. The model can automatically identify where to re-allocate system input resources at the hospital level in order to optimize overall system performance, while considering uncertainty in the model parameters. The model is applied to 128 hospitals in the three services (Air Force, Army, and Navy) in the MHS using hospital-level data from 2009 - 2013. The results are compared to the traditional input-oriented variable returns-to-scale Data Envelopment Analysis (DEA) model. The application of SMAOM to the MHS increases the expected system-wide technical efficiency by 18 % over the DEA model while also accounting for uncertainty of health system inputs and outputs. The developed method is useful for decision-makers in the Defense Health Agency (DHA), who have a strategic level objective of integrating clinical and business processes through better sharing of resources across the MHS and through system-wide standardization across the services. It is also less sensitive to data outliers or sampling errors than traditional DEA methods.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption—for heating, cooling, ventilation, lighting and plug and process loads—and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results ofmore » two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio® software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.« less
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Input Files and Procedures for Analysis of SMA Hybrid Composite Beams in MSC.Nastran and ABAQUS
NASA Technical Reports Server (NTRS)
Turner, Travis L.; Patel, Hemant D.
2005-01-01
A thermoelastic constitutive model for shape memory alloys (SMAs) and SMA hybrid composites (SMAHCs) was recently implemented in the commercial codes MSC.Nastran and ABAQUS. The model is implemented and supported within the core of the commercial codes, so no user subroutines or external calculations are necessary. The model and resulting structural analysis has been previously demonstrated and experimentally verified for thermoelastic, vibration and acoustic, and structural shape control applications. The commercial implementations are described in related documents cited in the references, where various results are also shown that validate the commercial implementations relative to a research code. This paper is a companion to those documents in that it provides additional detail on the actual input files and solution procedures and serves as a repository for ASCII text versions of the input files necessary for duplication of the available results.
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Role of Linguistic Input in Third Person Singular -"s" Use in the Speech of Young Children
ERIC Educational Resources Information Center
Finneran, Denise A.; Leonard, Laurence B.
2010-01-01
Purpose: To examine the role of linguistic input in how young, typically developing children use the 3rd person singular -"s" (3S) inflection. Method: Novel verbs were presented to 16 young children in either 3S contexts (e.g., "The tiger heens") or nonfinite (NF) contexts (e.g., "Will the tiger heen?"). The input was further manipulated for…
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Method and Apparatus for Improving the Resolution of Digitally Sampled Analog Data
NASA Technical Reports Server (NTRS)
Liaghati, Amir L. (Inventor)
2017-01-01
A system and method is described for converting an analog signal into a digital signal. The gain and offset of an ADC is dynamically adjusted so that the N-bits of input data are assigned to a narrower channel instead of the entire input range of the ADC. This provides greater resolution in the range of interest without generating longer digital data strings.
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A Step-Wise Approach to Elicit Triangular Distributions
NASA Technical Reports Server (NTRS)
Greenberg, Marc W.
2013-01-01
Adapt/combine known methods to demonstrate an expert judgment elicitation process that: 1.Models expert's inputs as a triangular distribution, 2.Incorporates techniques to account for expert bias and 3.Is structured in a way to help justify expert's inputs. This paper will show one way of "extracting" expert opinion for estimating purposes. Nevertheless, as with most subjective methods, there are many ways to do this.
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Multiple Input Design for Real-Time Parameter Estimation in the Frequency Domain
NASA Technical Reports Server (NTRS)
Morelli, Eugene
2003-01-01
A method for designing multiple inputs for real-time dynamic system identification in the frequency domain was developed and demonstrated. The designed inputs are mutually orthogonal in both the time and frequency domains, with reduced peak factors to provide good information content for relatively small amplitude excursions. The inputs are designed for selected frequency ranges, and therefore do not require a priori models. The experiment design approach was applied to identify linear dynamic models for the F-15 ACTIVE aircraft, which has multiple control effectors.
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Device and method to enhance availability of cluster-based processing systems
NASA Technical Reports Server (NTRS)
Lupia, David J. (Inventor); Ramos, Jeremy (Inventor); Samson, Jr., John R. (Inventor)
2010-01-01
An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.
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Correction of I/Q channel errors without calibration
Doerry, Armin W.; Tise, Bertice L.
2002-01-01
A method of providing a balanced demodular output for a signal such as a Doppler radar having an analog pulsed input; includes adding a variable phase shift as a function of time to the input signal, applying the phase shifted input signal to a demodulator; and generating a baseband signal from the input signal. The baseband signal is low-pass filtered and converted to a digital output signal. By removing the variable phase shift from the digital output signal, a complex data output is formed that is representative of the output of a balanced demodulator.
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Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor
NASA Technical Reports Server (NTRS)
Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell
2011-01-01
Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.
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NASA Astrophysics Data System (ADS)
Arsenault, Louis-François; Neuberg, Richard; Hannah, Lauren A.; Millis, Andrew J.
2017-11-01
We present a supervised machine learning approach to the inversion of Fredholm integrals of the first kind as they arise, for example, in the analytic continuation problem of quantum many-body physics. The approach provides a natural regularization for the ill-conditioned inverse of the Fredholm kernel, as well as an efficient and stable treatment of constraints. The key observation is that the stability of the forward problem permits the construction of a large database of outputs for physically meaningful inputs. Applying machine learning to this database generates a regression function of controlled complexity, which returns approximate solutions for previously unseen inputs; the approximate solutions are then projected onto the subspace of functions satisfying relevant constraints. Under standard error metrics the method performs as well or better than the Maximum Entropy method for low input noise and is substantially more robust to increased input noise. We suggest that the methodology will be similarly effective for other problems involving a formally ill-conditioned inversion of an integral operator, provided that the forward problem can be efficiently solved.
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Model predictive controller design for boost DC-DC converter using T-S fuzzy cost function
NASA Astrophysics Data System (ADS)
Seo, Sang-Wha; Kim, Yong; Choi, Han Ho
2017-11-01
This paper proposes a Takagi-Sugeno (T-S) fuzzy method to select cost function weights of finite control set model predictive DC-DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T-S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T-S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.
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T-load microchannel array and fabrication method
Swierkowski, Stefan P.
2000-01-01
A three-dimensional (3-D) T-load for planar microchannel arrays for electrophoresis, for example, which enables sample injection directly onto a plane perpendicular to the microchannels' axis, at their ends. This is accomplished by forming input wells that extend beyond the ends of the microchannel thereby eliminating the right angle connection from the input well into the end of the microchannel. In addition, the T-load input well eases the placement of electrode in or adjacent the well and thus enables very efficient reproducible electrokinetic (ek) injection. The T-load input well eliminates the prior input well/microchannel alignment concerns, since the input well can be drilled after the top and bottom microchannel plates are bonded together. The T-load input well may extend partially or entirely through the bottom microchannel plate which enables more efficient gel and solution flushing, and also enables placement of multiple electrodes to assist in the ek sample injection.
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Implementation and Validation of an Impedance Eduction Technique
NASA Technical Reports Server (NTRS)
Watson, Willie R.; Jones, Michael G.; Gerhold, Carl H.
2011-01-01
Implementation of a pressure gradient method of impedance eduction in two NASA Langley flow ducts is described. The Grazing Flow Impedance Tube only supports plane-wave sources, while the Curved Duct Test Rig supports sources that contain higher-order modes. Multiple exercises are used to validate this new impedance eduction method. First, synthesized data for a hard wall insert and a conventional liner mounted in the Grazing Flow Impedance Tube are used as input to the two impedance eduction methods, the pressure gradient method and a previously validated wall pressure method. Comparisons between the two results are excellent. Next, data measured in the Grazing Flow Impedance Tube are used as input to both methods. Results from the two methods compare quite favorably for sufficiently low Mach numbers but this comparison degrades at Mach 0.5, especially when the hard wall insert is used. Finally, data measured with a hard wall insert mounted in the Curved Duct Test Rig are used as input to the pressure gradient method. Significant deviation from the known solution is observed, which is believed to be largely due to 3-D effects in this flow duct. Potential solutions to this issue are currently being explored.
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Horsager, Jacob; Munk, Ole Lajord; Sørensen, Michael
2015-01-01
Metabolic liver function can be measured by dynamic PET/CT with the radio-labelled galactose-analogue 2-[(18)F]fluoro-2-deoxy-D-galactose ((18)F-FDGal) in terms of hepatic systemic clearance of (18)F-FDGal (K, ml blood/ml liver tissue/min). The method requires arterial blood sampling from a radial artery (arterial input function), and the aim of this study was to develop a method for extracting an image-derived, non-invasive input function from a volume of interest (VOI). Dynamic (18)F-FDGal PET/CT data from 16 subjects without liver disease (healthy subjects) and 16 patients with liver cirrhosis were included in the study. Five different input VOIs were tested: four in the abdominal aorta and one in the left ventricle of the heart. Arterial input function from manual blood sampling was available for all subjects. K*-values were calculated using time-activity curves (TACs) from each VOI as input and compared to the K-value calculated using arterial blood samples as input. Each input VOI was tested on PET data reconstructed with and without resolution modelling. All five image-derived input VOIs yielded K*-values that correlated significantly with K calculated using arterial blood samples. Furthermore, TACs from two different VOIs yielded K*-values that did not statistically deviate from K calculated using arterial blood samples. A semicircle drawn in the posterior part of the abdominal aorta was the only VOI that was successful for both healthy subjects and patients as well as for PET data reconstructed with and without resolution modelling. Metabolic liver function using (18)F-FDGal PET/CT can be measured without arterial blood samples by using input data from a semicircle VOI drawn in the posterior part of the abdominal aorta.
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NASA Technical Reports Server (NTRS)
Tumer, Kagan; Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)
2001-01-01
Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.
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Approach for Input Uncertainty Propagation and Robust Design in CFD Using Sensitivity Derivatives
NASA Technical Reports Server (NTRS)
Putko, Michele M.; Taylor, Arthur C., III; Newman, Perry A.; Green, Lawrence L.
2002-01-01
An implementation of the approximate statistical moment method for uncertainty propagation and robust optimization for quasi 3-D Euler CFD code is presented. Given uncertainties in statistically independent, random, normally distributed input variables, first- and second-order statistical moment procedures are performed to approximate the uncertainty in the CFD output. Efficient calculation of both first- and second-order sensitivity derivatives is required. In order to assess the validity of the approximations, these moments are compared with statistical moments generated through Monte Carlo simulations. The uncertainties in the CFD input variables are also incorporated into a robust optimization procedure. For this optimization, statistical moments involving first-order sensitivity derivatives appear in the objective function and system constraints. Second-order sensitivity derivatives are used in a gradient-based search to successfully execute a robust optimization. The approximate methods used throughout the analyses are found to be valid when considering robustness about input parameter mean values.
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Methods for freshwater riverine input into regional ocean models
NASA Astrophysics Data System (ADS)
Herzfeld, M.
2015-06-01
The input of freshwater at the coast in regional models is a non-trivial exercise that has been studied extensively in the past. Several issues are of relevance; firstly, estuaries process water properties along their length, so that while freshwater may enter at the estuary head, it is no longer fresh at the mouth. Secondly, models create a numerical response that results in excessive upstream or offshore transport compared to what is typically observed. The cause of this has been traced to the lack of landward flow at the coast where freshwater is input. In this study we assess the performance of various methods of freshwater input in coarse resolution regional models where the estuary cannot be explicitly resolved, and present a formulation that attempts to account for upstream flow in the salt wedge and in-estuary mixing that elevates salinity at the mouth.
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NASA Technical Reports Server (NTRS)
Generazio, Edward R. (Inventor)
2012-01-01
A method of validating a probability of detection (POD) testing system using directed design of experiments (DOE) includes recording an input data set of observed hit and miss or analog data for sample components as a function of size of a flaw in the components. The method also includes processing the input data set to generate an output data set having an optimal class width, assigning a case number to the output data set, and generating validation instructions based on the assigned case number. An apparatus includes a host machine for receiving the input data set from the testing system and an algorithm for executing DOE to validate the test system. The algorithm applies DOE to the input data set to determine a data set having an optimal class width, assigns a case number to that data set, and generates validation instructions based on the case number.
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NASA Technical Reports Server (NTRS)
Perri, Todd A.; Mckillip, R. M., Jr.; Curtiss, H. C., Jr.
1987-01-01
The development and methodology is presented for development of full-authority implicit model-following and explicit model-following optimal controllers for use on helicopters operating in the Nap-of-the Earth (NOE) environment. Pole placement, input-output frequency response, and step input response were used to evaluate handling qualities performance. The pilot was equipped with velocity-command inputs. A mathematical/computational trajectory optimization method was employed to evaluate the ability of each controller to fly NOE maneuvers. The method determines the optimal swashplate and thruster input histories from the helicopter's dynamics and the prescribed geometry and desired flying qualities of the maneuver. Three maneuvers were investigated for both the implicit and explicit controllers with and without auxiliary propulsion installed: pop-up/dash/descent, bob-up at 40 knots, and glideslope. The explicit controller proved to be superior to the implicit controller in performance and ease of design.
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A Neural Network Aero Design System for Advanced Turbo-Engines
NASA Technical Reports Server (NTRS)
Sanz, Jose M.
1999-01-01
An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.
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MODFLOW 2000 Head Uncertainty, a First-Order Second Moment Method
Glasgow, H.S.; Fortney, M.D.; Lee, J.; Graettinger, A.J.; Reeves, H.W.
2003-01-01
A computationally efficient method to estimate the variance and covariance in piezometric head results computed through MODFLOW 2000 using a first-order second moment (FOSM) approach is presented. This methodology employs a first-order Taylor series expansion to combine model sensitivity with uncertainty in geologic data. MODFLOW 2000 is used to calculate both the ground water head and the sensitivity of head to changes in input data. From a limited number of samples, geologic data are extrapolated and their associated uncertainties are computed through a conditional probability calculation. Combining the spatially related sensitivity and input uncertainty produces the variance-covariance matrix, the diagonal of which is used to yield the standard deviation in MODFLOW 2000 head. The variance in piezometric head can be used for calibrating the model, estimating confidence intervals, directing exploration, and evaluating the reliability of a design. A case study illustrates the approach, where aquifer transmissivity is the spatially related uncertain geologic input data. The FOSM methodology is shown to be applicable for calculating output uncertainty for (1) spatially related input and output data, and (2) multiple input parameters (transmissivity and recharge).
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Method and apparatus for creating time-optimal commands for linear systems
NASA Technical Reports Server (NTRS)
Seering, Warren P. (Inventor); Tuttle, Timothy D. (Inventor)
2004-01-01
A system for and method of determining an input command profile for substantially any dynamic system that can be modeled as a linear system, the input command profile for transitioning an output of the dynamic system from one state to another state. The present invention involves identifying characteristics of the dynamic system, selecting a command profile which defines an input to the dynamic system based on the identified characteristics, wherein the command profile comprises one or more pulses which rise and fall at switch times, imposing a plurality of constraints on the dynamic system, at least one of the constraints being defined in terms of the switch times, and determining the switch times for the input to the dynamic system based on the command profile and the plurality of constraints. The characteristics may be related to poles and zeros of the dynamic system, and the plurality of constraints may include a dynamics cancellation constraint which specifies that the input moves the dynamic system from a first state to a second state such that the dynamic system remains substantially at the second state.
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Systems and methods for improved telepresence
Anderson, Matthew O.; Willis, W. David; Kinoshita, Robert A.
2005-10-25
The present invention provides a modular, flexible system for deploying multiple video perception technologies. The telepresence system of the present invention is capable of allowing an operator to control multiple mono and stereo video inputs in a hands-free manner. The raw data generated by the input devices is processed into a common zone structure that corresponds to the commands of the user, and the commands represented by the zone structure are transmitted to the appropriate device. This modularized approach permits input devices to be easily interfaced with various telepresence devices. Additionally, new input devices and telepresence devices are easily added to the system and are frequently interchangeable. The present invention also provides a modular configuration component that allows an operator to define a plurality of views each of which defines the telepresence devices to be controlled by a particular input device. The present invention provides a modular flexible system for providing telepresence for a wide range of applications. The modularization of the software components combined with the generalized zone concept allows the systems and methods of the present invention to be easily expanded to encompass new devices and new uses.
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NASA Astrophysics Data System (ADS)
Kim, Joon-Suk; Lee, Hae-Woo
2016-12-01
The grain size and the texture of three specimens prepared at different heat inputs were determined using optical microscopy and the electron backscatter diffraction method of scanning electron microscopy. Each specimen was equally divided into fusion line zone (FLZ), columnar dendrite zone (CDZ), and surface zone (SZ), according to the location of the weld. Fine dendrites were observed in the FLZ, coarse dendrites in the CDZ, and dendrites grew perpendicular to the FLZ and CDZ. As the heat input increased, the melted zone in the vicinity of the FLZ widened due to the higher Fe content. A lower image quality value was observed for the FLZ compared to the other zones. The results of grain size measurement in each zone showed that the grain size of the SZ became larger as the heat input increased. From the inverse pole figure (IPF) map in the normal direction (ND) and the rolling direction (RD), as the heat input increased, a specific orientation was formed. However, a dominant [001] direction was observed in the RD IPF map.
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A Web Browsing System by Eye-gaze Input
NASA Astrophysics Data System (ADS)
Abe, Kiyohiko; Owada, Kosuke; Ohi, Shoichi; Ohyama, Minoru
We have developed an eye-gaze input system for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS) patients. This system utilizes a personal computer and a home video camera to detect eye-gaze under natural light. The system detects both vertical and horizontal eye-gaze by simple image analysis, and does not require special image processing units or sensors. We also developed the platform for eye-gaze input based on our system. In this paper, we propose a new web browsing system for physically disabled computer users as an application of the platform for eye-gaze input. The proposed web browsing system uses a method of direct indicator selection. The method categorizes indicators by their function. These indicators are hierarchized relations; users can select the felicitous function by switching indicators group. This system also analyzes the location of selectable object on web page, such as hyperlink, radio button, edit box, etc. This system stores the locations of these objects, in other words, the mouse cursor skips to the object of candidate input. Therefore it enables web browsing at a faster pace.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Jason; Winkler, Jon
Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less
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Test Input Generation for Red-Black Trees using Abstraction
NASA Technical Reports Server (NTRS)
Visser, Willem; Pasareanu, Corina S.; Pelanek, Radek
2005-01-01
We consider the problem of test input generation for code that manipulates complex data structures. Test inputs are sequences of method calls from the data structure interface. We describe test input generation techniques that rely on state matching to avoid generation of redundant tests. Exhaustive techniques use explicit state model checking to explore all the possible test sequences up to predefined input sizes. Lossy techniques rely on abstraction mappings to compute and store abstract versions of the concrete states; they explore under-approximations of all the possible test sequences. We have implemented the techniques on top of the Java PathFinder model checker and we evaluate them using a Java implementation of red-black trees.
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NASA Astrophysics Data System (ADS)
Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.
2018-03-01
In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.
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NASA Astrophysics Data System (ADS)
Bulthuis, Kevin; Arnst, Maarten; Pattyn, Frank; Favier, Lionel
2017-04-01
Uncertainties in sea-level rise projections are mostly due to uncertainties in Antarctic ice-sheet predictions (IPCC AR5 report, 2013), because key parameters related to the current state of the Antarctic ice sheet (e.g. sub-ice-shelf melting) and future climate forcing are poorly constrained. Here, we propose to improve the predictions of Antarctic ice-sheet behaviour using new uncertainty quantification methods. As opposed to ensemble modelling (Bindschadler et al., 2013) which provides a rather limited view on input and output dispersion, new stochastic methods (Le Maître and Knio, 2010) can provide deeper insight into the impact of uncertainties on complex system behaviour. Such stochastic methods usually begin with deducing a probabilistic description of input parameter uncertainties from the available data. Then, the impact of these input parameter uncertainties on output quantities is assessed by estimating the probability distribution of the outputs by means of uncertainty propagation methods such as Monte Carlo methods or stochastic expansion methods. The use of such uncertainty propagation methods in glaciology may be computationally costly because of the high computational complexity of ice-sheet models. This challenge emphasises the importance of developing reliable and computationally efficient ice-sheet models such as the f.ETISh ice-sheet model (Pattyn, 2015), a new fast thermomechanical coupled ice sheet/ice shelf model capable of handling complex and critical processes such as the marine ice-sheet instability mechanism. Here, we apply these methods to investigate the role of uncertainties in sub-ice-shelf melting, calving rates and climate projections in assessing Antarctic contribution to sea-level rise for the next centuries using the f.ETISh model. We detail the methods and show results that provide nominal values and uncertainty bounds for future sea-level rise as a reflection of the impact of the input parameter uncertainties under consideration, as well as a ranking of the input parameter uncertainties in the order of the significance of their contribution to uncertainty in future sea-level rise. In addition, we discuss how limitations posed by the available information (poorly constrained data) pose challenges that motivate our current research.
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Methods, systems and apparatus for controlling operation of two alternating current (AC) machines
Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA
2012-02-14
A system is provided for controlling two AC machines. The system comprises a DC input voltage source that provides a DC input voltage, a voltage boost command control module (VBCCM), a five-phase PWM inverter module coupled to the two AC machines, and a boost converter coupled to the inverter module and the DC input voltage source. The boost converter is designed to supply a new DC input voltage to the inverter module having a value that is greater than or equal to a value of the DC input voltage. The VBCCM generates a boost command signal (BCS) based on modulation indexes from the two AC machines. The BCS controls the boost converter such that the boost converter generates the new DC input voltage in response to the BCS. When the two AC machines require additional voltage that exceeds the DC input voltage required to meet a combined target mechanical power required by the two AC machines, the BCS controls the boost converter to drive the new DC input voltage generated by the boost converter to a value greater than the DC input voltage.
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Experiments on Linguistically-Based Term Associations.
ERIC Educational Resources Information Center
Ruge, Gerda
1992-01-01
Describes the hyperterm system REALIST (Retrieval Aids by Linguistics and Statistics) with emphasis on its semantic component, which generates term relations from free-text input. Experiments with various similarity measures are discussed, and the quality of the associated terms is evaluated using term recall and term precision measures. (22…
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Schemata as a Reading Strategy.
ERIC Educational Resources Information Center
Mustapha, Zaliha
Reading is a multileveled, interactive, and hypothesis-generating process in which readers construct a meaningful representation of text by using their knowledge of the world and of language. If reading involves grasping the significance of an input depending on the reader's mental cognitive-perceptual situation, then there is a form of background…
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NASA scientific and technical information for the 1990s
NASA Technical Reports Server (NTRS)
Cotter, Gladys A.
1990-01-01
Projections for NASA scientific and technical information (STI) in the 1990s are outlined. NASA STI for the 1990s will maintain a quality bibliographic and full-text database, emphasizing electronic input and products supplemented by networked access to a wide variety of sources, particularly numeric databases.
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The Effects of Noisy Data on Text Retrieval.
ERIC Educational Resources Information Center
Taghva, Kazem; And Others
1994-01-01
Discusses the use of optical character recognition (OCR) for inputting documents in an information retrieval system and describes a study that used an OCR-generated database and its corresponding corrected version to examine query evaluation in the presence of noisy data. Scanning technology, recognition technology, and retrieval technology are…
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Linguistically Motivated Features for CCG Realization Ranking
ERIC Educational Resources Information Center
Rajkumar, Rajakrishnan
2012-01-01
Natural Language Generation (NLG) is the process of generating natural language text from an input, which is a communicative goal and a database or knowledge base. Informally, the architecture of a standard NLG system consists of the following modules (Reiter and Dale, 2000): content determination, sentence planning (or microplanning) and surface…
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Keyboard Proficiency: An Essential Skill in a Technological Age. Number 2.
ERIC Educational Resources Information Center
Gillmon, Eve
A structured keyboard skills training scheme for students in England should be included within school curricula. Negative attitudes toward keyboard training prevail in schools although employers value keyboard application skills. There are several reasons why keyboard proficiency, which facilitates the efficient input and retrieval of text and…
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Advanced Food Science and Nutrition Reference Book.
ERIC Educational Resources Information Center
Texas Tech Univ., Lubbock. Home Economics Curriculum Center.
Developed with input from personnel in the industries, this reference book complements the curriculum guide for a laboratory course on the significance of nutrition in food science. The reference book is organized into 25 chapters, each beginning with essential elements and objectives. Within the text, italicized, bold-faced vocabulary terms are…
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Next-Generation Lightweight Mirror Modeling Software
NASA Technical Reports Server (NTRS)
Arnold, William R., Sr.; Fitzgerald, Mathew; Rosa, Rubin Jaca; Stahl, Phil
2013-01-01
The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 5-10 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any editor, all the key shell thickness parameters are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models possible
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Next Generation Lightweight Mirror Modeling Software
NASA Technical Reports Server (NTRS)
Arnold, William; Fitzgerald, Matthew; Stahl, Philip
2013-01-01
The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 5-10 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any editor, all the key shell thickness parameters are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models possible.
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Next Generation Lightweight Mirror Modeling Software
NASA Technical Reports Server (NTRS)
Arnold, William R., Sr.; Fitzgerald, Mathew; Rosa, Rubin Jaca; Stahl, H. Philip
2013-01-01
The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 5-10 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any editor, all the key shell thickness parameters are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models easier.
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Calculating semantic relatedness for biomedical use in a knowledge-poor environment.
Rybinski, Maciej; Aldana-Montes, José
2014-01-01
Computing semantic relatedness between textual labels representing biological and medical concepts is a crucial task in many automated knowledge extraction and processing applications relevant to the biomedical domain, specifically due to the huge amount of new findings being published each year. Most methods benefit from making use of highly specific resources, thus reducing their usability in many real world scenarios that differ from the original assumptions. In this paper we present a simple resource-efficient method for calculating semantic relatedness in a knowledge-poor environment. The method obtains results comparable to state-of-the-art methods, while being more generic and flexible. The solution being presented here was designed to use only a relatively generic and small document corpus and its statistics, without referring to a previously defined knowledge base, thus it does not assume a 'closed' problem. We propose a method in which computation for two input texts is based on the idea of comparing the vocabulary associated with the best-fit documents related to those texts. As keyterm extraction is a costly process, it is done in a preprocessing step on a 'per-document' basis in order to limit the on-line processing. The actual computations are executed in a compact vector space, limited by the most informative extraction results. The method has been evaluated on five direct benchmarks by calculating correlation coefficients w.r.t. average human answers. It also has been used on Gene - Disease and Disease- Disease data pairs to highlight its potential use as a data analysis tool. Apart from comparisons with reported results, some interesting features of the method have been studied, i.e. the relationship between result quality, efficiency and applicable trimming threshold for size reduction. Experimental evaluation shows that the presented method obtains results that are comparable with current state of the art methods, even surpassing them on a majority of the benchmarks. Additionally, a possible usage scenario for the method is showcased with a real-world data experiment. Our method improves flexibility of the existing methods without a notable loss of quality. It is a legitimate alternative to the costly construction of specialized knowledge-rich resources.
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A hybrid brain-computer interface-based mail client.
Yu, Tianyou; Li, Yuanqing; Long, Jinyi; Li, Feng
2013-01-01
Brain-computer interface-based communication plays an important role in brain-computer interface (BCI) applications; electronic mail is one of the most common communication tools. In this study, we propose a hybrid BCI-based mail client that implements electronic mail communication by means of real-time classification of multimodal features extracted from scalp electroencephalography (EEG). With this BCI mail client, users can receive, read, write, and attach files to their mail. Using a BCI mouse that utilizes hybrid brain signals, that is, motor imagery and P300 potential, the user can select and activate the function keys and links on the mail client graphical user interface (GUI). An adaptive P300 speller is employed for text input. The system has been tested with 6 subjects, and the experimental results validate the efficacy of the proposed method.
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A Hybrid Brain-Computer Interface-Based Mail Client
Yu, Tianyou; Li, Yuanqing; Long, Jinyi; Li, Feng
2013-01-01
Brain-computer interface-based communication plays an important role in brain-computer interface (BCI) applications; electronic mail is one of the most common communication tools. In this study, we propose a hybrid BCI-based mail client that implements electronic mail communication by means of real-time classification of multimodal features extracted from scalp electroencephalography (EEG). With this BCI mail client, users can receive, read, write, and attach files to their mail. Using a BCI mouse that utilizes hybrid brain signals, that is, motor imagery and P300 potential, the user can select and activate the function keys and links on the mail client graphical user interface (GUI). An adaptive P300 speller is employed for text input. The system has been tested with 6 subjects, and the experimental results validate the efficacy of the proposed method. PMID:23690880
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Development of an online incident-reporting system for management of medical risks at hospital.
Kanda, Hirohito
2011-01-01
To minimize their occurrence, it is important to gather and analyze data regarding cases of not only medical accidents but also of incidents involving potential harm to patients. In gathering data, we have separated reporting between the details of such incidents and information about their occurrence. We have implemented a system involving a first report to achieve prompt notification and a second report to provide details. An online report input system has been established taking into consideration both ease of input and promptness of information sharing. We discuss the input of the first and second reports in a total of 951 cases over a period of 6 months. From the data regarding the timing of the first report, 307 and 789 cases were reported within 24 h and 48 h, respectively, indicating that the first report was input mostly without delay in accordance with the operational guidelines. On the other hand, it took 14 days to surpass a second report rate of 80%. Cases that took more than 2 weeks to be reported would likely have gone unreported had there not been a first report to indicate and confirm that an incident had even occurred. Investigation is needed, especially for problematic cases, so we assume that discovering important incidents via the first report has been successful. In addition, details of incidents can be input into this system in free-text, yielding information that cannot be acquired with multiple choice input as in standard reporting systems.
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NASA Astrophysics Data System (ADS)
Nishina, Kazuya; Ito, Akihiko; Hanasaki, Naota; Hayashi, Seiji
2017-02-01
Currently, available historical global N fertilizer map as an input data to global biogeochemical model is still limited and existing maps were not considered NH4+ and NO3- in the fertilizer application rates. This paper provides a method for constructing a new historical global nitrogen fertilizer application map (0.5° × 0.5° resolution) for the period 1961-2010 based on country-specific information from Food and Agriculture Organization statistics (FAOSTAT) and various global datasets. This new map incorporates the fraction of NH4+ (and NO3-) in N fertilizer inputs by utilizing fertilizer species information in FAOSTAT, in which species can be categorized as NH4+- and/or NO3--forming N fertilizers. During data processing, we applied a statistical data imputation method for the missing data (19 % of national N fertilizer consumption) in FAOSTAT. The multiple imputation method enabled us to fill gaps in the time-series data using plausible values using covariates information (year, population, GDP, and crop area). After the imputation, we downscaled the national consumption data to a gridded cropland map. Also, we applied the multiple imputation method to the available chemical fertilizer species consumption, allowing for the estimation of the NH4+ / NO3- ratio in national fertilizer consumption. In this study, the synthetic N fertilizer inputs in 2000 showed a general consistency with the existing N fertilizer map (Potter et al., 2010) in relation to the ranges of N fertilizer inputs. Globally, the estimated N fertilizer inputs based on the sum of filled data increased from 15 to 110 Tg-N during 1961-2010. On the other hand, the global NO3- input started to decline after the late 1980s and the fraction of NO3- in global N fertilizer decreased consistently from 35 to 13 % over a 50-year period. NH4+-forming fertilizers are dominant in most countries; however, the NH4+ / NO3- ratio in N fertilizer inputs shows clear differences temporally and geographically. This new map can be utilized as input data to global model studies and bring new insights for the assessment of historical terrestrial N cycling changes. Datasets available at doi:10.1594/PANGAEA.861203.
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NASA Astrophysics Data System (ADS)
Nadeau-Beaulieu, Michel
In this thesis, three mathematical models are built from flight test data for different aircraft design applications: a ground dynamics model for the Bell 427 helicopter, a prediction model for the rotor and engine parameters for the same helicopter type and a simulation model for the aeroelastic deflections of the F/A-18. In the ground dynamics application, the model structure is derived from physics where the normal force between the helicopter and the ground is modelled as a vertical spring and the frictional force is modelled with static and dynamic friction coefficients. The ground dynamics model coefficients are optimized to ensure that the model matches the landing data within the FAA (Federal Aviation Administration) tolerance bands for a level D flight simulator. In the rotor and engine application, rotors torques (main and tail), the engine torque and main rotor speed are estimated using a state-space model. The model inputs are nonlinear terms derived from the pilot control inputs and the helicopter states. The model parameters are identified using the subspace method and are further optimised with the Levenberg-Marquardt minimisation algorithm. The model built with the subspace method provides an excellent estimate of the outputs within the FAA tolerance bands. The F/A-18 aeroelastic state-space model is built from flight test. The research concerning this model is divided in two parts. Firstly, the deflection of a given structural surface on the aircraft following a differential ailerons control input is represented by a Multiple Inputs Single Outputs linear model whose inputs are the ailerons positions and the structural surfaces deflections. Secondly, a single state-space model is used to represent the deflection of the aircraft wings and trailing edge flaps following any control input. In this case the model is made non-linear by multiplying model inputs into higher order terms and using these terms as the inputs of the state-space equations. In both cases, the identification method is the subspace method. Most fit coefficients between the estimated and the measured signals are above 73% and most correlation coefficient are higher than 90%.
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Inspection Methods in Programming.
1981-06-01
Counting is a a specialization of Iterative-generation in which the generating function is Oneplus ) Waters’ second category of plan building method...is Oneplus and the initial input is 1. 0 I 180 CHAPTER NINE -ta a acio f igr9-.IeaieGnrtoPln 7 -7 STEADY STATE PLANS 181 TemporalPlan counting...specializalion iterative-generation roles .action(afu nction) ,tail(counting) conslraints .action.op = oneplus A .action.input = 1 The lItcrative-application
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Ubiquitous Creation of Bas-Relief Surfaces with Depth-of-Field Effects Using Smartphones.
Sohn, Bong-Soo
2017-03-11
This paper describes a new method to automatically generate digital bas-reliefs with depth-of-field effects from general scenes. Most previous methods for bas-relief generation take input in the form of 3D models. However, obtaining 3D models of real scenes or objects is often difficult, inaccurate, and time-consuming. From this motivation, we developed a method that takes as input a set of photographs that can be quickly and ubiquitously captured by ordinary smartphone cameras. A depth map is computed from the input photographs. The value range of the depth map is compressed and used as a base map representing the overall shape of the bas-relief. However, the resulting base map contains little information on details of the scene. Thus, we construct a detail map using pixel values of the input image to express the details. The base and detail maps are blended to generate a new depth map that reflects both overall depth and scene detail information. This map is selectively blurred to simulate the depth-of-field effects. The final depth map is converted to a bas-relief surface mesh. Experimental results show that our method generates a realistic bas-relief surface of general scenes with no expensive manual processing.
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Ubiquitous Creation of Bas-Relief Surfaces with Depth-of-Field Effects Using Smartphones
Sohn, Bong-Soo
2017-01-01
This paper describes a new method to automatically generate digital bas-reliefs with depth-of-field effects from general scenes. Most previous methods for bas-relief generation take input in the form of 3D models. However, obtaining 3D models of real scenes or objects is often difficult, inaccurate, and time-consuming. From this motivation, we developed a method that takes as input a set of photographs that can be quickly and ubiquitously captured by ordinary smartphone cameras. A depth map is computed from the input photographs. The value range of the depth map is compressed and used as a base map representing the overall shape of the bas-relief. However, the resulting base map contains little information on details of the scene. Thus, we construct a detail map using pixel values of the input image to express the details. The base and detail maps are blended to generate a new depth map that reflects both overall depth and scene detail information. This map is selectively blurred to simulate the depth-of-field effects. The final depth map is converted to a bas-relief surface mesh. Experimental results show that our method generates a realistic bas-relief surface of general scenes with no expensive manual processing. PMID:28287487
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The short time Fourier transform and local signals
NASA Astrophysics Data System (ADS)
Okumura, Shuhei
In this thesis, I examine the theoretical properties of the short time discrete Fourier transform (STFT). The STFT is obtained by applying the Fourier transform by a fixed-sized, moving window to input series. We move the window by one time point at a time, so we have overlapping windows. I present several theoretical properties of the STFT, applied to various types of complex-valued, univariate time series inputs, and their outputs in closed forms. In particular, just like the discrete Fourier transform, the STFT's modulus time series takes large positive values when the input is a periodic signal. One main point is that a white noise time series input results in the STFT output being a complex-valued stationary time series and we can derive the time and time-frequency dependency structure such as the cross-covariance functions. Our primary focus is the detection of local periodic signals. I present a method to detect local signals by computing the probability that the squared modulus STFT time series has consecutive large values exceeding some threshold after one exceeding observation following one observation less than the threshold. We discuss a method to reduce the computation of such probabilities by the Box-Cox transformation and the delta method, and show that it works well in comparison to the Monte Carlo simulation method.
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Human Splice-Site Prediction with Deep Neural Networks.
Naito, Tatsuhiko
2018-04-18
Accurate splice-site prediction is essential to delineate gene structures from sequence data. Several computational techniques have been applied to create a system to predict canonical splice sites. For classification tasks, deep neural networks (DNNs) have achieved record-breaking results and often outperformed other supervised learning techniques. In this study, a new method of splice-site prediction using DNNs was proposed. The proposed system receives an input sequence data and returns an answer as to whether it is splice site. The length of input is 140 nucleotides, with the consensus sequence (i.e., "GT" and "AG" for the donor and acceptor sites, respectively) in the middle. Each input sequence model is applied to the pretrained DNN model that determines the probability that an input is a splice site. The model consists of convolutional layers and bidirectional long short-term memory network layers. The pretraining and validation were conducted using the data set tested in previously reported methods. The performance evaluation results showed that the proposed method can outperform the previous methods. In addition, the pattern learned by the DNNs was visualized as position frequency matrices (PFMs). Some of PFMs were very similar to the consensus sequence. The trained DNN model and the brief source code for the prediction system are uploaded. Further improvement will be achieved following the further development of DNNs.
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Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong
2011-12-01
In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.
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pong: fast analysis and visualization of latent clusters in population genetic data.
Behr, Aaron A; Liu, Katherine Z; Liu-Fang, Gracie; Nakka, Priyanka; Ramachandran, Sohini
2016-09-15
A series of methods in population genetics use multilocus genotype data to assign individuals membership in latent clusters. These methods belong to a broad class of mixed-membership models, such as latent Dirichlet allocation used to analyze text corpora. Inference from mixed-membership models can produce different output matrices when repeatedly applied to the same inputs, and the number of latent clusters is a parameter that is often varied in the analysis pipeline. For these reasons, quantifying, visualizing, and annotating the output from mixed-membership models are bottlenecks for investigators across multiple disciplines from ecology to text data mining. We introduce pong, a network-graphical approach for analyzing and visualizing membership in latent clusters with a native interactive D3.js visualization. pong leverages efficient algorithms for solving the Assignment Problem to dramatically reduce runtime while increasing accuracy compared with other methods that process output from mixed-membership models. We apply pong to 225 705 unlinked genome-wide single-nucleotide variants from 2426 unrelated individuals in the 1000 Genomes Project, and identify previously overlooked aspects of global human population structure. We show that pong outpaces current solutions by more than an order of magnitude in runtime while providing a customizable and interactive visualization of population structure that is more accurate than those produced by current tools. pong is freely available and can be installed using the Python package management system pip. pong's source code is available at https://github.com/abehr/pong aaron_behr@alumni.brown.edu or sramachandran@brown.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
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Product Recommendation System Based on Personal Preference Model Using CAM
NASA Astrophysics Data System (ADS)
Murakami, Tomoko; Yoshioka, Nobukazu; Orihara, Ryohei; Furukawa, Koichi
Product recommendation system is realized by applying business rules acquired by data maining techniques. Business rules such as demographical patterns of purchase, are able to cover the groups of users that have a tendency to purchase products, but it is difficult to recommend products adaptive to various personal preferences only by utilizing them. In addition to that, it is very costly to gather the large volume of high quality survey data, which is necessary for good recommendation based on personal preference model. A method collecting kansei information automatically without questionnaire survey is required. The constructing personal preference model from less favor data is also necessary, since it is costly for the user to input favor data. In this paper, we propose product recommendation system based on kansei information extracted by text mining and user's preference model constructed by Category-guided Adaptive Modeling, CAM for short. CAM is a feature construction method that can generate new features constructing the space where same labeled examples are close and different labeled examples are far away from some labeled examples. It is possible to construct personal preference model by CAM despite less information of likes and dislikes categories. In the system, retrieval agent gathers the products' specification and user agent manages preference model, user's likes and dislikes. Kansei information of the products is gained by applying text mining technique to the reputation documents about the products on the web site. We carry out some experimental studies to make sure that prefrence model obtained by our method performs effectively.
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Image based SAR product simulation for analysis
NASA Technical Reports Server (NTRS)
Domik, G.; Leberl, F.
1987-01-01
SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.
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Unsteady hovering wake parameters identified from dynamic model tests, part 1
NASA Technical Reports Server (NTRS)
Hohenemser, K. H.; Crews, S. T.
1977-01-01
The development of a 4-bladed model rotor is reported that can be excited with a simple eccentric mechanism in progressing and regressing modes with either harmonic or transient inputs. Parameter identification methods were applied to the problem of extracting parameters for linear perturbation models, including rotor dynamic inflow effects, from the measured blade flapping responses to transient pitch stirring excitations. These perturbation models were then used to predict blade flapping response to other pitch stirring transient inputs, and rotor wake and blade flapping responses to harmonic inputs. The viability and utility of using parameter identification methods for extracting the perturbation models from transients are demonstrated through these combined analytical and experimental studies.
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NASA Astrophysics Data System (ADS)
Yira, Yacouba; Diekkrüger, Bernd; Steup, Gero; Yaovi Bossa, Aymar
2017-04-01
This study evaluates climate change impacts on water resources using an ensemble of six regional climate models (RCMs)-global climate models (GCMs) in the Dano catchment (Burkina Faso). The applied climate datasets were performed in the framework of the COordinated Regional climate Downscaling Experiment (CORDEX-Africa) project.
After evaluation of the historical runs of the climate models' ensemble, a statistical bias correction (empirical quantile mapping) was applied to daily precipitation. Temperature and bias corrected precipitation data from the ensemble of RCMs-GCMs was then used as input for the Water flow and balance Simulation Model (WaSiM) to simulate water balance components.
The mean hydrological and climate variables for two periods (1971-2000 and 2021-2050) were compared to assess the potential impact of climate change on water resources up to the middle of the 21st century under two greenhouse gas concentration scenarios, the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicate (i) a clear signal of temperature increase of about 0.1 to 2.6 °C for all members of the RCM-GCM ensemble; (ii) high uncertainty about how the catchment precipitation will evolve over the period 2021-2050; (iii) the applied bias correction method only affected the magnitude of the climate change signal; (iv) individual climate models results lead to opposite discharge change signals; and (v) the results for the RCM-GCM ensemble are too uncertain to give any clear direction for future hydrological development. Therefore, potential increase and decrease in future discharge have to be considered in climate change adaptation strategies in the catchment. The results further underline on the one hand the need for a larger ensemble of projections to properly estimate the impacts of climate change on water resources in the catchment and on the other hand the high uncertainty associated with climate projections for the West African region. A water-energy budget analysis provides further insight into the behavior of the catchment.
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Understanding Coreference in a System for Solving Physics Word Problems.
NASA Astrophysics Data System (ADS)
Bulko, William Charles
In this thesis, a computer program (BEATRIX) is presented which takes as input an English statement of a physics problem and a figure associated with it, understands the two kinds of input in combination, and produces a data structure containing a model of the physical objects described and the relationships between them. BEATRIX provides a mouse-based graphic interface with which the user sketches a picture and enters English sentences; meanwhile, BEATRIX creates a neutral internal representation of the picture similar to the which might be produced as the output of a vision system. It then parses the text and the picture representation, resolves the references between objects common to the two data sources, and produces a unified model of the problem world. The correctness and completeness of this model has been validated by applying it as input to a physics problem-solving program currently under development. Two descriptions of a world are said to be coreferent when they contain references to overlapping sets of objects. Resolving coreferences to produce a correct world model is a common task in scientific and industrial problem-solving: because English is typically not a good language for expressing spatial relationships, people in these fields frequently use diagrams to supplement textual descriptions. Elementary physics problems from college-level textbooks provide a useful and convenient domain for exploring the mechanisms of coreference. Because flexible, opportunistic control is necessary in order to recognize coreference and to act upon it, the understanding module of BEATRIX uses a blackboard control structure. The blackboard knowledge sources serve to identify physical objects in the picture, parse the English text, and resolve coreferences between the two. We believed that BEATRIX demonstrates a control structure and collection of knowledge that successfully implements understanding of text and picture by computer. We also believe that this organization can be applied successfully to similar understanding tasks in domains other than physics problem -solving, where data such as the output from vision systems and speech understanders can be used in place of text and pictures.
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The integration of Human Factors (HF) in the SAR process training course text
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ryan, T.G.
1995-03-01
This text provides the technical basis for a two-day course on human factors (HF), as applied to the Safety Analysis Report (SAR) process. The overall objective of this text and course is to: provide the participant with a working knowledge of human factors-related requirements, suggestions for doing a human safety analysis applying a graded approach, and an ability to demonstrate using the results of the human safety analysis, that human factors elements as defined by DOE (human factors engineering, procedures, training, oversight, staffing, qualifications), can support wherever necessary, nuclear safety commitments in the SAR. More specifically, the objectives of themore » text and course are: (1) To provide the SAR preparer with general guidelines for doing HE within the context of a graded approach for the SAR; (2) To sensitize DOE facility managers and staff, safety analysts and SAR preparers, independent reviewers, and DOE reviewers and regulators, to DOE Order 5480.23 requirements for HE in the SAR; (3) To provide managers, analysts, reviewers and regulators with a working knowledge of HE concepts and techniques within the context of a graded approach for the SAR, and (4) To provide SAR managers and DOE reviewers and regulators with general guidelines for monitoring and coordinating the work of preparers of HE inputs throughout the SAR process, and for making decisions regarding the safety relevance of HE inputs to the SAR. As a ready reference for implementing the human factors requirements of DOE Order 5480.22 and DOE Standard 3009-94, this course text and accompanying two-day course are intended for all persons who are involved in the SAR.« less
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NASA Technical Reports Server (NTRS)
Simons, Rainee N (Inventor); Chevalier, Christine T (Inventor); Wintucky, Edwin G (Inventor); Freeman, Jon C (Inventor)
2016-01-01
One or more embodiments of the present invention describe an apparatus and method to combine unequal powers. The apparatus includes a first input port, a second input port, and a combiner. The first input port is operably connected to a first power amplifier and is configured to receive a first power from the first power amplifier. The second input port is operably connected to a second power amplifier and is configured to receive a second power from the second power amplifier. The combiner is configured to simultaneously receive the first power from the first input port and the second power from the second input port. The combiner is also configured to combine the first power and second power to produce a maximized power. The first power and second power are unequal.
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Identification of modal parameters including unmeasured forces and transient effects
NASA Astrophysics Data System (ADS)
Cauberghe, B.; Guillaume, P.; Verboven, P.; Parloo, E.
2003-08-01
In this paper, a frequency-domain method to estimate modal parameters from short data records with known input (measured) forces and unknown input forces is presented. The method can be used for an experimental modal analysis, an operational modal analysis (output-only data) and the combination of both. A traditional experimental and operational modal analysis in the frequency domain starts respectively, from frequency response functions and spectral density functions. To estimate these functions accurately sufficient data have to be available. The technique developed in this paper estimates the modal parameters directly from the Fourier spectra of the outputs and the known input. Instead of using Hanning windows on these short data records the transient effects are estimated simultaneously with the modal parameters. The method is illustrated, tested and validated by Monte Carlo simulations and experiments. The presented method to process short data sequences leads to unbiased estimates with a small variance in comparison to the more traditional approaches.
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Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance
2017-01-01
This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529
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Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods
NASA Astrophysics Data System (ADS)
Wang, Yunhua; DeBrunner, Linda; DeBrunner, Victor; Zhou, Dayong
2008-12-01
Tsatsanis and Xu have applied the constrained minimum output variance (CMOV) principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE) equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.
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NASA Astrophysics Data System (ADS)
Casasent, David P.; Shenoy, Rajesh
1997-10-01
Classification and pose estimation of distorted input objects are considered. The feature space trajectory representation of distorted views of an object is used with a new eigenfeature space. For a distorted input object, the closest trajectory denotes the class of the input and the closest line segment on it denotes its pose. If an input point is too far from a trajectory, it is rejected as clutter. New methods for selecting Fukunaga-Koontz discriminant vectors, the number of dominant eigenvectors per class and for determining training, and test set compatibility are presented.
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System and method for pre-cooling of buildings
Springer, David A.; Rainer, Leo I.
2011-08-09
A method for nighttime pre-cooling of a building comprising inputting one or more user settings, lowering the indoor temperature reading of the building during nighttime by operating an outside air ventilation system followed, if necessary, by a vapor compression cooling system. The method provides for nighttime pre-cooling of a building that maintains indoor temperatures within a comfort range based on the user input settings, calculated operational settings, and predictions of indoor and outdoor temperature trends for a future period of time such as the next day.
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Pendulation control system and method for rotary boom cranes
Robinett, III, Rush D.; Groom, Kenneth N.; Feddema, John T.; Parker, Gordon G.
2002-01-01
A command shaping control system and method for rotary boom cranes provides a way to reduce payload pendulation caused by real-time input signals, from either operator command or automated crane maneuvers. The method can take input commands and can apply a command shaping filter to reduce contributors to payload pendulation due to rotation, elevation, and hoisting movements in order to control crane response and reduce tangential and radial payload pendulation. A filter can be applied to a pendulation excitation frequency to reduce residual radial pendulation and tangential pendulation amplitudes.
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NASA Technical Reports Server (NTRS)
Young, J. W.; Schy, A. A.; Johnson, K. G.
1977-01-01
An analytical method has been developed for predicting critical control inputs for which nonlinear rotational coupling may cause sudden jumps in aircraft response. The analysis includes the effect of aerodynamics which are nonlinear in angle of attack. The method involves the simultaneous solution of two polynomials in roll rate, whose coefficients are functions of angle of attack and the control inputs. Results obtained using this procedure are compared with calculated time histories to verify the validity of the method for predicting jump-like instabilities.
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Identifying the location of the OMP separatrix in DIII-D using power accounting
Stangeby, Peter C.; Canik, John M.; Elder, J. D.; ...
2015-08-07
In order to identify reliable scalings for the scrape-off layer (SOL) power width it is necessary to know the location of the separatrix in divertor tokamaks as accurately as possible, specifically its location at the outside midplane (OMP) the standard reference location. Two methods are described which use power accounting to improve the accuracy of identifying the location of the OMP separatrix. The first uses the infrared-measured deposited power profile at the outer target as the primary input, the 'more » $$P_{{\\rm SOL}}^{{\\rm exhaust}}$$ method'. The second uses the measured power input to the SOL, obtained by subtracting the power radiated from inside the separatrix from the total heating power, the ' $$P_{{\\rm SOL}}^{{\\rm input}}$$ method'. Furthermore, these two power accounting methods are illustrated with the examples of 21 H-mode DIII-D discharges. High spatial resolution Thomson scattering measured profiles of ne and Te for the main SOL near the OMP are also used as primary input to the analysis; only between-edge localized mode data are used here. The Thomson profiles are used to calculate the electron parallel conducted heat flux profiles which are then matched to the measured $$P_{{\\rm SOL}}^{{\\rm exhaust}}$$ and $$P_{{\\rm SOL}}^{{\\rm input}}$$ by adjusting the location of the OMP separatrix relative to that of the Thomson data. For these attached discharges, it is found that the values of $$R_{{\\rm sep}}^{{\\rm omp}}$$ given by the two power accounting methods agree to within ~1 mm of each other and also to within ~1 mm of the values given by the 'standard DIII-D method' described by Porter et al (1998 Phys. Plasmas 5 1410). Lastly, the shifted $$R_{{\\rm sep}}^{{\\rm omp}}$$ results in only modest changes to the values of ne and Te at the OMP separatrix relative to the 'standard' values, increasing $$n_{{\\rm e}}^{{\\rm sep}}$$ by 8% and $$T_{{\\rm e}}^{{\\rm sep}}$$ by 20%.« less
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A Mis-recognized Medical Vocabulary Correction System for Speech-based Electronic Medical Record
Seo, Hwa Jeong; Kim, Ju Han; Sakabe, Nagamasa
2002-01-01
Speech recognition as an input tool for electronic medical record (EMR) enables efficient data entry at the point of care. However, the recognition accuracy for medical vocabulary is much poorer than that for doctor-patient dialogue. We developed a mis-recognized medical vocabulary correction system based on syllable-by-syllable comparison of speech text against medical vocabulary database. Using specialty medical vocabulary, the algorithm detects and corrects mis-recognized medical vocabularies in narrative text. Our preliminary evaluation showed 94% of accuracy in mis-recognized medical vocabulary correction.
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Real-time flood forecasts & risk assessment using a possibility-theory based fuzzy neural network
NASA Astrophysics Data System (ADS)
Khan, U. T.
2016-12-01
Globally floods are one of the most devastating natural disasters and improved flood forecasting methods are essential for better flood protection in urban areas. Given the availability of high resolution real-time datasets for flood variables (e.g. streamflow and precipitation) in many urban areas, data-driven models have been effectively used to predict peak flow rates in river; however, the selection of input parameters for these types of models is often subjective. Additionally, the inherit uncertainty associated with data models along with errors in extreme event observations means that uncertainty quantification is essential. Addressing these concerns will enable improved flood forecasting methods and provide more accurate flood risk assessments. In this research, a new type of data-driven model, a quasi-real-time updating fuzzy neural network is developed to predict peak flow rates in urban riverine watersheds. A possibility-to-probability transformation is first used to convert observed data into fuzzy numbers. A possibility theory based training regime is them used to construct the fuzzy parameters and the outputs. A new entropy-based optimisation criterion is used to train the network. Two existing methods to select the optimum input parameters are modified to account for fuzzy number inputs, and compared. These methods are: Entropy-Wavelet-based Artificial Neural Network (EWANN) and Combined Neural Pathway Strength Analysis (CNPSA). Finally, an automated algorithm design to select the optimum structure of the neural network is implemented. The overall impact of each component of training this network is to replace the traditional ad hoc network configuration methods, with one based on objective criteria. Ten years of data from the Bow River in Calgary, Canada (including two major floods in 2005 and 2013) are used to calibrate and test the network. The EWANN method selected lagged peak flow as a candidate input, whereas the CNPSA method selected lagged precipitation and lagged mean daily flow as candidate inputs. Model performance metric show that the CNPSA method had higher performance (with an efficiency of 0.76). Model output was used to assess the risk of extreme peak flows for a given day using an inverse possibility-to-probability transformation.
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a Method for Preview Vibration Control of Systems Having Forcing Inputs and Rapidly-Switched Dampers
NASA Astrophysics Data System (ADS)
ElBeheiry, E. M.
1998-07-01
In a variety of applications, especially in large scale dynamic systems, the mechanization of different vibration control elements in different locations would be decided by limitations placed on the modal vibration of the system and the inherent dynamic coupling between its modes. Also, the quality of vibration control to the economy of producing the whole system would be another trade-off leading to a mix of passive, active and semi-active vibration control elements in one system. This termactiveis limited to externally powered vibration control inputs and the termsemi-activeis limited to rapidly switched dampers. In this article, an optimal preview control method is developed for application to dynamic systems having active and semi-active vibration control elements mechanized at different locations in one system. The system is then a piecewise (bilinear) controller in which two independent sets of control inputs appear additively and multiplicatively. Calculus of variations along with the Hamiltonian approach are employed for the derivation of this method. In essence, it requires the active elements to be ideal force generators and the switched dampers to have the property of on-line variation of the damping characteristics to pre-determined limits. As the dampers switch during operation the whole system's structure differs, and then values of the active forcing inputs are adapted to match these rapid changes. Strictly speaking, each rapidly switched damper has pre-known upper and lower damping levels and it can take on any in-between value. This in-between value is to be determined by the method as long as the damper tracks a pre-known fully active control demand. In every damping state of each semi-active damper the method provides the optimal matching values of the active forcing inputs. The method is shown to have the feature of solving simple standard matrix equations to obtain closed form solutions. A comprehensive 9-DOF tractor semi-trailer model is used to demonstrate the effectiveness of the method. Time domain predictions are made to compare performance of ride and tyre-to-road contact in the model for the presented method with those of some other active and semi-active suspension designs.
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Image based book cover recognition and retrieval
NASA Astrophysics Data System (ADS)
Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine
2017-11-01
In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.
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Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Robertson, J.; Polly, B.; Collis, J.
2013-09-01
This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define 'explicit' input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAEmore » 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.« less
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Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
and Ben Polly, Joseph Robertson; Polly, Ben; Collis, Jon
2013-09-01
This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAEmore » 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.« less
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Method for analyzing the chemical composition of liquid effluent from a direct contact condenser
Bharathan, Desikan; Parent, Yves; Hassani, A. Vahab
2001-01-01
A computational modeling method for predicting the chemical, physical, and thermodynamic performance of a condenser using calculations based on equations of physics for heat, momentum and mass transfer and equations of equilibrium thermodynamics to determine steady state profiles of parameters throughout the condenser. The method includes providing a set of input values relating to a condenser including liquid loading, vapor loading, and geometric characteristics of the contact medium in the condenser. The geometric and packing characteristics of the contact medium include the dimensions and orientation of a channel in the contact medium. The method further includes simulating performance of the condenser using the set of input values to determine a related set of output values such as outlet liquid temperature, outlet flow rates, pressures, and the concentration(s) of one or more dissolved noncondensable gas species in the outlet liquid. The method may also include iteratively performing the above computation steps using a plurality of sets of input values and then determining whether each of the resulting output values and performance profiles satisfies acceptance criteria.
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Natural Language Processing in Radiology: A Systematic Review.
Pons, Ewoud; Braun, Loes M M; Hunink, M G Myriam; Kors, Jan A
2016-05-01
Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are stored for communication and documentation of diagnostic imaging, harnessing their potential requires efficient and automated information extraction: they exist mainly as free-text clinical narrative, from which it is a major challenge to obtain structured data. Natural language processing (NLP) provides techniques that aid the conversion of text into a structured representation, and thus enables computers to derive meaning from human (ie, natural language) input. Used on radiology reports, NLP techniques enable automatic identification and extraction of information. By exploring the various purposes for their use, this review examines how radiology benefits from NLP. A systematic literature search identified 67 relevant publications describing NLP methods that support practical applications in radiology. This review takes a close look at the individual studies in terms of tasks (ie, the extracted information), the NLP methodology and tools used, and their application purpose and performance results. Additionally, limitations, future challenges, and requirements for advancing NLP in radiology will be discussed. (©) RSNA, 2016 Online supplemental material is available for this article.
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Reconstruction of nonlinear wave propagation
Fleischer, Jason W; Barsi, Christopher; Wan, Wenjie
2013-04-23
Disclosed are systems and methods for characterizing a nonlinear propagation environment by numerically propagating a measured output waveform resulting from a known input waveform. The numerical propagation reconstructs the input waveform, and in the process, the nonlinear environment is characterized. In certain embodiments, knowledge of the characterized nonlinear environment facilitates determination of an unknown input based on a measured output. Similarly, knowledge of the characterized nonlinear environment also facilitates formation of a desired output based on a configurable input. In both situations, the input thus characterized and the output thus obtained include features that would normally be lost in linear propagations. Such features can include evanescent waves and peripheral waves, such that an image thus obtained are inherently wide-angle, farfield form of microscopy.
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Methods and systems for determining angular orientation of a drill string
Cobern, Martin E.
2010-03-23
Preferred methods and systems generate a control input based on a periodically-varying characteristic associated with the rotation of a drill string. The periodically varying characteristic can be correlated with the magnetic tool face and gravity tool face of a rotating component of the drill string, so that the control input can be used to initiate a response in the rotating component as a function of gravity tool face.
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Statistical plant set estimation using Schroeder-phased multisinusoidal input design
NASA Technical Reports Server (NTRS)
Bayard, D. S.
1992-01-01
A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Shi, E-mail: sjin@wisc.edu; Institute of Natural Sciences, Department of Mathematics, MOE-LSEC and SHL-MAC, Shanghai Jiao Tong University, Shanghai 200240; Lu, Hanqing, E-mail: hanqing@math.wisc.edu
2017-04-01
In this paper, we develop an Asymptotic-Preserving (AP) stochastic Galerkin scheme for the radiative heat transfer equations with random inputs and diffusive scalings. In this problem the random inputs arise due to uncertainties in cross section, initial data or boundary data. We use the generalized polynomial chaos based stochastic Galerkin (gPC-SG) method, which is combined with the micro–macro decomposition based deterministic AP framework in order to handle efficiently the diffusive regime. For linearized problem we prove the regularity of the solution in the random space and consequently the spectral accuracy of the gPC-SG method. We also prove the uniform (inmore » the mean free path) linear stability for the space-time discretizations. Several numerical tests are presented to show the efficiency and accuracy of proposed scheme, especially in the diffusive regime.« less
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In-Flight System Identification
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1998-01-01
A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.
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Fuzzy set methods for object recognition in space applications
NASA Technical Reports Server (NTRS)
Keller, James M.
1991-01-01
During the reporting period, the development of the theory and application of methodologies for decision making under uncertainty was addressed. Two subreports are included; the first on properties of general hybrid operators, while the second considers some new research on generalized threshold logic units. In the first part, the properties of the additive gamma-model, where the intersection part is first considered to be the product of the input values and the union part is obtained by an extension of De Morgan's law to fuzzy sets, is explored. Then the Yager's class of union and intersection is used in the additive gamma-model. The inputs are weighted to some power that represents their importance and thus their contribution to the compensation process. In the second part, the extension of binary logic synthesis methods to multiple valued logic synthesis methods to enable the synthesis of decision networks when the input/output variables are not binary is discussed.
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Method and apparatus for fault tolerance
NASA Technical Reports Server (NTRS)
Masson, Gerald M. (Inventor); Sullivan, Gregory F. (Inventor)
1993-01-01
A method and apparatus for achieving fault tolerance in a computer system having at least a first central processing unit and a second central processing unit. The method comprises the steps of first executing a first algorithm in the first central processing unit on input which produces a first output as well as a certification trail. Next, executing a second algorithm in the second central processing unit on the input and on at least a portion of the certification trail which produces a second output. The second algorithm has a faster execution time than the first algorithm for a given input. Then, comparing the first and second outputs such that an error result is produced if the first and second outputs are not the same. The step of executing a first algorithm and the step of executing a second algorithm preferably takes place over essentially the same time period.
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Method of Controlling Steering of a Ground Vehicle
NASA Technical Reports Server (NTRS)
Guo, Raymond (Inventor); Atluri, Venkata Prasad (Inventor); Bluethmann, William J. (Inventor); Lee, Chunhao J. (Inventor); Vitale, Robert L. (Inventor); Dawson, Andrew D. (Inventor)
2016-01-01
A method of controlling steering of a vehicle through setting wheel angles of a plurality of modular electronic corner assemblies (eModules) is provided. The method includes receiving a driving mode selected from a mode selection menu. A position of a steering input device is determined in a master controller. A velocity of the vehicle is determined, in the master controller, when the determined position of the steering input device is near center. A drive mode request corresponding to the selected driving mode to the plurality of steering controllers is transmitted to the master controller. A required steering angle of each of the plurality of eModules is determined, in the master controller, as a function of the determined position of the steering input device, the determined velocity of the vehicle, and the selected first driving mode. The eModules are set to the respective determined steering angles.
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Optimal allocation of testing resources for statistical simulations
NASA Astrophysics Data System (ADS)
Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick
2015-07-01
Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.
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Road simulation for four-wheel vehicle whole input power spectral density
NASA Astrophysics Data System (ADS)
Wang, Jiangbo; Qiang, Baomin
2017-05-01
As the vibration of running vehicle mainly comes from road and influence vehicle ride performance. So the road roughness power spectral density simulation has great significance to analyze automobile suspension vibration system parameters and evaluate ride comfort. Firstly, this paper based on the mathematical model of road roughness power spectral density, established the integral white noise road random method. Then in the MATLAB/Simulink environment, according to the research method of automobile suspension frame from simple two degree of freedom single-wheel vehicle model to complex multiple degrees of freedom vehicle model, this paper built the simple single incentive input simulation model. Finally the spectrum matrix was used to build whole vehicle incentive input simulation model. This simulation method based on reliable and accurate mathematical theory and can be applied to the random road simulation of any specified spectral which provides pavement incentive model and foundation to vehicle ride performance research and vibration simulation.
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Refining Linear Fuzzy Rules by Reinforcement Learning
NASA Technical Reports Server (NTRS)
Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil
1996-01-01
Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.
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Srivastava, Saurabh Kumar; Singh, Sandeep Kumar; Suri, Jasjit S
2018-04-13
A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy because the text classification systems lack the ability to model the input text data in terms of noise characteristics. This research study proposes a concept of misrepresentation ratio (MRR) on input healthcare text data and models the PE criteria for validating the hypothesis. Further, such a novel system provides a platform to amalgamate several attributes of the ML system such as: data size, classifier type, partitioning protocol and percentage MRR. Our comprehensive data analysis consisted of five types of text data sets (TwitterA, WebKB4, Disease, Reuters (R8), and SMS); five kinds of classifiers (support vector machine with linear kernel (SVM-L), MLP-based neural network, AdaBoost, stochastic gradient descent and decision tree); and five types of training protocols (K2, K4, K5, K10 and JK). Using the decreasing order of MRR, our ML system demonstrates the mean classification accuracies as: 70.13 ± 0.15%, 87.34 ± 0.06%, 93.73 ± 0.03%, 94.45 ± 0.03% and 97.83 ± 0.01%, respectively, using all the classifiers and protocols. The corresponding AUC is 0.98 for SMS data using Multi-Layer Perceptron (MLP) based neural network. All the classifiers, the best accuracy of 91.84 ± 0.04% is shown to be of MLP-based neural network and this is 6% better over previously published. Further we observed that as MRR decreases, the system robustness increases and validated by standard deviations. The overall text system accuracy using all data types, classifiers, protocols is 89%, thereby showing the entire ML system to be novel, robust and unique. The system is also tested for stability and reliability.
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ERGONOMICS ABSTRACTS 48347-48982.
ERIC Educational Resources Information Center
Ministry of Technology, London (England). Warren Spring Lab.
IN THIS COLLECTION OF ERGONOMICS ABSTRACTS AND ANNOTATIONS THE FOLLOWING AREAS OF CONCERN ARE REPRESENTED--GENERAL REFERENCES, METHODS, FACILITIES, AND EQUIPMENT RELATING TO ERGONOMICS, SYSTEMS OF MAN AND MACHINES, VISUAL, AUDITORY, AND OTHER SENSORY INPUTS AND PROCESSES (INCLUDING SPEECH AND INTELLIGIBILITY), INPUT CHANNELS, BODY MEASUREMENTS,…
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Verloock, Leen; Joseph, Wout; Gati, Azeddine; Varsier, Nadège; Flach, Björn; Wiart, Joe; Martens, Luc
2013-06-01
An experimental validation of a low-cost method for extrapolation and estimation of the maximal electromagnetic-field exposure from long-term evolution (LTE) radio base station installations are presented. No knowledge on downlink band occupation or service characteristics is required for the low-cost method. The method is applicable in situ. It only requires a basic spectrum analyser with appropriate field probes without the need of expensive dedicated LTE decoders. The method is validated both in laboratory and in situ, for a single-input single-output antenna LTE system and a 2×2 multiple-input multiple-output system, with low deviations in comparison with signals measured using dedicated LTE decoders.
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NASA Technical Reports Server (NTRS)
Jacob, H. G.
1972-01-01
An optimization method has been developed that computes the optimal open loop inputs for a dynamical system by observing only its output. The method reduces to static optimization by expressing the inputs as series of functions with parameters to be optimized. Since the method is not concerned with the details of the dynamical system to be optimized, it works for both linear and nonlinear systems. The method and the application to optimizing longitudinal landing paths for a STOL aircraft with an augmented wing are discussed. Noise, fuel, time, and path deviation minimizations are considered with and without angle of attack, acceleration excursion, flight path, endpoint, and other constraints.
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NASA Astrophysics Data System (ADS)
Cyganek, Boguslaw; Smolka, Bogdan
2015-02-01
In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.
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On the fusion of tuning parameters of fuzzy rules and neural network
NASA Astrophysics Data System (ADS)
Mamuda, Mamman; Sathasivam, Saratha
2017-08-01
Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.
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Automated method for the systematic interpretation of resonance peaks in spectrum data
Damiano, B.; Wood, R.T.
1997-04-22
A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.
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Automated method for the systematic interpretation of resonance peaks in spectrum data
Damiano, Brian; Wood, Richard T.
1997-01-01
A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.
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Operational Retrievals of Evapotranspiration: Are we there yet?
NASA Astrophysics Data System (ADS)
Neale, C. M. U.; Anderson, M. C.; Hain, C.; Schull, M.; Isidro, C., Sr.; Goncalves, I. Z.
2017-12-01
Remote sensing based retrievals of evapotranspiration (ET) have progressed significantly over the last two decades with the improvement of methods and algorithms and the availability of multiple satellite sensors with shortwave and thermal infrared bands on polar orbiting platforms. The modeling approaches include simpler vegetation index (VI) based methods such as the reflectance-based crop coefficient approach coupled with surface reference evapotranspiration estimates to derive actual evapotranspiration of crops or, direct inputs to the Penman-Monteith equation through VI relationships with certain input variables. Methods that are more complex include one-layer or two-layer energy balance approaches that make use of both shortwave and longwave spectral band information to estimate different inputs to the energy balance equation. These models mostly differ in the estimation of sensible heat fluxes. For continental and global scale applications, other satellite-based products such as solar radiation, vegetation leaf area and cover are used as inputs, along with gridded re-analysis weather information. This presentation will review the state-of-the-art in satellite-based evapotranspiration estimation, giving examples of existing efforts to obtain operational ET retrievals over continental and global scales and discussing difficulties and challenges.
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Zavou, Christina; Kkoushi, Antria; Koutsou, Achilleas; Christodoulou, Chris
2017-11-01
The aim of the current work is twofold: firstly to adapt an existing method measuring the input synchrony of a neuron driven only by excitatory inputs in such a way so as to account for inhibitory inputs as well and secondly to further appropriately adapt this measure so as to be correctly utilised on experimentally-recorded data. The existing method uses the normalized pre-spike slope (NPSS) of the membrane potential, resulting from observing the slope of depolarization of the membrane potential of a neuron prior to the moment of crossing the threshold within a short period of time, to identify the response-relevant input synchrony and through it to infer the operational mode of a neuron. The first adaptation of NPSS is made such that its upper bound calculation accommodates for the higher possible slope values caused by the lower average and minimum membrane potential values due to inhibitory inputs. Results indicate that when the input spike trains arrive randomly, the modified NPSS works as expected inferring that the neuron is operating as a temporal integrator. When the input spike trains arrive in perfect synchrony though, the modified NPSS works as expected only when the level of inhibition is much higher than the level of excitation. This suggests that calculation of the upper bound of the NPSS should be a function of the ratio between excitatory and inhibitory inputs in order to be able to correctly capture perfect synchrony at a neuron's input. In addition, we effectively demonstrate a process which has to be followed when aiming to use the NPSS on real neuron recordings. This process, which relies on empirical observations of the slope of depolarisation for estimating the bounds for the range of observed interspike interval lengths, is successfully applied to experimentally-recorded data showing that through it both a real neuron's operational mode and the amount of input synchrony that caused its firing can be inferred. Copyright © 2017 Elsevier B.V. All rights reserved.
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Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1993-01-01
The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.
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Development of a User Interface for a Regression Analysis Software Tool
NASA Technical Reports Server (NTRS)
Ulbrich, Norbert Manfred; Volden, Thomas R.
2010-01-01
An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.
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Address entry while driving: speech recognition versus a touch-screen keyboard.
Tsimhoni, Omer; Smith, Daniel; Green, Paul
2004-01-01
A driving simulator experiment was conducted to determine the effects of entering addresses into a navigation system during driving. Participants drove on roads of varying visual demand while entering addresses. Three address entry methods were explored: word-based speech recognition, character-based speech recognition, and typing on a touch-screen keyboard. For each method, vehicle control and task measures, glance timing, and subjective ratings were examined. During driving, word-based speech recognition yielded the shortest total task time (15.3 s), followed by character-based speech recognition (41.0 s) and touch-screen keyboard (86.0 s). The standard deviation of lateral position when performing keyboard entry (0.21 m) was 60% higher than that for all other address entry methods (0.13 m). Degradation of vehicle control associated with address entry using a touch screen suggests that the use of speech recognition is favorable. Speech recognition systems with visual feedback, however, even with excellent accuracy, are not without performance consequences. Applications of this research include the design of in-vehicle navigation systems as well as other systems requiring significant driver input, such as E-mail, the Internet, and text messaging.
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Label-indicator morpheme growth on LSTM for Chinese healthcare question department classification.
Hu, Yang; Wen, Guihua; Ma, Jiajiong; Li, Danyang; Wang, Changjun; Li, Huihui; Huan, Eryang
2018-04-26
Current Chinese medicine has an urgent demand for convenient medical services. When facing a large number of patients, understanding patients' questions automatically and precisely is useful. Different from the high professional medical text, patients' questions contain only a small amount of descriptions regarding the symptoms, and the questions are slightly professional and colloquial. The aim of this paper is to implement a department classification system for patient questions. Patients' questions will be classified into 11 departments, such as surgery and others. This paper presents a morpheme growth model that enhances the memories of key elements in questions, and later extracts the "label-indicators" and germinates the expansion vectors around them. Finally, the model inputs the expansion vectors into a neural network to assign department labels for patients' questions. All compared methods are validated by experiments on three datasets that are composed of real patient questions. The proposed method has some ability to improve the performance of the classification. The proposed method is effective for the departments classification of patients questions and serves as a useful system for the automatic understanding of patient questions. Copyright © 2018. Published by Elsevier Inc.
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WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms.
Chi, Sang-Mun; Nam, Dougu
2012-04-01
We present an accurate and fast web server, WegoLoc for predicting subcellular localization of proteins based on sequence similarity and weighted Gene Ontology (GO) information. A term weighting method in the text categorization process is applied to GO terms for a support vector machine classifier. As a result, WegoLoc surpasses the state-of-the-art methods for previously used test datasets. WegoLoc supports three eukaryotic kingdoms (animals, fungi and plants) and provides human-specific analysis, and covers several sets of cellular locations. In addition, WegoLoc provides (i) multiple possible localizations of input protein(s) as well as their corresponding probability scores, (ii) weights of GO terms representing the contribution of each GO term in the prediction, and (iii) a BLAST E-value for the best hit with GO terms. If the similarity score does not meet a given threshold, an amino acid composition-based prediction is applied as a backup method. WegoLoc and User's guide are freely available at the website http://www.btool.org/WegoLoc smchiks@ks.ac.kr; dougnam@unist.ac.kr Supplementary data is available at http://www.btool.org/WegoLoc.
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Learning Japanese by Reading "Manga": The Rise of "Soft Power Pedagogy"
ERIC Educational Resources Information Center
Armour, William Spencer
2011-01-01
Multimodal examples of Japanese language input (such as "manga" and anime) have now become the default choice for curriculum designers, material developers, and classroom teachers to make learning "fun". More traditional written only text-based materials are now in direct competition with such materials. While there has been a…
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Composeable Chat over Low-Bandwidth Intermittent Communication Links
2007-04-01
Compression (STC), introduced in this report, is a data compression algorithm intended to compress alphanumeric... Ziv - Lempel coding, the grandfather of most modern general-purpose file compression programs, watches for input symbol sequences that have previously... data . This section applies these techniques to create a new compression algorithm called Small Text Compression . Various sequence compression
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Medical Language Processing for Knowledge Representation and Retrievals
Lyman, Margaret; Sager, Naomi; Chi, Emile C.; Tick, Leo J.; Nhan, Ngo Thanh; Su, Yun; Borst, Francois; Scherrer, Jean-Raoul
1989-01-01
The Linguistic String Project-Medical Language Processor, a system for computer analysis of narrative patient documents in English, is being adapted for French Lettres de Sortie. The system converts the free-text input to a semantic representation which is then mapped into a relational database. Retrievals of clinical data from the database are described.
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ERIC Educational Resources Information Center
Chinkina, Maria; Ruiz, Simón; Meurers, Detmar
2017-01-01
We integrate insights from research in Second Language Acquisition (SLA) and Computational Linguistics (CL) to generate text-based questions. We discuss the generation of wh- questions as functionally-driven input enhancement facilitating the acquisition of particle verbs and report the results of two crowdsourcing studies. The first study shows…
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Brain Activations Associated with Sign Production Using Word and Picture Inputs in Deaf Signers
ERIC Educational Resources Information Center
Hu, Zhiguo; Wang, Wenjing; Liu, Hongyan; Peng, Danling; Yang, Yanhui; Li, Kuncheng; Zhang, John X.; Ding, Guosheng
2011-01-01
Effective literacy education in deaf students calls for psycholinguistic research revealing the cognitive and neural mechanisms underlying their written language processing. When learning a written language, deaf students are often instructed to sign out printed text. The present fMRI study was intended to reveal the neural substrates associated…
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Chinese-English Machine Translation System.
ERIC Educational Resources Information Center
Wang, William S-Y; And Others
The report documents results of a two-year R&D effort directed at the completion of a prototype system for Chinese-English machine translation of S&T literature. The system, designated QUINCE, accepts Chinese input exactly as printed, with no pre-editing of any kind, and produces English output on experimental basis. Coding of Chinese text via…
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The Use of Humourous Texts in Improving ESL Learners' Vocabulary Comprehension and Retention
ERIC Educational Resources Information Center
Zabidin, Nursyafiqah Binti
2015-01-01
Successful language acquisition requires extensive word knowledge. However, learners are reportedly unable to increase their word knowledge due to insufficient meaningful input in the language classrooms. This paper intended to present another tool to encourage learners' vocabulary development. It examined the effect(s) of using short narrative…
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The Effect of Frequency of Input-Enhancements on Word Learning and Text Comprehension
ERIC Educational Resources Information Center
Rott, Susanne
2007-01-01
Research on second language lexical development during reading has found positive effects for word frequency, the provision of glosses, and elaborative word processing. However, findings have been inconclusive regarding the effect of such intervention tasks on long-term retention. Likewise, few studies have looked at the cumulative effect of…
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Fuzzy/Neural Software Estimates Costs of Rocket-Engine Tests
NASA Technical Reports Server (NTRS)
Douglas, Freddie; Bourgeois, Edit Kaminsky
2005-01-01
The Highly Accurate Cost Estimating Model (HACEM) is a software system for estimating the costs of testing rocket engines and components at Stennis Space Center. HACEM is built on a foundation of adaptive-network-based fuzzy inference systems (ANFIS) a hybrid software concept that combines the adaptive capabilities of neural networks with the ease of development and additional benefits of fuzzy-logic-based systems. In ANFIS, fuzzy inference systems are trained by use of neural networks. HACEM includes selectable subsystems that utilize various numbers and types of inputs, various numbers of fuzzy membership functions, and various input-preprocessing techniques. The inputs to HACEM are parameters of specific tests or series of tests. These parameters include test type (component or engine test), number and duration of tests, and thrust level(s) (in the case of engine tests). The ANFIS in HACEM are trained by use of sets of these parameters, along with costs of past tests. Thereafter, the user feeds HACEM a simple input text file that contains the parameters of a planned test or series of tests, the user selects the desired HACEM subsystem, and the subsystem processes the parameters into an estimate of cost(s).
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End-to-End ASR-Free Keyword Search From Speech
NASA Astrophysics Data System (ADS)
Audhkhasi, Kartik; Rosenberg, Andrew; Sethy, Abhinav; Ramabhadran, Bhuvana; Kingsbury, Brian
2017-12-01
End-to-end (E2E) systems have achieved competitive results compared to conventional hybrid hidden Markov model (HMM)-deep neural network based automatic speech recognition (ASR) systems. Such E2E systems are attractive due to the lack of dependence on alignments between input acoustic and output grapheme or HMM state sequence during training. This paper explores the design of an ASR-free end-to-end system for text query-based keyword search (KWS) from speech trained with minimal supervision. Our E2E KWS system consists of three sub-systems. The first sub-system is a recurrent neural network (RNN)-based acoustic auto-encoder trained to reconstruct the audio through a finite-dimensional representation. The second sub-system is a character-level RNN language model using embeddings learned from a convolutional neural network. Since the acoustic and text query embeddings occupy different representation spaces, they are input to a third feed-forward neural network that predicts whether the query occurs in the acoustic utterance or not. This E2E ASR-free KWS system performs respectably despite lacking a conventional ASR system and trains much faster.
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[Change in soil enzymes activities after adding biochar or straw by fluorescent microplate method].
Zhang, Yu-Lan; Chen, Li-Jun; Duan, Zheng-Hu; Wu, Zhi-Jie; Sun, Cai-Xia; Wang, Jun-Yu
2014-02-01
The present work was aimed to study soil a-glucosidase and beta-glucosidase activities of and red soils based on fluorescence detection method combined with 96 microplates with TECAN Infinite 200 Multi-Mode Microplate Reader. We added biochar or straw (2.5 g air dry sample/50g air dry soil sample) into and red soils and the test was carried under fixed temperature and humidity condition (25 degrees C, 20% soil moisture content). The results showed that straw addition enhances soil alpha-glucosidase and beta-glucosidase activities, beta-glucosidase activity stimulated by rice straw treatment was higher than that of corn straw treatment, and activity still maintains strong after 40 days, accounting for increasing soil carbon transformation with straw inputting. Straw inputting increased soil nutrients contents and may promote microbial activity, which also lead to the increase oin enzyme Straw inputting increased soil nutrients contents and may promote microbial activity, which also lead to the increase oin enzyme activities. Different effects of straw kinds may be related to material source that needs further research. However, biochar inputting has little effect on soil alpha-glucosidase and beta-glucosidase activity. Biochar contains less available nutrients than straw and have degradation-resistant characteristics. Compared with the conventional spectrophotometric method, fluorescence microplate method is more sensitive to soil enzyme activities in suspension liquid, which can be used in a large number of samples. In brief, fluorescence microplate method is fast, accurate, and simple to determine soil enzymes activities.
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Li, Tingting; Cheng, Zhengguo; Zhang, Le
2017-01-01
Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency. PMID:29194393
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Li, Tingting; Cheng, Zhengguo; Zhang, Le
2017-12-01
Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency.
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Burkitt, A N
2006-08-01
The integrate-and-fire neuron model describes the state of a neuron in terms of its membrane potential, which is determined by the synaptic inputs and the injected current that the neuron receives. When the membrane potential reaches a threshold, an action potential (spike) is generated. This review considers the model in which the synaptic input varies periodically and is described by an inhomogeneous Poisson process, with both current and conductance synapses. The focus is on the mathematical methods that allow the output spike distribution to be analyzed, including first passage time methods and the Fokker-Planck equation. Recent interest in the response of neurons to periodic input has in part arisen from the study of stochastic resonance, which is the noise-induced enhancement of the signal-to-noise ratio. Networks of integrate-and-fire neurons behave in a wide variety of ways and have been used to model a variety of neural, physiological, and psychological phenomena. The properties of the integrate-and-fire neuron model with synaptic input described as a temporally homogeneous Poisson process are reviewed in an accompanying paper (Burkitt in Biol Cybern, 2006).
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Enriching Triangle Mesh Animations with Physically Based Simulation.
Li, Yijing; Xu, Hongyi; Barbic, Jernej
2017-10-01
We present a system to combine arbitrary triangle mesh animations with physically based Finite Element Method (FEM) simulation, enabling control over the combination both in space and time. The input is a triangle mesh animation obtained using any method, such as keyframed animation, character rigging, 3D scanning, or geometric shape modeling. The input may be non-physical, crude or even incomplete. The user provides weights, specified using a minimal user interface, for how much physically based simulation should be allowed to modify the animation in any region of the model, and in time. Our system then computes a physically-based animation that is constrained to the input animation to the amount prescribed by these weights. This permits smoothly turning physics on and off over space and time, making it possible for the output to strictly follow the input, to evolve purely based on physically based simulation, and anything in between. Achieving such results requires a careful combination of several system components. We propose and analyze these components, including proper automatic creation of simulation meshes (even for non-manifold and self-colliding undeformed triangle meshes), converting triangle mesh animations into animations of the simulation mesh, and resolving collisions and self-collisions while following the input.
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Noise in Charge Amplifiers— A gm/ID Approach
NASA Astrophysics Data System (ADS)
Alvarez, Enrique; Avila, Diego; Campillo, Hernan; Dragone, Angelo; Abusleme, Angel
2012-10-01
Charge amplifiers represent the standard solution to amplify signals from capacitive detectors in high energy physics experiments. In a typical front-end, the noise due to the charge amplifier, and particularly from its input transistor, limits the achievable resolution. The classic approach to attenuate noise effects in MOSFET charge amplifiers is to use the maximum power available, to use a minimum-length input device, and to establish the input transistor width in order to achieve the optimal capacitive matching at the input node. These conclusions, reached by analysis based on simple noise models, lead to sub-optimal results. In this work, a new approach on noise analysis for charge amplifiers based on an extension of the gm/ID methodology is presented. This method combines circuit equations and results from SPICE simulations, both valid for all operation regions and including all noise sources. The method, which allows to find the optimal operation point of the charge amplifier input device for maximum resolution, shows that the minimum device length is not necessarily the optimal, that flicker noise is responsible for the non-monotonic noise versus current function, and provides a deeper insight on the noise limits mechanism from an alternative and more design-oriented point of view.
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Method and system for conserving power in a telecommunications network during emergency situations
Conrad, Stephen H [Algodones, NM; O'Reilly, Gerard P [Manalapan, NJ
2011-10-11
Disclosed is a method and apparatus for conserving power in a telecommunications network during emergency situations. A permissible number list of emergency and/or priority numbers is stored in the telecommunications network. In the event of an emergency or power failure, input digits of a call to the telecommunications network are compared to the permissible number list. The call is processed in the telecommunications network and routed to its destination if the input digits match an entry in the permissible number list. The call is dropped without any further processing if the input digits do not match an entry in the permissible number list. Thus, power can be conserved in emergency situations by only allowing emergency and/or priority calls.
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Gaze and Feet as Additional Input Modalities for Interacting with Geospatial Interfaces
NASA Astrophysics Data System (ADS)
Çöltekin, A.; Hempel, J.; Brychtova, A.; Giannopoulos, I.; Stellmach, S.; Dachselt, R.
2016-06-01
Geographic Information Systems (GIS) are complex software environments and we often work with multiple tasks and multiple displays when we work with GIS. However, user input is still limited to mouse and keyboard in most workplace settings. In this project, we demonstrate how the use of gaze and feet as additional input modalities can overcome time-consuming and annoying mode switches between frequently performed tasks. In an iterative design process, we developed gaze- and foot-based methods for zooming and panning of map visualizations. We first collected appropriate gestures in a preliminary user study with a small group of experts, and designed two interaction concepts based on their input. After the implementation, we evaluated the two concepts comparatively in another user study to identify strengths and shortcomings in both. We found that continuous foot input combined with implicit gaze input is promising for supportive tasks.
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On-Chip Power-Combining for High-Power Schottky Diode Based Frequency Multipliers
NASA Technical Reports Server (NTRS)
Siles Perez, Jose Vicente (Inventor); Chattopadhyay, Goutam (Inventor); Lee, Choonsup (Inventor); Schlecht, Erich T. (Inventor); Jung-Kubiak, Cecile D. (Inventor); Mehdi, Imran (Inventor)
2015-01-01
A novel MMIC on-chip power-combined frequency multiplier device and a method of fabricating the same, comprising two or more multiplying structures integrated on a single chip, wherein each of the integrated multiplying structures are electrically identical and each of the multiplying structures include one input antenna (E-probe) for receiving an input signal in the millimeter-wave, submillimeter-wave or terahertz frequency range inputted on the chip, a stripline based input matching network electrically connecting the input antennas to two or more Schottky diodes in a balanced configuration, two or more Schottky diodes that are used as nonlinear semiconductor devices to generate harmonics out of the input signal and produce the multiplied output signal, stripline based output matching networks for transmitting the output signal from the Schottky diodes to an output antenna, and an output antenna (E-probe) for transmitting the output signal off the chip into the output waveguide transmission line.
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NASA Technical Reports Server (NTRS)
Dreisbach, R. L. (Editor)
1979-01-01
The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.
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Effects of Meteorological Data Quality on Snowpack Modeling
NASA Astrophysics Data System (ADS)
Havens, S.; Marks, D. G.; Robertson, M.; Hedrick, A. R.; Johnson, M.
2017-12-01
Detailed quality control of meteorological inputs is the most time-intensive component of running the distributed, physically-based iSnobal snow model, and the effect of data quality of the inputs on the model is unknown. The iSnobal model has been run operationally since WY2013, and is currently run in several basins in Idaho and California. The largest amount of user input during modeling is for the quality control of precipitation, temperature, relative humidity, solar radiation, wind speed and wind direction inputs. Precipitation inputs require detailed user input and are crucial to correctly model the snowpack mass. This research applies a range of quality control methods to meteorological input, from raw input with minimal cleaning, to complete user-applied quality control. The meteorological input cleaning generally falls into two categories. The first is global minimum/maximum and missing value correction that could be corrected and/or interpolated with automated processing. The second category is quality control for inputs that are not globally erroneous, yet are still unreasonable and generally indicate malfunctioning measurement equipment, such as temperature or relative humidity that remains constant, or does not correlate with daily trends observed at nearby stations. This research will determine how sensitive model outputs are to different levels of quality control and guide future operational applications.
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O'Sullivan, F; Kirrane, J; Muzi, M; O'Sullivan, J N; Spence, A M; Mankoff, D A; Krohn, K A
2010-03-01
Kinetic quantitation of dynamic positron emission tomography (PET) studies via compartmental modeling usually requires the time-course of the radio-tracer concentration in the arterial blood as an arterial input function (AIF). For human and animal imaging applications, significant practical difficulties are associated with direct arterial sampling and as a result there is substantial interest in alternative methods that require no blood sampling at the time of the study. A fixed population template input function derived from prior experience with directly sampled arterial curves is one possibility. Image-based extraction, including requisite adjustment for spillover and recovery, is another approach. The present work considers a hybrid statistical approach based on a penalty formulation in which the information derived from a priori studies is combined in a Bayesian manner with information contained in the sampled image data in order to obtain an input function estimate. The absolute scaling of the input is achieved by an empirical calibration equation involving the injected dose together with the subject's weight, height and gender. The technique is illustrated in the context of (18)F -Fluorodeoxyglucose (FDG) PET studies in humans. A collection of 79 arterially sampled FDG blood curves are used as a basis for a priori characterization of input function variability, including scaling characteristics. Data from a series of 12 dynamic cerebral FDG PET studies in normal subjects are used to evaluate the performance of the penalty-based AIF estimation technique. The focus of evaluations is on quantitation of FDG kinetics over a set of 10 regional brain structures. As well as the new method, a fixed population template AIF and a direct AIF estimate based on segmentation are also considered. Kinetics analyses resulting from these three AIFs are compared with those resulting from radially sampled AIFs. The proposed penalty-based AIF extraction method is found to achieve significant improvements over the fixed template and the segmentation methods. As well as achieving acceptable kinetic parameter accuracy, the quality of fit of the region of interest (ROI) time-course data based on the extracted AIF, matches results based on arterially sampled AIFs. In comparison, significant deviation in the estimation of FDG flux and degradation in ROI data fit are found with the template and segmentation methods. The proposed AIF extraction method is recommended for practical use.
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Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Karipineni, Neelima; Chang, Frank; Yan, Xuemin; Chang, Fenny; Dimaggio, Dana; Goldman, Debora S.; Rocha, Roberto A.
2011-01-01
Clinical information is often coded using different terminologies, and therefore is not interoperable. Our goal is to develop a general natural language processing (NLP) system, called Medical Text Extraction, Reasoning and Mapping System (MTERMS), which encodes clinical text using different terminologies and simultaneously establishes dynamic mappings between them. MTERMS applies a modular, pipeline approach flowing from a preprocessor, semantic tagger, terminology mapper, context analyzer, and parser to structure inputted clinical notes. Evaluators manually reviewed 30 free-text and 10 structured outpatient clinical notes compared to MTERMS output. MTERMS achieved an overall F-measure of 90.6 and 94.0 for free-text and structured notes respectively for medication and temporal information. The local medication terminology had 83.0% coverage compared to RxNorm’s 98.0% coverage for free-text notes. 61.6% of mappings between the terminologies are exact match. Capture of duration was significantly improved (91.7% vs. 52.5%) from systems in the third i2b2 challenge. PMID:22195230
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Response sensitivity of barrel neuron subpopulations to simulated thalamic input.
Pesavento, Michael J; Rittenhouse, Cynthia D; Pinto, David J
2010-06-01
Our goal is to examine the relationship between neuron- and network-level processing in the context of a well-studied cortical function, the processing of thalamic input by whisker-barrel circuits in rodent neocortex. Here we focus on neuron-level processing and investigate the responses of excitatory and inhibitory barrel neurons to simulated thalamic inputs applied using the dynamic clamp method in brain slices. Simulated inputs are modeled after real thalamic inputs recorded in vivo in response to brief whisker deflections. Our results suggest that inhibitory neurons require more input to reach firing threshold, but then fire earlier, with less variability, and respond to a broader range of inputs than do excitatory neurons. Differences in the responses of barrel neuron subtypes depend on their intrinsic membrane properties. Neurons with a low input resistance require more input to reach threshold but then fire earlier than neurons with a higher input resistance, regardless of the neuron's classification. Our results also suggest that the response properties of excitatory versus inhibitory barrel neurons are consistent with the response sensitivities of the ensemble barrel network. The short response latency of inhibitory neurons may serve to suppress ensemble barrel responses to asynchronous thalamic input. Correspondingly, whereas neurons acting as part of the barrel circuit in vivo are highly selective for temporally correlated thalamic input, excitatory barrel neurons acting alone in vitro are less so. These data suggest that network-level processing of thalamic input in barrel cortex depends on neuron-level processing of the same input by excitatory and inhibitory barrel neurons.
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Forkert, N D; Cheng, B; Kemmling, A; Thomalla, G; Fiehler, J
2014-01-01
The objective of this work is to present the software tool ANTONIA, which has been developed to facilitate a quantitative analysis of perfusion-weighted MRI (PWI) datasets in general as well as the subsequent multi-parametric analysis of additional datasets for the specific purpose of acute ischemic stroke patient dataset evaluation. Three different methods for the analysis of DSC or DCE PWI datasets are currently implemented in ANTONIA, which can be case-specifically selected based on the study protocol. These methods comprise a curve fitting method as well as a deconvolution-based and deconvolution-free method integrating a previously defined arterial input function. The perfusion analysis is extended for the purpose of acute ischemic stroke analysis by additional methods that enable an automatic atlas-based selection of the arterial input function, an analysis of the perfusion-diffusion and DWI-FLAIR mismatch as well as segmentation-based volumetric analyses. For reliability evaluation, the described software tool was used by two observers for quantitative analysis of 15 datasets from acute ischemic stroke patients to extract the acute lesion core volume, FLAIR ratio, perfusion-diffusion mismatch volume with manually as well as automatically selected arterial input functions, and follow-up lesion volume. The results of this evaluation revealed that the described software tool leads to highly reproducible results for all parameters if the automatic arterial input function selection method is used. Due to the broad selection of processing methods that are available in the software tool, ANTONIA is especially helpful to support image-based perfusion and acute ischemic stroke research projects.
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Hybrid powertrain system including smooth shifting automated transmission
Beaty, Kevin D.; Nellums, Richard A.
2006-10-24
A powertrain system is provided that includes a prime mover and a change-gear transmission having an input, at least two gear ratios, and an output. The powertrain system also includes a power shunt configured to route power applied to the transmission by one of the input and the output to the other one of the input and the output. A transmission system and a method for facilitating shifting of a transmission system are also provided.
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NASA Technical Reports Server (NTRS)
Kurmanaliyev, T. I.; Breslavets, A. V.
1974-01-01
The difficulties in obtaining exact calculation data for the labor input and estimated cost are noted. The method of calculating the labor cost of the design work using the provisional normative indexes with respect to individual forms of operations is proposed. Values of certain coefficients recommended for use in the practical calculations of the labor input for the development of new scientific equipment for space research are presented.
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Heebner, John E [Livermore, CA
2009-09-08
In one general embodiment, a method for deflecting an optical signal input into a waveguide is provided. In operation, an optical input signal is propagated through a waveguide. Additionally, an optical control signal is applied to a mask positioned relative to the waveguide such that the application of the optical control signal to the mask is used to influence the optical input signal propagating in the waveguide. Furthermore, the deflected optical input signal output from the waveguide is detected in parallel on an array of detectors. In another general embodiment, a beam deflecting structure is provided for deflecting an optical signal input into a waveguide, the structure comprising at least one wave guiding layer for guiding an optical input signal and at least one masking layer including a pattern configured to influence characteristics of a material of the guiding layer when an optical control signal is passed through the masking layer in a direction of the guiding layer. In another general embodiment, a system is provided including a waveguide, an attenuating mask positioned on the waveguide, and an optical control source positioned to propagate pulsed laser light towards the attenuating mask and the waveguide such that a pattern of the attenuating mask is applied to the waveguide and material properties of at least a portion of the waveguide are influenced.
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Method and apparatus for automatic control of a humanoid robot
NASA Technical Reports Server (NTRS)
Abdallah, Muhammad E (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)
2013-01-01
A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes.